PUBLICATION: Global Health Action
Yé, Y., Hoshen, M., Kyobutungi, C., Louis, V.R., & Sauerborn, R.
Background: To support malaria control strategies, prior knowledge of disease risk is necessary. Developing a
model to explain the transmission of malaria, in endemic and epidemic regions, is of high priority in
developing health system interventions. We develop, fit and validate a non-spatial dynamic model driven by
meteorological conditions that can capture seasonal malaria transmission dynamics at the village level in a
malaria holoendemic area of north-western Burkina Faso.
Methods: A total of 676 children aged 659 months took part in this study. Trained interviewers visited
children 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.
Results: The overall P. falciparum malaria infection incidence was 1.1 episodes per person year. There was
strong seasonal variation in P. falciparum malaria infection incidence with a peak observed in August and
September, corresponding to the rainy season and a high number of mosquitoes. The model estimates of
monthly mosquito abundance and the incidence of malaria infection correlated well with observed values. The
fit was sensitive to daily mosquito survival and daily human parasite clearance.
Conclusion: The model has demonstrated 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 managers in identifying high-risk periods for more
Catherine holds a PhD (2006) in Epidemiology from the University of Heidelberg, and a Master of Science (2002) in Community Health and Health Management. She is the Executive Director at the African Population and Health Research...