Learning to Trust Flu Shots: Quasi‐Experimental Evidence from the 2009 Swine Flu Pandemic

Abstract

This paper studies consumer learning in influenza vaccination decisions. We examine consumer learning in influenza vaccine demand within a reduced form instrumental variable framework that exploits differences in risk characteristics of different influenza viruses as a natural experiment to distinguish the effects of learning based on previous influenza vaccination experiences from unobserved heterogeneity. The emergence of a new virus strain (influenza A H1N1/09) during the 2009 'Swine flu' pandemic resulted in two different vaccines being recommended for distinct population subgroups with some people, who were not usually targeted by seasonal vaccination programs, being specifically recommended for the new Swine flu vaccine. We use these differences in vaccination targeting to construct instrumental variables for estimating the effect of past influenza vaccination experiences on the demand for pandemic vaccine. We find large causal effects of previous seasonal vaccination on pandemic vaccination. Causal effects of past influenza vaccination experiences on perceived vaccination safety are likely to be an important pathway linking past vaccination experiences with future vaccine uptake. Our results suggest a significant role of learning in vaccination decisions. Current efforts to expand seasonal vaccination may thus have potentially important long-term effects on future influenza vaccination levels and pandemic preparedness. Copyright © 2016 John Wiley & Sons, Ltd.

On the demand for telemedicine: Evidence from the COVID‐19 pandemic

“…1 By showing that demand dramatically increased after the onset of the COVID‐19 epidemic, and by presenting preliminary evidence of persistence of those effects, our results contribute to the large literature that analyzes patient learning about health‐care markets. For example, similar learning processes have be shown to reduce the costs of the drug‐patient matching process in pharmaceutical markets (Crawford & Shum, 2005), to increase the take up of new vaccines (Maurer & Harris, 2016), and to affect the choice of health‐insurance plans (Chernew et al., 2008). 2…”

“…1 By showing that demand dramatically increased after the onset of the COVID-19 epidemic, and by presenting preliminary evidence of persistence of those effects, our results contribute to the large literature that analyzes patient learning about health-care markets. For example, similar learning processes have be shown to reduce the costs of the drug-patient matching process in pharmaceutical markets (Crawford & Shum, 2005), to increase the take up of new vaccines (Maurer & Harris, 2016), and to affect the choice of health-insurance plans (Chernew et al, 2008). 2 This paper also contributes to the strand of the literature that studies how demand for new health-care services is affected by exogenous changes in factors such as prices of services (Berman & Fenaughty, 2005), consumer's beliefs and social norms (Cranen et al, 2011), or the education and wealth of households (Chunara et al, 2020).…”

COVID-19 health policy evaluation: integrating health and economic perspectives with a data envelopment analysis approach

“…Of particular interest in the context of pandemics is the tension between medical efficacy and economic efficiency [ 69 ], which is increased by the quality of health care and the equitable use of health goods. When evaluating medical or health policy interventions during or after pandemic outbreaks, health economics analyses adopt different perspectives: (1) the perspective of health service providers (doctors, hospitals) studying, e.g., direct costs necessary to treat patients [ 22 , 84 ], stockpiling of drugs [ 7 , 63 ], or withholding effective novel antidotes [ 90 ], (2 patient-centered investigations on, e.g., consumer learning in vaccination decisions [ 88 ], (3) examinations through the lens of vaccine producers, e.g., analyzing the profit-maximizing capacity [ 53 ], and (4) studies evaluating the economic effect of pandemics, e.g., on companies through the lens of employee absences from work [ 40 ], effects on tourism and certain production sectors [108], and overall effects on a country’s economy [ 74 , 77 ]. The objective of our study was to provide a country-specific efficiency evaluation of the fight against COVID-19 for 19 OECD countries while focusing on the role of pre-pandemic health care policy and its interconnection to ad hoc interventions (case 1 and case 2), as well as the impact of COVID-19 as an exogenous health threat to the country’s economy (case 3) [ 8 ].…”