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Sharing a household with children and risk of COVID-19: a study of over 300,000 adults living in healthcare worker households in Scotland

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Objective Children are relatively protected from COVID-19, possibly due to cross-protective immunity. We investigated if contact with children also affords adults a degree of protection from COVID-19. Design Cohort study based on linked administrative data. Setting Scotland Study population All NHS Scotland healthcare workers and their household contacts as of March 2020. Main exposure Number of young children (0-11 years) living in the participant’s household. Main outcomes COVID-19 requiring hospitalisation, and any COVID-19 (any positive test for SARS-CoV-2) in adults aged ≥18 years between 1 March and 12 October 2020. Results 241,266, 41,198, 23,783 and 3,850 adults shared a household with 0, 1, 2, and 3 or more young children respectively. Over the study period, the risk of COVID-19 requiring hospitalisation was reduced progressively with increasing numbers of household children - fully adjusted hazard ratio (aHR) 0.93 per child (95% CI 0.79-1.10). The risk of any COVID-19 was similarly reduced, with the association being statistically significant (aHR per child 0.93; 95% CI 0.88-0.98). After schools reopened to all children in August 2020, no association was seen between exposure to young children and risk of any COVID-19 (aHR per child 1.03; 95% CI 0.92-1.14). Conclusion Between March and October 2020, living with young children was associated with an attenuated risk of any COVID-19 and COVID-19 requiring hospitalisation among adults living in healthcare worker households. There was no evidence that living with young children increased adults’ risk of COVID-19, including during the period after schools re-opened.
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Sharing a household with children and risk of COVID-19: a study of over
300,000 adults living in healthcare worker households in Scotland
Rachael Wood, Reader and Consultant in Public Health Medicine1,2;
Emma C Thomson, Professor in Infectious Diseases3;
Robert Galbraith, Retired;
Ciara Gribben, 2, Statistician;
David Caldwell2, Statistician;
Jennifer Bishop2, Statistician;
Martin Reid2, Statistician;
Anoop S V Shah, Associate Professor and honorary consultant cardiologist4,5;
Kate Templeton, Consultant Clinical Scientist and Honorary Senior Lecturer in Medical Microbiology1;
David Goldberg2, Professor and Consultant in Public Health Medicine;
Chris Robertson2,, Professor of Statistics;
Sharon Hutchinson2,6, Professor of Epidemiology and Population Health;
Helen Colhoun2,7, AXA Chair of Medical Informatics and Life Course Epidemiology and Honorary
Consultant in Public Health Medicine ;
Paul McKeigue2,8, Professor of Genetic Epidemiology and Statistical Genetics and Honorary
Consultant in Public Health Medicine;
David A McAllister 2,9, Wellcome Trust Intermediate Clinical Fellow and Beit Fellow and Honorary
Consultant in Public Health Medicine
Affiliations
1. Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK.
2. Public Health Scotland, Edinburgh, UK.
3. MRC Centre for Virus Research, University of Glasgow, Glasgow, UK.
4. Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine,
London, UK.
5. Department of cardiology, Imperial College NHS Trust, London, UK
6. School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, UK.
7. MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK.
8. Usher Institute, University of Edinburgh, Edinburgh, UK.
9. Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.
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2
Abstract
Background
Children are relatively protected from novel coronavirus infection (COVID-19). The reasons for this
protection are not well understood but differences in the immune response to Severe Acute
Respiratory Syndrome coronavirus 2 (SARS-CoV-2) have been implicated. If such differences are due
to differential exposure to non-SARS-CoV-2 infectious agents, adults who are close contacts of
children may partly share in this protection. Such a protective effect would have important
implications for the lives of children, not least in terms of schooling.
Methods
Using a Scotland-wide record-linkage based occupational cohort comprising healthcare workers and
members of their households, we examined whether sharing a household with young children (aged
0 to 11) attenuated the risk of hospitalisation with COVID-19, and/or testing positive for COVID-19
infection of any severity (any case of Covid-19). All healthcare workers directly employed by the
National health Service (NHS) in Scotland, or contracted to provide general practice services, were
included. Outcome and covariate data were obtained via linkage to Scotland-wide microbiology,
drug prescribing, hospitalisation and death data.
Results
241,266 adults did not share a household with young children; 41,198, 23,783 and 3,850 shared a
household with 1, 2 and 3 or more young children respectively. The risk of hospitalisation with
COVID-19 was lower in those with one child and lower still in those with two or more children,
adjusting for age the hazard ratio (HR) was 0.83 per child (95% CI 0.70-0.99). On additionally
adjusting for sex, socioeconomic deprivation, occupation, professional role, staff/non-staff status,
the number of adults and adolescents in each household, and comorbidity, the HR was 0.89 per child
(95% CI 0.74-1.06). An association of the same magnitude, but more precisely estimated, was
obtained for any case of COVID-19 (fully adjusted model, HR per child 0.89; 95% CI 0.84-0.95).
Conclusion
Increased household exposure to young children was associated with an attenuated risk of testing
positive for SARS-CoV-2 and appeared to also be associated with an attenuated risk of COVID-19
disease severe enough to require hospitalisation.
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Introduction
Children are relatively protected from Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-
2). When exposed, children are less likely to develop symptomatic infection (COVID-19), and when
infected they are less like to become seriously ill.1 This difference is large; in the UK over the peak 9
weeks of the epidemic, the mortality in the UK population for SARS-CoV-2 was 0.0005% among
children aged 0 to 14, compared to 0.003% for adults aged 25-44 and 0.11% for adults aged 65 to
74.2
The reasons why COVID-19 is milder in childhood are not well understood, and differences in both
the innate and acquired immune systems have been implicated.3 While developmental factors alone
may account for any differences, pre-exposure to antigenically-similar infectious agents may also be
relevant. Evidence of B and T-cell cross-reactivity between endemic coronaviruses and SARS-CoV-2
has been demonstrated in independent studies,410 and children may have higher levels of exposure
to endemic coronaviruses than adults.11,12 Alternatively, there may be non-specific “training” of the
innate immune response as a result of increased exposure to childhood vaccinations and respiratory
viruses.13
If differential exposure to infectious agents is an important mechanism, adults who are close
contacts of children, such as childcare providers, teachers and parents may also benefit. Despite a
lack of empirical evidence that children are important in the transmission of COVID-19, schools and
nurseries throughout the world have been closed, resulting in substantial harms to the health and
wellbeing of children,14 while a substantial proportion of staff who work in schools have reported
feeling unsafe about the reopening of educational establishments.15 Consequently, if exposure to
children was found to be protective, rather than harmful, this would have important implications for
policy. Few studies, however, have examined this question.16
We recently reported the risk of hospitalisation for COVID-19 in around 160,000 healthcare workers
and 250,000 members of their households in Scotland.17 Using this cohort, who are at increased risk
of exposure to SARS-CoV-2 and COVID-19, we now test the hypothesis that the risk of COVID-19 is
attenuated where adults share households with children aged 11 and younger.
Methods
Population, data sources and record linkage
The population studied is described in detail elsewhere. Briefly, we previously created a cohort of
adults who were either healthcare workers (aged 18 to 65) or healthcare worker’s household
members (all ages). Healthcare workers were identified via a human resources database which
includes all staff directly-employed by the NHS in Scotland on the 1st of March 2020, as well as via a
database of doctors contracted to provide general practice services. Household members of these
groups were identified via a common address using a complete listing of all individuals registered
with general practices in Scotland (which includes almost the entire Scottish population). Individuals
were assigned to the same household only if the address (including house and, if included,
apartment number) was identical; fuzzy matching was not allowed. We linked these data to multiple
Scotland-wide databases.17 These included datasets containing individual level clinical information
for virology testing for SARS-CoV-2, general hospitalisation data, community prescribing, critical care
admissions and statutory death registration records.
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Outcome
Outcome, exposure, and covariate information was examined for all adults aged 18 years or over
living in a healthcare worker household. The primary outcome was COVID-19 requiring
hospitalisation, defined as a first positive PCR test for SARS-CoV-2 up to 28 days prior to, or during, a
hospital admission. We also report findings for the secondary outcomes of any COVID-19 (defined
as any positive PCR test for SARS-CoV-2, regardless of hospitalisation or death status) and severe
COVID-19 (defined as a first positive PCR test for SARS-CoV-2 up to 28 days prior to admission to
intensive care or a high-dependency unit, or death). Any outcome event occurring between the 1st
of March and 7th of July 2020 was included.
COVID-19 requiring hospitalisation was chosen as the primary outcome rather than any COVID-19 as
we were concerned that higher rates of acute respiratory infections in members of households
containing small children may lead to increased testing for SARS-CoV-2 and hence ascertainment
bias.
Exposure
The primary exposure was the number of children aged 0 to 11 (hereafter referred to as young
children) in each household. In additional analyses, risks for household members of pre-school
children (aged 0-4) and primary school-aged children (aged 5-11) were examined separately as were
the risks of sharing a household with older children (aged 12-17) and with other adults.
Covariates
Data on age, sex and the Scottish Index of Multiple Deprivation (SIMD) quintile (an area-based
measure of socioeconomic deprivation) were obtained from the linked databases. Pre-specified
comorbidities (see Table S1) were defined using previous hospitalisation and prescribing data.
Ethnicity was estimated using the ONOMAP algorithm, which estimates ethnicity based on forename
and surname.18
Occupational covariates were defined at the household level based on the characteristics of the
household member who was a healthcare worker. These included the healthcare worker’s
occupation (eg medical, nursing, allied health professional), exposure to patients (eg in a patient
facing or non-patient facing role) seniority-level, length of service, immigration status, and full/part-
time working status. Where more than one household member was a healthcare worker, the highest
risk designation (eg patient facing rather than non-patient facing) was applied.
Statistical analysis
The cumulative incidence of hospitalisation for COVID-19 for adults was plotted according to the
number of young children in their household. We modelled COVID-19 requiring hospitalisation using
Cox regression, calculating robust standard errors to allow for clustering due to shared household
membership and stratifying on groups of health board areas to allow for differences in baseline
hazard. We present effect estimates for a minimal model adjusting for age, a full model including all
the covariates and intermediate models to allow readers to judge the robustness of any findings to
different model specifications. In addition to the primary outcome, we also produced estimates for
two other outcomes any COVID-19 and severe COVID-19. We also conducted a range of sensitivity
analyses including additional covariates, and/or restricting the cohort to different populations (eg
households where all adults were healthcare workers).
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Results
Of the 310,097 adults living in a healthcare worker household, 241,266 (78%), 41,198 (13%), 23,783
(7.8%) and 3,850 (1.2%) shared a household with 0, 1, 2 and 3 or more young children respectively.
The proportion of women were similar across these categories. Those who did not share a
household with young children were on average 5-years older than those who did; were more likely
to live in the most deprived areas. However, adults who were of non-white ethnicity were more
likely to share a household with young children (Table 1) than were those of white ethnicity.
Comorbidity was less common among adults sharing households with young children, and the
proportion with comorbid diseases fell as the number of young children in the household increased
(Table 1 and Supplementary Table S1).
Household composition differed according to the number of younger children. Households with
more children were more likely to include 2 or more adults. More than a quarter of adults who
shared a household with a single child under 12 also shared a household with a child aged 12-17.
Fewer than 1 in 10 adults in a household with young children also shared a household with anyone
over the age of 65 (Supplementary Table S2).
Testing for SARS-CoV-2
Testing for SARS-CoV-2 was low overall but was commoner among adults who shared a household
with young children. The proportion of adults tested ranged from 6.11% among those who did not
share a household with young children to 9.19% in those who shared a household 3 or more young
children (Table 1).
COVID-19 requiring hospitalisation
Compared to those in households without children, the risk of COVID-19 requiring hospitalisation
was lower in those with one child and lower still in those with two or more children (Figure 1). In
unadjusted analyses, the hazard ratio (HR) for this association was 0.72 per child (95% CI 0.60-0.85, p
<0.001, Table 2) - ie the risk of COVID-19 requiring hospitalisation fell, on average, by 0.72-fold per
each additional young child in the household. On adjusting for the adult’s own age (ie not the age of
the children in the household), this association was attenuated (HR per child 0.83; 95% CI 0.70-0.99),
with further smaller changes after adjusting for remaining pre-specified potential confounders (sex,
socioeconomic deprivation, occupation, professional role, staff/non-staff status, the number of
adolescents in the household, the number of adults in each household, and the comorbidity counts
plus selected comorbidities - see Table S1) and for whether or not the healthcare worker in the
adult’s household was part-time or full time, which was not pre-specified. For this fully adjusted
analysis, the confidence interval included the null, and so was consistent with no beneficial effect of
sharing a household with young children (HR per child 0.89; 95% CI 0.74-1.06).
Similar, but slightly stronger associations were found when the analysis was restricted to households
where at least one member of staff had a patient-facing role (fully adjusted model, HR per child 0.83;
95% CI 0.68-1.02, Supplementary Table S3), a group with greater occupational exposure to SARS-
CoV-2 than non-patient facing healthcare workers, although on formally testing for an interaction
between patient facing and non-patient facing groups, the coefficient included the null, (P-value for
interaction = 0.80). There was also a clearer “dose response” across categories from 0 to ≥3 children
in both the unadjusted and adjusted models for adults in patient facing compared to adults in non-
patients facing households (Supplementary Table S3).
To explore whether there was residual confounding even after adjusting for part-time working (i.e.
in case part-time workers with more children worked fewer hours and hence had less exposure to
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people with COVID-19) we also stratified adults by whether or not they shared a household with a
healthcare worker who worked part-time. We found an inverse association between the number of
young children in the household and risk of COVID-19 requiring hospitalisation in the part-time
stratum (HR per child 0.63; 95% CI 0.43-0.92) but not in the whole time stratum (1.04; 95% CI 0.84-
1.28, P-interaction = 0.007). Separately, to examine for residual confounding by comorbidity, we
restricted the analyses to adults who had no known comorbidities, finding similar effect measure
estimates to those seen in the main analysis (HR per child on adjusting for demographic and
occupational factors 0.83; 95% CI 0.68-1.03). Similar results were also obtained on restricting to
adults who had 2 or fewer prescriptions within the previous 9 months (HR per child was 0.91; 95% CI
0.71-1.18, 1.34; 95% CI 0.84-2.15).
Any COVID-19
The point estimate for the inverse association between number of young children in the household
and the risk of any COVID-19 was similar to that found for the risk of COVID-19 requiring
hospitalisation (Table 3). However, reflecting the much larger number of outcome events when
looking at any COVID-19 compared to COVID-19 requiring hospitalisation, confidence intervals were
narrower for any COVID-19 and did not include the null (HR per child in fully adjusted models 0.89;
95% CI 0.84-0.95).
As with the primary outcome, we found similar inverse associations between number of young
children in the household and the risk of any COVID-19 after restricting the analysis to participants
without any known comorbidities (0.89; 95% CI 0.84-0.95) and to those who had 2 or fewer
prescriptions within the previous 9 months (adjusting for demographic and occupational factors the
HR per child was 0.89; 95% CI 0.83-0.96.). Compared to the primary outcome, the associations for
any COVID-19 was more similar according to part-time working status (HR per child 0.85; 95% CI
0.77-0.92 for part-time and 0.92; 95% CI 0.84-1.00 non-part time, P-interaction = 0.75).
Adjusting for the same variables, we explored the risk of any COVID-19 after more finely categorising
younger children into primary school and pre-school children. On formal testing, this separate
categorisation improved the model fit (Chi-square = 5.74, df = 0.99, p = 0.02) and slightly stronger
associations were observed in pre-school children than in primary school children (in age adjusted
models, HR per pre-school child 0.82; 95% CI 0.74-0.91 versus HR per primary school child 0.94; 95%
CI 0.88-1.00). In contrast there was no evidence of a lower risk where adolescents or adults 18 or
older were present in the household (Table 4). Similar differences between the age-groups, but with
wider 95% confidence intervals reflecting the smaller numbers of events, were also found for the
primary outcome of COVID-19 requiring hospitalisation (Supplementary Appendix Table S4).
Additional analyses
We also examined associations for the much less common outcome, severe COVID-19, the results of
which are shown in the supplementary appendix in Tables S5 and S6. The full set of regression
coefficients and standard errors for all fitted models are provided at
github_repository_to_be_made_public_following peer_review.
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Discussion
We found that among a cohort of over 300,000 adults living in a household containing a healthcare
worker in Scotland, the risk of testing positive for SARS-CoV-2 during the first wave of the COVID-19
pandemic was lower for individuals living with young children (0-11 years), and that this persisted
after adjusting for potential confounding variables. Risk of hospitalisation for COVID-19 (our primary
outcome) was similarly lower for those living with young children, although this finding did not reach
statistical significance.
To support decision making concerning the closure of schools during the COVID-19 pandemic,
several studies have examined the transmission of COVID-19 from children to adults. A community
surveillance study in England and Wales conducted by Public Health England found that children
rarely tested positive for SARS-CoV-2, even when they had symptoms of acute respiratory infection;
this was particularly true for younger children19 Studies examining contacts of younger children with
SARS-CoV-2 have also shown low rates of secondary cases, particularly in non-household settings,
consistent with minimal or no transmission from children to adults.20 Although we were mainly
concerned with testing the hypothesis that contact with children might exert a protective effect in a
high-risk population (healthcare workers), our study is also consistent with the findings that children
do not pose a substantial risk of infection to adults with whom they share a household.
Our pre-specified hypothesis, that close contact with young children may actually protect against the
risk of COVID-19 among adults, has not been extensively studied. We only found one study which
touched on this question, a survey of exposures among people who had recovered from SARS-CoV-
2.16 Ours is the first cohort study of which we are aware to formally test this hypothesis, for which
the findings provide a degree of support.
A number of limitations of this study should be acknowledged. First, the observed inverse
association may be a chance finding. For the primary outcome, on including in our regression models
the potential confounders which we had pre-specified, the confidence interval included the null.
Although we knew that statistical power would be limited, we had decided, a priori, to use COVID-19
requiring hospitalisation as the primary outcome rather than any COVID-19 (which was much
commoner), as we were concerned that high rates of (non-SARS-CoV-2) acute respiratory infection
in households with small children may cause ascertainment bias, increasing the apparent rate of any
COVID-19 in these groups as a result of increased testing. The level of testing was indeed higher
among those adults who shared a household with young children, suggesting that there may be
increased ascertainment. Despite this, in the fully adjusted models, we found similar point estimates
regardless of whether the outcome was hospitalisation or any COVID-19. For the commoner
outcome these estimates were more precise with confidence intervals that did not include the null,
which suggests that the finding for the primary outcome may be real, rather than a chance
observation.
Another possibility is that the identified association may have been confounded by part-time
working. For the primary outcome, on stratifying the analysis into households where healthcare
workers did and did not work part time, the association was evident in the former group but null in
the latter. Since within part-time healthcare workers those with more children may work fewer
hours (and therefore have lower exposure to SARS-CoV-2), and since we lacked accurate data on
hours worked during the pandemic, the apparent effect of sharing a household with young children
may be due to unmeasured confounding. Nonetheless, the association between the number of
children and the risk of any case of COVID-19 a much commoner outcome did persist on
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stratifying for part-time/whole-time status. Consequently, unmeasured confounding by time spent
in high-risk occupational settings seems unlikely.
Residual confounding due to better health in those households with more children (perhaps
affecting the decision to have more children) is also an unlikely explanation because the observed
associations were also found on restricting the analyses to healthier adults.
From first principles, any protective effect of children on COVID-19 rate and severity in their
household contacts would seem likely to involve cross-reactive immunity to endemic coronavirus
infections acquired outside the home, e.g. at nursery or school. Evidence of antigenic similarity
between N proteins of SARS-CoV-2 and those of endemic beta coronaviruses (strains Cov-OC43 and
Cov-NL63) have now been shown in studies of cell-mediated immunity, and there is also evidence of
cross-reactivity in antibody-mediated immunity, although it is currently uncertain how well this
protects against COVID-19.49 Secondly, children who had respiratory samples (sputum, broncho-
alveolar washings etc) obtained for clinical reasons (e.g. respiratory tract infection) have previously
been found to have high levels of seasonal coronaviruses,11 and a similar study identified that CoV-
OC43 which like SARS-CoV-2 is a beta-coronavirus, was commonest in children under 5.12 Thirdly, as
well as having higher rates of infection (or asymptomatic carriage) children must also be capable of
transmitting seasonal coronaviruses to adults with whom they share households. Younger adults
(aged 15-44) which includes those ages most likely to share households with young children, have
higher levels of antibodies to N proteins of CoV-OC43 than do older adults,21 but whether this
reflects exposure at home via contact with children, or elsewhere, is unknown.
Alternatively, children could exert a protective effect through stimulation of the innate immune
system of adults with whom they are close contacts13 Children positive for seasonal coronaviruses
often test positive for unrelated respiratory viruses. It is likely that any such effect would be shorter-
term than one based on changes in specific acquired immunity. Two clinical trials are currently
underway involving vaccination with BCG for COVID-19,22,23 which will help determine whether such
an effect is plausible.
Notwithstanding possible mechanisms, our findings provide sufficient evidence of a potentially
interesting protective effect against COVID-19 infection in households with young children to
warrant further study in other settings. High exposure settings, such as occupational groups or
populations which have had increased exposure to SARS-CoV-2, would be of particular interest.
Other adults that could usefully be studied are those who have had contact with large numbers of
children, such as those who work in primary schools and nurseries, particularly in geographical
settings where exposure to SARS-CoV-2 has also been common. As reliable population screening for
antibodies to SARS-CoV-2 becomes widespread, another interesting test of our hypothesis would be
to compare the prevalence of antibodies to SARS-CoV-2, and in parallel antibodies to seasonal
antibodies viz. Cov-OC43, in those with and without substantive exposure to children of different
age groups.
Our findings also raise intriguing questions around the design and evaluation of future vaccination
programmes against SARS-CoV-2. For example, it would be important to examine the differential
production of IgM and IgG antibodies to SARS-CoV-2 in adults and children to evaluate the possibility
that children might pre-immunize’ adults with endemic coronaviruses. Subsequent vaccination
could then trigger a more rapid secondary immune response. This is an important practical point,
since recent studies of antibody kinetics following natural infection with SARS-CoV-2 have indicated
that antibodies are generally not detectable for 10-14 days, and in some patients are never
detectable.24 This lag time may be too long to ensure protection against severe COVID-19. Could
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9
exposure to children perhaps enhance the efficacy of SARS-CoV-2 vaccines? Further, although long-
term studies are not yet feasible with SARS-CoV-2, follow-up after experimental Cov-OC43 infection
indicates that seropositivity wanes fairly rapidly over time, with many volunteers becoming negative
within a year.10 This raises the possible risk of re-infection, and the consequent need for follow-up
vaccination, in which case any possible role of children acting as ‘natural vaccine boosters;’ should
be taken into consideration.
Conclusion
In a large occupational cohort, increased household exposure to young children was associated with
an attenuated risk of testing positive for SARS-CoV-2 and appeared to also be associated with (non-
statistically-significant) attenuated risk of COVID-19 disease severe enough to require
hospitalisation. Verification of this finding is needed in other settings where both exposure to SARS-
CoV-2 and contact with young children are common. These findings have potentially important
implications for future control of the COVID-19 pandemic, for example through informing policy on
nursery and school closure and vaccination.
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12
Table 1 - Baseline characteristics of adults living in healthcare worker households by
number of young children in household
0 children
aged 0-11
1 child
aged 0-11
2 children
aged 0-11
3+ children
aged 0-11
Number of adults
241266
41198
23783
3850
Adults who are healthcare workers
121004 (50.15)
22025 (53.46)
13179 (55.41)
2237 (58.10)
Age, mean (standard deviation)
44.53 (15.04)
39.82 (10.58)
39.01 (8.08)
38.47 (6.62)
Male
105116 (43.57)
17639 (42.82)
10803 (45.42)
1783 (46.31)
Scottish index of multiple deprivation
1 - most deprived
37242 (15.44)
5655 (13.73)
2447 (10.29)
373 (9.69)
2
46147 (19.13)
7700 (18.69)
3599 (15.13)
582 (15.12)
3
48659 (20.17)
7491 (18.18)
4280 (18.00)
706 (18.34)
4
52847 (21.90)
9701 (23.55)
6102 (25.66)
999 (25.95)
5 - least deprived
56371 (23.36)
10651 (25.85)
7355 (30.93)
1190 (30.91)
Race/ethnicity - Non-white
7768 (3.22)
2088 (5.07)
1162 (4.89)
259 (6.73)
Comorbidity count
None
207796 (86.13)
37315 (90.57)
21924 (92.18)
3564 (92.57)
One
24897 (10.32)
3231 (7.84)
1579 (6.64)
252 (6.55)
Two or more
8573 (3.55)
652 (1.58)
280 (1.18)
34 (0.88)
Occupation of healthcare worker in
household
Nursing and midwifery
102514 (42.49)
18688 (45.36)
10085 (42.40)
1530 (39.74)
Administrative services
44929 (18.62)
6710 (16.29)
3236 (13.61)
404 (10.49)
Support services
27294 (11.31)
3232 (7.85)
1386 (5.83)
236 (6.13)
Medical and dental
20836 (8.64)
4326 (10.50)
3586 (15.08)
849 (22.05)
Allied health profession
20007 (8.29)
3798 (9.22)
2974 (12.50)
442 (11.48)
Other
25686 (10.65)
4444 (10.79)
2516 (10.58)
389 (10.10)
Occupational role of healthcare worker in
household
Non-patient facing
50441 (20.91)
7453 (18.09)
3667 (15.42)
471 (12.23)
Patient facing
137697 (57.07)
25461 (61.80)
15485 (65.11)
2627 (68.23)
Undetermined
53128 (22.02)
8284 (20.11)
4631 (19.47)
752 (19.53)
Part time working in healthcare worker in
household
Whole time
147608 (61.18)
19482 (47.29)
8296 (34.88)
1206 (31.32)
Part time
88351 (36.62)
20329 (49.34)
14183 (59.64)
2281 (59.25)
Not recorded
5307 (2.20)
1387 (3.37)
1304 (5.48)
363 (9.43)
Tested for SARS-CoV-2
14736 (6.11)
2835 (6.88)
1823 (7.67)
354 (9.19)
Statistics are the number (percentage) of adults with each characteristic except for age, which is given as the mean and standard
deviation.
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13
Table 2 - Risk and hazard ratios for COVID-19 requiring hospitalisation for adults living
in healthcare worker households by number of young children in household
1 child aged
0-11
2 children
aged 0-11
3+ children
aged 0-11
Per child
N adults with COVID-19 requiring
hospitalisation
52
15
2
-
Total N adults
41198
23783
3850
-
Risk per 10,000
12.6
6.3
5.2
-
Unadjusted
0.86
(0.64-1.16)
0.41
(0.25-0.69)
0.36
(0.09-1.45)
0.72
(0.60-0.85)
Model 1
1.07
(0.79-1.45)
0.54
(0.32-0.91)
0.50
(0.12-2.00)
0.83
(0.70-0.99)
Model 2
1.10
(0.81-1.50)
0.57
(0.34-0.96)
0.49
(0.12-2.00)
0.85
(0.72-1.01)
Model 3
1.12
(0.82-1.52)
0.58
(0.35-0.98)
0.50
(0.12-2.02)
0.86
(0.72-1.02)
Model 4
1.15
(0.84-1.58)
0.62
(0.37-1.05)
0.55
(0.14-2.21)
0.89
(0.74-1.06)
Hazard ratios obtained from Cox proportional hazard models. Model 1 adjusts for age using a penalised spline function. Model 2
additionally adjusts for sex, Scottish Index of Multiple Deprivation, occupation (eg nursing, medical), occupational role (patient facing, non-
patient facing, undetermined), healthcare worker (yes/no), length of service, number of children aged 12 to 17 in household, number of
adults in household. Model 3 additionally adjusts for the comorbidity count and specific conditions (ischaemic heart disease, other heart
disease, other circulatory system diseases, advanced chronic kidney disease, asthma and chronic lower respiratory disease, neurological
disorders, decompensated liver disease, any immunological condition, malignant neoplasms, disorders of oesophagus, stomach and
duodenum, type 1 diabetes and type 2 diabetes). Model 4 additionally adjusts for part-time status.
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14
Table 3 - Risk and hazard ratios for any COVID-19 for adults living in healthcare worker
households by number of young children in household
No children
aged 0-11
1 child aged 0-
11
2 children aged
0-11
3+ children aged
0-11
Per child
N adults with
any COVID-19
3222
507
268
52
-
Total N adults
241266
41198
23783
3850
-
Risk per 10,000
133.5
123.1
112.7
135.1
-
Unadjusted
1
0.92
(0.83-1.01)
0.84
(0.73-0.96)
1.02
(0.75-1.37)
0.94
(0.89-0.99)
Model 1
1
0.84
(0.75-0.93)
0.75
(0.65-0.86)
0.89
(0.66-1.21)
0.88
(0.83-0.93)
Model 2
1
0.84
(0.75-0.93)
0.74
(0.65-0.86)
0.85
(0.63-1.15)
0.88
(0.83-0.93)
Model 3
1
0.83
(0.75-0.93)
0.75
(0.65-0.86)
0.85
(0.63-1.15)
0.88
(0.83-0.93)
Model 4
1
0.85
(0.77-0.95)
0.77
(0.67-0.89)
0.89
(0.66-1.20)
0.89
(0.84-0.95)
Model fitting and covariates as per footnote of Table 2.
Table 4 - Hazard ratios for any COVID-19 for adults living in healthcare worker
households by number of persons in household of different ages
Per child
aged 0 to 4
Per child
aged 5 to 11
Per child
aged 12 to 17
Per adult
aged 18 or above
Unadjusted
0.86
(0.78-0.95)
0.98
(0.92-1.05)
1.05
(0.98-1.12)
0.81
(0.78-0.84)
Model 1
0.83
(0.74-0.92)
0.91
(0.85-0.97)
1.00
(0.93-1.07)
0.97
(0.89-1.06)
Model 2
0.80
(0.72-0.89)
0.92
(0.86-0.99)
1.02
(0.95-1.09)
1.04
(1.01-1.08)
Model 3
0.80
(0.72-0.89)
0.92
(0.86-0.99)
1.02
(0.95-1.09)
1.04
(1.01-1.08)
Model 4
0.82
(0.74-0.91)
0.94
(0.88-1.00)
1.02
(0.96-1.10)
1.04
(1.01-1.07)
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15
Model specification and covariates as per footnote of Table 2. The unadjusted models and model 1 were fitted separately for each
exposure (eg aged 0 to5, aged 6 to 11 etc) but all exposures were included in models 2, 3 and 4. The effect estimates corresponds to “per
child” column in Tables 2-3, where the counts of children and adults were treated as continuous variables, which assumes that any
association between the number of children (or adults) and the hazard rate is log-linear.
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16
Figure 1 Risk of COVID-19 requiring hospitalisation in adults living in healthcare worker
households by number of young children (aged 0 to 11) in household
Cumulative incidence (risk) plots of COVID-19 requiring hospitalisation by number of young children (aged 0 to 11) in household.
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1
Table S1 Comorbidity among adults living in healthcare worker
households by number of young children in household
0 children
aged 0-11
1 child aged
0-11
2 children
aged 0-11
3 or more children
aged 0-11
Any comorbidity
33470
(13.87)
3883
(9.43)
1859
(7.82)
286 (7.43)
Ischaemic heart disease
4067 (1.69)
256
(0.62)
74 (0.31)
13 (0.34)
Other heart disease
7298 (3.02)
604
(1.47)
250 (1.05)
38 (0.99)
Other circulatory system diseases
4386 (1.82)
494
(1.20)
237 (1.00)
49 (1.27)
Advanced chronic kidney disease
224 (0.09)
30 (0.07)
14 (0.06)
0
Asthma and chronic lower
respiratory disease
5311 (2.20)
745
(1.81)
394 (1.66)
65 (1.69)
Neurological disorders
1249 (0.52)
161
(0.39)
91 (0.38)
11 (0.29)
Decompensated liver disease
203 (0.08)
13 (0.03)
8 (0.03)
0
Any immunological condition
217 (0.09)
25 (0.06)
13 (0.05)
0
Malignant Neoplasms
7854 (3.26)
819
(1.99)
443 (1.86)
52 (1.35)
Disorders of oesophagus, stomach
and duodenum
5707 (2.37)
676
(1.64)
325 (1.37)
50 (1.30)
Diabetes, type 1
1617 (0.67)
274
(0.67)
160 (0.67)
17 (0.44)
Diabetes, type 2
7660 (3.17)
618
(1.50)
205 (0.86)
32 (0.83)
Diabetes, unknown type
470 (0.19)
57 (0.14)
24 (0.10)
6 (0.16)
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2
Tables S2a to S2d Number of adults living in healthcare worker
households according household composition
Table S2a Number of adults aged 18 by number of young children and children aged
12-17 in household
Number of
children aged 12
to 17 in
household
0 children aged
0-11
1 child aged 0-11
2 children aged
0-11
3 or more
children aged 0-
11
0 aged 12-17
208714 (86.51)
29855 (72.47)
21470 (90.27)
3559 (92.44)
1 aged 12 to 17
24359 (10.10)
9521 (23.11)
2051 (8.62)
215 (5.58)
2 aged 12 to 17
7596 (3.15)
1677 (4.07)
244 (1.03)
61 (1.58)
3+ aged 12 to 17
597 (0.25)
145 (0.35)
18 (0.08)
15 (0.39)
Table S2b Number of adults aged 18 by number of young children and adults aged
18 or older in household
Number of adults
aged 18 or older
in household
0 children aged
0-11
1 child aged 0-11
2 children aged
0-11
3 or more
children aged 0-
11
1 aged 18
39395 (16.33)
5026 (12.20)
2041 (8.58)
365 (9.48)
2 aged 18
78980 (32.74)
23042 (55.93)
17499 (73.58)
3273 (85.01)
3+ aged 18
122891 (50.94)
13130 (31.87)
4243 (17.84)
212 (5.51)
Table S2c Number of adults aged 18 by number of young children and adults aged 65
to 74 in household
Number of adults
aged 65 to 74 in
household
0 children aged
0-11
1 child aged 0-11
2 children aged
0-11
3 or more
children aged 0-
11
0 aged 65-74
219469 (90.97)
39659 (96.26)
23208 (97.58)
3797 (98.62)
1 aged 65-74
17701 (7.34)
1310 (3.18)
509 (2.14)
43 (1.12)
2 aged 65-74
3925 (1.63)
229 (0.56)
66 (0.28)
10 (0.26)
3+ aged 65-74
171 (0.07)
0
0
0
Table S2d Number of adults aged 18 by number of young children and adults aged
75 or older in household
Number of adults
aged 75 or older
in household
0 children aged
0-11
1 child aged 0-11
2 children aged
0-11
3 or more
children aged 0-
11
0 aged 75
231223 (95.84)
40226 (97.64)
23387 (98.33)
3817 (99.14)
1 aged 75
8290 (3.44)
827 (2.01)
361 (1.52)
17 (0.44)
2 aged 75
1674 (0.69)
145 (0.35)
35 (0.15)
16 (0.42)
3+ aged 75
79 (0.03)
0
0
0
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3
Table S3 Risk and hazard ratios for COVID-19 requiring hospitalisation
for adults living in patient-facing healthcare worker households* by
number of young children in household.
0
children
aged 0-
11
1 child
aged 0-
11
2 children
aged 0-11
3 or more
children
aged 0-11
Per
child
Events
252
36
13
1
-
N
137697
25461
15485
2627
-
Risk per 10,000
18.3
14.1
8.4
3.8
-
Unadjusted
1
0.78
(0.55-
1.12)
0.44
(0.26-
0.76)
0.21
(0.03-1.53)
0.69
(0.57-
0.84)
Model 1
1
0.90
(0.63-
1.29)
0.52
(0.30-
0.91)
0.26
(0.04-1.85)
0.76
(0.62-
0.92)
Model 2
1
0.95
(0.66-
1.36)
0.59
(0.33-
1.03)
0.29
(0.04-2.03)
0.80
(0.65-
0.97)
Model 3
1
0.96
(0.67-
1.38)
0.59
(0.34-
1.04)
0.29
(0.04-2.05)
0.80
(0.66-
0.98)
Model 4
1
1.00
(0.69-
1.44)
0.64
(0.36-
1.13)
0.32
(0.05-2.27)
0.83
(0.68-
1.02)
Model fitting and covariates as per footnote of Table 2 in the main manuscript
* Households where at least one healthcare worker occupies a patient facing role.
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4
Table S4 Hazard ratios for COVID-19 requiring hospitalisation for
adults living in healthcare worker households by number of persons in
household of different ages
Per child
aged 0 to 4
Per child
aged 5 to 11
Per child
aged 12 to 17
Per adult
aged 18 or above
Unadjusted
0.59 (0.41-0.84)
0.79 (0.65-0.97)
1.01 (0.81-1.25)
0.95 (0.87-1.03)
Model 1
0.79 (0.56-1.13)
0.85 (0.69-1.05)
1.00 (0.81-1.24)
0.97 (0.89-1.06)
Model 2
0.80 (0.56-1.14)
0.87 (0.71-1.08)
1.02 (0.82-1.27)
1.04 (0.94-1.13)
Model 3
0.81 (0.57-1.15)
0.88 (0.71-1.09)
1.03 (0.83-1.27)
1.04 (0.95-1.14)
Model 4
0.84 (0.59-1.20)
0.91 (0.73-1.12)
1.04 (0.84-1.29)
1.03 (0.94-1.13)
Model specification and covariates as per footnote of Table 4.
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5
Table S5 Risks and hazard ratios for severe COVID-19 for adults living
in healthcare worker households by number of young children in
household
0 children
aged 0-11
1 child
aged 0-11
2 children
aged 0-11
3 or more
children aged 0-
11
Per child
N adults with
severe COVID-19
83
11
3
0
-
Total N adults
241266
41198
23783
3850
-
Risk per 10,000
3.4
2.7
1.3
0.0
-
Unadjusted
1
0.78 (0.42-
1.46)
0.37 (0.12-
1.18)
<0.01
0.65
(0.44-
0.95)
Model 1
1
1.30 (0.69-
2.46)
0.75 (0.24-
2.36)
<0.01
0.94
(0.66-
1.34)
Model 2
1
1.35 (0.72-
2.52)
0.75 (0.23-
2.38)
<0.01
0.94
(0.67-
1.34)
Model 3
1
1.39 (0.74-
2.60)
0.73 (0.23-
2.38)
<0.01
0.93
(0.66-
1.31)
Model 4
1
1.44 (0.77-
2.71)
0.80 (0.24-
2.60)
<0.01
0.99
(0.69-
1.40)
Model fitting and covariates as per footnote of Table 2 in the main manuscript.
Table S6 Hazard ratios for severe COVID-19 for adults living in
healthcare worker households by number of persons in household of
different ages
Per child
aged 0 to 5
Per child
aged 6 to 11
Per child
aged 12 to 17
Per adult
aged 18 or above
Unadjusted
0.41 (0.14-1.20)
0.78 (0.51-1.19)
0.62 (0.36-1.08)
1.23 (1.05-1.45)
Model 1
0.75 (0.27-2.05)
1.02 (0.67-1.54)
0.68 (0.39-1.17)
1.22 (1.02-1.46)
Model 2
0.70 (0.25-1.95)
1.06 (0.71-1.57)
0.68 (0.39-1.17)
1.22 (1.01-1.48)
Model 3
0.67 (0.24-1.87)
1.05 (0.71-1.56)
0.68 (0.39-1.17)
1.23 (1.02-1.48)
Model 4
0.72 (0.27-1.96)
1.11 (0.74-1.66)
0.68 (0.40-1.18)
1.23 (1.02-1.48)
Model specification and covariates as per footnote of Table 4.
. CC-BY 4.0 International licenseIt is made available under a
perpetuity.
is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted September 22, 2020. ; https://doi.org/10.1101/2020.09.21.20196428doi: medRxiv preprint
... It has now been shown several times that although young children are significantly less involved in virus transmission than adults, they probably make an age-dependent contribution to the distribution of the virus -which does not, however, justify school closures [50]. On the other hand, a study of 300,000 households found that the more children a family had, the less frequently severe COVID-19 disease occurred in adults [51]. (This study could easily be replicated using secondary health insurance data in many countries). ...
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Background: Whether children (0-11 years) and adolescents (12 to 18 years) should receive COVID-19 vaccinations is a topic of debate. Methods: Through iterative and systematic engagement with the literature, aspects were collected that should be clarified collectively and individually before vaccines are recommended. These aspects were analyzed and discussed in a consensus process and sent to pediatric professional associations for comment. Feedback was fully considered. Results: On the question of whether COVID-19 vaccination should be recommended for children in general, 7 child-related aspects and 7 society-related aspects to be considered were identified: 1. acute burden of disease, 2. sequelae (PIMS and Long-COVID vs. Long-Lockdown),, 3. mortality, 4. short-, medium-, and long-term side-effect spectrum of vaccines and ingredients, 5. immunity development to vaccination, 6. influence of vaccination on the emergence of immune escape mutations, 7. natural vs. vaccine-induced immunity. The society-related aspects concern whether COVID-19 vaccination of children can be recommended for the good of the community, independent of (or even counter to) the good of children: 8. Role of children in the pandemic, 9. Reduction of transmission, 10. Vaccine-specific reduction of severe or fatal cases in adults by vaccinating children, 11. Environmental, economic, and social consequences of vaccination, 12. Impact of childhood vaccination on selection pressures, 13. Risk of shifting disease from childhood to later life, including the unlikelihood of eradicating SARS-CoV-2. 14. Access to community facilities and participation in social life. Discussion: These 14 aspects provide a guideline for clarifying whether a particular vaccination should be recommended – for the respective age groups and in the context of the respective family, the respective country and its conditions. For Germany, there is currently no indication for a general vaccination recommendation for children and adolescents.
... An important finding of our study is that participants living with children aged <12 years were less likely to be seropositive. Findings from a Scottish study among over 300'000 HCW households [14] and a population-based UK cohort [15] are consistent with our results. An intriguing hypothesis is that frequent infections in childhood with endemic coronaviruses (e.g. ...
Article
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Objectives Protecting healthcare workers (HCW) from Coronavirus Disease-19 (COVID-19) is critical to preserve the functioning of healthcare systems. We therefore assessed seroprevalence and identified risk factors for Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) seropositivity in this population. Methods Between June 22nd and August 15th 2020, HCW from institutions in Northern/Eastern Switzerland were screened for SARS-CoV-2 antibodies. We recorded baseline characteristics, non-occupational and occupational risk factors. We used pairwise tests of associations and multivariable logistic regression to identify factors associated with seropositivity. Results Among 4’664 HCW from 23 healthcare facilities, 139 (3%) were seropositive. Non-occupational exposures independently associated with seropositivity were contact with a COVID-19-positive household (adjusted OR=59, 95%-CI: 33-106), stay in a COVID-19 hotspot (aOR=2.3, 95%-CI: 1.2-4.2), and male sex (aOR=1.9, 95%-CI: 1.1-3.1). Blood group 0 vs. non-0 (aOR=0.5, 95%-CI: 0.3-0.8), active smoking (aOR=0.4, 95%-CI: 0.2-0.7), living with children <12 years (aOR=0.3, 95%-CI: 0.2-0.6), and being a physician (aOR 0.2, 95%-CI: 0.1-0.5) were associated with decreased risk. Other occupational risk factors were close contact to COVID-19 patients (aOR=2.7, 95%-CI: 1.4-5.4), exposure to COVID-19-positive co-workers (aOR=1.9, 95%-CI: 1.1-2.9), poor knowledge of standard hygiene precautions (aOR=1.9, 95%-CI: 1.2-2.9), and frequent visits to the hospital canteen (aOR=2.3, 95%-CI: 1.4-3.8). Conclusions Living with COVID-19-positive households showed the strongest association with SARS-CoV-2 seropositivity. We identified several potentially modifiable work-related risk factors, which might allow mitigation of the COVID-19 risk among HCW. The lower risk among those living with children, even after correction for multiple confounders, is remarkable and merits further study.
... It has now been shown several times that although young children are significantly less involved in virus transmission than adults, they probably make an age-dependent contribution to the distribution of the virus -which does not, however, justify school closures [50]. On the other hand, a study of 300,000 households found that the more children a family had, the less frequently severe COVID-19 disease occurred in adults [51]. (This study could easily be replicated using secondary health insurance data in many countries). ...
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Hintergrund: Die Frage der COVID-19 Impfung von Kindern und Jugendlichen wird gegenwärtig diskutiert. Methode: Durch iterative und systematische Auseinandersetzung mit der Literatur wurden Aspekte gesammelt, die kollektiv und individuell geklärt werden sollten, bevor Impfungen für Kinder empfohlen werden. Diese Aspekte wurden in einem Konsensverfahren mit Kolleg*innen und Eltern analysiert, diskutiert und anschließend an pädiatrische Fachverbände zur Kommentierung geschickt. Rückmeldungen wurden vollumfänglich berücksichtigt. Ergebnisse: Zu der Frage, ob eine COVID-19-Impfung für Kinder allgemein empfohlen werden sollte, wurden 7 kinderbezogene und 7 gesellschaftsbezogene zu berücksichtigende Aspekte identifiziert. Kinderbezogene Aspekte betreffen: 1. Akute Krankheitslast, 2. Folgeschäden (PIMS und Long-COVID vs. Long-Lockdown), 3. Mortalität, 4. Kurz-, Mittel-, und Langzeitnebenwirkungsspektrum der Impfungen und Ingredienzen, 5. Immunitätsentwicklung gegen Impfungen, 6. Einfluss der Impfungen auf das Entstehen von Immun-Escape Mutationen, 7. Natürliche vs. impfbedingte Immunität. Die gesellschaftsbezogenen Aspekte betreffen die Frage, ob die COVID-19-Impfung von Kindern zum Wohle der Gemeinschaft, unabhängig vom Wohle der Kinder (oder sogar ihm entgegengerichtet), empfohlen werden kann: 8. Rolle der Kinder in der Pandemie, 9. Reduktion der Transmission, 10. Reduktion von schweren oder tödlichen Fällen bei Erwachsenen durch Impfung der Kinder, 11. Ökologische, ökonomische und soziale Konsequenzen der Impfung, 12. Einfluss einer Impfung der Kinder auf den Selektionsdruck, 13. Risiko einer Verschiebung der Erkrankung von der Kindheit auf ein höheres Lebensalter, auch im Hinblick auf die Unwahrscheinlichkeit, SARS-CoV-2 auszurotten, 14. Zugang zu Gemeinschaftseinrichtungen und Teilhabe am gesellschaftlichen Leben. Diskussion: Die genannten Aspekte bieten einen Anhaltspunkt für die Klärung der Frage, ob eine jeweilige Impfung empfohlen werden sollte, für die jeweiligen Altersgruppen und im Kontext der jeweiligen Familie, des jeweiligen Landes und dessen Bedingungen. Für Deutschland ergibt sich zum aktuellen Zeitpunkt keine wissenschaftliche oder medizinische Basis für eine generelle Impfempfehlung von Kindern und Jugendlichen.
... In Europe, children under 10 years of age rarely seem to be spreaders in this infection process, although data from India, a country with a different hygiene background, do ascribe a certain transmission role to children (although without differentiation between 5-year-olds and 17-year-olds) [12]. A Scottish study of 300,000 households found that the more children in the household, the less likely adults are to be hospitalized with COVID-19 [13]. A recent study suggests that children emit less aerosol when singing and talking than adults [14]. ...
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Background: Narratives about complaints in children and adolescents caused by wearing a mask are accumulating. There is, to date, no registry for side effects of masks. Methods: In the context of the www.co-ki.de multi-study-complex an online registry has been set up where parents, doctors, pedagogues and others can enter their observations. On 20.10.2020, 363 doctors were asked to make entries and to make parents and teachers aware of the registry. Results: By 26.10.2020 the registry had been used by 20,353 people. In this publication we report the results from the parents, who entered data on a total of 25,930 children. The average reported wearing time of masks was 270 minutes per day. Impairments caused by wearing the mask were reported by 68% of the parents. These included irritability (60%), headache (53%), difficulty concentrating (50%), less happiness (49%), reluctance to go to school/kindergarten (44%), malaise (42%) impaired learning (38%) and drowsiness or fatigue (37%). Discussion: This world's first registry for recording the effects of wearing masks in children is dedicated to a new research question. Bias with respect to preferential documentation of children who are particularly severely affected or who are fundamentally critical of protective measures cannot be dismissed. The frequency of the registry’s use and the spectrum of symptoms registered indicate the importance of the topic and call for representative surveys, randomized controlled trials with various masks and a renewed risk-benefit assessment for the vulnerable group of children.
... Very few studies have directly examined whether contact with children affords adults protection from SARS-CoV-2. Prior to our recent preprint, 21 only one study touching on this question was identified. 17 In this German study, 1186 of 4010 patients who had recovered from COVID-19 responded to a survey. ...
Article
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Objective Children are relatively protected from COVID-19, due to a range of potential mechanisms. We investigated if contact with children also affords adults a degree of protection from COVID-19. Design Cohort study based on linked administrative data. Setting Scotland. Study population All National Health Service Scotland healthcare workers and their household contacts as of March 2020. Main exposure Number of young children (0–11 years) living in the participant’s household. Main outcomes COVID-19 requiring hospitalisation, and any COVID-19 (any positive test for SARS-CoV-2) in adults aged ≥18 years between 1 March and 12 October 2020. Results 241 266, 41 198, 23 783 and 3850 adults shared a household with 0, 1, 2 and 3 or more young children, respectively. Over the study period, the risk of COVID-19 requiring hospitalisation was reduced progressively with increasing numbers of household children—fully adjusted HR (aHR) 0.93 per child (95% CI 0.79 to 1.10). The risk of any COVID-19 was similarly reduced, with the association being statistically significant (aHR per child 0.93; 95% CI 0.88 to 0.98). After schools reopened to all children in August 2020, no association was seen between exposure to young children and risk of any COVID-19 (aHR per child 1.03; 95% CI 0.92 to 1.14). Conclusion Between March and October 2020, living with young children was associated with an attenuated risk of any COVID-19 and COVID-19 requiring hospitalisation among adults living in healthcare worker households. There was no evidence that living with young children increased adults’ risk of COVID-19, including during the period after schools reopened.
... In Europe, children under 10 years of age rarely seem to be spreaders in this infection process, although data from India, a country with a different hygiene background, do ascribe a certain transmission role to children (although without differentiation between 5-year-olds and 17-year-olds) [12]. A Scottish study of 300,000 households found that the more children in the household, the less likely adults are to be hospitalized with COVID-19 [13]. A recent study suggests that children emit less aerosol when singing and talking than adults [14]. ...
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Full-text available
Background: Narratives about complaints in children and adolescents caused by wearing a mask are accumulating. There is, to date, no registry for side effects of masks. Methods: At the University of Witten/Herdecke an online registry has been set up where parents, doctors, pedagogues and others can enter their observations. On 20.10.2020, 363 doctors were asked to make entries and to make parents and teachers aware of the registry. Results: By 26.10.2020 the registry had been used by 20,353 people. In this publication we report the results from the parents, who entered data on a total of 25,930 children. The average wearing time of the mask was 270 minutes per day. Impairments caused by wearing the mask were reported by 68% of the parents. These included irritability (60%), headache (53%), difficulty concentrating (50%), less happiness (49%), reluctance to go to school/kindergarten (44%), malaise (42%) impaired learning (38%) and drowsiness or fatigue (37%). Discussion: This world's first registry for recording the effects of wearing masks in children is dedicated to a new research question. Bias with respect to preferential documentation of children who are particularly severely affected or who are fundamentally critical of protective measures cannot be dismissed. The frequency of the registry’s use and the spectrum of symptoms registryed indicate the importance of the topic and call for representative surveys, randomized controlled trials with various masks and a renewed risk-benefit assessment for the vulnerable group of children: adults need to collecticely reflect the circumstances under which they would be willing to take a residual risk upon themselves in favor of enabling children to have a higher quality of life without having to wear a mask.
... We and others have previously reported lower risk in teachers compared with others of the same age and sex [7,14]. The inverse association of severe disease with the number of school-age children in the household extends and confirms the findings of an earlier study of health care workers and their families [15]. In the OPENSAFELY cohort, the rate ratio for fatal COVID-19 associated with living with children aged 0-11 years was 0.75 after adjusting for covariates, but no dose-response relationship was reported [16]. ...
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* Objectives - To investigate:(1) the risk of severe COVID-19 in those eligible for shielding, and (2) the relation of severe COVID-19 to transmission-related factors in those in shielding and the general population. * Design - Matched case-control study (REACT-SCOT). * Setting - Population of Scotland from 1 March 2020 to 28 January 2021. * Participants - All 160307 diagnosed cases of COVID-19 and 1564782 controls matched for age, sex and primary care practice, linked with all 204913 individuals identified as eligible for shielding by Public Health Scotland. * Main outcome measure - Severe COVID-19, defined as cases that entered critical care or were fatal. * Results - With those without risk conditions as reference category, the univariate rate ratio for severe COVID-19 was 5.3 (95% CI 5.0 to 5.7, p=4 x 10−527) in those with moderate risk conditions and 7.6 (95% CI 7.1 to 8.3, p=1 x 10−527) in those eligible for shielding. The highest rate was in solid organ transplant recipients: rate ratio 13.6 (95% CI 9.6 to 19.2, p=8 x 10−50). In both the shielded and the general population, the risk of severe COVID-19 increased with the number of adults but decreased with the number of school-age children in the household. Severe COVID-19 was strongly associated with recent exposure to hospital (defined as 5 to 14 days before presentation date): rate ratio 12.6 (95% CI 11.7 to 13.6, p=2 x 10−989) overall. In a case-crossover analysis with less recent exposure only (15 to 24 days before first testing positive) as reference category, the rate ratio associated with recent exposure only was 6.3 (95% CI 3.6 to 11.1, p=2 x 10−10). Among those eligible for shielding, the population attributable risk fraction (PARF) of severe cases for recent exposure to hospital was 36%. In the general population the PARF for recent exposure to hospital peaked at 46% in May 2020 and again at 64% in December 2020. * Conclusions - The effectiveness of shielding vulnerable individuals was limited by the inability to control transmission in hospital and from other adults in the household. For solid organ transplant recipients, in whom the efficacy of vaccines is uncertain, these results support a policy of offering vaccination to household contacts. Mitigating the impact of the epidemic requires control of nosocomial transmission.
... i) there is evidence that suggests households with children are not at higher risk than other kinds of households (Wood et al 2020), ...
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Children and young people have been less affected than other age groups by coronavirus infection itself, but have been disproportionately impacted by the social, educational and economic impacts of the pandemic. There is evidence that many of the known risk factors for poorer outcomes for children and young people have been increased by the pandemic and subsequent lockdowns, including, for example, financial hardship and academic pressures. Research on the impacts has so far mainly been focused on wellbeing and mental health. In both cases the data are equivocal, leading to the conclusion that a considerable amount of variation in impact sits below the 'average' effects for children and young people as whole. In particular, young people already facing challenges in their lives (such as those living in poverty, living with a disability or in challenging family situations) seem likely to have been hardest hit. There is particular concern about the 'slow burn' impacts of educational and employment constraints, and the role the pandemic is playing in widening health inequalities. Lots of young people are going to need help in the months and years ahead. There is not one programme or intervention that is going to be the "quick fix". However, we can start to put a range of mitigating actions in place now.
... In Europe, children under 10 years of age rarely seem to be spreaders in this infection process, although data from India, a country with a different hygiene background, do ascribe a certain transmission role to children (although without differentiation between 5-year-olds and 17-year-olds) [12]. A Scottish study of 300,000 households found that the more children in the household, the less likely adults are to be hospitalized with COVID-19 [13]. A recent study suggests that children emit less aerosol when singing and talking than adults [14]. ...
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Full-text available
Zusammenfassung Hintergrund Bei Kindern- und Jugendlichen häufen sich Narrative über Beschwerden durch das Tragen eines Mund-Nasen-Schutzes (Maske). Weltweit existiert bisher kein Register für mögliche Nebenwirkungen von Masken. Methode Im Rahmen des www.Co-Ki.de Multi-Studienkomplexes wurde ein Online-Register aufgebaut, im dem Eltern, Ärzt*innen, Pädagog*innen und andere ihre Beobachtungen zu den Auswirkungen des Tragens einer Maske bei Kindern und Jugendlichen eintragen können. Am 20.10.2020 wurden 363 Ärzt*innen eingeladen, Eintragungen zu tätigen und auf das Register hinzuweisen. Ergebnisse Bis zum 26.10.2020 hatten 20.353 Personen an der Umfrage teilgenommen. Allein die Gruppe der Eltern gab Daten zu 25.930 Kindern ein. Die angegebene durchschnittliche Tragedauer der Maske lag bei 270 min am Tag. Die Eingebenden berichten zu 68 %, dass Kinder über Beeinträchtigungen durch das Maskentragen klagen. Zu den Nebenwirkungen zählten Gereiztheit (60 %), Kopfschmerzen (53 %), Konzentrationsschwierigkeiten (50 %), weniger Fröhlichkeit (49 %), Schul‑/Kindergartenunlust (44 %), Unwohlsein (42 %), Beeinträchtigungen beim Lernen (38 %) und Benommenheit/Müdigkeit (37 %). Diskussion Dieses weltweit erste Register zur Erfassung von Auswirkungen des Tragens eines Mund-Nasen-Schutzes bei Kindern und Jugendlichen widmet sich einer neuen Forschungsfrage. Eine Verzerrung im Hinblick auf die präferenzielle Dokumentation besonders schwer betroffener Kinder oder den Schutzmaßnahmen grundsätzlich kritisch gegenüberstehenden Personen lässt sich nicht ausschließen. Die Nutzungshäufigkeit und das Symptomspektrum weisen auf die Wichtigkeit des Themas hin und rufen nach repräsentativen Surveys, randomisierten kontrollierten Studien mit verschiedenen Maskensorten und nach einer Nutzen-Risiko-Abwägung der Maskenpflicht bei der vulnerablen Gruppe der Kinder.
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Objective To investigate whether risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and outcomes of coronavirus disease 2019 (covid-19) differed between adults living with and without children during the first two waves of the UK pandemic. Design Population based cohort study, on behalf of NHS England. Setting Primary care data and pseudonymously linked hospital and intensive care admissions and death records from England, during wave 1 (1 February to 31 August 2020) and wave 2 (1 September to 18 December 2020). Participants Two cohorts of adults (18 years and over) registered at a general practice on 1 February 2020 and 1 September 2020. Main outcome measures Adjusted hazard ratios for SARS-CoV-2 infection, covid-19 related admission to hospital or intensive care, or death from covid-19, by presence of children in the household. Results Among 9 334 392 adults aged 65 years and under, during wave 1, living with children was not associated with materially increased risks of recorded SARS-CoV-2 infection, covid-19 related hospital or intensive care admission, or death from covid-19. In wave 2, among adults aged 65 years and under, living with children of any age was associated with an increased risk of recorded SARS-CoV-2 infection (hazard ratio 1.06 (95% confidence interval 1.05 to 1.08) for living with children aged 0-11 years; 1.22 (1.20 to 1.24) for living with children aged 12-18 years) and covid-19 related hospital admission (1.18 (1.06 to 1.31) for living with children aged 0-11; 1.26 (1.12 to 1.40) for living with children aged 12-18). Living with children aged 0-11 was associated with reduced risk of death from both covid-19 and non-covid-19 causes in both waves; living with children of any age was also associated with lower risk of dying from non-covid-19 causes. For adults 65 years and under during wave 2, living with children aged 0-11 years was associated with an increased absolute risk of having SARS-CoV-2 infection recorded of 40-60 per 10 000 people, from 810 to between 850 and 870, and an increase in the number of hospital admissions of 1-5 per 10 000 people, from 160 to between 161 and 165. Living with children aged 12-18 years was associated with an increase of 160-190 per 10 000 in the number of SARS-CoV-2 infections and an increase of 2-6 per 10 000 in the number of hospital admissions. Conclusions In contrast to wave 1, evidence existed of increased risk of reported SARS-CoV-2 infection and covid-19 outcomes among adults living with children during wave 2. However, this did not translate into a materially increased risk of covid-19 mortality, and absolute increases in risk were small.
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Objective To characterise the clinical features of children and young people admitted to hospital with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the UK and explore factors associated with admission to critical care, mortality, and development of multisystem inflammatory syndrome in children and adolescents temporarily related to coronavirus disease 2019 (covid-19) (MIS-C). Design Prospective observational cohort study with rapid data gathering and near real time analysis. Setting 260 hospitals in England, Wales, and Scotland between 17 January and 3 July 2020, with a minimum follow-up time of two weeks (to 17 July 2020). Participants 651 children and young people aged less than 19 years admitted to 138 hospitals and enrolled into the International Severe Acute Respiratory and emergency Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK study with laboratory confirmed SARS-CoV-2. Main outcome measures Admission to critical care (high dependency or intensive care), in-hospital mortality, or meeting the WHO preliminary case definition for MIS-C. Results Median age was 4.6 (interquartile range 0.3-13.7) years, 35% (225/651) were under 12 months old, and 56% (367/650) were male. 57% (330/576) were white, 12% (67/576) South Asian, and 10% (56/576) black. 42% (276/651) had at least one recorded comorbidity. A systemic mucocutaneous-enteric cluster of symptoms was identified, which encompassed the symptoms for the WHO MIS-C criteria. 18% (116/632) of children were admitted to critical care. On multivariable analysis, this was associated with age under 1 month (odds ratio 3.21, 95% confidence interval 1.36 to 7.66; P=0.008), age 10-14 years (3.23, 1.55 to 6.99; P=0.002), and black ethnicity (2.82, 1.41 to 5.57; P=0.003). Six (1%) of 627 patients died in hospital, all of whom had profound comorbidity. 11% (52/456) met the WHO MIS-C criteria, with the first patient developing symptoms in mid-March. Children meeting MIS-C criteria were older (median age 10.7 (8.3-14.1) v 1.6 (0.2-12.9) years; P<0.001) and more likely to be of non-white ethnicity (64% (29/45) v 42% (148/355); P=0.004). Children with MIS-C were five times more likely to be admitted to critical care (73% (38/52) v 15% (62/404); P<0.001). In addition to the WHO criteria, children with MIS-C were more likely to present with fatigue (51% (24/47) v 28% (86/302); P=0.004), headache (34% (16/47) v 10% (26/263); P<0.001), myalgia (34% (15/44) v 8% (21/270); P<0.001), sore throat (30% (14/47) v (12% (34/284); P=0.003), and lymphadenopathy (20% (9/46) v 3% (10/318); P<0.001) and to have a platelet count of less than 150 × 10 ⁹ /L (32% (16/50) v 11% (38/348); P<0.001) than children who did not have MIS-C. No deaths occurred in the MIS-C group. Conclusions Children and young people have less severe acute covid-19 than adults. A systemic mucocutaneous-enteric symptom cluster was also identified in acute cases that shares features with MIS-C. This study provides additional evidence for refining the WHO MIS-C preliminary case definition. Children meeting the MIS-C criteria have different demographic and clinical features depending on whether they have acute SARS-CoV-2 infection (polymerase chain reaction positive) or are post-acute (antibody positive). Study registration ISRCTN66726260.
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In response to the coronavirus disease 2019 (COVID-19) pandemic, 107 countries had implemented national school closures by March 18, 2020. It is unknown whether school measures are effective in coronavirus outbreaks (eg, due to severe acute respiratory syndrome [SARS], Middle East respiratory syndrome, or COVID-19). We undertook a systematic review by searching three electronic databases to identify what is known about the effectiveness of school closures and other school social distancing practices during coronavirus outbreaks. We included 16 of 616 identified articles. School closures were deployed rapidly across mainland China and Hong Kong for COVID-19. However, there are no data on the relative contribution of school closures to transmission control. Data from the SARS outbreak in mainland China, Hong Kong, and Singapore suggest that school closures did not contribute to the control of the epidemic. Modelling studies of SARS produced conflicting results. Recent modelling studies of COVID-19 predict that school closures alone would prevent only 2-4% of deaths, much less than other social distancing interventions. Policy makers need to be aware of the equivocal evidence when considering school closures for COVID-19, and that combinations of social distancing measures should be considered. Other less disruptive social distancing interventions in schools require further consideration if restrictive social distancing policies are implemented for long periods.
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Objectives To assess disease trends, testing practices, community surveillance, case-fatality and excess deaths in children as compared with adults during the first pandemic peak in England. Setting England. Participants Children with COVID-19 between January and May 2020. Main outcome measures Trends in confirmed COVID-19 cases, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity rates in children compared with adults; community prevalence of SARS-CoV-2 in children with acute respiratory infection (ARI) compared with adults, case-fatality rate in children with confirmed COVID-19 and excess childhood deaths compared with the previous 5 years. Results Children represented 1.1% (1,408/129,704) of SARS-CoV-2 positive cases between 16 January 2020 and 3 May 2020. In total, 540 305 people were tested for SARS-COV-2 and 129,704 (24.0%) were positive. In children aged <16 years, 35,200 tests were performed and 1408 (4.0%) were positive for SARS-CoV-2, compared to 19.1%–34.9% adults. Childhood cases increased from mid-March and peaked on 11 April before declining. Among 2,961 individuals presenting with ARI in primary care, 351 were children and 10 (2.8%) were positive compared with 9.3%–45.5% in adults. Eight children died and four (case-fatality rate, 0.3%; 95% CI 0.07% to 0.7%) were due to COVID-19. We found no evidence of excess mortality in children. Conclusions Children accounted for a very small proportion of confirmed cases despite the large numbers of children tested. SARS-CoV-2 positivity was low even in children with ARI. Our findings provide further evidence against the role of children in infection and transmission of SARS-CoV-2.
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It is known that severe COVID-19 cases in small children are rare. If a childhood-related infection would be protective against severe course of COVID-19, it would be expected that adults with intensive and regular contact to small children also may have a mild course of COVID-19 more frequently. To test this hypothesis, a survey among 4,010 recovered COVID-19 patients was conducted in Germany. 1,186 complete answers were collected. 6.9% of these patients reported frequent and regular job-related contact to children below 10 years of age and 23.2% had own small children, which is higher than expected. In the relatively small subgroup with intensive care treatment (n=19), patients without contact to small children were overrepresented. These findings are not well explained by age, gender or BMI distribution of those patients and should be validated in other settings.
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Memory T cells induced by previous pathogens can shape the susceptibility to, and clinical severity of, subsequent infections¹. Little is known about the presence of pre-existing memory T cells in humans with the potential to recognize SARS-CoV-2. Here, we first studied T cell responses to structural (nucleocapsid protein, NP) and non-structural (NSP-7 and NSP13 of ORF1) regions of SARS-CoV-2 in COVID-19 convalescents (n=36). In all of them we demonstrated the presence of CD4 and CD8 T cells recognizing multiple regions of the NP protein. We then showed that SARS-recovered patients (n=23) still possess long-lasting memory T cells reactive to SARS-NP 17 years after the 2003 outbreak, which displayed robust cross-reactivity to SARS-CoV-2 NP. Surprisingly, we also frequently detected SARS-CoV-2 specific T cells in individuals with no history of SARS, COVID-19 or contact with SARS/COVID-19 patients (n=37). SARS-CoV-2 T cells in uninfected donors exhibited a different pattern of immunodominance, frequently targeting the ORF-1-coded proteins NSP7 and 13 as well as the NP structural protein. Epitope characterization of NSP7-specific T cells showed recognition of protein fragments with low homology to “common cold” human coronaviruses but conserved amongst animal betacoranaviruses. Thus, infection with betacoronaviruses induces multispecific and long-lasting T cell immunity to the structural protein NP. Understanding how pre-existing NP- and ORF-1-specific T cells present in the general population impact susceptibility and pathogenesis of SARS-CoV-2 infection is of paramount importance for the management of the current COVID-19 pandemic.
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The World Health Organization has declared the ongoing outbreak of COVID-19, which is caused by a novel coronavirus SARS-CoV-2, as pandemic. There is currently a lack of knowledge about the antibody response elicited from SARS-CoV-2 infection. One major immunological question concerns antigenic differences between SARS-CoV-2 and SARS-CoV. We address this question by analyzing plasma from patients infected by SARS-CoV-2 or SARS-CoV, and from infected or immunized mice. Our results show that, while cross-reactivity in antibody binding to the spike protein is common, cross-neutralization of the live viruses may be rare, indicating the presence of non-neutralizing antibody response to conserved epitopes in the spike. Whether such low or non-neutralizing antibody response leads to antibody-dependent disease enhancement needs to be addressed in the future. Overall, this study not only addresses a fundamental question regarding antigenicity differences between SARS-CoV-2 and SARS-CoV, but also has implications for immunogen design and vaccine development.
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Several related human coronaviruses (HCoVs) are endemic in the human population, causing mild respiratory infections. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiologic agent of Coronavirus disease 2019 (COVID-19), is a recent zoonotic infection that has quickly reached pandemic spread. Zoonotic introduction of novel coronaviruses is thought to occur in the absence of pre-existing immunity in the target human population. Using diverse assays for detection of antibodies reactive with the SARS-CoV-2 Spike (S) glycoprotein, we demonstrate the presence of pre-existing immunity in uninfected and unexposed humans to the new coronavirus. SARS-CoV-2 S-reactive antibodies, exclusively of the IgG class, were readily detectable by a sensitive flow cytometry-based method in SARS-CoV-2-uninfected individuals with recent HCoV infection and targeted the S2 subunit. In contrast, SARS-CoV-2 infection induced higher titres of SARS-CoV-2 S-reactive IgG antibodies, as well as concomitant IgM and IgA antibodies throughout the observation period of 6 weeks since symptoms onset. HCoV patient sera also variably reacted with SARS-CoV-2 S and nucleocapsid (N), but not with the S1 subunit or the receptor binding domain (RBD) of S on standard enzyme immunoassays. Notably, HCoV patient sera exhibited specific neutralising activity against SARS-CoV-2 S pseudotypes, according to levels of SARS-CoV-2 S-binding IgG and with efficiencies comparable to those of COVID-19 patient sera. Distinguishing pre-existing and de novo antibody responses to SARS-CoV-2 will be critical for serology, seroprevalence and vaccine studies, as well as for our understanding of susceptibility to and natural course of SARS-CoV-2 infection.
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The duration and nature of immunity generated in response to SARS-CoV-2 infection is unknown. Many public health responses and modeled scenarios for COVID-19 outbreaks caused by SARS-CoV-2 assume that infection results in an immune response that protects individuals from future infections or illness for some amount of time. The timescale of protection is a critical determinant of the future impact of the pathogen. The presence or absence of protective immunity due to infection or vaccination (when available) will affect future transmission and illness severity. The dynamics of immunity and nature of protection are relevant to discussions surrounding therapeutic use of convalescent sera as well as efforts to identify individuals with protective immunity. Here, we review the scientific literature on antibody immunity to coronaviruses, including SARS-CoV-2 as well as the related SARS-CoV-1, MERS-CoV and human endemic coronaviruses (HCoVs). We reviewed 1281 abstracts and identified 322 manuscripts relevant to 5 areas of focus: 1) antibody kinetics, 2) correlates of protection, 3) immunopathogenesis, 4) antigenic diversity and cross-reactivity, and 5) population seroprevalence. While studies of SARS-CoV-2 are necessary to determine immune responses to it, evidence from other coronaviruses can provide clues and guide future research.
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Public health preparedness for coronavirus (CoV) disease 2019 (COVID-19) is challenging in the absence of setting-specific epidemiological data. Here we describe the epidemiology of seasonal CoVs (sCoVs) and other cocirculating viruses in the West of Scotland, United Kingdom. We analyzed routine diagnostic data for >70 000 episodes of respiratory illness tested molecularly for multiple respiratory viruses between 2005 and 2017. Statistical associations with patient age and sex differed between CoV-229E, CoV-OC43, and CoV-NL63. Furthermore, the timing and magnitude of sCoV outbreaks did not occur concurrently, and coinfections were not reported. With respect to other cocirculating respiratory viruses, we found evidence of positive, rather than negative, interactions with sCoVs. These findings highlight the importance of considering cocirculating viruses in the differential diagnosis of COVID-19. Further work is needed to establish the occurrence/degree of cross-protective immunity conferred across sCoVs and with COVID-19, as well as the role of viral coinfection in COVID-19 disease severity.