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  • Oral presentation
  • Open Access

Modeling the effects of vector control interventions in reducing malaria transmission, morbidity and mortality

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Malaria Journal20109 (Suppl 2) :O7

  • Published:


  • Malaria
  • Malaria Transmission
  • Indoor Residual Spray
  • Malaria Prevalence
  • Malaria Intervention

Malaria interventions are usually prioritized using efficacy estimates from intervention trials, without considering the context of existing intervention packages or long-term dynamics. We use numerical simulation of mathematical models of malaria in humans and mosquitoes to provide robust quantitative predictions of effectiveness of different strategies in reducing transmission, morbidity and mortality.

We can simulate indoor residual spraying (IRS) and insecticide-treated nets (ITNs), used singly and in combination with each other and with other interventions such as improved case management, intermittent preventive treatment (IPT). We can estimate reductions in entomological inoculation rate (EIR), clinical cases, prevalence and malaria deaths from simulations of different coverage levels ITNs and IRS with different properties, and at different transmission and health system settings.

Our results suggest that sustained coverage of one or two interventions reduces malaria prevalence in two to three years but does not lead to further gains (Figure 1). However, in some settings, even with sustained coverage, clinical incidence of malaria increases as the population loses its naturally acquired immunity. In some low to medium transmission settings, our simulations suggest that high coverage of both interventions can lead to interruption of transmission.
Figure 1
Figure 1

Model predictions of the effect of IRS with DDT on malaria prevalence. We assume two annual IRS DDT spray rounds (each with 95% coverage) for 12 years; simulations are of 1000 humans exposed to seasonal transmission based on a Tanzanian setting, with an initial EIR of 320 infectious bites per person per annum. The blue line is the median prevalence from four runs of each of 15 different model paramerizations for malaria in humans; grey area: interquartile range; dashed lines: maxima and minima.

Authors’ Affiliations

Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, P.O. Box, CH-4002, Basel, Switzerland
University of Basel, P.O. Box, CH-4003, Basel, Switzerland
MACEPA-PATH, 01210 Ferney Voltaire, France


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© Boutsika et al; licensee BioMed Central Ltd. 2010

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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