Seven Challenges for Spatial Analyses of Vector-Borne Diseases

Abstract

Prediction of spatial heterogeneity in disease incidence based on measurable spatial factors is a major goal of spatial epidemiology. There are a number of applied goals of these predictions, including appropriately targeting resources for surveillance and intervention and accurately quantifying disease burden. Although spatial heterogeneity is evident in the epidemiology of many diseases, several aspects of the biology of vector-borne diseases amplify this form of heterogeneity. Here, we review several aspects of this biology, highlighting seven distinct ways in which the biology of vector-borne diseases impacts understanding spatial heterogeneity in disease incidence. Whereas traditional methods place emphasis on spatial regression and other forms of statistical analysis of empirical data, the goal here is to offer a perspective on potential pitfalls of analyses that take data at face value and do not acknowledge the complex, nonlinear, and dynamic relationships between spatial patterns of disease incidence and spatial heterogeneity in transmission.