PreprintArticleVersion 1This version is not peer-reviewed
Identifying the Drivers Related to Animal Reservoirs, Environment, and Socio-demography of Human Leptospirosis in Different Community types of Southern-Chile: A One Health Perspective
Version 1
: Received: 18 July 2024 / Approved: 19 July 2024 / Online: 19 July 2024 (11:57:43 CEST)
How to cite:
Talukder, H.; Munoz-Zanzi, C.; Salgado, M.; Berg, S.; Yang, A. Identifying the Drivers Related to Animal Reservoirs, Environment, and Socio-demography of Human Leptospirosis in Different Community types of Southern-Chile: A One Health Perspective. Preprints2024, 2024071593. https://doi.org/10.20944/preprints202407.1593.v1
Talukder, H.; Munoz-Zanzi, C.; Salgado, M.; Berg, S.; Yang, A. Identifying the Drivers Related to Animal Reservoirs, Environment, and Socio-demography of Human Leptospirosis in Different Community types of Southern-Chile: A One Health Perspective. Preprints 2024, 2024071593. https://doi.org/10.20944/preprints202407.1593.v1
Talukder, H.; Munoz-Zanzi, C.; Salgado, M.; Berg, S.; Yang, A. Identifying the Drivers Related to Animal Reservoirs, Environment, and Socio-demography of Human Leptospirosis in Different Community types of Southern-Chile: A One Health Perspective. Preprints2024, 2024071593. https://doi.org/10.20944/preprints202407.1593.v1
APA Style
Talukder, H., Munoz-Zanzi, C., Salgado, M., Berg, S., & Yang, A. (2024). Identifying the Drivers Related to Animal Reservoirs, Environment, and Socio-demography of Human Leptospirosis in Different Community types of Southern-Chile: A One Health Perspective. Preprints. https://doi.org/10.20944/preprints202407.1593.v1
Chicago/Turabian Style
Talukder, H., Sergey Berg and Anni Yang. 2024 "Identifying the Drivers Related to Animal Reservoirs, Environment, and Socio-demography of Human Leptospirosis in Different Community types of Southern-Chile: A One Health Perspective" Preprints. https://doi.org/10.20944/preprints202407.1593.v1
Abstract
Leptospirosis is a zoonosis with global public health impact, particularly in poor socio-economic settings of tropical regions. Transmitted through urine-contaminated water or soil from rodents, dogs, and livestock, leptospirosis causes over a million clinical cases annually. Risk factors include outdoor activities, livestock production, and substandard housing that foster high densities of animal reservoirs. This One Health study in southern Chile examined Leptospira serological evi-dence of exposure people from urban slums, semi-rural, and farm settings, using the Extreme Gradient Boosting algorithm to identify key influencing factors. In urban slums, age, shrub terrain, distance to Leptospira-positive households, and neighborhood housing density were contributing factors. Human exposure in semi-rural communities was linked to environmental factors (tree, shrub, and lower vegetation terrain) and animal variables (Leptospira-positive dogs and rodents, and proximity to Leptospira-positive households). On farms, dog counts, animal Leptospira preva-lence, and proximity to Leptospira-contaminated water samples were significant drivers. The study underscores that disease dynamics vary across landscapes, with distinct drivers in each community setting. This case study demonstrates how the integration of machine learning with comprehensive cross-sectional epidemiological and geospatial data provides valuable insights into leptospirosis eco-epidemiology. These insights are crucial for informing targeted public health strategies and for generating hypotheses for future research.
Keywords
Leptospirosis; Communities; One Health; Extreme Gradient Boosting; Eco-epidemiology
Subject
Public Health and Healthcare, Public, Environmental and Occupational Health
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
