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

2012136 citationsJournal Articlegold Open Access

Authors

Alemayehu Midekisa · South Dakota State University

G. B. Senay · United States Geological Survey

Geoffrey M. Henebry · South Dakota State University

Paulos Semuniguse · Ethiopian Public Health Association

Michael C. Wimberly · South Dakota State University

Abstract

Malaria risk indicators such as satellite-based rainfall estimates, LST, EVI, and ETa exhibited significant lagged associations with malaria cases in the Amhara region and improved model fit and prediction accuracy. These variables can be monitored frequently and extensively across large geographic areas using data from earth-observing sensors to support public health decisions.

Topics & Keywords

Malaria Research and Control Species Distribution and Climate Change Mosquito-borne diseases and control

UN Sustainable Development Goals

Good health and well-being

Publication Details

Published in: Malaria Journal

Volume 11, Issue 1, pp. 165-165

DOI: 10.1186/1475-2875-11-165

Field-Weighted Citation Impact: 7.85