Spatiotemporal Study of COVID-19 in Fars Province, Iran, October-November 2020: Establishment of Early Warning System

A. Semati, Azimeh Zare, M. Zare, A. Mirahmadizadeh, M. Ebrahimi
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Abstract

Background Using time series and spatiotemporal analyses, this study aimed to establish an Early Warning System (EWS) for COVID-19 in Fars province Iran. Methods A EWS was conducted on (i) daily basis city-level time series data including 53 554 cases recorded during 18 February–30 September 2020, which were applied to forecast COVID-19 cases during 1 October–14 November 2020, and (ii) the spatiotemporal analysis, which was conducted on the forecasted cases to predict spatiotemporal outbreaks of COVID-19. Results A total of 55 369 cases were forecasted during 1 October–14 November 2020, most of which (26.9%) occurred in Shiraz. In addition, 65.80% and 34.20% of the cases occurred in October and November, respectively. Four significant spatiotemporal outbreaks were predicted, with the Most Likely Cluster (MLC) occurring in ten cities during 2–22 October (P < 0.001 for all). Moreover, subgroup analysis demonstrated that Zarrindasht was the canon of the epidemic on 6 October (P=0.04). As a part of EWS, the epidemic was triggered from Jahrom, involving the MLC districts in the center, west, and south parts of the province. Then, it showed a tendency to move towards Zarrindasht in the south and progress to Lar in the southernmost part. Afterwards, it simultaneously progressed to Fasa and Sepidan in the central and northwestern parts of the province, respectively. Conclusion EWS, which was established based on the current protocol, alarmed policymakers and health managers on the progression of the epidemic and on where and when to implement medical facilities. These findings can be used to tailor province-level policies to servile the ongoing epidemic in the area; however, governmental level effort is needed to control the epidemic at a larger scale in the future.
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2020年10 - 11月伊朗法尔斯省新冠肺炎疫情时空研究:预警系统建立
背景采用时间序列和时空分析方法,建立伊朗法尔斯省新冠肺炎预警系统。方法采用EWS方法对2020年2月18日至9月30日的53554例城市日时间序列数据进行EWS分析,用于预测2020年10月1日至11月14日的病例数;对预测病例数进行时空分析,用于预测2019冠状病毒病的时空暴发。结果2020年10月1日至11月14日共预测病例55 369例,其中设拉子地区占26.9%;10月和11月分别占65.80%和34.20%。预测了4次显著的时空暴发,10月2日至22日期间最可能聚集(MLC)发生在10个城市(所有P < 0.001)。此外,亚组分析表明,Zarrindasht是10月6日流行的典型(P=0.04)。作为EWS的一部分,疫情是从Jahrom引发的,涉及该省中部、西部和南部的MLC区。然后,它显示出向南部的扎林达什特移动,向最南端的拉尔移动的趋势。随后,它分别在该省中部和西北部同时向Fasa和Sepidan移动。基于现行议定书建立的EWS使决策者和卫生管理人员对流行病的进展以及在何处和何时实施医疗设施感到震惊。这些发现可用于制定省级政策,以遏制该地区正在发生的流行病;然而,未来需要政府层面的努力来更大规模地控制这一流行病。
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