Managing Malaria ; an evolutionary modelling approach
As the resistance of the malaria parasite to antimalarial drugs continues to increase, like the malarial mosquito to insecticides, the efficacy of efforts to control malaria in many tropical countries is diminishing. This trend, together with the projected consequences of climate change, could prove to substantially exacerbate the significance of malaria in the coming decades.
Using an evolutionary modelling approach to simulate the adaptation of mosquitoes and parasites to the available insecticides and drugs, the so-called "genetic algorithms" were coupled with a dynamic malaria-epidemiological model. In doing so a complex adaptive system was derived, capable of simulating adaptive and evolutory processes in both the mosquito and the parasite populations. A thorough sensitivity analysis of the development of resistance addressed the impact of migration of susceptible mosquitoes and parasites, various coverage rates of insecticides and drugs, and the level of initial resistance.
Furthermore, the impact of temperature change on the occurrence of malaria is investigated. The results suggest that from the sensitivity analysis the adequate use of insecticides and drugs could reduce the occurrence of malaria in regions of low endemicity, although increased efforts would be necessary in the event of a climate change. However, the model indicates that in regions of high endemicity the use of insecticides and drugs may lead to an increase in incidence due to enhanced resistance development. Projected climate change, on the other hand, may lead to a limited reduction of the occurrence of malaria due to the presence of a higher percentage of immune persons in the older age class.
Elements of a sustainable antimalarial policy in regions of high endemicity will probably need to fall back on a stimulation of socio-economic development and provision of vector-proof housing. The modelling approach presented here is very well tuned to the current focus on the importance of evolutionary principles in health science. Therefore this modelling approach is expected to be applied to a wider range of diseases, for example, TBC and Multi-Resistant Staphylococcus Aureus (MRSA) to support decision- making in health care.
|Author(s)||Janssen MA ; Martens WJM|