Institute of Management Studies, Goldsmiths, University of London, London, United Kingdom.
Department of Economics, University of Technology Sydney, Sydney, Australia.
PLoS One. 2021 Nov 29;16(11):e0260364. doi: 10.1371/journal.pone.0260364. eCollection 2021.
Epidemiological models used to inform government policies aimed to reduce the contagion of COVID-19, assume that the reproduction number is reduced through Non-Pharmaceutical Interventions (NPIs) leading to physical distancing. Available data in the UK show an increase in physical distancing before the NPIs were implemented and a fall soon after implementation. We aimed to estimate the effect of people's behaviour on the epidemic curve and the effect of NPIs taking into account this behavioural component. We have estimated the effects of confirmed daily cases on physical distancing and we used this insight to design a behavioural SEIR model (BeSEIR), simulated different scenaria regarding NPIs and compared the results to the standard SEIR. Taking into account behavioural insights improves the description of the contagion dynamics of the epidemic significantly. The BeSEIR predictions regarding the number of infections without NPIs were several orders of magnitude less than the SEIR. However, the BeSEIR prediction showed that early measures would still have an important influence in the reduction of infections. The BeSEIR model shows that even with no intervention the percentage of the cumulative infections within a year will not be enough for the epidemic to resolve due to a herd immunity effect. On the other hand, a standard SEIR model significantly overestimates the effectiveness of measures. Without taking into account the behavioural component, the epidemic is predicted to be resolved much sooner than when taking it into account and the effectiveness of measures are significantly overestimated.
用于为旨在减少 COVID-19 传播的政府政策提供信息的流行病学模型假设，通过非药物干预（NPIs）导致身体距离，繁殖数会减少。英国的现有数据表明，在实施 NPIs 之前，身体距离增加，而在实施后不久就下降了。我们旨在估计人们的行为对流行曲线的影响以及考虑到这种行为成分的 NPIs 的效果。我们已经估计了确诊的日常病例对身体距离的影响，并利用这一见解设计了一个行为 SEIR 模型（BeSEIR），模拟了关于 NPIs 的不同场景，并将结果与标准 SEIR 进行了比较。考虑到行为方面的见解，大大改善了对传染病动态的描述。如果没有 NPIs，BeSEIR 对感染人数的预测要比 SEIR 低几个数量级。但是，BeSEIR 预测表明，即使没有采取措施，早期措施仍将对减少感染产生重要影响。BeSEIR 模型表明，即使没有干预，由于群体免疫效应，一年内累积感染的百分比也不足以使疫情得到解决。另一方面，标准 SEIR 模型严重高估了措施的有效性。如果不考虑行为成分，那么与考虑行为成分相比，预计疫情会更早得到解决，并且措施的有效性将被严重高估。
