Quantifying the roles of vomiting, diarrhea, and residents vs. staff in norovirus transmission in U.S. nursing home outbreaks

Carly Adams; David Young; Paul A Gastañaduy; Prabasaj Paul; Zach Marsh; Aron J Hall; Benjamin A Lopman

Statistical algorithms can be used to infer outbreak transmission trees (i.e., who infected 97 whom) from case onset dates and independent estimates of the serial interval (i.e., the time 98 between symptom onset in primary cases and the secondary cases they generate) between 99 generations of case pairs [17] . Individual reproduction numbers (R i ), or the number of secondary 100 cases an individual generates, can then be calculated for all cases. We quantified the contribution 101 of specific symptoms and residents vs. staff in norovirus transmission by examining the 102 associations between these variables and individual case infectivity, which was characterized by 103 6 104 overall aim was to inform implementation of effective norovirus prevention and control 105 measures to reduce the size and duration of norovirus outbreaks in nursing homes. We achieved 106 this aim by characterizing norovirus transmission in these settings.