dc.creatorRainisch, Gabriel
dc.creatorUndurraga Fourcade, Eduardo Andrés
dc.creatorChowell, Gerardo
dc.date.accessioned2020-07-03T20:50:27Z
dc.date.available2020-07-03T20:50:27Z
dc.date.created2020-07-03T20:50:27Z
dc.date.issued2020
dc.identifier1878-3511
dc.identifierhttps://doi.org/10.1016/j.ijid.2020.05.043
dc.identifierhttps://pubmed.ncbi.nlm.nih.gov/32425631/
dc.identifier10.1016/j.ijid.2020.05.043
dc.description.abstractObjectives: Public health officials need tools to assist in anticipating the healthcare resources required to confront the SARS-COV-2 pandemic. We constructed a modeling tool to aid active public health officials to estimate healthcare demand from the pandemic in their jurisdictions and to evaluate the potential impact of population-wide social-distancing interventions. Methods: The tool uses an SEIR compartmental model to project the pandemic’s local spread. 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 six to 50 times the current supply of beds and ventilators. A lockdown strategy or combination of case isolation, home quarantine, social distancing of individuals >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.
dc.languageen
dc.relationInternational Journal of Infectious Diseases, no. 96 (2020), pp. 376-383
dc.subjectCOVID-19
dc.subjectHospital
dc.subjectCapacity
dc.subjectIntervention
dc.subjectSocial distancing
dc.titleA dynamic modeling tool for estimating healthcare demand from the COVID19 epidemic and evaluating population-wide interventions
dc.typeArtículo


Este ítem pertenece a la siguiente institución