Spatial Scale and Modeling Disease Transmission Risk: The Case of Malaria in sub-Saharan Africa and the Kenya Highlands

Open Access
Elliott, Laura Marie
Area of Honors:
Bachelor of Science
Document Type:
Thesis Supervisors:
  • Roger Michael Downs, Thesis Supervisor
  • Roger Michael Downs, Honors Advisor
  • Robert George Crane, Faculty Reader
  • malaria
  • Kenya
  • Kenya highlands
Students in introductory courses in plant pathology, public health, and immunology recognize the disease triangle and epidemiologic triad as conceptual models detailing the necessary components for presence of disease – a susceptible host, an infectious pathogen, and a conducive environment. A rich subset of the literature deals with “modifications” of these basic models, and, today, advanced spatial and mathematical models operate on the same principles as do the triad and triangle. As understanding of the precise mechanisms involved in the occurrence of multiple diseases improves, a challenge in the use of advanced models in predictive efforts has been the incorporation of the “complexity” of disease dynamics. Sub-Saharan Africa is a focal point in literature on studies of disease transmission. Moreover, as exemplified by recent “debates” in published work, the “re-emergence” of malaria in the previously “malaria-free” East African highlands is a prime example of the “complexity” of disease. This thesis develops a conceptual model for understanding disease transmission risk through an expansion of Grulke’s modification of the classic disease triangle model. This “modified Grulke model” (MGM) is applied to gain insight into malaria transmission risk for the region of sub-Saharan Africa (SSA), and, within the region of the Kenya highlands, for Kericho, a site of much discussion and debate in recent literature. Although questions still remain regarding malaria transmission risk in these areas, the MGM seeks a step forward in understanding the complex impacts and interactions of risk factors.