Barriers of COVID-19 vaccination in Ukraine during the war: the simulation study using ARIMA model

Q3 Computer Science
D. Chumachenko, T. Chumachenko, Nataliia Kirinovych, I. Meniailov, O. Muradyan, O. Salun
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引用次数: 1

Abstract

The COVID-19 pandemic has become a challenge to public health systems worldwide. As of June 2022, more than 545 million cases have been registered worldwide, more than 6.34 million of which have died. The gratuitous and bloody war launched by Russia in Ukraine has affected the public health system, including disruptions to COVID-19 vaccination plans. The use of simulation models to estimate the necessary coverage of COVID-19 vaccination in Ukraine will make it possible to rapidly change the policy to combat the pandemic in the wartime. This study aims to develop a COVID-19 vaccination model in Ukraine and to study the impact of war on this process. The study is multidisciplinary and includes a sociological study of the attitude of the population of Ukraine toward COVID-19 vaccination before the escalation of the war, the modeling of the vaccine campaign, forecasting the required number of doses administered after the start of the war, epidemiological analysis of the simulation results. This research targeted the COVID-19 epidemic process during the war. The research subjects are the methods and models of epidemic process simulation based on statistical machine learning. Sociological analysis methods were applied to achieve this goal, and an ARIMA model was developed to assess COVID-19 vaccination coverage As a result of the study, the population of Ukraine was clustered in attitude to COVID-19 vaccination. As a result of a sociological study of 437 donors and 797 medical workers, four classes were distinguished: supporters, loyalists, conformists, and skeptics. An ARIMA model was built to simulate the daily coverage of COVID-19 vaccinations. A retrospective forecast verified the model's accuracy for the period 01/25/22 - 02/23/22 in Ukraine. The forecast accuracy for 30 days was 98.79%. The model was applied to estimate the required vaccination coverage in Ukraine for the period 02/24/22 – 03/25/22. Conclusions. A multidisciplinary study made it possible to assess the adherence of the population of Ukraine to COVID-19 vaccination and develop an ARIMA model to assess the necessary COVID-19 vaccination coverage in Ukraine. The model developed is highly accurate and can be used by public health agencies to adjust vaccine policies in wartime. Given the barriers to vaccination acceptance, despite the hostilities, it is necessary to continue to perform awareness-raising work in the media, covering not only the events of the war but also setting the population on the need to receive the first and second doses of the COVID-19 vaccine for previously unvaccinated people, and a booster dose for those who have previously received two doses of the vaccine, involving opinion leaders in such works.
战争期间乌克兰新冠肺炎疫苗接种障碍的ARIMA模型模拟研究
新冠肺炎大流行已成为全球公共卫生系统面临的挑战。截至2022年6月,全球已登记超过5.45亿例病例,其中634多万人死亡。俄罗斯在乌克兰发动的无端血腥战争影响了公共卫生系统,包括破坏了新冠肺炎疫苗接种计划。使用模拟模型来估计新冠肺炎疫苗在乌克兰的必要覆盖率,将有可能在战时迅速改变抗击疫情的政策。本研究旨在开发乌克兰新冠肺炎疫苗接种模型,并研究战争对这一过程的影响。这项研究是多学科的,包括战争升级前乌克兰人民对新冠肺炎疫苗接种态度的社会学研究、疫苗运动模型、战争开始后所需接种剂量的预测、模拟结果的流行病学分析。这项研究针对新冠肺炎在战争期间的流行过程。研究主题是基于统计机器学习的流行病过程模拟方法和模型。为了实现这一目标,应用了社会学分析方法,并开发了ARIMA模型来评估新冠肺炎疫苗接种覆盖率。研究结果表明,乌克兰人口对新冠肺炎疫苗接种的态度是聚集的。根据对437名捐赠者和797名医务工作者的社会学研究,区分出四个阶层:支持者、忠诚者、墨守成规者和怀疑论者。建立ARIMA模型来模拟新冠肺炎疫苗接种的每日覆盖率。回顾性预测验证了该模型在乌克兰2022年1月25日至2022年2月23日期间的准确性。30天的预测准确率为98.79%。该模型用于估计乌克兰2022年2月24日至2022年3月25日期间所需的疫苗接种覆盖率。结论。通过一项多学科研究,可以评估乌克兰人口对新冠肺炎疫苗接种的依从性,并开发ARIMA模型来评估乌克兰必要的新冠肺炎疫苗接种覆盖率。所开发的模型高度准确,可供公共卫生机构用于战时调整疫苗政策。鉴于接受疫苗接种的障碍,尽管存在敌对行动,但有必要继续在媒体上进行宣传工作,不仅报道战争事件,而且让民众认识到需要为以前未接种疫苗的人接种第一剂和第二剂新冠肺炎疫苗,以及为之前接种过两剂疫苗的人接种加强针,让意见领袖参与此类工作。
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来源期刊
Radioelectronic and Computer Systems
Radioelectronic and Computer Systems Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
3.60
自引率
0.00%
发文量
50
审稿时长
2 weeks
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