Exploratory Spatio-Temporal Data Analysis (ESTDA) of Dengue and its association with climatic,environmental, and sociodemographic factors in Punjab,India |
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| Institution: | 1. Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India;2. Department of Health and Family Welfare, Government of Punjab, India;1. Warnell School of Forestry and Natural Resources, University of Georgia, 180 E. Green Street, Athens, GA 30602, USA;2. Tall Timbers, 13093 Henry Beadel Drive, Tallahassee, FL 32312, USA;1. Environmental Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2, Canada;2. Johnson Shoyama Graduate School of Public Policy, University of Regina, Saskatchewan S4S 0A2, Canada;1. Ecology and Environmental Modelling Laboratory, Department of Environmental Science, The University of Burdwan, Purba Bardhaman, 713104, India;2. Department of Geography, The University of Burdwan, Purba Bardhaman, 713104, West Bengal, India;3. Department of Basic Sciences and Humanities, Institute of Engineering & Management, Sector -V, Salt Lake City, Kolkata 700091, West Bengal, India;1. Shijiazhuang Institute of Railway Technology, Shijiazhuang 050018, China;2. School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072, Australia;3. College of Forestry, Beijing Forestry University, Beijing 100083, China;4. Pingwu Panda Valley Family Farm, Pingwu 622550, China;5. The Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China;6. UQ Spatial Epidemiology Laboratory, School of Veterinary Science, University of Queensland, Gatton 4343, Australia |
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| Abstract: | Routine health data is rich in information but underutilised for research in Low and Middle-Income countries. The present study was carried out to understand spatiotemporal patterns of dengue and its association with risk factors using routine data from health and allied sectors. ESTDA included estimation of dengue incidence rates, time series features and correlation coefficients up to the sub-district level. Scatter plots and correlation coefficients were used to identify relationships between covariates. Dengue incidence in 2015–19 was 47.76, 33.64, 52.03, 49.71, and 33.36 per 100,000, respectively, with a mean (SD) age of 34.33 (16.78) years and the majority being males (63.94%). Dengue had significant cross-correlation, non-linear relationships, and spatio-temporal associations with climatic, environmental, and socio-demographic risk factors. Significant autocorrelation of dengue occurrence was present at a lag of one month with seasonal patterns. The reproducible open-source algorithms add value to existing Routine Health Information Systems, and the findings will enable the development of Spatio-temporal models in future research. The research was done using R version 4.1.0. |
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