Models of infectious diseases in spatially heterogeneous environments

Bull Math Biol. 2001 May;63(3):547-71. doi: 10.1006/bulm.2001.0231.

Abstract

Most models of dynamics of infectious diseases have assumed homogeneous mixing in the host population. However, it is increasingly recognized that heterogeneity can arise through many processes. It is then important to consider the existence of subpopulations of hosts, and that the contact rate within subpopulations is different than that between subpopulations. We study models with hosts distributed in subpopulations as a consequence of spatial partitioning. Two types of models are considered. In the first one there is direct transmission. The second one is a model of dynamics of a mosquito-borne disease, with indirect transmission, and applicable to malaria. The contact between subpopulations is achieved through the visits of hosts. Two types of visit are considered: a first one in which the visit time is independent of the distance travelled, and a second one in which visit time decreases with distance. There are two types of spatial arrangement: one dimensional, and two dimensional. Conditions for the establishment of the disease are obtained. Results indicate that the disease becomes established with greater difficulty when the degree of spatial partition increases, and when visit time decreases. In addition, when visit time decreases with distance, the establishment of the disease is more difficult when the spatial arrangement is one dimensional than when it is two dimensional. The results indicate the importance of knowing the spatial distribution and mobility patterns to understand the dynamics of infectious diseases. The consequences of these results for the design of public health policies are discussed.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Communicable Diseases / epidemiology
  • Communicable Diseases / transmission*
  • Culicidae / growth & development
  • Disease Transmission, Infectious*
  • Humans
  • Insect Vectors
  • Malaria / epidemiology
  • Malaria / transmission
  • Models, Biological*
  • Public Health*