伊朗法尔斯省新冠肺炎的空间流行病学和气象危险因素。

IF 1 4区医学 Q4 HEALTH CARE SCIENCES & SERVICES

Geospatial Health Pub Date : 2022-06-08 DOI:10.4081/gh.2022.1065

M. Zare, A. Semati, A. Mirahmadizadeh, Abdulrasool Hemmati, M. Ebrahimi

{"title":"伊朗法尔斯省新冠肺炎的空间流行病学和气象危险因素。","authors":"M. Zare, A. Semati, A. Mirahmadizadeh, Abdulrasool Hemmati, M. Ebrahimi","doi":"10.4081/gh.2022.1065","DOIUrl":null,"url":null,"abstract":"This study aimed at detecting space-time clusters of COVID-19 cases in Fars Province, Iran and at investigating their potential association with meteorological factors, such as temperature, precipitation and wind velocity. Time-series data including 53,554 infected people recorded in 26 cities from 18 February to 30 September 2020 together with 5876 meteorological records were subjected to the analysis. Applying a significance level of P<0.05, the analysis of space-time distribution of COVID-19 resulted in nine significant outbreaks within the study period. The most likely cluster occurred from 27 March to 13 July 2020 and contained 11% of the total cases with eight additional, secondary clusters. We found that the COVID-19 incidence rate was affected by high temperature (OR=1.64; 95% CI: 1.44-1.87), while precipitation and wind velocity had less effect (OR=0.84; 95% CI: 0.75-0.89 and OR=0.27; 95% CI: 0.14-0.51), respectively.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"17 s1 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial epidemiology and meteorological risk factors of COVID-19 in Fars Province, Iran.\",\"authors\":\"M. Zare, A. Semati, A. Mirahmadizadeh, Abdulrasool Hemmati, M. Ebrahimi\",\"doi\":\"10.4081/gh.2022.1065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aimed at detecting space-time clusters of COVID-19 cases in Fars Province, Iran and at investigating their potential association with meteorological factors, such as temperature, precipitation and wind velocity. Time-series data including 53,554 infected people recorded in 26 cities from 18 February to 30 September 2020 together with 5876 meteorological records were subjected to the analysis. Applying a significance level of P<0.05, the analysis of space-time distribution of COVID-19 resulted in nine significant outbreaks within the study period. The most likely cluster occurred from 27 March to 13 July 2020 and contained 11% of the total cases with eight additional, secondary clusters. We found that the COVID-19 incidence rate was affected by high temperature (OR=1.64; 95% CI: 1.44-1.87), while precipitation and wind velocity had less effect (OR=0.84; 95% CI: 0.75-0.89 and OR=0.27; 95% CI: 0.14-0.51), respectively.\",\"PeriodicalId\":56260,\"journal\":{\"name\":\"Geospatial Health\",\"volume\":\"17 s1 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2022-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geospatial Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.4081/gh.2022.1065\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geospatial Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4081/gh.2022.1065","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}

引用次数: 0

摘要

这项研究旨在检测伊朗法尔斯省新冠肺炎病例的时空集群，并调查其与温度、降水和风速等气象因素的潜在关联。对2020年2月18日至9月30日26个城市记录的53554名感染者以及5876份气象记录的时间序列数据进行了分析。应用显著性水平的P＜0.05，新冠肺炎的时空分布分析导致研究期间发生了9起显著疫情。最有可能的集群发生在2020年3月27日至7月13日，占总病例的11%，另有8个次级集群。我们发现新冠肺炎发病率受高温影响（OR=1.64；95%CI:1.44-1.87），而降水和风速的影响较小（OR=0.84；95%CI:0.75-0.89和OR=0.27；95%CI:0.14-0.51）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Spatial epidemiology and meteorological risk factors of COVID-19 in Fars Province, Iran.

This study aimed at detecting space-time clusters of COVID-19 cases in Fars Province, Iran and at investigating their potential association with meteorological factors, such as temperature, precipitation and wind velocity. Time-series data including 53,554 infected people recorded in 26 cities from 18 February to 30 September 2020 together with 5876 meteorological records were subjected to the analysis. Applying a significance level of P<0.05, the analysis of space-time distribution of COVID-19 resulted in nine significant outbreaks within the study period. The most likely cluster occurred from 27 March to 13 July 2020 and contained 11% of the total cases with eight additional, secondary clusters. We found that the COVID-19 incidence rate was affected by high temperature (OR=1.64; 95% CI: 1.44-1.87), while precipitation and wind velocity had less effect (OR=0.84; 95% CI: 0.75-0.89 and OR=0.27; 95% CI: 0.14-0.51), respectively.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Geospatial Health 医学-公共卫生、环境卫生与职业卫生

CiteScore

2.40

自引率

11.80%

发文量

审稿时长

12 months

期刊介绍： The focus of the journal is on all aspects of the application of geographical information systems, remote sensing, global positioning systems, spatial statistics and other geospatial tools in human and veterinary health. The journal publishes two issues per year.