Suppr超能文献

预测孟加拉国的新冠疫情形势。

Forecasting COVID-19 situation in Bangladesh.

作者信息

Nesa Mossamet Kamrun, Babu Md Rashed, Mamun Khan Mohammad Tareq

机构信息

Department of Statistics, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh.

Moulvibazar Government Women College, Moulvibazar 3203, Bangladesh.

出版信息

Biosaf Health. 2022 Feb;4(1):6-10. doi: 10.1016/j.bsheal.2021.12.003. Epub 2021 Dec 25.

Abstract

Forecasting the COVID-19 confirmed cases, deaths, and recoveries demands time to know the severity of the novel coronavirus. This research aims to predict all types of COVID-19 cases (verified people, deaths, and recoveries) from the deadliest 3rd wave data of the COVID-19 pandemic in Bangladesh. We used the official website of the Directorate General of Health Services as our data source. To identify and predict the upcoming trends of the COVID-19 situation of Bangladesh, we fit the Auto-Regressive Integrated Moving Average (ARIMA) model on the data from Mar. 01, 2021 to Jul. 31, 2021. The finding of the ARIMA model (forecast model) reveals that infected, deaths, and recoveries number will have experienced exponential growth in Bangladesh to October 2021. Our model reports that confirmed cases and deaths will escalate by four times, and the recoveries will improve by five times at a later point in October 2021 if the trend of the three scenarios of COVID-19 from March to July lasts. The prediction of the COVID-19 scenario for the next three months is very frightening in Bangladesh, so the strategic planner and field-level personnel need to search for suitable policies and strategies and adopt these for controlling the mass transmission of the virus.

摘要

预测新冠确诊病例、死亡人数和康复人数需要时间来了解新型冠状病毒的严重程度。本研究旨在根据孟加拉国新冠疫情最致命的第三波数据预测各类新冠病例(确诊者、死亡者和康复者)。我们将卫生服务总局的官方网站作为数据源。为了识别和预测孟加拉国新冠疫情的未来趋势,我们对2021年3月1日至2021年7月31日的数据拟合了自回归积分滑动平均(ARIMA)模型。ARIMA模型(预测模型)的结果显示,到2021年10月,孟加拉国的感染、死亡和康复人数将呈指数增长。我们的模型报告称,如果3月至7月新冠疫情三种情况的趋势持续下去,到2021年10月后期,确诊病例和死亡人数将增加四倍,康复人数将增加五倍。孟加拉国未来三个月的新冠疫情预测非常令人担忧,因此战略规划者和实地工作人员需要寻找合适的政策和策略并加以采用,以控制病毒的大规模传播。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/86d4/8709792/d7bb322e354d/gr1_lrg.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验