Beyond cost-effectiveness: Using systems analysis for infectious disease preparedness. (20th January 2017)

• Record Type: Journal Article
• Authors: Phelps, Charles; Madhavan, Guruprasad; Rappuoli, Rino; Colwell, Rita; Fineberg, Harvey
• Is Part Of: Vaccine. Volume 35(2017)Suuplement 1
• Page Start: A46
• Page End: A49
• Publication Date: 2017-01-20
• Subjects: Cost-effectiveness -- Systems analysis -- Ebola -- Infectious diseases -- Global health -- Preparedness -- Zika; Vaccines -- Periodicals; 615.372
• DOI: 10.1016/j.vaccine.2016.08.090
• Languages: English
• ISSNs: 0264-410X

Abstract

Abstract: Until the recent outbreaks, Ebola vaccines ranked low in decision makers' priority lists based on cost-effectiveness analysis and (or) corporate profitability. Despite a relatively small number of Ebola-related cases and deaths (compared to other causes), Ebola vaccines suddenly leapt to highest priority among international health agencies and vaccine developers. Clearly, earlier cost-effectiveness analyses badly missed some factors affecting real world decisions. Multi-criteria systems analysis can improve evaluation and prioritization of vaccine development and also of many other health policy and investment decisions. Neither cost-effectiveness nor cost-benefit analysis can capture important aspects of problems such as Ebola or the emerging threat of Zika, especially issues of inequality and disparity—issues that dominate the planning of many global health and economic organizations. Cost-benefit analysis requires assumptions about the specific value of life—an idea objectionable to many analysts and policy makers. Additionally, standard cost-effectiveness calculations cannot generally capture effects on people uninfected with Ebola for example, but nevertheless affected through such factors as contagion, herd immunity, and fear of dread disease, reduction of travel and commerce, and even the hope of disease eradication. Using SMART Vaccines, we demonstrate how systems analysis can visibly include important "other factors" and more usefully guide decision making and beneficially alter priority setting processes.