Understanding the spread of infectious diseases in edge areas of hotspots: dengue epidemics in tropical metropolitan regions

IF 3 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH International Journal of Health Geographics Pub Date : 2023-12-10 DOI:10.1186/s12942-023-00355-2
Ya-Peng Lee, Tzai-Hung Wen
{"title":"Understanding the spread of infectious diseases in edge areas of hotspots: dengue epidemics in tropical metropolitan regions","authors":"Ya-Peng Lee, Tzai-Hung Wen","doi":"10.1186/s12942-023-00355-2","DOIUrl":null,"url":null,"abstract":"Identifying clusters or hotspots from disease maps is critical in research and practice. Hotspots have been shown to have a higher potential for transmission risk and may be the source of infections, making them a priority for controlling epidemics. However, the role of edge areas of hotspots in disease transmission remains unclear. This study aims to investigate the role of edge areas in disease transmission by examining whether disease incidence rate growth is higher in the edges of disease hotspots during outbreaks. Our data is based on the three most severe dengue epidemic years in Kaohsiung city, Taiwan, from 1998 to 2020. We employed conditional autoregressive (CAR) models and Bayesian areal Wombling methods to identify significant edge areas of hotspots based on the extent of risk difference between adjacent areas. The difference-in-difference (DID) estimator in spatial panel models measures the growth rate of risk by comparing the incidence rate between two groups (hotspots and edge areas) over two time periods. Our results show that in years characterized by exceptionally large-scale outbreaks, the edge areas of hotspots have a more significant increase in disease risk than hotspots, leading to a higher risk of disease transmission and potential disease foci. This finding explains the geographic diffusion mechanism of epidemics, a pattern mixed with expansion and relocation, indicating that the edge areas play an essential role. The study highlights the importance of considering edge areas of hotspots in disease transmission. Furthermore, it provides valuable insights for policymakers and health authorities in designing effective interventions to control large-scale disease outbreaks.","PeriodicalId":48739,"journal":{"name":"International Journal of Health Geographics","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2023-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Health Geographics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12942-023-00355-2","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0

Abstract

Identifying clusters or hotspots from disease maps is critical in research and practice. Hotspots have been shown to have a higher potential for transmission risk and may be the source of infections, making them a priority for controlling epidemics. However, the role of edge areas of hotspots in disease transmission remains unclear. This study aims to investigate the role of edge areas in disease transmission by examining whether disease incidence rate growth is higher in the edges of disease hotspots during outbreaks. Our data is based on the three most severe dengue epidemic years in Kaohsiung city, Taiwan, from 1998 to 2020. We employed conditional autoregressive (CAR) models and Bayesian areal Wombling methods to identify significant edge areas of hotspots based on the extent of risk difference between adjacent areas. The difference-in-difference (DID) estimator in spatial panel models measures the growth rate of risk by comparing the incidence rate between two groups (hotspots and edge areas) over two time periods. Our results show that in years characterized by exceptionally large-scale outbreaks, the edge areas of hotspots have a more significant increase in disease risk than hotspots, leading to a higher risk of disease transmission and potential disease foci. This finding explains the geographic diffusion mechanism of epidemics, a pattern mixed with expansion and relocation, indicating that the edge areas play an essential role. The study highlights the importance of considering edge areas of hotspots in disease transmission. Furthermore, it provides valuable insights for policymakers and health authorities in designing effective interventions to control large-scale disease outbreaks.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
了解传染病在热点边缘地区的传播:热带大都市地区的登革热疫情
在研究和实践中,从疾病地图中识别群集或热点至关重要。研究表明,热点地区具有较高的潜在传播风险,可能是传染源,因此是控制流行病的重点。然而,热点边缘区域在疾病传播中的作用仍不清楚。本研究旨在通过研究疾病爆发期间,疾病热点边缘地区的发病率增长率是否更高,来探讨边缘地区在疾病传播中的作用。我们的数据基于 1998 年至 2020 年台湾高雄市登革热疫情最严重的三个年份。我们采用条件自回归(CAR)模型和贝叶斯均值 Wombling 方法,根据相邻地区之间的风险差异程度来识别重要的热点边缘地区。空间面板模型中的差分估算器(DID)通过比较两组(热点地区和边缘地区)在两个时间段内的发病率来衡量风险增长率。我们的结果表明,在爆发异常大规模疫情的年份,热点地区的边缘地区比热点地区的疾病风险增长更显著,导致疾病传播和潜在疾病病灶的风险更高。这一发现解释了流行病的地理扩散机制,即扩张与迁移混合的模式,表明边缘地区起着至关重要的作用。这项研究强调了考虑疾病传播热点边缘地区的重要性。此外,它还为政策制定者和卫生当局设计有效的干预措施以控制大规模疾病爆发提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
International Journal of Health Geographics
International Journal of Health Geographics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
10.20
自引率
2.00%
发文量
17
审稿时长
12 weeks
期刊介绍: A leader among the field, International Journal of Health Geographics is an interdisciplinary, open access journal publishing internationally significant studies of geospatial information systems and science applications in health and healthcare. With an exceptional author satisfaction rate and a quick time to first decision, the journal caters to readers across an array of healthcare disciplines globally. International Journal of Health Geographics welcomes novel studies in the health and healthcare context spanning from spatial data infrastructure and Web geospatial interoperability research, to research into real-time Geographic Information Systems (GIS)-enabled surveillance services, remote sensing applications, spatial epidemiology, spatio-temporal statistics, internet GIS and cyberspace mapping, participatory GIS and citizen sensing, geospatial big data, healthy smart cities and regions, and geospatial Internet of Things and blockchain.
期刊最新文献
Using spatial video and deep learning for automated mapping of ground-level context in relief camps. The influence of malaria control interventions and climate variability on changes in the geographical distribution of parasite prevalence in Kenya between 2015 and 2020. Understanding Ixodes ricinus occurrence in private yards: influence of yard and landscape features. Accessibility, neighborhood socioeconomic disadvantage and expenditures on electronic gambling machines: a spatial analysis based on player account data. Comparing mapped park and greenspace boundaries in Philadelphia: implications for exposure assessment in health studies.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1