Document text
Asymptomatic SARS-CoV-2 infection: A systematic
review and meta-analysis
Pratha Saha, Meagan C. Fitzpatricka,b, Charlotte F. Zimmera, Elaheh Abdollahic, Lyndon Juden-Kellyc,
Seyed M. Moghadasc, Burton H. Singerd,1, and Alison P. Galvania
aCenter for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520;bCenter for Vaccine Development and Global
Health, University of Maryland School of Medicine, Baltimore, MD 21201;cAgent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3,
Canada; anddEmerging Pathogens Institute, University of Florida, Gainesville, FL 32610
Contributed by Burton H. Singer, July 8, 2021 (sent for review May 19, 2021; reviewed by David Fisman and Claudio Jose Struchiner)
Quantification of asymptomatic infections is fundamental for
effective public health responses to the COVID 19 pandemic. Dis
crepancies regarding the extent of asymptomaticity have arisen
from inconsistent terminology as well as conflation of index andsecondary cases which biases toward lower asymptomaticity. Wesearched PubMed, Embase, Web of Science, and World Health Or
ganization Global Research Database on COVID 19 between Janu
ary 1, 2020 and April 2, 2021 to identify studies that reported silentinfections at the time of testing, whether presymptomatic or
asymptomatic. Index cases were removed to minimize representa
tional bias that would result in overestimation of symptomaticity.By analyzing over 350 studies, we estimate that the percentage ofinfections that never developed clinical symptoms, and thus were
truly asymptomatic, was 35.1% (95% CI: 30.7 to 39.9%). At the
time of testing, 42.8% (95% prediction interval: 5.2 to 91.1%) ofcases exhibited no symptoms, a group comprising both asymptomatic and presymptomatic infections. Asymptomaticity was signifi
cantly lower among the elderly, at 19.7% (95% CI: 12.7 to 29.4%)
compared with children at 46.7% (95% CI: 32.0 to 62.0%). Wealso found that cases with comorbidities had significantly lower
asymptomaticity compared to cases with no underlying medical
conditions. Without proactive policies to detect asymptomatic infections, such as rapid contact tracing, prolonged efforts for pandemiccontrol may be needed even in the presence of vaccination.
asymptomatic fraction |presymptomatic |silent transmission |
novel coronavirus |comorbidity
COVID 19 surveillance provides real time information about
the epidemiological trajectory of the pandemic, informing
risk assessments and mitigation policies around the world. Given
that COVID 19 surveillance systems predominantly rely onsymptom based screening, the prevalence of asymptomatic infec
tion is often not fully captured. Cross sectional surveys, such as
mass testing once an outbreak is identified, do not distinguish thetruly asymptomatic from the presymptomatic. Often, the follow up
period after testing is too brief to ascertain whether patients
subsequently develop symptoms. The percentage of silent infections identified by such studies is thus context specific, as it de
pends on the setting, phase of the epidemic, and efficiency of
contact tracing. By contrast, the prevalence of truly asymptomatic
infections should be stable across similar demographic settings,
regardless of epidemiological trajectory and contact tracing.
Compounded by ambiguities about the different clinical mani
festations of the disease, which can lead to misinterpretation ofclinical and epidemiological studies (1), there have been substantial aberrations in reports and media coverage claiming the
asymptomatic percentage to be as low as 4% (2, 3) or as high as 80
to 90% (4, 5). Similarly, the US Centers for Disease Control andPrevention guidelines for COVID 19 pandemic forecasting offer
wide bounds for the asymptomatic percentage, ranging from 10 to
70% (6).
Previous meta analyses of 41 studies (7), 13 studies (8), and 79
studies (9) estimate pooled asymptomaticity ranging from 16 to20%. Two met hodological issues limit the accuracy of these studies.
First, pooled asymptomaticity reported in these studies is likely bi
ased downward because they did not account for study designs
which have a higher representation of cases experiencing symptoms
(10). Second, one of the meta analyses (7) did not consider biases in
reported asymptomaticity that can arise from inadequate longitudinal follow up. Studies that assess the symptom profile only at the
time of testing or do not follow up symptoms for a sufficiently long
time period cannot distinguish presymptomatic from asymptomatic
infection, overestimating those that are truly asymptomatic.
Accurate estimates of true disease prevalence, including
asymptomatic infections, are essential to calculate key clinical
parameters, project epidemiological trajectories, and optimize
mitigation measures. Clinical evidence indicates that viral loadsamong asymptomatic and symptomatic infections may be com
parable (11 15). Unaware of their risk to others, individuals with
silent infections are likely to continue usual behavior patterns.
Accounting for silent severe acute respiratory syndrome corona
virus 2 (SARS CoV 2) infections in the assessment of diseasecontrol measures is necessary to interrupt community transmission
(16). Although the discrepancy between reported incidence and
seroprevalence gives a sense of the extent of asymptomaticity, not
Significance
Asymptomatic infections have been widely reported for COVID
19. However, many studies do not distinguish between the
presymptomatic stage and truly asymptomatic infections. We
conducted a systematic review and meta analysis of COVID 19literature reporting laboratory confirmed infections to deter
mine the burden of asymptomatic infections and removed index
cases from our calculations to avoid conflation. By analyzingover 350 papers, we estimated that more than one third of infections are truly asymptomatic. We found evidence of greater
asymptomaticity in children compared with the elderly, and
lower asymptomaticity among cases with comorbidities compared to cases with no underlying medical conditions. Greaterasymptomaticity at younger ages suggests that heightened
vigilance is needed among these individuals, to prevent spillover
into the broader community.
Author contributions: P.S., M.C.F., S.M.M., and A.P.G. designed research; P.S., M.C.F.,
C.F.Z., E.A., L.J.-K., S.M.M., B.H.S., and A.P.G. performed research; P.S., M.C.F., C.F.Z.,
E.A., L.J.-K., S.M.M., and A.P.G. analyzed data; and P.S., M.C.F., S.M.M., B.H.S., and
A.P.G. wrote the paper.
Reviewers: D.F., University of Toronto; and C.J.S., Fundacao Getulio Vargas.
The authors declare no competing interest.
This open access article is distributed under Creative Commons Attribution License 4.0
(CC BY).
See online for related content such as Commentaries.
1To whom correspondence may be addressed. Email: [email protected].
This article contains supporting information online at https://www.pnas.org/lookup/suppl/
doi:10.1073/pnas.2109229118/-/DCSupplemental .
Published August 10, 2021.
PNAS 2021 Vol. 118 No. 34 e2109229118 https://doi.org/10.1073/pnas.2109229118 |1o f1 2
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all symptomatic cases are reported, and not all asymptomatic cases
(for instance, those identified on the basis of exposure) are missed.
Consequently, it is not sufficient to simply compare the reported
cases to results from seroprevalence studies. We therefore conducted a systematic review and meta analysis of COVID 19 lit
erature reporting laboratory confirmed infections to estimate the
percentage of SARS CoV 2 infections that are truly asymptomatic. We also investigated differences in asymptomaticity with re
spect to age, sex, comorbidity, study design, publication date,
duration of symptom follow up, geographic location, and setting.
Results
We identified a total of 114,124 abstracts based on our search
criteria. After excluding duplicate and irrelevant studies, we
used 390 in our meta analyses (Fig. 1 and SI Appendix ,T a b l e
S2). Most studies were conducted in China ( n=104, 27%),
followed by the United States ( n=74, 19%), Italy ( n=21,
5%), and South Korea ( n=13, 3%). These studies included a
total of 104,058 laboratory confirmed COVID 19 cases, of
which 25,050 exhibited no symptoms at the time of testing and
7,220 remained asymptomatic. We identified 170 studies
that reported asymptomatic infections (11 13, 17 183), 332studies that reported silent infections at the time of testing
(1012, 14, 17 20, 23 27, 31, 32, 35 40, 42 44, 46, 47, 49, 50,
52, 53, 56 58, 60 66, 68, 69, 73 75, 77 79, 81, 84, 87, 90 94,
97, 99, 101, 103, 104, 106, 111, 113 116, 118, 119, 121 123,125, 127, 128, 131, 133, 135, 137, 138, 140, 143, 145, 146,148 152, 154, 156, 158, 160 163, 166 170, 172 174, 176, 177,
179, 180, 182 405), and 143 that delineated presymptomatic and
asymptomatic infections by following up with those silently infected (11 13, 17 20, 22 29, 31 33, 35 40, 42 44, 46 54, 56 70,
72 75, 77 81, 83, 84, 87, 89 94, 96, 97,
99, 101, 103, 104, 106 109,
111 119 , 121 125, 127 129, 131, 133, 135 138, 140, 141, 143,
145 156, 158 164, 166 170, 172 174, 176 183). Among the
studies that reported follow up of clinical symptoms after testing,11.0% reported at time points at 1 wk to 2 wk, 33.8% reported at2 wk to 3 wk, and 55.2% reported longer than 3 wk. Among thestudies that reported asymptomatic infections, 58.8% reported
zero index cases, either because cases were identified through a
screening design or because the study only reported the cases thatwere identified through contact tracing. Of the 41.2% studies thatreported data on index cases, these included household members,long term care residents, members of the community, or travelersreturning from COVID 19 hotspots ( SI Appendix ,T a b l eS 1 ).
114,108 articles identified by database search
6,888 records screene d by title and abstract107,236 duplicates removed
916 full-text articles assessed for eligibility
390 articles included in meta-ana lysis
170 in meta-analysis of asymptomatic percentage
332 in meta-analysis of silent infections at the time of testing615 articles included in systematic review16 articles identified from citations of relevant articles
5,972 articles excluded based on title and abstract
301articles excluded after full-text screening61 modelling studies39 reviews25 incomplete symptom assessment26 incomplete laboratory confirma tion of infecti on
20 unpublished studies
11 less than 2 cases21 English translation not available3 study not on humans1 retracted
11 full text unavailable
29 commentaries37 no silent infections reported16 duplicates1 study provided only Bayesian estimate
225 articles excluded for not identifying index case(s)
Fig. 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram showing the numbers of studies screened and included
in the meta-analysis.
2o f1 2 |PNAS Sah et al.
https://doi.org/10.1073/pnas.2109229118 Asymptomatic SARS-CoV-2 infection: A systematic review and meta-analysis
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A summary of the risk of bias assessment is presented in SI Ap
pendix ,T a b l eS 2 . Out of the 170 studies included in the calculation
of asymptomaticity, 75 had low risk of bias, 10 had moderate risk
of bias, and 85 had serious risk of bias.
The percentage of cases that were truly asymptomatic among
laboratory confirmed cases was 35.1% (95% CI: 30.7 to 39.9%;
Fig. 2). By contrast, a larger percentage of cases exhibited no
symptoms at the time of testing (42.8%, 95% prediction interval:5.2 to 91.1%) due to mischaracterization of presymptomaticcases as asymptomatic. To investigate the degree of mischarac
terization, we considered a subset of studies that reported
symptoms both at the time of testing and a minimum of 7 d after.Within this subset of studies, 31.8% (95% prediction interval: 5.6
to 78.7%) of cases exhibiting no symptoms at the time of testing
progressed to develop symptoms. The percentage of trulyasymptomatic cases among these studies was therefore 36.9%(95% CI: 31.8 to 42.4%), similar to that estimated for all studies
reporting asymptomatic infections.
These estimates were obtained after removing index cases
from our calculations, correcting bias toward overrepresentation
of symptomatic cases that would lead to underestimatio n of asymp
tomaticity. Without excluding index cases, estimates of asymptomaticinfections using our two complementary approaches would be 27.8%(95% CI: 24 3 to 31.7%) and 29.4 (95% CI: 25 2 to 33.9%). Toevaluate the impact of sample selection bias arising from higher
participation among those experiencing symptoms, we next restricted
our analysis to 25 studies in which complete screening of every individual present at the setting was performed. The pooled asymp
tomaticity among this smaller subset of studies was 47.3% (95% CI:
34.0 to 61.0%).
We found a statistically significant trend toward a lower
asymptomatic percentage with increasing age ( P<0.01; Table 1).
In pairwise comparisons, the asymptomatic percentage was significantly lower for the elderly, at 19.7% (95% CI: 12.7 to 29.4%)compared with 46.7% (95% CI: 32.0 to 62.0%) for children ( P<
0.01). Asymptomaticity also varied across study settings ( P=0.03;
Table 1). In particular, studies on long term care facilities reportedlower asymptomaticity compared with studies on healthcare facilities (P =0.04) and household transmission ( P=0.04). We
found no association between asymptomatic percentage and
geographic location, study design, follow up duration, or publi
cation date (Table 1). We found that asymptomaticity in maleswas similar to that in females (log incidence rate ratio [IRR] 0.09,95% CI 0.07 to 0.25, P=0.27; SI Appendix ,F i g .S 1 ). Cases with
comorbidities had lower asymptomaticity compared to cases withno underlying medical conditions (log IRR 0.43, 95% CI 0.82
to0.04, P=0.03; SI Appendix ,F i g .S 2 ).
Egger ’s test for asymptomatic percentage was significant ( P=
0.04; SI Appendix ,F i g .S 3 ), providing evidence of potential small
study effects. We therefore conducted a sensitivity analysis byexcluding studies with relatively small sample sizes (less than 10
infections). The pooled estimate in the restricted meta analysis
(33.1%; 95% CI: 28.0 to 38.5%) was similar to our original estimate, suggesting that our estimates are robust to publication bias.
Discussion
The SARS CoV 2 pandemic infected more than 80 million
people within a year and is still spreading rapidly despite widespread control efforts. The elements of the global response are
similar to those deployed during the SARS CoV 1 outbreak:
detecting new cases through symptom based surveillance, subsequent testing, and isolation of confirmed cases. In 2002, these
measures achieved containment within 8 mo and fewer than
8,500 cases worldwide. Given that the aerosol and surface stability of the two viruses are similar (406), a crucial differencebetween the two outbreaks could be the role of silent infections
in propagating transmission chains. Multiple clinical studies have
indicated that viral loads in asymptomatic and symptomaticinfections of COVID 19 may be similar (11 14, 354). Further
more, the presymptomatic phase of SARS CoV 2 is highly in
fectious (53), and transmission from those in this phase may be
responsible for more than
50% of incidence (16). This is aStudy
Random effects model
He e ogenei y I2 = 94%1 92 = 2942 54 (p = 0)Bla n 2020b
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Lytras 2020R vera 2020Bae 2020Green 2021Gupta 2020bHasanoglu 2020Huang 2020cJoshi 2020Liu 2020fLuo 2020bPat l 2021Saidy 2020Sha ma 2021bShen 2020bSzegedi 2020Asymptomatic
0 0 0 0 0 0 0
15
4 4 2 8 5 3 8
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2 1
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16 17
3 6
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3 3
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7
193
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50 89
3
11 33
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27 58 16 14
1935
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20 41 67 19 13 91
5 6
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6
22 19 15 16 25
3 5 5 3 2 2 1Cases
17272 38 12
2
37
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568 108
95 46
175
82 48
127 217
27 12
161 111
18 69
138 138
23 46
178
28
7
146
34 46
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38 76
493
6
12 48 59 39 11 11 11 60 32
736
30 10 80 10 10 66
131
14 14
279
4 4 4
40
4
20
8 4 4
43 26
710
11 11 72 18
7 7 7 7
172 297
10 35
104
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2617
12 26 53 86 24 16
111
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6
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3 5 5 3 2 2 1
02 0 4 0 6 0 8 0 1 0 0
PercentagePercentage
35 10 00 00 00 00 00 00 02 63 74 24 34 66 16 26 37 47 48 38 79 0
11 111 611 612 313 013 014 014 314 314 414 715 215 315 815 816 216 716 716 716 917 918 218 218 218 318 819 820 020 020 020 020 021 221 421 421 422 625 025 025 025 025 025 025 025 025 025 626 927 227 327 327 827 828 628 628 628 629 130 030 031 431 733 333 333 333 333 333 333 333 333 736 837 538 239 240 040 040 040 540 841 042 142 342 942 943 245 245 545 650 050 050 050 050 050 050 050 051 953 553 8
54 5
56 757 157 157 157 158 358 558 860 0
60 0
62 262 462 563 564 366 766 766 7
66 7
66 771 171 672 773 773 975 076 977 477 979 281 282 083 385 787 588 5
100 0100 0100 0100 0100 0100 0100 0100 0100 0100 0100 0100 0100 095% CI
[30 7 39 9][ 0 0 9 3]
[ 0 0 26 5][ 0 0 84 2]
[ 0 0 9 5]
[ 0 0 70 8][ 0 0 52 2][ 0 0 60 2]
[ 1 5 4 3][ 1 0 9 2]
[ 1 2 10 4][ 0 5 14 8]
[ 2 0 8 8]
[ 2 0 13 7][ 1 3 17 2][ 2 8 12 0][ 4 3 11 7][ 0 9 24 3][ 0 2 38 5][ 4 8 14 2][ 4 4 15 9][ 1 4 34 7][ 5 1 21 6][ 6 8 18 1][ 7 3 19 0][ 2 8 33 6][ 4 9 26 3][ 9 3 20 0][ 4 0 32 7][ 0 4 57 9][ 9 1 21 1][ 5 0 31 1][ 6 3 28 9][ 9 2 23 4][ 6 0 31 3][ 8 4 26 0]
[13 1 19 8]
[ 0 4 64 1][ 2 1 48 4][ 7 5 30 2][ 8 4 29 0][ 7 5 33 5][ 2 3 51 8][ 2 3 51 8][ 2 3 51 8][ 9 5 30 4][ 7 2 36 4]
[17 0 22 9]
[ 7 7 38 6][ 2 5 55 6]
[11 9 30 4]
[ 2 5 55 6][ 2 5 55 6]
[12 1 33 0][14 7 29 4]
[ 4 7 50 8][ 4 7 50 8]
[17 8 27 9]
[ 0 6 80 6][ 0 6 80 6][ 0 6 80 6]
[12 7 41 2]
[ 0 6 80 6][ 8 7 49 1][ 3 2 65 1][ 0 6 80 6][ 0 6 80 6]
[13 5 41 2][11 6 47 8][23 9 30 6]
[ 6 0 61 0][ 6 0 61 0]
[17 9 39 6]
[ 9 7 53 5][ 3 7 71 0][ 3 7 71 0][ 3 7 71 0][ 3 7 71 0]
[22 4 36 5][24 8 35 5]
[ 6 7 65 2]
[16 9 49 3][22 9 41 6]
[ 9 9 65 1]
[13 3 59 0][24 3 43 4]
[ 4 3 77 7][ 9 9 65 1][ 7 5 70 1][ 0 8 90 6][ 9 9 65 1]
[27 3 40 5][16 3 61 6]
[ 8 5 75 5]
[22 2 56 4][28 4 50 9][12 2 73 8][12 2 73 8]
[ 5 3 85 3]
[24 8 57 9][29 3 53 2][34 4 47 9][20 3 66 5][31 2 54 0][17 7 71 1][17 7 71 1][40 2 46 1][33 5 57 3][24 4 67 8][37 6 53 7]
[ 6 8 93 2][ 1 3 98 7]
[11 8 88 2]
[ 1 3 98 7]
[23 0 77 0][31 3 68 7][24 7 75 3]
[ 6 8 93 2]
[50 2 53 7][48 7 58 1]
[25 1 80 8]
[47 1 61 7]
[47 6 65 5][28 9 82 3][18 4 90 1][18 4 90 1][37 2 75 5][27 7 84 8][45 6 70 6][40 7 75 4][26 2 87 8]
[14 7 94 7]
[54 9 69 2][56 4 68 1][24 5 91 5][54 9 71 6][35 1 87 2][41 0 86 7][22 3 95 7][29 9 92 5][34 9 90 1][22 3 95 7][54 1 84 6][60 5 81 1][49 8 89 3][48 8 90 9][72 2 75 6][42 8 94 5][56 4 91 0][63 8 87 7][67 7 86 1][57 8 92 9][54 4 96 0][73 6 88 6][35 9 99 6][42 1 99 6][73 2 95 8][77 8 95 3]
[54 1 100 0][84 6 100 0][82 4 100 0][78 2 100 0][79 4 100 0][86 3 100 0][29 2 100 0][47 8 100 0][47 8 100 0][29 2 100 0][15 8 100 0][15 8 100 0]
[ 2 5 100 0]Weights
100 0%0 3%0 3%0 2%0 3%0 2%0 3%0 2%0 8%0 7%0 6%0 5%0 7%0 7%0 6%0 7%0 8%0 5%0 4%0 8%0 7%0 5%0 7%0 8%0 8%0 6%0 7%0 8%0 6%0 4%0 8%0 7%0 7%0 8%0 7%0 8%0 8%0 4%0 5%0 7%0 7%0 7%0 5%0 5%0 5%0 7%0 7%0 8%0 7%0 5%0 8%0 5%0 5%0 8%0 8%0 6%0 6%0 8%0 3%0 3%0 3%0 7%0 3%0 6%0 5%0 3%0 3%0 7%0 7%0 8%0 6%0 6%0 8%0 6%0 5%0 5%0 5%0 5%0 8%0 8%
0 6%
0 7%0 8%0 6%0 7%0 8%0 5%0 6%0 5%0 3%0 6%0 8%0 7%0 5%0 7%0 8%0 6%0 6%0 4%0 7%0 8%0 8%0 7%0 8%0 6%0 6%0 8%0 8%
0 7%
0 8%0 4%0 3%0 5%0 3%0 6%0 7%0 7%0 4%0 8%0 8%0 6%
0 8%
0 8%0 6%0 5%0 5%0 7%0 6%0 8%0 7%0 6%
0 4%
0 8%0 8%0 5%0 8%0 6%0 7%0 5%0 5%0 6%0 5%0 7%0 8%0 7%0 6%0 8%0 6%0 7%0 7%0 8%0 7%0 6%0 8%0 4%0 4%0 7%0 7%0 3%0 3%0 3%0 3%0 3%0 3%0 2%0 3%0 3%0 2%0 2%0 2%0 2%
Fig. 2. Pooled percentage of laboratory-confirmed COVID-19 cases which
remained asymptomatic. Studies that did not report follow-up of silent in-
fections or failed to identify index cases were excluded from the analysis.
Sah et al. PNAS |3o f1 2
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striking difference from SARS CoV 1 in which the infectious
ness peaked at 12 d to 14 d after symptom onset (407). Althoughsilent infections of SARS CoV 1 were reported, no knowntransmission occurred from silently infected or even mildlysymptomatic SARS cases.
Since the emergence of COVID 19, there has been much
speculation about the silent transmission of the disease. Crosssectional studies testing exposed individuals who do not exhibitsymptoms often conflate asymptomatic infections with those inthe presymptomatic phase, leading to substantial overestimationof asymptomatic infection. Longitudinal studies without sufficient follow up similarly lead to overestimation of asymptomaticity (408). Additionally, inconsistent use of terminology has ledto confusion, particularly when distinguishing infections which aresilent at the time of testing from those which are truly asymptomatic (4, 5). A previous meta analysis, for example, incorrectlyincludes infections in the presymptomatic phase to calculatepooled estimate of asymptomatic percentage (409). By contrast,several studies conducted early in the pandemic reported fewasymptomatic infections, primarily due to restrictive testing criteria which focused on testing of severe cases that required hospitalization (410, 411). Inaccuracy in either direction is detrimentalfor public health. Overestimation of asymptomaticity engenders aperception that SARS CoV 2 is less virulent, whereas underestimation skews key epidemiological parameters such as infection
fatality rate and hospitalization rate upward, leading to suboptimal
policy decisions.
To robustly estimate the asymptomatic percentage from studies
with varying degrees of methodological vigor, we conducted twoseparate meta analyses. In the first analysis, we estimated theasymptomatic percentage as 35.1% (95% CI: 30.7 to 39.9%), byincluding all studies with a duration of follow up sufficient toidentify asymptomatic infections. In the second analysis, we onlyincluded studies that both delineated silent infections at the timeof testing and conducted follow up to distinguish the presymptomatic stage from asymptomatic infections. With this analysis, weestimated the asymptomatic percentage as 36.9% (95% CI: 31.8 to42.4%). Our estimates have overlapping CIs, which suggests thatour pooled analysis is robust to methodological differences insymptom assessment. Our estimates are higher than the 15.6%(95% CI: 10.1 to 23.0%), 17% (95% CI: 14 to 20%), and 20%(95% CI: 17 to 25%) reported by three previous meta analysesusing 41 studies (7), 13 studies (8), and 79 studies (9). In largepart, this difference arises because we excluded index cases fromour calculation, correcting a bias that leads to underestimation ofasymptomaticity. Our estimates of asymptomatic percentagewithout excluding index cases were 27 8% and 29.4%, for our twoapproaches. The lower bounds of 24% and 25%, for the twoanalyses overlaps with the range of the previous largest metaanalysis. Compared with other respiratory infections, the lower
bound of our analyses is higher than the 13 to 19% estimated for
influenza (412, 413), and the 13% for SARS CoV 1 (414).
We found that 42.8% (95% prediction interval: 5.2 to 91.1%)
of infections were silent at the time of testing. These cases havebeen incorrectly referred to as asymptomatic in previous studies(4, 5, 189, 239). This rate is context specific, as it is likely influenced by the association between symptomaticity and the timewindow when an infection is detectable or tested by RT PCR.Additionally, the proportion of silent infections at the time oftesting is highly sensitive to the efficiency of contact tracing. Ifmost contacts are identified and tested swiftly, then nearly allinfections will be silent at the time of testing. By contrast, ifcontact tracing is slow and incomplete, then a larger fraction of
individuals will have developed symptoms by the time they are
approached for testing, and a smaller proportion of those testedwill be symptom free. Reports of silent infections at the time oftesting are also likely impacted by epidemic trajectory largely dueto the predominance of recent infections in samples taken duringTable 1. Pooled estimates for percentages of all positive cases which remain asymptomatic
stratified by age, gender, publication date, symptom follow up duration, study design,
and study setting
n Estimate (%) CI (95%) Pvalue (test of overall effect)
Age class <0.01
Children (0 y to 18 y) 18 46.7 32.0 to 62.0
Adults (19 y to 59 y) 17 32.1 22.2 to 43.9Elderly ( ≥60 y) 17 19.7 12.7 to 29.4
Study design 0.10
Population screening 102 38.2 32.0 to 44.8Others 68 30.7 24.8 to 37.4
Publication date 0.18
January April 2020 27 34.8 23.6 to 47.9
May August 2020 69 29.5 24.2 to 35.4
September December 2020 50 41.1 31.4 to 51.4January April 2021 24 38.4 25.6 to 53.1
Symptom follow up duration 0.07
7 d to 21 d 73 40.6 32.9 to 48.6
21+ d 90 32.1 27.0 to 37.7
Setting 0.03
Community 39 34.0 25.3 to 43.8
Healthcare facility 81 38.5 31.6 to 45.9
Household 18 42.5 30.9 to 54.9
Long term care facility 15 17.8 9.7 to 30.3Others 17 38.4 23.5 to 55.9
Geographic location 0.78
China 50 33.6 26.1 to 42.0
United States 28 33.3 22.6 to 46.1
Others 92 36.8 30.4 to 43.6
Stratifications with statistically significant subgroup differences ( P<0.05) are in bold.
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the growth phase, in contrast with a higher proportion of older
infections in samples taken during the declining phase. Unbiased
measures of asymptomaticity, on the other hand, should be con
sistent across similar demographic settings, regardless of contacttracing and epidemic trajectory.
Several gaps remain in our understanding of asymptomatic
carriage of COVID 19. Particularly, it is unclear why certaininfections remain asymptomatic while the majority developclinical symptoms. Our results indicate that children have greaterasymptomaticity compared to the elderly. We also found that
cases with comorbidities have lower asymptomaticity compared
with cases with no underlying medical conditions. Additionally,studies on long term care facilities reported lower asymptoma
ticity compared to other study settings. Given that the risk of
severe illness is high among the elderly, the age associationidentified by our study implies that absence of symptoms maycorrelate with the tendency of developing milder symptoms.
Case severity in SARS CoV 2 patients has been linked to a cy
tokine storm which occurs more frequently in elderly patients(415, 416). Genetic (417), environmental risk factors, sex linkeddifferences (418), and cross reactive immunity (419) might also
contribute, although no studies have unequivocally demon
strated their association with either symptom status or severity.
Higher representation of asymptomatic SARS CoV 2 infec
tions among younger people has grave implications for control
policies in daycares, schools, and universities. Settings with close,
extensive contact among large groups of younger individuals areparticularly susceptible to superspreader events of COVID 19
which may go undetected if surveillance focuses on symptomatic
cases. This close congregation of relatively large groups similarlyexplains why influenza, mumps, and measles often spread morerapidly in schools and college campuses than in the broader
community (420 422). As schools and universities convene in the
midst of the COVID 19 pandemic, campus outbreaks are in
creasingly reported (423). Although COVID 19 severity is loweramong young people, campus transmission with a large unde
tected component could more easily bridge to the rest of the
population, fueling local and regional resurgence.
Our meta analyses are subject to limitations, many related to the
unprecedented pace of clinical research since the emergence of
COVID 19. First, we found considerable heterogeneity in the
percentage of asymptomatic infections. Subgroup analysis revealedthat studies with longer follow up reported lower asymptomaticity.Second, all reports of asymptomatic cases are confounded by the
subjective and shifting definition of symptoms. For instance, the list
of clinical manifestations associated with COVID 19 has expandedsince the initial definitions (424). These changing definitions im
pact the classification of infections as asymptomatic or silent, and
the more limited suite of symptoms initially considered indicationsof COVID 19 could bias early studies toward higher percentages inthese categories. Nonetheless, we found no statistically significant
differences in asymptomatic percentage when we stratified studies
based on publication date. Third, in the studies included in ourmeta analysis, it is possible that early mild symptoms occurringbefore a positive PCR test might go unrecorded, biasing the studies
toward higher asymptomaticity. Fourth, although we corrected for
the bias introduced by inclusion of predominantly symptomaticindex cases, our estimates are still likely affected by sample selection bias, as participation is expected to be highest among those
experiencing symptoms (10). Additionally, factors such as socio
economic position, occupation, ethnicity, place of residence, internet and technological access, and scientific and medical interest
could have contributed to nonrandom enrollment (425). To eval
uate the effect of these biases, we calculated the pooled asymptomatic percentage using 25 studies that reported screening of allindividuals in the study setting. Asymptomaticity among this
smaller subset of studies was 47.3% (95% CI: 34.0 to 61.0%), with
CIs that overlap with our primary analysis but the point estimate ishigher than the base case CI. We therefore cannot rule outnonrandom sampling as a source of bias for estimation of the
asymptomatic percentage.
In our meta analysis, we excluded 225 studies that did not
identify index cases. Additionally, 223 studies reported silent
infections at the time of testing but were excluded from analysis
of asymptomaticity for not reporting symptom assessment during
follow up for at least 7 d or for not specifying the duration offollow up. Large scale longitudinal surveys should prioritize the
inclusion of these data to facilitate accurate estimation of the
asymptomatic percentage. At minimum, such studies should report the number of index cases among their study participants,the clinical symptom status of individuals at the time of testing,
the duration of symptom follow up, and symptom status during
the follow up. Ideally, studies would additionally provide a fullsymptom profile both at time of testing and by the end of followup, to facilitate reclassification as case definitions are updated.
Estimating the extent of COVID 19 asymptomaticity is critical
for calculating key epidemiological characteristics, quantifying thetrue prevalence of infection, and developing appropriate mitigationefforts. This meta analysis also establishes a baseline for asympto
maticity, prior to widespread vaccination coverage. Amid concerns
that vaccines may be less protective against infection than disease,widespread vaccination coverage may soon lead to a rise in the
percentage of infections that present asymptomatically. The high
prevalence of silent infections even at baseline, coupled with theirtransmission potential, necessitates accelerated contact tracing,testing, and isolation of infectious individuals, as symptom based
surveillance alone is inadequate for control.
Methods
Definition of Silent, Asymptomatic, and Presymptomatic Infection. We defined
silent infections as laboratory-confirmed COVID-19 cases that did not exhibit
any clinical symptoms, including fever, upper respiratory symptoms, pneu-monia, fatigue, headache, myalgia, dehydration, or gastrointestinal dys-
function, at the time of testing. Asymptomatic infections include those that
continued to exhibit no clinical symptoms during at least 7 d of follow-upafter testing. Presymptomatic cases were those that developed clinicalsymptoms subsequent to initial testing. The presymptomatic stage beginswith the start of infectiousness and ends with the onset of symptoms (426).
Search Strategy and Selection Criteria. We conducted a systematic review to
identify studies reporting laboratory-confirmed COVID-19 cases without symp-
toms at the time of testing. Our search was inclusive of all studies that provided
data regarding cases that were asymptomatic, presymptomatic, or both. We fi-
nalized systematic search criteria on May 1, 2020, and study collection was ini-tiated by searching PubMed, EMBASE, We b of Science, and the World Health
Organization Global Research Database on COVID-19 (427) weekly from incep-tion through April 2, 2021, with no language restrictions. Our search termsincluded “SARS-CoV-2, ”“novel coronavirus, ”“coronavirus 2019,”“ COVID-
19,”“ COVID 2019 ”AND “asymptomatic, ”“no symptoms, ”“presymptomatic, ”
“paucisymptomatic, ”“sub-clinical, ”“silent transmission, ”“silent infection, ”
“without any symptoms, ”and “without symptoms” (SI Appendix,T a b l eS 1 ). All
studies of any design that included these terms, were published after January 1,2020, and described the symptom status of COVID-19 cases were considered inthe screening step. No changes were made to the search criteria after the studyinitiation on May 1, 2020. The study protocol is available in the Open Science
Framework online public database, registration DOI: 10.17605/OSF.IO/ZCJ62.
All articles were double-screened (by P.S. and C.F.Z.) based on the title and
abstract. Studies were excluded if they were 1) duplicate publications, 2)
editorials, reviews, discussions, or opinion pieces, 3) ambiguous about thepresence of silent infection, 4) modeling studies without primary data, 5)
based on fewer than two cases, 6) not conducted in humans, or 7) retracted.
All identified full-text articles were reviewed by P.S. and C.F.Z. For each full-text article, we manually searched references for additional relevant studies.Studies included in our meta-analysis either reported laboratory confirma-tions of COVID-19 at a single time point, providing a snapshot of diseaseprevalence in the study subjects, or reported longitudinal data over a period
of follow-up.
Risk of bias was assessed independently by two authors, and consensus was
achieved through discussion. We adapted the ROBINS-I checklist (428) to
include seven items: 1) enrollment of all patients satisfying the criteria for
Sah et al. PNAS |5o f1 2
Asymptomatic SARS-CoV-2 infection: A systematic review and meta-analysis https://doi.org/10.1073/pnas.2109229118
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BIOLOGY
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inclusion, 2) enrollment of cases regardless of symptom status, 3) confir-
mation of cases using RT-PCR, 4) symptoms monitored by clinicians ratherthan self-reporting, 5) symptom assessment at the end of the follow-upperiod, 6) symptom follow-up duration of at least 7 d, and 7) loss to
follow-up less than 5%.
Data Analysis. We conducted a meta-analysis using the studies identified
through our systematic review to determine the prevalence of those truly
asymptomatic among infected individuals. To delineate true asymptoma-ticity from the combination of asymptomatic and presymptomatic infec-tions, we pursued two complementary analyses: 1) a single-step analysisbased on reports of those who were asymptomatic at the end of a follow-upperiod and 2) a two-step analysis first evaluating the percentage of infec-
tions without symptoms at the time of testing and then assessing asymp-
tomaticity by subtracting those that progressed to develop symptoms. In thesingle-step analysis, we calculated asymptomaticity as the percentage ofconfirmed COVID-19 cases that continued to exhibit no clinical symptoms forat least 7 d after testing, whether or not symptom status was reportedspecifically at the time of testing. In the two-step analysis, we focused on a
subset of studies that distinguished asymptomatic cases from those that
were presymptomatic by reporting symptoms at time of testing as well asconducting follow-up of symptoms for at least 7 d after testing. In bothanalyses, we removed index case(s) from the denominator of our calcula-tions to minimize representational bias that would result in overestimationof symptomaticity. As a sensitivity analysis, we repeated our calculationsincluding index cases. For studies that did not follow a population screening
design, we assumed that single infections without an epidemiological link
were necessarily detected due to their symptoms. Therefore, we subset thecalculations to include only those infections which were part of a cluster.
To calculate pooled estimates, study outcomes were logit transformed,
each study was assigned a weight using the inverse variance method (429),the DerSimonian −Laird estimator was applied to evaluate between-study
variance (430), and the Clopper Pearson method was used to determineCIs (431). Given heterogeneity in asymptomatic percentages estimatedacross studies, we used a random-effects meta-analysis model, applying theHartung and Knapp (432) method to adjust test statistics and CIs for therandom effect. We evaluated small-study effects visually with a contour-enhanced funnel plot and statistically with Egger ’s test (433). As a sensitiv-
ity analysis, we excluded studies with a small sample size ( <10 infections),
and we considered whether their removal impacted the pooling of results.We conducted subgroup analysis stratified by age class, study design
(population screening or not), publication date, duration of symptom follow-
up, geographic location, and setting (community, healthcare facility, house-
hold, long-term care facilities, and other which encompassed schools, ships,
conference, call centers, labor and delivery units, homeless shelters, and de-tention facilities). For subgroup analysis involving age class, we selected studieswhere all confirmed cases were either children (0 y to 18 y), adults (19 y to 59 y)
or the elderly ( ≥60 y). We evaluated sex-based differences in asymptomaticity
by selecting only those studies that stratified asymptomatic cases with respect
to sex. For each of these studies we calculated the IRR, which was the ratio ofthe asymptomatic percentage in males relative to that in females. A similar
analysis was performed to evaluate the asymptomaticity in cases with
comorbidity relative to those without.
We next evaluated the impact of sample selection bias arising from higher
participation among those experiencing symptoms in studies with voluntaryparticipation. In this analysis, we calculated the pooled asymptomaticity afterrestricting to a smaller subset of studies that performed screening of everyindividual at the study setting. To avoid age-dependent bias in asympto-
maticity, we removed studies where all participants belonged to a single age
class (children, adults, or the elderly). Out of the 25 studies selected, 7 studiesperformed screening of all close household contacts (64, 80, 83, 103, 117,131), 3 screened all flight passengers (28, 84, 91), and 2 screened all members
of a tourist/pilgrim group (94, 129). Others were based on screening of
healthcare workers (25, 110), inpatients admitted for non −COVID-19 reasons
(19, 50, 59, 72, 108, 113), rigorously community screening (82, 166), travelers(18, 180), and those associated with a detention facility (92).
The meta-analysis and subgroup analyses were conducted using the
metaprop function from the R package meta. Meta-analyses of sex-basedand comorbidity-based differences in asymptomaticity were performed us-ing the rma function from the R package metafor.
Data Availability. All study data are included in the article and SI Appendix .
ACKNOWLEDGMENTS. A.P.G. acknowledges funding from NSF Expeditions
Grant 1918784, NIH Grant 1R01AI151176-01, NSF Grant RAPID-2027755, and
the Notsew Orm Sands Foundation. S.M.M. was supported by the CanadianInstitutes of Health Research [OV4 170643, COVID-19 Rapid Research] and
Natural Sciences and Engineering Research Council of Canada Emerging In-fectious Diseases Modelling Initiative (NSERC EIDM), Mathematics for Public
Health (MfPH) grant.
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