Using Meteorologically Based Dynamic Model to Assess Malaria Transmission Dynamic Among Under Five Children in an Endemic Region

Ye Yazoume, African Population and Health Research Center (APHRC)
Catherine Kyobutungi, African Population and Health Research Center (APHRC)
Hoshen Moshe, Hebrew University of Jerusalem

We develop, fit and validate a non-spatial dynamic malaria transmission model driven by meteorological conditions. 676 children aged 6-59 months were visited at home weekly from December 2003 to November 2004 for Plasmodium falciparum malaria infection detection. Anopheles daily biting rate, mortality rate and growth rate were evaluated. Digital meteorological stations measured ambient temperature, humidity and rainfall in each site. Malaria infection incidence was 1.1 episodes per person year. There was a strong seasonal variation of the Malaria infection incidence. The model estimate of monthly mosquito abundance and the incidence of malaria infection correlate well with observed values. The model has shown a potential for local scale seasonal prediction of P falciparum malaria infection. It could therefore be used to understand malaria transmission dynamics using meteorological parameters as the driving force and to help district health in identifying the risk period for more focused interventions.