Grillo Ardila Elvia Karina, Santaella-Tenorio Julián, Guerrero Rodrigo, Bravo Luis Eduardo
Universidad del Valle, Facultad de Salud, Doctorado en Salud. Estudiente de Doctorado, Cali, Colombia.
Universidad del Valle, Facultad de Salud, Escuela de Salud Pública, Cali, Colombia.
Colomb Med (Cali). 2020 Jun 30;51(2):e4277. doi: 10.25100/cm.v51i2.4277.
Currently, there are several mathematical models that have been developed to understand the dynamics of COVID-19 infection. However, the difference in the sociocultural contexts between countries requires the specific adjustment of these estimates to each scenario. This article analyses the main elements used for the construction of models from epidemiological patterns, to describe the interaction, explain the dynamics of infection and recovery, and to predict possible scenarios that may arise with the introduction of public health measures such as social distancing and quarantines, specifically in the case of the pandemic unleashed by the new SARS-CoV-2/COVID-19 virus.
Mathematical models are highly relevant for making objective and effective decisions to control and eradicate the disease. These models used for COVID-19 have supported and will continue to provide information for the selection and implementation of programs and public policies that prevent associated complications, reduce the speed of the virus spread and minimize the occurrence of severe cases of the disease that may collapse health systems.
目前,已经开发了几种数学模型来了解新冠病毒感染的动态。然而,各国社会文化背景的差异要求根据每种情况对这些估计进行具体调整。本文分析了用于构建模型的主要要素,这些要素从流行病学模式出发,描述相互作用、解释感染和康复动态,并预测在实施诸如社交距离和隔离等公共卫生措施时可能出现的情况,特别是在新型严重急性呼吸综合征冠状病毒2/新冠病毒引发的大流行情况下。
数学模型对于做出控制和根除疾病的客观有效决策高度相关。这些用于新冠病毒的模型已经提供并将继续为预防相关并发症、降低病毒传播速度以及尽量减少可能使卫生系统不堪重负的严重病例发生的项目和公共政策的选择与实施提供信息。