Behavioral factors and SARS-CoV-2 transmission heterogeneity within a household cohort in Costa Rica

Abstract

Introduction: Variability in household secondary attack rates and transmission risks factors of SARS-CoV-2 remain poorly understood.

Methods: We conducted a household transmission study of SARS-CoV-2 in Costa Rica, with SARS-CoV-2 index cases selected from a larger prospective cohort study and their household contacts were enrolled. A total of 719 household contacts of 304 household index cases were enrolled from November 21, 2020, through July 31, 2021. Blood specimens were collected from contacts within 30-60 days of index case diagnosis; and serum was tested for presence of spike and nucleocapsid SARS-CoV-2 IgG antibodies. Evidence of SARS-CoV-2 prior infections among household contacts was defined based on the presence of both spike and nucleocapsid antibodies. We fitted a chain binomial model to the serologic data, to account for exogenous community infection risk and potential multi-generational transmissions within the household.

Results: Overall seroprevalence was 53% (95% confidence interval (CI) 48-58%) among household contacts. The estimated household secondary attack rate is 34% (95% CI 5-75%). Mask wearing by the index case is associated with the household transmission risk reduction by 67% (adjusted odds ratio = 0.33 with 95% CI: 0.09-0.75) and not sharing bedroom with the index case is associated with the risk reduction of household transmission by 78% (adjusted odds ratio = 0.22 with 95% CI 0.10-0.41). The estimated distribution of household secondary attack rates is highly heterogeneous across index cases, with 30% of index cases being the source for 80% of secondary cases.

Conclusions: Modeling analysis suggests that behavioral factors are important drivers of the observed SARS-CoV-2 transmission heterogeneity within the household.

Fig. 1. The overall cumulative infection risk among household members and cumulative infection risk by different risk factors (unadjusted).

The overall cumulative infection risk is calculated as fraction of seropositive among all 719 household contacts. The cumulative infection risk within a given stratum is calculated as the fraction of seropositive individuals among the household contacts within the stratum. We stratified the 719 household contacts by household level characteristics of household size; index case characteristics including index cases’ age, sex, obesity or not, mask wearing frequency; household member properties including household contacts’ age, sex, obesity or not, mask wearing frequency, if cared for index case, shared bedroom with index case or interaction frequency with index case after the diagnosis of the index case. Confidence intervals are based on a generalized estimating equation analysis applied to each risk factor one at a time that takes within household correlations into account.

Fig. 2. Estimates from chain-binomial household transmission model.

a Estimated odds ratios (adjusted) of the transmission risk factors fitted to 304 index cases and their 719 contacts. Solid dots and horizontal lines represent point estimates and 95% confidence intervals. Circles represent the reference class. b Baseline transmission risks from the index case and seropositive household members as well as baseline risks of acquiring infection from the community. c–f Distribution (histogram) of model projected community infection risk and household secondary attack rate across the study participants. c Distribution of cumulative community infection risks* d Distribution of the secondary attack rate attributable to seropositive household members who are not the index cases e Distribution of the secondary attack rate attributable to the index case. f Distribution of the secondary attack rate by the index case in a counterfactual scenario where no preventive measures (PM) were taken after diagnosis of the index case. g Distribution of the secondary attack rate by the index case in a counterfactual scenario where all preventive measures (PM) were taken after diagnosis of the index case. (*All results are from model with best fit to the data: model 15, Table S1).

Fig. 3. COVID-19 related symptom presentations among both seropositive and seronegative individuals.

a Prevalence of symptoms among both seropositive (red bar) and seronegative individuals (green bar). b The relative risk of symptom presentation in seropositive vs seronegative individuals. Panel b share the same y axis as panel a. Dots and horizontal lines represent point estimate and 95% confidence interval, based on the symptom presentations of 719 household contacts. c The prevalence of symptoms by symptom frequency (Asym. denotes asymptomatic individuals, 1–3 denotes individuals having 1–3 of all symptoms listed in a, 4–6 denotes having 4–6 of all symptoms listed in a and 7+ denotes having more than 7 symptoms listed in a. d Regression analysis on the risk of being symptomatic (having a least 1 symptom in a by serologic status and age. “If sero + ” denotes if the individual is seropositive; “Age (sero-)” denotes the age dependency of being symptomatic among seronegative individuals; Age (sero + ) denotes the age dependency of being symptomatic among seropositive individuals. Dots and horizontal lines represent point estimate and 95% confidence interval, based on the symptom presentations of 719 household contacts.