Online, semi-parametric estimation of optimal treatment allocations for the control of emerging epidemics
published: July 28, 2015, recorded: June 2015, views: 21
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
A key component in controlling the spread of an epidemic is deciding where, when, and to whom to apply an intervention. Here, we conceptualize the epidemic as spreading across nodes in an network. A treatment allocation strategy formalizes this process as a sequence of functions, one per treatment period, that map up-to-date information on the epidemic to a subset of nodes to receive treatment. An optimal treatment allocation strategy minimizes the expectation of some cumulative measure of harm, e.g., the number of infected individuals, the geographic footprint of the disease, the estimated total cost of the disease, or a composite outcome weighing several important measures. One approach to estimating an optimal allocation strategy is to model the underlying disease dynamics and then use to simulation—optimization. However, constructing a high-quality estimator of the complete system dynamics is difficult especially in the context of emerging epidemics where there is little scientific theory to inform a class of models. We derive estimating equations for the optimal allocation strategy that does not require a model the system dynamics. Furthermore, because this estimator does not require simulation of the disease process it is computationally tractable even for very large problems. We demonstrate the proposed methodology using data on the spread of white-nose syndrome in bats
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !