Maximum likelihood estimation of influenza vaccine effectiveness against transmission from the household and from the community

Abstract

Influenza vaccination is recommended as the best way to protect against influenza infection and illness. Due to seasonal changes in influenza virus types and subtypes, a new vaccine must be produced, and vaccine effectiveness (VE) must be estimated, annually. Since 2010, influenza vaccination has been recommended universally in the United States, making randomized clinical trials unethical. Recent studies have used a monitored household cohort study design to determine separate VE estimates against influenza transmission from the household and community. We developed a probability model and accompanying maximum likelihood procedure to estimate vaccine-related protection against transmission of influenza from the household and the community. Using agent-based stochastic simulations, we validated that we can obtain maximum likelihood estimates of transmission parameters and VE close to their true values. Sensitivity analyses to examine the effect of deviations from our assumptions were conducted. We used our method to estimate transmission parameters and VE from data from a monitored household study in Michigan during the 2012-2013 influenza season and were able to detect a significant protective effect of influenza vaccination against community-acquired transmission.

Household transmission of influenza A and B within a prospective cohort during the 2013‐2014 and 2014‐2015 seasons

“…For almost a century, researchers have prospectively followed households to elucidate many of the intricacies of the natural history of influenza and other respiratory illnesses: the range of severity, the collection of symptoms, the diversity of etiologies, the spatiotemporal trends, the incidence within subgroups, and the transmission within the household 1‐64 . Additionally, case‐ascertained household studies have sought to also answer similar questions about influenza by following the household contacts of a case series 65‐133 .…”

Mathematical Modeling of Vaccines That Prevent SARS-CoV-2 Transmission

“…It remains an urgent research priority to continually update estimates for VE SUSC , VE SYMP and VE INF for vaccines, particularly against variant B.1.167.2 and future variants of concern which may exhibit different levels of immune evasion [60,61]. Studies which attempt to directly measure secondary infections in households [62,63], or to assess the degree of protection afforded to unvaccinated members of communities with partial vaccination relative to communities with less vaccination, would potentially be useful. They would need to be performed quickly to obtain actionable results and may suffer from confounding relative to controlled clinical trials, however.…”

Vaccines that prevent SARS-CoV-2 transmission may prevent or dampen a spring wave of COVID-19 cases and deaths in 2021

“…Therefore, it is an urgent research priority to identify reasonable estimates for VE SUSC , VE SYMP and VE INF for vaccines that will be given to the population at large. Trial strategies which attempt to directly measure secondary infections in households ( 39, 40 ), or to assess the degree of protection afforded to unvaccinated members of communities with partial vaccination relative to communities with less vaccination, would potentially be conclusive. They will need to be performed quickly to obtain actionable results prior to spring 2021.…”