The epidemiological and radiographical characteristics of asymptomatic infections with the novel coronavirus (COVID-19): A systematic review and meta-analysis

Highlights

• To provide a quantified understanding of the proportion of asymptomatic individuals among cases with COVID-19 infection.

• To describe the specific population that is asymptomatic.

• Findings could help to develop prevention and control strategies for asymptomatic individuals.

Abstract

Objectives

The role of asymptomatic infections in the transmission of COVID-19 have drawn considerable attention. Here, we performed a meta-analysis to summarize the epidemiological and radiographical characteristics of asymptomatic infections associated with COVID-19.

Methods

Data on the epidemiological and radiographical characteristics of asymptomatic infections were extracted from the existing literature. Pooled proportions with 95% confidence intervals were then calculated using a random effects model.

Results

A total of 104 studies involving 20,152 cases were included. The proportion of asymptomatic individuals among those with COVID-19 was 13.34% (10.86%–16.29%), among which presymptomatic and covert infections accounted for 7.64% (4.02%–14.04%) and 8.44% (5.12%–13.62%), respectively. The proportions of asymptomatic infections among infected children and healthcare workers were 32.24% (23.08%–42.13%) and 36.96% (18.51%–60.21%), respectively. The proportion of asymptomatic infections was significantly higher after 2020/02/29 than before (33.53% vs 10.19%) and in non-Asian regions than in Asia (28.76% vs 11.54%). The median viral shedding duration of asymptomatic infections was 14.14 days (11.25–17.04). A total of 47.62% (31.13%–72.87%) of asymptomatic infections showed lung abnormalities, especially ground-glass opacity (41.11% 19.7%–85.79%).

Conclusions

Asymptomatic infections were more commonly found in infected children and healthcare workers and increased after 2020/02/29 and in non-Asian regions. Chest radiographical imaging could be conducive to the early identification of asymptomatic infections.