Transmission of SARS-CoV-2 by Children
Background: Six months into the COVID-19 pandemic, children appear largely spared from the direct effects of disease, suggesting age as an important predictor of infection and severity. They remain, however, impacted by far-reaching public health interventions. One crucial question often posed is whether children generally transmit SARS-CoV-2 effectively.
Methods: We assessed the components of transmission and the different study designs and considerations necessary for valid assessment of transmission dynamics. We searched for published evidence about transmission of SARS-CoV-2 by children employing a narrative review methodology through 25 June, 2020.
Results: Transmission dynamics must be studied in representative pediatric populations with a combination of study designs including rigorous epidemiological studies (e.g. in households, schools, daycares, clinical settings) and laboratory studies while taking into account the social and socio-economic contexts. Viral load (VL) estimates from representative pediatric samples of infected children are missing so far. Currently available evidence suggests that the secondary attack rate stratified by age of the infector is lower for children, however this age pattern needs to be better quantified and understood.
Conclusion: A generalizable pediatric evidence base is urgently needed to inform policy making now, later when facing potential subsequent waves, and extending through a future in which endemicity alongside vaccination may become the enduring reality.
Age has been one of the most important factors in the prognosis of those affected by COVID-19 (e1). Differential SARS-CoV-2 infection, transmission and clinical manifestation by age have important implications for social policy decisions, such as closure of schools. By April 2020, interventions to limit SARS-CoV-2 transmission left over 90% of children confined at home worldwide (e2). Such closures reduce contacts not only between students, but also prevent parents from working (1) and have proven effective during influenza epidemics (2).
It quickly became clear, however, that children were relatively spared by SARS-CoV-2. They account for a small proportion of confirmed cases, with symptoms absent or mild and fleeting (e3) and have half the odds of infection compared to adults (3). We review evidence about transmission of SARS-CoV-2 by children, and how relevant parameters may be ascertained through epidemiologic and laboratory techniques. It is essential to know if children need to adapt their individual contacts with close family members at risk for severe COVID-19. This evidence is also required for rational policies that balance harms and benefits of education and recreation, as well prioritization of future vaccination efforts. Most acutely, continued interruption of formal education carries a huge social cost to health and development of children (4), and to social and professional functioning of parents (e4). Evidence to guide balancing of those risks against potential epidemic spread is therefore urgently needed.
We assessed the components of transmission and the different study designs and requirements necessary for assessment of transmission dynamics. We searched for the evidence base of transmission of SARS-CoV-2 by children using narrative review methodology (e5, e6) until 25 June 2020, including a PubMed search using the terms “child”, “SARS-CoV-2” and “transmission” (eBox).
Components of Transmission
Disease transmission is a complex interaction between infectious and susceptible hosts, an agent and the environment (5). For a child to become a possible source of infection, they need to have been previously exposed to, replicate and effectively shed the infectious virus. Components of transmission dynamics, the spread of the infection over time, are biological, behavioral and contextual. Knowledge of all three components is required to define effective transmission and its evolution over time.
Children differ from adults in biological and behavioral characteristics related to transmission. For example, they differ in contact type, rate, duration and intensity and they primarily interact with other children (e7). It remains unknown which variables play critical roles in the transmission dynamics of SARS-CoV-2 (6). Current consensus is that respiratory droplet expulsion is key, especially during speech (7), but this has not been studied among children. There is presently insufficient evidence for feco-oral transmission. Context also matters, and most documented transmission occurs in adult settings like bars, conferences, meat-plants and ships (8). Like other infectious diseases, SARS-CoV-2 data suggest that ~20% of the cases are responsible for ~80% of local transmission (9). So far, these ~20% appear to be predominantly adults, not children (8, e8).
Most work on transmission dynamics focuses on susceptible hosts and calculates risk of becoming infected. To know whether children transmit the SARS-CoV-2 virus as effectively as adults, one needs to know the secondary attack rate (i.e. number of new cases an initial case infects, per 100 exposed individuals [e9]) stratified by age of infector. This is the most direct measure of the infectiousness of a particular agent.
Epidemiological and Experimental Designs
The question of pediatric contagiousness is not a theoretical one, but a real-world phenomenon in the specific context of the current pandemic. A natural approach is via epidemiologic designs, observing populations directly and measuring chains of transmission to ascertain how many cases stem from an infected child.
The primary design for this purpose is the study of households, which are well-defined settings that offer the closest and most intense contact with and between children (e10, e11). These may be incidence or prevalence studies, using PCR or serology, or both. Pediatric transmission can also be studied in outbreaks at schools, daycares, or in clinical settings. In a subset of investigations, phylogenetic tools (e12) can also be used to enhance specificity. Further inference can be derived from intervention studies, using longitudinal data to evaluate the impact of prevention measures on reducing transmission. Finally, the epidemiologic profile is enhanced by population surveys, either of acute or past infection (10). These designs share the virtue of being direct observations of the series of events that culminate with transmission, and therefore provide direct answers to scientific questions about epidemic spread. The results of epidemiologic designs may be subsequently used in mathematical models, to expand inference to hypothetical and counterfactual scenarios, and for the purpose of forecasting (e4). In contrast to the artificial sterility of the laboratory, “epidemiology is the gold standard to measure transmission potential of patients”(11).
Because inference about transmission dynamics occurs at the population level, attention needs to be given to how and which study participants are recruited (Table 1) (12). Systematic differences in recruitment can lead to bias in population estimates, for example if only symptomatic children are followed, or only hospitalized cases are recruited (e13). This generates a skewed impression of the true frequencies of events and representativeness issues, and also leads to biases that arise from associations in the sample that are artifacts of the recruitment process (13). Analyses must also account for imperfect measurement of case status as a function of diagnostic test accuracy (14, e14). These potential biases may be exacerbated when they are age-dependent, for example if test accuracy varies by age, or pediatric cases are rare. Small sample sizes in addition result in imprecise estimates.
Results from laboratories, animal models and controlled experiments on SARS-CoV-2 and other respiratory pathogens contribute to knowledge about transmission, but issues of generalization remain central (e15). For example, how does transmission between hamsters translate to transmission dynamics and intervention effects in a 4th grade classroom (15)? Experiments offer the advantage of controlled environments but never approximate real-world conditions. These studies therefore provide important mechanistic insights, but do not directly inform policy decisions. For example, environmental studies provided crucial information about duration of SARS-CoV-2 on different types of surfaces (16). To what extent transmission and infection occur from such media remains unknown, with epidemiology suggesting it may be relatively infrequent (e16). A recent study estimates that a minute of loud speaking generates at least 1000 virion-containing droplet nuclei that can remain airborne for more than 8 minutes (7). This suggests a plausible mechanism behind super-spreading events, but actual transmission cannot be predicted without accounting for real-world contextual factors such as airflow patterns (e17).
The presence of sufficient infectious virus is a necessary condition for transmission, and this minimal number of viable organisms required to infect a non-immune individual is expressed as the median tissue culture infective dose. This is an in vitro phenomenon and remains unknown for SARS-CoV-2. It is cumbersome to measure and therefore high levels of viral replication are commonly quantified using a more convenient proxy, the viral load (VL) expressed in copies/ml (e18).
The VL provides a quantitative estimate of the amount of target RNA obtained from clinical samples and can be indirectly measured by PCR testing. Finding RNA does not imply presence of viable and replicating virus, however. Virus quantification by PCR testing uses a backwards calculation of cycle threshold (Ct) values (e19). The Ct value is the cycle number during the amplification phase when fluorescence of a PCR product can be detected above the background signal. The lower the value, the larger the initial amount of viral genetic material present in the sample. The minimal VL necessary to infect a secondary case is not known for SARS-CoV-2 and likely varies across hosts (17), although presumably more virus translates into increased infectivity. Pediatric cases with high VL have been reported (e20), but transmission is never guaranteed even with a large number of viral copies detected in the respiratory tract (18).
To quantify the amount of virus present in a typical infected child, one needs to account for pre-analytical and analytical sample and assay characteristics (19, e21). The respiratory specimen type, such as nasopharyngeal versus nasal swab, determines the sensitivity and specificity of a PCR test and measured VL will therefore vary (19). The ideal specimen to diagnose SARS-COV-2 infection in children has not been determined and could potentially be different from adults.
It has been shown that variation in VL is dependent on the timing of specimen collection in relation to initial exposure, (14, 19), with high VL early in the disease course (20). This is confirmed in samples from pediatric case-studies and case series (e20). Infectious virus is no longer detected after 7 days since onset of symptoms (21). An estimated 56.4% (34.9–78.0%) (e22) of adult transmission takes place in the pre-symptomatic phase (22). It remains unclear if this is mainly because of high peak VL at that moment, or because infector and infectee are unaware of the infection and therefore taking no precautions, or both, and if this plays out similarly in children.
To estimate the distribution of VLs in children attending schools, one needs to follow basic epidemiologic principles of generalizability (Table 1) (e23), using a study sample with representative demography, including age, sex, and social class. For valid population inference, selection into the study should not be based on presence of symptoms, severity of disease or presence of relevant co-morbidities. Diligent use of laboratory data in conjunction with epidemiological investigation illustrates the real potential to learn about transmission probabilities and effective transmission in relation to the skewed curve of VL (23).
Knowledge Synthesis from Existing Studies
Published household transmission studies show that children are rarely the index case and investigations of cases and clusters suggest that children with SARS-CoV-2 seldom cause secondary cases (24). A review of household cluster studies compared household transmission during H5N1 influenza epidemics where 30/56 of the index cases were children, to the COVID-19 pandemic, where 3/31 clusters had a child who potentially infected a secondary case (25).
Most of the household cases published to date are from countries affected early in the pandemic and include confined children with consequently restricted exposure. In a Swiss study (26), 3/39 of households had a child who developed symptoms prior to other household contacts, but without evidence of transmission from the child. A preprint from Israel (e24) including 3353 people in 637 households, estimated children up to age 20 to be 85% as infective as adults (that is, relative 15% less infective). Published data from the first 13 families show an adult index case in all but one instance (27).
In settings where schools remained open or using data prior to closures, there is little evidence of outbreaks or major transmission into the community. In Australian schools (28) two children contracted COVID-19 after exposure to 9 infected students and 9 infected staff among 735 students and 128 staff. An outbreak in a French high-school is described among 15–17 year olds, with limited cases among sibling contacts (29). An Irish study (30) describes exposure to an infected child in primary school, two in high-school and 3 infected adults, and yet follow-up and testing detected no cases. In Sweden, where schools for children up to 15 years remained open, only hospitalization data are published (e25), during a period in which cross-sectional PCR surveillance showed overall positivity <3% in both children and adults (e26). Data free from selection bias on the impact on broader transmission and a useful comparison remain lacking.
Elsewhere, prevalence data using serology from published sero-surveys of population samples and their households (31), from residual blood sample data (e27) and national public health agency initiatives (32), reveal lower sero-prevalence in children than adults. A pre-print from the Paris region reports a high sero-prevalence of 10.7% among 605 children ages 0–15, sampled at visits to ambulatory pediatricians. This is a highly selected sample in which 17.1% and 32.3% of the included children had confirmed or suspected COVID-19 positive household contacts, respectively (33). This is substantially higher than the Paris average, and shows the sample to be unrepresentative of the overall population. Many more reports are posted by public health agencies (3) but do not adequately describe sampling and methods to infer pediatric rates.
Although VL estimates from representative pediatric samples remain unavailable, symptomatic children and adults showed similar VL in one descriptive study without formal statistical investigation (34). VL above a putative infectiousness threshold were present in 29.0% of 38 patients ages 0–6 years versus 51.4% among 3153 adults in a German study (35), but with insufficient information about sampling to suggest generalizability.
Modeling studies have shown effects confining children among a suite of interventions (36), however, even assuming equal infectiousness in children compared to adults, they show limited impact at the peak and the need for prolonged closure to control transmission (37). More recent models include lower susceptibility and infectivity and decreased impact (38).
Despite limited evidence, the general pattern emerges that transmission from children occurs, but contributes much less to evolution of the epidemic than do contacts between adults, and school-re-openings have not lead to transmission spikes in low transmission countries (e28). Possible changes in transmission among older students, as suggested using German data, warrant further assessment. Unlike other respiratory diseases such as influenza, it seems quite clear that the secondary attack rate from pediatric cases is substantially lower than for adults, and that mechanisms underlying this difference require elucidation.
Rather than simply a question of viral load, policy decisions such as school reopening are complex considerations that require balancing competing risks and benefits in the broader context of fear and uncertainty (e29). School closures have negative impacts on mental, educational, nutritional and social development, and disrupt relationships between children, peers and families (e30). They most adversely compromise children with special needs and those from marginalized households, exacerbating inequalities (39).
Transmission dynamics inevitably change over time (e31) and are modified by other interventions. The contribution of children to the spread of COVID-19 is therefore a highly contingent question. Many children still have limited exposure to infection, and become infected less frequently. When infected, they are generally less sick than adults. Six months into the pandemic, children have not shown any evidence of being a significant factor in its propagation (40). As societies worldwide relax or reintroduce restrictions, pragmatic studies to measure changes in transmission in various groups, particularly children, are needed more than ever.
We thank Prof. Dr. med. Andreas Stang for helpful suggestions on the content and assistance with the German translation.
Conflict of interest statement
Joanna Merckx is employed by bioMérieux Canada as Director of Medical Affairs.
Jeremy A Labrecque and Jay S Kaufman declare that no conflict of interest exists.
Manuscript received on 11 June 2020, revised version accepted on
2 July 2020
Jay S. Kaufman, Ph.D
Department of Epidemiology, Biostatistics, and Occupational Health
1020 Pine Ave West
Montreal, Quebec H3A 1A2
Cite this as:
Merckx J, Labrecque JA, Kaufman JS: Transmission of
SARS-CoV-2 by children. Dtsch Arztebl Int 2020; 117: 553–60. DOI: 10.3238/arztebl.2020.0553
A retrospective closed cohort study. medRxiv 2020; DOI: 10.1101/2020.04.18.20071134 (ePub ahead of print) CrossRef
Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands: Jeremy A Labrecque, PhD
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