Use of the test-negative design to estimate the protective effect of a scalar immune measure: A simulation analysis

BackgroundThe relationship between antibody levels (more generally, a scalar measure of immune protection) at the time of exposure to infection (so-called exposure-proximal correlates of protection) and the risk of infection given exposure is of central interest in evaluating the evolution of immune protection conferred by prior infection and/or vaccination. A version of the test-negative study design (TND), adapted from vaccine effectiveness studies, has been used to assess this relationship. However, the conditions under which such a study identifies the relationship between immune measurements and protection have not been defined. ObjectiveTo evaluate the conditions for TNDs to estimate the relationship between antibody levels or a similar scalar measurement of immunity (hereafter exposure-proximal correlates of protection, COP) and the relative incidence rate of infection given exposure. MethodIndividual-based transmission models, linking infection risk linearly and nonlinearly with COP value and accounting for waning immunity post-vaccination and -infection, were used. Simulations were performed of a TND with sampling on predetermined dates. Data from either one or multiple simulation days were analyzed using logistic regression and generalized additive models. ResultA correctly specified logistic regression model provided an unbiased estimate of the effectiveness of specific COP levels (analogous to vaccine effectiveness). Aggregating data across different simulation dates with incidence-density sampling also provided reliable estimates of protection. When, as is generally the case, the functional form relating COP level to protection is unknown, generalized additive models offer a more flexible alternative to traditional logistic regression approaches. ConclusionA TND can validly estimate the relative effect of an immune COP at the time of exposure on the incidence rate of infection via logistic regression if the functional form of the effect is known and appropriately modeled or unknown a semiparametric approach. Future research should further examine the dynamics of immunity waning and boosting for more reliable inference.