Abstract:
INTRODUCTION : estimating the number of SARS-CoV-2 infected individuals
at any specific time point is always a challenge due to asymptomatic
cases, the incubation period and testing delays. Here we use an empirical
analysis of cumulative death count, transmission-to-death time lag, and
infection fatality rate (IFR) to evaluate and estimate the actual cases at
a specific time point as a strategy of tracking the spread of COVID-19.
METHODS : this method mainly uses death count, as COVID-19 related
deaths are arguably more reliably reported than infection case numbers.
Using an IFR estimate of 0.66%, we back-calculate the number of cases
that would result in the cumulative number of deaths at a given time
point in South Africa between 27 February and 14 April. We added the
mean incubation period (6.4 days) and the onset-to-death time lag (17.8
days) to identify the estimated time lag between transmission and death
(25 days, rounded up). We use the statistical programming language R
to analyze the data and produce plots.
RESULTS : we estimate 28,182 cases as of 14 April, compared with 3,465
reported cases. Weekly growth rate of actual cases dropped immediately
after lockdown implementation and has remained steady, measuring at
51.2% as of 14 April. The timing of drop in growth rate suggests that
South Africa’s infection prevention strategy may have been effective at
reducing viral transmission.
CONCLUSION : estimating the actual number of cases at a specific time
point can support evidence-based policies to reduce and prevent the
spread of COVID-19. Non-reported, asymptomatic, hard to reach and,
mild cases are possible sources of outbreaks that could emerge after
lockdown. Therefore, close monitoring, optimized screening strategy and
prompt response to COVID-19 could help in stopping the spread of the
virus.