The Influence of Epidemiologic Context on the Success of Partner Notification Programs: Analysis of Gonorrhea Transmission Dynamics.

Abstract

Limited estimates exist on the population-level impact of partner notification (PN) for gonorrhea, with uncertainty in the influence of local epidemiology on PN effectiveness. An ecologic study in New York found a 6% reduction in diagnoses with a 10% increase in PN coverage. We estimated gonorrhea incidence reductions via PN across different epidemiologic conditions to compare the effects with the prior finding and to understand key determinants of variation. We developed a stochastic network model of men who have sex with men and calibrated gonorrhea transmission dynamics to varied epidemiologic conditions. The population-level impact of increasing PN was summarized by incidence rate ratios (IRRs), and the relative importance of explanatory variables (including network density, baseline burden, and natural history parameters) was assessed via linear regression modeling of IRR and bootstrapping to evaluate uncertainty in estimation. We estimated an IRR of 0.97 (95% range, 0.93-0.99) for a 10% relative increase in PN coverage, comparable to the IRR of 0.94 (0.91-0.97) identified in the empirical study. PN retained effectiveness under diverse epidemiologic conditions. In a univariate sensitivity analysis, the strongest influence on IRR came from parameters governing index case testing probability, with an IRR of 0.93 when testing was at its highest. Other factors, such as network density, baseline incidence, and various natural history parameters, had relatively minor effects on the IRR. We observed larger individual-level benefits from PN for individuals with higher numbers of partners. Our findings support prior population-level estimates of the impact of PN on gonorrhea incidence.