Household transmission of endemic human coronaviruses in the US

In a recent study published in the Journal of Infectious Diseases, researchers performed a large household transmission study to describe clinical outcomes of endemic human coronavirus (hCoV) infections and the risk of household and community-level transmission likelihoods in Allegheny County, Pennsylvania, in the United States Of America (USA).

Study: Household Transmission Dynamics of Seasonal Human Coronaviruses. Image Credit: MariaSbytova/Shutterstock.com

Background

The researchers described and quantitatively characterized age-stratified CoV attack rates, symptom frequency, and community and household CoV transmission probabilities.

To do this, they used a chain-binomial model within a Bayesian framework that corrected for missing data from untested households.

Endemic hCoVs cause respiratory illnesses, on average, at least once in children below five years. All four hCoV strains, HCoV-229E, HCoV-HKU1, HCoV-OC43, and HCoV-NL63, will have infected people by adulthood. Serology and virological studies have shown that they reinfect people throughout their lives.

Contact-tracing studies have previously demonstrated that household contacts are at a higher risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) acquisition than their non-household counterparts.

Due to the continuous evolution of SARS-CoV-2 and widespread population-level immunity from infection and vaccination, surveillance of asymptomatic individuals has become even more crucial to understanding SARS-CoV-2 household transmission.

In this regard, understanding the epidemiology of endemic HCoVs, their characterization by household transmission studies, and their comparison to SARS-CoV-2 epidemiology could help figure out transmission and risk factors change for SARS-CoV-2 change as the coronavirus disease 2019 (COVID-19) pandemic progresses.

Further, it could help identify another endemic pathogen that could infect humans.

About the study

In the present study, researchers used data from a school-based study, the Surveillance Monitoring of Absenteeism and Respiratory Transmission (SMART). The study was conducted among five to 19-year-old school-going children and their household members in Allegheny County, Pennsylvania, to estimate the probability of transmitting reverse-transcriptase polymerase chain reaction (RT-PCR)-confirmed hCoV infections from infected individuals to household contacts.

The study population experienced 121 RT-PCR-confirmed seasonal hCoV infections, assessed by weekly disease surveillance over two respiratory virus seasons, December 2015–April 2016 and January 2017–May 2017.

The team prospectively followed up with 164 and 163 households for influenza-like illness (ILI) for 22 and 16 weeks in the first and second years, respectively. Overall, they recruited and followed up with 947 individuals from 223 households.

Next, the researchers sent self-administrable nasal swab kits to all households reporting an ILI event. Then, they tested these swab samples using a multiplex RT-PCR panel to identify samples positive for respiratory HCoVs.

The study model assumed only one generation of within-household transmission per household week, meaning no index case. Also, it worked on the assumption that individuals infected with one HCoV transmitted that strain to other prone individuals within the household. Later, they maximized the sum of all four strain-specific log-likelihoods.

The study focused primarily on four hCoVs, viz., HCoV-229E, HcoV-HKU1, HcoV-NL63, and HcoV-OC43, and five age groups, children less than five years, children between five to nine years, adolescents aged 10 to 19 years, adults aged 20 to 49 years, and ≥50-year adults.

The team reported the proportion of HCoV infections by demographic and clinical characteristics and continuous and categorical variables as the median and percentages (%), respectively, and household secondary attack rate (SAR) for households with at least one HCoV case.

They computed SAR as HCoV infections minus one divided by household size minus one. They also reported exact binomial 95% confidence intervals (CIs) for proportions.

Results

The authors noted that transmission among household members accounted for 21% of all HCoV infections, and most infections occurred due to subtype HCoV-OC43. However, unlike previous studies, the authors observed no difference in community acquisition between adults and children.

Compared to hCoV-infected adults, a higher proportion of children (<19 years) developed ILI symptoms (relative risk 3, 95% CI), indicated by fever and cough/sore throat, and weekly community acquisition probability was 7%. Though household transmission likely occurred from symptomatic and asymptomatic individuals, asymptomatic individuals contributed 20% to 40% of household transmission of endemic CoVs across different models.

All children, especially younger children, more frequently experienced symptomatic infection, suggesting they had less pre-existing immunity than older individuals reporting fewer symptoms and higher proportions of asymptomatic infections.

Typically adults are prone to hCoV infection, but have some immunity. Yet, community or household transmission probabilities did not vary by age or symptom status. Further, simulations suggested that this study was underpowered to detect such differences.

Conclusions

This study combined symptomatic surveillance with household swabbing to capture symptomatic and asymptomatic infections and study the relative contribution of each to the household transmission of common endemic hCoVs.

However, studies with larger sample sets are warranted to fetch robust results about transmissibility-related variations by individual characteristics.

Nonetheless, the study gave much-needed insights into the extent of household transmission and factors associated with SAR in households to inform study designs for SARS-CoV-2 household transmission.

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.