Susceptibility to SARS-CoV-2 Infection Among Children and Adolescents Compared With Adults: A Systematic Review and Meta-analysis | Adolescent Medicine | JAMA Pediatrics | JAMA Network
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Figure 1.  PRISMA Flow Diagram for Search
PRISMA Flow Diagram for Search
Figure 2.  Pooled Estimate of Odds of Being an Infected Contact Among Children and Adolescents Compared With Adults for All Contact-Tracing Studies
Pooled Estimate of Odds of Being an Infected Contact Among Children and Adolescents Compared With Adults for All Contact-Tracing Studies

Children and adolescents included those younger than 20 years, and adults included those 20 years and older. OR indicates odds ratio.

Figure 3.  Pooled Estimate of Odds of Being an Infected Contact Among Children and Among Adolescents Compared With Adults for Contact-Tracing Studies
Pooled Estimate of Odds of Being an Infected Contact Among Children and Among Adolescents Compared With Adults for Contact-Tracing Studies

Children included those younger than 10 years, adolescents included those aged 10 to 19 years, and adults included those 20 years and older. OR indicates odds ratio.

Figure 4.  Ratios of the Prevalence of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Children and Adolescents Compared With Adults in Population Screening Studies
Ratios of the Prevalence of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Children and Adolescents Compared With Adults in Population Screening Studies
Table.  Characteristics of Included Studies
Characteristics of Included Studies
1.
Lee  PI, Hu  YL, Chen  PY, Huang  YC, Hsueh  PR.  Are children less susceptible to COVID-19?   J Microbiol Immunol Infect. 2020;53(3):371-372. doi:10.1016/j.jmii.2020.02.011PubMedGoogle ScholarCrossref
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Munro  APS, Faust  SN.  Children are not COVID-19 super spreaders: time to go back to school.   Arch Dis Child. 2020;105(7):618-619. doi:10.1136/archdischild-2020-319474PubMedGoogle ScholarCrossref
3.
Brurberg  KG.  The Role of Children in the Transmission of SARS-CoV-2 (COVID-19), 1st Update—A Rapid Review. Norwegian Institute of Public Health; 2020.
4.
Epidemiology Working Group for NCIP Epidemic Response, Chinese Center for Disease Control and Prevention.  The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China.  Article in Chinese.  Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(2):145-151.PubMedGoogle Scholar
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6.
CDC COVID-19 Response Team.  Coronavirus disease 2019 in children—United States, February 12-April 2, 2020.   MMWR Morb Mortal Wkly Rep. 2020;69(14):422-426. doi:10.15585/mmwr.mm6914e4PubMedGoogle ScholarCrossref
7.
National Institute for Public Health and the Environment. Children and schools. Accessed July 20, 2020. https://www.rivm.nl/en/novel-coronavirus-covid-19/children-and-covid-19
8.
COVID-19 National Incident Room Surveillance Team.  COVID-19, Australia: epidemiology report 13 (reporting week to 23:59 AEST 26 April 2020).   Commun Dis Intell. Published online May 1, 2020. doi:10.33321/cdi.2020.44.35PubMedGoogle Scholar
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Ricardo  F, Ajelli  M, Andrianou  X,  et al. Epidemiological characteristics of COVID-19 cases in Italy and estimates of the reproductive numbers one month into the epidemic. medRxiv. Preprint posted online April 11, 2020. doi:10.1101/2020.04.08.20056861
10.
Zhang  J, Litvinova  M, Liang  Y,  et al.  Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China.   Science. 2020;368(6498):1481-1486. doi:10.1126/science.abb8001PubMedGoogle ScholarCrossref
11.
Bi  Q, Wu  Y, Mei  S,  et al.  Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study.   Lancet Infect Dis. 2020;20(8):911-919. doi:10.1016/S1473-3099(20)30287-5PubMedGoogle ScholarCrossref
12.
Park  YJ, Choe  YJ, Park  O,  et al; COVID-19 National Emergency Response Center, Epidemiology and Case Management Team.  Contact tracing during coronavirus disease outbreak, South Korea, 2020.   Emerg Infect Dis. 2020;26(10). doi:10.3201/eid2610.201315PubMedGoogle Scholar
13.
Kim  J, Choe  YJ, Lee  J,  et al.  Role of children in household transmission of COVID-19.   Arch Dis Child. Published online August 7, 2020. doi:10.1136/archdischild-2020-319910PubMedGoogle Scholar
14.
Li  X, Xu  W, Dozier  M, He  Y, Kirolos  A, Theodoratou  E; UNCOVER.  The role of children in transmission of SARS-CoV-2: a rapid review.   J Glob Health. 2020;10(1):011101. doi:10.7189/jogh.10.011101PubMedGoogle Scholar
15.
Joanna Briggs Institute. Checklist for prevalence studies. Accessed June 8, 2020. https://joannabriggs.org/sites/default/files/2019-05/JBI_Critical_Appraisal-Checklist_for_Prevalence_Studies2017_0.pdf
16.
Li  W, Zhang  B, Lu  J,  et al.  The characteristics of household transmission of COVID-19.   Clin Infect Dis. Published online April 17, 2020. doi:10.1093/cid/ciaa450PubMedGoogle Scholar
17.
Cheng  HY, Jian  SW, Liu  DP, Ng  TC, Huang  WT, Lin  HH; Taiwan COVID-19 Outbreak Investigation Team.  Contact tracing assessment of COVID-19 transmission dynamics in Taiwan and risk at different exposure periods before and after symptom onset.   JAMA Intern Med. 2020;180(9):1156-1163. doi:10.1001/jamainternmed.2020.2020PubMedGoogle ScholarCrossref
18.
Wang  Z, Ma  W, Zheng  X, Wu  G, Zhang  R.  Household transmission of SARS-CoV-2.   J Infect. 2020;81(1):179-182. doi:10.1016/j.jinf.2020.03.040PubMedGoogle ScholarCrossref
19.
Mizumoto  K, Omori  R, Nishiura  H. Age specificity of cases and attack rate of novel coronavirus disease (COVID-19). medRxiv. Preprint posted online March 13, 2020. doi:10.1101/2020.03.09.20033142
20.
Wang  Y, Tian  H, Zhang  L,  et al.  Reduction of secondary transmission of SARS-CoV-2 in households by face mask use, disinfection and social distancing: a cohort study in Beijing, China.   BMJ Glob Health. 2020;5(5):e002794. doi:10.1136/bmjgh-2020-002794PubMedGoogle Scholar
21.
Dattner  I, Goldberg  Y, Katriel  G,  et al. The role of children in the spread of COVID-19: Using household data from Bnei Brak, Israel, to estimate the relative susceptibility and infectivity of children. medRxiv. Preprint posted online June 5, 2020. doi:10.1101/2020.06.03.20121145
22.
Hu  S, Wang  W, Wang  Y,  et al. Infectivity, susceptibility, and risk factors associated with SARS-CoV-2 transmission under intensive contact tracing in Hunan, China. medRxiv. Preprint posted online August 7, 2020. doi:10.1101/2020.07.23.20160317
23.
Laxminarayan  R, Wahl  B, Dudala  SR,  et al. Epidemiology and transmission dynamics of COVID-19 in two Indian states. medRxiv. Preprint posted online July 17, 2020. doi:10.1101/2020.07.14.20153643
24.
Liu  T, Liang  W, Zhong  H,  et al.  Risk factors associated with COVID-19 infection: a retrospective cohort study based on contacts tracing.   Emerg Microbes Infect. 2020;9(1):1546-1553. doi:10.1080/22221751.2020.1787799PubMedGoogle ScholarCrossref
25.
Rosenberg  ES, Dufort  EM, Blog  DS,  et al; New York State Coronavirus 2019 Response Team.  COVID-19 testing, epidemic features, hospital outcomes, and household prevalence, New York State—March 2020.   Clin Infect Dis. Published online May 8, 2020. doi:10.1093/cid/ciaa549PubMedGoogle Scholar
26.
Yousaf  AR, Duca  LM, Chu  V,  et al.  A prospective cohort study in non-hospitalized household contacts with SARS-CoV-2 infection: symptom profiles and symptom change over time.   Clin Infect Dis. Published online July 28, 2020. doi:10.1093/cid/ciaa1072PubMedGoogle Scholar
27.
Chaw  L, Koh  WC, Jamaludin  SA, Naing  L, Alikhan  MF, Wong  J. SARS-CoV-2 transmission in different settings: analysis of cases and close contacts from the Tablighi cluster in Brunei Darussalam. medRxiv. Preprint posted online July 10, 2020. doi:10.1101/2020.05.04.20090043
28.
van der Hoek  W, Backer  JA, Bodewes  R,  et al.  The role of children in the transmission of SARS-CoV-2.  Article in Dutch.  Ned Tijdschr Geneeskd. 2020;164:D5140.PubMedGoogle Scholar
29.
Macartney  K, Quinn  HE, Pillsbury  AJ,  et al; NSW COVID-19 Schools Study Team.  Transmission of SARS-CoV-2 in Australian educational settings: a prospective cohort study.   Lancet Child Adolesc Health. Published online August 3, 2020. doi:10.1016/S2352-4642(20)30251-0PubMedGoogle Scholar
30.
Heavey  L, Casey  G, Kelly  C, Kelly  D, McDarby  G.  No evidence of secondary transmission of COVID-19 from children attending school in Ireland, 2020.   Euro Surveill. 2020;25(21):2000903. doi:10.2807/1560-7917.ES.2020.25.21.2000903PubMedGoogle Scholar
31.
Yung  CF, Kam  KQ, Nadua  KD,  et al.  Novel coronavirus 2019 transmission risk in educational settings.   Clin Infect Dis. Published online June 25, 2020. doi:10.1093/cid/ciaa794PubMedGoogle Scholar
32.
Gudbjartsson  DF, Helgason  A, Jonsson  H,  et al.  Spread of SARS-CoV-2 in the Icelandic population.   N Engl J Med. 2020;382(24):2302-2315. doi:10.1056/NEJMoa2006100PubMedGoogle ScholarCrossref
33.
Lavezzo  E, Franchin  E, Ciavarella  C,  et al; Imperial College COVID-19 Response Team.  Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo’.   Nature. 2020;584(7821):425-429. doi:10.1038/s41586-020-2488-1PubMedGoogle ScholarCrossref
34.
Public Health Agency of Sweden. Förekomsten av covid-19 i Sverige 21-24 april och 25-28 maj 2020. Accessed July 28, 2020. https://www.folkhalsomyndigheten.se/publicerat-material/publikationsarkiv/f/forekomsten-av-covid-19-i-sverige-21-24-april-och-25-28-maj-2020/
35.
Office for National Statistics. Coronavirus (COVID-19) infection survey pilot: England and Wales, 11 September 2020. Accessed July 28, 2020. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/coronaviruscovid19infectionsurveypilot/11september2020
36.
Pollán  M, Pérez-Gómez  B, Pastor-Barriuso  R,  et al; ENE-COVID Study Group.  Prevalence of SARS-CoV-2 in Spain (ENE-COVID): a nationwide, population-based seroepidemiological study.   Lancet. 2020;396(10250):535-544. doi:10.1016/S0140-6736(20)31483-5PubMedGoogle ScholarCrossref
37.
National Institute for Public Health and the Environment. PIENTER Corona study. Accessed September 16, 2020. https://www.rivm.nl/en/pienter-corona-study
38.
Hallal  P, Hartwig  F, Horta  B,  et al. Remarkable variability in SARS-CoV-2 antibodies across Brazilian regions: nationwide serological household survey in 27 states. medRxiv. Preprint posted online May 30, 2020. doi:10.1101/2020.05.30.20117531
39.
Shakiba  M, Hashemi Nazari  SS, Mehrabian  F, Rezvani  SM, Ghasempour  Z, Heidarzadeh  A. Seroprevalence of COVID-19 virus infection in Guilan province, Iran. medRxiv. Preprint posted online May 1, 2020. doi:10.1101/2020.04.26.20079244
40.
Biggs  HM, Harris  JB, Breakwell  L,  et al; CDC Field Surveyor Team.  Estimated community seroprevalence of SARS-CoV-2 antibodies—two Georgia counties, April 28-May 3, 2020.   MMWR Morb Mortal Wkly Rep. 2020;69(29):965-970. doi:10.15585/mmwr.mm6929e2PubMedGoogle ScholarCrossref
41.
Stringhini  S, Wisniak  A, Piumatti  G,  et al.  Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): a population-based study.   Lancet. 2020;396(10247):313-319. doi:10.1016/S0140-6736(20)31304-0PubMedGoogle ScholarCrossref
42.
Nawa  N, Kuramochi  J, Sonoda  S,  et al. Seroprevalence of SARS-CoV-2 IgG Antibodies in Utsunomiya City, Greater Tokyo, after first pandemic in 2020 (U-CORONA): a household- and population-based study. medRxiv. Preprint posted online July 26, 2020. doi:10.1101/2020.07.20.20155945
43.
Pagani  G, Conti  F, Giacomelli  A,  et al. Seroprevalence of SARS-CoV-2 IgG significantly varies with age: results from a mass population screening (SARS-2-SCREEN-CdA). medRxiv. Preprint posted online August 28, 2020. doi:10.1101/2020.06.24.20138875
44.
Weis  S, Scherag  A, Baier  M,  et al. Seroprevalence of SARS-CoV-2 antibodies in an entirely PCR-sampled and quarantined community after a COVID-19 outbreak—the CoNAN study. medRxiv. Preprint posted online July 17, 2020. doi:10.1101/2020.07.15.20154112
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Streeck  H, Schulte  B, Kuemmerer  B,  et al. Infection fatality rate of SARS-CoV-2 infection in a German community with a super-spreading event. medRxiv. Preprint posted online June 2, 2020. doi:10.1101/2020.05.04.20090076
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Davies  NG, Klepac  P, Liu  Y, Prem  K, Jit  M, Eggo  RM; CMMID COVID-19 Working Group.  Age-dependent effects in the transmission and control of COVID-19 epidemics.   Nat Med. 2020;26(8):1205-1211. doi:10.1038/s41591-020-0962-9PubMedGoogle ScholarCrossref
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Torres  JP, Piñera  C, De La Maza  V,  et al.  SARS-CoV-2 antibody prevalence in blood in a large school community subject to a Covid-19 outbreak: a cross-sectional study.   Clin Infect Dis. Published only July 10, 2020. doi:10.1093/cid/ciaa955PubMedGoogle Scholar
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Fontanet  A, Tondeur  L, Madec  Y,  et al. Cluster of COVID-19 in northern France: a retrospective closed cohort study. medRxiv. Preprint posted online April 23, 2020. doi:10.1101/2020.04.18.20071134
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Zhu  Y, Bloxham  CJ, Hulme  KD,  et al. Children are unlikely to have been the primary source of household SARS-CoV-2 infections. medRxiv. Preprint posted online March 30, 2020. doi:10.1101/2020.03.26.20044826
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Sun  K, Viboud  C.  Impact of contact tracing on SARS-CoV-2 transmission.   Lancet Infect Dis. 2020;20(8):876-877. doi:10.1016/S1473-3099(20)30357-1PubMedGoogle ScholarCrossref
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Jing  QL, Liu  MJ, Zhang  ZB,  et al.  Household secondary attack rate of COVID-19 and associated determinants in Guangzhou, China: a retrospective cohort study.   Lancet Infect Dis. Published online June 17, 2020. doi:10.1016/S1473-3099(20)30471-0PubMedGoogle Scholar
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    1 Comment for this article
    EXPAND ALL
    Is GI Covid-19 Going Undetected?
    Robert Stephens, MB BS FACD | North West Sydney Dermatology
    A possible source of bias is the reliance on pharyngeal swabs to establish diagnosis of Covid-19. Pharyngeal swabs may capture the vast majority of infections involving the respiratory tract but will not necessarily capture infections that follow ingestion of the virus.

    Gastrointestinal (GI) cases of Covid-19 may be escaping detection. GI Covid-19 may present with very mild symptoms or without symptoms, similar to how betacoronavirus infections exist in bats. Young children have a higher incidence of diarrhoea with Covid-19 (2) and there have been very few studies scrutinising the value of rectal swabs outside of severe disease cohorts.
    Li et al found that in their cohort of 10 asymptomatic children that rectal swabs were positive in 8 of them and rectal swab positivity persisted beyond pharyngeal swabs in all 8 (3). Zhao et al reported that in their cohort of 401 patients (positive on pharyngeal swabs), rectal swab positivity was 17% in those aged 18 years and over, but a much higher 57% in paediatric patients ( < 18 years) (4)

    REFERENCES

    1. https://www.mdpi.com/1999-4915/11/3/210
    2. https://www.bmj.com/content/370/bmj.m3484
    3. https://www.nature.com/articles/s41591-020-0817-4
    4. https://www.gastrojournal.org/article/S0016-5085(20)30663-6/pdf
    CONFLICT OF INTEREST: None Reported
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    Original Investigation
    September 25, 2020

    Susceptibility to SARS-CoV-2 Infection Among Children and Adolescents Compared With Adults: A Systematic Review and Meta-analysis

    Author Affiliations
    • 1UCL Great Ormond Street Institute of Child Health, London, United Kingdom
    • 2MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
    • 3London School of Hygiene and Tropical Medicine, London, United Kingdom
    • 4College of Medicine and Health, University of Exeter, Exeter, United Kingdom
    • 5Department of Medicine, University of Cambridge, Cambridge, United Kingdom
    • 6UCL Institute of Education, London, United Kingdom
    • 7National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
    • 8University of Sydney, Sydney, Australia
    • 9St George’s University of London, London, United Kingdom
    • 10Department of Applied Health Research, University College London, London, United Kingdom
    JAMA Pediatr. Published online September 25, 2020. doi:10.1001/jamapediatrics.2020.4573
    Key Points

    Question  What is the evidence on the susceptibility to and transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among children and adolescents compared with adults?

    Findings  In this systematic review and meta-analysis including 32 studies, children and adolescents younger than 20 years had 44% lower odds of secondary infection with SARS-CoV-2 compared with adults 20 years and older; this finding was most marked in those younger than 10 to 14 years. Data were insufficient to conclude whether transmission of SARS-CoV-2 by children is lower than by adults.

    Meaning  Preliminary evidence suggests that children have a lower susceptibility to SARS-CoV-2 infection compared with adults, but the role that children and adolescents play in transmission of this virus remains unclear.

    Abstract

    Importance  The degree to which children and adolescents are infected by and transmit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unclear. The role of children and adolescents in transmission of SARS-CoV-2 is dependent on susceptibility, symptoms, viral load, social contact patterns, and behavior.

    Objective  To systematically review the susceptibility to and transmission of SARS-CoV-2 among children and adolescents compared with adults.

    Data Sources  PubMed and medRxiv were searched from database inception to July 28, 2020, and a total of 13 926 studies were identified, with additional studies identified through hand searching of cited references and professional contacts.

    Study Selection  Studies that provided data on the prevalence of SARS-CoV-2 in children and adolescents (younger than 20 years) compared with adults (20 years and older) derived from contact tracing or population screening were included. Single-household studies were excluded.

    Data Extraction and Synthesis  PRISMA guidelines for abstracting data were followed, which was performed independently by 2 reviewers. Quality was assessed using a critical appraisal checklist for prevalence studies. Random-effects meta-analysis was undertaken.

    Main Outcomes and Measures  Secondary infection rate (contact-tracing studies) or prevalence or seroprevalence (population screening studies) among children and adolescents compared with adults.

    Results  A total of 32 studies comprising 41 640 children and adolescents and 268 945 adults met inclusion criteria, including 18 contact-tracing studies and 14 population screening studies. The pooled odds ratio of being an infected contact in children compared with adults was 0.56 (95% CI, 0.37-0.85), with substantial heterogeneity (I2 = 94.6%). Three school-based contact-tracing studies found minimal transmission from child or teacher index cases. Findings from population screening studies were heterogenous and were not suitable for meta-analysis. Most studies were consistent with lower seroprevalence in children compared with adults, although seroprevalence in adolescents appeared similar to adults.

    Conclusions and Relevance  In this meta-analysis, there is preliminary evidence that children and adolescents have lower susceptibility to SARS-CoV-2, with an odds ratio of 0.56 for being an infected contact compared with adults. There is weak evidence that children and adolescents play a lesser role than adults in transmission of SARS-CoV-2 at a population level. This study provides no information on the infectivity of children.

    Introduction

    The degree to which children and adolescents younger than 20 years are infected by and transmit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an unanswered question.1-3 These data are vital to inform national plans for relaxing social distancing measures, including reopening schools.

    Children and adolescents account for 1% to 3% of reported coronavirus disease 2019 (COVID-19) cases across countries4-8 and an even smaller proportion of severe cases and deaths.5,9 Children appear more likely to have asymptomatic infection than adults, and analyses based on symptom-based series underestimate infections in children. The role that children and adolescents play in transmission of SARS-CoV-2 is dependent on their risk of exposure, their probability of being infected on exposure (susceptibility), the extent to which they develop symptoms on infection, the extent to which they develop a viral load sufficiently high to transmit, and their propensity for making potentially infectious contact with others, dependent on numbers of social contacts across age groups and behavior during those contacts.

    Different study types may provide useful information on susceptibility and transmission in children compared with adults, yet each is open to bias. Contact-tracing studies with systematic follow-up of all contacts to estimate secondary attack rates in children and adults can provide strong evidence on differential susceptibility. Findings from some contact-tracing studies suggest that children have lower SARS-CoV-2 secondary attack rates than adults,10 although others have found no difference by age.11 One study from South Korea12 has suggested adolescents but not children may have higher secondary attack rates, although a separate analysis of child cases from the same population identified minimal transmission from these individuals.13

    Population screening studies may identify infection through viral RNA detection or antibodies indicating prior infection. However, the prevalence of SARS-CoV-2 in children in a population is not a direct indicator of susceptibility or transmission, as the expected prevalence depends on exposure, susceptibility, proportions of children in the population, mixing rates among children and between adults and children, and timing of social distancing interventions that disrupt mixing.

    A number of authors have concluded that children and adolescents may be less susceptible to SARS-CoV-2,2,14 although there are multiple sources of bias in each study type, which can complicate straightforward analysis. In contact-tracing studies, testing of only symptomatic contacts will introduce significant bias, as will seroprevalence studies drawn from clinical contact studies (eg, primary care) or residual laboratory sera. Many studies undertaken quickly during the pandemic are underpowered to identify age differences.

    We undertook a systematic review and meta-analysis of published and unpublished literature to assess child and adolescent susceptibility to SARS-CoV-2 compared with adults. We limited this review to contact-tracing studies and population-based studies, as these are likely to be most informative and least open to bias.

    Methods

    Our review question was “What is the susceptibility to SARS-CoV-2 of children and adolescents compared with adults?” We undertook a rapid systematic review and included contact-tracing studies or prevalence studies in published or preprint form as well as data from a national public health website reporting government statistics and studies. Studies were required to provide data on proven SARS-CoV-2 infection (by polymerase chain reaction or serology) and report either rate of secondary infections in children and adolescents compared with adults or infection prevalence or seroprevalence in children and adolescents separate from adults. We excluded reports of single household or single institution outbreaks; studies of hospitalized patients, clinical studies, and cohorts defined by symptoms; studies of unconfirmed cases, ie, cases based on self-report or symptoms, including contact-tracing studies where only symptomatic contacts were traced; modeling studies or reviews, unless these reported new data; and prevalence studies with ascertainment based on clinical contact and seroprevalence studies of residual sera, as these are likely to underrepresent children. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline.

    Where studies were drawn from populations that overlapped, we excluded studies where the time periods overlapped but included studies where time periods did not overlap. We did not include seroprevalence studies only in children in this review, as these did not allow comparison with adults.

    We searched 2 electronic databases, PubMed and the medical preprint server medRxiv, on May 16, 2020, and updated this on July 28, 2020. We used the following search terms in PubMed: (“COVID-19”[tw] OR “2019-nCoV”[tw] OR “SARS-CoV-2”[tw]) AND ((child* OR infant*) OR (“transmission”[tw] OR “transmission” [mh]) OR (“Disease Susceptibility”[tw] OR “susceptibility”(mh)) OR (“epidemiology”[tw] OR “epidemiology” [mh]) OR (“contact tracing”[tw] or “communicable disease contact tracing”[mh])). In medRxiv, we undertook separate searches for “child and covid-19,” “covid-19 and epidemiology,” “covid-19 and susceptibility,” and “covid-19 transmission,” as more complex Boolean searches are not available.

    Figure 1 shows the PRISMA flow diagram. One researcher (R. M. V.) screened studies based on titles and abstracts to identify potentially eligible studies for full-text review. Full-text studies were then reviewed by 2 researchers for eligibility (R. M. V. and O. T. M. or C. W.), and data were extracted independently by 2 researchers (R. M. V. and either O. T. M. or C. W.). We hand searched cited references in all potentially eligible studies for additional studies and identified additional studies through authors’ professional networks. Data were extracted on country, study type, study context with regards social distancing measures and school closures at the time of the study, case definition, testing method, sampling method, and infection rates in adults and children.

    Methodological quality of included studies was assessed independently by 3 authors (R. V. M., O. T. M., and C. W.) based on a critical appraisal checklist for prevalence studies.15 We assessed risk of bias using 2 additional criteria: whether symptomatic contacts (in contact-tracing studies) or individuals (in population screening studies) were more likely to participate than asymptomatic ones and whether the obtained sample was more than 75% of the intended sample. Studies were categorized as high quality if they met all quality criteria and had low risk of bias on both criteria; medium quality if they had low risk of bias on 1 or more criteria and met 5 or more of 7 quality criteria; low quality if they met less than 5 quality criteria; or uncertain quality if multiple domains could not be scored.

    Contact-tracing studies and population prevalence studies were considered separately. Random-effects meta-analysis with restricted maximum likelihood estimation was undertaken using the meta commands in Stata version 16 (StataCorp). Odds ratios (ORs) were used as the primary metric for contact-tracing studies. Prevalence ratios were used as the primary metric in population-based studies. We planned subgroup analyses using restricted maximum likelihood based on quality of study and age of children and adolescents. P values were calculated using χ2 tests. Significance was set at a P value less than .05, and all P values were 2-tailed.

    Results

    The PubMed search resulted in 3465 studies and the medRxiv search resulted in 10 461 studies, of which 113 and 90 studies, respectively, were examined in full, and 16 studies included (Figure 1). We identified a further 6 studies through reference checking and 10 studies through professional networks. In total, 32 studies comprising 41 640 children and adolescents and 268 945 adults were included (Table),7,10,12,16-45 with quality and bias assessments shown in eTable 1 in the Supplement and weblinks for included studies shown in eTable 2 in the Supplement. A total of 18 studies were contact-tracing studies (CTSs),7,10,12,16-31 with 3 based in schools,29-31 and 14 studies were population screening studies.7,32-45 Two were high quality,33,35 22 were medium quality,10,12,16,21,22,24-27,29-32,34,36,38,40-45 7 were low quality,17-20,23,28,39 and 1 was uncertain quality.7,37

    Contact-Tracing Studies

    A total of 6 studies were from mainland China,10,16,18,20,22,24 2 from the US,25,26 and 1 each from Taiwan,17 Japan,19 South Korea,12 Israel,21 the Netherlands,7,28 Brunei,27 and India,23 with 3 CTSs based in schools from Australia,29 Ireland,30 and Singapore.31 Lower secondary attack rates in children and adolescents compared with adults were reported by 11 studies: 5 from provinces of China, including Hunan,10,22 Hubei,16,18 and Beijing,20 and 6 from other countries, including Taiwan,17 Japan,19 the US,25,26 Israel,21 and the Netherlands,7,28 although confidence intervals were wide in some studies.

    No significant differences in secondary attack rates by age were reported in 3 studies from Guangdong province, China,24 Brunei,27 and the states of Tamil Nadu and Andhra Pradesh in India,23 with 1 study from South Korea12 reporting high secondary attack rates in those younger than 19 years. In 3 of these studies,12,23,27 secondary attack rates in younger children were low compared with adults, but those among teenagers were as high as or higher than adults.

    We undertook a random-effects meta-analysis of secondary attack rates in children and adolescents compared with adults, with data included from 14 studies.10,12,16-21,23-28 We combined data on children and adolescents younger than 20 years and compared it with an adult group 20 years and older; thus, ORs and prevalence rates for adults may differ from those reported in studies. The pooled OR estimate for all contact-tracing studies of being a child with secondary infection compared with being an adult was 0.56 (95% CI, 0.37-0.85), with high heterogeneity (I2 = 94.6%) (Figure 2).10,12,16-21,23-28

    We undertook a meta-analysis of 8 CTSs grouped by age of child (Figure 3)10,12,21,23-25,27,28; the ages differed across studies, and children were defined as those younger than 10 to 14 years, adolescents as those older than 10 to 12 years, and adults as those 20 years and older. The pooled OR for children was 0.52 (95% CI, 0.33-0.82), significantly lower than adults (1 [reference]). For adolescents, this was nonsignificant (OR, 1.23; 95% CI, 0.64-2.36). χ2 Test suggested this group difference was significant (χ2 = 4.54; P = .03). When only the 8 high-quality and medium-quality studies with low risk of bias were examined,10,12,16,21,24-27 this finding was no longer significant (OR, 0.68; 95% CI, 0.41-1.11); however, the difference in estimates between low-quality studies and high-quality and medium-quality studies was not significant (eFigure 1 in the Supplement).

    We hypothesized that CTSs including only household contacts might provide a clearer indication of the relative susceptibility to infection of children vs adults because all contacts within households might be assumed to receive a similar exposure to infection from index cases. A post hoc analysis by type of contacts (eFigure 2 in the Supplement) showed that studies of household contacts had a lower pooled OR (OR, 0.41; 95% CI, 0.22-0.76)) than studies of all contacts (OR, 0.91; 95% CI, 0.69-1.21; between-group variance: χ21 = 5.31; P = .02).

    Three studies undertook contact tracing in schools.29-31 A statewide population-based CTS in educational settings in Australia before and during school closures29 found that 27 primary cases (56% staff) across 25 schools or early-years nurseries resulted in 18 secondary cases in 4 settings, including an outbreak of 13 cases in 1 early-years setting initiated by a staff member, with no evidence of child-to-adult transmission. The secondary attack rate was 1.2% (18 of 1448) overall, 0.4% (5 of 1411) when excluding the early-years outbreak, and 2.8% (18 of 633) in those tested. Other national CTSs undertaken in schools in Ireland30 and Singapore31 before schools closed identified very few secondary cases in schools.

    Population Screening Studies

    Data from prevalence studies for children and adolescents compared with adults are shown in Figure 4.7,32-36,38-45 We did not undertake a meta-analysis of population screening studies given the important differences in the populations, epidemic time points, and methodologies involved.

    Four studies reported virus prevalence.32-35 National prevalence studies from Iceland32 and Sweden34 undertaken while primary schools were open showed lower prevalence among children and adolescents than adults, as did a municipal study from Italy33 undertaken just before lockdown while schools were open. However, a nationally representative survey from England covering lockdown and the subsequent month identified no significant differences by age.35

    A total of 10 studies reported seroprevalence,7,36,38-45 3 being nationally representative.7,36,38 A lower seroprevalence was identified in children and in some adolescents compared with adults in a number of studies, including a nationally representative study in Spain (ENE-COVID),36 a Dutch nationally representative study (PIENTER Corona study),7,37 and city or regional studies from Iran,39 the US,40 Switzerland,41 and Japan,42 although no difference by age was found in a survey in 133 sentinel cities in 26 Brazilian states.38 Two community-based studies following localized outbreaks found lower seroprevalence among children and adolescents than adults in Lombardy, Italy,43 and Thuringia, Germany,44 with a second German postoutbreak study45 finding no overall association with age. Examination of seroprevalence findings in children separate from adolescents (eFigure 3 in the Supplement) suggested that seroprevalence was lower among children younger than 10 years than adults but not lower among adolescents aged 10 to 19 years than adults, although this was not formally tested.

    Discussion

    We identified 32 studies from 21 countries that met our eligibility criteria and provided information on susceptibility to and transmission of SARS-CoV-2 in children and adolescents compared with adults. We excluded studies and study types open to very significant bias, yet studies were predominantly of medium and low quality, with only 2 high-quality studies.34,35 Most studies were from middle-income and high-income countries in East Asia and Europe.

    We found preliminary evidence from 15 contact-tracing studies that children and adolescents have lower susceptibility to SARS-CoV-2 infection than adults, with a pooled OR of 0.56 (95% CI, 0.37-0.85). This estimate was little changed when only medium-quality or high-quality studies were examined, although power was reduced and significance was attenuated. Only 1 study13 found a higher odds of infection in those younger than 20 years than adults, although this finding was confined to those aged 10 to 19 years. When studies were categorized by age, lower susceptibility appeared to be confined to those younger than 10 to 14 years, who had 48% lower odds of infection compared with those 20 years and older. The age bands of the studies were not aligned, making direct comparisons challenging.

    Data from population screening studies were heterogenous and were not suitable for meta-analysis. Findings consistent with lower seroprevalence in those younger than 20 years compared with adults were reported by 2 national studies,7,36 1 regional study,40 and all of the municipal postoutbreak studies,43-45 although confidence intervals were wide in some cases. Two virus prevalence studies similarly reported lower infection rates in those younger than 20 years. In contrast, other studies reported no age-related differences. No studies reported higher prevalence in children and adolescents. Examination of seroprevalence findings in children separate from adolescents showed that most studies were consistent with lower seroprevalence in children compared with adults, although seroprevalence in adolescents appeared similar to adults in all studies.

    The findings from the CTSs and prevalence studies are largely consistent in suggesting that those younger than 10 to 14 years are less susceptible to SARS-CoV-2 infection than those 20 years and older, resulting in lower prevalence and seroprevalence. Data specifically on adolescents are sparse but consistent with susceptibility and prevalence rates of adults. Our findings on susceptibility are similar to a modeling analysis by Davies et al,46 which estimated that those younger than 20 years were approximately half as susceptible to SARS-CoV-2 as adults.

    We found few data that were informative on the onward transmission of SARS-CoV-2 from children to others. Data from a large Australian school contact-tracing study29 suggest that, at a population level, children and adolescents might play only a limited role in the transmission of this virus. This is consistent with the data on susceptibility noted above, ie, suggesting that lower rates of secondary infection mean that children and adolescents have less opportunity for onward transmission. There is evidence of transmission from children to others in households and in schools, and there have been reported outbreaks in schools.47,48 Other very small studies in Ireland30 and Singapore31 have found low numbers of secondary cases resulting from infected children attending school. This is consistent with a national South Korean study,13 which found the secondary attack rate from children to household members was extremely low. The available studies suggest children and adolescents play a lesser role in transmission of SARS-CoV-2, which is in marked contrast to pandemic influenza.49

    Limitations

    Our study has a number of limitations. We remain early in the COVID-19 pandemic, and data continue to evolve. It is possible that unknown factors related to age, eg, transience of infection or waning of immunity, bias findings in ways we do not yet understand. Some studies were low quality, and nearly all included studies were open to bias. The secondary infection rate in some CTSs was low, and this may represent an underestimate of the unmitigated household attack rate of SARS-CoV-2, as transmission chains were cut short because of strict control measures.50 Most of the CTSs were undertaken when strict social distancing measures had been introduced, eg, closures of schools and workplaces and restriction of travel. This would have reduced contacts outside the home, especially contacts between children, but it may have increased contacts between children and adults by increasing the household contact rate. The number of contacts nominated and traced for those younger than 20 years was low compared with adults in some studies,12,23 which may have introduced bias. We identified 3 CTSs from Guangdong province11,51,52 that were excluded as they overlapped with findings from Liu et al24; however, findings were unchanged if these studies were included. We included 2 recent large CTSs from India23 and South Korea12; however, numbers of children and data quality appeared low, making firm conclusions difficult.

    For population screening studies, the numbers of children tested was small in most of the studies and was frequently less than the 15% to 25% of the population that are younger than 18 years in most countries. This likely reflects lower recruitment of children and may be a source of bias, although the direction of this bias is unclear. Age differentials in sensitivity of swab or antibody tests may also confound findings. Interpreting the observed prevalence and seroprevalence studies requires thorough quantification of social mixing and transmission between age groups and how that changed during lockdowns and social distancing interventions.

    Conclusions

    There is preliminary evidence that those younger than 10 to 14 years have lower susceptibility to SARS-CoV-2 infection than adults, with adolescents appearing to have similar susceptibility to adults. There is some weak evidence that children and adolescents play a limited role in transmission of SARS-CoV-2; however, this is not directly addressed by our study.

    We remain early in our knowledge of SARS-CoV-2, and further data are urgently needed, particularly from low-income settings. These include further large, high-quality contact-tracing studies with repeated swabbing and high-quality virus detection and seroprevalence studies. Studies that investigate secondary infections from child or adolescent index cases compared with secondary infections from adult index cases are particularly needed to assess transmission. Monitoring of infection rates and contact-tracing studies within child care and school settings will also be important. A range of serological studies are planned in many countries, and these need to be sufficiently powered to assess differences in seroprevalence across different age groups and include repeated sampling at different time periods as social distancing restrictions are lifted. We will continue to update this review, including further data as available and updating preliminary data from some included studies.

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    Article Information

    Accepted for Publication: August 23, 2020.

    Published Online: September 25, 2020. doi:10.1001/jamapediatrics.2020.4573

    Correction: This article was corrected on November 2, 2020, to add the Funding/Support and Role of the Funder/Sponsor sections and fix the degree for Jasmina Panovska-Griffiths.

    Corresponding Author: Russell M. Viner, PhD, UCL Great Ormond Street Institute of Child Health, 30 Guilford St, London WC1N 1EH, United Kingdom (r.viner@ucl.ac.uk).

    Author Contributions: Dr Viner had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Study concept and design: Viner, Bonell, Hudson, Eggo.

    Acquisition, analysis, or interpretation of data: Viner, Mytton, Bonell, Melendez-Torres, Ward, Waddington, Thomas, Russell, van der Klis, Koirala, Ladhani, Panovska-Griffiths, Davies, Booy, Eggo.

    Drafting of the manuscript: Viner, Mytton, Bonell, Melendez-Torres, Waddington, Thomas, Eggo.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Viner, Melendez-Torres, Waddington, Thomas, Russell, Booy, Eggo.

    Administrative, technical, or material support: Viner, Mytton, Waddington, Koirala.

    Study supervision: Viner, Bonell, Eggo.

    Conflict of Interest Disclosures: Dr Mytton has received grants from the National Institute of Health Research and personal fees from Public Health England. No other disclosures were reported.

    Funding/Support: Dr Eggo was supported by grant MR/S003975/1 from Health Data Research UK and grant MC_PC 19065 from the Medical Research Council.

    Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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