{"title":"孟加拉国人口快速流动与登革热传播:基于2019冠状病毒病大流行和开斋节不同政策措施的时空分析","authors":"Jahirul Islam, Wenbiao Hu","doi":"10.1186/s40249-024-01267-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>We obtained district-wise aggregated dengue incidence data from the Management Information System, Directorate 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.</p><p><strong>Results: </strong>The global Moran's I indicated significant spatial autocorrelation in dengue incidence during the pre-pandemic (Moran's I: 0.14, P < 0.05) and post-pandemic periods (Moran's I: 0.42, P < 0.01), while the pandemic period (2020-2022) showed weaker, non-significant spatial clustering (Moran's I: 0.07, P > 0.05). Following the pandemic, we identified the emergence of new dengue hotspots. We found a strong negative relationship between monthly dengue incidence and the SI (r<sub>spearman</sub>: - 0.62, P < 0.01). Through the selection of an optimal Seasonal autoregressive integrated moving average model, we observed that the closure of public transport (β = - 1.66, P < 0.10) and restrictions on internal movement (β = - 2.13, P < 0.10) 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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":48820,"journal":{"name":"Infectious Diseases of Poverty","volume":"13 1","pages":"99"},"PeriodicalIF":8.1000,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11670399/pdf/","citationCount":"0","resultStr":"{\"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.\",\"authors\":\"Jahirul Islam, Wenbiao Hu\",\"doi\":\"10.1186/s40249-024-01267-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>We obtained district-wise aggregated dengue incidence data from the Management Information System, Directorate 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.</p><p><strong>Results: </strong>The global Moran's I indicated significant spatial autocorrelation in dengue incidence during the pre-pandemic (Moran's I: 0.14, P < 0.05) and post-pandemic periods (Moran's I: 0.42, P < 0.01), while the pandemic period (2020-2022) showed weaker, non-significant spatial clustering (Moran's I: 0.07, P > 0.05). Following the pandemic, we identified the emergence of new dengue hotspots. We found a strong negative relationship between monthly dengue incidence and the SI (r<sub>spearman</sub>: - 0.62, P < 0.01). Through the selection of an optimal Seasonal autoregressive integrated moving average model, we observed that the closure of public transport (β = - 1.66, P < 0.10) and restrictions on internal movement (β = - 2.13, P < 0.10) 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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":48820,\"journal\":{\"name\":\"Infectious Diseases of Poverty\",\"volume\":\"13 1\",\"pages\":\"99\"},\"PeriodicalIF\":8.1000,\"publicationDate\":\"2024-12-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11670399/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Infectious Diseases of Poverty\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s40249-024-01267-4\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infectious Diseases of Poverty","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40249-024-01267-4","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
Background: 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.
Methods: We obtained district-wise aggregated dengue incidence data from the Management Information System, Directorate 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.
Results: The global Moran's I indicated significant spatial autocorrelation in dengue incidence during the pre-pandemic (Moran's I: 0.14, P < 0.05) and post-pandemic periods (Moran's I: 0.42, P < 0.01), while the pandemic period (2020-2022) showed weaker, non-significant spatial clustering (Moran's I: 0.07, P > 0.05). Following the pandemic, we identified the emergence of new dengue hotspots. We found a strong negative relationship between monthly dengue incidence and the SI (rspearman: - 0.62, P < 0.01). Through the selection of an optimal Seasonal autoregressive integrated moving average model, we observed that the closure of public transport (β = - 1.66, P < 0.10) and restrictions on internal movement (β = - 2.13, P < 0.10) 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.
Conclusions: 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.
期刊介绍:
Infectious Diseases of Poverty is an open access, peer-reviewed journal that focuses on addressing essential public health questions related to infectious diseases of poverty. The journal covers a wide range of topics including the biology of pathogens and vectors, diagnosis and detection, treatment and case management, epidemiology and modeling, zoonotic hosts and animal reservoirs, control strategies and implementation, new technologies and application. It also considers the transdisciplinary or multisectoral effects on health systems, ecohealth, environmental management, and innovative technology. The journal aims to identify and assess research and information gaps that hinder progress towards new interventions for public health problems in the developing world. Additionally, it provides a platform for discussing these issues to advance research and evidence building for improved public health interventions in poor settings.