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Generation of Dynamical Environmental Conditions using a High-Throughput Microfluidic Device
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Decoupling environmental effects and host population dynamics for anthrax, a classic reservoir-driven disease
Juan Pablo Gomez1,2,3, Dawn M Nekorchuk1,2,4, Liang Mao2
1Spatial Epidemiology and Ecology Research Laboratory, Department of Geography, University of Florida, Gainesville, Florida, United States of America.
Plos One
|December 13, 2018
Summary
Environmental factors, not host population dynamics, drive anthrax outbreaks. Seasonal variations in the force of infection are key to predicting disease intensity and potential losses in wildlife and livestock.
Area of Science:
- Ecology
- Epidemiology
- Mathematical Modeling
Background:
- Quantitative disease transmission models often overlook environmental influences on outbreaks.
- Understanding the interplay between host population dynamics and environmental factors is crucial for predicting disease spread.
Purpose of the Study:
- To investigate how external factors and host population dynamics interact to influence indirectly transmitted disease outbreaks.
- To model the independent contribution of recruitment and environment to the force of infection.
Main Methods:
- Developed deterministic and stochastic compartmental models for anthrax, parameterized with literature and field data.
- Modeled the force of infection as a pure birth process influenced by pathogen dispersion and seasonal environmental variables.
- Utilized simulations and a maximum likelihood framework to analyze disease dynamics and estimate outbreak parameters.
Main Results:
- Anthrax disease dynamics in grasslands are decoupled from host population dynamics.
- Seasonal environmental forcing, rather than host reproductive events, dictates outbreak occurrence.
- Pathogen dispersion's role in disease persistence varies significantly between epizootic and endemic years.
Conclusions:
- Environmental variables are critical determinants of anthrax outbreak intensity.
- The model can aid in predicting future outbreaks, mitigating losses in wildlife and livestock.
- Seasonal variations in the force of infection are essential for realistic disease transmission modeling.
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