University of Michigan
The most commonly used dose-response models implicitly assume that accumulation of dose is a time-independent process where each pathogen has a fixed risk of initiating infection. Immune particle neutralization of pathogens, however, may create strong time dependence; i.e. temporally clustered pathogens have a better chance of overwhelming the immune particles than pathogen exposures that occur at lower levels for longer periods of time. In environmental transmission systems, we expect different routes of transmission to elicit different dose-timing patterns and thus potentially different realizations of risk. We present a dose-response model that captures time dependence in a manner that incorporates the dynamics of initial immune response. We then demonstrate the parameter estimation of our model in a dose-response survival analysis using empirical time-series data of inhalational anthrax in monkeys in which we find slight dose-timing effects. Future dose-response experiments should include varying the time pattern of exposure in addition to varying the total doses delivered. Ultimately, the dynamic dose-response paradigm presented here will improve modelling of environmental transmission systems where different systems have different time patterns of exposure.