Impact of Seasonal Conditions on Vector-Borne Epidemiological Dynamics

Abstract

Vector-borne diseases such as malaria, dengue fever, West Nile virus, and so forth are some of the most prominent threats to human health. They are transmitted to the human population by infected insects or by direct transmission between humans. The epidemic process relies on suitable environmental and climatic conditions. Indeed, climatic factors affect the development of pathogens in vectors as well as the population dynamics of the vectors impacting significantly the incidence of disease in the human population. While the influence of the climatic conditions on Vector-borne diseases is well-documented, there is a strong need to design more realistic epidemiological models incorporating environmental features that show a close relationship with the epidemic process observed in the human population. Indeed, classical models concentrate either on the climatic influence on the vector population dynamics or on the connectivity patterns of the host population, loosing the full picture of the epidemic process dynamics. Inspired by real data of infectious diseases, a Seasonal Susceptible-Infected-Recovered (Seasonal SIR) epidemiological model is developed and analyzed. The proposed model incorporates the influence of the temperature variations together with the heterogeneous structure of the human interaction network on the spreading process of vector-borne diseases. Simulations are performed in order to get a better understanding of the climate variations and of the heterogeneous nature of the contact network on the transmission dynamics. Results show that failing to incorporate these features on the model can lead to a poor estimation of the maximum fraction of infected individuals in the host population. Furthermore there is a serious influence on the time needed to reach this maximum. The Seasonal SIR model proves to finely model the dynamics of outbreaks observed in real-world situations. It provides a basis for more effective predictions of disease outbreaks that can be used in order to implement appropriate control measures to contain epidemics.

Keywords

• Vector-borne diseases
• epidemics
• heterogeneous contact network
• climate variations
• dynamics on networks
• SIR model