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

• Published in: Military medical research Vol. 8; no. 1; p. 31
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: England BioMed Central 18.05.2021; BMC
• Subjects: Armed forces; Coronaviruses; COVID-19; Disease control; Epidemics; Epidemiology; Letter to the Editor; Navy cluster; Outbreak management; Predictive modelling; SIR model; United States > US; Sri Lanka; COVID-19; Outbreak management; Predictive modelling; Navy cluster; SIR model
• ISSN: 2054-9369; 2095-7467; 2054-9369
• DOI: 10.1186/s40779-021-00325-4

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.