Development and validation of climate and ecosystem-based early malaria epidemic prediction models in East Africa
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Date
2014Author
Githeko, Andrew K
Ogallo, Laban
Lemnge, Martha
Okia, Michael
Ototo, Ednah N
Language
enMetadata
Show full item recordAbstract
Background: Malaria epidemics remain a serious threat to human populations living in the highlands of East Africa
where transmission is unstable and climate sensitive. An existing early malaria epidemic prediction model required
further development, validations and automation before its wide use and application in the region. The model has
a lead-time of two to four months between the detection of the epidemic signal and the evolution of the epidemic.
The validated models would be of great use in the early detection and prevention of malaria epidemics.
Methods: Confirmed inpatient malaria data were collected from eight sites in Kenya, Tanzania and Uganda for the
period 1995-2009. Temperature and rainfall data for the period 1960-2009 were collected from meteorological stations
closest to the source of the malaria data. Process-based models were constructed for computing the risk of an
epidemic in two general highland ecosystems using temperature and rainfall data. The sensitivity, specificity and
positive predictive power were used to validate the models.
Results: Depending on the availability and quality of the malaria and meteorological data, the models indicated good
functionality at all sites. Only two sites in Kenya had data that met the criteria for the full validation of the models. The
additive model was found most suited for the poorly drained U-shaped valley ecosystems while the multiplicative
model was most suited for the well-drained V-shaped valley ecosystem. The +18°C model was adaptable to any of the
ecosystems and was designed for conditions where climatology data were not available. The additive model scored
100% for sensitivity, specificity and positive predictive power. The multiplicative model had a sensitivity of 75%
specificity of 99% and a positive predictive power of 86%.
C o n c lu s i o n s : The additive and multiplicative models were validated and were shown to be robust and with high
climate-based, early epidemic predictive power. They are designed for use in the common, well- and poorly
drained valley ecosystems in the highlands of East Africa.
Ke y w o r d s : Malaria, Epidemic prediction, Models, Africa
Citation
Githeko, A. K., Ogallo, L., Lemnge, M., Okia, M., & Ototo, E. N. (2014). Development and validation of climate and ecosystem-based early malaria epidemic prediction models in East Africa. Malaria Journal, 13, 329. doi:10.1186/1475-2875-13-329Publisher
University of Nairobi