The novel coronavirus (COVID-19) pandemic continues to be a global health problem whose impact has been significantly felt in South Africa. With the global spread increasing and infecting millions, containment efforts by countries have largely focused on lockdowns and social distancing to minimise contact between persons. Social distancing has been touted as the best form of response in managing a rapid increase in the number of infected cases. In this paper, we present a deterministic model to describe the impact of social distancing on the transmission dynamics of COVID-19 in South Africa. The model is fitted to data from March 5 to April 13, 2020, on the cumulative number of infected cases, and a scenario analysis on different levels of social distancing is presented. The model shows that with the levels of social distancing under the initial lockdown level between March 26 and April 13, 2020, there would be a projected continued rise in the number of infected cases. The model also looks at the impact of relaxing the social distancing measures after the initial announcement of the lockdown. It is shown that relaxation of social distancing by 2% can result in a 23% rise in the number of cumulative cases whilst an increase in the level of social distancing by 2% would reduce the number of cumulative cases by about 18%. The model results accurately predicted the number of cases after the initial lockdown level was relaxed towards the end of April 2020. These results have implications on the management and policy direction in the early phase of the epidemic.

中文翻译：

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建模社交活动对南非COVID-19流行病的潜在影响

新型冠状病毒（COVID-19）大流行仍然是全球健康问题，其影响已在南非显着显现。随着全球范围的扩大和数以百万计的感染，各国的遏制努力主要集中在封锁和社会疏远上，以最大程度地减少人与人之间的接触。社会隔离已被吹捧为应对迅速增加的感染病例数的最佳应对方式。在本文中，我们提供了一个确定性模型来描述社会距离对南非COVID-19传播动力学的影响。该模型适用于2020年3月5日至4月13日的数据，该数据涉及受感染病例的累计数量，并提供了针对不同社会距离水平的情景分析。该模型显示，在2020年3月26日至2020年4月13日期间，社会疏散水平低于最初的锁定水平，预计感染病例数将继续增加。该模型还着眼于首次宣布封锁后放松社会隔离措施的影响。研究表明，社会距离的放宽2％可以使累计病例数增加23％，而社会距离的水平提高2％可以使累计病例数减少约18％。模型结果准确地预测了到2020年4月底放松初始锁定水平后的病例数。这些结果对流行病早期的管理和政策方向产生了影响。预计感染病例数将继续增加。该模型还着眼于首次宣布封锁后放松社会隔离措施的影响。研究表明，社会距离的放宽2％可以使累计病例数增加23％，而社会距离的水平提高2％可以使累计病例数减少约18％。模型结果准确地预测了到2020年4月底放松初始锁定水平后的病例数。这些结果对流行病早期的管理和政策方向产生了影响。预计感染病例数将继续增加。该模型还着眼于首次宣布封锁后放松社会隔离措施的影响。研究表明，社会距离的放宽2％可以使累计病例数增加23％，而社会距离的水平提高2％可以使累计病例数减少约18％。模型结果准确地预测了到2020年4月底放松初始锁定水平后的病例数。这些结果对流行病早期的管理和政策方向产生了影响。该模型还着眼于首次宣布封锁后放松社会隔离措施的影响。研究表明，社会距离的放宽2％可以使累计病例数增加23％，而社会距离的水平提高2％可以使累计病例数减少约18％。模型结果准确地预测了到2020年4月底放松初始锁定水平后的病例数。这些结果对流行病早期的管理和政策方向产生了影响。该模型还着眼于首次宣布封锁后放松社会隔离措施的影响。结果表明，社会距离的放宽2％可以使累计病例数增加23％，而社会距离的水平提高2％则可以减少累计病例数约18％。模型结果准确地预测了到2020年4月底放松初始锁定水平后的病例数。这些结果对流行病早期的管理和政策方向产生了影响。