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意大利封锁 60 天后,对确诊和治愈病例的 COVID-19 病毒爆发预测:基于数据驱动的模型方法。

COVID-19 virus outbreak forecasting of registered and recovered cases after sixty day lockdown in Italy: A data driven model approach.

机构信息

Center for Telemedicine and Telepharmacy, University of Camerino, Camerino, Italy.

Center for Telemedicine and Telepharmacy, University of Camerino, Camerino, Italy; Research Department, International Medical Radio Center Foundation (C.I.R.M.), Rome, Italy.

出版信息

J Microbiol Immunol Infect. 2020 Jun;53(3):396-403. doi: 10.1016/j.jmii.2020.04.004. Epub 2020 Apr 13.

Abstract

BACKGROUND

Till 31 March 2020, 105,792 COVID-19 cases were confirmed in Italy including 15,726 deaths which explains how worst the epidemic has affected the country. After the announcement of lockdown in Italy on 9 March 2020, situation was becoming stable since last days of March. In view of this, it is important to forecast the COVID-19 evaluation of Italy condition and the possible effects, if this lock down could continue for another 60 days.

METHODS

COVID-19 infected patient data has extracted from the Italian Health Ministry website includes registered and recovered cases from mid February to end March. Adoption of seasonal ARIMA forecasting package with R statistical model was done.

RESULTS

Predictions were done with 93.75% of accuracy for registered case models and 84.4% of accuracy for recovered case models. The forecasting of infected patients could be reach the value of 182,757, and recovered cases could be registered value of 81,635 at end of May.

CONCLUSIONS

This study highlights the importance of country lockdown and self isolation in control the disease transmissibility among Italian population through data driven model analysis. Our findings suggest that nearly 35% decrement of registered cases and 66% growth of recovered cases will be possible.

摘要

背景

截至 2020 年 3 月 31 日,意大利已确诊 105792 例 COVID-19 病例,包括 15726 例死亡病例,这说明了疫情对该国的影响有多严重。2020 年 3 月 9 日意大利宣布封锁后,自 3 月底以来,情况开始趋于稳定。鉴于此,如果这种封锁再持续 60 天,预测 COVID-19 对意大利的评估以及可能产生的影响就显得尤为重要。

方法

从意大利卫生部网站上提取了 COVID-19 感染患者的数据,包括 2 月中旬至 3 月底的确诊和治愈病例。采用季节性 ARIMA 预测包和 R 统计模型进行分析。

结果

对于确诊病例模型,预测的准确率为 93.75%,对于治愈病例模型,预测的准确率为 84.4%。到 5 月底,预测感染患者人数可能达到 182757 人,治愈人数可能达到 81635 人。

结论

本研究通过数据驱动模型分析,强调了国家封锁和自我隔离对控制意大利人群中疾病传播的重要性。我们的研究结果表明,登记病例可能减少近 35%,治愈病例可能增加 66%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e2/7152918/2097e31a2d39/gr1_lrg.jpg

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