Predictive modelling for COVID-19 outbreak control: lessons from the navy cluster in Sri Lanka

In response to an outbreak of coronavirus disease 2019 (COVID-19) within a cluster of Navy personnel in Sri Lanka commencing from 22nd April 2020, an aggressive outbreak management program was launched by the Epidemiology Unit of the Ministry of Health. To predict the possible number of cases within...

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Detalles Bibliográficos
Autores principales: Wijesekara, N. W. A. N. Y., Herath, Nayomi, Kodituwakku, K. A. L. C., Herath, H. D. B., Ginige, Samitha, Ruwanpathirana, Thilanga, Kariyawasam, Manjula, Samaraweera, Sudath, Herath, Anuruddha, Jayawardena, Senarupa, Gamge, Deepa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Letter to the Editor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8128624/
https://www.ncbi.nlm.nih.gov/pubmed/34001251
http://dx.doi.org/10.1186/s40779-021-00325-4
Descripción
Sumario:In response to an outbreak of coronavirus disease 2019 (COVID-19) within a cluster of Navy personnel in Sri Lanka commencing from 22nd April 2020, an aggressive outbreak management program was launched by the Epidemiology Unit of the Ministry of Health. To predict the possible number of cases within the susceptible population under four social distancing scenarios, the COVID-19 Hospital Impact Model for Epidemics (CHIME) was used. With increasing social distancing, the epidemiological curve flattened, and its peak shifted to the right. The observed or actually reported number of cases was above the projected number of cases at the onset; however, subsequently, it fell below all predicted trends. Predictive modelling is a useful tool for the control of outbreaks such as COVID-19 in a closed community.

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