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Lee BY, Pavilonis B, John DC, Heneghan J, Bartsch SM, Kavouras I. The Need to Focus More on Climate Change Communication and Incorporate More Systems Approaches. JOURNAL OF HEALTH COMMUNICATION 2024; 29:1-10. [PMID: 38831666 DOI: 10.1080/10810730.2024.2361566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
Society is at an inflection point-both in terms of climate change and the amount of data and computational resources currently available. Climate change has been a catastrophe in slow motion with relationships between human activity, climate change, and the resulting effects forming a complex system. However, to date, there has been a general lack of urgent responses from leaders and the general public, despite urgent warnings from the scientific community about the consequences of climate change and what can be done to mitigate it. Further, misinformation and disinformation about climate change abound. A major problem is that there has not been enough focus on communication in the climate change field. Since communication itself involves complex systems (e.g. information users, information itself, communications channels), there is a need for more systems approaches to communication about climate change. Utilizing systems approaches to really understand and anticipate how information may be distributed and received before communication has even occurred and adjust accordingly can lead to more proactive precision climate change communication. The time has come to identify and develop more effective, tailored, and precise communication for climate change.
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Affiliation(s)
- Bruce Y Lee
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, New York, USA
| | - Brian Pavilonis
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
| | - Danielle C John
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
| | - Jessie Heneghan
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, New York, USA
| | - Sarah M Bartsch
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, New York, USA
| | - Ilias Kavouras
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
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Heneghan J, John DC, Bartsch SM, Piltch-Loeb R, Gilbert C, Kass D, Chin KL, Dibbs A, Shah TD, O'Shea KJ, Scannell SA, Martinez MF, Lee BY. A Systems Map of the Challenges of Climate Communication. JOURNAL OF HEALTH COMMUNICATION 2024; 29:77-88. [PMID: 38845202 DOI: 10.1080/10810730.2024.2361842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Over the past sixty years, scientists have been warning about climate change and its impacts on human health, but evidence suggests that many may not be heeding these concerns. This raises the question of whether new communication approaches are needed to overcome the unique challenges of communicating what people can do to slow or reverse climate change. To better elucidate the challenges of communicating about the links between human activity, climate change and its effects, and identify potential solutions, we developed a systems map of the factors and processes involved based on systems mapping sessions with climate change and communication experts. The systems map revealed 27 communication challenges such as "Limited information on how individual actions contribute to collective human activity," "Limited information on how present activity leads to long-term effects," and "Difficult to represent and communicate complex relationships." The systems map also revealed several themes among the identified challenges that exist in communicating about climate change, including a lack of available data and integrated databases, climate change disciplines working in silos, a need for a lexicon that is easily understood by the public, and the need for new communication strategies to describe processes that take time to manifest.
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Affiliation(s)
- Jessie Heneghan
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, USA
| | - Danielle C John
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Pandemic Response Institute, New York City, New York, USA
| | - Sarah M Bartsch
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, USA
| | - Rachael Piltch-Loeb
- Environmental, Occupational, and Geospatial Health Sciences, City University of New York Graduate School of Public Health and Health Policy, New York City, New York, USA
| | - Christine Gilbert
- School of Communication & Journalism, Stony Brook University, Stony Brook, New York, USA
- Alan Alda Center for Communicating Science, Stony Brook University, Stony Brook, New York, USA
- School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York, USA
| | - Dan Kass
- Vital Strategies, New York, New York, USA
| | - Kevin L Chin
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, USA
| | - Alexis Dibbs
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, USA
| | - Tej D Shah
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, USA
| | - Kelly J O'Shea
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, USA
| | - Sheryl A Scannell
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, USA
| | - Marie F Martinez
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, USA
| | - Bruce Y Lee
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, New York, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, New York, 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, USA
- Pandemic Response Institute, New York City, New York, USA
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Enayati S, Campbell JF, Li H. Vaccine distribution with drones for less developed countries: A case study in Vanuatu. Vaccine X 2023; 14:100312. [PMID: 37234593 PMCID: PMC10205531 DOI: 10.1016/j.jvacx.2023.100312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/28/2023] Open
Abstract
Drones (uncrewed aerial vehicles or UAVs) introduce new opportunities to improve vaccine distribution systems, particularly in regions with limited transportation infrastructure where maintaining the cold chain is challenging. This paper addresses the use of drones to deliver vaccines to hard-to-reach populations using a novel optimization model to strategically design a multimodal vaccine distribution network. The model is illustrated in a case study for distributing routine childhood vaccines in Vanuatu, a South Pacific island nation with limited transportation infrastructure. Our research incorporates multiple drone types, recharging of drones, a cold chain travel time limit, transshipment delays for switching transport modes, and practical limits on the vaccine paths and drone trips. The goal is to locate facilities (distribution centers, drone bases, and relay stations) and design vaccine paths to minimize transportation costs, including the fixed costs for facilities and transportation links and variable costs for transportation through the network. Results show large potential cost savings and improved service quality provided by incorporating drones in a multimodal vaccine distribution system. Results also show the impact of introducing drones on the usage of other more expensive or slower transport modes.
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Lee BY, Greene D, Scannell SA, McLaughlin C, Martinez MF, Heneghan JL, Chin KL, Zheng X, Li R, Lindenfeld L, Bartsch SM. The Need for Systems Approaches for Precision Communications in Public Health. JOURNAL OF HEALTH COMMUNICATION 2023; 28:13-24. [PMID: 37390012 PMCID: PMC10373800 DOI: 10.1080/10810730.2023.2220668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2023]
Abstract
A major challenge in communicating health-related information is the involvement of multiple complex systems from the creation of the information to the sources and channels of dispersion to the information users themselves. To date, public health communications approaches have often not adequately accounted for the complexities of these systems to the degree necessary to have maximum impact. The virality of COVID-19 misinformation and disinformation has brought to light the need to consider these system complexities more extensively. Unaided, it is difficult for humans to see and fully understand complex systems. Luckily, there are a range of systems approaches and methods, such as systems mapping and systems modeling, that can help better elucidate complex systems. Using these methods to better characterize the various systems involved in communicating public health-related information can lead to the development of more tailored, precise, and proactive communications. Proceeding in an iterative manner to help design, implement, and adjust such communications strategies can increase impact and leave less opportunity for misinformation and disinformation to spread.
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Affiliation(s)
- Bruce Y. Lee
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Danielle Greene
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Sheryl A. Scannell
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Christopher McLaughlin
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Marie F. Martinez
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Jessie L. Heneghan
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Kevin L. Chin
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Xia Zheng
- School of Communication & Journalism, Stony Brook University, Stony Brook, NY, USA
- Alan Alda Center for Communicating Science, Stony Brook University, Stony Brook, NY, USA
| | - Ruobing Li
- School of Communication & Journalism, Stony Brook University, Stony Brook, NY, USA
- Alan Alda Center for Communicating Science, Stony Brook University, Stony Brook, NY, USA
| | - Laura Lindenfeld
- School of Communication & Journalism, Stony Brook University, Stony Brook, NY, USA
- Alan Alda Center for Communicating Science, Stony Brook University, Stony Brook, NY, USA
| | - Sarah M. Bartsch
- Center for Advanced Technology and Communication in Health (CATCH), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
- New York City Pandemic Response Institute (PRI), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
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Alghamdi S. The role of vaccines in combating antimicrobial resistance (AMR) bacteria. Saudi J Biol Sci 2021; 28:7505-7510. [PMID: 34867055 PMCID: PMC8626314 DOI: 10.1016/j.sjbs.2021.08.054] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/08/2021] [Accepted: 08/16/2021] [Indexed: 12/24/2022] Open
Abstract
Most pathogens have developed an intrinsic capacity to thrive by developing resistance to antimicrobial compounds utilized in treatment. Antimicrobial resistance arises when microbial agents such as bacteria, viruses, fungi, and parasites alter their behaviour to make current conventional medicines inefficient. Vaccination is one of the most effective strategies to fight antimicrobial resistance. Vaccines, unlike drugs, are less likely to produce resistance since they are precise to their target illnesses. Vaccines against infectious agents such as Streptococcus pneumoniae and Haemophilus influenzae have already been shown to reduce tolerance to antimicrobial medications; however, vaccines against some antimicrobial-resistant pathogens such as Vibrio cholerae, Salmonella typhi, Escherichia coli, nosocomial infections, and pulmonary and diarrheal disease viruses require more research and development. This paper describes vaccine roles in combatting antimicrobial resistance, quantifies the overall advantages of vaccination as an anti-antimicrobial resistance approach, analyzes existing antimicrobial vaccines and those currently under development, and emphasizes some of the obstacles and prospects of vaccine research and development.
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Affiliation(s)
- Saad Alghamdi
- Laboratory Medicne Department, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah 21955, Saudi Arabia
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Ozawa S, Yemeke TT, Mitgang E, Wedlock PT, Higgins C, Chen HH, Pallas SW, Abimbola T, Wallace A, Bartsch SM, Lee BY. Systematic review of the costs for vaccinators to reach vaccination sites: Incremental costs of reaching hard-to-reach populations. Vaccine 2021; 39:4598-4610. [PMID: 34238610 PMCID: PMC10680154 DOI: 10.1016/j.vaccine.2021.05.019] [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: 01/03/2021] [Revised: 04/07/2021] [Accepted: 05/06/2021] [Indexed: 11/24/2022]
Abstract
INTRODUCTION Economic evidence on how much it may cost for vaccinators to reach populations is important to plan vaccination programs. Moreover, knowing the incremental costs to reach populations that have traditionally been undervaccinated, especially those hard-to-reach who are facing supply-side barriers to vaccination, is essential to expanding immunization coverage to these populations. METHODS We conducted a systematic review to identify estimates of costs associated with getting vaccinators to all vaccination sites. We searched PubMed and the Immunization Delivery Cost Catalogue (IDCC) in 2019 for the following costs to vaccinators: (1) training costs; (2) labor costs, per diems, and incentives; (3) identification of vaccine beneficiary location; and (4) travel costs. We assessed if any of these costs were specific to populations that are hard-to-reach for vaccination, based on a framework for examining supply-side barriers to vaccination. RESULTS We found 19 studies describing average vaccinator training costs at $0.67/person vaccinated or targeted (SD $0.94) and $0.10/dose delivered (SD $0.07). The average cost for vaccinator labor and incentive costs across 29 studies was $2.15/dose (SD $2.08). We identified 13 studies describing intervention costs for a vaccinator to know the location of a beneficiary, with an average cost of $19.69/person (SD $26.65), and six studies describing vaccinator travel costs, with an average cost of $0.07/dose (SD $0.03). Only eight of these studies described hard-to-reach populations for vaccination; two studies examined incremental costs per dose to reach hard-to-reach populations, which were 1.3-2 times higher than the regular costs. The incremental cost to train vaccinators was $0.02/dose, and incremental labor costs for targeting hard-to-reach populations were $0.16-$1.17/dose. CONCLUSION Additional comparative costing studies are needed to understand the potential differential costs for vaccinators reaching the vaccination sites that serve hard-to-reach populations. This will help immunization program planners and decision-makers better allocate resources to extend vaccination programs.
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Affiliation(s)
- Sachiko Ozawa
- Division of Practice Advancement and Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA; Department of Maternal and Child Health, UNC Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
| | - Tatenda T Yemeke
- Division of Practice Advancement and Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
| | - Elizabeth Mitgang
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Patrick T Wedlock
- Public Health Informatics, Computational, and Operations Research (PHICOR), CUNY Graduate School of Public Health and Health Policy, New York City, NY, USA
| | - Colleen Higgins
- Division of Practice Advancement and Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
| | - Hui-Han Chen
- Division of Practice Advancement and Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
| | - Sarah W Pallas
- Global Immunization Division, U.S. Centers for Disease Control and Prevention (CDC), Atlanta, GA, USA
| | - Taiwo Abimbola
- Global Immunization Division, U.S. Centers for Disease Control and Prevention (CDC), Atlanta, GA, USA
| | - Aaron Wallace
- Global Immunization Division, U.S. Centers for Disease Control and Prevention (CDC), Atlanta, GA, USA
| | - 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
| | - 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
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