A Spatio-Temporal Infectious Disease Model in the Presence of Uncertainty from Multiple, Imperfect Diagnostic Tests (306499)Grant Brown, University of Iowa
Jacob Oleson, University of Iowa
*Caitlin Ward, University of Iowa
Keywords: Bayesian, epidemic, infectious, sensitivity, specificity, spatio-temporal, diagnostic tests, mumps
Bayesian compartmental infectious disease models yield important inference on disease transmission, by appropriately accounting for the dynamics of infection processes. In addition to estimating transition probabilities and reproductive numbers, these models allow researchers to assess disease risk factors and effectiveness of interventions. Standard infectious disease models assume that all individuals with positive diagnostic tests are infectious, however in reality such procedures produce both false-positives and false-negatives at varying rates. We propose a spatio-temporal infectious disease modeling framework that accounts for the additional uncertainty in the diagnostic testing and classification process and provides estimates of the important transmission dynamics of interest to researchers. The method is applied to data on the 2006 mumps epidemic in Iowa, in which almost 1,500 suspected mumps cases were tested using a buccal or oral swab specimen and/or a blood specimen. While both procedures are believed to have high specificities, the sensitivities can be low and vary depending on the timing of the test as well as the vaccination status of the individual being tested.