Spatial patterns of spread of dengue with human and vector mobility

Abstract

Dengue is a vector borne disease transmitted to humans by {\it{Aedes Aegypti}} mosquitoes carrying Dengue virus of different serotypes. Primarily an urban epidemic, Dengue exhibits complex spatial and temporal dynamics, influenced by many biological, human and environmental factors. However, most of the existing models neglect the spatial factors influencing the spread of Dengue. This work sheds light on how Dengue parameters and human mobility changes the spatial spread of the infection and size of the epidemic. We model the Dengue as a stochastic Cellular Automata (CA) process following Susceptible, Exposed, Infected, Recovered (SEIR) -Susceptible, Exposed, Infected (SEI)- for human and vector dynamics respectively in each cell, and analyze the spatial and temporal spreading disease using parameters from field studies. We use the data on mosquito density from Ahmedabad city of India as input to our model to predict the dynamics of Dengue incidence and compare it to the reported data on the prevalence of the disease from 2006-2012. We find that for certain infection rates, CA model closely reproduces observed peaks and intensity. We used data based statistical models of human mobility such as exponential step length and super diffusive L\'evy flight to study mobility effects on Dengue spreading within the city. We find an interesting result that inclusion of human mobility in many cases can decrease the incidence of Dengue, and may suppress the infection completely. The scale and intensity of reduction depend on the relative strengths of infection transmission rate and mobility step length. The primarily reason for decline can be attributed to the significant fraction of the susceptible and exposed population moving to the regions where majority have already recovered and can no longer be infected.