Estimating cholera risk from an exploratory analysis of its association with satellite-derived land surface temperatures. Issue 13 (3rd July 2019)

• Record Type: Journal Article
• Authors: Khan, Rakibul; Aldaach, Haidar; McDonald, Claire; Alam, Munirul; Huq, Anwar; Gao, Yongxuan; Akanda, Ali S; Colwell, Rita; Jutla, Antarpreet
• Is Part Of: International journal of remote sensing. Volume 40:Issue 13(2019)
• Page Start: 4898
• Page End: 4909
• Publication Date: 2019-07-03
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2019.1577575
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: Occurrence and growth of Vibrio cholerae, the causative agent of cholera, is linked to modalities of elevated temperatures and heavy precipitation. Previous studies have employed temperature- and satellite-derived precipitation data to determine the risk of cholera, but predictions were limited because of the coarse spatial resolution of temperature data (about 50 km). Cholera estimation has a severe impact on those in vulnerable regions with marginal civil infrastructure and those suffering additional damage after a natural disaster. In this study, a new remote-sensing data-based algorithm is proposed that includes a pathway to associate coarse-resolution cholera prediction with high-resolution land surface temperature (LST) dataset. The algorithm allows identification and prediction of regions with elevated risk of cholera at least four weeks in advance. Additionally, it employs a hierarchical structure comprising long-term anomalous LST values to determine hot spots of potential Vibrio cholerae . The algorithm was tested in five cholera epidemic regions of Sub-Saharan Africa (Mozambique, Central African Republic, Cameroon, South Sudan, and Rwanda), with realistic accuracy in demarcating regions where human cholera cases had been reported.