{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T14:22:21Z","timestamp":1787840541413,"version":"build-2784847793"},"reference-count":17,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/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":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background &amp; objectives:<\/jats:title>\n                    <jats:p>Dengue fever is a significant public health challenge in India. The threat has been amplified by rapid urbanization. This study analyzes the spatiotemporal patterns of dengue transmission, the influence of climate on dengue transmission, and predict future trends of dengue incidence in Dakshina Kannada district of Karnataka, India from 2024 to 2026.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>The study used retrospective data from January 1 2019 to April 30 2024, and covered 288 locations in the Dakshina Kannada. Data was collected in Microsoft Excel and analyzed using Jamovi 2.3.28 for descriptive statistics. Time series analysis was performed in R version 4.4.0, while spatiotemporal clusters were identified using SaTScan V10.1.2 and visualized in QGIS version 3.30.0. Multivariable linear regression was conducted to identify climate factors affecting dengue cases. ARIMA models were employed for predictive forecasting of future dengue cases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>A total of 1836 recorded dengue cases was retrieved from the Health Management Information System (HMIS) at the district level. The study identified significant spatiotemporal clusters of dengue cases, with the primary cluster occurring from May 1 2022 to April 30 2024. Climatic factors, particularly rainfall and temperature, showed significant correlations with dengue incidence. The ARIMA (3,1,1) (1,0,0) model demonstrated robust forecasting capability for dengue cases, indicating a continuing upward trend, which appears to be influenced by seasonal patterns.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Interpretation &amp; conclusion:<\/jats:title>\n                    <jats:p>Dengue transmission in Dakshina Kannada is significantly influenced by climatic factors such as temperature, rainfall, and humidity. The ARIMA-based predictive modeling forecasted increased dengue cases in the coming years. These findings show the need for targeted public health interventions in identified hotspot areas, along with continuous climate-based surveillance to support timely and effective dengue control measures.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/jvbd.jvbd_29_25","type":"journal-article","created":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T06:00:28Z","timestamp":1749448828000},"page":"88-94","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["Forecasting dengue incidence in Dakshina Kannada, Karnataka, India using time series analysis"],"prefix":"10.4103","volume":"63","author":[{"given":"Navya","family":"Mohana","sequence":"first","affiliation":[{"name":"Department of Public Health, Nitte Institute of Allied Health Sciences (NIAHS), NITTE University (Deemed to be University), Mangaluru, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mackwin Kenwood","family":"Dmello","sequence":"additional","affiliation":[{"name":"Department of Public Health, Nitte Institute of Allied Health Sciences (NIAHS), NITTE University (Deemed to be University), Mangaluru, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suresha","family":"Kharvi","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Nitte Institute of Allied Health Sciences (NIAHS), NITTE University (Deemed to be University), Mangaluru, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neevan","family":"Dsouza","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Nitte Institute of Allied Health Sciences (NIAHS), NITTE University (Deemed to be University), Mangaluru, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,2,27]]},"reference":[{"issue":"3","key":"R3-20260302","first-page":"373","article-title":"Dengue in India","volume":"136","author":"Gupta","year":"2012","journal-title":"Indian Journal Med Research"},{"key":"R4-20260302","doi-asserted-by":"crossref","first-page":"199018","DOI":"10.1016\/j.virusres.2022.199018","article-title":"Dengue virus infection - areview of pathogenesis, vaccines, diagnosis and therapy","volume":"324","author":"Kok","year":"2023","journal-title":"Virus Research"},{"issue":"1","key":"R6-20260302","first-page":"9","article-title":"Dengue infection: Global importance, immunopathology and management","volume":"22","author":"Kularatne","year":"2022","journal-title":"Clinical Medicine, Journal of the Royal College of Physicians of London"},{"issue":"8","key":"R7-20260302","first-page":"70","article-title":"Dengue burden in India: Recent trends and importance of climatic parameters","volume":"6","author":"Mutheneni","year":"2017","journal-title":"Emerg Microbes Infect"},{"issue":"12","key":"R8-20260302","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1371\/journal.pntd.0000920","article-title":"Quantifying the spatial dimension of dengue virus epidemic spread within a tropical urban environment","volume":"4","author":"Vazquez-Prokopec","year":"2010","journal-title":"PLoS Negl Trop Dis"},{"issue":"4","key":"R9-20260302","first-page":"05","article-title":"Spatio-Temporal analysis of dengue fever cases: A retrospective study","volume":"14","author":"Nayak","year":"2020","journal-title":"Journal of Clinical and Diagnostic Research"},{"issue":"2","key":"R10-20260302","doi-asserted-by":"crossref","first-page":"043848","DOI":"10.1136\/bmjopen-2020-043848","article-title":"Temporal variation and geospatial clustering of dengue in Delhi, India 2015-2018","volume":"11","author":"Singh","year":"2021","journal-title":"BMJ Open"},{"issue":"4","key":"R11-20260302","first-page":"197","article-title":"Hot spot detection and spatio-temporal dynamics of dengue in Queensland, Australia","volume":"8","author":"Naish","year":"2014","journal-title":"International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives"},{"issue":"1","key":"R12-20260302","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.1186\/s12879-014-0610-4","article-title":"Spatiotemporal clustering, climate periodicity, and social-ecological risk factors for dengue during an outbreak in Machala, Ecuador, in 2010","volume":"14","author":"Stewart-Ibarra","year":"2014","journal-title":"BMC Infect Dis"},{"issue":"10","key":"R13-20260302","first-page":"3398","article-title":"Correlates of climate variability and dengue fever in two metropolitan cities in Bangladesh","volume":"10","author":"Zahirul","year":"2018","journal-title":"Cureus"},{"issue":"4","key":"R14-20260302","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1177\/1010539518769809","article-title":"Spatiotemporal distribution and geospatial diffusion patterns of 2013 dengue outbreak in Jhapa District, Nepal","volume":"30","author":"Acharya","year":"2018","journal-title":"Asia Pac J Public Health"},{"issue":"2","key":"R15-20260302","doi-asserted-by":"crossref","first-page":"75","DOI":"10.36685\/phi.v7i2.411","article-title":"Forecasting prevalence of dengue hemorrhagic fever using ARIMA model in Sulawesi Tenggara Province, Indonesia","volume":"7","author":"Mistawati","year":"2021","journal-title":"Public Health of Indonesia"},{"issue":"2","key":"R16-20260302","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1007\/s10661-018-7162-9","article-title":"Spatiotemporal analysis of dengue outbreaks in Samanabad town, Lahore metropolitan area, using geospatial techniques","volume":"191","author":"Mahmood","year":"2019","journal-title":"Environ Monit Assess"},{"issue":"11","key":"R17-20260302","doi-asserted-by":"crossref","first-page":"2281","DOI":"10.18520\/cs\/v114\/i11\/2281-2291","article-title":"Data mining techniques for predicting dengue outbreak in geospatial domain using weather parameters for New Delhi, India","volume":"114","author":"Agarwal","year":"2018","journal-title":"Current Science"},{"issue":"10","key":"R18-20260302","doi-asserted-by":"crossref","first-page":"2417","DOI":"10.1371\/journal.pgph.0002417","article-title":"Common patterns between dengue cases, climate, and local environmental variables in Costa Rica: A wavelet approach","volume":"3","author":"Garc\u00eda","year":"2023","journal-title":"PLOS Global Public Health"},{"issue":"1","key":"R19-20260302","first-page":"1019238","article-title":"Possible factorsinfluencing the seroprevalence of dengue among residents of the forest fringe areas of Peninsular Malaysia","volume":"7","author":"Abd-Jamil","year":"2020","journal-title":"J Trop Med"},{"issue":"3","key":"R20-20260302","first-page":"299","article-title":"Epidemiology of dengue: Past, present and future prospects","volume":"5","author":"Murray","year":"2013","journal-title":"Clinical Epidemiology"}],"container-title":["Journal of Vector Borne Diseases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ovid.com\/10.4103\/jvbd.jvbd_29_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T13:24:38Z","timestamp":1787837078000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ovid.com\/10.4103\/jvbd.jvbd_29_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":17,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026]]}},"URL":"https:\/\/doi.org\/10.4103\/jvbd.jvbd_29_25","relation":{},"ISSN":["0972-9062"],"issn-type":[{"value":"0972-9062","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"2025-02-19","name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-05-23","name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}}]}}