Transmission of rhinovirus in the Utah BIG-LoVE families: Consequences of age and household structure

Abstract

Background: Common cold viruses create significant health and financial burdens, and understanding key loci of transmission would help focus control strategies. This study (1) examines factors that influence when individuals transition from a negative to positive test (acquisition) or a positive to negative test (loss) of rhinovirus (HRV) and other respiratory tract viruses in 26 households followed weekly for one year, (2) investigates evidence for intrahousehold and interhousehold transmission and the characteristics of individuals implicated in transmission, and (3) builds data-based simulation models to identify factors that most strongly affect patterns of prevalence.

Methods: We detected HRV, coronavirus, paramyxovirus, influenza and bocavirus with the FilmArray polymerase chain reaction (PCR) platform (BioFire Diagnostics, LLC). We used logistic regression to find covariates affecting acquisition or loss of HRV including demographic characteristics of individuals, their household, their current infection status, and prevalence within their household and across the population. We apply generalized linear mixed models to test robustness of results.

Results: Acquisition of HRV was less probable in older individuals and those infected with a coronavirus, and higher with a higher proportion of other household members infected. Loss of HRV is reduced with a higher proportion of other household members infected. Within households, only children and symptomatic individuals show evidence for transmission, while between households only a higher number of infected older children (ages 5-19) increases the probability of acquisition. Coronaviruses, paramyxoviruses and bocavirus also show evidence of intrahousehold transmission. Simulations show that age-dependent susceptibility and transmission have the largest effects on mean HRV prevalence.

Conclusions: Children are most likely to acquire and most likely to transmit HRV both within and between households, with infectiousness concentrated in symptomatic children. Simulations predict that the spread of HRV and other respiratory tract viruses can be reduced but not eliminated by practices within the home.

Fig 1. Univariate effects of covariates in the final generalized linear models.

Probability of acquisition (a-e) or loss (f) of HRV as a function of a) week, b) age, c) age of youngest household member, d) concurrent positive test for coronavirus, e) fraction of other household members testing positive (pooled into six categories to smooth results), and f) number of other household members testing positive. Red lines showed a smoothed fit (supsmu function in R).

Fig 2. Univariate effects of significant specific infection classes.

Average probability of infection as a function of specific infection classes. Number of data points indicated by numbers in a-c and by dot size in (d), ranging from the smallest value of 23 with 13 individuals infected to a largest value of 662 with 3 individuals infected. Error bars are one standard error.

Fig 3. Results of simulations.

We compare data (in black) with simulation (in red) for a) the trajectory for full year of data and first five years of the simulation, b) mean prevalence as a function of household size, c) mean prevalence as a function of age group, d) the index of dispersion θ for each household, with smaller values indicating a greater deviation from the binomial distribution (arrows connecting data to simulation added for clarity). The model includes age-dependent susceptibility, specific infection classes for age both within and between households and intrahousehold reinfection. Households match those at the beginning of the BIG-LoVE study. Coefficients of the logistic regression model are Intercept = -0.632, Week = -0.00943, Age group = -0.798, Household HRV frequency in age group 1 = 2.482, Household HRV frequency in age group 2 = 1.573, Population HRV number in age group 2 = 0.0495.

Fig 4. Effects of population mean household size and model structure on a) mean HRV prevalence in the entire population and b) the slope of HRV prevalence against household size within a population.

The population mean household sizes follow the Poisson distribution with the given mean.