Does spatial proximity drive norovirus transmission during outbreaks in hospitals?

Harris, John P; Lopman, Ben A; Cooper, Ben S; O'Brien, Sarah J

We then used the matrix of π ij values to simulate 1000 possible infection trees for each outbreak, by assigning the infector of patient i to be patient j with probability π ij. In these simulations, we assumed that the case with the earliest onset time was the index case and had no infectors on the ward. If more than one patient had the earliest onset date in a given outbreak, we selected the index case from these patients with equal probability in each simulation. For each outbreak k, we used these 1000 simulations to produce a proximity metric, P k , defined as where s ijkl is equal to 1 if patient i was infected by patient j in simulation l of outbreak k and is zero otherwise. The p ijk terms measure proximity between patients i and j in outbreak k. In this application, we consider this to be a binary variable equal to 1 if patients i and j occupied the same bay at the time of first symptom onset of these patients. An overall proximity metric, P, is obtained by summing the P k values.The value of P (and of P k for individual outbreaks) should be interpreted as a measure of how much transmission occurs between patients in the same bay.