论文标题
受到Covid-19的挑战的教训
Lessons from being challenged by COVID-19
论文作者
论文摘要
我们提出了不同方法的结果,以模拟阿根廷Covid-19的流行病的演变,特别关注布宜诺斯艾利斯市及其大都市地区的大型,其中包括41个地区,其中包括超过1300万居民。我们首先强调了鉴于来自国外的传染性旅行者,解释流行病的早期阶段的相关性。接下来,我们对某些提出的解决方案进行了批判性评估,以基于生殖数的瞬时修改含有流行病。最后,我们构建了越来越复杂和现实的模型,从用于估计本地繁殖数字的简单均匀模型到完全耦合的不均匀(确定性或随机)模型,这些模型包含了手机位置数据中的移动性估计。这些模型能够产生与官方数量拟合和微调的官方案例相一致的预测。我们讨论了所提出的模型的优势和局限性,重点关注不同必要的第一近似值的有效性,并提示未来的建模努力,以在解释长期预测的解释以及采用数值模拟支持的非药态干预措施中。
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.