INTEGRATING DATA STREAMS WITH MULTI-SCALE MODELING TO GUIDE NOROVIRUS VACCINE DECISION-MAKING

PROJECT SUMMARYNoroviruses cause over 20 million diarrhea cases annually in the United States, one-fifth of all diarrhea casesglobally, and over 200,000 deaths worldwide. Norovirus vaccines are currently in development. Our goal is todevelop a comprehensive detailed, user-friendly norovirus transmission and vaccination simulator that will helpguide and inform norovirus vaccine design and implementation.To achieve this goal, a number of specific insights and parameter estimates are required, such as: At what ratedoes immunity to norovirus wane in individuals? How does prior infection (or vaccination) affect the course ofillness and the duration/quantity of viral shedding? What is the degree of cross-protecting immunity at thegenogroup, genotype and strain-level? With such results in hand, we can answer the following vaccine strategyquestions: What frequency of re-vaccination is required for control? How often will a norovirus vaccine need tobe updated to keep up with viral evolution? What are the population-level health impacts of age-targeted (orother) vaccination strategies?To answer these questions, we will integrate detailed data from multiple sources including volunteer infectionstudies, national surveillance, and viral sequence datasets. We will fit mathematical and statistical models tothese datasets to answer the questions posed above. Our analyses will provide a thorough understanding ofthe epidemiological and evolutionary dynamics of the virus. This information will be used to develop andimplement a detailed norovirus transmission and vaccination simulator. This simulator will be packaged as auser-friendly application for vaccine designers and policy implementers to analyze and forecast possibleimpacts of vaccine formulations and distribution strategies.