Outreach Strategies for Vaccine Distribution: A Multi-period Stochastic Modeling Approach

Vaccination has been proven to be the most effective method to prevent infectious diseases. However, in many low- and middle-income countries with geographically dispersed and nomadic populations, last-mile vaccine delivery can be extremely complex. Because newborns in remote population centers often do not have direct access to clinics and hospitals, they face significant risk from diseases and infections. An approach known as outreach is typically utilized to raise immunization rates in these situations. A set of these remote locations is chosen, and over an appropriate planning period, teams of clinicians and support personnel are sent from a depot to set up mobile clinics at these locations to vaccinate people there and in the immediate surrounding area. In this paper, we model the problem of optimally designing outreach efforts as a mixed integer program that is a combination of a set covering problem and a vehicle routing problem. In addition, because elements relevant to outreach (such as populations and road conditions) are often unstable and unpredictable, we address uncertainty and determine the worst-case solutions. This is done using a multi-period stochastic modeling approach that considers updated model parameter estimates and revised plans for subsequent planning periods. We also conduct numerical experiments to provide insights on how demographic characteristics affect outreach planning and where outreach planners should focus their attention when gathering data.