{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T16:00:58Z","timestamp":1789142458214,"version":"build-2803163510"},"reference-count":90,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T00:00:00Z","timestamp":1735171200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T00:00:00Z","timestamp":1735171200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Infect Dis Poverty"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Rapid human movement plays a crucial role in the spatial dissemination of the dengue virus. Nevertheless, robust quantification of this relationship using both spatial and temporal models remains necessary. This study aims to explore the spatial and temporal patterns of dengue transmission under various human movement contexts.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>We obtained district-wise aggregated dengue incidence data from the Management Information System,\u00a0Directorate General of Health Services of Bangladesh. The stringency index (SI), along with eight individual policy measures (from the Oxford Coronavirus Government Response Tracker database) and six mobility indices (as measured by Google's Community Mobility Reports) were obtained as human movement indicators. A multi-step correlative modelling approach, including various spatial and temporal models, was utilized to explore the associations of dengue incidence with the SI, fourteen human movement indices and the Eid festival.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The global Moran\u2019s <jats:italic>I<\/jats:italic> indicated significant spatial autocorrelation in dengue incidence during the pre-pandemic (Moran\u2019s <jats:italic>I<\/jats:italic>: 0.14, <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.05) and post-pandemic periods (Moran\u2019s I: 0.42, <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.01), while the pandemic period (2020\u20132022) showed weaker, non-significant spatial clustering (Moran\u2019s <jats:italic>I<\/jats:italic>: 0.07, <jats:italic>P<\/jats:italic>\u2009&gt;\u20090.05). Following the pandemic, we identified the emergence of new dengue hotspots. We found a strong negative relationship between monthly dengue incidence and the SI (<jats:italic>r<\/jats:italic><jats:sub>spearman<\/jats:sub>: \u2212\u00a00.62, <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.01). Through the selection of an optimal Seasonal autoregressive integrated moving average model, we observed that the closure of public transport (\u03b2\u2009=\u2009\u2212\u00a01.66, <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.10) and restrictions on internal movement (\u03b2\u2009=\u2009\u2212\u00a02.13, <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.10) were associated with the reduction of dengue incidence. Additionally, observed cases were substantially lower than predicted cases during the period from 2020 to 2022. By utilising additional time-series models, we were able to identify in 2023 a rise in dengue incidence associated with the Eid festival intervention, even after adjusting for important climate variables.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>Overall, rapid human movement was found to be associated with increased dengue transmission in Bangladesh. Consequently, the implemention of effective mosquito control interventions prior to large festival periods is necessary for preventing the spread of the disease nationwide. We emphasize the necessity for developing advanced surveillance and monitoring networks to track real-time human movement patterns and dengue incidence.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Graphical Abstract<\/jats:title>\n                \n              <\/jats:sec>","DOI":"10.1186\/s40249-024-01267-4","type":"journal-article","created":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T02:51:33Z","timestamp":1735181493000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Rapid human movement and dengue transmission in Bangladesh: a spatial and temporal analysis based on different policy measures of COVID-19 pandemic and Eid festival"],"prefix":"10.1186","volume":"13","author":[{"given":"Jahirul","family":"Islam","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6422-9240","authenticated-orcid":false,"given":"Wenbiao","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,26]]},"reference":[{"key":"1267_CR1","unstructured":"World Health Organization (WHO). 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