• FluTrackers.com Inc. does not provide medical advice. Information on this web site is collected from various internet resources, and the FluTrackers board of directors makes no warranty to the safety, efficacy, correctness or completeness of the information posted on this site by any author or poster. The information collated here is for instructional and/or discussion purposes only and is NOT intended to diagnose or treat any disease, illness, or other medical condition. Every individual reader or poster should seek advice from their personal physician/healthcare practitioner before considering or using any interventions that are discussed on this website. By continuing to access this website you agree to consult your personal physican before using any interventions posted on this website, and you agree to hold harmless FluTrackers.com Inc., the board of directors, the members, and all authors and posters for any effects from use of any medication, supplement, vitamin or other substance, device, intervention, etc. mentioned in posts on this website, or other internet venues referenced in posts on this website.
  • We are not asking for any donations. Do not donate to any entity who says they are raising funds for us.

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

tetano

Editor, Senior Moderator
Mil Med Res


. 2021 May 18;8(1):31.
doi: 10.1186/s40779-021-00325-4.
Predictive modelling for COVID-19 outbreak control: lessons from the navy cluster in Sri Lanka


N W A N Y Wijesekara[SUP] 1 [/SUP], Nayomi Herath[SUP] 2 [/SUP], K A L C Kodituwakku[SUP] 2 [/SUP], H D B Herath[SUP] 2 [/SUP], Samitha Ginige[SUP] 3 [/SUP], Thilanga Ruwanpathirana[SUP] 3 [/SUP], Manjula Kariyawasam[SUP] 3 [/SUP], Sudath Samaraweera[SUP] 3 [/SUP], Anuruddha Herath[SUP] 4 [/SUP], Senarupa Jayawardena[SUP] 4 [/SUP], Deepa Gamge[SUP] 3 [/SUP]



Affiliations

Abstract

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.

Keywords: COVID-19; Navy cluster; Outbreak management; Predictive modelling; SIR model.
 
Back
Top Bottom