Objectives: The impact of COVID-19 in metropolitan areas has been extensively studied. The geographic spread to smaller cities is of great concern and may follow hierarchical influence of urban centers. With that in mind, we investigated factors that affect vulnerability of inner municipalities in São Paulo State, Brazil, an area with 24 million inhabitants. Methods: Surveillance data for confirmed COVID-19 cases and admissions for severe acute respiratory disease (SARD) up to April 18^th were recorded for each of 604 municipalities that lay outside São Paulo metropolitan area. Vulnerability was assessed in Multivariable models, including sociodemographic indexes, road distance to the State Capital and the municipalities classification proposed by the Brazilian Institute of Geography and Statistics. Municipalities of great regional relevance were used as reference category for that classification. The outcome of interest for Cox regression was having COVID-cases, with time counting from the first report in São Paulo State. For binomial negative regression models, the outcomes of interest were rates of confirmed COVID-19 cases and admissions for SARD.Results: A total of 198 (32.8%) municipalities had autochthonous COVID-19 cases. In Cox models, affected municipalities were likely to have greater population density (Hazard Ratio[HR] for each 100 inhabitants per square kilometer, 1.07; 95% Confidence Interval [CI], (1.05-1.10)), proportion of inhabitants in urban area (HR, 1.02; 95%CI, 1.00-1.04), higher human development index (HDI, HR for 1%, 1.06; 95%CI, 1.00-1.13) and Gini Index for Inequality of income (HR for 1%, 1.04, 95% CI, 1.00-1.07). On the other hand, distance from the Capital was protective (HR for each 100Km, 0.82; 95%CI, 0.74-0.90). The HR95%[95%CI] also varied negatively according to the categories of influence of major centers (0.41 [0.22-0.77], 0.16 [0.09-0.32], 0.07 [0.03-0.15]). The binomial negative regression models for COVID-19 incidence also detected positive association with population density (Incidence Rate Ratio[IRR], 1.13; 95%CI, 1.07-1.18) and proportion of urban population (IRR, 1.04; 95%CI, 1.01-1.05), protection for cities distant to the Capital (IRR=0.73; 95%CI, 0.68-0.81) and increasing negative association for categories of influence (0.19 [0.09-0.42], 0.07 [0.03-0.15] and 0.03 [0.02-0.08]). Similar findings were detected when we used SARD incidence as outcome.Conclusion: Municipalities with greater population, density and regional influence were more likely to be affected earlier and more intensely by COVID-19. Non-pharmacological measures should be strengthened in those areas of greater risk.

The reserves of water, which is one of the most important requirements for human life, gradually decreases under current conditions and rapidly depletes despite being one of the renewable resources. Considering the global water reserves, it became imperative to implement measures to protect the anticipated water reserves. The fact that the amount of quality water per capita decreases every day in the world and the increasing competition in water management could be considered among the indicators of the above-mentioned case. In recent years, as the effects of this adversity became increasingly more evident, several sustainable methods were adopted all over the world such as rain gardens and rainwater storage facilities. These sustainable techniques could be observed in many areas, especially in urban centers. In the present study, the area with the highest water collection was determined at Karadeniz Technical University Kanuni Campus and identified as the study area. Precipitation per square meter and surface runoff volume were identified based on the GIS (Geographic Information System) data, annual water collection volume was calculated, and information on economic and ecological recycling of the water was provided. In conclusion, the precipitation data for 11 years were compared, and it was calculated that the average annual precipitation was 64.06 kg/m² and annual surface runoff water was 552.77 m³. Based on the surface runoff water volume in the months when no irrigation is conducted, a reservoir was designed under the vehicle road and water recycling recommendations were developed.

Numerous Epidemiologic studies have used remote sensing to quantify the contribution of greenness, air pollution, and wildfire smoke to asthma and other respiration outcomes. This is the first review paper to evaluate the influence of remote sensing exposures to specific outcome severity and risk factors in different ecologic settings. Literature searches utilizing PubMed and Google Scholar identified 61 unique studies published between 2009-2023, with 198 specific outcomes. Respiration specific outcomes were lower in greenness, and higher in air pollution, and in wildfire ecologic settings. Aerosol optical depth (AOD)-PM2.5 readings and specific outcomes were higher in economically developing than in economically developed countries. Prospective studies found prenatal and infant exposure to higher ambient AOD-PM2.5 concentration level readings contributed to higher childhood asthma incidence. Lung function was higher in greenness, and lower in the other two ecologic settings. Age, environment, gender, other, and total risk factors showed significant differences between health outcomes and ecologic settings. Published studies utilized physiologic mechanisms of immune, inflammation, and oxidative stress to describe obtained results. Individual and total physiologic mechanisms differed between ecologic settings. Study results were used to develop a descriptive physiologic asthma model and then use it to propose updated population-based asthma intervention program guidelines.