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Review 1: "Household Transmission of SARS-COV-2: Insights from a Population-based Serological Survey"

Published onMar 20, 2022
Review 1: "Household Transmission of SARS-COV-2: Insights from a Population-based Serological Survey"
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key-enterThis Pub is a Review of
Household Transmission of SARS-CoV-2: Insights from a Population-based Serological Survey
Description

AbstractBackgroundKnowing the transmissibility of asymptomatic infections and risk of infection from household- and community-exposures is critical to SARS-CoV-2 control. Limited previous evidence is based primarily on virologic testing, which disproportionately misses mild and asymptomatic infections. Serologic measures are more likely to capture all previously infected individuals.ObjectiveEstimate the risk of SARS-CoV-2 infection from household and community exposures, and identify key risk factors for transmission and infection.DesignCross-sectional household serosurvey and transmission model.SettingGeneva, SwitzerlandParticipants4,524 household members ≥5 years from 2,267 households enrolled April-June 2020.MeasurementsPast SARS-CoV-2 infection confirmed through IgG ELISA. Chain-binomial models based on the number of infections within households used to estimate the cumulative extra-household infection risk and infection risk from exposure to an infected household member by demographics and infector’s symptoms.ResultsThe chance of being infected by a SARS-CoV-2 infected household member was 17.3% (95%CrI,13.7-21.7%) compared to a cumulative extra-household infection risk of 5.1% (95%CrI,4.5-5.8%). Infection risk from an infected household member increased with age, with 5-9 year olds having 0.4 times (95%CrI, 0.07-1.4) the odds of infection, and ≥65 years olds having 2.7 (95%CrI,0.88-7.4) times the odds of infection of 20-49 year olds. Working-age adults had the highest extra-household infection risk. Seropositive asymptomatic household members had 69.6% lower odds (95%CrI,33.7-88.1%) of infecting another household member compared to those reporting symptoms, accounting for 14.7% (95%CrI,6.3-23.2%) of all household infections.LimitationsSelf-reported symptoms, small number of seropositive kids and imperfect serologic tests.ConclusionThe risk of infection from exposure to a single infected household member was more than three-times that of extra-household exposures over the first pandemic wave. Young children had a lower risk of infection from household members. Asymptomatic infections are far less likely to transmit than symptomatic ones but do cause infections.Funding SourceSwiss Federal Office of Public Health, Swiss School of Public Health (Corona Immunitas research program), Fondation de Bienfaisance du Groupe Pictet, Fondation Ancrage, Fondation Privée des Hôpitaux Universitaires de Genève, and Center for Emerging Viral Diseases.

RR:C19 Evidence Scale rating by reviewer:

  • Potentially informative. The main claims made are not strongly justified by the methods and data, but may yield some insight. The results and conclusions of the study may resemble those from the hypothetical ideal study, but there is substantial room for doubt. Decision-makers should consider this evidence only with a thorough understanding of its weaknesses, alongside other evidence and theory. Decision-makers should not consider this actionable, unless the weaknesses are clearly understood and there is other theory and evidence to further support it.

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Review:

The paper under review examines the dynamics of within and out-of-household transmission of SARS-CoV-2 in Geneva, Switzerland based on serological data. The results of the paper represent a useful contribution to our understanding of within-household transmission dynamics. However, there are several aspects of the modelling approach in the paper that can be further examined/improved. Below are some suggestions to the authors.

1. An important covariate not accounted for in the model is the effect of spouses. Earlier studies have suggested that among adult household contacts of an index case, the risk of infection is higher for spouses, e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7184465/ , https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239243/. A serological study of a SARS-CoV2 outbreak on a US Navy ship found that cumulative incidence of infection was higher among persons who reported sharing the same sleeping berth with a crew member who had positive test results compared with those who did not, OR = 3.3 (1.8,6.1). https://www.cdc.gov/mmwr/volumes/69/wr/mm6923e4.htm This further supports the case that among contacts of an index case in a household, the spouse might face an additional risk for infection due to shared bed, or room. For the paper under review, infection rates in persons aged over 65y and 20-49y are highest in households of size 2, pointing to the potential effect of contacts with spouses. Accounting for the effect of spouses may help explain the high risk of household transmission to persons aged over 65y – in fact, for persons aged over 65y in the study data not living alone, the vast majority of them live in households of size 2 (Figure S2), presumably overwhelmingly with their spouses.

2. It is assumed that the risk of outside infection does not depend on household size. However, older persons living in large households might have less need to go outside (particularly for shopping) compared to older persons living in smaller households. In fact, for persons aged over 65y, infection rates in households of size 1 are higher than in households of size 3+ (Figure S2).

3. In many cities, there was significant geographic variability in infection rates. This suggest that for some households, risks of outside infection given equal demographic parameters (age & gender) are elevated for all household members compared to corresponding members of other households. Perhaps clustering by geographic location in the estimation of the risk of outside transmission may improve the model performance.

4. Certain studies suggested declining seroprevalence across different age groups (including younger children), presumably due to declining antibody titers https://www.medrxiv.org/content/10.1101/2020.06.08.20125179v3. The issue of (potentially) missed infections should be further discussed in the paper.


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