Data_Sheet_1_Conditions for a Second Wave of COVID-19 Due to Interactions Between Disease Dynamics and Social Processes.PDF

In May 2020, many jurisdictions around the world began lifting physical distancing restrictions against the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This gave rise to concerns about a possible second wave of coronavirus disease 2019 (COVID-19). These restrictions were imposed in response to the presence of COVID-19 in populations, usually with the broad support of affected populations. However, the lifting of restrictions is also a population response to the accumulating socio-economic impacts of restrictions, and lifting of restrictions is expected to increase the number of COVID-19 cases, in turn. This suggests that the COVID-19 pandemic exemplifies a coupled behavior-disease system where disease dynamics and social dynamics are locked in a mutual feedback loop. Here we develop a minimal mathematical model of the interaction between social support for school and workplace closure and the transmission dynamics of SARS-CoV-2. We find that a second wave of COVID-19 occurs across a broad range of plausible model input parameters governing epidemiological and social conditions, on account of instabilities generated by behavior-disease interactions. The second wave tends to have a higher peak than the first wave when the efficacy of restrictions is greater than 40% and when the basic reproduction number R0 is less than 2.4. Surprisingly, we also found that a lower R0 value makes a second wave more likely, on account of behavioral feedback (although a lower R0 does not necessarily cause more infections, in total). We conclude that second waves of COVID-19 can be interpreted as the outcome of non-linear interactions between disease dynamics and social behavior. We also suggest that further development of mathematical models exploring behavior-disease interactions could help us better understand how social and epidemiological conditions together determine how pandemics unfold.

2020年5月，全球众多地区开始逐步放宽针对严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）传播的物理距离限制措施。此举引发了人们对可能出现的新一波冠状病毒病2019（COVID-19）疫情的担忧。这些限制措施的实施是对COVID-19在人群中存在的回应，通常在受影响人群中得到广泛支持。然而，限制措施的解除也是对限制措施累积产生的社会经济影响的群体反应，预计解除限制措施将导致COVID-19病例数的增加。这表明，COVID-19大流行体现了行为-疾病系统的耦合行为，其中疾病动力学和社会动力学陷入相互反馈的循环。在此，我们构建了一个关于社会对学校和工作场所关闭的支持与SARS-CoV-2传播动力学之间相互作用的简化数学模型。我们发现，在影响流行病学和社会条件的诸多可合理设定的模型输入参数中，由于行为-疾病相互作用产生的稳定性问题，COVID-19的第二波疫情可能发生。当限制措施的有效性大于40%且基本再生数R0小于2.4时，第二波疫情往往比第一波疫情具有更高的峰值。令人惊讶的是，我们还发现，较低的R0值使得第二波疫情的可能性增加，这是由于行为反馈的结果（尽管较低的R0并不一定导致感染总数增加）。我们得出结论，COVID-19的第二波疫情可以解释为疾病动力学与社会行为之间非线性交互作用的结果。我们亦建议，进一步发展探索行为-疾病相互作用的数学模型，有助于我们更好地理解社会和流行病学条件如何共同决定大流行的展开。