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Willem L, Abrams S, Franco N, Coletti P, Libin PJK, Wambua J, Couvreur S, André E, Wenseleers T, Mao Z, Torneri A, Faes C, Beutels P, Hens N. The impact of quality-adjusted life years on evaluating COVID-19 mitigation strategies: lessons from age-specific vaccination roll-out and variants of concern in Belgium (2020-2022). BMC Public Health 2024; 24:1171. [PMID: 38671366 PMCID: PMC11047051 DOI: 10.1186/s12889-024-18576-w] [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: 10/27/2023] [Accepted: 04/11/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND When formulating and evaluating COVID-19 vaccination strategies, an emphasis has been placed on preventing severe disease that overburdens healthcare systems and leads to mortality. However, more conventional outcomes such as quality-adjusted life years (QALYs) and inequality indicators are warranted as additional information for policymakers. METHODS We adopted a mathematical transmission model to describe the infectious disease dynamics of SARS-COV-2, including disease mortality and morbidity, and to evaluate (non)pharmaceutical interventions. Therefore, we considered temporal immunity levels, together with the distinct transmissibility of variants of concern (VOCs) and their corresponding vaccine effectiveness. We included both general and age-specific characteristics related to SARS-CoV-2 vaccination. Our scenario study is informed by data from Belgium, focusing on the period from August 2021 until February 2022, when vaccination for children aged 5-11 years was initially not yet licensed and first booster doses were administered to adults. More specifically, we investigated the potential impact of an earlier vaccination programme for children and increased or reduced historical adult booster dose uptake. RESULTS Through simulations, we demonstrate that increasing vaccine uptake in children aged 5-11 years in August-September 2021 could have led to reduced disease incidence and ICU occupancy, which was an essential indicator for implementing non-pharmaceutical interventions and maintaining healthcare system functionality. However, an enhanced booster dose regimen for adults from November 2021 onward could have resulted in more substantial cumulative QALY gains, particularly through the prevention of elevated levels of infection and disease incidence associated with the emergence of Omicron VOC. In both scenarios, the need for non-pharmaceutical interventions could have decreased, potentially boosting economic activity and mental well-being. CONCLUSIONS When calculating the impact of measures to mitigate disease spread in terms of life years lost due to COVID-19 mortality, we highlight the impact of COVID-19 on the health-related quality of life of survivors. Our study underscores that disease-related morbidity could constitute a significant part of the overall health burden. Our quantitative findings depend on the specific setup of the interventions under review, which is open to debate or should be contextualised within future situations.
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Affiliation(s)
- Lander Willem
- Department of Family Medicine and Population Health, Antwerp, Belgium.
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium.
| | - Steven Abrams
- Department of Family Medicine and Population Health, Antwerp, Belgium
- Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Nicolas Franco
- Data Science Institute, Hasselt University, Hasselt, Belgium
- Namur Institute for Complex Systems (naXys) and Department of Mathematics, University of Namur, Namur, Belgium
| | - Pietro Coletti
- Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Pieter J K Libin
- Data Science Institute, Hasselt University, Hasselt, Belgium
- Artificial Intelligence Lab, Vrije Universiteit Brussel, Brussels, Belgium
- Rega Institute for Medical Research, Clinical and Epidemiological Virology, University of Leuven, Leuven, Belgium
| | - James Wambua
- Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Simon Couvreur
- Department of Epidemiology and public health, Sciensano, Brussel, Belgium
| | - Emmanuel André
- National Reference Centre for Respiratory Pathogens, University Hospitals Leuven, Leuven, Belgium
- Department of Microbiology, Immunology and Transplantation, University of Leuven, Leuven, Belgium
| | - Tom Wenseleers
- Laboratory of Socioecology and Social Evolution, University of Leuven, Leuven, Belgium
| | - Zhuxin Mao
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
| | - Andrea Torneri
- Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Christel Faes
- Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Philippe Beutels
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- School of Public Health and Community Medicine, The University of New South Wales, Sydney, Australia
| | - Niel Hens
- Centre for Health Economic Research and Modelling Infectious Diseases, University of Antwerp, Antwerp, Belgium
- Data Science Institute, Hasselt University, Hasselt, Belgium
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Espinosa O, Mora L, Sanabria C, Ramos A, Rincón D, Bejarano V, Rodríguez J, Barrera N, Álvarez-Moreno C, Cortés J, Saavedra C, Robayo A, Franco OH. Predictive models for health outcomes due to SARS-CoV-2, including the effect of vaccination: a systematic review. Syst Rev 2024; 13:30. [PMID: 38229123 PMCID: PMC10790449 DOI: 10.1186/s13643-023-02411-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 12/04/2023] [Indexed: 01/18/2024] Open
Abstract
BACKGROUND The interaction between modelers and policymakers is becoming more common due to the increase in computing speed seen in recent decades. The recent pandemic caused by the SARS-CoV-2 virus was no exception. Thus, this study aims to identify and assess epidemiological mathematical models of SARS-CoV-2 applied to real-world data, including immunization for coronavirus 2019 (COVID-19). METHODOLOGY PubMed, JSTOR, medRxiv, LILACS, EconLit, and other databases were searched for studies employing epidemiological mathematical models of SARS-CoV-2 applied to real-world data. We summarized the information qualitatively, and each article included was assessed for bias risk using the Joanna Briggs Institute (JBI) and PROBAST checklist tool. The PROSPERO registration number is CRD42022344542. FINDINGS In total, 5646 articles were retrieved, of which 411 were included. Most of the information was published in 2021. The countries with the highest number of studies were the United States, Canada, China, and the United Kingdom; no studies were found in low-income countries. The SEIR model (susceptible, exposed, infectious, and recovered) was the most frequently used approach, followed by agent-based modeling. Moreover, the most commonly used software were R, Matlab, and Python, with the most recurring health outcomes being death and recovery. According to the JBI assessment, 61.4% of articles were considered to have a low risk of bias. INTERPRETATION The utilization of mathematical models increased following the onset of the SARS-CoV-2 pandemic. Stakeholders have begun to incorporate these analytical tools more extensively into public policy, enabling the construction of various scenarios for public health. This contribution adds value to informed decision-making. Therefore, understanding their advancements, strengths, and limitations is essential.
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Affiliation(s)
- Oscar Espinosa
- Directorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS) & Economic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de Colombia, Bogotá, D.C., Colombia.
| | - Laura Mora
- Directorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, Colombia
| | - Cristian Sanabria
- Directorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, Colombia
| | - Antonio Ramos
- Directorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS) & Economic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de Colombia, Bogotá, D.C., Colombia
| | - Duván Rincón
- Directorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, Colombia
| | - Valeria Bejarano
- Directorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS) & Economic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de Colombia, Bogotá, D.C., Colombia
| | - Jhonathan Rodríguez
- Directorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS) & Economic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de Colombia, Bogotá, D.C., Colombia
| | - Nicolás Barrera
- Directorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, Colombia
| | | | - Jorge Cortés
- Faculty of Medicine, Universidad Nacional de Colombia, Bogotá, D.C., Colombia
| | - Carlos Saavedra
- Faculty of Medicine, Universidad Nacional de Colombia, Bogotá, D.C., Colombia
| | - Adriana Robayo
- Directorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, Colombia
| | - Oscar H Franco
- University Medical Center Utrecht, Utrecht University & Harvard T.H. Chan School of Public Health, Harvard University, Cambridge, USA
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Salah H, Sinan I, Alsamani O, Abdelghani LS, ElLithy MH, Bukamal N, Jawad H, Hussein RRS, Elgendy MO, Rabie ASI, Khalil DM, Said ASA, AlAhmad MM, Khodary A. COVID-19 Booster Doses: A Multi-Center Study Reflecting Healthcare Providers' Perceptions. Vaccines (Basel) 2023; 11:1061. [PMID: 37376450 DOI: 10.3390/vaccines11061061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/22/2023] [Accepted: 06/01/2023] [Indexed: 06/29/2023] Open
Abstract
(1) Background: During 2019, the COVID-19 pandemic was threatening healthcare services and workers, and acquiring immunity was an option to stop or limit the burden of this pandemic. Herd immunity was a top priority worldwide as the virus was spreading rapidly. It was estimated that 67% of the total global population should be immunized against COVID-19 to achieve herd immunity. The aim of the current study is to investigate different perceptions of healthcare workers in the Kingdom of Bahrain and Egypt using an online survey in an attempt to evaluate their awareness and concerns regarding new variants and booster doses. (2) Methods: This study conducted a survey on healthcare workers in the Kingdom of Bahrain and Egypt about their perception and concerns on the COVID-19 vaccines. (3) Results: The study found that out of 389 healthcare workers 46.1% of the physicians were not willing to take the booster doses (p = 0.004). Physicians also did not support taking the COVID-19 vaccine as an annual vaccine (p = 0.04). Furthermore, to assess the association between the type of vaccine taken with the willingness of taking a booster vaccine, healthcare workers beliefs on vaccine effectiveness (p = 0.001), suspension or contact with patients (p = 0.000), and infection after COVID-19 vaccination (p = 0.016) were significant. (4) Conclusion: Knowledge about vaccine accreditation and regulation should be dispersed more widely to ensure that the population has a positive perception on vaccine safety and effectiveness.
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Affiliation(s)
- Hager Salah
- Pharmaceutical Services Department, King Hamad University Hospital, Al Sayh 24343, Bahrain
| | - Israa Sinan
- Education and Proficiency Centre, King Hamad University Hospital, Al Sayh 24343, Bahrain
| | - Omar Alsamani
- Pharmaceutical Services Department, King Hamad University Hospital, Al Sayh 24343, Bahrain
- Pharmacy Program, Allied Health Department, College of Health Sciences, University of Bahrain, Manama 32038, Bahrain
| | | | - May Hassan ElLithy
- Pharmaceutical Services Department, King Hamad University Hospital, Al Sayh 24343, Bahrain
| | - Nazar Bukamal
- Cardiothoracic ICU and Anesthesia Department, Mohammed Bin Khalifa Specialist Cardiac Center, Awali 183261, Bahrain
| | - Huda Jawad
- Allied Health Department, College of Health Sciences, University of Bahrain, Manama 32038, Bahrain
| | - Raghda R S Hussein
- Department of Clinical Pharmacy, Faculty of Pharmacy, Beni-Suef University, Beni-Suef 62521, Egypt
- Department of Clinical Pharmacy, Faculty of Pharmacy, October 6 University, 6th October City 12511, Egypt
| | - Marwa O Elgendy
- Department of Clinical Pharmacy, Faculty of Pharmacy, Nahda University (NUB), Beni-Suef 62521, Egypt
- Department of Clinical Pharmacy, Beni-Suef University Hospitals, Faculty of Medicine, Beni-Suef University, Beni-Suef 62521, Egypt
| | - Al Shaimaa Ibrahim Rabie
- Clinical Pharmacy Department, Faiyum Oncology Center, Fayium 63511, Egypt
- Clinical Nutrition Department, Fayium Health Insurance Authority, Fayium 63511, Egypt
| | - Doaa Mahmoud Khalil
- Public Health and Community Medicine Department, Faculty of Medicine, Beni-Suef University, Beni-Suef 62514, Egypt
| | - Amira S A Said
- Department of Clinical Pharmacy, Faculty of Pharmacy, Beni-Suef University, Beni-Suef 62521, Egypt
- Clinical Pharmacy Department, College of Pharmacy, Al Ain University, Abu Dhabi P.O. Box 112612, United Arab Emirates
| | - Mohammad M AlAhmad
- Clinical Pharmacy Department, College of Pharmacy, Al Ain University, Abu Dhabi P.O. Box 112612, United Arab Emirates
| | - Azza Khodary
- Mental Health Department, Faculty of Education, Helwan University, Helwan 11795, Egypt
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Chen K, Jiang X, Li Y, Zhou R. A stochastic agent-based model to evaluate COVID-19 transmission influenced by human mobility. NONLINEAR DYNAMICS 2023; 111:1-17. [PMID: 37361002 PMCID: PMC10148626 DOI: 10.1007/s11071-023-08489-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 03/20/2023] [Indexed: 06/28/2023]
Abstract
The COVID-19 pandemic has created an urgent need for mathematical models that can project epidemic trends and evaluate the effectiveness of mitigation strategies. A major challenge in forecasting the transmission of COVID-19 is the accurate assessment of the multiscale human mobility and how it impacts infection through close contacts. By combining the stochastic agent-based modeling strategy and hierarchical structures of spatial containers corresponding to the notion of geographical places, this study proposes a novel model, Mob-Cov, to study the impact of human traveling behavior and individual health conditions on the disease outbreak and the probability of zero-COVID in the population. Specifically, individuals perform power law-type local movements within a container and global transport between different-level containers. It is revealed that frequent long-distance movements inside a small-level container (e.g., a road or a county) and a small population size reduce both the local crowdedness and disease transmission. It takes only half of the time to induce global disease outbreaks when the population increases from 150 to 500 (normalized unit). When the exponent c 1 of the long-tail distribution of distance k moved in the same-level container, p ( k ) ∼ k - c 1 · level , increases, the outbreak time decreases rapidly from 75 to 25 (normalized unit). In contrast, travel between large-level containers (e.g., cities and nations) facilitates global spread of the disease and outbreak. When the mean traveling distance across containers 1 d increases from 0.5 to 1 (normalized unit), the outbreak occurs almost twice as fast. Moreover, dynamic infection and recovery in the population are able to drive the bifurcation of the system to a "zero-COVID" state or to a "live with COVID" state, depending on the mobility patterns, population number and health conditions. Reducing population size and restricting global travel help achieve zero-COVID-19. Specifically, when c 1 is smaller than 0.2, the ratio of people with low levels of mobility is larger than 80% and the population size is smaller than 400, zero-COVID can be achieved within fewer than 1000 time steps. In summary, the Mob-Cov model considers more realistic human mobility at a wide range of spatial scales, and has been designed with equal emphasis on performance, low simulation cost, accuracy, ease of use and flexibility. It is a useful tool for researchers and politicians to apply when investigating pandemic dynamics and when planning actions against disease. Supplementary Information The online version contains supplementary material available at 10.1007/s11071-023-08489-5.
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Affiliation(s)
- Kejie Chen
- School of Optoelectric Engineering and Instrumental Science, Dalian University of Technology, Dalian, 116024 China
| | - Xiaomo Jiang
- Provincial Key Lab of Digital Twin for Industrial Equipment, Dalian, 116024 China
- School of Energy and Power Engineering, Dalian, 116024 China
| | - Yanqing Li
- School of Optoelectric Engineering and Instrumental Science, Dalian University of Technology, Dalian, 116024 China
| | - Rongxin Zhou
- School of Optoelectric Engineering and Instrumental Science, Dalian University of Technology, Dalian, 116024 China
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Truszkowska A, Zino L, Butail S, Caroppo E, Jiang Z, Rizzo A, Porfiri M. Exploring a COVID-19 Endemic Scenario: High-Resolution Agent-Based Modeling of Multiple Variants. ADVANCED THEORY AND SIMULATIONS 2023; 6:2200481. [PMID: 36718198 PMCID: PMC9878004 DOI: 10.1002/adts.202200481] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 09/29/2022] [Indexed: 11/13/2022]
Abstract
Our efforts as a society to combat the ongoing COVID-19 pandemic are continuously challenged by the emergence of new variants. These variants can be more infectious than existing strains and many of them are also more resistant to available vaccines. The appearance of these new variants cause new surges of infections, exacerbated by infrastructural difficulties, such as shortages of medical personnel or test kits. In this work, a high-resolution computational framework for modeling the simultaneous spread of two COVID-19 variants: a widely spread base variant and a new one, is established. The computational framework consists of a detailed database of a representative U.S. town and a high-resolution agent-based model that uses the Omicron variant as the base variant and offers flexibility in the incorporation of new variants. The results suggest that the spread of new variants can be contained with highly efficacious tests and mild loss of vaccine protection. However, the aggressiveness of the ongoing Omicron variant and the current waning vaccine immunity point to an endemic phase of COVID-19, in which multiple variants will coexist and residents continue to suffer from infections.
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Affiliation(s)
- Agnieszka Truszkowska
- Center for Urban Science and ProgressTandon School of EngineeringNew York University370 Jay StreetBrooklynNY11201USA
- Department of Mechanical and Aerospace EngineeringTandon School of EngineeringNew York UniversitySix MetroTech CenterBrooklynNY11201USA
- Department of Chemical and Materials EngineeringUniversity of Alabama in Huntsville301 Sparkman DriveHuntsvilleAL35899USA
| | - Lorenzo Zino
- Engineering and Technology Institute GroningenUniversity of GroningenNijenborgh 4GroningenAG9747The Netherlands
- Department of Electronics and TelecommunicationsPolitecnico di TorinoCorso Duca degli Abruzzi 24Turin10129Italy
| | - Sachit Butail
- Department of Mechanical EngineeringNorthern Illinois UniversityDeKalbIL60115USA
| | - Emanuele Caroppo
- Department of Mental HealthLocal Health Unit ROMA 2Rome00159Italy
- University Research Center He.R.A.Université Cattolica del Sacro CuoreRome00168Italy
| | - Zhong‐Ping Jiang
- Department of Electrical and Computer EngineeringTandon School of EngineeringNew York University370 Jay StreetBrooklynNY11201USA
| | - Alessandro Rizzo
- Department of Electronics and TelecommunicationsPolitecnico di TorinoCorso Duca degli Abruzzi 24Turin10129Italy
- Institute for InventionInnovation and EntrepreneurshipTandon School of EngineeringNew York UniversitySix MetroTech CenterBrooklynNY11201USA
| | - Maurizio Porfiri
- Center for Urban Science and ProgressTandon School of EngineeringNew York University370 Jay StreetBrooklynNY11201USA
- Department of Mechanical and Aerospace EngineeringTandon School of EngineeringNew York UniversitySix MetroTech CenterBrooklynNY11201USA
- Department of Biomedical EngineeringTandon School of EngineeringNew York UniversitySix MetroTech CenterBrooklynNY11201USA
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Ghazy RM, Abdou MS, Awaidy S, Sallam M, Elbarazi I, Youssef N, Fiidow OA, Mehdad S, Hussein MF, Adam MF, Abdullah FSA, Rebai WK, Raad EB, Hussein M, Shehata SF, Ismail II, Salam AA, Samhouri D. Acceptance of COVID-19 Vaccine Booster Doses Using the Health Belief Model: A Cross-Sectional Study in Low-Middle- and High-Income Countries of the East Mediterranean Region. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph191912136. [PMID: 36231447 PMCID: PMC9566578 DOI: 10.3390/ijerph191912136] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 09/18/2022] [Accepted: 09/20/2022] [Indexed: 05/07/2023]
Abstract
Coronavirus disease (COVID-19) booster doses decrease infection transmission and disease severity. This study aimed to assess the acceptance of COVID-19 vaccine booster doses in low, middle, and high-income countries of the East Mediterranean Region (EMR) and its determinants using the health belief model (HBM). In addition, we aimed to identify the causes of booster dose rejection and the main source of information about vaccination. Using the snowball and convince sampling technique, a bilingual, self-administered, anonymous questionnaire was used to collect the data from 14 EMR countries through different social media platforms. Logistic regression analysis was used to estimate the key determinants that predict vaccination acceptance among respondents. Overall, 2327 participants responded to the questionnaire. In total, 1468 received compulsory doses of vaccination. Of them, 739 (50.3%) received booster doses and 387 (26.4%) were willing to get the COVID-19 vaccine booster doses. Vaccine booster dose acceptance rates in low, middle, and high-income countries were 73.4%, 67.9%, and 83.0%, respectively (p < 0.001). Participants who reported reliance on information about the COVID-19 vaccination from the Ministry of Health websites were more willing to accept booster doses (79.3% vs. 66.6%, p < 0.001). The leading causes behind booster dose rejection were the beliefs that booster doses have no benefit (48.35%) and have severe side effects (25.6%). Determinants of booster dose acceptance were age (odds ratio (OR) = 1.02, 95% confidence interval (CI): 1.01-1.03, p = 0.002), information provided by the Ministry of Health (OR = 3.40, 95% CI: 1.79-6.49, p = 0.015), perceived susceptibility to COVID-19 infection (OR = 1.88, 95% CI: 1.21-2.93, p = 0.005), perceived severity of COVID-19 (OR = 2.08, 95% CI: 137-3.16, p = 0.001), and perceived risk of side effects (OR = 0.25, 95% CI: 0.19-0.34, p < 0.001). Booster dose acceptance in EMR is relatively high. Interventions based on HBM may provide useful directions for policymakers to enhance the population's acceptance of booster vaccination.
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Affiliation(s)
- Ramy Mohamed Ghazy
- Tropical Health Department, High Institute of Public Health, Alexandria University, Alexandria 21561, Egypt
- Correspondence:
| | - Marwa Shawky Abdou
- Department of Epidemiology, High Institute of Public Health, Alexandria University, Alexandria 21561, Egypt
| | - Salah Awaidy
- Health Affairs, Ministry of Health, Muscat 100, Oman
| | - Malik Sallam
- Department of Pathology, Microbiology and Forensic Medicine, School of Medicine, The University of Jordan, Amman 11942, Jordan
- Department of Clinical Laboratories and Forensic Medicine, Jordan University Hospital, Amman 11942, Jordan
- Department of Translational Medicine, Faculty of Medicine, Lund University, 22184 Malmö, Sweden
| | - Iffat Elbarazi
- Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, AlAin 15551, United Arab Emirates
| | - Naglaa Youssef
- Department of Medical-Surgical Nursing, College of Nursing, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia
| | - Osman Abubakar Fiidow
- School of Public Health and Research, Somali National University, Mogadishu P.O. Box 15, Somalia
| | - Slimane Mehdad
- Physiology and Physiopathology Research Team, Research Centre of Human Pathology Genomics, Faculty of Sciences, Mohammed V University, Rabat BP 8007, Morocco
| | - Mohamed Fakhry Hussein
- Occupational Health and Industrial Medicine Department, High Institute of Public Health, Alexandria University, Alexandria 21526, Egypt
| | | | | | | | - Etwal Bou Raad
- Department of Epidemiology and Population Health, American University of Beirut, Beirut P.O. Box 110236, Lebanon
- School of Pharmacy, Lebanese International University, Beirut P.O. Box 146404, Lebanon
| | - Mai Hussein
- Clinical Research Administration, Alexandria Directorate of Health Affairs, Egyptian Ministry of Health and Population, Alexandria 21554, Egypt
- Harvard Medical School, Boston, MA 02115, USA
| | - Shehata F. Shehata
- Department of Family and Community Medicine, King Khalid University, Abha 62529, Saudi Arabia
- Biostatistics Department, High Institute of Public Health, Alexandria University, Alexandria 21561, Egypt
| | - Ismail Ibrahim Ismail
- Department of Neurology, Ibn Sina Hospital, Gamal Abdel Nasser Street, Sabah Medical Area, Safat 070001, Kuwait
| | | | - Dalia Samhouri
- Emergency Preparedness and International Health Regulations, WHO EMRO (DS), P.O. Box 7608, Naser City 11371, Egypt
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On the caveats of a multiplex test for SARS-CoV-2 to detect seroconversion after infection or vaccination. Sci Rep 2022; 12:10366. [PMID: 35725758 PMCID: PMC9208546 DOI: 10.1038/s41598-022-14294-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 06/03/2022] [Indexed: 11/24/2022] Open
Abstract
The Covid-19 pandemic, caused by SARS-CoV-2, has resulted in over 6 million reported deaths worldwide being one of the biggest challenges the world faces today. Here we present optimizations of all steps of an enzyme-linked immunosorbent assay (ELISA)-based test to detect IgG, IgA and IgM against the trimeric spike (S) protein, receptor binding domain (RBD), and N terminal domain of the nucleocapsid (N-NTD) protein of SARS-CoV-2. We discuss how to determine specific thresholds for antibody positivity and its limitations according to the antigen used. We applied the assay to a cohort of 126 individuals from Rio de Janeiro, Brazil, consisting of 23 PCR-positive individuals and 103 individuals without a confirmed diagnosis for SARS-CoV-2 infection. To illustrate the differences in serological responses to vaccinal immunization, we applied the test in 18 individuals from our cohort before and after receiving ChAdOx-1 nCoV-19 or CoronaVac vaccines. Taken together, our results show that the test can be customized at different stages depending on its application, enabling the user to analyze different cohorts, saving time, reagents, or samples. It is also a valuable tool for elucidating the immunological consequences of new viral strains and monitoring vaccination coverage and duration of response to different immunization regimens.
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Truszkowska A, Zino L, Butail S, Caroppo E, Jiang Z, Rizzo A, Porfiri M. Predicting the Effects of Waning Vaccine Immunity Against COVID-19 through High-Resolution Agent-Based Modeling. ADVANCED THEORY AND SIMULATIONS 2022; 5:2100521. [PMID: 35540703 PMCID: PMC9073999 DOI: 10.1002/adts.202100521] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 01/24/2022] [Indexed: 02/06/2023]
Abstract
The potential waning of the vaccination immunity to COVID-19 could pose threats to public health, as it is tenable that the timing of such waning would synchronize with the near-complete restoration of normalcy. Should also testing be relaxed, a resurgent COVID-19 wave in winter 2021/2022 might be witnessed. In response to this risk, an additional vaccine dose, the booster shot, is being administered worldwide. A projected study with an outlook of 6 months explores the interplay between the rate at which boosters are distributed and the extent to which testing practices are implemented, using a highly granular agent-based model tuned on a medium-sized US town. Theoretical projections indicate that the administration of boosters at the rate at which the vaccine is currently administered could yield a severe resurgence of the pandemic. Projections suggest that the peak levels of mid-spring 2021 in the vaccination rate may prevent such a scenario to occur, although exact agreement between observations and projections should not be expected due to the continuously evolving nature of the pandemic. This study highlights the importance of testing, especially to detect asymptomatic individuals in the near future, as the release of the booster reaches full speed.
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Affiliation(s)
- Agnieszka Truszkowska
- Center for Urban Science and Progress, Tandon School of EngineeringNew York University370 Jay StreetBrooklynNY11201USA
- Department of Mechanical and Aerospace Engineering, Tandon School of EngineeringNew York UniversitySix MetroTech CenterBrooklynNY11201USA
| | - Lorenzo Zino
- Faculty of Science and EngineeringUniversity of GroningenNijenborgh 4Groningen9747AGThe Netherlands
| | - Sachit Butail
- Department of Mechanical EngineeringNorthern Illinois UniversityDeKalbIL60115USA
| | - Emanuele Caroppo
- Department of Mental HealthLocal Health Unit ROMA 2Rome00159Italy
- University Research Center He.R.A.Universitá Cattolica del Sacro CuoreRome00168Italy
| | - Zhong‐Ping Jiang
- Department of Electrical and Computer Engineering, Tandon School of EngineeringNew York University370 Jay StreetBrooklynNY11201USA
| | - Alessandro Rizzo
- Department of Electronics and TelecommunicationsPolitecnico di TorinoTurin10129Italy
- Institute for Invention, Innovation and Entrepreneurship, Tandon School of EngineeringNew York UniversitySix MetroTech CenterBrooklynNY11201USA
| | - Maurizio Porfiri
- Center for Urban Science and Progress, Tandon School of EngineeringNew York University370 Jay StreetBrooklynNY11201USA
- Department of Mechanical and Aerospace Engineering, Tandon School of EngineeringNew York UniversitySix MetroTech CenterBrooklynNY11201USA
- Department of Biomedical Engineering, Tandon School of EngineeringNew York UniversitySix MetroTech CenterBrooklynNY11201USA
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9
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Wu F, Yuan Y, Deng Z, Yin D, Shen Q, Zeng J, Xie Y, Xu M, Yang M, Jiang S, Zhang C, Lu H, Sun C. Acceptance of COVID-19 Booster Vaccination Based on the Protection Motivation Theory (PMT): A Cross-Sectional Study in China. J Med Virol 2022; 94:4115-4124. [PMID: 35506329 PMCID: PMC9348068 DOI: 10.1002/jmv.27825] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 04/12/2022] [Accepted: 04/30/2022] [Indexed: 12/11/2022]
Abstract
The promotion of the booster shots against severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection is an open issue to be discussed. Little is known about the public intention and the influencing factors regarding the booster vaccine. A cross‐sectional survey in Chinese adults was conducted using an online questionnaire, which designed on the basis of protection motivation theory (PMT) scale and vaccine hesitancy scale (VHS). Hierarchical multiple regression was used to compare the fitness of the PMT scale and VHS for predicting booster vaccination intention. Multivariable logistic regression was used to analyze the factors associated with the acceptance. Six thousand three hundred twenty‐one (76.8%) of participants were willing to take the booster shot. However, the rest of the participants (23.2%) were still hesitant to take the booster vaccine. The PMT scale was more powerful than the VHS in explaining the vaccination intention. Participants with high perceived severity (adjusted odds ratio [aOR] = 0.69) and response cost (aOR = 0.47) were less willing to take the booster shots, but participants with high perceived susceptibility (aOR = 1.19), response efficacy (aOR = 2.13), and self‐efficacy (aOR = 3.33) were more willing to take the booster shots. In summary, interventions based on PMT can provide guidance to ensure the acceptance of the booster vaccine.
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Affiliation(s)
- Fan Wu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Yue Yuan
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Zhaomin Deng
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Di Yin
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Qiufeng Shen
- Huadu Center for Disease Control and Prevention, Guangzhou, 510800, China
| | - Jiehua Zeng
- Recheng Community Health Service Station of Huadu District Huashan Town Health Center, Guangzhou, 510880, China
| | - Yanhong Xie
- Huadu Vaccination Clinic of Tanbu Town Central Health Center, Guangzhou, 510820, China
| | - Meifen Xu
- Shiling Town synthetic community health service center of Huadu District, Guangzhou, 510800, China
| | - Meiyi Yang
- Jianshebei Community Health Service center of Huadu District, Guangzhou, 510800, China
| | - Shiqiang Jiang
- Nanshan District Center for Disease Control and Prevention, Shenzhen, 518000, China
| | - Chunhuan Zhang
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, China
| | - Huixi Lu
- Huadu Center for Disease Control and Prevention, Guangzhou, 510800, China
| | - Caijun Sun
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China.,Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Ministry of Education, Guangzhou, 510080, China
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10
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Yaladanda N, Mopuri R, Vavilala HP, Mutheneni SR. Modelling the impact of perfect and imperfect vaccination strategy against SARS CoV-2 by assuming varied vaccine efficacy over India. CLINICAL EPIDEMIOLOGY AND GLOBAL HEALTH 2022; 15:101052. [PMID: 35535224 PMCID: PMC9068602 DOI: 10.1016/j.cegh.2022.101052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 04/04/2022] [Accepted: 04/18/2022] [Indexed: 11/06/2022] Open
Abstract
Background The outbreak of Coronavirus disease (COVID-19) has swiftly spread globally and caused public health and socio-economic disruption in many countries. An epidemiological modelling studies in the susceptible-infectious-removed (SIR) has played an important role for making effective public health policy to mitigate the spread of COVID-19. The aim of the present study is to investigate the optimal vaccination strategy to control the COVID-19 pandemic in India. Methods We have applied compartment mathematical model susceptible-vaccination-infectious-removed (SVIR) with different range of vaccine efficacy scenarios and predicted the population to be covered for vaccination per day in India as well as state level was performed. Results The model assumed that a vaccine has 100% efficacy, predicted that >5 million populace to be vaccinated per day to flatten the epidemic curve in India. Similarly, different vaccination mechanisms such as ‘all-or-nothing’ (AoN) and leaky vaccines does not have potential discordance in their effectiveness at higher efficacies (>70%). However, AoN vaccine was found to be marginally effective than leaky at lower efficacies (<70%) when administered at the higher coverage strategies. Further state level analyses were performed and it was found that 0.3, 0.3, 0.2 and 1 million vaccinations required per day in Andhra Pradesh, Gujarat, Kerala and Maharashtra as it assumes that the vaccine efficacy is 70%. Conclusion The proposed modelling approach shows a range of assumptions on the efficacy of vaccine which helps the health authorities to prioritize the vaccination strategies to prevent the transmission as well as disease.
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