Transmission Modeling with Regression Adjustment for Analyzing Household-based Studies of Infectious Disease


Background: Household contacts of people infected with a transmissible disease may be at risk due to this proximate exposure, or from other unobserved sources. Understanding sources of variation in infection risk is essential for effectively targeting interventions.

Methods: We develop an analytical approach to estimate household and exogenous forces of infection, while accounting for individual-level characteristics that may affect susceptibility to disease, and factors that may affect transmissibility. We apply this approach to a longitudinal cohort study conducted in Lima, Peru during 2009-2012 of 18,544 subjects in 4,500 households with at least one active tuberculosis (TB) case, and compare the results to those obtained by Poisson and logistic regression.

Results: We estimate that HIV-coinfected (susceptibility hazard ratio, SHR=3.80, 1.56-9.29), child (SHR=1.72, 1.32-2.23) and teenage (SHR=2.00, 1.49-2.68) household contacts of TB cases experience a higher hazard of TB as a result of such household contact than do adult contacts. Isoniazid preventive therapy (SHR=0.30, 0.21-0.42) and previous BCG vaccination (SHR=0.66, 0.51-0.86) substantially reduce the risk of disease among household contacts. TB cases that were not microbiologically confirmed exert a smaller hazard of causing TB among their close contacts compared with cases that were smear or culture positive (excess HR=0.88, 0.82-0.93 for HIV− cases and 0.82, 0.57-0.94 for HIV+ cases). We estimated the extra-household force of infection results in 0.01 (95% CI: 0.004,0.028) TB cases per susceptible household contact per year, and the rate of transmission between a microbiologically confirmed TB case and susceptible household contact at 0.08 (95% CI: 0.045,0.129) TB cases per pair, per year.

Conclusions: Accounting for exposure to infected household contacts permits estimation of risk factors for disease susceptibility/transmissibility, and comparison of within-household and exogenous forces of infection.

Jon Zelner
Jon Zelner
Assistant Professor

My research interests include distributed robotics, mobile computing and programmable matter.