Byambasuren Oyungerel, Cardona Magnolia, Bell Katy, Clark Justin, McLaws Mary-Louise, Glasziou Paul
Institute for Evidence-Based Healthcare, Bond University, Gold Coast, Queensland, Australia.
School of Public Health, University of Sydney, Sydney, New South Wales, Australia.
J Assoc Med Microbiol Infect Dis Can. 2020 Dec 31;5(4):223-234. doi: 10.3138/jammi-2020-0030. eCollection 2020 Dec.
Knowing the prevalence of true asymptomatic coronavirus disease 2019 (COVID-19) cases is critical for designing mitigation measures against the pandemic. We aimed to synthesize all available research on asymptomatic cases and transmission rates.
We searched PubMed, Embase, Cochrane COVID-19 trials, and Europe PMC for primary studies on asymptomatic prevalence in which (1) the sample frame includes at-risk populations and (2) follow-up was sufficient to identify pre-symptomatic cases. Meta-analysis used fixed-effects and random-effects models. We assessed risk of bias by combination of questions adapted from risk of bias tools for prevalence and diagnostic accuracy studies.
We screened 2,454 articles and included 13 low risk-of-bias studies from seven countries that tested 21,708 at-risk people, of which 663 were positive and 111 asymptomatic. Diagnosis in all studies was confirmed using a real-time reverse transcriptase-polymerase chain reaction test. The asymptomatic proportion ranged from 4% to 41%. Meta-analysis (fixed effects) found that the proportion of asymptomatic cases was 17% (95% CI 14% to 20%) overall and higher in aged care (20%; 95% CI 14% to 27%) than in non-aged care (16%; 95% CI 13% to 20%). The relative risk (RR) of asymptomatic transmission was 42% lower than that for symptomatic transmission (combined RR 0.58; 95% CI 0.34 to 0.99, = 0.047).
Our one-in-six estimate of the prevalence of asymptomatic COVID-19 cases and asymptomatic transmission rates is lower than those of many highly publicized studies but still sufficient to warrant policy attention. Further robust epidemiological evidence is urgently needed, including in subpopulations such as children, to better understand how asymptomatic cases contribute to the pandemic.
了解2019冠状病毒病(COVID-19)真正无症状病例的流行情况对于制定应对该大流行的缓解措施至关重要。我们旨在综合所有关于无症状病例和传播率的现有研究。
我们在PubMed、Embase、Cochrane COVID-19试验库和欧洲生物医学文献数据库(Europe PMC)中搜索关于无症状流行率的原始研究,其中(1)样本框架包括高危人群,(2)随访时间足以识别症状出现前的病例。荟萃分析使用固定效应模型和随机效应模型。我们通过结合来自流行率和诊断准确性研究的偏倚风险工具的问题来评估偏倚风险。
我们筛选了2454篇文章,纳入了来自七个国家的13项低偏倚风险研究,这些研究对21708名高危人群进行了检测,其中663人呈阳性,111人无症状。所有研究均使用实时逆转录聚合酶链反应检测进行确诊。无症状比例在4%至41%之间。荟萃分析(固定效应)发现,无症状病例的总体比例为17%(95%置信区间14%至20%),老年护理机构中的比例(20%;95%置信区间14%至27%)高于非老年护理机构(16%;95%置信区间13%至20%)。无症状传播的相对风险(RR)比有症状传播低42%(合并RR 0.58;95%置信区间0.34至0.99,P = 0.047)。
我们对COVID-19无症状病例流行率和无症状传播率的六分之一估计低于许多广为宣传的研究,但仍足以引起政策关注。迫切需要进一步有力的流行病学证据,包括在儿童等亚人群中的证据,以更好地了解无症状病例如何推动大流行。