Relationships Between Meteorological Factors and Mongolian Gerbils and Its Flea Burdens - Xilingol League, Inner Mongolia Autonomous Region, China, 2012-2021.

China CDC Wkly

National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.

Published: June 2024

Introduction: Plague is a significant global infectious disease, its spread is linked to host and flea populations. Meteorological conditions can impact flea populations and host densities, hence influencing plague outbreaks. Investigating the connection between meteorological factors, flea populations, and rodent densities in Inner Mongolia's natural plague foci can aid in predicting and managing plague outbreaks.

Methods: Monthly data on flea index, rodent density, meteorological factors, and normalized difference vegetation index (NDVI) were collected for the study area. Generalized additive modeling (GAM) was used to analyze the non-linear and lag effects of meteorological factors on flea index and rodent density. Structural equation modeling (SEM) was employed to investigate the relationships among meteorological factors, NDVI, flea index, and rodent density.

Results: GAM analysis revealed that temperature, precipitation, relative humidity, and NDVI had significant linear, non-linear, and time-lagged impacts on the density of Mongolian gerbils and the flea index. SEM analysis indicated that meteorological factors could directly influence the density and flea index of Mongolian gerbils, or indirectly impact NDVI, subsequently influencing gerbil density and the flea index.

Conclusions: Meteorological factors primarily influence gerbil density and flea index indirectly by affecting NDVI and the relationship between flea index and gerbil density. This study offers additional support for the significance of meteorological factors and NDVI in influencing the vector-rodent system, offering valuable insights for predicting and managing plague outbreaks.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11196875PMC
http://dx.doi.org/10.46234/ccdcw2024.107DOI Listing

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