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To measure adolescent girls’ preferences over features of human papillomavirus (HPV) vaccines in order to provide quantitative estimates of the perceived benefits of…
To measure adolescent girls’ preferences over features of human papillomavirus (HPV) vaccines in order to provide quantitative estimates of the perceived benefits of vaccination and potential vaccine uptake.
A discrete choice experiment (DCE) survey was developed to measure adolescent girls’ preferences over features of HPV vaccines. The survey was fielded to a U.S. sample of 307 girls aged 13–17 years who had not yet received an HPV vaccine in June 2008.
In a latent class logit model, two distinct groups were identified – one with strong preferences against vaccination which largely did not differentiate between vaccine features, and another that was receptive to vaccination and had well-defined preferences over vaccine features. Based on the mean estimates over the entire sample, we estimate that girls’ valuation of bivalent and quadrivalent HPV vaccines ranged between $400 and $460 in 2008, measured as willingness-to-pay (WTP). The additional value of genital warts protection was $145, although cervical cancer efficacy was the most preferred feature. We estimate maximum uptake of 54–65%, close to the 53% reported for one dose in 2011 surveillance data, but higher than the 35% for three doses in surveillance data.
We conclude that adolescent girls do form clear opinions and some place significant value on HPV vaccination, making research on their preferences vital to understanding the determinants of HPV vaccine demand.
DCE studies may be used to design more effective vaccine-promotion programs and for reassessing public health recommendations and guidelines as new vaccines are made available.
Annual influenza epidemics cause great losses in both human and financial terms. The purpose of this paper is to propose a model for optimizing a large-scale influenza…
Annual influenza epidemics cause great losses in both human and financial terms. The purpose of this paper is to propose a model for optimizing a large-scale influenza vaccination program (VP). The goal is to minimize the total cost of the vaccination supply chain while guaranteeing a sufficiently high level of population protection. From a practical point of view, the analysis returns the number of shipments and the quantity of vaccines in each periodic shipment that should be delivered from the manufacturers to the distribution center (DC), from the DC to the clinics, and from the clinics to each sub-group of customers during the vaccination season.
A mixed-integer programming optimization model is developed to describe the problem for a supply chain consisting of vaccine manufacturers, the healthcare organization (HCO) (comprising the DC and clinics), and the population being vaccinated (customers). The model suggests a VP that implemented by a nation-wide HCO.
The benefits of the proposed approach are shown to be particularly salient in cases of limited resources, as the model distributes demand backlogs in an efficient manner, prioritizing high-risk sub-groups of the population over lower-risk sub-groups. In particular, the authors show a reduction in direct medical burden of consumers, such as the need for doctors, hospitalization resources, and reduction of indirect, non-medical burden, such as loss of workdays.
Drawing from the extended enterprise paradigm, and, in particular, taking consumer benefits into account, the authors suggest an operational-strategic model that creates impressive added value in a highly constrained supply chain. The model constitutes a powerful decision tool for the deployment of large-scale seasonal products, and its implementation can yield multiple benefits for various consumer segments.
The model proposed herein constitutes a decision support tool comprising operational-tactical and tactical-strategic perspectives, which logistics managers can utilize to create an enterprise-oriented plan that takes into account medical and non-medical costs.