Farida Adimi, Radina P
Soebiyanto, Najibullah Safi and Richard Kiang
Abstract
Background: Malaria is a
significant public health concern in Afghanistan. Currently, approximately 60%
of the population, or nearly 14 million people, live in a malaria-endemic area.
Afghanistan's diverse landscape and terrain contributes to the heterogeneous
malaria prevalence across the country. Understanding the role of environmental variables
on malaria transmission can further the effort for malaria control programme.
Methods: Provincial
malaria epidemiological data (2004-2007) collected by the health posts in 23
provinces were used in conjunction with space-borne observations from NASA
satellites. Specifically, the environmental variables, including precipitation,
temperature and vegetation index measured by the Tropical Rainfall Measuring
Mission and the Moderate Resolution Imaging Spectoradiometer, were used.
Regression techniques were employed to model malaria cases as a function of
environmental predictors. The resulting model was used for predicting malaria
risks in Afghanistan. The entire time series except the last 6 months is used
for training, and the last 6-month data is used for prediction and validation.
Results: Vegetation index,
in general, is the strongest predictor, reflecting the fact that irrigation is
the main factor that promotes malaria transmission in Afghanistan. Surface
temperature is the second strongest predictor. Precipitation is not shown as a
significant predictor, as it may not directly lead to higher larval population.
Autoregressiveness of the malaria epidemiological data is apparent from the
analysis. The malaria time series are modelled well, with provincial average R2
of 0.845. Although the R2 for prediction has larger variation, the total
6-month cases prediction is only 8.9% higher than the actual cases.
Conclusions: The provincial
monthly malaria cases can be modelled and predicted using satellite-measured environmental
parameters with reasonable accuracy. The Third Strategic Approach of the WHO
EMRO Malaria Control and Elimination Plan is aimed to develop a cost-effective
surveillance system that includes forecasting, early warning and detection. The
predictive and early warning capabilities shown in this paper support this
strategy.
Malaria Journal 2010, 9:125
Malaria Journal 2010, 9:125
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