A stochastic multi-host model for West Nile virus transmission

Area of Science:

• Epidemiology
• Mathematical Biology
• Ecology

Background:

• Enzootic diseases like West Nile Virus (WNV) can either die out or cause major outbreaks upon introduction into a new population.
• Predicting disease emergence requires understanding transmission dynamics within ecological communities.

Purpose of the Study:

• To develop a mathematical model predicting WNV extinction probability based on the initial introduction source.
• To investigate how host-vector interactions and community composition influence WNV transmission and extinction risk.

Main Methods:

• Utilized a Continuous-Time Markov Chain model to simulate WNV transmission between two avian host species and one vector.
• Applied multitype branching process theory to calculate extinction probabilities based on the initial infectious or exposed state of introduced individuals (vector or host).
• Compared theoretical model predictions with results from stochastic simulations.

Main Results:

• The probability of WNV extinction is significantly influenced by the specific type of individual (exposed vector, infectious vector, or infectious host) that initially introduces the virus.
• Disease extinction likelihood is sensitive to host species' WNV transmission competence, vector biting rates, and the relative abundance of hosts and vectors.
• Community composition (hosts and vectors) and the mode of disease introduction are critical determinants of WNV extinction probability.

Conclusions:

• The initial introduction pathway and the ecological community structure are crucial factors determining the fate of WNV in a population.
• Mathematical modeling provides valuable insights into disease dynamics and extinction probabilities, aiding in predicting potential outbreaks.