Basic Reproduction Rate and Case Fatality Rate of COVID-19: Application of Meta-analysis

Abstract

1. The robust estimate of Basic Reproduction Rate (R0) of COVID-19 based on a meta-analysis performed on the pieces of evidence available across countries is 3.11 (2.49-3.71) persons for a generalised population in the absence of any control measures 2. The robust estimate of Case Fatality Rate (CFR) based on a meta-analysis performed on the pieces of evidence available across countries equals to 2.56 (2.06-3.05) per cent for a generalised population in approximately one-and-a-half months from the onset of the disease COVID-19. A significant regional variation is evident for the Basic Reproduction Rate (R0)but not for the Case Fatality Rate (CFR) 4. The peer-reviewed articles with a small sample size do not suffer from publication bias in a meta-analysis of COVID-19. Added Value of this StudyOut study combine available evidence of the parameter values, such as reproduction rate and case fatality rate, of the generalised epidemiological models for coronavirus disease of 2019 . In this way, we have reduced the dependency on data from a particular region or time or a homogeneous population. By applying meta-analysis, we estimated the robust estimate of reproduction rate and case fatality rate, which is applicable across heterogeneous populations. We proclaim that the reproduction rate of COVID-19 varies across subgroups of populations and regions and periods, but the case fatality rate remained the same. These estimates of reproduction rate and case fatality rate are worthwhile for developing countries like India and at a lower level of geography, in ambivalence. AbstractBackground: The outbreak of novel coronavirus disease of 2019 (COVID-19) has a wider geographical spread than other previous viruses such as Ebola and H1N1. The onset of disease and its transmission and severity has become a global concern. The policymakers have a serious concern for containing the spread and minimising the risk of death.Aim: This study aims to provide the estimates of basic reproduction rate (R0) and case fatality rate (CFR) which applies to a generalised population.Methods: A systematic review was carried out to retrieve the published estimates of reproduction rate and case fatality rate in peer-reviewed articles from PubMed MEDLINE database with defined inclusion and exclusion criteria in the period 15 December 2019 to 3 May 2020. The systematic review led to the selection of 24 articles for R0 and 17 articles for CFR. These studies used data from China and its provinces, other Asian countries such as Japan, Korea, the Philippines, and countries from other parts of the world such as Nigeria, Iran, Italy, Europe as a whole, France, Latin America, Turkey, the United Kingdom (UK), and the United States of America (USA). These selected articles gave an output of 30 counts of R0 and 29 counts of CFR which were used in a meta-analysis. A meta-analysis, with the inverse variance method, fixed-and random-effects model and the Forest plot, was performed to estimate the mean effect size or mean value of basic reproduction rate and case fat...

The effectiveness of eight nonpharmaceutical interventions against COVID-19 in 41 countries

“…When countries introduced stay-at-home orders, they nearly always also banned gatherings and closed schools, universities, and some or most businesses, if they had not done so already (Figure 3, bottom left). Flaxman et al 1 and Hsiang et al 3 add the effect of these distinct NPIs to the effectiveness of stay-at-home orders, and accordingly find a large effect. In contrast, we account for these other NPIs separately and isolate the additional effect of ordering the population to stay at home (when large gatherings are banned and educational institutions and some businesses closed).…”

“…Additionally, since school and university closures almost perfectly coincided in the countries we study, our approach cannot distinguish their individual effects (Appendix D.2.1). This limitation likely also holds for other observational studies which do not include data on university closures and estimate only the effect of school closures [1][2][3][5][6][7][8] . Previous evidence on school and university closures is mixed 1,6,26 .…”

“…The growth of the epidemic is determined by the time- and country-specific reproduction number R t,c , which depends on: a) the (unobserved) basic reproduction number R 0, c given no active NPIs and b) the active NPIs at time t . R 0, c accounts for all time-invariant factors that affect transmission in country c , such as differences in demographics, population density, culture, and health systems 18 . We assume that the effect of each NPI on R t,c is stable across countries and time.…”

“…To disentangle the effects of individual NPIs, we need to leverage data from multiple countries with diverse sets of interventions in place. Previous data-driven studies (Table F.8) estimate effectiveness for individual countries [2][3][4] or NPIs, although some exceptions exist 1,[5][6][7][8]. In contrast, we evaluate the impact of 8 NPIs on the epidemic's growth in 34 European and 7 non-European countries.…”

Impact of non-pharmaceutical interventions on the COVID-19 epidemic: A modelling study

“…We modelled the different scenarios based on the following assumptions: (1) no intervention or controls, we used an estimate of R 0 at 3.11 and a CFR of 2.63%. 12 Two scenarios for early intervention 4 weeks after the first case were modelled using a mean R 0 of 1.41; (2B) and a mean R 0 of 1.57 the upper most point of the 95% confidence interval. The late two scenarios modelled were based on a late intervention of 6 weeks after first case with a mean R 0 of 1.41 and R 0 of 1.57 the upper most point of the 95% confidence interval.…”