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Bartsch SM, Wedlock PT, O’Shea KJ, Cox SN, Strych U, Nuzzo JB, Ferguson MC, Bottazzi ME, Siegmund SS, Hotez PJ, Lee BY. Lives and Costs Saved by Expanding and Expediting Coronavirus Disease 2019 Vaccination. J Infect Dis 2021; 224:938-948. [PMID: 33954775 PMCID: PMC8136017 DOI: 10.1093/infdis/jiab233] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 04/28/2021] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND With multiple coronavirus disease 2019 (COVID-19) vaccines available, understanding the epidemiologic, clinical, and economic value of increasing coverage levels and expediting vaccination is important. METHODS We developed a computational model (transmission and age-stratified clinical and economics outcome model) representing the United States population, COVID-19 coronavirus spread (February 2020-December 2022), and vaccination to determine the impact of increasing coverage and expediting time to achieve coverage. RESULTS When achieving a given vaccination coverage in 270 days (70% vaccine efficacy), every 1% increase in coverage can avert an average of 876 800 (217 000-2 398 000) cases, varying with the number of people already vaccinated. For example, each 1% increase between 40% and 50% coverage can prevent 1.5 million cases, 56 240 hospitalizations, and 6660 deaths; gain 77 590 quality-adjusted life-years (QALYs); and save $602.8 million in direct medical costs and $1.3 billion in productivity losses. Expediting to 180 days could save an additional 5.8 million cases, 215 790 hospitalizations, 26 370 deaths, 206 520 QALYs, $3.5 billion in direct medical costs, and $4.3 billion in productivity losses. CONCLUSIONS Our study quantifies the potential value of decreasing vaccine hesitancy and increasing vaccination coverage and how this value may decrease with the time it takes to achieve coverage, emphasizing the need to reach high coverage levels as soon as possible, especially before the fall/winter.
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Affiliation(s)
- Sarah M Bartsch
- Public Health Informatics, Computational, and Operations Research, Graduate School of Public Health and Health Policy, City University of New York, New York City, New York, USA
| | - Patrick T Wedlock
- Public Health Informatics, Computational, and Operations Research, Graduate School of Public Health and Health Policy, City University of New York, New York City, New York, USA
| | - Kelly J O’Shea
- Public Health Informatics, Computational, and Operations Research, Graduate School of Public Health and Health Policy, City University of New York, New York City, New York, USA
| | - Sarah N Cox
- Public Health Informatics, Computational, and Operations Research, Graduate School of Public Health and Health Policy, City University of New York, New York City, New York, USA
| | - Ulrich Strych
- National School of Tropical Medicine and Departments of Pediatrics and Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA
| | - Jennifer B Nuzzo
- Johns Hopkins Center for Health Security, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Marie C Ferguson
- Public Health Informatics, Computational, and Operations Research, Graduate School of Public Health and Health Policy, City University of New York, New York City, New York, USA
| | - Maria Elena Bottazzi
- National School of Tropical Medicine and Departments of Pediatrics and Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA
| | - Sheryl S Siegmund
- Public Health Informatics, Computational, and Operations Research, Graduate School of Public Health and Health Policy, City University of New York, New York City, New York, USA
| | - Peter J Hotez
- National School of Tropical Medicine and Departments of Pediatrics and Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA
| | - Bruce Y Lee
- Public Health Informatics, Computational, and Operations Research, Graduate School of Public Health and Health Policy, City University of New York, New York City, New York, USA
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Bartsch SM, O'Shea KJ, Wedlock PT, Strych U, Ferguson MC, Bottazzi ME, Randall SL, Siegmund SS, Cox SN, Hotez PJ, Lee BY. The Benefits of Vaccinating With the First Available COVID-19 Coronavirus Vaccine. Am J Prev Med 2021; 60:605-613. [PMID: 33632650 PMCID: PMC7817395 DOI: 10.1016/j.amepre.2021.01.001] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 01/05/2021] [Accepted: 01/07/2021] [Indexed: 01/27/2023]
Abstract
INTRODUCTION During a pandemic, there are many situations in which the first available vaccines may not have as high effectiveness as vaccines that are still under development or vaccines that are not yet ready for distribution, raising the question of whether it is better to go with what is available now or wait. METHODS In 2020, the team developed a computational model that represents the U.S. population, COVID-19 coronavirus spread, and vaccines with different possible efficacies (to prevent infection or to reduce severe disease) and vaccination timings to estimate the clinical and economic value of vaccination. RESULTS Except for a limited number of situations, mainly early on in a pandemic and for a vaccine that prevents infection, when an initial vaccine is available, waiting for a vaccine with a higher efficacy results in additional hospitalizations and costs over the course of the pandemic. For example, if a vaccine with a 50% efficacy in preventing infection becomes available when 10% of the population has already been infected, waiting until 40% of the population are infected for a vaccine with 80% efficacy in preventing infection results in 15.6 million additional cases and 1.5 million additional hospitalizations, costing $20.6 billion more in direct medical costs and $12.4 billion more in productivity losses. CONCLUSIONS This study shows that there are relatively few situations in which it is worth foregoing the first COVID-19 vaccine available in favor of a vaccine that becomes available later on in the pandemic even if the latter vaccine has a substantially higher efficacy.
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Affiliation(s)
- Sarah M Bartsch
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health & Health Policy, New York City, New York
| | - Kelly J O'Shea
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health & Health Policy, New York City, New York
| | - Patrick T Wedlock
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health & Health Policy, New York City, New York
| | - Ulrich Strych
- National School of Tropical Medicine, Baylor College of Medicine, Houston, Texas; Department of Pediatrics, Baylor College of Medicine, Houston, Texas; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas
| | - Marie C Ferguson
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health & Health Policy, New York City, New York
| | - Maria Elena Bottazzi
- National School of Tropical Medicine, Baylor College of Medicine, Houston, Texas; Department of Pediatrics, Baylor College of Medicine, Houston, Texas; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas
| | - Samuel L Randall
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health & Health Policy, New York City, New York
| | - Sheryl S Siegmund
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health & Health Policy, New York City, New York
| | - Sarah N Cox
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health & Health Policy, New York City, New York
| | - Peter J Hotez
- National School of Tropical Medicine, Baylor College of Medicine, Houston, Texas; Department of Pediatrics, Baylor College of Medicine, Houston, Texas; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas
| | - Bruce Y Lee
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health & Health Policy, New York City, New York.
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Bartsch SM, O'Shea KJ, Wedlock PT, Ferguson MC, Siegmund SS, Lee BY. Potential Clinical and Economic Value of Norovirus Vaccination in the Community Setting. Am J Prev Med 2021; 60:360-368. [PMID: 33516583 PMCID: PMC8415104 DOI: 10.1016/j.amepre.2020.10.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 09/04/2020] [Accepted: 10/30/2020] [Indexed: 12/20/2022]
Abstract
INTRODUCTION With norovirus vaccine candidates currently under development, now is the time to identify the vaccine characteristics and implementation thresholds at which vaccination becomes cost effective and cost saving in a community setting. METHODS In 2020, a norovirus transmission, clinical, and economics computational simulation model representing different U.S. population segments was developed to simulate the spread of norovirus and the potential impact of vaccinating children aged <5 years and older adults (aged ≥65 years). RESULTS Compared with no vaccination, vaccinating preschool-aged children averted 8%-72% of symptomatic norovirus cases in a community, whereas vaccinating older adults averted 2%-29% of symptomatic cases (varying with vaccine efficacy [25%-75%] and vaccination coverage [10%-80%]). Vaccination with a 25% vaccine efficacy was cost effective (incremental cost-effectiveness ratio ≤$50,000 per quality-adjusted life year) when vaccination cost ≤$445 and cost saving at ≤$370 when vaccinating preschool-aged children and ≤$42 and ≤$30, respectively, when vaccinating older adults. With a 50% vaccine efficacy, vaccination was cost effective when it cost ≤$1,190 and cost saving at ≤$930 when vaccinating preschool-aged children and ≤$110 and ≤$64, respectively, when vaccinating older adults. These cost thresholds (cost effective and cost saving, respectively) further increased with a 75% vaccine efficacy to ≤$1,600 and ≤$1,300 for preschool-aged children and ≤$165 and ≤$100 for older adults. CONCLUSIONS This study outlines thresholds at which a norovirus vaccine would be cost effective and cost saving in the community when vaccinating children aged <5 years and older adults. Establishing these thresholds can help provide decision makers with targets to consider when developing and implementing a norovirus vaccine.
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Affiliation(s)
- Sarah M Bartsch
- Public Health Informatics, Computational, and Operations Research (PHICOR), Graduate School of Public Health and Health Policy, City University of New York, New York City, New York
| | - Kelly J O'Shea
- Public Health Informatics, Computational, and Operations Research (PHICOR), Graduate School of Public Health and Health Policy, City University of New York, New York City, New York
| | - Patrick T Wedlock
- Public Health Informatics, Computational, and Operations Research (PHICOR), Graduate School of Public Health and Health Policy, City University of New York, New York City, New York
| | - Marie C Ferguson
- Public Health Informatics, Computational, and Operations Research (PHICOR), Graduate School of Public Health and Health Policy, City University of New York, New York City, New York
| | - Sheryl S Siegmund
- Public Health Informatics, Computational, and Operations Research (PHICOR), Graduate School of Public Health and Health Policy, City University of New York, New York City, New York
| | - Bruce Y Lee
- Public Health Informatics, Computational, and Operations Research (PHICOR), Graduate School of Public Health and Health Policy, City University of New York, New York City, New York.
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Lee BY, Bartsch SM, Ferguson MC, Wedlock PT, O’Shea KJ, Siegmund SS, Cox SN, McKinnell JA. The value of decreasing the duration of the infectious period of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. PLoS Comput Biol 2021; 17:e1008470. [PMID: 33411742 PMCID: PMC7790237 DOI: 10.1371/journal.pcbi.1008470] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 10/27/2020] [Indexed: 01/08/2023] Open
Abstract
Finding medications or vaccines that may decrease the infectious period of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could potentially reduce transmission in the broader population. We developed a computational model of the U.S. simulating the spread of SARS-CoV-2 and the potential clinical and economic impact of reducing the infectious period duration. Simulation experiments found that reducing the average infectious period duration could avert a median of 442,852 [treating 25% of symptomatic cases, reducing by 0.5 days, reproductive number (R0) 3.5, and starting treatment when 15% of the population has been exposed] to 44.4 million SARS-CoV-2 cases (treating 75% of all infected cases, reducing by 3.5 days, R0 2.0). With R0 2.5, reducing the average infectious period duration by 0.5 days for 25% of symptomatic cases averted 1.4 million cases and 99,398 hospitalizations; increasing to 75% of symptomatic cases averted 2.8 million cases. At $500/person, treating 25% of symptomatic cases saved $209.5 billion (societal perspective). Further reducing the average infectious period duration by 3.5 days averted 7.4 million cases (treating 25% of symptomatic cases). Expanding treatment to 75% of all infected cases, including asymptomatic infections (R0 2.5), averted 35.9 million cases and 4 million hospitalizations, saving $48.8 billion (societal perspective and starting treatment after 5% of the population has been exposed). Our study quantifies the potential effects of reducing the SARS-CoV-2 infectious period duration. Finding medications or vaccines that may decrease the infectious period of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could potentially reduce transmission in the broader population. We developed a computational model of the U.S. simulating the spread of SARS-CoV-2 and the potential clinical and economic impact of reducing the infectious period duration. Our simulation experiments found that reducing the average infectious period duration could avert a median of 442,852 to 44.4 million SARS-CoV-2 cases, varying the proportion of cases treated, average duration of the infectious period, and the reproductive rate. At $500/person, treating 25% of symptomatic cases saved $209.5 billion (societal perspective, R0 2.5). Further reducing the average infectious period duration by 3.5 days averted 7.4 million cases (treating 25% of symptomatic cases). Expanding treatment to 75% of all infected cases, including asymptomatic infections (R0 2.5), averted 35.9 million cases and 4 million hospitalizations, saving $48.8 billion (societal perspective and starting treatment after 5% of the population has been exposed). Our study suggests that finding ways to reduce the infectious period of SARS-CoV-2 could help decrease its spread and impact.
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Affiliation(s)
- Bruce Y. Lee
- Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York Graduate School of Public Health and Health Policy, New York City, New York, United States of America
- * E-mail:
| | - Sarah M. Bartsch
- Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York Graduate School of Public Health and Health Policy, New York City, New York, United States of America
| | - Marie C. Ferguson
- Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York Graduate School of Public Health and Health Policy, New York City, New York, United States of America
| | - Patrick T. Wedlock
- Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York Graduate School of Public Health and Health Policy, New York City, New York, United States of America
| | - Kelly J. O’Shea
- Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York Graduate School of Public Health and Health Policy, New York City, New York, United States of America
| | - Sheryl S. Siegmund
- Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York Graduate School of Public Health and Health Policy, New York City, New York, United States of America
| | - Sarah N. Cox
- Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York Graduate School of Public Health and Health Policy, New York City, New York, United States of America
| | - James A. McKinnell
- Infectious Disease Clinical Outcomes Research Unit (ID-CORE), Lundquist Institute, Harbor-UCLA Medical Center, Torrance, California, United States of America
- Torrance Memorial Medical Center, Torrance, California, United States of America
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Ferguson MC, O'Shea KJ, Hammer LD, Hertenstein DL, Syed RM, Nyathi S, Gonzales MS, Domino M, S Siegmund S, Randall S, Wedlock P, Adam A, Lee BY. Can following formula-feeding recommendations still result in infants who are overweight or have obesity? Pediatr Res 2020; 88:661-667. [PMID: 32179869 PMCID: PMC7492437 DOI: 10.1038/s41390-020-0844-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 02/04/2020] [Accepted: 02/08/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Studies show that by 3 months, over half of US infants receive formula, and guidelines play a key role in formula feeding. The question then is, what might happen if caregivers follow guidelines and, more specifically, are there situations where following guidelines can result in infants who are overweight/have obesity? METHODS We used our "Virtual Infant" agent-based model representing infant-caregiver pairs that allowed caregivers to feed infants each day according to guidelines put forth by Johns Hopkins Medicine (JHM), Children's Hospital of Philadelphia (CHOP), Children's Hospital of the King's Daughters (CHKD), and Women, Infants, and Children (WIC). The model simulated the resulting development of the infants from birth to 6 months. The two sets of guidelines vary in their recommendations, and do not provide studies that support amounts at given ages. RESULTS Simulations identified several scenarios where caregivers followed JHM/CHOP/CHKD and WIC guidelines, but infants still became overweight/with obesity by 6 months. For JHM/CHOP/CHKD guidelines, this occurred even when caregivers adjusted feeding based on infant's weight. For WIC guidelines, when caregivers adjusted formula amounts, infants maintained healthy weight. CONCLUSIONS WIC guidelines may be a good starting point for caregivers who adjust as their infant grows, but the minimum amounts for JHM/CHKD/CHOP recommendations may be too high. IMPACT Our virtual infant simulation study answers the question: can caregivers follow current formula-feeding guidelines and still end up with an infant who is overweight or has obesity? Our study identified several situations in which unhealthy weight gain and/or weight loss could result from following established formula-feeding recommendations. Our study also suggests that the minimum recommended amount of daily formula feeding should be lower for JHM/CHOP/CHKD guidelines to give caregivers more flexibility in adjusting daily feeding levels in response to infant weight. WIC guidelines may be a good starting point for caregivers who adjust as their infant grows. In order to understand how to adjust guidelines, we can use computational simulation models, which serve as "virtual laboratories" to help overcome the logistical and ethical issues of clinical trials.
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Affiliation(s)
- Marie C Ferguson
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | - Kelly J O'Shea
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | | | - Daniel L Hertenstein
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | - Rafay M Syed
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | - Sindiso Nyathi
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | - Mario Solano Gonzales
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | - Molly Domino
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | - Sheryl S Siegmund
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | - Samuel Randall
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | - Patrick Wedlock
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | - Atif Adam
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA
| | - Bruce Y Lee
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York (previously at Johns Hopkins University, Baltimore, MD), New York, NY, USA.
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Bartsch SM, O'Shea KJ, Ferguson MC, Bottazzi ME, Wedlock PT, Strych U, McKinnell JA, Siegmund SS, Cox SN, Hotez PJ, Lee BY. Vaccine Efficacy Needed for a COVID-19 Coronavirus Vaccine to Prevent or Stop an Epidemic as the Sole Intervention. Am J Prev Med 2020; 59:493-503. [PMID: 32778354 PMCID: PMC7361120 DOI: 10.1016/j.amepre.2020.06.011] [Citation(s) in RCA: 183] [Impact Index Per Article: 45.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 06/26/2020] [Accepted: 06/30/2020] [Indexed: 10/28/2022]
Abstract
INTRODUCTION Given the continuing COVID-19 pandemic and much of the U.S. implementing social distancing owing to the lack of alternatives, there has been a push to develop a vaccine to eliminate the need for social distancing. METHODS In 2020, the team developed a computational model of the U.S. simulating the spread of COVID-19 coronavirus and vaccination. RESULTS Simulation experiments revealed that to prevent an epidemic (reduce the peak by >99%), the vaccine efficacy has to be at least 60% when vaccination coverage is 100% (reproduction number=2.5-3.5). This vaccine efficacy threshold rises to 70% when coverage drops to 75% and up to 80% when coverage drops to 60% when reproduction number is 2.5, rising to 80% when coverage drops to 75% when the reproduction number is 3.5. To extinguish an ongoing epidemic, the vaccine efficacy has to be at least 60% when coverage is 100% and at least 80% when coverage drops to 75% to reduce the peak by 85%-86%, 61%-62%, and 32% when vaccination occurs after 5%, 15%, and 30% of the population, respectively, have already been exposed to COVID-19 coronavirus. A vaccine with an efficacy between 60% and 80% could still obviate the need for other measures under certain circumstances such as much higher, and in some cases, potentially unachievable, vaccination coverages. CONCLUSIONS This study found that the vaccine has to have an efficacy of at least 70% to prevent an epidemic and of at least 80% to largely extinguish an epidemic without any other measures (e.g., social distancing).
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Affiliation(s)
- Sarah M Bartsch
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York
| | - Kelly J O'Shea
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York
| | - Marie C Ferguson
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York
| | - Maria Elena Bottazzi
- National School of Tropical Medicine, Baylor College of Medicine, Houston, Texas; Department of Pediatrics, Baylor College of Medicine, Houston, Texas; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas
| | - Patrick T Wedlock
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York
| | - Ulrich Strych
- National School of Tropical Medicine, Baylor College of Medicine, Houston, Texas; Department of Pediatrics, Baylor College of Medicine, Houston, Texas; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas
| | - James A McKinnell
- Infectious Disease Clinical Outcomes Research Unit (ID-CORE), Lundquist Institute, Harbor-UCLA Medical Center, Torrance, California; Torrance Memorial Medical Center, Torrance, California
| | - Sheryl S Siegmund
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York
| | - Sarah N Cox
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York
| | - Peter J Hotez
- National School of Tropical Medicine, Baylor College of Medicine, Houston, Texas; Department of Pediatrics, Baylor College of Medicine, Houston, Texas; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas
| | - Bruce Y Lee
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health and Health Policy, New York City, New York.
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Bartsch SM, Mitgang EA, Geller G, Cox SN, O'Shea KJ, Boyce A, Siegmund SS, Kahn J, Lee BY. What If the Influenza Vaccine Did Not Offer Such Variable Protection? J Infect Dis 2020; 222:1138-1144. [PMID: 32386323 DOI: 10.1093/infdis/jiaa240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 05/06/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The protection that an influenza vaccine offers can vary significantly from person to person due to differences in immune systems, body types, and other factors. The question, then, is what is the value of efforts to reduce this variability such as making vaccines more personalized and tailored to individuals. METHODS We developed a compartment model of the United States to simulate different influenza seasons and the impact of reducing the variability in responses to the influenza vaccine across the population. RESULTS Going from a vaccine that varied in efficacy (0-30%) to one that had a uniform 30% efficacy for everyone averted 16.0-31.2 million cases, $1.9-$3.6 billion in direct medical costs, and $16.1-$42.7 billion in productivity losses. Going from 0-50% in efficacy to just 50% for everyone averted 27.7-38.6 million cases, $3.3-$4.6 billion in direct medical costs, and $28.8-$57.4 billion in productivity losses. Going from 0-70% to 70% averted 33.6-54.1 million cases, $4.0-$6.5 billion in direct medical costs, and $44.8-$64.7 billion in productivity losses. CONCLUSIONS This study quantifies for policy makers, funders, and vaccine developers and manufacturers the potential impact of efforts to reduce variability in the protection that influenza vaccines offer (eg, developing vaccines that are more personalized to different individual factors).
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Affiliation(s)
- Sarah M Bartsch
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health & Health Policy, New York City, New York, USA
| | - Elizabeth A Mitgang
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health & Health Policy, New York City, New York, USA
| | - Gail Geller
- Johns Hopkins Berman Institute of Bioethics, Baltimore, Maryland, USA
| | - Sarah N Cox
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health & Health Policy, New York City, New York, USA
| | - Kelly J O'Shea
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health & Health Policy, New York City, New York, USA
| | - Angie Boyce
- Johns Hopkins Berman Institute of Bioethics, Baltimore, Maryland, USA
| | - Sheryl S Siegmund
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health & Health Policy, New York City, New York, USA
| | - Jeffrey Kahn
- Johns Hopkins Berman Institute of Bioethics, Baltimore, Maryland, USA
| | - Bruce Y Lee
- Public Health Informatics, Computational, and Operations Research, CUNY Graduate School of Public Health & Health Policy, New York City, New York, USA
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Ferguson MC, Morgan MJ, O’Shea KJ, Winch L, Siegmund SS, Gonzales MS, Randall S, Hertenstein D, Montague V, Woodberry A, Cassatt T, Lee BY. Using Simulation Modeling to Guide the Design of the Girl Scouts Fierce & Fit Program. Obesity (Silver Spring) 2020; 28:1317-1324. [PMID: 32378341 PMCID: PMC7311310 DOI: 10.1002/oby.22827] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 03/07/2020] [Accepted: 03/28/2020] [Indexed: 01/29/2023]
Abstract
OBJECTIVE The study aim was to help the Girl Scouts of Central Maryland evaluate, quantify, and potentially modify the Girl Scouts Fierce & Fit program. METHODS From 2018 to 2019, our Public Health Informatics, Computational, and Operations Research team developed a computational simulation model representing the 250 adolescent girls participating in the Fierce & Fit program and how their diets and physical activity affected their BMI and subsequent outcomes, including costs. RESULTS Changing the Fierce & Fit program from a 6-week program meeting twice a week, with 5 minutes of physical activity each session, to a 12-week program meeting twice a week with 30 minutes of physical activity saved an additional $84,828 ($80,130-$89,526) in lifetime direct medical costs, $81,365 ($76,528-$86,184) in lifetime productivity losses, and 7.85 (7.38-8.31) quality-adjusted life-years. The cost-benefit of implementing this program was $95,943. Based on these results, the Girl Scouts of Central Maryland then implemented these changes in the program. CONCLUSIONS This is an example of using computational modeling to help evaluate and revise the design of a program aimed at increasing physical activity among girls.
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Affiliation(s)
- Marie C. Ferguson
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York Graduate School of Public Health and Health Policy, New York, New York, (formerly at Johns Hopkins University, Baltimore, MD)
| | - Matthew J. Morgan
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York Graduate School of Public Health and Health Policy, New York, New York, (formerly at Johns Hopkins University, Baltimore, MD)
| | - Kelly J. O’Shea
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York Graduate School of Public Health and Health Policy, New York, New York, (formerly at Johns Hopkins University, Baltimore, MD)
| | - Lucas Winch
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York Graduate School of Public Health and Health Policy, New York, New York, (formerly at Johns Hopkins University, Baltimore, MD)
| | - Sheryl S. Siegmund
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York Graduate School of Public Health and Health Policy, New York, New York, (formerly at Johns Hopkins University, Baltimore, MD)
| | - Mario Solano Gonzales
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York Graduate School of Public Health and Health Policy, New York, New York, (formerly at Johns Hopkins University, Baltimore, MD)
| | - Samuel Randall
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York Graduate School of Public Health and Health Policy, New York, New York, (formerly at Johns Hopkins University, Baltimore, MD)
| | - Daniel Hertenstein
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York Graduate School of Public Health and Health Policy, New York, New York, (formerly at Johns Hopkins University, Baltimore, MD)
| | | | | | | | - Bruce Y. Lee
- PHICOR (Public Health Informatics, Computational and Operations Research), City University of New York Graduate School of Public Health and Health Policy, New York, New York, (formerly at Johns Hopkins University, Baltimore, MD)
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Bartsch SM, Ferguson MC, McKinnell JA, O'Shea KJ, Wedlock PT, Siegmund SS, Lee BY. The Potential Health Care Costs And Resource Use Associated With COVID-19 In The United States. Health Aff (Millwood) 2020; 39:927-935. [PMID: 32324428 PMCID: PMC11027994 DOI: 10.1377/hlthaff.2020.00426] [Citation(s) in RCA: 217] [Impact Index Per Article: 54.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
With the coronavirus disease 2019 (COVID-19) pandemic, one of the major concerns is the direct medical cost and resource use burden imposed on the US health care system. We developed a Monte Carlo simulation model that represented the US population and what could happen to each person who got infected. We estimated resource use and direct medical costs per symptomatic infection and at the national level, with various "attack rates" (infection rates), to understand the potential economic benefits of reducing the burden of the disease. A single symptomatic COVID-19 case could incur a median direct medical cost of $3,045 during the course of the infection alone. If 80 percent of the US population were to get infected, the result could be a median of 44.6 million hospitalizations, 10.7 million intensive care unit (ICU) admissions, 6.5 million patients requiring a ventilator, 249.5 million hospital bed days, and $654.0 billion in direct medical costs over the course of the pandemic. If 20 percent of the US population were to get infected, there could be a median of 11.2 million hospitalizations, 2.7 million ICU admissions, 1.6 million patients requiring a ventilator, 62.3 million hospital bed days, and $163.4 billion in direct medical costs over the course of the pandemic.
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Affiliation(s)
- Sarah M Bartsch
- Sarah M. Bartsch is a project director at Public Health Informatics, Computational, and Operations Research (PHICOR), Graduate School of Public Health and Health Policy, City University of New York, in New York City
| | - Marie C Ferguson
- Marie C. Ferguson is a project director at PHICOR, Graduate School of Public Health and Health Policy, City University of New York
| | - James A McKinnell
- James A. McKinnell is an associate professor of medicine in the Infectious Disease Clinical Outcomes Research Unit, Lundquist Institute, Harbor-UCLA Medical Center, in Los Angeles, California
| | - Kelly J O'Shea
- Kelly J. O'Shea is a senior research analyst at PHICOR, Graduate School of Public Health and Health Policy, City University of New York
| | - Patrick T Wedlock
- Patrick T. Wedlock is a senior research analyst at PHICOR, Graduate School of Public Health and Health Policy, City University of New York
| | - Sheryl S Siegmund
- Sheryl S. Siegmund is director of operations at PHICOR, Graduate School of Public Health and Health Policy, City University of New York
| | - Bruce Y Lee
- Bruce Y. Lee is a professor of health policy and management at the Graduate School of Public Health and Health Policy and executive director of PHICOR, both at the City University of New York
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Bartsch SM, O'Shea KJ, Ferguson MC, Bottazzi ME, Cox SN, Strych U, McKinnell JA, Wedlock PT, Siegmund SS, Hotez PJ, Lee BY. How Efficacious Must a COVID-19 Coronavirus Vaccine be to Prevent or Stop an Epidemic by Itself. medRxiv 2020. [PMID: 32511569 DOI: 10.1101/2020.05.29.20117184] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND Given the continuing coronavirus disease 2019 (COVID-19) pandemic and much of the U.S. implementing social distancing due to the lack of alternatives, there has been a push to develop a vaccine to eliminate the need for social distancing. METHODS In 2020, we developed a computational model of the U.S. simulating the spread of COVID-19 coronavirus and vaccination. RESULTS Simulation experiments revealed that when vaccine efficacy exceeded 70%, coverage exceeded 60%, and vaccination occurred on day 1, the attack rate dropped to 22% with daily cases not exceeding 3.2 million (reproductive rate, R0, 2.5). When R0 was 3.5, the attack rate dropped to 41% with daily cases not exceeding 14.4 million. Increasing coverage to 75% when vaccination occurred by day 90 resulted in 5% attack rate and daily cases not exceeding 258,029when R0 was 2.5 and a 26% attack rate and maximum daily cases of 22.6 million when R0 was 3.5. When vaccination did not occur until day 180, coverage (i.e., those vaccinated plus those otherwise immune) had to reach 100%. A vaccine with an efficacy between 40% and 70% could still obviate the need for other measures under certain circumstances such as much higher, and in some cases, potentially unachievable, vaccination coverages. CONCLUSION Our study found that to either prevent or largely extinguish an epidemic without any other measures (e.g., social distancing), the vaccine has to have an efficacy of at least 70%.
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Ferguson MC, O'Shea KJ, Hammer LD, Hertenstein DL, Schwartz NJ, Winch LE, Siegmund SS, Lee BY. The Impact of Following Solid Food Feeding Guides on BMI Among Infants: A Simulation Study. Am J Prev Med 2019; 57:355-364. [PMID: 31353163 PMCID: PMC6871772 DOI: 10.1016/j.amepre.2019.04.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Revised: 04/08/2019] [Accepted: 04/09/2019] [Indexed: 11/29/2022]
Abstract
INTRODUCTION There are several recommendations advising caregivers when and how to introduce solid food to infants. These complementary feeding guides vary in terms of the recommendations for timing and portions. The objective of this study is to determine the impact of following different guidelines on weight trajectories of infants. METHODS In 2018, the study team developed a computational simulation model to capture feeding behaviors, activity levels, metabolism, and body size of infants from 6 months to 1 year. Daily food intake of virtual infants based on feeding recommendations translated to changes in body weight. Next, simulations tested the impact of the following complementary feeding recommendations that provided amount, type, and timing of foods: Children's Hospital of Philadelphia, Johns Hopkins Medicine, Enfamil, and Similac. RESULTS When virtual caregivers fed infants according to the four different guides, none of the simulated situations resulted in normal weight at 12 months when infants were also being breastfed along average observed patterns. Reducing breast milk portions in half while caregivers fed infants according to complementary feeding guidelines resulted in overweight BMIs between 9 and 11 months for Children's Hospital of Philadelphia, Johns Hopkins Medicine, and Enfamil guidelines. Cutting breast milk portions in half also led to infants reaching unhealthy underweight BMI percentiles between 7 and 11 months for female and male infants when caregivers followed Children's Hospital of Philadelphia, Johns Hopkins Medicine, and Similac guidelines. CONCLUSIONS This study identified situations in which infants could reach unhealthy weights, even while following complementary feeding guidelines, suggesting that current recommended portion sizes should be tightened.
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Affiliation(s)
- Marie C Ferguson
- Global Obesity Prevention Center (GOPC) at Johns Hopkins, Baltimore, Maryland; Public Health Computational and Operations Research (PHICOR), Baltimore, Maryland
| | - Kelly J O'Shea
- Global Obesity Prevention Center (GOPC) at Johns Hopkins, Baltimore, Maryland; Public Health Computational and Operations Research (PHICOR), Baltimore, Maryland
| | | | - Daniel L Hertenstein
- Global Obesity Prevention Center (GOPC) at Johns Hopkins, Baltimore, Maryland; Public Health Computational and Operations Research (PHICOR), Baltimore, Maryland
| | - Nathaniel J Schwartz
- Global Obesity Prevention Center (GOPC) at Johns Hopkins, Baltimore, Maryland; Public Health Computational and Operations Research (PHICOR), Baltimore, Maryland
| | - Lucas E Winch
- Global Obesity Prevention Center (GOPC) at Johns Hopkins, Baltimore, Maryland; Public Health Computational and Operations Research (PHICOR), Baltimore, Maryland
| | - Sheryl S Siegmund
- Global Obesity Prevention Center (GOPC) at Johns Hopkins, Baltimore, Maryland; Public Health Computational and Operations Research (PHICOR), Baltimore, Maryland
| | - Bruce Y Lee
- Global Obesity Prevention Center (GOPC) at Johns Hopkins, Baltimore, Maryland; Public Health Computational and Operations Research (PHICOR), Baltimore, Maryland.
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12
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Wedlock PT, Mitgang EA, Oron AP, Hagedorn BL, Leonard J, Brown ST, Bakal J, Siegmund SS, Lee BY. Modeling the economic impact of different vial-opening thresholds for measles-containing vaccines. Vaccine 2019; 37:2356-2368. [PMID: 30914223 PMCID: PMC6467546 DOI: 10.1016/j.vaccine.2019.03.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 03/07/2019] [Accepted: 03/11/2019] [Indexed: 10/27/2022]
Abstract
INTRODUCTION The lack of specific policies on how many children must be present at a vaccinating location before a healthcare worker can open a measles-containing vaccine (MCV) - i.e. the vial-opening threshold - has led to inconsistent practices, which can have wide-ranging systems effects. METHODS Using HERMES-generated simulation models of the routine immunization supply chains of Benin, Mozambique and Niger, we evaluated the impact of different vial-opening thresholds (none, 30% of doses must be used, 60%) and MCV presentations (10-dose, 5-dose) on each supply chain. We linked these outputs to a clinical- and economic-outcomes model which translated the change in vaccine availability to associated infections, medical costs, and DALYs. We calculated the economic impact of each policy from the health system perspective. RESULTS The vial-opening threshold that maximizes vaccine availability while minimizing costs varies between individual countries. In Benin (median session size = 5), implementing a 30% vial-opening threshold and tailoring distribution of 10-dose and 5-dose MCVs to clinics based on session size is the most cost-effective policy, preventing 671 DALYs ($471/DALY averted) compared to baseline (no threshold, 10-dose MCVs). In Niger (median MCV session size = 9), setting a 60% vial-opening threshold and tailoring MCV presentations is the most cost-effective policy, preventing 2897 DALYs ($16.05/ DALY averted). In Mozambique (median session size = 3), setting a 30% vial-opening threshold using 10-dose MCVs is the only beneficial policy compared to baseline, preventing 3081 DALYs ($85.98/DALY averted). Across all three countries, however, a 30% vial-opening threshold using 10-dose MCVs everywhere is the only MCV threshold that consistently benefits each system compared to baseline. CONCLUSION While the ideal vial-opening threshold policy for MCV varies by supply chain, implementing a 30% vial-opening threshold for 10-dose MCVs benefits each system by improving overall vaccine availability and reducing associated medical costs and DALYs compared to no threshold.
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Affiliation(s)
- Patrick T Wedlock
- HERMES Logistics Modeling Team, Baltimore, MD & Pittsburgh, PA, United States; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Elizabeth A Mitgang
- HERMES Logistics Modeling Team, Baltimore, MD & Pittsburgh, PA, United States; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Assaf P Oron
- Institute for Disease Modeling, Bellevue, WA, United States
| | | | - Jim Leonard
- HERMES Logistics Modeling Team, Baltimore, MD & Pittsburgh, PA, United States; Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Shawn T Brown
- HERMES Logistics Modeling Team, Baltimore, MD & Pittsburgh, PA, United States; McGill Centre for Integrative Neuroscience, McGill Neurological Institute, McGill University, Montreal, Canada
| | - Jennifer Bakal
- HERMES Logistics Modeling Team, Baltimore, MD & Pittsburgh, PA, United States; Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Sheryl S Siegmund
- HERMES Logistics Modeling Team, Baltimore, MD & Pittsburgh, PA, United States; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Bruce Y Lee
- HERMES Logistics Modeling Team, Baltimore, MD & Pittsburgh, PA, United States; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
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Wedlock PT, Mitgang EA, Haidari LA, Prosser W, Brown ST, Krudwig K, Siegmund SS, DePasse JV, Bakal J, Leonard J, Welling J, Steinglass R, Mwansa FD, Phiri G, Lee BY. The value of tailoring vial sizes to populations and locations. Vaccine 2018; 37:637-644. [PMID: 30578087 DOI: 10.1016/j.vaccine.2018.12.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 11/19/2018] [Accepted: 12/04/2018] [Indexed: 10/27/2022]
Abstract
BACKGROUND Frequently, a country will procure a single vaccine vial size, but the question remains whether tailoring the use of different size vaccine vial presentations based on populations or location characteristics within a single country could provide additional benefits, such as reducing open vial wastage (OVW) or reducing missed vaccination opportunities. METHODS Using the Highly Extensible Resource for Modeling Supply Chains (HERMES) software, we built a simulation model of the Zambia routine vaccine supply chain. At baseline, we distributed 10-dose Measles-Rubella (MR) vials to all locations, and then distributed 5-dose and 1-dose MR vials to (1) all locations, (2) rural districts, (3) rural health facilities, (4) outreach sites, and (5) locations with average MR session sizes <5 and <10 children. We ran sensitivity on each scenario using MR vial opening thresholds of 0% and 50%, i.e. a healthcare worker opens an MR vaccine for any number of children (0%) or if at least half will be used (50%). RESULTS Replacing 10-dose MR with 5-dose MR vials everywhere led to the largest reduction in MR OVW, saving 573,892 doses (103,161 doses with the 50% vial opening threshold) and improving MR availability by 1% (9%). This scenario, however, increased cold chain utilization and led to a 1% decrease in availability of other vaccines. Tailoring 5-dose MR vials to rural health facilities or based on average session size reduced cold transport constraints, increased total vaccine availability (+1%) and reduced total cost per dose administered (-$0.01) compared to baseline. CONCLUSIONS In Zambia, tailoring 5-dose MR vials to rural health facilities or by average session size results in the highest total vaccine availability compared to all other scenarios (regardless of OVT policy) by reducing open vial wastage without increasing cold chain utilization.
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Affiliation(s)
- Patrick T Wedlock
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; HERMES Logistics Modeling Team, Pittsburgh, PA, USA; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205, USA; Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA
| | - Elizabeth A Mitgang
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; HERMES Logistics Modeling Team, Pittsburgh, PA, USA; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205, USA; Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA
| | - Leila A Haidari
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; HERMES Logistics Modeling Team, Pittsburgh, PA, USA; Pittsburgh Supercomputing Center (PSC) at Carnegie Mellon University, 300 Craig Street, Pittsburgh, PA 15213, USA
| | | | - Shawn T Brown
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; HERMES Logistics Modeling Team, Pittsburgh, PA, USA; McGill Centre for Integrative Neuroscience, McGill Neurological Institute, McGill University, Montreal, Canada
| | | | - Sheryl S Siegmund
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; HERMES Logistics Modeling Team, Pittsburgh, PA, USA; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205, USA; Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA
| | - Jay V DePasse
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; HERMES Logistics Modeling Team, Pittsburgh, PA, USA; Pittsburgh Supercomputing Center (PSC) at Carnegie Mellon University, 300 Craig Street, Pittsburgh, PA 15213, USA
| | - Jennifer Bakal
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; HERMES Logistics Modeling Team, Pittsburgh, PA, USA; Pittsburgh Supercomputing Center (PSC) at Carnegie Mellon University, 300 Craig Street, Pittsburgh, PA 15213, USA
| | - Jim Leonard
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; HERMES Logistics Modeling Team, Pittsburgh, PA, USA; Pittsburgh Supercomputing Center (PSC) at Carnegie Mellon University, 300 Craig Street, Pittsburgh, PA 15213, USA
| | - Joel Welling
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; HERMES Logistics Modeling Team, Pittsburgh, PA, USA; Pittsburgh Supercomputing Center (PSC) at Carnegie Mellon University, 300 Craig Street, Pittsburgh, PA 15213, USA
| | | | | | | | - Bruce Y Lee
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; HERMES Logistics Modeling Team, Pittsburgh, PA, USA; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205, USA; Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA.
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Wedlock PT, Mitgang EA, Siegmund SS, DePasse J, Bakal J, Leonard J, Welling J, Brown ST, Lee BY. Dual-chamber injection device for measles-rubella vaccine: The potential impact of introducing varying sizes of the devices in 3 countries. Vaccine 2018; 36:5879-5885. [PMID: 30146404 PMCID: PMC6143385 DOI: 10.1016/j.vaccine.2018.08.026] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 08/07/2018] [Accepted: 08/09/2018] [Indexed: 11/17/2022]
Abstract
Introduction By pairing diluent with vaccines, dual-chamber vaccine injection devices simplify the process of reconstituting vaccines before administration and thus decrease associated open vial wastage and adverse events. However, since these devices are larger than current vaccine vials for lyophilized vaccines, manufacturers need guidance as to how the size of these devices may affect vaccine distribution and delivery. Methods Using HERMES-generated immunization supply chain models of Benin, Bihar (India), and Mozambique, we replace the routine 10-dose measles-rubella (MR) lyophilized vaccine with single-dose MR dual-chamber injection devices, ranging the volume-per-dose (5.2–26 cm3) and price-per-dose ($0.70, $1.40). Results At a volume-per-dose of 5.2 cm3, a dual-chamber injection device results in similar vaccine availability, decreased open vial wastage (OVW), and similar total cost per dose administered as compared to baseline in moderately constrained supply chains. Between volumes of 7.5 cm3 and 26 cm3, these devices lead to a reduction in vaccine availability between 1% and 14% due to increases in cold chain storage utilization between 1% and 7% and increases in average peak transport utilization between 2% and 44%. At the highest volume-per-dose, 26 cm3, vaccine availability decreases between 9% and 14%. The total costs per dose administered varied between each scenario, as decreases in vaccine procurement costs were coupled with decreases in doses administered. However, introduction of a dual-chamber injection device only resulted in improved total cost per dose administered for Benin and Mozambique (at 5.2 cm3 and $0.70-per-dose) when the total number of doses administered changed <1% from baseline. Conclusion In 3 different country supply chains, a single-dose MR dual-chamber injection device would need to be no larger than 5.2 cm3 to not significantly impair the flow of other vaccines.
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Affiliation(s)
- Patrick T Wedlock
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Elizabeth A Mitgang
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Sheryl S Siegmund
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jay DePasse
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Jennifer Bakal
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Jim Leonard
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Joel Welling
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Shawn T Brown
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; McGill Centre for Integrative Neuroscience, McGill Neurological Institute, McGill University, Montreal, Canada
| | - Bruce Y Lee
- HERMES Logistics Modeling Team, Baltimore, MD and Pittsburgh, PA, USA; Global Obesity Prevention Center (GOPC) at Johns Hopkins University, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
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