ABSTRACT
Background Households are specific transmission settings, as they involve close and repeated contacts between individuals of different generations. Household surveys provide a unique opportunity to better understand SARS-CoV-2 transmission and the role of individual characteristics. Here, we assessed the risk of SARS-CoV-2 acquisition from household and community exposure according to age, family ties, and socioeconomic and living conditions using data from the nationwide population-based EpiCov cohort/ORCHESTRA collaboration in November-December 2020. Methods A history of SARS-CoV-2 infection was defined by a positive Euroimmun Anti-SARS-CoV-2 ELISA IgG result in November-December 2020. We applied stochastic chain binomial models fitted to the final distribution of infections in households to data from 17,983 individuals [≥]5 years enrolled from 8,165 households. Models estimated the competing risks of being infected from community and household exposure. Results Young adults aged 18-24 years had the highest risk of extra-household infection (8.9%, [95% credible interval, Crl]: 7.5 - 10.4), whereas the oldest (>75) and the youngest (6 - 10) had the lowest risk, 2.6% (1.8 - 3.5) and 3.4% (1.9 - 5.2), respectively. Extra-household infection was also independently associated with socioeconomic conditions. Within households, the probability of person-to-person transmission increased with age: 10.6% (5.0 - 17.9) among 6-10-year-olds to 43.1% (32.6 - 53.2) among 65-74-year-olds. It was higher between partners 29.9% (25.6 - 34.3) and from mother to child 29.1% (21.4 - 37.3) than between individuals related by other family ties. Conclusion In 2020 in France, the main factors identified for extra-household infection were age and socioeconomic conditions. Intra-household infection mainly depended on age and family ties.
Subject(s)
COVID-19ABSTRACT
COVID-19 pandemic responses have dramatically modified the global ecological and epidemiological landscape of many infectious diseases. However, the pandemics impacts on antimicrobial resistance (AMR) are currently poorly understood and lack data. While surges in COVID-19 cases during the first wave of the pandemic may have exacerbated AMR, decreases in antibiotic use may have had the opposite effect. To disentangle how pandemic impacts such as lockdowns and modified antibiotic prescribing may affect AMR, we developed a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and colonization with a bacterial pathogen across six pandemic scenarios. We used simulation to assess the effect of each scenario on the bacterial carriage prevalence, antibiotic resistance rate, and the invasive bacterial disease (IBD) incidence, using parameters based on the commensal community bacterium Streptococcus pneumoniae. Pandemic scenarios without community-wide lockdowns all resulted in a decrease in carriage prevalence of antibiotic-sensitive bacteria and an increase in the prevalence of antibiotic-resistant bacteria, while the addition of a population-wide lockdown resulted in a large reduction in colonization prevalence and IBD incidence for both strains (>70%). This translated to an increase in the antibiotic resistance rate across all scenarios to varying degrees, with lingering effects after the cessation of COVID-19 response measures. In the absence of lockdown, a population-wide surge in antibiotic prescribing coincident with the peak in SARS-CoV-2 infection resulted in the greatest increases in resistance rate (23%) and resistant IBD incidence (6%). Within-host interactions, SARS-CoV-2 variants, and population immunity are found to further drive the magnitude of pandemic impacts on resistant IBD incidence. Sensitivity analyses suggest that the extent of such impacts likely varies across different bacterial species. Although real-life scenarios are significantly more complicated, our findings suggest that COVID-19 pandemic responses may significantly impact antibiotic resistance in the community and support the need for monitoring resistance during pandemic waves.
Subject(s)
COVID-19 , Bacterial Infections , Communicable DiseasesABSTRACT
Background: We aimed to study whether social patterns of exposure to SARS-CoV-2 infection changed in France throughout the year 2020, in light to the easing of social contact restrictions. Methods: A population-based cohort of individuals aged 15 years or over was randomly selected from the national tax register to collect socio-economic data, migration history, and living conditions in May and November 2020. Home self-sampling on dried blood was proposed to a 10% random subsample in May and to all in November. A positive anti-SARS-CoV-2 ELISA IgG result against the virus spike protein (ELISA-S) was the primary outcome. The design, including sampling and post-stratification weights, was taken into account in univariate and multivariate analyses. Results: Of the 134,391 participants in May, 107,759 completed the second questionnaire in November, and respectively 12,114 and 63,524 were tested. The national ELISA-S seroprevalence was 4.5% [95%CI: 4.0%-5.1%] in May and 6.2% [5.9%-6.6%] in November. It increased markedly in 18-24-year-old population from 4.8% to 10.0%, and among second-generation immigrants from outside Europe from 5.9% to 14.4%. This group remained strongly associated with seropositivity in November, after controlling for any contextual or individual variables, with an adjusted OR of 2.1 [1.7-2.7], compared to the majority population. In both periods, seroprevalence remained higher in healthcare professions than in other occupations. Conclusion: The risk of Covid-19 infection increased among young people and second-generation migrants between the first and second epidemic waves, in a context of less strict social restrictions, which seems to have reinforced territorialized socialization among peers.