BACKGROUND: Asymptomatic SARS-CoV-2 infections are responsible for potentially significant transmission of COVID-19. Worldwide, a number of studies were conducted to estimate the magnitude of asymptomatic COVID-19 cases. However, there is a need for more robust and well-designed studies to have a relevant public health intervention. Synthesis of the available studies significantly strengthens the quality of evidences for public health practice. Thus, this systematic review and meta-analysis aimed to determine the overall magnitude of asymptomatic COVID-19 cases throughout the course of infection using available evidences. METHODS: We followed the PRISMA checklist to present this study. Two experienced review authors (MA and DBK) were systematically searched international electronic databases for studies. We performed meta-analysis using R statistical software. The overall weighted proportion of asymptomatic COVID-19 cases throughout the course infection was computed. The pooled estimates with 95% confidence intervals were presented using forest plot. Egger's tests were used to assess publication bias, and primary estimates were pooled using a random effects model. Furthermore, a sensitivity analysis was conducted to assure the robustness of the result. RESULTS: A total of 28 studies that satisfied the eligibility criteria were included in this systematic review and meta-analysis. Consequently, in the meta-analysis, a total of 6,071 COVID-19 cases were included. The proportion of asymptomatic infections among the included studies ranged from 1.4% to 78.3%. The findings of this meta-analysis showed that the weighted pooled proportion of asymptomatic COVID-19 cases throughout the course of infection was 25% (95%CI: 16-38). The leave-one out result also revealed that the weighted pooled average of asymptomatic SARS-CoV-2 infection was between 28% and 31.4%. CONCLUSIONS: In conclusion, one-fourth of SARS-CoV-2 infections are remained asymptomatic throughout the course infection. Scale-up of testing, which targeting high risk populations is recommended to tackle the pandemic.
BACKGROUND: Asymptomatic SARS-CoV-2 infections are responsible for potentially significant transmission of COVID-19. Worldwide, a number of studies were conducted to estimate the magnitude of asymptomatic COVID-19 cases. However, there is a need for more robust and well-designed studies to have a relevant public health intervention. Synthesis of the available studies significantly strengthens the quality of evidences for public health practice. Thus, this systematic review and meta-analysis aimed to determine the overall magnitude of asymptomatic COVID-19 cases throughout the course of infection using available evidences. METHODS: We followed the PRISMA checklist to present this study. Two experienced review authors (MA and DBK) were systematically searched international electronic databases for studies. We performed meta-analysis using R statistical software. The overall weighted proportion of asymptomatic COVID-19 cases throughout the course infection was computed. The pooled estimates with 95% confidence intervals were presented using forest plot. Egger's tests were used to assess publication bias, and primary estimates were pooled using a random effects model. Furthermore, a sensitivity analysis was conducted to assure the robustness of the result. RESULTS: A total of 28 studies that satisfied the eligibility criteria were included in this systematic review and meta-analysis. Consequently, in the meta-analysis, a total of 6,071 COVID-19 cases were included. The proportion of asymptomatic infections among the included studies ranged from 1.4% to 78.3%. The findings of this meta-analysis showed that the weighted pooled proportion of asymptomatic COVID-19 cases throughout the course of infection was 25% (95%CI: 16-38). The leave-one out result also revealed that the weighted pooled average of asymptomatic SARS-CoV-2 infection was between 28% and 31.4%. CONCLUSIONS: In conclusion, one-fourth of SARS-CoV-2 infections are remained asymptomatic throughout the course infection. Scale-up of testing, which targeting high risk populations is recommended to tackle the pandemic.
Authors: Michael C Grant; Luke Geoghegan; Marc Arbyn; Zakaria Mohammed; Luke McGuinness; Emily L Clarke; Ryckie G Wade Journal: PLoS One Date: 2020-06-23 Impact factor: 3.240
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Authors: Ellen de Bock; Mando D Filipe; Roger K J Simmermacher; A Christiaan Kroese; Menno R Vriens; Milan C Richir Journal: BMJ Open Date: 2022-07-07 Impact factor: 3.006
Authors: Kevin Escandón; Angela L Rasmussen; Isaac I Bogoch; Eleanor J Murray; Karina Escandón; Saskia V Popescu; Jason Kindrachuk Journal: BMC Infect Dis Date: 2021-07-27 Impact factor: 3.090
Authors: Ashley Quigley; Phi Yen Nguyen; Haley Stone; David J Heslop; Abrar Ahmad Chughtai; C Raina MacIntyre Journal: J Racial Ethn Health Disparities Date: 2022-05-11