Related Experiment Video
Updated: Jun 22, 2025

Author Spotlight: Establishing a Rodent Model for Investigating Depression Factors in Traditional Mongolian Medicine
Published on: October 27, 2023
Relationships Between Meteorological Factors and Mongolian Gerbils and Its Flea Burdens - Xilingol League, Inner
Ke Li1, Zhenxu Wang1, Xiaohui Wei1,2
1National 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.
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.
Insights
Meteorological factors indirectly impact plague outbreaks by influencing rodent and flea populations, primarily through vegetation changes. Understanding these links is key for predicting and controlling the spread of this infectious disease.
Area of Science:
- Ecology
- Epidemiology
- Environmental Science
Background:
- Plague outbreaks are influenced by host and flea populations.
- Meteorological conditions affect flea populations and host densities, impacting disease spread.
- Inner Mongolia's natural plague foci require investigation into these ecological dynamics.
Purpose of the Study:
- To investigate the relationship between meteorological factors, flea populations, and rodent densities in Inner Mongolia.
- To understand how environmental variables influence the vector-rodent system related to plague.
- To provide insights for predicting and managing plague outbreaks.
Main Methods:
- Collected monthly data on flea index, rodent density, meteorological factors, and NDVI.
- Utilized Generalized Additive Modeling (GAM) for non-linear and lagged effects analysis.
- Employed Structural Equation Modeling (SEM) to explore interrelationships between variables.
Main Results:
- Meteorological factors (temperature, precipitation, humidity) and NDVI significantly impacted Mongolian gerbil density and flea index, with linear, non-linear, and lagged effects.
- SEM showed meteorological factors influence gerbil density and flea index directly and indirectly via NDVI.
- Meteorological factors primarily affect the vector-rodent system indirectly through NDVI and the flea-rodent relationship.
Conclusions:
- Meteorological factors and NDVI play a crucial role in the vector-rodent dynamics of plague.
- Environmental influences on vegetation (NDVI) are key mediators in the relationship between weather, rodents, and fleas.
- Findings offer valuable insights for the prediction and management of plague outbreaks.

