The effectiveness of public health interventions against COVID-19: Lessons from the Singapore experience.
Abstract
<h4>Background</h4>In dealing with community spread of COVID-19, two active interventions
have been attempted or advocated-containment, and mitigation. Given the extensive
impact of COVID-19 globally, there is international interest to learn from best practices
that have been shown to work in controlling community spread to inform future outbreaks.
This study explores the trajectory of COVID-19 infection in Singapore had the government
intervention not focused on containment, but rather on mitigation. In addition, we
estimate the actual COVID-19 infection cases in Singapore, given that confirmed cases
are publicly available.<h4>Methods and findings</h4>We developed a COVID-19 infection
model, which is a modified SIR model that differentiate between detected (diagnosed)
and undetected (undiagnosed) individuals and segments total population into seven
health states: susceptible (S), infected asymptomatic undiagnosed (A), infected asymptomatic
diagnosed (I), infected symptomatic undiagnosed (U), infected symptomatic diagnosed
(E), recovered (R), and dead (D). To account for the infection stages of the asymptomatic
and symptomatic infected individuals, the asymptomatic infected individuals were further
disaggregated into three infection stages: (a) latent (b) infectious and (c) non-infectious;
while the symptomatic infected were disaggregated into two stages: (a) infectious
and (b) non-infectious. The simulation result shows that by the end of the current
epidemic cycle without considering the possibility of a second wave, under the containment
intervention implemented in Singapore, the confirmed number of Singaporeans infected
with COVID-19 (diagnosed asymptomatic and symptomatic cases) is projected to be 52,053
(with 95% confidence range of 49,370-54,735) representing 0.87% (0.83%-0.92%) of the
total population; while the actual number of Singaporeans infected with COVID-19 (diagnosed
and undiagnosed asymptomatic and symptomatic infected cases) is projected to be 86,041
(81,097-90,986), which is 1.65 times the confirmed cases and represents 1.45% (1.36%-1.53%)
of the total population. A peak in infected cases is projected to have occurred on
around day 125 (27/05/2020) for the confirmed infected cases and around day 115 (17/05/2020)
for the actual infected cases. The number of deaths is estimated to be 37 (34-39)
among those infected with COVID-19 by the end of the epidemic cycle; consequently,
the perceived case fatality rate is projected to be 0.07%, while the actual case fatality
rate is estimated to be 0.043%. Importantly, our simulation model results suggest
that there about 65% more COVID-19 infection cases in Singapore that have not been
captured in the official reported numbers which could be uncovered via a serological
study. Compared to the containment intervention, a mitigation intervention would have
resulted in early peak infection, and increase both the cumulative confirmed and actual
infection cases and deaths.<h4>Conclusion</h4>Early public health measures in the
context of targeted, aggressive containment including swift and effective contact
tracing and quarantine, was likely responsible for suppressing the number of COVID-19
infections in Singapore.
Type
Journal articleSubject
HumansContact Tracing
Models, Statistical
Public Health
Quarantine
Singapore
Outcome Assessment, Health Care
COVID-19
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https://hdl.handle.net/10161/22734Published Version (Please cite this version)
10.1371/journal.pone.0248742Publication Info
Ansah, John P; Matchar, David Bruce; Shao Wei, Sean Lam; Low, Jenny G; Pourghaderi,
Ahmad Reza; Siddiqui, Fahad Javaid; ... Ong, Marcus Eng Hock (2021). The effectiveness of public health interventions against COVID-19: Lessons from the
Singapore experience. PloS one, 16(3). pp. e0248742. 10.1371/journal.pone.0248742. Retrieved from https://hdl.handle.net/10161/22734.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
David Bruce Matchar
Professor of Medicine
My research relates to clinical practice improvement - from the development of clinical
policies to their implementation in real world clinical settings. Most recently my
major content focus has been cerebrovascular disease. Other major clinical areas in
which I work include the range of disabling neurological conditions, cardiovascular
disease, and cancer prevention. Notable features of my work are: (1) reliance on
analytic strategies such as meta-analysis, simulation, decision analy

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