论文标题
一种动态建模工具，用于估算COVID19流行病的医疗保健需求并评估人口范围的干预措施
A dynamic modeling tool for estimating healthcare demand from the COVID19 epidemic and evaluating population-wide interventions
论文作者
论文摘要
目标。公共卫生官员需要工具来协助预期面对SARS-COV-2大流行所需的医疗资源。我们建立了一种建模工具，以帮助实践公共卫生官员，以估计其司法管辖区的大流行的医疗保健需求，并评估人口范围内社会持有的干预措施的潜在影响。方法。该工具使用SEIR隔室模型来投射大流行的局部扩散。用户输入案例计数，医疗保健资源和选择评估的干预策略。输出包括有或不进行干预的感染和死亡的数量，以及相对于现有容量的医院，重症监护床和呼吸机的需求。我们使用来自智利三个区域的数据来说明该工具。结果。我们的方案表明，199名患者的激增可能会在6月之前淹没智利医院，在7月或8月达到峰值，是当前床和呼吸机供应的6至50倍。隔离策略或案例隔离，家庭隔离，个人距离超过70年的社会距离以及远程办公干预措施的结合可能会使治疗需求低于容量。结论。积极的干预措施可以避免Covid-19的重大发病率和死亡率。我们的工具允许在新数据可用时快速评估本地可应用的策略方案和结果的更新。
Objectives. Public health officials need tools to assist with anticipating the healthcare resources required to confront the SARS-COV-2 pandemic. We built a modeling tool to aid practicing public health officials with estimating healthcare demand from the pandemic in their jurisdictions and to evaluate the potential impacts of population-wide social-distancing interventions. Methods. The tool uses a SEIR compartmental model to project the local spread of the pandemic. Users input case counts, healthcare resources, and select intervention strategies to evaluate. Outputs include the number of infections and deaths with and without intervention, and the demand for hospital and critical care beds and ventilators relative to existing capacity. We illustrate the tool using data from three regions of Chile. Results. Our scenarios indicate a surge in COVID-19 patients could overwhelm Chilean hospitals by June, peaking in July or August at 6 to 50 times the current supply of beds and ventilators. A lockdown strategy or combination of case isolation, home quarantine, social distancing of individuals greater than 70 years, and telework interventions may keep treatment demand below capacity. Conclusions. Aggressive interventions can avert substantial morbidity and mortality from COVID-19. Our tool permits rapid evaluation of locally-applicable policy scenarios and updating of results as new data become available.
