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加纳2019冠状病毒病感染动态的数学建模:政府与个人层面综合干预措施的影响评估

Mathematical modeling of COVID-19 infection dynamics in Ghana: Impact evaluation of integrated government and individual level interventions.

作者信息

Dwomoh Duah, Iddi Samuel, Adu Bright, Aheto Justice Moses, Sedzro Kojo Mensah, Fobil Julius, Bosomprah Samuel

机构信息

Department of Biostatistics, School of Public Health, College of Health Sciences, University of Ghana, Legon, Accra, Greater Accra, Ghana.

Department of Statistics, University of Ghana, Legon, Accra, Greater Accra, Ghana.

出版信息

Infect Dis Model. 2021;6:381-397. doi: 10.1016/j.idm.2021.01.008. Epub 2021 Jan 22.

Abstract

The raging COVID-19 pandemic is arguably the most important threat to global health presently. Although there Although there is currently a a a vaccine, preventive measures have been proposed to reduce the spread of infection but the efficacy of these interventions, and their likely impact on the number of COVID-19 infections is unknown. In this study, we proposed the SEIQHRS model (susceptible-exposed-infectious-quarantine-hospitalized-recovered-susceptible) model that predicts the trajectory of the epidemic to help plan an effective control strategy for COVID-19 in Ghana. We provided a short-term forecast of the early phase of the epidemic trajectory in Ghana using the generalized growth model. We estimated the effective basic Reproductive number Re in real-time using three different estimation procedures and simulated worse case epidemic scenarios and the impact of integrated individual and government interventions on the epidemic in the long term using compartmental models. The maximum likelihood estimates of Re and the corresponding 95% confidence interval was 2.04 [95% CI: 1.82-2.27; 12th March-7th April 2020]. The Re estimate using the exponential growth method was 2.11 [95% CI: 2.00-2.24] within the same period. The Re estimate using time-dependent (TD) method showed a gradual decline of the Effective Reproductive Number since March 12, 2020 when the first 2 index cases were recorded but the rate of transmission remains high (TD: Re = 2.52; 95% CI: [1.87-3.49]). The current estimate of Re based on the TD method is 1.74 [95% CI: 1.41-2.10; (13th May 2020)] but with comprehensive integrated government and individual level interventions, the Re could reduce to 0.5 which is an indication of the epidemic dying out in the general population. Our results showed that enhanced government and individual-level interventions and the intensity of media coverage could have a substantial effect on suppressing transmission of new COVID-19 cases and reduced death rates in Ghana until such a time that a potent vaccine or drug is discovered.

摘要

肆虐的新冠疫情无疑是当前全球健康面临的最重要威胁。尽管目前已有疫苗,但人们已提出预防措施以减少感染传播,然而这些干预措施的效果以及它们对新冠感染病例数可能产生的影响尚不清楚。在本研究中,我们提出了SEIQHRS模型(易感 - 暴露 - 感染 - 隔离 - 住院 - 康复 - 易感)来预测疫情发展轨迹,以帮助制定加纳新冠疫情的有效防控策略。我们使用广义增长模型对加纳疫情轨迹的早期阶段进行了短期预测。我们使用三种不同的估计程序实时估计有效基本再生数Re,并使用 compartmental模型模拟了最坏情况下的疫情场景以及长期来看个体和政府综合干预措施对疫情的影响。Re的最大似然估计值及相应的95%置信区间为2.04 [95% CI:1.82 - 2.27;2020年3月12日 - 4月7日]。同期使用指数增长法估计的Re为2.11 [95% CI:2.00 - 2.24]。使用时间依赖(TD)方法估计的Re显示,自2020年3月12日记录到首例2例病例以来,有效再生数逐渐下降,但传播率仍然很高(TD:Re = 2.52;95% CI:[1.87 - 3.49])。基于TD方法目前对Re的估计值为1.74 [95% CI:1.41 - 2.10;(2020年5月13日)],但通过政府和个体层面的全面综合干预,Re可降至0.5,这表明疫情在普通人群中将会逐渐消失。我们的结果表明,加强政府和个体层面的干预以及媒体报道力度,对于抑制加纳新增新冠病例的传播和降低死亡率可能会产生重大影响,直至发现有效的疫苗或药物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d23/7889985/7a3e2300e96f/gr1.jpg

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