被COVID-19质疑的教训
Lessons from being challenged by COVID-19
摘要：
我们介绍了不同方法的结果，以模拟阿根廷COVID-19疫情的演变，特别关注布宜诺斯艾利斯市及其大都市区所形成的特大城市，包括41个地区，人口超过1300万。我们首先强调，根据从国外入境的传染性旅行者来解释流行病的早期阶段是有意义的。接下来，我们批判性地评估某些建议的解决方案，以遏制流行病的基础上瞬时修改的再生数。最后，我们建立越来越复杂和现实的模型，从简单的同质模型用于估计当地的繁殖数量，完全耦合的非同质（确定性或随机性）模型，结合移动性估计从手机位置数据。这些模型能够以最小的参数拟合和微调产生与官方案例数高度一致的预测。我们讨论了所提出的模型的优势和局限性，重点是不同的必要的第一近似的有效性，并警告未来的建模工作，以行使非常谨慎的长期预测的解释，并在通过非药物干预支持的数值模拟。
英文摘要：
We present results of different approaches to model the evolution of the COVID-19 epidemic in Argentina, with a special focus on the megacity conformed by the city of Buenos Aires and its metropolitan area, including a total of 41 districts with over 13 million inhabitants. We first highlight the relevance of interpreting the early stage of the epidemic in light of incoming infectious travelers from abroad. Next, we critically evaluate certain proposed solutions to contain the epidemic based on instantaneous modifications of the reproductive number. Finally, we build increasingly complex and realistic models, ranging from simple homogeneous models used to estimate local reproduction numbers, to fully coupled inhomogeneous (deterministic or stochastic) models incorporating mobility estimates from cell phone location data. The models are capable of producing forecasts highly consistent with the official number of cases with minimal parameter fitting and fine-tuning. We discuss the strengths and limitations of the proposed models, focusing on the validity of different necessary first approximations, and caution future modeling efforts to exercise great care in the interpretation of long-term forecasts, and in the adoption of non-pharmaceutical interventions backed by numerical simulations.
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