Purpose: When it comes to improving citizen service delivery standard and processes, or broadly, management in government (MIG), many reform programs and improvement efforts are ongoing across different ministries, departments, and agencies. This paper is part of a larger empirical research where we are interested to know what those programs and projects are, and how they are doing, and what the gaps are. Design/methodology/approach: Analyzing the publicly available data on the government portal and donors’ website, this article provides an overall idea of current reforms in various places of government. In parallel, field research was conducted through visiting agency offices, observing office environment and mechanisms, and interviewing public managers who are working at district and sub-district level offices of directorates or agencies.Findings: As a trend, state-led development process and the traditional mode of administration have moved to New Public Management based quality and performance approach. All donors have their own strategy framework document like ‘Country Assistance strategy’, ‘Country Operations and Business Plan’, Logical Framework Document, Focus or Priority Streams, etc. Many of the projects are sectoral and agency or ministry specific and have an inherent limitations, due to ‘cadre’ based organizational structural arrangement. So, it is common ‘not to own the projects’, rather ‘using the fund as much as possible anyway within the given project duration’. When the fund ends, implementing units, either government or NGOs, abandon the projects. That is why many projects are actually half done without significant and sustained direction.Originality/value: We can conclude that the typical ‘top-down’ or ‘trickle down’ conception is still dominant in design and implementation of reforms programs and service quality efforts. So, how to reach systemically at the bottom where public managers provide services to citizens, needs even more deliberation.

We propose a new scheme based on ephemeral elliptic curves over the ring Z/nZ where n=pq is an RSA modulus with p=up^2+vp^2, q=uq^2+vq^2, up≡uq≡3(mod4). The new scheme is a variant of both the RSA and the KMOV cryptosystems. The scheme can be used for both signature and encryption. We study the security of the new scheme and show that is immune against factorization attacks, discrete logarithm problem attacks, sum of two squares attacks, sum of four squares attacks, isomorphism attacks, and homomorphism attacks. Moreover, we show that the private exponents can be much smaller than the ordinary exponents for RSA and KMOV, which makes the decryption phase in the new scheme more efficient.

(1) Influenza causes a significant health and socio-economic burden every year, and health personnel (HP) are at higher risk of exposure to respiratory pathogens than general population. (2) The study purpose was to describe and compare influenza vaccine uptake and its prognostic factors among Medical Doctors (MDs) and Non-Medical Health Personnel (NMHP) vs Non-HP (NHP). We analysed 2014-2018 data (N=105,608) from the Italian Behavioural Risk Factor Surveillance System PASSI that, since 2008, has been collecting health-related information continuously in sampled adults. (3) MDs and NMHP represented, respectively, 1.1% and 4.6% of the sample. Among HP, 22.8% (CI 19.8% - 26.1%) of MDs and 8.5% (CI 7.5% - 9.5%) of NMHP reported to have been vaccinated vs 6.3% (CI 6.1% - 6.5%) in NHP. This difference is confirmed in the three categories (MDs, NMHP, NHP), even more across age groups: in 18-34yy, respectively, 9.9%, 4.4%, 3.4% vs 28.4%, 13.9%, 10.6% in 50-64yy. PASSI surveillance shows an increasing influenza vaccination uptake over time, especially among MDs (22.2% in 2014 vs 30.5% in 2018). (4) Despite such increase, especially among younger HP, influenza vaccination uptake is low. Even more under pandemic scenarios, these figures represent key information to address effective strategies for disease prevention and health promotion.

As the COVID-19 pandemic begins to abate and national public health systems are treating the SARS-Cov-2 virus as endemic, many public health measures are no longer mandated, but remain recommended with voluntary participation. One of these is the wearing of fitted face masks, initially mandated to contain, or at least slow, the spread of SARS-CoV-2 which is primarily transmitted via aerosols emitted while breathing, coughing, or sneezing. While the habit of once wearing fitted face masks recedes into memory for much of the population, so does the knowledge of the various types of masks that were once en vogue. To create a record for the future, this paper provides the first comprehensive documentation of the nature and range of fitted facemasks that circulated during the COVID-19 pandemic.

The risk of 'zoonotic spillovers,' or the transmission of viruses from animals to humans, has been raised by climate change and the devastation of nature, as infectious disease experts have long warned. Even as the world works to stop the spread of the currently unfolding pandemic of coronavirus disease 2019 (COVID-19) and the breakout of monkeypox virus (MPXV), a new animal virus, the Langya henipavirus (LayV), has been discovered in humans in Eastern China. The scientists say there is little danger of the virus spreading among humans, but it shares genetic material with Hendra virus and Nipah virus, two other henipaviruses that infect humans and cause life-threatening respiratory diseases. Humans infected with LayV can expect to experience high body temperature, cough, weariness, poor appetite, muscle discomfort, myalgia, nausea and vomiting. It is likely that the virus will spread from animals to humans. Currently, the health authorities of Taiwan and other health organizations are tracking the progress of the ailment to ensure it does not reach humans. Researchers have examined 25 species of small wild animals for presence of the virus, and so far, shrews are the only ones that have tested positive for the virus's RNA. Based on these results, shrews are a possible candidate for the virus's natural reservoir. Too far, no therapies or vaccines have been developed and licensed for henipaviruses like the LayV. When other therapies fail to alleviate viral infections, ribavirin may be the next best thing. The need for novel vaccinations against the LayV infection and the timely delivery of these vaccines to areas at high epidemiological risk is real. To lessen the likelihood of a health calamity being caused by this newly developing virus, it is crucial to conduct active surveillance in a transparent and globally collaborative manner. The questions that have not been answered yet require additional study.

E-petitioning is a useful object of study for observing the potential emergence of a new relationship to politics and new forms of political participation. Access to a dataset of hundreds of thousands of users of an electronic petitioning platform, provides the opportunity to overcome a certain number of limitations that are associated with traditional methods of studying political participation, since it allows us to focus on the reality of the signatories’ behaviour rather than on their declarations. We follow the traces left by the petitioners on this site to better understand the process of dissemination of an online petition, and its linked with offline activities. Our examination of the three most signed petitions in the ‘environment’ category, combining an analysis of their petitioning dynamics and an analysis of the comments attached to them, allows us to show: firstly, that there is an interwoven relationship between the local anchoring of the mobilisation and the processes of dissemination by which petitions extend from local signatories to signatories who are geographically more distant; and secondly, that it is not accurate to imagine that just anyone can sign any petition, since petitioning dynamics proceed from one person to the next, whether these dynamics start from a pre-existing local anchorage on the ground, or act through a platform effect which is dependent on the attractiveness of the petition in question.

Students are often portrayed as future leaders. Their participation in climate change mitigation would improve when they access climate information and gain a high level of climate change awareness. This study was initiated to assess the Congolese students’ awareness of climate change by focusing on their sources of information on climate change, knowledge about the causes and impacts of climate change and activities that can raise awareness on climate change. Using a convenience sampling technique, we collected data through individual interviews conducted among 1,278 students from 13 universities across the Democratic Republic of Congo (DRC). The interview results showed that all students irrespective of their disciplines were concerned about climate change, a phenomenon strongly driven by human activities, such as deforestation (78%), urbanisation (30%), agriculture activities (30%) and transport services (26%). The students’ perceptions of climate change impacts included increase in temperature (82%), decrease in the number of rainy days (66%), proliferation of pests (60%) and increase in the number of malaria patients (39%). The primary sources of information that significantly affected students’ awareness of climate change included environment-related university courses and television broadcasts. The awareness-raising and mitigation actions related to climate change recommended by the students included educating people about good waste management (56%), planting trees (65%) and using the taxes paid by mining companies for the restoration of degraded ecosystems. The students believed that in DRC, all layers of the society (educational institutions, civil society organisations, community members and businesses) are important in building resilience to climate change. This study can guide teachers to focus their educational efforts on shaping pro-environmental behaviour in students.

Objectives: Low and Middle Income Countries (LMICs) are experiencing a fast-paced epidemiological rise in clusters of non-communicable diseases (NCDs) such as diabetes and cardiovascular disease, forming an imminent rise in multimorbidity (MMD). However, preventing MMD has received little attention in LMICs, especially in Sub-Saharan African Countries. Design: Narrative review which scoped the most recent evidence in LMICs about MMD determinants and appropriated them for potential MMD prevention strategies. Methods: MMD in LMICs is affected by several determinants including increased age, female gender, environment, lower socio-economic status, obesity, and lifestyle behavious, especially poor nutrition and physical inactivity. Results: MMD public health interventions in LMICs, especially Sub-Saharan are currently impeded by local and regional economic disparity, underdeveloped healthcare systems, and concurrent prevalence of communicable diseases. However, lifestyle interventions that are targeted towards preventing highly prevalent MMD clusters, especially hypertension, diabetes and cardiovascular disease, can provide an early prevention of MMD, especially within Sub-Saharan African countries with emerging economies and socio-economic disparity. Conclusion: Future public health initiatives should consider targeted lifestyle interventions and appropriate policies and guidelines in preventing MMD in LMICs.

In open, sustainable policymaking, we are expecting to develop the valuable results that will bring us closer to a fairer and more balanced society. One way to involve the public in these processes is to engage them in online e-participation projects. Despite the hopes, empirical analyses show that many e-participation initiatives have failed to deliver expected benefits. Revealing what actually works in examined projects and what requires improvement would allow for better policy planning in the future. In this article, I made an attempt to identify and assess the cognitive processes enabling emergence of collective intelligence (CI) in a singular e-participation project. For this reason, I worked out and tested an evaluation technique, combining the MILCS framework for group cognition and the results of empirical research on CI. A case study method based on semi-structured interviews was selected to evaluate a sample participatory budgeting initiative, Civic Budget of the City of Kraków. Results reveal that most cognitive processes are working satisfactorily, but the real problem is using collective memory, which works only to a very limited extent. A guideline for future policymakers should be to develop a shared memory system, to which all community members should have access.

Health innovations are generally oriented on a techno-economic vision. In this perspective, technologies are seen as an end in themselves, and there is no arrangement between the technical and the social values of innovation. This vision prevails in sanitary crises, in which management is carried out based on the search for punctual, reactive, and technical solutions to remedy a specific problem without a systemic/holistic, sustainable, or proactive approach. This paper attempts to contribute to the literature on the epistemological orientation of innovations in the field of public health. Taking the Covid-19 and Ebola crises as examples, the primary objective is to show how innovation in health is oriented towards a techno-economic paradigm. Second, we propose a repositioning of public health innovation towards a social paradigm that will put more emphasis on the interaction between social and health dimensions in the perspective of social change.

The ongoing COVID-19 global pandemic is affecting every facet of human lives (e.g., public health, education, economy, transportation, and the environment). This novel pandemic and citywide implemented lockdown measures are affecting virus transmission, people’s travel patterns, and air quality. Many studies have been conducted to predict the COVID-19 diffusion, assess the impacts of the pandemic on human mobility and air quality, and assess the impacts of lockdown measures on viral spread with a range of Machine Learning (ML) techniques. This review study aims to analyze results from past research to understand the interactions among the COVID-19 pandemic, lockdown measures, human mobility, and air quality. The critical review of prior studies indicates that urban form, people's socioeconomic and physical conditions, social cohesion, and social distancing measures significantly affect human mobility and COVID-19 transmission. During the COVID-19 pandemic, many people are inclined to use private transportation for necessary travel purposes to mitigate coronavirus-related health problems. This review study also noticed that COVID-19 related lockdown measures significantly improve air quality by reducing the concentration of air pollutants, which in turn improves the COVID-19 situation by reducing respiratory-related sickness and deaths of the people. It is argued that ML is a powerful, effective, and robust analytic paradigm to handle complex and wicked problems such as a global pandemic. This study also discusses policy implications, which will be helpful for policymakers to take prompt actions to moderate the severity of the pandemic and improve urban environments by adopting data-driven analytic methods.

Scientists observe, discover, justify and eventually share their findings with the scientific community. Dissemination is an integral aspect of scientific discovery since discoveries which go unnoticed have no or little impact on science. Today, peer-review is part of this process of scientific dissemination as it contributes proactively to the quality of a scientific article. As the numbers of scientific journals and scientific articles published therein are increasing steady, processes such as the single-blind or double-blind peer review are facing a near collapse situation. In fact, these traditional forms of reviewing have reached their limits and, because of this, are also increasingly considered as unfair, sloppy, superficial and even biased. In this manuscript we propose forms of Post Publication Public Peer Review (P4R) as valuable alternatives to the traditional blind peer review system. We describe how the journal Sci has explored such an approach and provide first empirical evidence of the benefits and also challenges such a P4R approach is facing.

Affordable Housing, the basic human necessity has now become a critical problem in global cities with direct impacts on people's well-being. While a well-functioning housing market may augment the economic efficiency and productivity of a city, it may trigger housing affordability issues leading crucial economic and political crises side by side if not handled properly. In global cities e.g. Singapore and Hong Kong where affordable housing for all has become one of the greatest concerns of the Government, this issue can be tackled capably by the provision of public housing. In Singapore, nearly 90% of the total population lives in public housing including public rental and subsidized ownership, whereas the figure tally only about 45% in Hong Kong. Hence this study is an effort to scrutinizing the key drivers of success in affordable public housing through following a qualitative case study based research methodological approach to present successful experience and insight from different socio-economic and geo-political context. As a major intervention, this research has clinched that, housing affordability should be backed up by demand-side policies aiming to help occupants and proprietors to grow financial capacity e.g. subsidized rental and subsidized ownership can be an integral part of the public housing system to improve housing affordability.

Urban accessibility represents one of the great challenges of the contemporary city, which is required to adopt sustainable development models in line with the UN Agenda 2030 objectives, recently confirmed by the health emergency. Urban accessibility and walkability are topics closely related to those aiming at a livable, healthy and inclusive city, based on a system of high-quality public spaces and on a network of services and infrastructures. However, these principles collide with the fragmentation of many urban contexts, built following vehicular accessibility needs. Within this framework, the city of Cagliari represents an interesting case study as it is affected by the disposal of public properties which appear as “enclaves” in the historic urban fabric. This research aims to evaluate if and in which terms the abandoned assets can facilitate the development of the 15-minutes city, as a city reducing the need to move over a certain time and space and therefore granting a more equal access to urban services to a wide range of citizens. This is done by proposing indexes defined as porosity, crossing and attractiveness, which constitute a combined index to improve the pedestrian accessibility in the “central places” of the contemporary city, where the walkability can also become a possible “free choice” for a new healthy lifestyle. These indexes were calculated for the most significant large disused public buildings in the historic center to guide future scenarios towards a 15 minutes city.

This paper presents a Multilayer Perceptron and Support Vector Machine algorithms approach to predict the number of COVID19 infections in different countries of America. It intends to serve as a tool for decision-making and tackling the pandemic that the world is currently facing. The models were trained and tested using open data from the European Union repository where a time series of confirmed contagious cases was modeled until May 25, 2020. The hyperparameters as number of neurons per layer were set up using a tabu list algorithm. The countries selected to carry out the study were Brazil, Chile, Colombia, Mexico, Peru and the United States. The metrics used are Pearson's correlation coefficient (CP), Mean Absolute Error (MAE), and Mean Percentage Error (MPE). For the testing stage we obtained the following results: Brazil, CP=0.65, MAE=2508 and MPE=17%; Chile, CP=0.64, MAE=504, MPE=16%; Colombia, CP=0.83, MAE=76, MPE=9%; Mexico, CP=0.77, MAE=231, MPE=9%; Peru, CP=0.76, MAE=686, MPE=18% and the United States of America, CP=0.93, MAE=799, MPE=4%. This resulted in powerful machine learning tools although it is necessary to use specific algorithms depending on the data and the stage of the country’s pandemic.

Thanks to rapid advances in the Internet of Things (IoT) and Edge-Fog-Cloud Computing technologies, Smart Public Safety (SPS) system has become feasible by integrating heterogeneous computing devices and different types of networks to collaboratively provide seamless public safety services. While SPS facilitates convenient exchanges of surveillance data streams among device owners and third-party applications, the existing monolithic service oriented architecture (SOA) architecture is unable to provide scalable and extensible services in a large-scale heterogeneous network environment. Moreover, traditional security solutions rely on centralized trusted third-party authority, which not only can be a performance bottleneck or the single point of failure, but it also incurs privacy concerns on improperly use of private information. Inspired by blockchain and microservices technologies, this paper proposed a BLockchain-ENabled Decentralized Smart Public Safety (BlendSPS) system. Leveraging hybrid blockchain fabrics, a microservices based security mechanism is implemented to enable decentralized security architecture, and it supports immutability, auditability and traceability for secured data sharing and operations among participants of the SPS system. An extensive experimental study verified the feasibility of the proposed Blend-SPS that possesses security and privacy proprieties with limited overhead on IoT based edge networks.

With the continuous emergence and application of new technologies, the construction of smart cities has entered the practical promotion period. Since 2012, the pilot construction of smart city has been promoted by the government in China. On the basis of these practical experiences, this paper presents an overview of the latest technologies and applications for smart city construction in China and demonstrates that smart city strategy needs to be implemented according to local conditions, adhering to the people-oriented concept and using scientific and effective top-level design and planning. The construction of smart city is comprehensive system engineering, including the integration of geographic information sharing service platform, full-cycle management and control system of urban planning, construction and social management, as well as intelligent business information management system of gardening, water conservancy, environmental protection and other industries and departments. The information system (GIS), satellite remote sensing (SRS), global navigation satellite system (GNSS), Internet of things, mobile applications, cloud computing, visualization technology ware used to promote urban construction and sustainable development, and to meet the needs of future smart city development. Results show that centralized management is very important for the construction of smart city. The government plays a major role in the construction of smart city, which will be conducive to the development of new technologies and the effective use of smart city construction resources.

Background: SARS-CoV-2 has resulted in a global pandemic, COVID-19. The disease has spread outrageously from Wuhan, china to rest of the world affecting millions of people. The human transmission is mainly known to occur by aerosols. As almost every dental procedure is associated with aerosol production, oral health care professionals are at a high risk of getting the infection. An attempt has been made to render cohesive practical suggestions for dental professionals amid COVID-19 outbreak. Objectives: The paper aims at providing evidence based information in managing dental patients during this pandemic. Material and Methods: The paper provides a broad overview of predominant findings based on electronic database search regarding COVID-19 outbreak and its effect on dental practice. Conclusion: Dental care should not be neglected due to the pandemic. Thorough knowledge about the disease and its prevention will not only help us in providing care to these patients but will also help in preventing the nosocomial spread of infection.

We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.

We develop a mathematical model to provide epidemic predictions for the 2019-nCov epidemic in Wuhan, China. We use reported case data up to January 31, 2020 from the Chinese Center for Disease Control and Prevention and the Wuhan Municipal Health Commission to parameterize the model. From the parameterized model we identify the number of unreported cases. We then use the model to project the epidemic forward with varying level of public health interventions. The model predictions emphasize the importance of major public health interventions in controlling 2019-nCov epidemics.

Internet of things security will be a big challenge for the enterprises working behind the build-up of the internet of things, and it’s application. With IoT, another buzzword is blockchain-based cryptocurrency bitcoin. Blockchain technology has proven itself as one of the most secured existing technology. In this paper, we have discussed the significant challenges that will come up in identity management due to the heterogeneity of devices. We have proposed a solution for privacy preservation using secure identity management and possible communication methodology by using public key-based cryptography used in the blockchain. We have taken the ecosystem of smart home management and smart health management. At last, we have concluded with the discussion of futuristic applications of blockchain in other applications of the internet of things.

Among the array of structurally and toxicologically diverse mycotoxins, aflatoxins have attracted the most interest of scientific research due to their high toxicity and incidence in foods and feeds. Despite the undeniable progress made in various aspects related to aflatoxins, the ultimate goal consisting of reducing the associated public health risks worldwide is far from being reached due to multiplicity of social, political, economic, geographic, climatic, and development factors. However, a reasonable degree of health protection is attained in industrialized countries owing to their scientific, administrative, and financial capacities allowing them to use high-tech agricultural management systems. Less fortunate situation exists in equatorial and sub-equatorial developing countries mainly practicing traditional agriculture managed by smallholders for subsistence, and where the climate is suitable for mould growth and aflatoxin production. A situation that worsens by the climatic change being increasingly suitable for aflatoxigenic mold growth and toxin production. Accordingly, it is difficult to harmonize the regulatory standards of aflatoxins worldwide, which prevents agri-foods of developing countries from access to the market of industrialized countries. To tackle the multi-facetted aflatoxin problems, actions should be taken collectively by the international community involving scientific research, technological and social development, environment protection, awareness promotion, etc. International cooperation should foster technology transfer and exchange of pertinent technical information. This review presents the main historical discoveries leading to our present knowledge on aflatoxins and the challenges that should be addressed presently and in the future at various levels to ensure higher health protection for everybody. In short, it aims to elucidate where we come from and where we should go in terms of aflatoxin research/development.

We do this research to investigate the relationship between renewable energy, public health expenditure, logistics performance indices, and economic and environmental sustainability in the ASEAN member states, through the analysis of a panel data from 2007 to 2017. The study used secondary data, which is downloaded from the World Bank Website and employs SEM (Structural Equation Modelling) model for testing hypothesis. The results show that the usage of renewable energy in logistical operations would enhance the environmental and economic performance in terms of mitigating carbon emissions and greenhouse gas emissions. While, public health expenditure and environmental performance is negatively correlated, which confirms that greater environmental sustainability with lower carbon emissions and greenhouse gases will improve human health and economic growth. Moreover, greater public health expenditure and poor environmental performance has negative effect on economic growth, inefficiency and low productivity of labor slowdown to the economic activities. For another side, the usage of renewable energy and the adoption of green practices in international logistics will develop the environmental sustainability, establish better image of a country and attract foreign direct investment inflows, and also minimize carbon emissions and public health expenditure, spurring sustainable economic growth with better export opportunities in pro-environmental countries.

The management and proper use of the Urban Public Transport Systems (UPTS) constitutes a critical field that has not been investigated in accordance to its relevance and urgent idiosyncrasy within smart cities realm. Swarm Intelligence is a very promising paradigm to deal with such complex and dynamic systems. It presents robust, scalable and self-organized behaviour to deal with dynamic and fast changing systems. The intelligence of cities can be modelled as a swarm of digital telecommunication networks (the nerves), ubiquitously embedded intelligence, sensors and tags, and software. In this paper, a new approach based on the use of the Natural Computing paradigm and Collective Computation is shown, more concretely taking advantage of an Ant Colony Optimization algorithm variation and Fireworks algorithms in order to build a system that makes the complete control of the UPTS a tangible reality.

BACKGROUND Epidemiological sciences have been evolving at an exponential rate paralleled only by the comparable growth within the discipline of data science. Digital epidemiological studies are playing a vital role in medical science analytics for the past few decades. To date, there are no published attempts at deploying the use of real-time analytics in connection with the disciplines of Dentistry or Medicine. AIMS AND OBJECTIVES We deployed a real-time statistical analysis in connection with topics in Dental Anatomy and Dental Pathology represented by the maxillary sinus, posterior maxillary teeth, related oral pathology. The purpose is to infer the digital epidemiology based on a continuous stream of raw data retrieved from Google Trends database. MATERIALS AND METHODS Statistical analysis was carried out via Microsoft Excel 2016 and SPSS version 24. Google Trends database was used to retrieve data for digital epidemiology. Real-time analytics and the statistical inference were based on encoding a programming script using Python high-level programming language. A systematic review of the literature was carried out via PubMed-NCBI, the Cochrane Library, and Elsevier databases. RESULTS The comprehensive review of databases of the literature, based on specific keywords search, yielded 491813 published studies. These were distributed as 488884 (PubMed-NCBI), 1611 (the Cochrane Library), and 1318 (Elsevier). However, there was no single study attempting real-time analytics. Nevertheless, we succeeded in achieving an automated real-time stream of data accompanied by a statistical inference based on data extrapolated from Google Trends. CONCLUSION Real-time analytics are of considerable impact when implemented in biological and life sciences as they will tremendously reduce the required resources for research. Predictive analytics, based on artificial neural networks and machine learning algorithms, can be the next step to be deployed in continuation of the real-time systems to prognosticate changes in the temporal trends and the digital epidemiology of phenomena of interest.

Multi-receiver encryption enables a sender to encrypt a message and transmit the ciphertext to a set of authorized users, while no one out this group of authorized users can decrypt the message. Multi-receiver encryption is of great importance in many sectors such as broadcast communication, cloud computing, wireless communications, networking applications, e-voting, lottery, and medical applications. This paper proposes an efficient multi-receiver public key encryption scheme based on Lucas sequences. The results of the computational analysis show that, projected scheme is better against renown attacks and prevailing anonymous multireceiver algorithms

This study attempts to investigate a method for creating an index from mobility data that not only correlates with the number of people who relocate to a place but also has causal influence on the number of such individuals. By creating an index based on human mobility data, it becomes possible to predict the influence of urban development on future residential movements. In this paper, we propose a method called the travel cost method for multiple places (TCM4MP) by extending the conventional travel cost method (TCM). We assume that the opportunity cost of travel time on non-working days reflects the convenience and amenities of a neighborhood. However, conventional TCM does not assume that the opportunity cost of travel time varies according to the departure place. In this paper, TCM4MP is proposed to estimate the opportunity cost of travel time with respect to the departure place. We consider such estimation to be possible due to the use of massive mobility data. We assume that the opportunity cost of travel time on non-working days reflects the convenience and amenities of the neighborhood. Therefore, we consider that the opportunity cost of travel time has a causal influence on future residential mobility. In this paper, the validity of the proposed method is tested using the smart card data of public transportation in Western Japan. Our proposed method is beneficial for urban planners in estimating the effects of urban development and detecting the shrinkage and growth of a population.

Public participation is significant for the success of any urban planning project. However, most members of the general public are not planning professionals and may not understand the technical details of a 2D paper-based plan, which might hamper their participation. One way to expand the participation of citizens is to present plans in well-designed, user-friendly and interactive platforms that allow participation regardless of the technical skills of the participants. This paper investigates the impacts of the combined use of 3D visualization and E-participation on public participation in Kisumu, Kenya. A 3D City model, created with CityEngine2016, was exported into a web-based geo-portal and used as a Planning Support System in two stakeholder workshops in order to evaluate its usability. For e-participation, 300 questionnaires given out to planning practitioners. Five indicators were developed for evaluating the usability of the 3D model while the usability of e-participation was evaluated using communication, collaboration and learning as indicators. Results showed that effectiveness and efficiency varies within different professional groups while the questionnaires showed strong preference for e-participation methods, especially SMSs/USSDs and emails. The study concludes that the use of 3D visualization and E-participation has the potential for improving the quality and quantity of public participation and recommends further research on the subject.

The article analyzes Bernoulli 's binary sequences in representation of empirical events about the distribution of natural resources and population sizes. Considering the event as a nonlinear system, and consisting of two dependent random variables, with memory and probabilities in maximum finite or infinite lengths, constant and equal to ½ for both variables (stationary process). The expressions of the possible trajectories remain constant in sequences that are repeated alternating the presence or absence of one of the variables at each iteration (asymmetric). There are constant oscillations in the event except if the variables X₁ and X₂ are regulated as a function of time Y. It is observed that the variables X₁ and X₂ assume in time T_k → ∞ specific behaviors (geometric variable) that can be used as management tools for random systems. In this way, the article seeks to know from this analyzes, the maximum entropy of information in the system by a theoretical view and how to model resources distribution or containment in the given problem.

In this paper we present an application of the dynamic tracking games framework to a monetary union. We use a small stylized nonlinear three-country macroeconomic model of a monetary union to analyse the interactions between fiscal (governments) and monetary (common central bank) policy makers, assuming different objective functions of these decision makers. Using the OPTGAME algorithm we calculate solutions for several games: a noncooperative solution where each government and the central bank play against each other (a feedback Nash Equilibrium solution), a fully cooperative solution with all players following a joint course of action (a Pareto optimal solution), and three solutions where various coalitions (subsets of the players) play against coalitions of the other players in a noncooperative way. It turns out that the fully cooperative solution yields the best results, the noncooperative solution fares worst, and the coalition games lie in between, with a broad coalition of the fiscally more responsible countries and the central bank against the less thrifty country coming closest to the Pareto optimum.

The manuscript wants to investigate the debate on urban resilience and climate change linking theory and practice, describing the possible innovations that concern urban design, urban normative and regional laws developing in different countries. The approach pursued would encourage resilience and flood protection through smart planning and through the architectural and urban project; considering public space as strategic soil where developing the resilient city, using engineering technical climate defence as new space for citizens and communities. Resilience themes are included in all levels of government and in spatial and strategic development policies such as in some project concerning public and private space and in municipal plans; the urban defense structures has to become new pleasant space for the city; these actions will not only contribute to making cities more resilient but will contribute to the creation of a more pleasant and attractive urban environment. The Resilience is the main keyword of some strategic vision of the Netherlands and of Italian laws and the concept is tested in some best practice such as in Rotterdam, in Bordeaux, in London and in the research carried out by "Arquitectos de Cabecera" in Barcelona. Resilience is seen as a new paradigm of smart planning.

In an era marked by swift technological progress, the pivotal role of Artificial Intelligence (AI) is increasingly evident across various sectors, including local governments. These governmental bodies are progressively leveraging AI technologies to enhance service delivery to their communities, ranging from simple task automation to more complicated engineering endeavours. While more and more local governments are adopting AI, it is imperative to understand the functions, implications, and consequences of AI. Despite the growing importance of this domain, a significant gap persists within the scholarly discourse. This study strives to bridge this void by exploring the applications of AI technologies within the context of local government service provision and using this inquiry to generate lessons and best practices for similar smart city initiatives. Through a comprehensive grey literature review, we analysed 262 real-world AI implementations across 170 local governments worldwide. The findings underscore several key points: (a) There has been a consistent upward trajectory in the adoption of AI by local governments over the last decade; (b) Local governments from China, the US, and the UK are at the forefront of AI adoption; (c) Among local government AI technologies, Natural Language Processing and Robotic Process Automation emerge as the most prevalent ones; (d) Local governments primarily deploy AI across 28 distinct services; (e) Information management, back-office work, and transportation and traffic management are leading domains in terms of AI adoption. This study enriches the extant body of knowledge by providing an overview of existing AI applications within the sphere of local governance. It offers insights for smart city policymakers and decision-makers considering the adoption, expansion, or refinement of AI technologies in urban service provision. Additionally, it underscores the importance of using these insights to guide the successful integration and optimisation of AI in future smart city projects, ensuring they meet the evolving needs of communities.

In this article, we analyze the relationships that connect graduates from high school, the training system and employment rates and conditions in the Italian regions between 2004 and 2022. The data used refer to the Istat Bes database. The results show that the growth in the number of high school graduates is positively associated with higher university education and employment with the exception of job satisfaction. Subsequently we also present a clusterization with k-Means algorithm confronting the Silhouette Coefficient with the Elbow Method. Finally, we confront seven different machine-learning algorithms for the prediction of the level of graduated from high school. We also present economic policy suggestions to increase schooling in the Italian regions. The results are critically discussed.

The interconnection between the objectives of territorial development and the agro-ecological transition highlights the value of past knowledge in the sustainable management of resources and agro-ecological systems. However, retrospection in rural areas presents difficulties due to a lack of data. This paper contributes to the search for such knowledge from the past by developing an interactive methodology capable of combining heterogeneous sources of information and the activation of local collective memory. Its effectiveness is based on ensuring the interoperability of information and communication in an environment simultaneously shaped by geoinformatics and 3D geo-visualizations. This virtual environment fosters participation and interactivity, supported by representations of the paleo-landscape. Furthermore, synergies were achieved between information sources and their integration into local spatial systems. The application example involved identifying a rice field that existed from the 15th to the 19th century in Thessaly, Greece. It is an interesting case because the location and organization of cultivation in combination with its spatio-temporal coordination ensures the sustainable use of natural resources. It appears that the interplay between information and communication facilitates community participation and the activation of its collective memory as a source of information that enriches the search and local intelligence.

Sleep disorders have become a public health problem for many reasons. The aim of this systematic review is to describe social, economic, and environmental determinants of sleep disturbances in Australia and New Zealand. A total of 22 studies, 14 from Australia and 8 from New Zealand involving children, adolescents and adults are included in the review. In summary, we found that sleep health disparities among children and adolescents in both countries are strongly associated to parental SES. Overall, lower family SES such as low parental income, low parental education, low SES area index are associated with higher sleep disturbances among children and adolescents. In adults, results revealed that SES determinants such as low income, lower education, unemployment, and night work were associated with sleep disturbances. Specifically, unemployment was associated with poor sleep quality, insomnia, and increased likelihood of suboptimal sleep efficiency. Low income and lower education were associated with high risk of OSA, longer sleep duration, insomnia, higher odds of suboptimal sleep duration and sleep onset latency.

As breast cancer continues to take a devasting public health toll, most primary prevention approaches are targeted at individual actions. We have proposed, instead, developing systemic, population approaches to preventing the disease. We used a combined qualitative-quantitative methodology, Group Concept Mapping (GCM), to identify Importance and Feasibility ratings of systemic interventions across a wide spectrum of approaches and stakeholders. Participants (n=351) from across the state of California sorted 84 potential interventions into topical piles, and then rated each intervention on perceived Importance and Feasibility. Multidimensional scaling and cluster analysis identified eleven clusters or themes of interventions. Participants rated interventions on Importance and Feasibility differently depending on the region of the state in which they lived. The results of this study underscore the importance of sharing health information with and seeking public health solutions from community partners in general and from beyond the urban areas usually studied.

Over the past decade, there has been a remarkable acceleration in the evolution of smart cities and intelligent spaces, driven by breakthroughs in technologies such as the Internet of Things (IoT), edge-fog-cloud computing, and machine learning (ML)/Artificial Intelligence (AI). As society begins to harness the full potential of these smart environments, the horizon brightens with the promise of an immersive, interconnected 3D world. The forthcoming paradigm shift in how we live, work, and interact owes much to groundbreaking innovations in augmented reality (AR), virtual reality (VR), extended reality (XR), Blockchain, and Digital Twins (DT). However, realizing the expansive digital vista in our daily lives is challenging. Current limitations include an incomplete integration of pivotal techniques, daunting bandwidth requirements, and the critical need for near-instantaneous data transmission, all impeding the digital VR Metaverse from fully manifesting as envisioned by its proponents. This paper seeks to delve deeply into the intricacies of the immersive, interconnected 3D realm, particularly in applications demanding high levels of intelligence. Specifically, this paper introduces Microverse, a task-oriented, edge-scale, pragmatic solution for smart cities. Unlike an all-encompassing Metaverses, each Microverse instance serves a specific task as a manageable digital twin of an individual network slice. Each Microverse enables on-site/near-site data processing, information fusion, and real-time decision-making within the edge-fog-cloud computing framework. The Microverse concept is verified using smart public safety surveillance (SPSS) for smart communities as a case study, demonstrating its feasibility in practical smart city applications. The aim is to stimulate discussions and inspire fresh ideas in our community, guiding us as we navigate the evolving digital landscape of smart cities to embrace the potential of the Metaverse.

Social media has become more popular in the last few years. It has been used in public health development and healthcare settings to promote healthier lifestyles. Given its important role in today's culture, it is necessary to understand its current trends and future directions in public health. This review aims to describe and summarize how public health professionals have been using social media to improve population outcomes. Additionally, it discusses potential future directions on how social media can be used to improve population health. The findings showed how social media has been used as a tool for research, designing and implementing health campaigns, messaging, and health promotion. In addition, social media integration with Artificial Intelligence (AI) and Generative Pre-Trained transformers (GPT) can have a big impact and offer an innovative approach to tackle the problems and difficulties in health informatics. These innovations might improve patient participation, individualized assistance, and care experiences. The research showed how likely social media will keep growing and evolving and, if used effectively, have the potential to help close public health gaps across different cultures and improve population health.

In several emergency situations, during natural or human-caused disasters, frontline responders need to be able to communicate and collaborate to properly carry out the relief mission. Some countries are building their national Public Safety Mobile Broadband based on cellular LTE technology to provide fast, safe, and secure emergency services. Otherwise, in several emergency situations, the cellular antennas can be overloaded or partially damaged in manner to affect the group communication services. Since few last years, direct device-to-device (D2D) communications have been proposed by 3GPP as an underlay to Long Term Evolution (LTE) networks based on proximity, reuse, and hop gains. This paper focuses on the loosely coupled model based on D2D direct communication for Public Safety context. Many scenarios related to user membership and network management are detailed. Both “less cost” and “optimized tree” approaches are proposed, implemented, and their performance evaluated in terms of network updates number and resulting average Channel Quality Indicator (CQI). Other optimization approaches with different CQI threshold and optimization interval values have been implemented, simulated and their performance are compared with the “optimized tree”.

Pregnancy at advanced maternal age is considered a risk factor for adverse maternal, fetal, and neonatal outcomes. Here we investigated whether maternal age could be associated with differences in the blood levels of newborn screening (NBS) markers for inborn metabolic disorders on the Recommended Universal Screening Panel (RUSP). Population-level NBS data from screen-negative singleton infants were examined, which included blood metabolic markers and covariates such as gestational age, birth weight, age at blood collection, infant sex, parent-reported ethnicity, and maternal age at delivery. Marker levels were compared between maternal age groups (age range: 15-44 years) using effect size analyses, which controlled for group size differences and potential confounding from other covariates. Our results showed that 13% of the markers had maternal age-related differences including newborn metabolites with either increased (C14, C16, C18, C18:1, C3DC) or decreased (C5OH) levels at advanced maternal age group (≥35 years, absolute Cohen’s d ≥ 0.2). The increased C3DC levels in this group correlated with a higher false-positive rate in newborn screening for malonic acidemia (p-value < 0.001), while no significant difference in screening performance was seen for other markers. Maternal age at delivery is associated with inborn metabolic differences and should be considered together with other clinical variables in genetic disease screening.

Background: This study delves into the examination of racial and ethnic disparities in the distribution of the Monkeypox (MPOX) virus vaccine within the United States, offering a critical healthcare perspective on an emerging public health concern. It particularly focuses on the demographic patterns associated with MPOX transmission and the allocation of vaccines. Methods: A comprehensive analysis was conducted, drawing on a wide array of data sources to understand the vaccine distribution and demographic trends in the United States. The study scrutinized three main aspects: MPOX cases by race and ethnicity, vaccine administration across different racial and gender categories, and the potential disparities therein. Results: The findings reveal significant disparities in the distribution of vaccine doses, with males, particularly gay, bisexual, and other Men who have sex with men (MSM), receiving the majority of doses. Moreover, substantial variations in MPOX cases are observed among different racial and ethnic groups, emphasizing the need for culturally sensitive public health strategies. Conclusions: The study underscores the urgent need for targeted public health interventions to address disparities and safeguard the well-being of those at higher risk, particularly MSM. It highlights the importance of equity in vaccine distribution and culturally sensitive approaches, and serves as a foundation for shaping effective public health policies and strategies to mitigate the spread of MPOX. This research advances our understanding of healthcare disparities in the context of an emerging viral infection, providing valuable insights for future public health initiatives.

The paper discusses the experience of implementing an efficient economic management system at the University of Vigo in Spain. This system, which focuses on managing secondments, aims to minimize bureaucracy and standardize economic procedures for various staff groups. By adopting a qualitative methodology and utilizing content analysis, the study compares the University of Vigo's fully digital administrative procedure with other universities in the CRUE network. The results show significant time and cost savings due to this implementation. The improved traceability and information for users support the administrative change, and the positive environmental impacts highlight the commitment to a more sustainable approach. The paper's originality lies in demonstrating how this approach enhances efficiency, reduces costs, and improves sustainability within a Spanish public administration setting.

Investigating transportation disasters in Western Asia over two decades (2003-2023), this study provides a meticulous examination of a comprehensive dataset, shedding light on the dynamics and nuances of these catastrophic events in terms of frequency, modality (air, rail, road, and water), and subsequent outcomes. The data reveals a concerning uptrend in mishaps from 2003 to 2010, which fortunately reverses into a notable decline in the subsequent years. Noteworthy is the predominance of road-related incidents, yet an alarming 73.8% of events are ambiguously categorized under "Unknown", hinting at potential gaps or inconsistencies in record-keeping. With Turkey being a significant epicenter, accounting for nearly 45% of all incidents, the regional distribution of these disasters becomes evident. Advanced ANOVA analyses discern marked variations in fatality rates over the years and between nations. However, the contrast in injury rates among different disaster categories did not achieve statistical significance. While the post-2010 era showcases a commendable reduction in calamities, the data punctuates the persistent necessity for robust safety measures, targeted public awareness campaigns, and infrastructural advancements. In synthesis, this study vehemently advocates for heightened regional collaboration and systematic knowledge dissemination as cornerstones for bolstering transportation safety across Western Asia.

Self-medication with natural products during disease outbreaks in developing countries poses significant public health challenges yet remains relatively unexplored in the published literature. This study aims to assess the implications of such practices, address the state and quality of evidence, identify gaps in the literature, explore determinants and contributing factors, elucidating the implications, and propose possible solutions. Using a modified systematic literature review methodology, 20 articles were selected from 1,683 reports after applying rigorous selection criteria and quality assessment using the AXIS critical evaluation tool. The findings revealed a dearth of literature concerning the implications of self-medication with natural products during disease outbreaks, highlighting the need for further investigation in this domain. Key determinants included gender, acquisition, and ideological factors, while common side effects comprised diarrhoea, stomach pain, sweating, headache, and nausea/vomiting. Notably, self-medication with natural products was associated with reduced communication with healthcare providers, leading to underreported side effects. It also creates a false sense of safety which may potentially exacerbate the spread of the prevailing disease. In conclusion, the rampant use of natural products for self-medication necessitates increased awareness among the population, encouraging individuals to seek professional medical care and support when faced with disease outbreaks.

This article presents a state-of-the-art literature review to understand people’s perceptions and opinions of Autonomous Vehicles (AVs) and the factors that influence AV adoption. A strategic literature search was conducted to select articles for this review. Most of the articles were published within the last five years and they used a household questionnaire survey to collect data. Mostly, they used statistical and econometric methods to evaluate the factors that affect people’s intentions to adopt AVs. The results show that psychological factors often appear as the most important internal factors of people’s willingness to adopt AVs. Additionally, other internal factors such as the socioeconomic profile of individuals and their household, and knowledge and familiarity with AV technologies would affect AV adoption tendencies. User attributes also indirectly affect AV adoption by influencing the psychological factors of users. We identify several critical external factors such as opportunities (e.g., safety and security, low congestion, energy use) and challenges (e.g., system failure, privacy breach, and legal issues), while another influential group includes transportation factors (e.g., travel mode, distance, and time), urban form (e.g., urban/rural, density, land use diversity), affinity to new technology, and the institutional regulatory environment. We discuss some recommendations for policy makers, auto industries, and private stakeholders to formulate policies and strategies to increase market share of AVs. Finally, we identify some limitations of previous studies and provide a blueprint for future research on AV adoption.

Monkeypox virus infection is a recognized public health emergency. Little research has been done on treatment options for this disease. Until recently, there was not a single published work describing the usage of specific drugs in human patients with monkeypox virus infection. This paper gives the first bibliometric analysis of monkeypox treatment options based on data available on PubMed and Scopus. It also reviews the specific drugs used in the treatment of monkeypox. That includes data on Tecovirimat, Cidofovir, Brincidofovir, and Vaccinia Immune Globulin. Tecovirimat is a promising option in progressive disease in terms of efficacy and safety. However, Brincidofovir has been associated with discontinuation of treatment. Cidofovir is also not the preferred drug among physicians. Currently, Tecovirimat can be further used for the management of aggravating cases. More studies should be conducted on Tecovirimat to treat this condition, mainly through controlled trials.

Non-woody forest products play a vital role in the economic uplifts of the local communities living in forest areas. This study was conducted in the Shishikoh Valley, district Chital to identify the economic importance of the Chilghoza nuts. The study was based on interviews and questionnaires, and a total of 50 questionnaires were collected from the whole valley. The results showed that before 2003, the people were unaware of the high economic value of the Chilghoza nuts, they used to sell the Chilghoza nuts at a very low price (US$ 1.7 to 2.4 per bag: approximately 5 Kg) and harvest it for fuelwood purposes. After the IPRP interventions, training and awareness, the local people started conservation of Chilghoza trees and sustainable cone harvesting. The total collection and sell out of Chilghoza nuts in the Shishikoh valley jumped to 87.9 tons and US$ 7.64/kg in 2005 from 32.7 tons and US$ 0.34-0.48/kg, respectively. This study concludes that IPRP interventions improved the economic values of Chilghoza nuts as well as the living standards of the local people.

Most vulnerable individuals are particularly affected by the COVID-19 pandemic. This study takes place in a large city in France. The aim of this study is to describe the mobility of the homeless population at the begin-ning of the health crisis and to analyze its impact in terms of COVID-19 prevalence. From June to August 2020 and September to December 2020, 1272 homeless people were invited to be tested for SARS-CoV-2 antibodies and virus in and completed questionnaires. Our data show that homeless populations are sociologically dif-ferent depending on where they live. We show that people living on the street were most likely to be relocated to emergency shelters than other inhabitants. Some neighborhoods are points of attraction for homeless peo-ple in the city while others emptied during the health crisis, which had consequences for virus circulation. People with a greater number of different dwellings reported became more infected. This first study of the mo-bility and epidemiology of homeless people in time of pandemic provides unique information about mobility mapping, sociological factors of this mobility, mobility at different scales and epidemiological consequences. We suggest that homeless policies need to be radically transformed since actual model exposes people to infection in emergency.

This paper describes a research project carried out in an Italian public school to assess whether parents were willing to take part in food procurement decisions, as well as their ability to accurately predict what foods children would pick at school lunch and their propensity to support sustainable food choices made by the school. The methodology included a questionnaire to 500 parents and an in-depth study of 138 child/parent pairs. The study comprised: (i) presentation of an innovative recipe in the weekly menu of the school canteen; (ii) meal observations of children’s intake at school lunch during the week of the menu modification; (iii) collection of both parents’ and children’s reports on their choices of recipes from the modified weekly menu. The results are commented in light of two important changes that have recently affected Italian public school food procurement: the opening of school canteens to lunches brought from home and the measures adopted since 2020 to contain the Covid-19 pandemic. Both events go in the direction of delegating to parents the multifaceted role of the school in the food arena. The article concludes that the results of the study should discourage this approach.

The COVID-19 pandemic has brought about unprecedented changes to human lifestyles across the world. The virus and associated social restriction measures have been linked to an increase in mental health conditions. A considerable body of evidence shows that spending time in and engaging with nature can improve human health and wellbeing. Our study explores nature’s role in supporting health during the COVID-19 pandemic. We created web-based questionnaires with validated health instruments and conducted spatial analyses in a geographic information system (GIS). We collected data on people’s patterns of nature exposure, associated health and wellbeing responses, and potential socioecological drivers such as relative deprivation, access to greenspaces, and land-cover greenness. We applied a range of statistical analyses including bootstrap resampled correlations and binomial regression models, adjusting for several potential confounding factors. We found that respondents significantly changed their patterns of visiting nature as a result of the COVID-19 pandemic. People spent more time in nature and visited nature more often during the pandemic. People generally visited nature for a health and wellbeing benefit and felt that nature helped them cope during the pandemic. Greater land-cover greenness within a 250 m radius around a respondent’s postcode was important in predicting higher levels of mental wellbeing. There were significantly more food-growing allotments within 100 m and 250 m of respondents with high mental wellbeing scores. The need for a mutually-advantageous relationship between humans and the wider biotic community has never been more important. We must conserve, restore and design nature-centric environments to maintain resilient societies and planetary health.

We previously proposed a public intervention framework concept that would allow people to resume personal and economic activities. We showed that intervention measures are used in a quantitative scale to reduce transmission probabilities and disease severity. In this article, we systematically examine the origin, assumptions, performance and limitations of epidemiological models from different views used in past review. We found that nearly all model assumptions fail to hold or are remote from reality; R0 does not exit or has no utility in guiding treatment options; personalized intervention measures are vitally important to COVID-19 due to its transmission characteristic; and current epidemiological models are unable to accurately assess the true benefits of personalized intervention measures. We suggest that poor performance of the models are attributed to flawed assumption that health/disease properties can be treated as transferable properties. The flaw creates a fiction that disease properties such as infection probabilities and death risks can be transferred from any vulnerable persons to anyone in the population and thus severely limit societal ability to fight the pandemic. We finally show that the benefits of personalized mitigation measures could be determined directly by using variable Ri values for infected persons (or nodes) together assessment of death rate and disability rate; the attempt of avoiding the disease by defeating all potential transmission probabilities is unrealistic; but mitigating disease severity for specific persons is more feasible and reliable. A most reliable strategy for reviving economy is using personalized protective measures and improving person health before effective vaccine is available.

COVID-19 severity is heterogeneously distributed over age strata, but current mitigation strategies are homogeneously applied to all population. Social-distancing and stay-home are effective conservative approaches but lack economic sustainability on long term. Conversely, herd-immunity is a nonrestrictive strategy which can cost remarkable number of human lives and can melt the healthcare system down. Here I propose an Age Adaptive Social Distancing (AASD) engineering strategy to mitigate COVID-19 outbreak. AASD is based on the scientific evidence that the fatality rate grows nonlinearly with age, hence also the containing strategy should adapt nonlinearly. Essentially, AASD suggests that ‘silent spreaders’ (age 0-39) should avoid/minimize direct and indirect contacts with individuals in ‘dangerous zone’ (age 40+). The rationale is: 0-19 should follow parents strategy, healthy 20-39 (low fatality rate) might conduct screened life under active surveillance, to sustain economy and acquire rational immunity; 40-59 should respect social distancing (waiting a therapy); 60+ should stay at home (waiting a vaccine). This might save human lives, reduce healthcare demand and improve economic sustainability. The final take-home message is that future studies should design precision and personalized strategies for specific contagious diseases that integrate different social constrains, active surveillance and contact tracing.

Urban areas face daunting economic challenges that have increased in scope in recent years. At the same time, cities provide for opportunities for growth and value creation. The interplay of these challenges and opportunities represents the area of intervention for policymakers and researchers. However, the traditional approach to urban policy, deriving from the managerial and economic policy theories, shows difficulties mainly related to the capacity to counterbalance the interests and expectations of a multitude of stakeholders participating to the value co-creation process and to bring all different components to synergically contribute to the sustainability of the system. The Author proposes an innovative approach to urban public policy, by adopting the theoretical corpus of the Viable Systems Approach ("VSA"). Urban planning will be particularly analysed, as systemic components of urban areas, with the aim to investigate the decision-making processes for an integrated, efficient, effective and sustainable management of the territory as a multidimensional, multisectoral and multi-stakeholder entity. By recovering different settings, the VSA intends the co-creation of value as the capacity of the viable systems to increase its surviving chances in its own context. The value derives, first of all, from the strategic decisions aimed at finding both dyadic and context consonance. Through its strategic decisions, the Governing Body of the territory develops a specific system as the overall synthesis of all possible systems organised within a specific area, identifying pattern of development agreed by the several stakeholders of the territory. In the dynamics of value co-creation in systemic multi-subjective organizations, where the level of complexity is particularly significant, the research for consonance among different stakeholders is particular important in order to achieve the most value for the territory. In this respect, the VSA may constitute a valid tool, helping to find the necessary capacities to imagine evolutionary paths towards new competencies.

Background: Our previous study highlighted important healthcare access and utilization concerns among new immigrants. Hence, in this study, we aimed to explore the role of public and patient involvement (PPI) may have in enhancing the accessibility and their contribution to migration health studies. Method: An open and in-depth interactive consecutive virtual discussion was conducted among volunteer asylum seekers and refugees from Eritrea and Syria in Switzerland. The novel PPI establishment had three phases; inception, training phase, and contribution phase. Result: At the beginning, the concept of PPI was apprehensive to grasp, as it was a new approach. After training and consecutive discussions, volunteers were ardent to engage actively. Hence, among the prime findings were the PPI's role and effect in raising awareness, PPI's role in exploring and communicating the healthcare system accessibilities and utilization among their community, the impact of PPI in echoing the healthcare needs of their fellow migrants, and PPI's contribution in enhancing and strengthening migration health researches. Conclusion: The PPI volunteers in the study were keen to raise their community's awareness through their networks, and bridge the research gap between researchers and the public.

For many tick-borne organisms, dogs may be utilized as sentinel hosts to estimate the risk of human infection. The detection of antibodies in these animals indicates the circulation of pathogens in each location for a set period of time. The standard protocol for the surveillance of tick-borne diseases established by the Brazilian National Reference Laboratory for Rickettsiosis at the Ezequiel Dias Foundation (FUNED) includes testing the seropositivity of dogs for Rickettsia spp. and Ehrlichia canis. Dog serum samples were collected during FUNED’s surveillance protocol in a preserved area in Brazil. Despite Anaplasma phagocytophilum being endemic in Brazil, this agent is not included in FUNED’s standard protocol. To determine if A. phagocytophilum should be included in the standard testing protocol, a collaboration with Fuller Laboratories was established and the seropositivity for A. phagocytophilum was tested. The estimated prevalence for singular infections: 25% Rickettsia spp.; 52.3% E. canis; and 70.5% A. phagocytophilum. The estimated prevalence for co-infections: 17% Rickettsia spp. and E. canis; 18.2% Rickettsia spp. and A. phagocytophilum; 39.8% E. canis and A. phagocytophilum; and 13.6% Rickettsia spp., E. canis, and A. phagocytophilum. These results confirmed a significant presence of A. phagocytophilum and establishes a potential threat upon the public health.

Objective: To employ Latent Class Analysis (LCA) to investigate dietary intake patterns among Sudanese children aged 0 to 2 years and to examine the association of these patterns with sociodemographic factors. Methods: This study leveraged the Sudan Multiple Indicator Cluster Survey (MICS) 2014 data to uncover dietary intake patterns among 7,362 children using latent class analysis (LCA). We investigated class memberships concerning demographic and socioeconomic factors. The model's adequacy was determined using several fit indices, including BIC, AIC, entropy, CAIC, and SABIC, providing a holistic evaluation of the model's accuracy in capturing dietary behaviors. Results: Three latent classes were identified: Class 1 (55%) with an average nutrition composition, Class 2 (28%) with limited nutrition composition, and Class 3 (17%) with good nutrition composition. Significant associations were found between latent class membership and sociodemographic factors, particularly mother's education level and household wealth. The three-class solution provided the best balance between model fit and class distinction. Conclusions: The LCA revealed distinct dietary intake patterns and underscored the influence of sociodemographic factors on child nutrition. The findings suggest that targeted nutritional interventions should be developed according to the specific needs of different latent classes. The study also highlights the utility of LCA as a robust statistical and machine learning tool in public health research, capable of informing tailored interventions and policies for improving child nutrition. Implications: The study emphasizes the importance of maternal education and socio-economic status in shaping dietary behaviors of children in Sudan. It implies the need for policies that address educational disparities, food security, and economic development as part of comprehensive nutritional interventions.

World Health Organization recommends adjusting the salt intake as a part of the nine global targets to reduce premature mortality from non-communicable chronic diseases as priority and most cost-effective intervention. In 2006. the main aim of the Croatian Action on Salt and Health was to decrease salt intake for 16% because of its critical intake and consequences on human health. We have organized educative activities for increasing awareness on salt harmfulness, defined food categories of prime interest, collaborate with industries and determine salt intake (24h urine-sodium excretion). It was determined that the proportion of salt in ready-to-eat baked bread should not exceed 1.4%. In the period 2014 –2022, salt in the semi-white bread was reduced 14%, in bakery 22% and in largest meat industry in Croatia 25%. Awareness of the harmfulness of salt on health increased from 65.3% in 2008 to 96.9% in 2023 and salt intake was reduced 15.9%-1.8 grams/day (22.8% men, 11.7% women). In last 18 years a significant decrease in salt intake was achieved in Croatia, awareness of its harmfulness increased, collaboration with food industry established and regulatory documents launched. However, salt intake is still very high underlying the need for continuation of efforts and even stronger activities.

Burnout represents a concern for all healthcare providers, particularly those specializing in emergency medical care for whom burnout outcomes have been well-documented. What remains unknown is the effect of burnout on redeployed medical specialists during the COVID-19 pandemic from an appointment-centered practice to emergency care directed by public health considerations. This research aims to identify and assess the burnout responses of fourteen medical specialties noted in searched returns of the four most cited articles published since 2020 about non-emergency physicians regarding their burnout brought on by the unanticipated need for them to provide emergency care during the recent pandemic. The hypothesis is that medical specialists accustomed to planning for emergency possibilities in their appointment-centered practice would demonstrate the least burnout regarding COVID-19-related emergencies. Considering coping as a process based on Lazarus's research, comparing and ranking the COVID-19 emergency responses across the various normally appointment-centered medical specialties in their employed coping strategies determines the outcome. With the hypothesis supported, suggested interventions for future pandemics—when these specialists are, again, redeployed to emergency care directed by public health considerations—are those coping strategies identified as most effective in reducing burnout while maintaining the viability of the medical specialty and excellent patient care.

This article proposes a particular strategy to proceed with a progressive electrification of public transport systems in cities. Starting from a bus operation model, the possible electrification of two routes is analysed, one urban and another extra-urban in the city of Pisa. An estimate is made of the energy uses associated with certain operating modes. The maximum level of consumption is estimated at approximately 280 kWh per day per bus for the urban route and excluding some special days, less than 215 kWh per day for the extra-urban route, for which a hybrid bus is proposed. Starting from an estimate of the daily consumption for the management of the two routes, the sizing of a photovoltaic system distributed on some modular shelters which serves to power the same routes is carried out. The resulting system has a power of the order of 190-200 kW. The modular solution is also outlined, and an installation is proposed. The analyzed case lends itself to being easily replicated.

Public restrooms are often a hub of microbial contamination, and the examination of bacterial contamination in these facilities can serve as an important indicator of the transmission of infectious diseases. This study was conducted to determine the prevalence of bacterial contamination in public restrooms based on the economic class of the building. Samples were collected from various spots in 32 restrooms found in 10 shopping malls, classifying them into two categories: upper-end restrooms and lower-end restrooms. The findings showed that the level of contamination was higher in the lower-end restrooms, with the seat being the most contaminated area. The most dominant Gram-positive bacteria were coagulase-negative staphylococci species, making up 86% of the identified Gram-positive isolates. The most dominant Gram-negative bacteria identified were Klebsiella pneumoniae and Pseudomonas aeruginosa. The antibiotic sensitivity test results revealed the presence of multi-drug resistant bacteria among the Gram-positive and negative isolates, including Staphylococcus haemolyticus, Staphylococcus kloosi, Acinetobacter baumanii, and Pseudomonas aeruginosa. In conclusion, the study underscores the significance of monitoring bacterial contamination in public restrooms and the need for measures to reduce the spread of infectious diseases. Further research is crucial to gain a complete understanding of the bacterial contamination in public restrooms and their resistance patterns, to ensure the safety and health of the public. The implementation of improved cleaning practices and hands-free designs in restrooms can help reduce the risk of cross-contamination and prevent the spread of diseases.

Infections with multi-drug-resistant (MDR) pathogens in food-animals threaten public health and food security. However, the epidemiology and factors associated with MDR Escherichia coli on Ugandan farms are not well known. This study investigated the prevalence, resistance patterns and factors associated with MDR E. coli carriage on chicken farms. A total of 158 E. coli strains were isolated from 158 chicken farms. The disc diffusion method for susceptibility testing was performed. Clinical breakpoints were interpreted according to Clinical and Laboratory Standards Institute guidelines. MDR was defined as resistance to three or more classes of antimicrobials. MDR E. coli prevalence on chicken farms was 62.7% (95% CI: 55.0 – 70.3). High resistance was observed against ampicillin 79.8% (95% CI: 72.7–85.4), tetracycline 72.8% (95% CI: 65.2–79.2), cotrimoxazole 55.7% (95% CI: 47.8–63.3), and ciprofloxacin 38% (95% CI: 30.7–45.9). Farmers who were males (APR = 0.72, CI: 0.55, 0.93), and attained at least secondary education (APR=0.64, CI: 0.46, 0.88) and administration of recommended antibiotic doses (APR = 0.76, CI: 0.59–0.96) posed a lower risk of MDR E. coli carriage. Farms without footbaths posed a heighten risk (APR=1.48, CI: 1.16–1.88). MDR E. coli were highly prevalent on chicken farms. This study underscores the need for antimicrobial stewardship and improved infection prevention strategies on chicken farms.

Accountable Care Organizations (ACOs) are healthcare delivery systems that aim to coordinate and improve the quality of care for patients while reducing costs. ACOs bring together doctors, hospitals, and other healthcare providers to work as a team to care for a defined population of patients. The idea behind ACOs is to shift the focus from paying for each individual service provided to patients, known as fee-for-service, to paying for the overall care and well-being of patients.ACOs typically operate under a shared savings model and also encourages providers to use data and technology to better coordinate care and improve patient outcomes.ACOs can be physician-led organizations, hospital-led organizations, and collaborations between healthcare providers. The success of ACOs depends on many factors, including the level of cooperation and collaboration among healthcare providers, the quality of care provided, and the ability to effectively manage costs.Despite their potential benefits, ACOs also face challenges, including the difficulty of coordinating care across multiple healthcare providers, the need to invest in technology and data management systems, and the challenge of changing provider behavior.This study assessed a number of systemic reviews and journals to assess the impact of ACO’s on population health. ACO’s have shifted away from costly care patterns and thus helped many countries.

The occurrence rate of occupational accidents caused by slipping and falling is 50% worldwide. Determining the slip safety risk is necessary to minimize the accidents caused by slipping in pedestrian walking areas. By on-site testing, this study aims to determine the slip risks of floor coverings used in walking areas with many pedestrians in public service buildings (PSB). For this purpose, on-site measurements were performed in two environments and six locations in PSB using portable GMG 200 and pendulum testers operating according to DIN 51131 and TS EN 14231 standards. These tests were performed on four-floor coverings with polished surface treatment in PSB. Since the floor coverings measured have a polished surface, it can be seen that the dynamic friction coefficients (DCOF) values are very low, and the slip risks are high. By statistically analyzing the slip test data using the K-means method, a new safety classification was made according to the usage areas of floor coverings. To minimize the risk of slip safety, especially for students, patients, and employees in PSB, it is recommended to use floor coverings with high DCOF values and low slip risk.

This research undertakes a quantitative exploration of the impact of procurement mo-dalities on economic efficiency and inclusive procurement within the Dominican Repub-lic's public sector. Applying data science methodologies and machine learning techniques, this study analyzes a rich dataset of public procurement contracts spanning from 2018 to 2023. A focus is placed on understanding how different procurement modalities affect contract amounts and processing times—two key indicators of economic efficiency. Machine learning models, including Random Forest and Gradient Boosting, are em-ployed to predict these essential metrics across different procurement modalities. The findings indicate a significant positive correlation between certain procurement modali-ties and economic efficiency. The machine learning models reveal that procurement strategies focused on local sourcing and transparent bidding processes tend to yield high-er economic returns and more equitable outcomes. This research underscores the poten-tial of quantitative analysis to inform procurement policies, fostering a more economi-cally efficient and inclusive procurement ecosystem in the Dominican Republic's public sector. The insights garnered from this study could have significant implications for the design of more inclusive procurement strategies, contributing to socio-economic growth and corruption reduction in the Dominican Republic.

Considering the aging society and budget constraints, a strategy for reforming public transportation welfare policies is essential for sustainability. Among the various transportation welfare policies, fare discount policies are provided to specific age groups, and most countries offer benefits to several public transportation. South Korea provides a fare-free policy limited to subways, and the need for policy modification is emerging due to sustainability problems caused by an aging society. Hence, the scope of the policy should be expanded to all travel modes, but the discount rate should be reduced, or the target group should be reduced in consideration of the budget. This study proposes a travel mode to focus on by city through the preference of the elderly. The latent class model is employed to classfy stated preference data collected from the survey. The estimation results show a significant preference heterogeneity depending on the level of subway supply by region, and a policy focused on subways would be more reasonable in cities with sufficient subway infrastructure. Hence, regarding sustainability, it may be more appropriate to focus on specific means than to provide the same discount policy for all public transport.

The study aimed to identify clinical pharmacology patterns of prescribed and taken medications in older cardiovascular patients using electronic health records (EHRs) (n = 704) (2019–2022). Medscape Drug Interaction Checker was used to identify pairwise drug-drug interactions (DDIs). Prevalence rates of DDIs were 73.5% and 68.5% among taken and prescribed drugs, respectively. However, total number of DDIs was significantly higher among prescribed medications compared with the list of taken drugs (p < 0.05). Serious DDIs comprised 16% and 7% of all DDIs among prescribed and taken medications, correspondingly (p < 0.05). Median DDI numbers between prescribed versus taken medications were Me = 2, IQR 0-7 and Me = 3, IQR 0-7 per record, respectively. Prevalence of polypharmacy was significantly higher among prescribed medications compared with taken medications (p < 0.05). Women were taking significantly more drugs and had higher rates of polypharmacy and DDIs (p < 0.05). No sex-related differences were observed in the list of prescribed medications. ICD code U07.1 (COVID-19, virus identified) was associated with the highest median DDI number per record. Further research is warranted to improve EHR structure, patient engagement in reporting adverse drug reactions, and genetic profiling of patients to avoid potentially serious DDIs.

Antibiotic resistance has emerged as one of the major concerns to public human health due to issues in treatment and control of major infectious diseases. From discovery of penicillin in 1940, the antibiotic resistance originated and now developed the microorganisms as resistive strains to the major available antibiotics. Furthermore, studies on this captivating activity of the microbes provide insight into the complexities of microbial physiology and may offer some guidance in preventing the onset and consequent development of antibiotic resistance. Despite of initiatives taken in last few decades to overcome the issues, the trends of antibiotic resistance gained much peak. Antibiotic resistance appears to have emerged as a result of various factors including antibiotics being misused and overused in both the medical field and the agricultural sector. Important factors in the development of antibiotic resistance also include bacterial mutation, unplanned evolution, and horizontal gene transfers. In addition, antibiotics resistance imposed the financial consequences to public health and drug development research. Future advancements related to innovative antibiotics and molecular drug designing become challenge for researchers due to intensive multiple antibiotics resistance among human population. Many researches have been conducted on origin, evolutionary aspect of antibiotic resistance and mechanisms of antibiotics resistance, but its effect on future drug development is little understood. Therefore, the recent review will highlight the role of antibiotic resistance in drug designing and impacts of antibiotic resistance on drug development in future.

This work analyzes a new indoor laboratory data set looking at early fire indicators in controlled and realistic experiments representing different incipient fire scenarios. The experiments were performed within the confines of an indoor laboratory setting using multiple distributed sensor nodes on different room positions. Each sensor node collected data of particulate matter (PM), volatile organic compounds (VOC), CO, CO2, H2, UV, air temperature and humidity in terms of a multivariate time series. These data hold immense value for researchers within the machine learning and data science communities who are keen on exploring innovative advanced statistical and machine learning techniques. They serve as a valuable resource for the development of early fire detection systems. The analysis of the collected data was carried out in dependence of the manhattan distance between the fire source and the sensor node. We found that especially larger particles (&gt; 0.5 μm) and VOCs show a significant dependency with respect to the intensity as a function of the manhattan distance to the source. Moreover, we observed differences in the propagation behavior of VOCs, PM, and CO, which are particularly relevant in incipient fire scenarios due to the presence of strand popagation effects.

The Kingdom of Saudi Arabia (KSA) is known for its high car ownership and usage as well its high GDP per capita. This is combined with low/ or no provision of public transportation (PT) systems, has been resulting in perceptual attitudes of full dependency on private car travel. The level of awareness of the benefits of reducing car use and increasing the travel by more sustainable options, has a great impact on social change and behaviour. The Kingdom is currently progressing towards a new phase of “national transfer” through implementation of strategic and sustainable measures and programs. The city of Riyadh is construction a massive metro-system in Riyadh, that is nearing completion and operation. The public is aware of the national agenda, aware of the newly constructed projects and aware of the needed social change to realize the new vision of the country. This paper aims to assess travel behaviour and attitudes towards public transportation of Saudi travellers’ who are witnessing the new transformation in the Kingdom and who are aware of the new sustainable projects. Depicted from the theory of random utility, a discrete choice model of the intent to use public transportation is calibrated as a function of social and attitudinal factors. An online survey was designed and carried out using social media means; a completed 399 questionnaires have been obtained and studied. The methodology includes examining attitudes and preferences of the participants towards using public transportation options against participants’ socio-economic data. The analysis was carried out using ordinal logistic regression analysis (OLR) which is an efficient technique that is derived from the theory of random utility. The results show a good support for PT; a higher support for public transportation modes, form participants who are young females, lower income groups and the university graduates were reported. The level of support seems higher with the higher level of awareness about the new PT system.

Earliest critical context of the pandemic, preceding the first real epidemiological wave of contagion in Bulgaria, was examined in a socio-affective perspective. A retrospective and agnostic analytical approach was adopted. Our goal was to identify traits and trends that explain public health support (PHS) of Bulgarians during the first two months of the declared state of emergency. We investigated a set of variables with a unified method within an international scientific network, named International Collaboration on Social &amp; Moral Psychology of COVID-19 (ICSMP) in April and May 2020. Conspiracy Theories beliefs were a significant predictor of lower PHS. Psychological Well-being was significantly associated with Physical Contact and Anti-Corona Policy Support. Physical Contact was significantly predicted by less Conspiracy Theories beliefs, higher Collective Narcissism, Open-mindedness, higher Trait Self-Control, Moral Identity, Risk Perception, and Psychological Well-Being. Physical Hygiene compliance was predicted by less Conspiracy Theories beliefs, Collective Narcissism, Morality-as-Cooperation, Moral Identity, and Psychological Well-Being. Results revealed two polar trends of support and non-support of public health policies. The contribution of this study is in providing evidence for affective polarization and phenomenology of (non)precarity during the outbreak of the pandemic.

In this article, we present the use of the coupled land surface model and groundwater flow model SWAT-MODFLOW with the decision support tool WEAP (Water Evaluation and Planning software) to predict future surface water abstraction scenarios in a complex river basin, under conditions of climate change. The modeling framework is applied to the Dee River catchment in Wales, United Kingdom. Regarding hydrology, the coupled model improves overall water balance and low streamflow conditions, compared to a stand-alone SWAT model. The calibrated SWAT-MODFLOW is employed with high resolution climate model data from the UKCP18 project with future scenario of RCP85 from 2020 to 2040. Then, water supply results from SWAT-MODFLOW are fed into WEAP as input for the river reach in the downstream region of the river basin. This system is utilized to create various future scenarios of surface water abstraction of public water supply in the downstream region: maximum licensed withdraw, 50 % authorized abstractions, monthly time series with 1% increase of water use, and maximum water withdraw year based on historical records repeated every year with 1% increase of water use, to estimate the unmet demands and streamflow requirement. This modeling approach can be used in other river basins to manage scenarios of supply and demand.

Since the 21st century, China's urbanization process has been rapid development, the concept and function of urban public space in the city has been gradually paid attention to. In order to guarantee life and water, most urban construction relies on rivers, and Bridges are the most important way to communicate between urban areas. The main functional part of the bridge is the span structure, that is, the bearing structure of the bridge, and the lower part of the "gray" space formed by the bridge structure. Considering the social level, with the economic growth and urbanization development, people have brought a better living environment and quality of life, and also improved the requirements for urban public environment. In the increasingly tense urban space, how to use and transform the space under the bridge is a problem that needs to be considered and solved. In view of this problem, in this study, we try to solve the micro-transformation of space under Bridges in cities through public art from the perspective of "regional culture" and "art for all". This paper analyzes the micro-transformation of space art under Bridges in two large cities of Shanghai and Foshan, namely, the space under Bridges under Songhong Road in Shanghai, the space under Bridges under Central Of Suzhou River and the space under Bridges under Pingsheng Bridge in Foshan. This paper discusses the cultural intervention of "regional culture" in the micro-transformation of the space under the bridge, and the influence and effect of "art for all" on the public art space under the bridge after the transformation to the community and the public.

The rapidly expanding corona pandemic in 2020 brought the world to virtual economic stagna-tion. While the impact on the environment from suspended air traffic, idle industry and economic lockdown has been considerable, so have the economic and social consequences of the crisis. To make matters worse, the resulting state of stagnation is neither economically nor socially sustaina-ble. Nevertheless, we need to ask ourselves what we can learn from the situation in order to ex-plore the benefits of globalization, intercept similar crisis situations more effectively in the future and move towards more sustainable development on an ecological, economic and social level. This paper identifies the areas of expanded externality management needed to further improve environmental quality, digitalization, network expansion and basic income. These central issues need to be addressed both during and after the crisis in order to deal with problems of inequality and climate change mitigation for current and future generations. Concrete concepts will be put forward and discussed in the paper.

This work examines the effects of two problematic trends in diesel passenger car emissions – increasing NO2/NOx ratio by conversion of NO into NO2 in catalysts and a disparity between the emission limit and the actual emissions in everyday driving – on ambient air quality in Prague. NO2 concentrations were measured by 104 membrane-closed Palmes passive samplers at 65 locations in Prague in March-April and September-October of 2019. NO2 concentrations measured by city stations during those periods were comparable with the 2016-2019. The average measured NO2 concentrations at the selected locations, after correcting for the 18.5% positive bias of samplers co-located with a monitoring station, were 36 µg/m3 (range 16-69 µg/m3, median 35.3 µg/m3), with the EU annual limit of 40 µg/m3 exceeded at 32% of locations. The NO2 concentrations have correlated well (R2=0.76) with the 2019 average daily vehicle counts, corrected for additional emissions due to uphill travel and intersections. In addition to expected “hot-spots” at busy intersections in the city center, new ones were identified, i.e. along a six-lane road V Holešovičkách. Comparison of data from six monitoring stations during March 15-April 30, 2020 travel restrictions with the same period in 2016-2019 revealed an overall reduction of NO2 and even a larger reduction of NO. The spatial analysis of data from passive samplers and time analysis of data during the travel restrictions both demonstrate a consistent positive correlation between traffic intensity and NO2 concentrations along/near the travel path. The slow pace of NO2 reductions in Prague suggests that stricter vehicle NOx emission limits, introduced in the last decade or two, have so far failed to sufficiently reduce the ambient NO2 concentrations, and there is no clear sign of remedy of Dieselgate NOx excess emissions.

The aim of this study was to develop and validate a predictive early tooth loss multivariable model for periodontitis patients before periodontal treatment. A total of 544 patients seeking periodontal care at a university dental hospital were enrolled in the study. Teeth extracted after periodontal diagnosis and due to periodontal reasons were recorded. Clinical and sociodemographic variables were analyzed, considering the risk of short-term tooth loss. This study followed the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines for development and validation, with two cohorts considered as follows: 455 patients in the development phase and 99 in the validation phase. As a result, it was possible to compute a predictive model based on tooth type and clinical attachment loss. The model explained 25.3% of the total variability and correctly ranked 98.9% of the cases. The final reduced model area under the curve (AUC) was 0.809 (95% Confidence Interval (95% CI): 0.629 - 0.989) for the validation sample and 0.920 (95% CI: 0.891 - 0.950) for the development cohort. The established model presented adequate prediction potential of early tooth loss due to periodontitis. This model may have clinical and epidemiologic relevance towards the prediction of tooth loss burden.

Many microbes live in habitats below their optimum temperature. Retention of metabolic heat by aggregation or insulation would boost growth. Generation of excess metabolic heat may also provide benefit. A cell that makes excess metabolic heat pays the cost of production, whereas the benefit may be shared by neighbors within a zone of local heat capture. Metabolic heat as a shareable public good raises interesting questions about conflict and cooperation of heat production and capture. Metabolic heat may also be deployed as a weapon. Species with greater thermotolerance gain by raising local temperature to outcompete less thermotolerant taxa. Metabolic heat may provide defense against bacteriophage attack, by analogy with fever in vertebrates. This article outlines the theory of metabolic heat in microbial conflict and cooperation, presenting several predictions for future study.

Background: Australia received its first case of coronavirus on 25 January 2020. Since then the demands of COVID-19 has presented unparalleled levels of strain on the public healthcare systems in the country. In this time of crisis, pharmacists and community pharmacy staff have modified work strategies according to the rapidly changing environment. With a delayed dissemination of resources and guidelines, pharmacist and pharmacies are practicing innovative infection control methods across Australia to protect their staff, patients and the community. This article seeks to explore the current activities undertaken by pharmacists in various community pharmacy settings across Australia in relation to the safety of the workplace environments for staff and patients. Information collected can help inform future decisions in pandemic preparation for pharmacies in response to similar health crisis now and in the future. Methods: An online cross-sectional survey study was conducted in Australia during the COVID-19 outbreak from 1^st to 30^th April 2020. The questionnaire addressed community pharmacist’s awareness and response to infection and sanitation control. Results: A total of 137 pharmacists took part in the survey, with almost half (45.26%) belonging to the age group of 25 to 34 years. Community pharmacy formed the bulk (89.05%) of the respondent’s primary place of practice. There was a good uptake of safety measures by pharmacists and their pharmacies to protect staff and patients. However the task of reassigning high health risk staff was not heavily practiced (34.31%). Regular cleaning took place in the pharmacy, but the use of gloves while cleaning was not practiced in 48.18% of respondents. In addition, only 46.72% of respondents reported observing script baskets being cleaned and disinfected. About one-third (37.96%) of pharmacists were aware of the two-step cleaning and disinfecting process, but only 18.98% of pharmacists reported observing or performing this sanitation procedure. More than half of surveyed pharmacists reported having difficulty keeping up with infection control changes and pharmacy practice guidelines during the pandemic. Conclusion: This study demonstrates that the majority of pharmacists are not fully aware of the infection control measures needed in a community pharmacy setting. The influx of coronavirus updates has made it difficult for pharmacists to implement accurate procedures on some aspects of workplace hygiene, which may have led to some gaps in infection control measures. Pharmacists must aim to uphold their public health ambassador role and aim to keep up-to-date with professional guidance to provide the necessary infection control measures to ensure staff, patient and public health safety.

Some of the European countries affected by COVID-19 have not learned from previous experience in China. Italy did not learn from China and Spain did neither learn from China nor from Italy. Confinement in Spain was postponed due to pressure from economic interests and traveling of infected people, especially from Madrid to the beaches in South-East Spain, was allowed. Strict confinement and border closure came late, when the curve of infected people and the death toll already had the worse trend worldwide. Tests to SARS-CoV-2 RNA detection by PCR, were first unavailable and, later, faulty and/or detecting antibodies and not the virus itself. Instead of mobilizing research laboratories for making tests, and instead of making masks and ventilators, mediatic scientists asked for money for controversial clinical trials and for obtaining a vaccine. In this scenario, common sense indicates that ad hoc measures should be taken at the end of confinement in order to minimize pain. The chain of errors should be avoided in the management of next pandemics by designing Good Practice Rules (GPRs). In addition, post-confinement measures should be implemented as soon as possible to be ready for SARS-CoV-2 return next season. In this sense a longitudinal study in the most affected cities (Madrid, Barcelona, Vitoria and Pamplona) should be performed with the primary objective of detecting carriers with no symptoms, to stratify patients according to symptoms, and to early detection of virus reappearance. Also relevant is to sequence as many viruses as possible to detect possible variants; there are still patients that are PCR positive.

There is a long trail of research studies testing the in vitro and in vivo efficacy of chloroquine and its derivatives in treating and preventing infection by various coronavirus species. More recent findings have highlighted the possibility of treating patients infected with the 2019 novel coronavirus, SARS-CoV-2. This review describes the mechanism of coronavirus infection, the mechanism of action of chloroquine, and summarizes the available literature highlighting the efficacy of chloroquine as an anti-coronavirus agent. These findings should encourage the wider scientific community to conduct thorough research on the possible efficacy of chloroquine and its derivatives in treating and preventing SARS-CoV-2 infection.

Background: After serious epidemics of chikungunya (CHIKV) and Zika (ZIKV) in the Americas, dengue (DENV) have reemerged in most countries. We analyzed the incidence, incidence rates, and evolution of DENV cases in Honduras from 2015-2018 and the ongoing 2019 epidemic. Methods: Using epidemiological weeks (EW) surveillance data on the DENV in Honduras, we estimated incidence rates (cases/100,000 population), and developed maps at national, departmental, and municipal levels. Results: From 1 January 2016 to 21 July 2019, a total of 109,557 cases of DENV were reported, 28,603 in 2019, for an incidence rate of 312.32 cases/100,000 pop this year; 0.13% laboratory-confirmed. The highest peak was reached on the EW 28°, 2019 (5,299 cases; 57.89 cases/100,000 pop). The department with the highest number of cases and incidence rate was Cortes (8,404 cases, 479.68 cases/100,000 pop in 2019). Discussion: The pattern and evolution of DENV epidemic in 2019 in Honduras has been similar to that which occurred for in 2015. As previously reported, this epidemic involved the north and central areas of the country predominantly, reaching municipality incidences there >1,000 cases/100,000 pop (1%). Studies using geographical information systems linked with clinical disease characteristics are necessary to attain accurate epidemiological data for public health systems. Such information is also useful for assessment of risk for travelers who visit specific areas in a destination country.

Background: Zika virus (ZIKV) infection has significantly affected Latin America in 2015–2017. Most studies have been reported from Brazil and Colombia, and only a few from Central America. For these reasons we analyzed the incidence, incidence rates and evolution of cases in Honduras from 2016–2017. Methods: Using epidemiological weeks (EW) surveillance data on the ZIKV epidemics in Honduras, we estimated incidence rates (cases/100,000 population), and developed maps at national, departmental and municipal levels. Results: From 1 January 2016 to 31 December 2017, a total of 32,607 cases of ZIKV were reported (98.5% in 2016 for an incidence rate of 36.85 cases/100,000 pop; 1% confirmed by RT-PCR). The highest peak was reached on the EW 6°, 2016 (2,559 cases; 29.34 cases/100,000 pop). The department with the highest number of cases and incidence rate was Cortés (13,128 cases, 791.08 cases/100,000 pop in 2016). Discussion: The pattern and evolution of ZIKV infection in Honduras has been similar to that which occurred for chikungunya in 2015. As previously reported, infection with chikungunya involved predominantly the central and capital area of the country, reaching incidences there >750 cases/100,000 pop. Studies using geographical information systems linked with clinical disease characteristics are necessary to attain accurate epidemiological data for public health systems. Such information is also useful for assessment of risk for travelers who visit specific areas in a destination country.

Limited observational studies have described the relationship between sleep duration and overall diet. The present study investigated the association between sleep duration at weekdays and empirically derived dietary patterns in a nationally representative sample of UK adults, aged 19-64 years old, participating in the 2008-2012 UK National Diet and Nutrition Survey Rolling Programme. Survey members completed between three to four days of dietary records. Sleep duration at weekdays was categorised into tertiles to reflect short, normal and long sleep duration. Social jetlag was calculated as the difference between sleep duration at weekends and weekdays. The association between sleep duration/ social jetlag and dietary patterns, derived by principal components analysis, was assessed regressing diet on sleep whilst accounting for the complex survey design and adjusting for relevant confounders. Survey members in the highest tertile of sleep duration had on average 0.45 (95% CI -0.78, -0.12) lower healthy dietary pattern score compared to middle tertile (p =0.007). There was an inverted u-shaped association between social jetlag and a healthy dietary pattern, such that when sleep at weekends exceeded weekday sleep by 1h 45min, scores for indicating a healthy dietary pattern declined (p =0.005). In conclusion, long sleep duration at weekdays and an increased social jetlag are associated with a lower healthy dietary pattern score. Further research is required to address factors influencing dietary patterns in long sleepers.

Civic participation is of great significance to urban management decision-making. In order to facilitate citizens to participate in city management decision-making, this paper proposes a large-scale group decision-making (LSGDM) method based on multi-granular probabilistic linguistic preference relations (MG-PLPRs). First, each decision maker selects a language terms set from the multi-granularity language terms set to represent individual preference relations and the MG-PLPRs are obtained by statistical calculation to represent sub-group’s preferences information. Then, an optimization model based on the expected consistency of PLPR and consensus measure of groups is established to achieving consensus reaching processes, which can ensure satisfactory individual consistency and group consensus. Finally, the validity and applicability of the proposed method is verified by a case of a city "shared garden" site selection with the participation of citizens.

Understanding and improving seismic resilience in regions prone to earthquakes is crucial for mitigating the effects of natural disasters. This study zeroes in on Montenegro, a region frequently affected by seismic activity, with the goals of critically evaluating current resilience levels, pinpointing key preparedness gaps, and assessing the efficacy of existing response strategies. Employing qualitative methods, the research involved semi-structured interviews with residents from Montenegro's most vulnerable areas, including Nikšić, Podgorica, Bar, Kotor, Cetinje, Budva, Herceg Novi, and Berane. These participants, selected for their firsthand experiences with significant earthquake impacts, contributed to a deeper understanding through discussions that aligned with a broad conceptual framework, exploring everything from the nuances of citi-zen resilience to local government responses and personal preparedness. The study aimed to gather in-depth views on community resilience during earthquakes, evaluate citizens' knowledge and preparedness for such disasters, and examine local governance strategies for enhancing seismic resilience. It revealed varying resilience levels across communities, with some displaying well-structured strategies while others showed notable deficiencies. The findings underscore the urgent need for community-specific preparedness programs and improvements in both structural and educational frameworks to enhance resilience. This research highlights the necessity of a comprehensive approach that includes detailed risk assessments, tailored preparedness training, and stronger public awareness efforts. Additionally, it emphasizes strengthening local governments' capabilities to enact and sustain effective response measures to ensure ongoing community resilience against future seismic challenges.

Avian influenza viruses (AIVs) are highly contagious respiratory viruses of birds, lead-ing to significant morbidity and mortality globally and causing substantial economic losses to the poultry industry. Since their first isolation in 2013, the Asian-origin H5N1 highly pathogenic avian influenza viruses (HPAI) of clade 2.3.4.4b have undergone unprecedented evolution and re-assortment of internal gene segments and have spread to Asia, Europe, Africa, and America, caus-ing outbreaks in all the poultry categories. Novel epidemiological and pathobiological character-istics, distinct from other clades, are specific of clade 2.3.4.4b viruses. Wild waterfowl, the natu-ral reservoir of AIVs, are frequently found infected with clade 2.3.4.4b viruses, which can also cause high morbidity and mortality in these birds. The sustained clade 2.3.4.4b virus circulation in waterfowl has also led to virus infection in other wild bird species, with implications for the conservation of endangered species. Furthermore, clade 2.3.4.4b viruses have been isolated in var-ious wild and domestic mammals worldwide, and critical mutations related to virus adaptation to mammalian species have been identified, raising concerns about virus spillover to humans. The main clinical signs, and anatomopathological findings associated to clade 2.3.4.4b virus infection in birds and non-human mammals are hereby summarized.

The focus of this article is the evaluation of the quality and the degree of community engagement in an expert-based, public-health communicative intervention for Alcohol Use Disorder (AUD). In 2023 the Canadian Alcohol Use Disorder Society collaborated with a grass-roots community health group, a regional health authority, and an academic participatory researcher to organize a working group to mount a social-marketing campaign to increase community support for AUD medical treatment in family-practice settings in a rural community in British Columbia. The partnership working group conducted a series of activities in the school system, the town council, and the community. This article covers the formative evaluation and the summative evaluation of the working group's effectiveness. The formative evaluation ("lessons learned" and "recommendations") consists of consensus evaluations of the quality of each activity using a variety of data sources. The formative evaluation followed improvement science methods and used consensus meetings to provide and reflect on formal and informal feedback. Formative results reflect the consensus of the participants in the working group and they record the reactions in the community. The summative evaluation measures evidence of community engagement found in transcribed text from meeting minutes. The summative evaluation used theory-based frameworks and text data visualization to assess the engagement dynamics of the working group. The summative evaluation helps to put the formative evaluation into perspective as communicative action. The summative evaluation validates the formative evaluation by revealing the communicative dynamics of engagement which resulted in the community’s increased capacity to understand and support Alcohol Use Disorder Treatment options. The working group and the entire intervention was seen by the participants and the public as a success and capable of replication. In a small community, it instilled new understandings and attitudes, bringing an emerging awareness of medication as an optional health mitigation strategy for Alcohol Use Disorder. Our study furthers this overall assessment by using theoretical constructs and analysis of communicative records to trace engagement characteristics of interest to researchers, societies, and community groups contemplating similar interventions in the future. The study also validates the effectiveness of communicative analysis as a measure of social-marketing for expert-based public health interventions.

In On Revolution, Hannah Arendt makes the case that a constitution must account for the need of the human person to participate in the building of society, both as a primordial and continual action of founding. This paper draws on Arendt's insight on the relationship between privacy and the notion of property, both of which the constitution must protect, as it is dependent on those notions. Property in its fullest sense is the means by which a person interacts with others and establishes a society. Particularly important for this notion of engagement are the concepts of shame and the love of goodness. The actor emerges from the private sphere to interact with others on the strength of the secrecy and confidentiality of her intimate, private relationships. Property is therefore essential to human flourishing and happiness. Following this, the activity of constructing the public forum on the basis of the private is an important feature of Arendt's constitutionalism. Human action showers third-party esteem on the actor's family and friends, binding them to the constitutional structure and strengthening familial relationships and social cohesion.

This study explores the intriguing relationship between personality traits, self-rated fitness (SRF), and physical activity (PA) variables among German university students (N = 4,244), and sheds light on the impact of personality on adherence to PA guidelines. Employing an online cross-sectional study, the short-form of the Big Five Inventory-2 assessed five domains of personality traits (Extraversion, Negative Emotionality, Agreeableness, Conscientiousness, and Open-Mindedness). PA, including sitting time, was assessed using the International Physical Activity Questionnaire (short-form). SRF and muscle-strengthening activities (MSA) were assessed with one item each. Multiple linear and logistic regression analyses examined associations of individual personality trait domains and all domains combined with SFR, PA variables, and adherence to PA guidelines, controlling for sociodemographic, behavioral, and (mental) health covariates. Most reliably, Extraversion and Conscientiousness revealed positive associations with PA variables, while Negative Emotionality yielded inverse relationships with PA variables. For instance, each unit increase in Extraversion corresponded to additional 17 minutes weekly MSA. Contrary, daily sitting time was unrelated to personality. Of note, high Open-Mindedness was associated with lower odds for adhering to current PA guidelines. The findings have implications for developing targeted interventions that promote a physically active lifestyle and support students' well-being and academic success.

Public Health Officers' (PHO) experiences in reaction to the COVID-19 pandemic can be based on whether the PHO is passive or active. Therefore, the study’s objectives are to identify the types of experiences and analyse the predictors of proactive practical experiences in solving COVID-19 among PHOs in the upper southern region of Thailand. Methods: An explanatory mixed-methods approach was used to collect data, through questionnaires and online in-depth interviews. The study was conducted from August 4, 2020, to August 3, 2021. Results: The results included 60 PHOs from 60 PCUs in 6 provinces, with 41 (68.3%) females and an average age of 35.57 years (SD = 11.61). The PHOs’ knowledge, understanding, and participation experience aspects were mostly proactive rather than passive. Factors that significantly predicted proactive practical experiences included sex (ORadj = 1.52, 95% CI = 1.04–2.21), age (ORadj = 1.69, 95% CI = 1.16-2.48), married status (ORadj = 1.69, 95% CI = 1.16-2.48), education level (ORadj = 1.50, 95% CI = 1.02–2.20), and position for work (ORadj = 1.69, 95% CI = 1.16-2.48). Conclusions: PHOs’ knowledge, understanding, opinion, and participation experiences were significant predictors of practical experience. Primary health care systems should promote proactive experiences in all four aspects to increase proactive practical experiences.

This article offers a theoretical framework to contextualise the concept of "Safety Culture" in the field of public safety and Disaster Risk Reduction (DRR), with the aim of supporting its understanding and measurement in our communities and finally attaining more disaster resilient societies. The work discusses the role of cultural dimensions in risk management and DRR and highlights the relevance of building knowledge and practices based on the consideration of culture and cultural variability in all phases of the risk management process. After an overview of the Safety Culture concept, including its origins, developments and applications, the text explores the transferability of this concept to the context of public safety. Then, based on the existing Safety Culture models, metrics and indicators from other sectors, the paper proposes an original definition of Safety Culture for the DRR context, shaped on a series of elements and dimensions specifically outlined for this context. Finally, the expected benefits of the application of Safety Culture concepts and techniques for further advances in DRR is discussed.

Older adults in low-and middle-income countries experience a disproportionate burden of non-communicable diseases (NCDs). Unintentional injuries are among the major NCDs, and falls are the second leading cause of these injuries and deaths worldwide, including in Thailand. We aimed to culturally adapt the CDC’s Stopping Elderly Accidents, Deaths, and Injuries (STEADI) for Thai older adults and explore the feasibility, appropriateness, and acceptability of using STEADI in primary care via trained community health workers (CHWs) and care managers (CMs). STEADI takes a coordinated care approach that consists of three steps: screening, assessing, and intervening. In Step a, CHWs screened fall risk in 20 community-dwelling older adults using three key questions and found that all of them had fall risk, then CHWs screened with a Stay Independent questionnaire (range 0-14) and found that 100% have high fall risk (total scores 9.7± 2.4). In Step b, CMs assessed balance, vision, footwear, postural hypotension, medications, and CHWs assessed home hazards. They found that 50% had poor balance, 70% took 4+ medications,75% fell on the walkway, and 70% had no bathroom modifications. In Step c, individual participants received fall prevention interventions to mitigate their specific fall risk factors. CHWs and CMs indicated high acceptability (19.20±.1.31 of 20 total), appropriateness (18.80± 1.79 of 20 total), and feasibility (18.60±1.67 of 20 total) of the Thai-STEADI intervention. Our study showed that the community-based multifactorial Thai-STEADI delivered by CHWs and CMs is feasible and acceptable to prevent falls in older adults with limited access to health care.

In the current socio-economic context, pension systems have become a crucial topic in the agenda of governments and international bodies. In this paper, an empirical study regarding the economic and social sustainability of pension systems in Central and Eastern European Countries was performed. The goal of the research is to establish the sustainability of pension systems with econometric modeling techniques on three dimensions as the research hypotheses are revealed: first, by strengthening the financial soundness of pension systems; second, consolidating the economic environment of pension systems; third, increasing the degree of social security systems with a direct effect of reducing poverty. The results led to relevant insights emphasizing the need for more inclusive economic, financial, and social reforms. From a policy perspective, these findings could be a starting point for the enhancement of the financial adequacy and economic and social sustainability of pension systems in Central and Eastern European Countries. The econometric techniques in this study highlight those modern pensions systems that need to be addressed in a more complex and empirical context that must encompass the main technical aspects. The conclusions suggest that in the future it needs judicial, economic, and social adjustments for the enhancement of the financial soundness of the pension systems.

Abstract This essay presents a real-world demonstration of the evidence-based science communication process, showing how it can be used to create scientific data visualizations for public audiences. Visualizing research data can be an important science communication tool. Maximizing its effectiveness has the potential to benefit millions of viewers. As with many forms of science communication, creators of such data visualizations typically rely on their own judgments and the views of the scientists providing the data to inform their science communication decision-making. But that leaves out a critical stakeholder in the communications pipeline: the intended audience. Here, we show the practical steps that our team - the Advanced Visualization Lab at the University of Illinois at Urbana-Champaign - has taken to shift towards more evidence-based practice to enhance our science communication impact. We do this using concrete examples from our work on two scientific documentary films, one on the theme of ‘solar superstorms’ and the other focusing on the black hole at the center of the Milky Way galaxy. We used audience research with each of these films to inform our strategies and designs. We describe how such research evidence informed our understanding of ‘what works and why’ with cinematic-style data visualizations for the public. We close the essay with our key ‘take home’ messages from this evidence-based science communication process.

A small proportion of health care users are recognised to use a significantly higher proportion of health system resources, largely due to systemic, inequitable access and disproportionate health burdens. These high-resource health system users are routinely characterised as older, with multiple comorbidities, and reduced access to adequate health care. Geographic trends also emerge, with more rural and isolated regions demonstrating higher rates of high-resource use than others. Despite known geographical discrepancies in health care access and outcomes, health policy and research initiatives remain focused on urban population centers. To alleviate mounting health system pressure from high-resource users, their characteristics must be better understood within the context in which it arises. To examine this, a scoping review was conducted to provide an overview of characteristics of high-resource users in rural and remote communities in Canada and Australia. In total, 21 papers were included in the review. Using qualitative thematic coding, primary findings characterised rural high-resource users as those of an older age; with increased comorbid conditions and condition severity; lower socioeconomic status; and elevated risk behaviours.

Childhood hygiene education has resulted in individuals engaging in hand washing and mask wearing to cope with COVID-19. Individuals can form sustainable development-related habits through childhood education.

The aim of this study was to investigate the spatio-temporal association between socio-economic deprivation and the incidence of COVID-19 and how this association changes through the seasons and due to the existence of restrictive public health measures. A retrospective observational study was conducted among COVID-19 cases that occurred in the Apulia region from 29 February 2020 to 31 December 2021, dividing the period into four phases with different levels of restrictions. A generalized estimating equations model was applied to test the independent effect of deprivation on the incidence rate of COVID-19, taking into account age, sex, and regional incidence rate as possible confounding effects and covariates such as season and levels of restrictions as possible modifying effects. The highest incidence rate was in areas with a Very High deprivation Index (DI) in winter (107.2 for 100,000 ab. ± 7.5), while in autumn, the highest Rate Ratio (RR) was estimated between Very High vs. Low DI (3.83, p<.001). During total lockdown, no RR between areas with different levels of DI was significant, while during soft lockdown, areas with Very High DI were more at risk than all other areas. The effects of social inequalities on incidence rate of COVID-19 change in as-sociation with the seasons and restrictions on public health. Disadvantaged areas showed a higher incidence rate of COVID-19 in the cold seasons and in the phases of soft lockdown.

Socioeconomic conditions and social attitudes are known to represent epidemiological determinants. Credible knowledge on socioeconomic driving factors of the COVID-19 epidemic is still incomplete. Based on a linear random effects regression, a predictive model is derived to estimate COVID-19 incidence in German rural districts from local socioeconomic factors and popularity of political parties in terms of their share of vote. Thereby, time series provided by Germany's public health institute (Robert Koch Institute) of weekly notified 7-day incidences per 100,000 inhabitants per district from the outset of the epidemic in 2020 up to December 1, 2021, have been used to construct the dependent variable. Local socioeconomic conditions including share of votes, retrieved from the Federal Statistical Office of Germany, have been used as potential risk factors. Popularity of the right-wing party Alternative for Germany (AfD) bears a considerable risk of increasing COVID-19 incidence both in terms of predicting the maximum incidences during three epidemic periods (alternatively, cumulative incidences over the periods are used to quantify the dependent variable) and in a time-continuous sense. Thus, districts with high AfD popularity rank on top in the time-average regarding COVID-19 incidence. The impact of the popularity of the Free Democrats (FDP) is markedly intermittent in the course of time showing two pronounced peaks in incidence but also occasional drops. A moderate risk emanates from popularities of the Green Party (GRÜNE) and the Christian Democratic Union (CDU/CSU) compared to the other parties with lowest risk level. Socioeconomic parameters like \emph{per capita} income, proportions of protection seekers and social benefit claimants, and educational level have negligible impact. To the contrary, incidence significantly increases with population density. In order to effectively combat the COVID-19 epidemic, public health policymakers are well advised to account for social attitudes and behavioural patterns reflected in local popularities of political parties, which are conceived as proper surrogates for these attitudes. Whilst causal relations between social attitudes and the presence of parties remain obscure, the political landscape in terms of share of votes constitutes at least viable predictive "markers" relevant for public health policy making.

Background. We aimed to assess the validity of the Mat-O-Covid Job Exposure Matrix (JEM) on SARS-CoV2 using compensation data from the French National Health Insurance compensation system for occupational-related COVID-19. Methods. Deidentified compensation data for occupational COVID-19 in France were obtained between August 2020 and August 2021. The acceptance was considered as the reference. Mat-O-Covid is an expert based French JEM on workplace exposure to SARS-CoV2. Bivariate and multivariate models were used to study the association between the exposure assessed by Mat-O-Covid and the reference, as well as the Area Under Curves (AUC), sensitivity, specificity, predictive values, and likelihood ratios. Results. In the 1140 cases included, there was a close association between the Mat-O-Covid index and the reference (p&lt;0.0001). The overall predictivity was good, with an AUC of 0.78 and an optimal threshold at 13 per thousand. Using Youden’s J statistic resulted in 0.67 sensitivity and 0.87 specificity. Both positive and negative likelihood ratios were significant: respectively 4.9 [2.4-6.4] and 0.4 [0.3-0.4]. Discussion. It was possible to assess Mat-O-Covid’s validity using data from the national compensation system for occupational COVID-19. Though further studies are needed, Mat-O-Covid exposure assessment appears to be accurate enough to be used in research.

Lattice and code cryptography can replace existing schemes such as Elliptic Curve Cryptography because of their resistance to quantum computers. In support of public key infrastructures, the distribution, validation and storage of the cryptographic keys is then more complex to handle longer keys. This paper describes practical ways to generate keys from physical unclonable functions, for both lattice and code based cryptography. Handshakes between client devices containing the PUFs and a server are used to select sets of addressable positions in the PUFs, from which streams of bits called seeds are generated on demand. The public and private cryptographic key pairs are computed from these seeds together with additional streams of random numbers. The method allows the server to independently validate the public key generated by the PUF, and act as a certificate authority in the network. Technologies such as High performance computing, and graphic processing units can further enhance security by preventing attackers to make this independent validation when only equipped with less powerful computers.

Let us all take a moment to talk, once again, about this new coronavirus pandemic that the world has been facing since November 2019 and about its global response. After a short period marked by the pandemic underestimation risk by most governments, the Western world went nuts and overreacted, most probably so as not to be accused of inaction. In many cases, the overall benefits of the chosen policies were not sufficiently questioned, which resulted in many side effects on global health .The medical motto “primum non nocere”, a moral principle everyone should at least consider following, was evidently not taken into account. It has been overlooked, and the virus has become an obsession, to the extent that nearly everything else, even the most valuable things in life, is still now under appreciated if not simply ignored. This review highlighted facts against this simplistic, one-dimensional view.