Spatial epidemiology of COVID-19 infection through the first outbreak in the city of Mashhad, Iran
Spatial epidemiology of COVID-19 infection through the first outbreak in the city of Mashhad, Iran
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DOI：
10.1007/s41324-022-00454-5
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发表时间：
2022-06-28
影响因子：
2.4
通讯作者：
中科院分区：
文献类型：
--
作者：
COVID-19疫情是目前全球最重要的公共卫生挑战。目前的研究旨在调查伊朗马什哈德首次爆发COVID-19疫情的空间流行病学。数据包括2020年2月4日至4月13日期间住院实验室确诊的COVID-19病例。对于组间比较，使用经典统计学分析。建立Logistic回归模型，分析影响死亡率的因素。在计算经验贝叶斯率（EBR）后，应用局部Moran's I统计量来量化疾病的空间自相关性。总累积发病率和病死率分别为4.6/10，000（95%CI：4.3-4.8）和23.1%（95%CI：23.2-25.4）。在1535例病例中，62%为男性，死亡率高于女性（校正比值比（aOR）：1.58，95%CI：1.23-2.04）。60岁以上患者的死亡几率超过3倍（aOR：3.66，95%CI：2.79-4.81）。尽管COVID-19患者在马什哈德的分布几乎是随机的，但在大部分双周时段，市中心地区的高-高聚集性最明显。最有可能影响市中心周围热点发展的因素包括拥挤的人口（由于圣地），低社会经济和贫困的社区，难以获得医疗设施，室内拥挤，以及进一步使用公共交通。不断提高公众认识，强调保持社会距离，增加整个社区的免疫接种，特别是在空间分析发现的高度优先领域，可以使人们的生活更加美好。
The COVID-19 epidemic is currently the most important public health challenge worldwide. The current study aimed to survey the spatial epidemiology of the COVID-19 outbreak in Mashhad, Iran, across the first outbreak. The data was including the hospitalized lab-confirmed COVID-19 cases from Feb 4 until Apr 13, 2020. For comparison between the groups, classical statistics analyses were used. A logistic regression model was built to detect the factors affecting mortality. After calculating the empirical Bayesian rate (EBR), the Local Moran’s I statistic was applied to quantify the spatial autocorrelation of disease. The total cumulative incidence and case fatality rates were respectively 4.6 per 10,000 (95% CI: 4.3–4.8) and 23.1% (95% CI: 23.2–25.4). Of 1535 cases, 62% were males and were more likely to die than females (adjusted Odds Ratio (aOR): 1.58, 95% CI: 1.23–2.04). The odds of death for patients over 60 years was more than three times (aOR: 3.66, 95% CI: 2.79–4.81). Although the distribution of COVID-19 patients was nearly random in Mashhad, the downtown area had the most significant high-high clusters throughout most of the biweekly periods. The most likely factors influencing the development of hotspots around the downtown include the congested population (due to the holy shrine), low socioeconomic and deprived neighborhoods, poor access to health facilities, indoor crowding, and further use of public transportation. Constantly raising public awareness, emphasizing social distancing, and increasing the whole community immunization, particularly in the high-priority areas detected by spatial analysis, can lead people to a brighter picture of their lives.
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影响因子：
28.3
作者：
Gorbalenya, Alexander E.;Baker, Susan C.;Ziebuhr, John
通讯作者：
Ziebuhr, John
DOI：
10.1007/s13762-018-2104-1
发表时间：
2020-02-01
影响因子：
3.1
作者：
Ardakani, A. H. H.;Shojaei, S.;Ekhtesasi, M. R.
通讯作者：
Ekhtesasi, M. R.
影响因子：
1.7
作者：
Hashtarkhani, Soheil;Kiani, Behzad;Matthews, Stephen A.
通讯作者：
Matthews, Stephen A.
影响因子：
3.7
作者：
Shahriarirad, Reza;Khodamoradi, Zohre;Moghadami, Mohsen
通讯作者：
Moghadami, Mohsen
影响因子：
2.4
作者：
Shojaei, Saeed;Alipur, Hamid;Khosravi, Hassan
通讯作者：
Khosravi, Hassan