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Nowalk MP, Smith KJ, Raviotta JM, Wateska A, Zimmerman RK. Cost-effectiveness of recombinant influenza vaccine compared with standard dose influenza vaccine in adults 18-64 years of age. Vaccine 2024; 42:126107. [PMID: 38971665 DOI: 10.1016/j.vaccine.2024.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 07/01/2024] [Accepted: 07/02/2024] [Indexed: 07/08/2024]
Abstract
BACKGROUND The Advisory Committee on Immunization Practices (ACIP) uses the Evidence to Recommendations Framework that includes cost-effectiveness analyses (CEA) for determining vaccine recommendations. ACIP's preference for protecting adults ≥ 65 years is enhanced vaccines, including recombinant influenza vaccine (RIV4), adjuvanted or high dose influenza vaccine. Less is known about the CEA of enhanced vaccines for younger adults. METHODS We used decision analysis modeling from a societal perspective to determine the cost-effectiveness, measured in quality adjusted life years (QALYs), of RIV4 compared with standard dose quadrivalent influenza vaccine (SD-IIV4) in adults 18-64 years old. Model inputs included 2018-2020 vaccine effectiveness (VE) estimates based on medical record data from a large local health system, 2019-2020 national vaccination and influenza epidemic parameters, with costs and population distributions fitted to the season. RESULTS Among adults ages 18-64 years, RIV4 cost $94,186/QALY gained, compared to SD-IIV4. Among those 50-64 years old, RIV4 was relatively more cost-effective ($61,329/QALY gained). Cost-effectiveness estimates for 18-64-year-olds were sensitive to the absolute difference in VE between SD-IIV4 and RIV4, among other parameters. Use of RIV4 in 18-64-year-olds would result in fewer cases (669,984), outpatient visits (261,293), hospitalizations (20,046) and deaths (1,018) annually. The majority (59 %; 597 of 1018) of the decreases in deaths occurred in the 50-64-year-olds. CONCLUSIONS While RIV4 was effective and cost-effective relative to SD-IIV4 for both 50-64-year-old and 18-64-year-old adults, cost-effectiveness was sensitive to small changes in parameters among 18-64-year-olds. Because substantial public health benefits occur with enhanced vaccines, health systems and policy makers may opt for preferential product use in select age/risk groups (e.g., 50-64 year olds) to maximize their cost-benefit ratios.
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Affiliation(s)
- Mary Patricia Nowalk
- University of Pittsburgh School of Medicine, Department of Family Medicine, Pittsburgh PA, 15261 USA
| | - Kenneth J Smith
- University of Pittsburgh School of Medicine, Department of Medicine, Pittsburgh PA, 15261 USA
| | - Jonathan M Raviotta
- University of Pittsburgh School of Medicine, Department of Family Medicine, Pittsburgh PA, 15261 USA.
| | - Angela Wateska
- University of Pittsburgh School of Medicine, Department of Medicine, Pittsburgh PA, 15261 USA
| | - Richard K Zimmerman
- University of Pittsburgh School of Medicine, Department of Family Medicine, Pittsburgh PA, 15261 USA
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2
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Bartsch SM, Weatherwax C, Wasserman MR, Chin KL, Martinez MF, Velmurugan K, Singh RD, John DC, Heneghan JL, Gussin GM, Scannell SA, Tsintsifas AC, O'Shea KJ, Dibbs AM, Leff B, Huang SS, Lee BY. How the Timing of Annual COVID-19 Vaccination of Nursing Home Residents and Staff Affects Its Value. J Am Med Dir Assoc 2024; 25:639-646.e5. [PMID: 38432644 PMCID: PMC10990766 DOI: 10.1016/j.jamda.2024.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 03/05/2024]
Abstract
OBJECTIVES To evaluate the epidemiologic, clinical, and economic value of an annual nursing home (NH) COVID-19 vaccine campaign and the impact of when vaccination starts. DESIGN Agent-based model representing a typical NH. SETTING AND PARTICIPANTS NH residents and staff. METHODS We used the model representing an NH with 100 residents, its staff, their interactions, COVID-19 spread, and its health and economic outcomes to evaluate the epidemiologic, clinical, and economic value of varying schedules of annual COVID-19 vaccine campaigns. RESULTS Across a range of scenarios with a 60% vaccine efficacy that wanes starting 4 months after protection onset, vaccination was cost saving or cost-effective when initiated in the late summer or early fall. Annual vaccination averted 102 to 105 COVID-19 cases when 30-day vaccination campaigns began between July and October (varying with vaccination start), decreasing to 97 and 85 cases when starting in November and December, respectively. Starting vaccination between July and December saved $3340 to $4363 and $64,375 to $77,548 from the Centers for Medicare & Medicaid Services and societal perspectives, respectively (varying with vaccination start). Vaccination's value did not change when varying the COVID-19 peak between December and February. The ideal vaccine campaign timing was not affected by reducing COVID-19 levels in the community, or varying transmission probability, preexisting immunity, or COVID-19 severity. However, if vaccine efficacy wanes more quickly (over 1 month), earlier vaccination in July resulted in more cases compared with vaccinating later in October. CONCLUSIONS AND IMPLICATIONS Annual vaccination of NH staff and residents averted the most cases when initiated in the late summer through early fall, at least 2 months before the COVID-19 winter peak but remained cost saving or cost-effective when it starts in the same month as the peak. This supports tethering COVID vaccination to seasonal influenza campaigns (typically in September-October) for providing protection against SARS-CoV-2 winter surges in NHs.
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Affiliation(s)
- Sarah M Bartsch
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Colleen Weatherwax
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | | | - Kevin L Chin
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Marie F Martinez
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Kavya Velmurugan
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Raveena D Singh
- Division of Infectious Diseases, University of California Irvine School of Medicine, Irvine, CA, USA
| | - Danielle C John
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Pandemic Response Institute, New York City, NY, USA
| | - Jessie L Heneghan
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Gabrielle M Gussin
- Division of Infectious Diseases, University of California Irvine School of Medicine, Irvine, CA, USA
| | - Sheryl A Scannell
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Alexandra C Tsintsifas
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Kelly J O'Shea
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Alexis M Dibbs
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Bruce Leff
- Division of Geriatric Medicine, Center for Transformative Geriatric Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Susan S Huang
- Division of Infectious Diseases, University of California Irvine School of Medicine, Irvine, CA, USA
| | - Bruce Y Lee
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Artificial Intelligence, Modeling, and Informatics, for Nutrition Guidance and Systems (AIMINGS) Center, CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA; Pandemic Response Institute, New York City, NY, USA.
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3
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Robinson LA, Eber MR, Hammitt JK. Valuing COVID-19 Morbidity Risk Reductions. JOURNAL OF BENEFIT-COST ANALYSIS 2022; 13:247-268. [PMID: 36090595 PMCID: PMC9455599 DOI: 10.1017/bca.2022.11] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Many economic analyses, including those that address the COVID-19 pandemic, focus on the value of averting deaths and do not include the value of averting nonfatal illnesses. Yet incorporating the value of averting nonfatal cases may change conclusions about the desirability of the policy. While per case values may be small, the number of nonfatal cases is often large, far outstripping the number of fatal cases. The value of averting nonfatal cases is also increasingly important in evaluating COVID-19 policy options as vaccine- and infection-related immunity and treatments reduce the case-fatality rate. Unfortunately, little valuation research is available that explicitly addresses COVID-19 morbidity. We describe and implement an approach for approximating the value of averting nonfatal illnesses or injuries and apply it to COVID-19 in the United States. We estimate gains from averting COVID-19 morbidity of about 0.01 quality-adjusted life year (QALY) per mild case averted, 0.02 QALY per severe case, and 3.15 QALYs per critical case. These gains translate into monetary values of about $5,300 per mild case, $11,000 per severe case, and $1.8 million per critical case. While these estimates are imprecise, they suggest the magnitude of the effects.
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Affiliation(s)
| | - Michael R. Eber
- Harvard T.H. Chan School of Public Health and Harvard Graduate School of Arts and Sciences
| | - James K. Hammitt
- Harvard T.H. Chan School of Public Health and Toulouse School of Economics, Université de Toulouse Capitole
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4
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Calabro' GE, Carini E, Tognetto A, Giacchetta I, Bonanno E, Mariani M, Ricciardi W, de Waure C. The Value(s) of Vaccination: Building the Scientific Evidence According to a Value-Based Healthcare Approach. Front Public Health 2022; 10:786662. [PMID: 35359753 PMCID: PMC8963736 DOI: 10.3389/fpubh.2022.786662] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 01/31/2022] [Indexed: 02/04/2023] Open
Abstract
Objectives To provide a new value-based immunization approach collating the available scientific evidence on the topic. Methods Four value pillars (personal, allocative, technical, and societal) applied to vaccination field were investigated. A systematic literature review was performed querying three database from December 24th, 2010 to May 27th, 2020. It included studies on vaccine-preventable diseases (VPDs) that mentioned the term value in any part and which were conducted in advanced economies. An in-depth analysis was performed on studies addressing value as key element. Results Overall, 107 studies were considered. Approximately half of the studies addressed value as a key element but in most of cases (83.3%) only a single pillar was assessed. Furthermore, the majority of papers addressed the technical value by looking only at classical methods for economic assessment of vaccinations whereas very few dealt with societal and allocative pillars. Conclusions Estimating the vaccinations value is very complex, even though their usefulness is certain. The assessment of the whole value of vaccines and vaccinations is still limited to some domains and should encompass the wider impact on economic growth and societies.
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Affiliation(s)
- Giovanna Elisa Calabro'
- Section of Hygiene, University Department of Life Sciences and Public Health; Catholic University of the Sacred Heart, Rome, Italy
- VIHTALI (Value In Health Technology and Academy for Leadership & Innovation), Spin-Off of Università Cattolica del Sacro Cuore, Rome, Italy
| | - Elettra Carini
- Section of Hygiene, University Department of Life Sciences and Public Health; Catholic University of the Sacred Heart, Rome, Italy
| | | | - Irene Giacchetta
- Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Ester Bonanno
- Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Marco Mariani
- Section of Hygiene, University Department of Life Sciences and Public Health; Catholic University of the Sacred Heart, Rome, Italy
| | - Walter Ricciardi
- Section of Hygiene, University Department of Life Sciences and Public Health; Catholic University of the Sacred Heart, Rome, Italy
| | - Chiara de Waure
- Department of Medicine and Surgery, University of Perugia, Perugia, Italy
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5
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Padula WV, Malaviya S, Reid NM, Cohen BG, Chingcuanco F, Ballreich J, Tierce J, Alexander GC. Economic value of vaccines to address the COVID-19 pandemic: a U.S. cost-effectiveness and budget impact analysis. J Med Econ 2021; 24:1060-1069. [PMID: 34357843 PMCID: PMC9897209 DOI: 10.1080/13696998.2021.1965732] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
AIMS The Novel Coronavirus (COVID-19) has infected over two hundred million worldwide and caused 4.4 million of deaths as of August 2021. Vaccines were quickly developed to address the pandemic. We sought to analyze the cost-effectiveness and budget impact of a non-specified vaccine for COVID-19. MATERIALS AND METHODS We constructed a Markov model of COVID-19 infections using a susceptible-exposed-infected-recovered structure over a 1-year time horizon from a U.S. healthcare sector perspective. The model consisted of two arms: do nothing and COVID-19 vaccine. Hospitalization and mortality rates were calibrated to U.S. COVID-19 reports as of November 2020. We performed economic calculations of costs in 2020 U.S. dollars and effectiveness in units of quality-adjusted life years (QALYs) to measure the budget impact and incremental cost-effectiveness at a $100,000/QALY threshold. RESULTS Vaccines have a high probability of reducing healthcare costs and increasing QALYs compared to doing nothing. Simulations showed reductions in hospital days and mortality by more than 50%. Even though this represents a major U.S. investment, the budget impacts of these technologies could save program costs by up to 60% or more if uptake is high. LIMITATIONS The economic evaluation draws on the reported values of the clinical benefits of COVID-19 vaccines, although we do not currently have long-term conclusive data about COVID-19 vaccine efficacies. CONCLUSIONS Spending on vaccines to mitigate COVID-19 infections offer high-value potential that society should consider. Unusually high uptake in vaccines in a short amount of time could result in unprecedented budget impacts to government and commercial payers. Governments should focus on expanding health system infrastructure and subsidizing payer coverage to deliver these vaccines efficiently.
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Affiliation(s)
- William V Padula
- Department of Pharmaceutical & Health Economics, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
- The Leonard D. Schaeffer Center for Health Policy & Economics, University of Southern California, Los Angeles, CA, USA
- Department of Acute & Chronic Care, Johns Hopkins School of Nursing, Baltimore, MD, USA
- Monument Analytics, Baltimore, MD, USA
| | - Shreena Malaviya
- Monument Analytics, Baltimore, MD, USA
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | | | | | - Jeromie Ballreich
- Monument Analytics, Baltimore, MD, USA
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jonothan Tierce
- Monument Analytics, Baltimore, MD, USA
- Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - G Caleb Alexander
- Monument Analytics, Baltimore, MD, USA
- Center for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of General Internal Medicine, Johns Hopkins Medicine, Baltimore, MD, USA
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6
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Bartsch SM, Taitel MS, DePasse JV, Cox SN, Smith-Ray RL, Wedlock P, Singh TG, Carr S, Siegmund SS, Lee BY. Epidemiologic and economic impact of pharmacies as vaccination locations during an influenza epidemic. Vaccine 2018; 36:7054-7063. [PMID: 30340884 PMCID: PMC6279616 DOI: 10.1016/j.vaccine.2018.09.040] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Revised: 09/14/2018] [Accepted: 09/18/2018] [Indexed: 11/24/2022]
Abstract
Introduction: During an influenza epidemic, where early vaccination is crucial, pharmacies may be a resource to increase vaccine distribution reach and capacity. Methods: We utilized an agent-based model of the US and a clinical and economics outcomes model to simulate the impact of different influenza epidemics and the impact of utilizing pharmacies in addition to traditional (hospitals, clinic/physician offices, and urgent care centers) locations for vaccination for the year 2017. Results: For an epidemic with a reproductive rate (R0) of 1.30, adding pharmacies with typical business hours averted 11.9 million symptomatic influenza cases, 23,577 to 94,307 deaths, $1.0 billion in direct (vaccine administration and healthcare) costs, $4.2–44.4 billion in productivity losses, and $5.2–45.3 billion in overall costs (varying with mortality rate). Increasing the epidemic severity (R0 of 1.63), averted 16.0 million symptomatic influenza cases, 35,407 to 141,625 deaths, $1.9 billion in direct costs, $6.0–65.5 billion in productivity losses, and $7.8–67.3 billion in overall costs (varying with mortality rate). Extending pharmacy hours averted up to 16.5 million symptomatic influenza cases, 145,278 deaths, $1.9 billion direct costs, $4.1 billion in productivity loss, and $69.5 billion in overall costs. Adding pharmacies resulted in a cost-benefit of $4.1 to $11.5 billion, varying epidemic severity, mortality rate, pharmacy hours, location vaccination rate, and delay in the availability of the vaccine. Conclusions: Administering vaccines through pharmacies in addition to traditional locations in the event of an epidemic can increase vaccination coverage, mitigating up to 23.7 million symptomatic influenza cases, providing cost-savings up to $2.8 billion to third-party payers and $99.8 billion to society. Pharmacies should be considered as points of dispensing epidemic vaccines in addition to traditional settings as soon as vaccines become available.
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Affiliation(s)
- Sarah M Bartsch
- Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Global Obesity Prevention Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Michael S Taitel
- Walgreens Center for Health & Wellbeing Research, Walgreens Company, Deerfield, IL, United States
| | - Jay V DePasse
- Pittsburgh Super Computing Center (PSC), Carnegie Mellon University, Pittsburgh, PA, United States
| | - Sarah N Cox
- Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Global Obesity Prevention Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Renae L Smith-Ray
- Walgreens Center for Health & Wellbeing Research, Walgreens Company, Deerfield, IL, United States
| | - Patrick Wedlock
- Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Global Obesity Prevention Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Tanya G Singh
- Walgreens Center for Health & Wellbeing Research, Walgreens Company, Deerfield, IL, United States
| | - Susan Carr
- Johns Hopkins Healthcare Solutions, Johns Hopkins University, Baltimore, MD, United States
| | - Sheryl S Siegmund
- Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Global Obesity Prevention Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Bruce Y Lee
- Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States; Global Obesity Prevention Center, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
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7
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Bragazzi NL, Gianfredi V, Villarini M, Rosselli R, Nasr A, Hussein A, Martini M, Behzadifar M. Vaccines Meet Big Data: State-of-the-Art and Future Prospects. From the Classical 3Is ("Isolate-Inactivate-Inject") Vaccinology 1.0 to Vaccinology 3.0, Vaccinomics, and Beyond: A Historical Overview. Front Public Health 2018; 6:62. [PMID: 29556492 PMCID: PMC5845111 DOI: 10.3389/fpubh.2018.00062] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Accepted: 02/16/2018] [Indexed: 12/20/2022] Open
Abstract
Vaccines are public health interventions aimed at preventing infections-related mortality, morbidity, and disability. While vaccines have been successfully designed for those infectious diseases preventable by preexisting neutralizing specific antibodies, for other communicable diseases, additional immunological mechanisms should be elicited to achieve a full protection. “New vaccines” are particularly urgent in the nowadays society, in which economic growth, globalization, and immigration are leading to the emergence/reemergence of old and new infectious agents at the animal–human interface. Conventional vaccinology (the so-called “vaccinology 1.0”) was officially born in 1796 thanks to the contribution of Edward Jenner. Entering the twenty-first century, vaccinology has shifted from a classical discipline in which serendipity and the Pasteurian principle of the three Is (isolate, inactivate, and inject) played a major role to a science, characterized by a rational design and plan (“vaccinology 3.0”). This shift has been possible thanks to Big Data, characterized by different dimensions, such as high volume, velocity, and variety of data. Big Data sources include new cutting-edge, high-throughput technologies, electronic registries, social media, and social networks, among others. The current mini-review aims at exploring the potential roles as well as pitfalls and challenges of Big Data in shaping the future vaccinology, moving toward a tailored and personalized vaccine design and administration.
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Affiliation(s)
- Nicola Luigi Bragazzi
- Department of Health Sciences (DISSAL), School of Public Health, University of Genoa, Genoa, Italy
| | - Vincenza Gianfredi
- Department of Experimental Medicine, Unit of Public Health, School of Specialization in Hygiene and Preventive Medicine, University of Perugia, Perugia, Italy
| | - Milena Villarini
- Unit of Public Health, Department of Pharmaceutical Science, University of Perugia, Perugia, Italy
| | | | - Ahmed Nasr
- Department of Medicine and Surgery, Pathology University Milan Bicocca, San Gerardo Hospital, Monza, Italy
| | - Amr Hussein
- Medical Faculty, University of Parma, Parma, Italy
| | - Mariano Martini
- Section of History of Medicine and Ethics, Department of Health Sciences, University of Genoa, Genoa, Italy
| | - Masoud Behzadifar
- Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran
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8
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Raviotta JM, Smith KJ, DePasse J, Brown ST, Shim E, Nowalk MP, Wateska A, France GS, Zimmerman RK. Cost-effectiveness and public health impact of alternative influenza vaccination strategies in high-risk adults. Vaccine 2017; 35:5708-5713. [PMID: 28890196 DOI: 10.1016/j.vaccine.2017.07.069] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 07/19/2017] [Accepted: 07/21/2017] [Indexed: 11/16/2022]
Abstract
PURPOSE High-dose trivalent inactivated influenza vaccine (HD-IIV3) or recombinant trivalent influenza vaccine (RIV) may increase influenza vaccine effectiveness (VE) in adults with conditions that place them at high risk for influenza complications. This analysis models the public health impact and cost-effectiveness (CE) of these vaccines for 50-64year-olds. METHODS Markov model CE analysis compared 5 strategies in 50-64year-olds: no vaccination; only standard-dose IIV3 offered (SD-IIV3 only), only quadrivalent influenza vaccine offered (SD-IIV4 only); high-risk patients receiving HD-IIV3, others receiving SD-IIV3 (HD-IIV3 & SD-IIV3); and high-risk patients receiving HD-IIV3, others receiving SD-IIV4 (HD-IIV3 & SD-IIV4). In a secondary analysis, RIV replaced HD-IIV3. Parameters were obtained from U.S. databases, the medical literature and extrapolations from VE estimates. Effectiveness was measured as 3%/year discounted quality adjusted life year (QALY) losses avoided. RESULTS The least expensive strategy was SD-IIV3 only, with total costs of $99.84/person. The SD-IIV4 only strategy cost an additional $0.91/person, or $37,700/QALY gained. The HD-IIV3 & SD-IIV4 strategy cost $1.06 more than SD-IIV4 only, or $71,500/QALY gained. No vaccination and HD-IIV3 & SD-IIV3 strategies were dominated. Results were sensitive to influenza incidence, vaccine cost, standard-dose VE in the entire population and high-dose VE in high-risk patients. The CE of RIV for high-risk patients was dependent on as yet unknown parameter values. CONCLUSIONS Based on available data, using high-dose influenza vaccine or RIV in middle-aged, high-risk patients may be an economically favorable vaccination strategy with public health benefits. Clinical trials of these vaccines in this population may be warranted.
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Affiliation(s)
- Jonathan M Raviotta
- Department of Family Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.
| | - Kenneth J Smith
- Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Jay DePasse
- Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Shawn T Brown
- Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Eunha Shim
- Department of Mathematics, Soongsil University, Seoul, South Korea
| | - Mary Patricia Nowalk
- Department of Family Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Angela Wateska
- Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Glenson S France
- Department of Economics, University of Pittsburgh, Greensburg, PA, United States
| | - Richard K Zimmerman
- Department of Family Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
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9
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Cost-effectiveness of inactivated seasonal influenza vaccination in a cohort of Thai children ≤60 months of age. PLoS One 2017; 12:e0183391. [PMID: 28837594 PMCID: PMC5570265 DOI: 10.1371/journal.pone.0183391] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Accepted: 08/03/2017] [Indexed: 12/01/2022] Open
Abstract
Background Vaccination is the best measure to prevent influenza. We conducted a cost-effectiveness evaluation of trivalent inactivated seasonal influenza vaccination, compared to no vaccination, in children ≤60 months of age participating in a prospective cohort study in Bangkok, Thailand. Methods A static decision tree model was constructed to simulate the population of children in the cohort. Proportions of children with laboratory-confirmed influenza were derived from children followed weekly. The societal perspective and one-year analytic horizon were used for each influenza season; the model was repeated for three influenza seasons (2012–2014). Direct and indirect costs associated with influenza illness were collected and summed. Cost of the trivalent inactivated seasonal influenza vaccine (IIV3) including promotion, administration, and supervision cost was added for children who were vaccinated. Quality-adjusted life years (QALY), derived from literature, were used to quantify health outcomes. The incremental cost-effectiveness ratio (ICER) was calculated as the difference in the expected total costs between the vaccinated and unvaccinated groups divided by the difference in QALYs for both groups. Results Compared to no vaccination, IIV3 vaccination among children ≤60 months in our cohort was not cost-effective in the introductory year (2012 season; 24,450 USD/QALY gained), highly cost-effective in the 2013 season (554 USD/QALY gained), and cost-effective in the 2014 season (16,200 USD/QALY gained). Conclusion The cost-effectiveness of IIV3 vaccination among children participating in the cohort study varied by influenza season, with vaccine cost and proportion of high-risk children demonstrating the greatest influence in sensitivity analyses. Vaccinating children against influenza can be economically favorable depending on the maturity of the program, influenza vaccine performance, and target population.
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10
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Lee BY, Alfaro-Murillo JA, Parpia AS, Asti L, Wedlock PT, Hotez PJ, Galvani AP. The potential economic burden of Zika in the continental United States. PLoS Negl Trop Dis 2017; 11:e0005531. [PMID: 28448488 PMCID: PMC5407573 DOI: 10.1371/journal.pntd.0005531] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 03/27/2017] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND As the Zika virus epidemic continues to spread internationally, countries such as the United States must determine how much to invest in prevention, control, and response. Fundamental to these decisions is quantifying the potential economic burden of Zika under different scenarios. METHODOLOGY/PRINCIPLE FINDINGS To inform such decision making, our team developed a computational model to forecast the potential economic burden of Zika across six states in the US (Alabama, Florida, Georgia, Louisiana, Mississippi, and Texas) which are at greatest risk of Zika emergence, under a wide range of attack rates, scenarios and circumstances. In order to accommodate a wide range of possibilities, different scenarios explored the effects of varying the attack rate from 0.01% to 10%. Across the six states, an attack rate of 0.01% is estimated to cost $183.4 million to society ($117.1 million in direct medical costs and $66.3 million in productivity losses), 0.025% would result in $198.6 million ($119.4 million and $79.2 million), 0.10% would result in $274.6 million ($130.8 million and $143.8 million) and 1% would result in $1.2 billion ($268.0 million and $919.2 million). CONCLUSIONS Our model and study show how direct medical costs, Medicaid costs, productivity losses, and total costs to society may vary with different attack rates across the six states and the circumstances at which they may exceed certain thresholds (e.g., Zika prevention and control funding allocations that are being debated by the US government). A Zika attack rate of 0.3% across the six states at greatest risk of Zika infection, would result in total costs that exceed $0.5 billion, an attack rate of 1% would exceed $1 billion, and an attack rate of 2% would exceed $2 billion.
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Affiliation(s)
- Bruce Y. Lee
- Public Health Computational and Operations Research (PHICOR) and Global Obesity Prevention Center (GOPC), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Jorge A. Alfaro-Murillo
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Alyssa S. Parpia
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Lindsey Asti
- Public Health Computational and Operations Research (PHICOR) and Global Obesity Prevention Center (GOPC), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Patrick T. Wedlock
- Public Health Computational and Operations Research (PHICOR) and Global Obesity Prevention Center (GOPC), Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Peter J. Hotez
- Sabin Vaccine Institute and Texas Children’s Hospital Center for Vaccine Development, National School of Tropical Medicine, Baylor College of Medicine, Houston, Texas, United States of America
| | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
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11
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Lee BY, Mueller LE, Tilchin CG. A systems approach to vaccine decision making. Vaccine 2016; 35 Suppl 1:A36-A42. [PMID: 28017430 DOI: 10.1016/j.vaccine.2016.11.033] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Revised: 11/04/2016] [Accepted: 11/05/2016] [Indexed: 12/14/2022]
Abstract
Vaccines reside in a complex multiscale system that includes biological, clinical, behavioral, social, operational, environmental, and economical relationships. Not accounting for these systems when making decisions about vaccines can result in changes that have little effect rather than solutions, lead to unsustainable solutions, miss indirect (e.g., secondary, tertiary, and beyond) effects, cause unintended consequences, and lead to wasted time, effort, and resources. Mathematical and computational modeling can help better understand and address complex systems by representing all or most of the components, relationships, and processes. Such models can serve as "virtual laboratories" to examine how a system operates and test the effects of different changes within the system. Here are ten lessons learned from using computational models to bring more of a systems approach to vaccine decision making: (i) traditional single measure approaches may overlook opportunities; (ii) there is complex interplay among many vaccine, population, and disease characteristics; (iii) accounting for perspective can identify synergies; (iv) the distribution system should not be overlooked; (v) target population choice can have secondary and tertiary effects; (vi) potentially overlooked characteristics can be important; (vii) characteristics of one vaccine can affect other vaccines; (viii) the broader impact of vaccines is complex; (ix) vaccine administration extends beyond the provider level; and (x) the value of vaccines is dynamic.
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Affiliation(s)
- Bruce Y Lee
- Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
| | - Leslie E Mueller
- Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Carla G Tilchin
- Public Health Computational and Operations Research (PHICOR), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
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12
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Chan YK, Wong RY, Ip M, Lee NL, You JH. Economic outcomes of influenza in hospitalized elderly with and without ICU admission. Antivir Ther 2016; 22:173-177. [PMID: 27740538 DOI: 10.3851/imp3102] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/10/2016] [Indexed: 10/20/2022]
Abstract
BACKGROUND To describe direct medical costs of influenza in hospitalized elderly, with and without intensive care unit (ICU) admission, during the 2014-2015 season in Hong Kong. METHODS A retrospective study was conducted in 110 inpatients aged ≥65 years with laboratory-confirmed influenza treated by antiviral therapy during season 2014-2015 in a tertiary hospital. Resource utilization of influenza-related diagnostic and laboratory tests, medications for influenza treatment, usage of general medical ward and ICU during the influenza-related length of hospital stay (IR-LOS) were collected. RESULTS There were 18 (16.4%) and 92 (83.4%) cases with and without ICU admission, respectively. The difference in influenza-related mortality rates between patients with (11.1%) and without ICU admission (2.2%) was not statistically significant (P=0.064). Patients with ICU admission reported longer IR-LOS (12.7 ±6.0 days versus 5.5 ±2.7 days; P<0.001) and higher direct costs (36,588 USD ±21,482 versus 5,773 USD ±2,017; P<0.001; 1 USD=7.8 HKD). Male gender (OR=14.50; 95% CI 1.68, 125.07) and respiratory complications (OR=9.61; 95% CI 1.90, 48.50) were positive predictors of ICU admission. Age ≥70 years (OR=0.09; 95% CI 0.02, 0.46) and antiviral therapy initiation within 7 days (OR=0.05; 95% CI 0.003, 0.79) were negative predictors of ICU admission. Influenza B was a positive predictor of high-cost hospitalization in non-ICU survivors (OR=7.33; 95% CI 1.24, 43.29). No predictor of mortality was identified. CONCLUSIONS Hospitalization cost in elderly for seasonal influenza was substantial in Hong Kong. The cost in patients with ICU admission was significantly higher than those without ICU care. Respiratory complications and male gender predicted ICU admission. Influenza B infection predicted high-cost hospitalization in non-ICU survivors.
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Affiliation(s)
- Yik-Kei Chan
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Rity Yk Wong
- Divison of Infectious Diseases, Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Margaret Ip
- Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Nelson Ls Lee
- Divison of Infectious Diseases, Department of Medicine & Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Joyce Hs You
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
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Raviotta JM, Smith KJ, DePasse J, Brown ST, Shim E, Nowalk MP, Zimmerman RK. Cost-Effectiveness and Public Health Effect of Influenza Vaccine Strategies for U.S. Elderly Adults. J Am Geriatr Soc 2016; 64:2126-2131. [PMID: 27709600 DOI: 10.1111/jgs.14323] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
OBJECTIVES To compare the cost-effectiveness of four influenza vaccines available in the United States for persons aged 65 and older: trivalent inactivated influenza vaccine (IIV3), quadrivalent inactivated influenza vaccine (IIV4), a more-expensive high-dose IIV3, and a newly approved adjuvanted IIV3. DESIGN Cost-effectiveness analysis using a Markov model and sensitivity analyses. SETTING A hypothetical influenza vaccination season modeled according to possible U.S. influenza vaccination policies. PARTICIPANTS Hypothetical cohort of individuals aged 65 and older in the United States. MEASUREMENTS Cost-effectiveness and public health benefits of available influenza vaccination strategies in U.S. elderly adults. RESULTS IIV3 cost $3,690 per quality-adjusted life year (QALY) gained, IIV4 cost $20,939 more than IIV3 per QALY gained, and high-dose IIV3 cost $31,214 more per QALY than IIV4. The model projected 83,775 fewer influenza cases and 980 fewer deaths with high-dose IIV3 than with the next most-effective vaccine: IIV4. In a probabilistic sensitivity analysis, high-dose IIV3 was the favored strategy if willingness to pay is $25,000 or more per QALY gained. Adjuvanted IIV3 cost-effectiveness depends on its price and effectiveness (neither yet determined in the United States) but could be favored if its relative effectiveness is 15% greater than that of IIV3. CONCLUSION From economic and public health standpoints, high-dose IIV3 for adults aged 65 years and older is likely to be favored over the other vaccines, based on currently available data. The cost-effectiveness of adjuvanted IIV3 should be reviewed after its effectiveness has been compared with that of other vaccines and its U.S. price is established.
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Affiliation(s)
| | | | - Jay DePasse
- Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Shawn T Brown
- Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, Pennsylvania
| | - Eunha Shim
- Department of Mathematics, Soongsil University, Seoul, South Korea
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14
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Buchan SA, Kwong JC. Trends in influenza vaccine coverage and vaccine hesitancy in Canada, 2006/07 to 2013/14: results from cross-sectional survey data. CMAJ Open 2016; 4:E455-E462. [PMID: 27975047 PMCID: PMC5143025 DOI: 10.9778/cmajo.20160050] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Past studies have reported influenza vaccination coverage below national targets, but up-to-date estimates are needed to understand trends and to identify areas for intervention. The objective of this study was to describe recent trends in influenza vaccination in Canada, timing of uptake and reasons for not receiving the vaccine. METHODS We pooled data from the 2007 to 2014 cycles of the Canadian Community Health Survey. Using bootstrapped survey weights, we examined influenza vaccine coverage by various groups, including by age and by presence of chronic medical conditions. RESULTS The overall sample included 481 526 respondents. Across all survey cycles combined, 29% of respondents reported receiving seasonal influenza vaccination in the past 12 months. Coverage levels were fairly consistent during the study period, but varied by province or territory. Vaccination coverage decreased over time among those aged 65 years and older. Among those who received a vaccination, it was most common to do so in October or November. Among those not vaccinated, the most frequently cited reason was believing it was unnecessary. INTERPRETATION Influenza vaccination coverage continues to fall below national targets, with substantial declines seen among those aged 65 years and older, a group for which vaccination is particularly important. More intensive efforts are needed to improve coverage in Canada, particularly for high-risk groups.
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Affiliation(s)
- Sarah A Buchan
- Dalla Lana School of Public Health (Buchan, Kwong), University of Toronto; Institute for Clinical Evaluative Sciences (Kwong); Department of Family and Community Medicine (Kwong), University of Toronto, Toronto, Ont
| | - Jeffrey C Kwong
- Dalla Lana School of Public Health (Buchan, Kwong), University of Toronto; Institute for Clinical Evaluative Sciences (Kwong); Department of Family and Community Medicine (Kwong), University of Toronto, Toronto, Ont
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15
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Leung MK, You JHS. Cost-effectiveness of an influenza vaccination program offering intramuscular and intradermal vaccines versus intramuscular vaccine alone for elderly. Vaccine 2016; 34:2469-76. [PMID: 27079928 DOI: 10.1016/j.vaccine.2016.04.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Revised: 03/19/2016] [Accepted: 04/04/2016] [Indexed: 12/22/2022]
Abstract
BACKGROUND Intradermal (ID) injection is an alternative route for influenza vaccine administration in elderly with potential improvement of vaccine coverage. This study aimed to investigate the cost-effectiveness of an influenza vaccination program offering ID vaccine to elderly who had declined intramuscular (IM) vaccine from the perspective of Hong Kong public healthcare provider. METHODS A decision analytic model was used to simulate outcomes of two programs: IM vaccine alone (IM program), and IM or ID vaccine (IM/ID program) in a hypothetic cohort of elderly aged 65 years. Outcome measures included influenza-related direct medical cost, infection rate, mortality rate, quality-adjusted life years (QALYs) loss, and incremental cost per QALY saved (ICER). Model inputs were derived from literature. Sensitivity analyses evaluated the impact of uncertainty of model variables. RESULTS In base-case analysis, the IM/ID program was more costly (USD52.82 versus USD47.59 per individual to whom vaccine was offered) with lower influenza infection rate (8.71% versus 9.65%), mortality rate (0.021% versus 0.024%) and QALYs loss (0.00336 versus 0.00372) than the IM program. ICER of IM/ID program was USD14,528 per QALY saved. One-way sensitivity analysis found ICER of IM/ID program to exceed willingness-to-pay threshold (USD39,933) when probability of influenza infection in unvaccinated elderly decreased from 10.6% to 5.4%. In 10,000 Monte Carlo simulations of elderly populations of Hong Kong, the IM/ID program was the preferred option in 94.7% of time. CONCLUSIONS An influenza vaccination program offering ID vaccine to elderly who had declined IM vaccine appears to be a highly cost-effective option.
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Affiliation(s)
- Man-Kit Leung
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
| | - Joyce H S You
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
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