2010 Articles

Simulating malaria transmission dynamics in the pilot areas of the Colombian Integrated National Adaptation Pilot project - First part: Malaria transmission models

Ruiz, D.; Molina, A. M.; Gutierrez, M. E.; Lopez, C.; Quinones, M. L.; Jimenez, M. M.; Thomson, M.; Connor, S.

The history of malaria mathematical modeling is reaching now more than a hundred years. In the first decade of the past century, Sir Ronald Ross, the British physician who first succeeded in demonstrating the life-cycle of malaria parasites in Anopheles mosquitoes, proposed the first mathematical approach for the study of malaria epidemiology. This tool, which was later revised and complemented by the British malariologist George Macdonald in the mid 1950s, provided valuable insights into the determinants of malaria transmission. The now referred to as the Ross-Macdonald model (see section 1.1, this chapter) is considered the basis of much of the epidemiological understanding of vector-borne diseases. A long list of dynamical models, each of them with a different level of complexity, can be cited in the recent history of malaria mathematical modeling. Most of them follow the traditional SIR (susceptible, infectious and recovered hosts) or SEIR (susceptible, infected, infectious, and recovered hosts) structures for the representation of malaria spread. Dynamical models can be used to analyze the general epidemiology of the disease (e.g. understand the role of climatic and non-climatic drivers); compare simulation outputs with actual malaria morbidity profiles observed in several endemic/epidemic- prone regions; simulate several changing epidemiological scenarios, to assess the effects of global warming and future changes in local climatic and socioeconomic conditions on malaria transmission; simulate the impact of control interventions; conduct stability analysis; and finally, stimulate an interactive learning environment.