Real-time prediction model of cVDPV2 outbreaks to aid outbreak response vaccination strategies.

Abstract

Circulating vaccine-derived poliovirus outbreaks are spreading more widely than anticipated, which has generated a crisis for the global polio eradication initiative. Effectively responding with vaccination activities requires a rapid risk assessment. This assessment is made difficult by the low case-to-infection ratio of type 2 poliovirus, variable transmissibility, changing population immunity, surveillance delays, and limited vaccine supply from the global stockpile. The geographical extent of responses have been highly variable between countries. We develop a statistical spatio-temporal model of short-term, district-level poliovirus spread that incorporates known risk factors, including historical wild poliovirus transmission risk, routine immunization coverage, population immunity, and exposure to the outbreak virus. We find that proximity to recent cVDPV2 cases is the strongest risk factor for spread of an outbreak, and find significant associations between population immunity, historical risk, routine immunization, and environmental surveillance (p<0.05). We examine the fit of the model to type 2 vaccine derived poliovirus spread since 2016 and find that our model predicts the location of cVDPV2 cases well (AUC=0.96). We demonstrate use of the model to estimate appropriate scope of outbreak response activities to current outbreaks. As type 2 immunity continues to decline following the cessation of tOPV in 2016, outbreak responses to new cVDPV2 detections will need to be faster and larger in scope. We provide a framework that can be used to support decisions on the appropriate size of a vaccination response when new detections are identified. While the model does not account for all relevant local factors that must be considered in the overall vaccination response, it enables a quantitative basis for outbreak response size.