Niels Bohr Institute, University of Copenhagen, København Ø, Denmark.
APMIS. 2021 Jul;129(7):401-407. doi: 10.1111/apm.13120. Epub 2021 Feb 23.
The first wave of the COVID-19 pandemic was characterized by an initial rapid rise in new cases followed by a peak and a more erratic behaviour that varies between regions. This is not easy to reproduce with traditional SIR models, which predict a more symmetric epidemic. Here, we argue that superspreaders and population heterogeneity would predict such behaviour even in the absence of restrictions on social life. We present an agent-based lattice model of a disease spreading in a heterogeneous population. We predict that an epidemic driven by superspreaders will spread rapidly in cities, but not in the countryside where the sparse population limits the maximal number of secondary infections. This suggests that mitigation strategies should include restrictions on venues where people meet a large number of strangers. Furthermore, mitigating the epidemic in cities and in the countryside may require different levels of restrictions.
第一波 COVID-19 大流行的特点是新病例最初迅速上升,随后达到高峰,然后在不同地区呈现出更为不稳定的趋势。这用传统的 SIR 模型很难重现,因为传统的 SIR 模型预测的是更对称的疫情。在这里,我们认为超级传播者和人群异质性即使在没有限制社会生活的情况下也能预测到这种情况。我们提出了一种基于主体的格子模型,用于研究在异质人群中传播的疾病。我们预测,由超级传播者驱动的传染病将在城市中迅速传播,但在农村地区不会传播,因为农村稀疏的人口限制了二次感染的最大数量。这表明,缓解策略应该包括限制人们与大量陌生人见面的场所。此外,在城市和农村地区缓解疫情可能需要不同程度的限制。