{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T16:38:28Z","timestamp":1787071108140,"version":"build-2736575974"},"reference-count":36,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"2","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:sec>\n                    <jats:title>Background &amp; objectives:<\/jats:title>\n                    <jats:p>Dengue has emerged as a major global public health threat, with a sharp rise in cases across endemic regions in recent decades. Bihar, a high-risk state in eastern India, has experienced its most severe dengue outbreaks recently, reporting 8136 cases in 2019, 11,285 in 2022, and 19,093 in 2023. This study investigates the relationship between climate variability and dengue incidence across Bihar\u2019s 38 districts, including the capital city, Patna, over the period 2019-2023.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>The analysis focuses on key meteorological factors, minimum, maximum, and mean temperatures, along with precipitation, and their time-lagged associations with weekly dengue case counts. Spatial patterns of dengue transmission are also assessed to identify regional hotspots.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Central Bihar exhibits the highest incidence of dengue during the study period. Among the examined variables, minimum temperature and rainfall show the strongest and most consistent correlations with dengue incidence, particularly with lags of 4 to 6 weeks.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Interpretation &amp; conclusion:<\/jats:title>\n                    <jats:p>These findings provide a foundation for developing climate-informed early warning systems and targeted vector control strategies, thereby enhancing preparedness and response to future dengue outbreaks in Bihar and similar regions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/jvbd.jvbd_114_25","type":"journal-article","created":{"date-parts":[[2025,8,16]],"date-time":"2025-08-16T10:00:15Z","timestamp":1755338415000},"page":"237-248","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":1,"title":["Unravelling the interplay of space, time, and weather in dengue outbreaks: An insight from Bihar, India"],"prefix":"10.4103","volume":"63","author":[{"given":"Anand","family":"Shankar","sequence":"first","affiliation":[{"name":"India Meteorological Department, Ministry of Earth Sciences, Govt. of India, Patna, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,6,1]]},"reference":[{"key":"R1-20260604","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1038\/nature12060","article-title":"The global distribution and burden of dengue","volume":"496","author":"Bhatt","year":"2013","journal-title":"Nature"},{"key":"R2-20260604","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/jtm\/taab146","article-title":"Global burden for dengue and the evolving pattern in the past 30 years","volume":"28","author":"Yang","year":"2021","journal-title":"J Travel Med"},{"issue":"2","key":"R3-20260604","first-page":"1","article-title":"A machine learning system for precipitation estimation using satellite and ground radar network observations","volume":"58","author":"Chen","year":"2019","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"R4-20260604","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41597-021-00914-x","article-title":"Dengue emergence in the temperate Argentinian province of Santa Fe, 2009-2020","volume":"8","author":"L\u00f3pez","year":"2021","journal-title":"Sci Data"},{"issue":"2","key":"R5-20260604","doi-asserted-by":"crossref","first-page":"163","DOI":"10.3390\/insects13020163","article-title":"Imported dengue case numbers and local climatic patterns are associated with dengue virus transmission in Florida, USA","volume":"13","author":"Stephenson","year":"2022","journal-title":"Insects"},{"key":"R6-20260604","doi-asserted-by":"crossref","first-page":"1264","DOI":"10.1289\/ehp.1306556","article-title":"Climate and dengue transmission: Evidence and implications","volume":"121","author":"Morin","year":"2013","journal-title":"Environ Health Perspect"},{"key":"R7-20260604","article-title":"Jim Skea (United Kingdom), Priyadarshi R Shukla (India), Andy Reisinger (New Zealand) R, Slade (United Kingdom), Minal Pathak (India), Alaa Al Khourdajie (United Kingdom\/ Syria) R, van Diemen (the Netherlands\/United Kingdom), Amjad Abdulla (Maldives) KA (Japan), et al. 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