Ospina Juan, Hincapié-Palacio Doracelly, Ochoa Jesús, Velásquez Carlos, Almanza Payares Rita
Logic and Computing Group, School of Sciences, Eafit University, Medellín, Colombia.
Theoretical Epidemiology, Epidemiology Group, University of Antioquia, "Héctor Abad Gomez" National Faculty of Public Health, Universidad de Antioquia, Medellín, Colombia.
J Public Health Res. 2022 Aug 23;11(3):22799036221115770. doi: 10.1177/22799036221115770. eCollection 2022 Jul.
COVID-19 cases in Medellín, the second largest city in Colombia, were monitored during the first year of the pandemic using both mathematical models based on transmission theory and surveillance from each observed epidemic phase.
Expected cases were estimated using mandatory reporting data from Colombia's national epidemiological surveillance system from March 7, 2020 to March 7, 2021. Initially, the range of daily expected cases was estimated using a Borel-Tanner stochastic model and a deterministic Susceptible-Infected-Removed (SIR) model. A subsequent expanded version of the SIR model was used to include asymptomatic cases, severe cases and deaths. The moving average, standard deviation, and goodness of fit of estimated cases relative to confirmed reported cases were assessed, and local transmission in Medellin was contrasted with national transmission in Colombia.
The initial phase was characterized by imported case detection and the later phase by community transmission and increases in case magnitude and severity. In the initial phase, a maximum range of expected cases was obtained based on the stochastic model, which even accounted for the reduction of new imported cases following the closure of international airports. The deterministic estimate achieved an adequate fit with respect to accumulated cases until the conclusion of the mandatory national quarantine and gradual reopening, when reported cases increased. The estimated new cases were reasonably fit with the maximum reported incidence.
Adequate model fit was obtained with the reported data. This experience of monitoring epidemic trajectory can be extended using models adapted to local conditions.
在疫情的第一年，对哥伦比亚第二大城市麦德林的新冠疫情病例进行了监测，采用了基于传播理论的数学模型以及对每个观察到的流行阶段的监测。
使用来自哥伦比亚国家流行病学监测系统2020年3月7日至2021年3月7日的强制报告数据估计预期病例数。最初，使用博雷尔 - 坦纳随机模型和确定性易感 - 感染 - 康复（SIR）模型估计每日预期病例数范围。随后使用SIR模型的扩展版本纳入无症状病例、重症病例和死亡病例。评估了估计病例相对于确诊报告病例的移动平均值、标准差和拟合优度，并将麦德林的本地传播与哥伦比亚的全国传播进行了对比。
初始阶段的特征是检测到输入性病例，后期阶段的特征是社区传播以及病例数量和严重程度的增加。在初始阶段，基于随机模型获得了预期病例的最大范围，该模型甚至考虑到国际机场关闭后新输入病例的减少。在全国强制检疫结束和逐步重新开放之前，确定性估计与累计病例数拟合良好，之后报告病例增加。估计的新病例数与报告的最高发病率合理拟合。
报告数据获得了足够的模型拟合。这种监测疫情轨迹的经验可以通过使用适用于当地情况的模型来扩展。
