Estimating the spatial distribution of acute undifferentiated fever (AUF) and associated risk factors using emergency call data in India. A symptom-based approach for public health surveillance. (January 2015)

• Record Type: Journal Article
• Authors: Kauhl, Boris; Pilot, Eva; Rao, Ramana; Gruebner, Oliver; Schweikart, Jürgen; Krafft, Thomas
• Is Part Of: Health & place. Volume 31(2015:Jan.)
• Page Start: 111
• Page End: 119
• Publication Date: 2015-01
• Subjects: Acute undifferentiated fever (AUF) -- Infectious diseases -- Geographic information systems (GIS) -- Spatial regression -- India; Health -- Social aspects -- Periodicals; Health services accessibility -- Periodicals; Public health -- Periodicals; Political planning -- Periodicals; Social medicine -- Periodicals; Epidemiology -- Periodicals; Health Policy -- Periodicals; Health Services Accessibility -- Periodicals; Public Health -- Periodicals; Public Policy -- Periodicals; Sociology, Medical -- Periodicals; Épidémiologie -- Périodiques; Politique sanitaire -- Périodiques; Santé, Services de -- Accessibilité -- Périodiques; Health services accessibility; Health -- Social aspects; Political planning; Public health; Social medicine; Periodicals; 613
• DOI: 10.1016/j.healthplace.2014.11.002
• Languages: English
• ISSNs: 1353-8292

Abstract

Abstract: The System for Early-warning based on Emergency Data (SEED) is a pilot project to evaluate the use of emergency call data with the main complaint acute undifferentiated fever (AUF) for syndromic surveillance in India. While spatio-temporal methods provide signals to detect potential disease outbreaks, additional information about socio-ecological exposure factors and the main population at risk is necessary for evidence-based public health interventions and future preparedness strategies. The goal of this study is to investigate whether a spatial epidemiological analysis at the ecological level provides information on urban–rural inequalities, socio-ecological exposure factors and the main population at risk for AUF. Our results displayed higher risks in rural areas with strong local variation. Household industries and proximity to forests were the main socio-ecological exposure factors and scheduled tribes were the main population at risk for AUF. These results provide additional information for syndromic surveillance and could be used for evidence-based public health interventions and future preparedness strategies. Highlights: We used emergency call data on acute undifferentiated fever (AUF) as indicator for infectious diseases. Spatial epidemiological methods at the ecological level were applied to investigate urban–rural differences and socio-ecological exposure factors for AUF. Proximity to forests and household industries were main socio-ecological exposure factors and scheduled tribes were identified as the main population at risk for AUF. A spatial epidemiological approach based on emergency call data might provide additional information for evidence-based public health interventions and future preparedness strategies.