{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T03:44:52Z","timestamp":1787024692828,"version":"build-2736575974"},"reference-count":73,"publisher":"IWA Publishing","issue":"2","license":[{"start":{"date-parts":[[2020,2,6]],"date-time":"2020-02-06T00:00:00Z","timestamp":1580947200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100011054","name":"Danish International Development Agency","doi-asserted-by":"publisher","award":["Combating Cholera Caused by Climate Change (C5) project"],"award-info":[{"award-number":["Combating Cholera Caused by Climate Change (C5) project"]}],"id":[{"id":"10.13039\/501100011054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["iwaponline.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Cholera, an acute diarrheal disease spread by lack of hygiene and contaminated water, is a major public health risk in many countries. As cholera is triggered by environmental conditions influenced by climatic variables, establishing a correlation between cholera incidence and climatic variables would provide an opportunity to develop a cholera forecasting model. Considering the auto-regressive nature and the seasonal behavioral patterns of cholera, a seasonal-auto-regressive-integrated-moving-average (SARIMA) model was used for time-series analysis during 2000\u20132013. As both rainfall (r = 0.43) and maximum temperature (r = 0.56) have the strongest influence on the occurrence of cholera incidence, single-variable (SVMs) and multi-variable SARIMA models (MVMs) were developed, compared and tested for evaluating their relationship with cholera incidence. A low relationship was found with relative humidity (r = 0.28), ENSO (r = 0.21) and SOI (r = \u22120.23). Using SVM for a 1 \u00b0C increase in maximum temperature at one-month lead time showed a 7% increase of cholera incidence (p &amp;lt; 0.001). However, MVM (AIC = 15, BIC = 36) showed better performance than SVM (AIC = 21, BIC = 39). An MVM using rainfall and monthly mean daily maximum temperature with a one-month lead time showed a better fit (RMSE = 14.7, MAE = 11) than the MVM with no lead time (RMSE = 16.2, MAE = 13.2) in forecasting. This result will assist in predicting cholera risks and better preparedness for public health management in the future.<\/jats:p>","DOI":"10.2166\/wh.2020.133","type":"journal-article","created":{"date-parts":[[2020,2,6]],"date-time":"2020-02-06T10:46:33Z","timestamp":1580985993000},"page":"207-223","update-policy":"https:\/\/doi.org\/10.2166\/iwapcrossmarkpolicypage","source":"Crossref","is-referenced-by-count":30,"title":["Developing a forecasting model for cholera incidence in Dhaka megacity through time series climate data"],"prefix":"10.2166","volume":"18","author":[{"given":"Salima Sultana","family":"Daisy","sequence":"first","affiliation":[{"name":"Institute of Water and Flood Management (IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A. K. M.","family":"Saiful Islam","sequence":"first","affiliation":[{"name":"Institute of Water and Flood Management (IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali Shafqat","family":"Akanda","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Rhode Island, Kingston, RI 02881, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abu Syed Golam","family":"Faruque","sequence":"first","affiliation":[{"name":"Centre for Nutrition and Food Security, International Centre for Diarrhoeal Disease Research, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nuhu","family":"Amin","sequence":"first","affiliation":[{"name":"Environmental Intervention Unit, Enteric and Respiratory Disease Program, Infectious Disease Division, International Centre for Diarrhoeal Disease Research, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter Kj\u00e6r Mackie","family":"Jensen","sequence":"first","affiliation":[{"name":"Copenhagen Center for Disaster Research, Department of Public Health, University of Copenhagen, Copenhagen, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"945","published-online":{"date-parts":[[2020,2,6]]},"reference":[{"issue":"6","key":"2020070602303330900_JWH-D-19-00133C1","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","article-title":"A new look at the statistical model identification","volume":"19","year":"1974","journal-title":"IEEE Trans. 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