Risk of SARS-CoV-2 Infection Among Households With Children in France, 2020-2022

Abstract

Importance: Understanding the contribution of children to SARS-CoV-2 circulation in households is critical for designing public health policies and mitigation strategies.

Objective: To identify temporal changes in the risk of SARS-CoV-2 infection in people living with children.

Design, setting, and participants: This case-control study included online questionnaire responses from French adults between October 2020 and October 2022. Eligible cases were adults with ongoing SARS-CoV-2 infection with an email address on record with the national health insurance system, which centralized all new diagnoses in France. Eligible controls were adults who had never tested positive for SARS-CoV-2 until February 2021, when eligibility was extended to all adults without ongoing SARS-CoV-2 infection.

Exposure: Transmission of SARS-CoV-2 from a child (aged under 18 years) within the household in the descriptive analysis, as reported by the participating case. Sharing household with a child (of any age or broken down by school level) in the case-control analysis.

Main outcome and measures: Ongoing SARS-CoV-2 infection diagnosed by reverse transcription-polymerase chain reaction or supervised rapid antigen test (ie, not self-tests).

Results: A total of 682 952 cases were included for the descriptive analysis (68.8% female, median [IQR] age, 44 [34-55] years). Among those, 45 108 (6.6%) identified a household child as the source case; this proportion peaked at 10.4% during the Omicron BA.1 wave (December 20, 2021, to April 8, 2022). For the case-control analysis, we matched 175 688 cases (with a 4:1 ratio) for demographic characteristics with 43 922 controls. In multivariable logistic regression analysis, household exposure to children was associated with an increased risk of infection mainly at the end of summer 2021 (receding Delta wave) and during winter 2022 (Omicron BA.1 wave). In subgroup analysis by school level of the child, living with children under the age of 6 was associated with increased odds of infection throughout the study period, peaking at an odds ratio (OR) 1.8 (95% CI, 1.6-2.1) for children looked after by professional in-home caregivers, 1.7 (95% CI, 1.5-1.7) for children in day care facilities, and 1.6 (95% CI, 1.4-1.8) for children in preschool. The ORs associated with household exposure to children aged 6 to 14 years increased during the Delta (August 14, 2021, to December 19, 2021) and Omicron BA.1 waves, reaching 1.6 (95% CI, 1.5-1.7) for primary school children and 1.4 (95% CI, 1.3-1.5) for middle school children. Exposure to older children aged 15 to 17 years was associated with a moderate risk until April 2021, with an OR of 1.2 (95% CI, 1.2-1.3) during curfew in early 2021 (December 4, 2020, to April 8, 2021).

Conclusions and relevance: The presence of children, notably very young ones, was associated with an increased risk of SARS-CoV-2 infection in other household members, especially during the Delta and Omicron BA.1 waves. These results should help to guide policies targeting children and immunocompromised members of their household.

Trial registration: ClinicalTrials.gov NCT04607941.

Figure 1.. Study Flowchart

Descriptive analysis was conducted on cases for which the source case lived in the same household and was aged <18 years. Study conducted in mainland France between October 2020 and October 2022.

Figure 2.. Risk of SARS-CoV-2 Infection in People Living With Children by Age and School Level

Odds ratios in fitted multivariable logistic regression models. The periods were defined on the basis of changes in SARS-CoV-2 incidence, predominant circulating strain, and major nonpharmaceutical interventions (the periods are indicated by shaded gray areas), with start dates as follows: (1) October 1, 2020; (2) December 4, 2020; (3) April 9, 2021; (4) June 14, 2021; (5) August 14, 2021; (6) October 2, 2021; (7) December 20, 2021; (8) March 18, 2022; (9) May 20, 2022 (study end date: October 2, 2022). Multivariable logistic regression models are adjusted for sociodemographic characteristics, health status (body mass index, immunosuppression, diabetes, hypertension, chronic respiratory disease), smoking status, COVID-19 vaccination status (number of doses and time since last dose), attendance of private or professional meetings, use of public transportation, travel abroad, sports activities, visits to retail facilities, restaurants, bars, or parties, and health care worker status.