Remote sensing-based time series models for malaria early warning in the highlands of Ethiopia.

Malaria Journal
Alemayehu MidekisaMichael C Wimberly

Abstract

Malaria is one of the leading public health problems in most of sub-Saharan Africa, particularly in Ethiopia. Almost all demographic groups are at risk of malaria because of seasonal and unstable transmission of the disease. Therefore, there is a need to develop malaria early-warning systems to enhance public health decision making for control and prevention of malaria epidemics. Data from orbiting earth-observing sensors can monitor environmental risk factors that trigger malaria epidemics. Remotely sensed environmental indicators were used to examine the influences of climatic and environmental variability on temporal patterns of malaria cases in the Amhara region of Ethiopia. In this study seasonal autoregressive integrated moving average (SARIMA) models were used to quantify the relationship between malaria cases and remotely sensed environmental variables, including rainfall, land-surface temperature (LST), vegetation indices (NDVI and EVI), and actual evapotranspiration (ETa) with lags ranging from one to three months. Predictions from the best model with environmental variables were compared to the actual observations from the last 12 months of the time series. Malaria cases exhibited positive associations with LST at a ...Continue Reading

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Citations

Nov 1, 2013·International Journal of Environmental Research and Public Health·Michael C WimberlyMichael B Hildreth
Jan 10, 2014·Malaria Journal·Divya Subash KumarMada Suresh Venkatesan
Dec 9, 2015·Environmental Modelling & Software : with Environment Data News·Yi LiuMichael C Wimberly
Aug 7, 2012·Tropical Medicine & International Health : TM & IH·Michael C WimberlyGabriel B Senay
Feb 6, 2015·Water Resources Research·Alemayehu MidekisaMichael C Wimberly
Jun 25, 2015·Parasites & Vectors·Alemayehu MidekisaMichael C Wimberly
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Software Mentioned

SAS
SARIMA
ArcGIS

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