key: cord-299899-is815pol
authors: He, Jingjing; Guo, Yifei; Mao, Richeng; Zhang, Jiming
title: Proportion of asymptomatic coronavirus disease 2019 (COVID‐19): a systematic review and meta‐analysis
date: 2020-07-21
journal: J Med Virol
DOI: 10.1002/jmv.26326
sha: 
doc_id: 299899
cord_uid: is815pol

OBJECTIVE: We aim to systematically review the characteristics of asymptomatic infection in the coronavirus disease 2019 (COVID‐19). METHODS: PubMed and EMBASE were electronically searched to identify original studies containing the rate of asymptomatic infection in COVID‐19 patients before 20 May 2020. Then mate‐analysis was conducted using R version 3.6.2. RESULTS: A total of 50155 patients from 41 studies with confirmed COVID‐19 were included. The pooled percentage of asymptomatic infection is 15.6% (95% CI: 10.1%‐23.0%). Ten included studies contain the number of pre‐symptomatic patients, who were asymptomatic at screening point and developed symptoms during follow‐up. The pooled percentage of pre‐symptomatic infection among 180 initially asymptomatic patients is 48.9% (95% CI: 31.6‐66.2%). The pooled proportion of asymptomatic infection among 1152 COVID‐19 children from 11 studies is 27.7% (95% CI: 16.4–42.7%), which is much higher than patients from all aged groups. Abnormal CT features are common in asymptomatic COVID‐19 infection. For 36 patients from 4 studies that CT results were available, 15 (41.7%) patients had bilateral involvement and 14 (38.9%) had unilateral involvement in CT results. Reduced white blood cell count, increased lactate dehydrogenase, and increased C‐reactive protein were also recorded. CONCLUSION: About 15.6% of confirmed COVID‐19 patients are asymptomatic. Nearly half of the patients with no symptoms at detection time will develop symptoms later. Children are likely to have a higher proportion of asymptomatic infection than adults. Asymptomatic COVID‐19 patients could have abnormal laboratory and radiational manifestations which can be used as screening strategies to identify asymptomatic infection. This article is protected by copyright. All rights reserved.

The current COVID-19 pneumonia pandemic, caused by a novel coronavirus SARS-CoV-2 that belongs to the beta-coronavirus lineage B, is spreading globally at an accelerated rate. First reported in a seafood market in Wuhan province China in December 2019 1 , this disease is now affecting more than 156 countries around the world. As of June 5 th , 2020, a total number of 4248389 laboratory-confirmed cases have been documented globally, leading to 294046 deaths 2 , which is far more than two Clinical manifestation of COVID-19 is protean. Significant clinical presentations of COVID-19 include fever, respiratory and gastrointestinal symptoms, pneumonia 3 , and other symptoms such as myasthenia, ageusia, and anosmia 4 . However, patients infected with SARS-CoV-2 could also be asymptomatic, confirmed by positive Nucleic acid testing results during the illness. As a potential source of COVID-19 infection, asymptomatic patients with subclinical manifestation could be missed by detection strategies and put a threat to infection control via person-to-person contact.

Asymptomatic cases inevitably distorting the COVID-19 epidemiologic reality. While a variety of studies on asymptomatic infection have been reported, the proportion of asymptomatic patients in confirmed COVID-19 cases is not well characterized. We conducted this meta-analysis to better understand the asymptomatic infection of COVID-19.

Two databases including PubMed and Embase were searched before 20 May 2020 following the PRISMA guideline. We included the following items: 

Records were identified through database searching. Confirmed COVID-19 was defined as one that had a throat-swab or other specimen tested positive for SARS-CoV2 using real-time RT-PCR assay. Asymptomatic infection was defined as patients who developed no symptoms such as fever, cough, or diarrhea during illness. A presymptomatic case was defined as a patient who has no symptoms at diagnosis time but developed symptoms during follow-up. Patients with no symptoms at screening point were defined as the number of asymptomatic patients plus the number of pre-Accepted Article symptomatic patients. Two authors (He and Guo) extracted data independently.

Disagreements were resolved by discussion until consensus was reached or by consulting a third author. Including criteria included: 1) Study objectives: Patients confirmed infected with SARS-CoV-2 (including adult, pediatric patients, and pregnant women). 2) Study types: prospective/retrospective cross-section cohort studies. There was no language restriction. Original articles reporting asymptomatic infection in confirmed COVID-19 patients were included for meta-analysis.

The methodological quality of the studies included in meta-analysis was assessed using an 11-item checklist which was recommended by Agency for Healthcare Research and Quality (AHRQ). If an item was answered 'NO' or 'UNCLEAR' it would be scored '0' and if it was answered 'YES', then the item scored '1'. Article quality was assessed as follows: low quality = 0-3; moderate quality = 4-7; high quality = 8-11.

After removing the duplicates, the abstract review was conducted through titles and abstracts. The following data were extracted: author, date of publication, site of study, study group, total number of people included in the study, age, sex, the number of 

All statistical analysis was performed using R version 3.6.2 (R Foundation for Statistical Computing) statistical software and Rstudio. Packages "meta", "metafor", and Accepted Article "weightr" were used. The proportion of asymptomatic infection was transformed using the logit transformation to make it conform to the normal distribution. A random effects model was applied to calculate the effect size and its 95% confidence interval (95% CI) by the method of moments (the Dorsmanin and Laird method) and as presented by Forest plot. The tau 2 and I 2 statistic was used to estimate the proportion of the observed heterogeneity. Studies containing the number of pre-symptomatic patients were extracted to analyze the proportion of pre-symptomatic infection in patients with no symptoms at screening point. Untransformed proportions and a random effects model by the method of moments (the Dorsmanin and Laird method) were applied to calculate the effect size and its 95% confidence interval (95% CI) and as presented by Forest plot.

Leave-One-Out Diagnostics and Regression Diagnostics were used to identify influential studies that pronouncedly contribute to heterogeneity in meta-analytic data.

Meta-Analysis via Linear was conducted to find the factor attributing to the overall heterogeneity, which was described in the article published by Wang in 2018 5 . Subgroup summary proportion analysis were conducted to explain the factor contributing to heterogeneity. Then subgroups forest plot was created by different study group: all, children, pregnant women or elderly people, and different place: China or outside of China. Publication bias was detected with funnel plot and Egger's regression test.

Study process is depicted in supplementary materials: Figure 

America: 3, Europe region: 3, UK: 2, Brunei: 1, Iraqi Kurdistan: 1, Thailand: 1, and Japan: 1). All studies were of high (27) or moderate (14) quality. There were no articles with low quality rating. 

There was a total of 10 studies containing the number of patients who were identified as silent COVID-19 patients but developed symptoms during follow-up. A total of 180 initial no-symptoms COVID-19 patients were included. The pooled percentage of pre-symptomatic infection among patients with no symptoms at screening point is 48.9% (95% CI: 31.6-66.2%) with heterogeneity noted among studies (p < 0.01, I 2 : 85%) ( Figure 2 ).

There were 24 studies of 48868 people in study cohorts from all age groups, 11 (Figure 3 ). There was a significant subgroup difference between the studies (p=0.0041).

The pooled prevalence of asymptomatic infection was 15.5% (95% CI: 8.8-25.7%) and 14.5% (95% CI: 9.8-21.1%) in studies from China and other countries respectively ( Figure 4 ). The p value between these two groups is 0.8313 with no significance. There was significant heterogeneity among the studies conducted in China (p<0.01; I 2 =98.3%) and fewer heterogeneity studies from other countries (p<0.01; I 2 =70.1%).

Leave-One-Out Diagnostics (Supplementary materials: Figure 2 Egger's regression test indicate that there may be publication bias (t=5.65, p < 0.0001).

Fifty-nine patients from 4 studies included in the meta-analysis 9,26-28 and 1 additional case series study 47 (26, 47) . In those two studies, 27.3% (3/26) of asymptomatic patients had reduced white blood cell count, 42.3% (11/26) of patients showed increased lactate dehydrogenase, and 11.5% (3/26) of patients recorded increased C-reactive protein.

Increased creatine kinase-MB, both decreased lymphocyte count and increased lymphocyte count were also recorded in those two studies. Noticeably, one study from Wuhan showed that 98/1021(9.6%) nucleic acid testing negative patients had lgG positive results, suggesting possible recovery from asymptomatic SARS-CoV-2 infection 54 . A study from Germany also demonstrates the importance of serological tests in COVID-19. In 5/316(1.6%) healthcare workers SARS-CoV-2-IgG antibodies could be detected. Four of the five subjects were tested negative for SARS-CoV-2 via PCR. One subject was not tested via PCR since he was asymptomatic 55 . All those results suggest that asymptomatic patients could use serological tests to detect COVID-19 infection.

Asymptomatic infection was believed to be less contagious as a consequence of a decreased virulence throughout the successive transmission, like SARS-CoV. In the study conducted by Schwierzeck et.al, the viral load of 6 asymptomatic patients is lower than 6 symptomatic cases 36 . This result was supported by a mass screening by Rivett et.al of health care workers as well as their contacts in the UK. Viral loads were significantly lower for 31 asymptomatic health care workers screening group than in those 30 individuals tested positive due to the presence of symptoms 42 . However, it's Accepted Article still too early to conclude that asymptomatic patients are less likely to transmit the virus.

Relatively high viral load was also detected in asymptomatic patients 51, 56 and the stool sample was tested positive in a well infant of COVID-19 51 , a man in his 20s 57 

Probing into asymptomatic infection proportion is a useful quantity to understand the true burden of disease transmission. In our meta-analysis, asymptomatic infection is 

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The present study was supported by the Shanghai Pujiang Pujiang Program (17PJD005) and the National Natural Science Foundation of China (81670528, 81672009, and 81871640).

The authors have declared that no competing interest exists.

The data that support the findings of this study are available from the corresponding author upon reasonable request.