title: 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.
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.
authors.affiliation: Department of International Health, CAPHRI School of Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences. Maastricht University, The Netherlands. Electronic address: boris.kauhl@maastrichtuniversity.nl.
authors.forename: Boris
authors.initials: B
authors.lastname: Kauhl
authors.affiliation: Department of Health, Ethics & Society, CAPHRI School of Public Health and Primary Care, Maastricht University, The Netherlands.
authors.forename: Eva
authors.initials: E
authors.lastname: Pilot
authors.affiliation: GVK Emergency Management Reseach Institute, Hyderabad, Andhra Pradesh, India.
authors.forename: Ramana
authors.initials: R
authors.lastname: Rao
authors.affiliation: Department of Epidemiology, Columbia University, NY, United States.
authors.forename: Oliver
authors.initials: O
authors.lastname: Gruebner
authors.affiliation: Beuth University of Applied Sciences, Department III, Civil Engineering and Geoinformatics, Berlin, Germany.
authors.forename: Jürgen
authors.initials: J
authors.lastname: Schweikart
authors.affiliation: Department of International Health, CAPHRI School of Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences. Maastricht University, The Netherlands; Institute of Environment Education and Research, Bharati Vidyapeeth University, Pune, India.
authors.forename: Thomas
authors.initials: T
authors.lastname: Krafft
mesh_terms: D000293:Adolescent; D000328:Adult; D002648:Child; D002675:Child, Preschool; D004196:Disease Outbreaks; D005260:Female; D005335:Fever of Unknown Origin / Q000453:epidemiology*; D040362:Geographic Information Systems; D006801:Humans; D015994:Incidence; D007194:India / Q000453:epidemiology; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D010865:Pilot Projects; D062486:Public Health Surveillance; D012307:Risk Factors
keywords: Acute undifferentiated fever (AUF); Geographic information systems (GIS); India; Infectious diseases; Spatial regression