论文标题
COVID-19的传播的流行病学模型：南非案例研究
An epidemiological model for the spread of COVID-19: A South African case study
论文作者
论文摘要
开发了一种流行病学模型，用于19日19日在南非的传播。使用经典隔室SEIR模型的变体，称为SEIQRDP模型。由于南非仍处于全球Covid -19大流行的早期阶段，并且确认的传染病病例尚未达到峰值，因此首先将SEIQRDP模型在德国，意大利和韩国的数据上首次参数化，而这些国家的传染性病例数量超过了高峰。可以合理预测COVID-19的确认案件，死亡和恢复案件的数量将结束时，最终会出现，并在何时何时获得合理的预测。然后，从3月23日至2020年5月8日的南非数据随后用于获得SEIQRDP模型参数。发现该模型非常适合初始疾病进展，但是该模型的长期预测能力相当差。随后，南非SEIQRDP模型被限制为报告值的基本繁殖数重新计算。最终的模型非常适合数据，并且长期预测似乎是合理的。南非SEIQRDP模型预测，确认的传染病人数的高峰将在2020年10月底发生，死亡人数的总数将在约10,000至90,000范围内，名义价值约为22,000。所有这些预测都在很大程度上取决于疾病控制措施以及对这些措施的遵守。这些预测进一步证明对确定基本繁殖数的参数特别敏感。未来的目的是将反馈控制方法与南非SEIQRDP模型一起确定南非政府提出的不同锁定水平的流行病学影响。
An epidemiological model is developed for the spread of COVID-19 in South Africa. A variant of the classical compartmental SEIR model, called the SEIQRDP model, is used. As South Africa is still in the early phases of the global COVID-19 pandemic with the confirmed infectious cases not having peaked, the SEIQRDP model is first parameterized on data for Germany, Italy, and South Korea - countries for which the number of infectious cases are well past their peaks. Good fits are achieved with reasonable predictions of where the number of COVID-19 confirmed cases, deaths, and recovered cases will end up and by when. South African data for the period from 23 March to 8 May 2020 is then used to obtain SEIQRDP model parameters. It is found that the model fits the initial disease progression well, but that the long-term predictive capability of the model is rather poor. The South African SEIQRDP model is subsequently recalculated with the basic reproduction number constrained to reported values. The resulting model fits the data well, and long-term predictions appear to be reasonable. The South African SEIQRDP model predicts that the peak in the number of confirmed infectious individuals will occur at the end of October 2020, and that the total number of deaths will range from about 10,000 to 90,000, with a nominal value of about 22,000. All of these predictions are heavily dependent on the disease control measures in place, and the adherence to these measures. These predictions are further shown to be particularly sensitive to parameters used to determine the basic reproduction number. The future aim is to use a feedback control approach together with the South African SEIQRDP model to determine the epidemiological impact of varying lockdown levels proposed by the South African Government.
