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Kelsall J. COVID-19 vaccine refusal as unfair free-riding. MEDICINE, HEALTH CARE, AND PHILOSOPHY 2024; 27:107-119. [PMID: 38189907 PMCID: PMC10904454 DOI: 10.1007/s11019-023-10188-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/30/2023] [Indexed: 01/09/2024]
Abstract
Contributions to COVID-19 vaccination programmes promise valuable collective goods. They can support public and individual health by creating herd immunity and taking the pressure off overwhelmed public health services; support freedom of movement by enabling governments to remove restrictive lockdown policies; and improve economic and social well-being by allowing businesses, schools, and other essential public services to re-open. The vaccinated can contribute to the production of these goods. The unvaccinated, who benefit from, but who do not contribute to these goods can be morally criticised as free-riders. In this paper defends the claim that in the case of COVID-19, the unvaccinated are unfair free-riders. I defend the claim against two objections. First, that they are not unfair free-riders because they lack the subjective attitudes and intentions of free-riders; second, that although the unvaccinated may be free-riders, their free-riding is not unfair.
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Affiliation(s)
- Joshua Kelsall
- University of Warwick, PAIS Building, Coventry, CV47AL, UK.
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2
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Blasioli E, Mansouri B, Tamvada SS, Hassini E. Vaccine Allocation and Distribution: A Review with a Focus on Quantitative Methodologies and Application to Equity, Hesitancy, and COVID-19 Pandemic. OPERATIONS RESEARCH FORUM 2023; 4:27. [PMCID: PMC10028329 DOI: 10.1007/s43069-023-00194-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
This review focuses on vaccine distribution and allocation in the context of the current COVID-19 pandemic. The implications discussed are in the areas of equity in vaccine distribution and allocation (at a national level as well as worldwide), vaccine hesitancy, game-theoretic modeling to guide decision-making and policy-making at a governmental level, distribution and allocation barriers (in particular in low-income countries), and operations research (OR) mathematical models to plan and execute vaccine distribution and allocation. To conduct this review, we adopt a novel methodology that consists of three phases. The first phase deploys a bibliometric analysis; the second phase concentrates on a network analysis; and the last phase proposes a refined literature review based on the results obtained by the previous two phases. The quantitative techniques utilized to conduct the first two phases allow describing the evolution of the research in this area and its potential ramifications in future. In conclusion, we underscore the significance of operations research (OR)/management science (MS) research in addressing numerous challenges and trade-offs connected to the current pandemic and its strategic impact in future research.
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Affiliation(s)
- Emanuele Blasioli
- grid.25073.330000 0004 1936 8227DeGroote School of Business, McMaster University, Hamilton, Canada
| | - Bahareh Mansouri
- grid.412362.00000 0004 1936 8219Sobey School of Business, Saint Mary’s University, Halifax, Canada
| | - Srinivas Subramanya Tamvada
- grid.29857.310000 0001 2097 4281Department of Industrial and Manufacturing Engineering, Pennsylvania State University, State College, PA, USA, PennsyIvania, USA
| | - Elkafi Hassini
- grid.25073.330000 0004 1936 8227DeGroote School of Business, McMaster University, Hamilton, Canada
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Deka A, Pantha B, Bhattacharyya S. Optimal Management of Public Perceptions During A Flu Outbreak: A Game-Theoretic Perspective. Bull Math Biol 2020; 82:139. [PMID: 33064223 PMCID: PMC7563916 DOI: 10.1007/s11538-020-00817-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 10/02/2020] [Indexed: 10/29/2022]
Abstract
Public perceptions and sentiments play a crucial role in the success of vaccine uptake in the community. While vaccines have proven to be the best preventive method to combat the flu, the attitude and knowledge about vaccines are a major hindrance to higher uptake in most of the countries. The yearly coverage, especially in the vulnerable groups in the population, often remains below the herd immunity level despite the Flu Awareness Campaign organized by WHO every year worldwide. This brings immense challenges to the nation's public health protection agency for strategic decision-making in controlling the flu outbreak every year. To understand the impact of public perceptions and vaccination decisions while designing optimal immunization policy, we model the individual decision-making as a two-strategy pairwise contest game, where pay-off is considered as a function of public health effort for the campaign. We use Pontryagin's maximum principle to identify the best possible strategy for public health to implement vaccination and reduce infection at a minimum cost. Our optimal analysis shows that the cost of public health initiatives is qualitatively and quantitatively different under different public perceptions and attitudes towards vaccinations. When individual risk perception evolves with vaccine uptake or disease induced death, our model demonstrates a feed-forward mechanism in the dynamics of vaccination and exhibits an increase in vaccine uptake. Using numerical simulation, we also observe that the optimal cost can be minimized by putting the effort in the beginning and later part of the outbreak rather than during the peak. It confers that public health efforts towards disseminating disease severity or actual vaccination risk might accelerate the vaccination coverage and mitigate the infection faster.
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Affiliation(s)
- Aniruddha Deka
- Disease Modelling Lab, Department of Mathematics, School of Natural Sciences, NH-91, Gautam Buddha Nagar, UP India
| | - Buddhi Pantha
- College of Arts and Sciences, Abraham Baldwin Agricultural College, Tifton, GA USA
| | - Samit Bhattacharyya
- Disease Modelling Lab, Department of Mathematics, School of Natural Sciences, NH-91, Gautam Buddha Nagar, UP India
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4
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Deka A, Bhattacharyya S. Game dynamic model of optimal budget allocation under individual vaccination choice. J Theor Biol 2019; 470:108-118. [PMID: 30904449 DOI: 10.1016/j.jtbi.2019.03.014] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 03/19/2019] [Accepted: 03/20/2019] [Indexed: 11/20/2022]
Abstract
Communicable diseases are leading cause of child mortality in developing and under-developed countries. Public health ministries in states and country allocate a considerable amount of budget every year for vaccination campaigns to control infections. Even third-party agencies such as Gates Foundation, UNDP, GAVI, World Bank, WHO also allocate huge funds to under-developed and developing countries for vaccination programs and disease eliminations. However, economic constraints and current disease prevalence are not enough driving factors for optimal decisions in budget allocations for vaccinations and controlling the disease. In a population under voluntary vaccination campaign, high vaccine coverage cannot be taken for granted, as individuals' free-riding behaviour plays a significant role in achieving the herd immunity level coverage. Individual-level vaccine exemptions and ignoring this important component by the policymakers are key determinants for failure of disease elimination program these days in many under-developed and developing countries. We integrate evolutionary game theory and compartmental model of disease transmission to analyze how individual vaccination choice influence the budget allocations and vice-versa. Our model illustrates that individuals' perceived risk plays an important role in optimal budget allocations to minimize infections. Analyses of our model indicate that the optimal distribution of third-party funds may be very different than usual, especially in multiple populations with contrasting demographic and economic profiles. These findings are certainly useful to public health policymakers and may help to quantify certain parameters in budget allocations to control vaccine-preventable diseases.
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Affiliation(s)
- Aniruddha Deka
- Disease Modelling Lab, Department of Mathematics, School of Natural Sciences, Shiv Nadar University, India.
| | - Samit Bhattacharyya
- Disease Modelling Lab, Department of Mathematics, School of Natural Sciences, Shiv Nadar University, India.
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5
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Individual decisions to vaccinate one's child or oneself: A discrete choice experiment rejecting free-riding motives. Soc Sci Med 2018; 207:106-116. [PMID: 29738898 DOI: 10.1016/j.socscimed.2018.04.038] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Revised: 04/18/2018] [Accepted: 04/24/2018] [Indexed: 02/03/2023]
Abstract
It is essential for public health to understand what drives people's hesitance towards vaccination. Theoretical models of vaccination decisions are ubiquitous, often incorporating herd immunity, perceptions of vaccine-related side-effects (VRSE) and of vaccine-preventable burden of disease, but with little to no empirical exploration. Herd immunity is a (usually) positive externality where vaccinated individuals influence others' risks by their reduced capability to transmit an infectious disease to them. It is often assumed that (rational) individuals incorporate this externality in their strategic vaccination decision, from which free-riding behavior arises. We performed a Bayesian D-efficient discrete choice experiment in February-March 2017 to study vaccination behavior in 1919 Belgian respondents. Choice sets with vaccine profiles were constructed using six attributes: vaccine effectiveness, VRSE, accessibility (in terms of convenience and reimbursement), vaccine-preventable burden of disease, local (respondents' network of contacts) vaccination coverage, and population (the population at large) vaccination coverage. VRSE and accessibility are the most influential attributes, followed by vaccine effectiveness and burden of disease. Both population and local coverage are less important than the other attributes, but show a significant direct linear relationship with vaccine utility. This supports the existence of peer influence (more incentivized as more and more vaccinate), rather than free-riding on herd immunity. These findings were independent of whether respondents made vaccine choices for themselves or for their child. Around 40% of the respondents indicated accepting vaccination with little or no questioning. These 'acceptors' were less sensitive to changes in the vaccine-preventable burden of disease for their child's vaccination choices (but not for themselves). Public health institutions are critical in stimulating vaccine uptake by making vaccines conveniently available at an affordable price and by communicating pro-actively on perceived VRSEs. The free-riding assumption as a driver of individual vaccine decisions, seems inappropriate, but this observation needs confirming in other populations.
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Verelst F, Willem L, Beutels P. Behavioural change models for infectious disease transmission: a systematic review (2010-2015). J R Soc Interface 2016; 13:20160820. [PMID: 28003528 PMCID: PMC5221530 DOI: 10.1098/rsif.2016.0820] [Citation(s) in RCA: 169] [Impact Index Per Article: 21.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Accepted: 11/25/2016] [Indexed: 12/13/2022] Open
Abstract
We review behavioural change models (BCMs) for infectious disease transmission in humans. Following the Cochrane collaboration guidelines and the PRISMA statement, our systematic search and selection yielded 178 papers covering the period 2010-2015. We observe an increasing trend in published BCMs, frequently coupled to (re)emergence events, and propose a categorization by distinguishing how information translates into preventive actions. Behaviour is usually captured by introducing information as a dynamic parameter (76/178) or by introducing an economic objective function, either with (26/178) or without (37/178) imitation. Approaches using information thresholds (29/178) and exogenous behaviour formation (16/178) are also popular. We further classify according to disease, prevention measure, transmission model (with 81/178 population, 6/178 metapopulation and 91/178 individual-level models) and the way prevention impacts transmission. We highlight the minority (15%) of studies that use any real-life data for parametrization or validation and note that BCMs increasingly use social media data and generally incorporate multiple sources of information (16/178), multiple types of information (17/178) or both (9/178). We conclude that individual-level models are increasingly used and useful to model behaviour changes. Despite recent advancements, we remain concerned that most models are purely theoretical and lack representative data and a validation process.
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Affiliation(s)
- Frederik Verelst
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Lander Willem
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Philippe Beutels
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- School of Public Health and Community Medicine, The University of New South Wales, Sydney, New South Wales, Australia
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7
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Keane CR. Resilience, tipping, and hydra effects in public health: emergent collective behavior in two agent-based models. BMC Public Health 2016; 16:265. [PMID: 26975419 PMCID: PMC4791925 DOI: 10.1186/s12889-016-2938-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2016] [Accepted: 03/08/2016] [Indexed: 01/30/2023] Open
Abstract
Background Collective health behavior often demonstrates counter-intuitive dynamics, sometimes resisting interventions designed to produce change, or even producing effects that are in the opposite direction than intended by the intervention, e.g. lowering infectivity resulting in increased infections. At other times collective health behavior exhibits sudden large-scale change in response to small interventions or change in the environment, a phenomenon often called “tipping.” I hypothesize that these seemingly very different phenomena can all be explained by the same dynamic, a type of collective resilience. Methods I compared two simple agent-based models of interactions in networks: a public health behavior game, in which individuals decide whether or not to adopt protective behavior, and a microbial-level game, in which three different strains of bacteria attack each other. I examined the type of networks and other conditions that support a dynamic balance, and determined what changes of conditions will tip the balance. Results Both models show lasting dynamic equilibrium and resilience, resulting from negative feedback that supports oscillating coexistence of diversity under a range of conditions. In the public health game, health protection is followed by free-riding defectors, followed by a rise in infection, in long-lasting cycles. In the microbial game, each of three strains takes turns dominating. In both games, the dynamic balance is tipped by lowering the level of local clustering, changing the level of benefit, or lowering infectivity or attack rate. Lowering infectivity has the surprising effect of increasing the numbers of infected individuals. We see parallel results in the microbial game of three bacterial strains, where lowering one strain’s attack rate (analogous to lowering infectivity) increases the numbers of the restrained attacker, a phenomenon captured by the phrase, “the enemy of my enemy is my friend.” Conclusions Collective behavior often shows a dynamic balance, resulting from negative feedback, supporting diversity and resisting change. Above certain threshold conditions, the dynamic balance is tipped towards uniformity of behavior. Under a certain range of conditions we see “hydra effects” in which interventions to lower attack rate or infectivity are self-defeating. Simple models of collective behavior can explain these seemingly disparate dynamics. Electronic supplementary material The online version of this article (doi:10.1186/s12889-016-2938-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Christopher Robert Keane
- Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, 130 DeSoto Street, Pittsburgh, PA, 15261, USA.
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Oraby T, Bauch CT. Bounded rationality alters the dynamics of paediatric immunization acceptance. Sci Rep 2015; 5:10724. [PMID: 26035413 PMCID: PMC4451793 DOI: 10.1038/srep10724] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2014] [Accepted: 04/24/2015] [Indexed: 11/26/2022] Open
Abstract
Interactions between disease dynamics and vaccinating behavior have been explored in many coupled behavior-disease models. Cognitive effects such as risk perception, framing, and subjective probabilities of adverse events can be important determinants of the vaccinating behaviour, and represent departures from the pure "rational" decision model that are often described as "bounded rationality". However, the impact of such cognitive effects in the context of paediatric infectious disease vaccines has received relatively little attention. Here, we develop a disease-behavior model that accounts for bounded rationality through prospect theory. We analyze the model and compare its predictions to a reduced model that lacks bounded rationality. We find that, in general, introducing bounded rationality increases the dynamical richness of the model and makes it harder to eliminate a paediatric infectious disease. In contrast, in other cases, a low cost, highly efficacious vaccine can be refused, even when the rational decision model predicts acceptance. Injunctive social norms can prevent vaccine refusal, if vaccine acceptance is sufficiently high in the beginning of the vaccination campaign. Cognitive processes can have major impacts on the predictions of behaviour-disease models, and further study of such processes in the context of vaccination is thus warranted.
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Affiliation(s)
- Tamer Oraby
- Department of Mathematics, University of Texas - Pan American, Edinburg, Texas, USA
| | - Chris T. Bauch
- Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada
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9
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Conflicts of interest during contact investigations: a game-theoretic analysis. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2014; 2014:952381. [PMID: 24982688 PMCID: PMC4052784 DOI: 10.1155/2014/952381] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2013] [Revised: 02/04/2014] [Accepted: 03/06/2014] [Indexed: 11/17/2022]
Abstract
The goal of contact tracing is to reduce the likelihood of transmission, particularly to individuals who are at greatest risk for developing complications of infection, as well as identifying individuals who are in need of medical treatment of other interventions. In this paper, we develop a simple mathematical model of contact investigations among a small group of individuals and apply game theory to explore conflicts of interest that may arise in the context of perceived costs of disclosure. Using analytic Kolmogorov equations, we determine whether or not it is possible for individual incentives to drive noncooperation, even though cooperation would yield a better group outcome. We found that if all individuals have a cost of disclosure, then the optimal individual decision is to simply not disclose each other. With further analysis of (1) completely offsetting the costs of disclosure and (2) partially offsetting the costs of disclosure, we found that all individuals disclose all contacts, resulting in a smaller basic reproductive number and an alignment of individual and group optimality. More data are needed to understand decision making during outbreak investigations and what the real and perceived costs are.
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Elmgren L, Li X, Wilson C, Ball R, Wang J, Cichutek K, Pfleiderer M, Kato A, Cavaleri M, Southern J, Jivapaisarnpong T, Minor P, Griffiths E, Sohn Y, Wood D. A global regulatory science agenda for vaccines. Vaccine 2014; 31 Suppl 2:B163-75. [PMID: 23598478 DOI: 10.1016/j.vaccine.2012.10.117] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2012] [Revised: 10/22/2012] [Accepted: 10/31/2012] [Indexed: 02/06/2023]
Abstract
The Decade of Vaccines Collaboration and development of the Global Vaccine Action Plan provides a catalyst and unique opportunity for regulators worldwide to develop and propose a global regulatory science agenda for vaccines. Regulatory oversight is critical to allow access to vaccines that are safe, effective, and of assured quality. Methods used by regulators need to constantly evolve so that scientific and technological advances are applied to address challenges such as new products and technologies, and also to provide an increased understanding of benefits and risks of existing products. Regulatory science builds on high-quality basic research, and encompasses at least two broad categories. First, there is laboratory-based regulatory science. Illustrative examples include development of correlates of immunity; or correlates of safety; or of improved product characterization and potency assays. Included in such science would be tools to standardize assays used for regulatory purposes. Second, there is science to develop regulatory processes. Illustrative examples include adaptive clinical trial designs; or tools to analyze the benefit-risk decision-making process of regulators; or novel pharmacovigilance methodologies. Included in such science would be initiatives to standardize regulatory processes (e.g., definitions of terms for adverse events [AEs] following immunization). The aim of a global regulatory science agenda is to transform current national efforts, mainly by well-resourced regulatory agencies, into a coordinated action plan to support global immunization goals. This article provides examples of how regulatory science has, in the past, contributed to improved access to vaccines, and identifies gaps that could be addressed through a global regulatory science agenda. The article also identifies challenges to implementing a regulatory science agenda and proposes strategies and actions to fill these gaps. A global regulatory science agenda will enable regulators, academics, and other stakeholders to converge around transformative actions for innovation in the regulatory process to support global immunization goals.
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Ball R. Perspectives on the future of postmarket vaccine safety surveillance and evaluation. Expert Rev Vaccines 2014; 13:455-62. [DOI: 10.1586/14760584.2014.891941] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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Oraby T, Thampi V, Bauch CT. The influence of social norms on the dynamics of vaccinating behaviour for paediatric infectious diseases. Proc Biol Sci 2014; 281:20133172. [PMID: 24523276 DOI: 10.1098/rspb.2013.3172] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Mathematical models that couple disease dynamics and vaccinating behaviour often assume that the incentive to vaccinate disappears if disease prevalence is zero. Hence, they predict that vaccine refusal should be the rule, and elimination should be difficult or impossible. In reality, countries with non-mandatory vaccination policies have usually been able to maintain elimination or very low incidence of paediatric infectious diseases for long periods of time. Here, we show that including injunctive social norms can reconcile such behaviour-incidence models to observations. Adding social norms to a coupled behaviour-incidence model enables the model to better explain pertussis vaccine uptake and disease dynamics in the UK from 1967 to 2010, in both the vaccine-scare years and the years of high vaccine coverage. The model also illustrates how a vaccine scare can perpetuate suboptimal vaccine coverage long after perceived risk has returned to baseline, pre-vaccine-scare levels. However, at other model parameter values, social norms can perpetuate depressed vaccine coverage during a vaccine scare well beyond the time when the population's baseline vaccine risk perception returns to pre-scare levels. Social norms can strongly suppress vaccine uptake despite frequent outbreaks, as observed in some small communities. Significant portions of the parameter space also exhibit bistability, meaning long-term outcomes depend on the initial conditions. Depending on the context, social norms can either support or hinder immunization goals.
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Affiliation(s)
- Tamer Oraby
- Department of Mathematics and Statistics, University of Guelph, , Guelph, Ontario, Canada, Department of Applied Mathematics, University of Waterloo, , Waterloo, Ontario, Canada
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Miller AC, Polgreen LA, Polgreen PM. Optimal screening strategies for healthcare associated infections in a multi-institutional setting. PLoS Comput Biol 2014; 10:e1003407. [PMID: 24391484 PMCID: PMC3879151 DOI: 10.1371/journal.pcbi.1003407] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2013] [Accepted: 11/11/2013] [Indexed: 11/29/2022] Open
Abstract
Health institutions may choose to screen newly admitted patients for the presence of disease in order to reduce disease prevalence within the institution. Screening is costly, and institutions must judiciously choose which patients they wish to screen based on the dynamics of disease transmission. Since potentially infected patients move between different health institutions, the screening and treatment decisions of one institution will affect the optimal decisions of others; an institution might choose to “free-ride” off the screening and treatment decisions of neighboring institutions. We develop a theoretical model of the strategic decision problem facing a health care institution choosing to screen newly admitted patients. The model incorporates an SIS compartmental model of disease transmission into a game theoretic model of strategic decision-making. Using this setup, we are able to analyze how optimal screening is influenced by disease parameters, such as the efficacy of treatment, the disease recovery rate and the movement of patients. We find that the optimal screening level is lower for diseases that have more effective treatments. Our model also allows us to analyze how the optimal screening level varies with the number of decision makers involved in the screening process. We show that when institutions are more autonomous in selecting whom to screen, they will choose to screen at a lower rate than when screening decisions are more centralized. Results also suggest that centralized screening decisions have a greater impact on disease prevalence when the availability or efficacy of treatment is low. Our model provides insight into the factors one should consider when choosing whether to set a mandated screening policy. We find that screening mandates set at a centralized level (i.e. state or national) will have a greater impact on the control of infectious disease. Healthcare associated infections are a major cause of morbidity and mortality. Screening patients on admission to the hospital may reduce prevalence by identifying infected individuals; infected individuals can then be treated or isolated to prevent further spread. Because screening is costly, institutions must weigh the benefits of reduced prevalence against the costs of screening. However, patients move between institutions carrying disease with them; consequently, when choosing who to screen, institutions must also consider the rates at which neighboring institutions screen patients as well. We develop a theoretical model that describes this strategic decision process. Using this model we are able to analyze the screening decision problem along three dimensions: (1) how disease specific parameters, such as the effectiveness of treatment, influence the optimal screening level, (2) how the degree of centralization in screening policy (e.g. local, state or federal) influences the optimal screening level, and (3) how these two sets of factors combine to influence the optimal screening level. Our model highlights factors to consider when choosing to implement screening policy, and results are of use to policy makers wishing to reduce the prevalence of infectious disease.
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Affiliation(s)
- Aaron C. Miller
- Department of Pharmacy Practice & Science, University of Iowa College of Pharmacy, Iowa City, Iowa, United States of America
- * E-mail:
| | - Linnea A. Polgreen
- Department of Pharmacy Practice & Science, University of Iowa College of Pharmacy, Iowa City, Iowa, United States of America
| | - Philip M. Polgreen
- Division of Infectious Diseases, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, United States of America
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Cohen MJ, Brezis M, Block C, Diederich A, Chinitz D. Vaccination, herd behavior, and herd immunity. Med Decis Making 2013; 33:1026-38. [PMID: 23695369 DOI: 10.1177/0272989x13487946] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND During the 2009 outbreak of novel influenza AH1N1, insufficient data were available to adequately inform decision makers about benefits and risks of vaccination and disease. We hypothesized that individuals would opt to mimic their peers, having no better decision anchor. We used Game Theory, decision analysis, and transmission models to simulate the impact of subjective risks and preference estimates on vaccination behavior. METHODS We asked 95 students to provide estimates of risk and health state valuations with regard to AH1N1 infection, complications, and expectations of vaccine benefits and risks. These estimates were included in a sequential chain of models: a dynamic epidemic model, a decision tree, and a population-level model. Additionally, participants' intentions to vaccinate or not at varying vaccination rates were documented. RESULTS The model showed that at low vaccination rates, vaccination dominated. When vaccination rates increased above 78%, nonvaccination was the dominant strategy. We found that vaccination intentions did not correspond to the shift in strategy dominance and segregated to 3 types of intentions: regardless of what others do 29/95 (31%) intended to vaccinate while 27/95 (28%) did not; among 39 of 95 (41%) intention was positively associated with putative vaccination rates. CONCLUSIONS Some people conform to the majority's choice, either shifting epidemic dynamics toward herd immunity or, conversely, limiting societal goals. Policy leaders should use models carefully, noting their limitations and theoretical assumptions. Behavior drivers were not explicitly explored in this study, and the discrepant results beg further investigation. Models including real subjective perceptions with empiric or subjective probabilities can provide insight into deviations from expected rational behavior and suggest interventions in order to provide better population outcomes.
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Affiliation(s)
- Matan J Cohen
- Center for Clinical Quality and Safety, Hadassah-Hebrew University Medical Center, Jerusalem, Israel (MJC, MB).,Division of Internal Medicine Ein Kerem campus, Hadassah-Hebrew University Medical Center, Jerusalem, Israel (MJC),Department of Clinical Microbiology and Infectious Diseases, Hadassah-Hebrew University Medical Center, Jerusalem, Israel (MJC, CB),Braun School of Public Health and Community Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel (MJC, DC)
| | - Mayer Brezis
- Center for Clinical Quality and Safety, Hadassah-Hebrew University Medical Center, Jerusalem, Israel (MJC, MB)
| | - Colin Block
- Department of Clinical Microbiology and Infectious Diseases, Hadassah-Hebrew University Medical Center, Jerusalem, Israel (MJC, CB)
| | | | - David Chinitz
- Braun School of Public Health and Community Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel (MJC, DC)
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15
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Shim E, Grefenstette JJ, Albert SM, Cakouros BE, Burke DS. A game dynamic model for vaccine skeptics and vaccine believers: measles as an example. J Theor Biol 2011; 295:194-203. [PMID: 22108239 DOI: 10.1016/j.jtbi.2011.11.005] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2011] [Revised: 10/03/2011] [Accepted: 11/07/2011] [Indexed: 11/30/2022]
Abstract
Widespread avoidance of Measles-Mumps-Rubella vaccination (MMR), with a consequent increase in the incidence of major measles outbreaks, demonstrates that the effectiveness of vaccination programs can be thwarted by the public misperceptions of vaccine risk. By coupling game theory and epidemic models, we examine vaccination choice among populations stratified into two behavioral groups: vaccine skeptics and vaccine believers. The two behavioral groups are assumed to be heterogeneous with respect to their perceptions of vaccine and infection risks. We demonstrate that the pursuit of self-interest among vaccine skeptics often leads to vaccination levels that are suboptimal for a population, even if complete coverage is achieved among vaccine believers. The demand for measles vaccine across populations driven by individual self-interest was found to be more sensitive to the proportion of vaccine skeptics than to the extent to which vaccine skeptics misperceive the risk of vaccine. Furthermore, as the number of vaccine skeptics increases, the probability of infection among vaccine skeptics increases initially, but it decreases once the vaccine skeptics begin receiving the vaccination, if both behavioral groups are vaccinated according to individual self-interest. Our results show that the discrepancy between the coverages of measles vaccine that are driven by self-interest and those driven by population interest becomes larger when the cost of vaccination increases. This research illustrates the importance of public education on vaccine safety and infection risk in order to maintain vaccination levels that are sufficient to maintain herd immunity.
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Affiliation(s)
- Eunha Shim
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.
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Wu B, Fu F, Wang L. Imperfect vaccine aggravates the long-standing dilemma of voluntary vaccination. PLoS One 2011; 6:e20577. [PMID: 21687680 PMCID: PMC3110791 DOI: 10.1371/journal.pone.0020577] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2011] [Accepted: 05/04/2011] [Indexed: 11/18/2022] Open
Abstract
Achieving widespread population immunity by voluntary vaccination poses a major challenge for public health administration and practice. The situation is complicated even more by imperfect vaccines. How the vaccine efficacy affects individuals' vaccination behavior has yet to be fully answered. To address this issue, we combine a simple yet effective game theoretic model of vaccination behavior with an epidemiological process. Our analysis shows that, in a population of self-interested individuals, there exists an overshooting of vaccine uptake levels as the effectiveness of vaccination increases. Moreover, when the basic reproductive number, R0, exceeds a certain threshold, all individuals opt for vaccination for an intermediate region of vaccine efficacy. We further show that increasing effectiveness of vaccination always increases the number of effectively vaccinated individuals and therefore attenuates the epidemic strain. The results suggest that 'number is traded for efficiency': although increases in vaccination effectiveness lead to uptake drops due to free-riding effects, the impact of the epidemic can be better mitigated.
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Affiliation(s)
- Bin Wu
- State Key Laboratory for Turbulence and Complex Systems, Center for Systems and Control, College of Engineering, Peking University, Beijing, China
- * E-mail: (BW); (FF)
| | - Feng Fu
- Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, United States of America
- * E-mail: (BW); (FF)
| | - Long Wang
- State Key Laboratory for Turbulence and Complex Systems, Center for Systems and Control, College of Engineering, Peking University, Beijing, China
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Ball R, Horne D, Izurieta H, Sutherland A, Walderhaug M, Hsu H. Statistical, epidemiological, and risk-assessment approaches to evaluating safety of vaccines throughout the life cycle at the Food and Drug Administration. Pediatrics 2011; 127 Suppl 1:S31-8. [PMID: 21502249 DOI: 10.1542/peds.2010-1722f] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
The public health community faces increasing demands for improving vaccine safety while simultaneously increasing the number of vaccines available to prevent infectious diseases. The passage of the US Food and Drug Administration (FDA) Amendment Act of 2007 formalized the concept of life-cycle management of the risks and benefits of vaccines, from early clinical development through many years of use in large numbers of people. Harnessing scientific and technologic advances is necessary to improve vaccine-safety evaluation. The Office of Biostatistics and Epidemiology in the Center for Biologics Evaluation and Research is working to improve the FDA's ability to monitor vaccine safety by improving statistical, epidemiologic, and risk-assessment methods, gaining access to new sources of data, and exploring the use of genomics data. In this article we describe the current approaches, new resources, and future directions that the FDA is taking to improve the evaluation of vaccine safety.
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Affiliation(s)
- Robert Ball
- Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, Food and Drug Administration, 1401 Rockville Pike, Rockville, MD 20852, USA.
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