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González-Parra G, Mahmud MS, Kadelka C. Learning from the COVID-19 pandemic: A systematic review of mathematical vaccine prioritization models. Infect Dis Model 2024; 9:1057-1080. [PMID: 38988830 PMCID: PMC11233876 DOI: 10.1016/j.idm.2024.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 04/26/2024] [Accepted: 05/10/2024] [Indexed: 07/12/2024] Open
Abstract
As the world becomes ever more connected, the chance of pandemics increases as well. The recent COVID-19 pandemic and the concurrent global mass vaccine roll-out provides an ideal setting to learn from and refine our understanding of infectious disease models for better future preparedness. In this review, we systematically analyze and categorize mathematical models that have been developed to design optimal vaccine prioritization strategies of an initially limited vaccine. As older individuals are disproportionately affected by COVID-19, the focus is on models that take age explicitly into account. The lower mobility and activity level of older individuals gives rise to non-trivial trade-offs. Secondary research questions concern the optimal time interval between vaccine doses and spatial vaccine distribution. This review showcases the effect of various modeling assumptions on model outcomes. A solid understanding of these relationships yields better infectious disease models and thus public health decisions during the next pandemic.
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Affiliation(s)
- Gilberto González-Parra
- Instituto de Matemática Multidisciplinar, Universitat Politècnica de València, València, Spain
- Department of Mathematics, New Mexico Tech, 801 Leroy Place, Socorro, 87801, NM, USA
| | - Md Shahriar Mahmud
- Department of Mathematics, Iowa State University, 411 Morrill Rd, Ames, 50011, IA, USA
| | - Claus Kadelka
- Department of Mathematics, Iowa State University, 411 Morrill Rd, Ames, 50011, IA, USA
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Barnsley G, Olivera Mesa D, Hogan AB, Winskill P, Torkelson AA, Walker DG, Ghani AC, Watson OJ. Impact of the 100 days mission for vaccines on COVID-19: a mathematical modelling study. Lancet Glob Health 2024; 12:e1764-e1774. [PMID: 39424569 DOI: 10.1016/s2214-109x(24)00286-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 06/19/2024] [Accepted: 07/01/2024] [Indexed: 10/21/2024]
Abstract
BACKGROUND The COVID-19 pandemic has underscored the beneficial impact of vaccines. It also highlighted the need for future investments to expedite an equitable vaccine distribution. The 100 Days Mission aims to develop and make available a new vaccine against a future pathogen with pandemic potential within 100 days of that pathogen threat being recognised. We assessed the value of this mission by estimating the impact that it could have had on the COVID-19 pandemic. METHODS Using a previously published model of SARS-CoV-2 transmission dynamics fitted to excess mortality during the COVID-19 pandemic, we projected scenarios for three different investment strategies: rapid development and manufacture of a vaccine, increasing manufacturing capacity to eliminate supply constraints, and strengthening health systems to enable faster vaccine roll-outs and global equity. Each scenario was compared against the observed COVID-19 pandemic to estimate the public health and health-economic impacts of each scenario. FINDINGS If countries implemented non-pharmaceutical interventions (NPIs) as they did historically, the 100 Days Mission could have averted an estimated 8·33 million deaths (95% credible interval [CrI] 7·70-8·68) globally, mostly in lower-middle income countries. This corresponds to a monetary saving of US$14·35 trillion (95% CrI 12·96-17·87) based on the value of statistical life-years saved. Investment in manufacturing and health systems further increases deaths averted to 11·01 million (95% CrI 10·60-11·49). Under an alternative scenario whereby NPIs are lifted earlier on the basis of vaccine coverage, the 100 Days Mission alone could have reduced restrictions by 12 600 days (95% CrI 12 300-13 100) globally while still averting 5·76 million deaths (95% CrI 4·91-6·81). INTERPRETATION Our findings show the value of the 100 Days Mission and how these can be amplified through improvements in manufacturing and health systems equity. However, these investments must be enhanced by prioritising a more equitable global vaccine distribution. FUNDING Schmidt Science Fellowship in partnership with the Rhodes Trust, WHO, UK Medical Research Council, Coalition for Epidemic Preparedness Innovations.
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Affiliation(s)
- Gregory Barnsley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Daniela Olivera Mesa
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Alexandra B Hogan
- School of Population Health, University of New South Wales, Sydney, NSW, Australia
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | | | | | - Azra C Ghani
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Oliver J Watson
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
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Fajgenblat M, Molenberghs G, Verbeeck J, Willem L, Crèvecoeur J, Faes C, Hens N, Deboosere P, Verbeke G, Neyens T. Evaluating the direct effect of vaccination and non-pharmaceutical interventions during the COVID-19 pandemic in Europe. COMMUNICATIONS MEDICINE 2024; 4:178. [PMID: 39261675 PMCID: PMC11391057 DOI: 10.1038/s43856-024-00600-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 08/29/2024] [Indexed: 09/13/2024] Open
Abstract
BACKGROUND Across Europe, countries have responded to the COVID-19 pandemic with a combination of non-pharmaceutical interventions and vaccination. Evaluating the effectiveness of such interventions is of particular relevance to policy-makers. METHODS We leverage almost three years of available data across 38 European countries to evaluate the effectiveness of governmental responses in controlling the pandemic. We developed a Bayesian hierarchical model that flexibly relates daily COVID-19 incidence to past levels of vaccination and non-pharmaceutical interventions as summarised in the Stringency Index. Specifically, we use a distributed lag approach to temporally weight past intervention values, a tensor-product smooth to capture non-linearities and interactions between both types of interventions, and a hierarchical approach to parsimoniously address heterogeneity across countries. RESULTS We identify a pronounced negative association between daily incidence and the strength of non-pharmaceutical interventions, along with substantial heterogeneity in effectiveness among European countries. Similarly, we observe a strong but more consistent negative association with vaccination levels. Our results show that non-linear interactions shape the effectiveness of interventions, with non-pharmaceutical interventions becoming less effective under high vaccination levels. Finally, our results indicate that the effects of interventions on daily incidence are most pronounced at a lag of 14 days after being in place. CONCLUSIONS Our Bayesian hierarchical modelling approach reveals clear negative and lagged effects of non-pharmaceutical interventions and vaccination on confirmed COVID-19 cases across European countries.
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Affiliation(s)
- Maxime Fajgenblat
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium.
- Laboratory of Freshwater Ecology, Evolution and Conservation, KU Leuven, Leuven, Belgium.
| | - Geert Molenberghs
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), KU Leuven, Leuven, Belgium
| | - Johan Verbeeck
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium
| | - Lander Willem
- Centre for Health Economics Research and Modelling of Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Jonas Crèvecoeur
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), KU Leuven, Leuven, Belgium
| | - Christel Faes
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium
| | - Niel Hens
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium
- Centre for Health Economics Research and Modelling of Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Patrick Deboosere
- Interface Demography (ID), Department of Sociology, Vrije Universiteit Brussel, Brussels, Belgium
| | - Geert Verbeke
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), KU Leuven, Leuven, Belgium
| | - Thomas Neyens
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), KU Leuven, Leuven, Belgium
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Ofori SK, Dankwa EA, Estrada EH, Hua X, Kimani TN, Wade CG, Buckee CO, Murray MB, Hedt-Gauthier BL. COVID-19 vaccination strategies in Africa: A scoping review of the use of mathematical models to inform policy. Trop Med Int Health 2024; 29:466-476. [PMID: 38740040 DOI: 10.1111/tmi.13994] [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] [Indexed: 05/16/2024]
Abstract
OBJECTIVE Mathematical models are vital tools to understand transmission dynamics and assess the impact of interventions to mitigate COVID-19. However, historically, their use in Africa has been limited. In this scoping review, we assess how mathematical models were used to study COVID-19 vaccination to potentially inform pandemic planning and response in Africa. METHODS We searched six electronic databases: MEDLINE, Embase, Web of Science, Global Health, MathSciNet and Africa-Wide NiPAD, using keywords to identify articles focused on the use of mathematical modelling studies of COVID-19 vaccination in Africa that were published as of October 2022. We extracted the details on the country, author affiliation, characteristics of models, policy intent and heterogeneity factors. We assessed quality using 21-point scale criteria on model characteristics and content of the studies. RESULTS The literature search yielded 462 articles, of which 32 were included based on the eligibility criteria. Nineteen (59%) studies had a first author affiliated with an African country. Of the 32 included studies, 30 (94%) were compartmental models. By country, most studies were about or included South Africa (n = 12, 37%), followed by Morocco (n = 6, 19%) and Ethiopia (n = 5, 16%). Most studies (n = 19, 59%) assessed the impact of increasing vaccination coverage on COVID-19 burden. Half (n = 16, 50%) had policy intent: prioritising or selecting interventions, pandemic planning and response, vaccine distribution and optimisation strategies and understanding transmission dynamics of COVID-19. Fourteen studies (44%) were of medium quality and eight (25%) were of high quality. CONCLUSIONS While decision-makers could draw vital insights from the evidence generated from mathematical modelling to inform policy, we found that there was limited use of such models exploring vaccination impacts for COVID-19 in Africa. The disparity can be addressed by scaling up mathematical modelling training, increasing collaborative opportunities between modellers and policymakers, and increasing access to funding.
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Affiliation(s)
- Sylvia K Ofori
- Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Emmanuelle A Dankwa
- Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Eve Hiyori Estrada
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Xinyi Hua
- Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia, USA
| | - Teresia N Kimani
- KAVI-Institute of Clinical Research, University of Nairobi, Nairobi, Kenya
- Center for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya
- Paul G Allen School for Global Animal Health, Washington State University, Pullman, Washington, USA
- Department of Health Services, Kiambu County, Ministry of Health Kenya, Kiambu County, Kenya
| | - Carrie G Wade
- Countway Library, Harvard School of Medicine, Boston, Massachusetts, USA
| | - Caroline O Buckee
- Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Megan B Murray
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Bethany L Hedt-Gauthier
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA
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Gonzalez-Parra G, Mahmud MS, Kadelka C. Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.04.24303726. [PMID: 38496570 PMCID: PMC10942533 DOI: 10.1101/2024.03.04.24303726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
As the world becomes ever more connected, the chance of pandemics increases as well. The recent COVID-19 pandemic and the concurrent global mass vaccine roll-out provides an ideal setting to learn from and refine our understanding of infectious disease models for better future preparedness. In this review, we systematically analyze and categorize mathematical models that have been developed to design optimal vaccine prioritization strategies of an initially limited vaccine. As older individuals are disproportionately affected by COVID-19, the focus is on models that take age explicitly into account. The lower mobility and activity level of older individuals gives rise to non-trivial trade-offs. Secondary research questions concern the optimal time interval between vaccine doses and spatial vaccine distribution. This review showcases the effect of various modeling assumptions on model outcomes. A solid understanding of these relationships yields better infectious disease models and thus public health decisions during the next pandemic.
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Affiliation(s)
- Gilberto Gonzalez-Parra
- Instituto de Matemática Multidisciplinar, Universitat Politècnica de València, València, Spain
- Department of Mathematics, New Mexico Tech, 801 Leroy Place, Socorro, 87801, NM, USA
| | - Md Shahriar Mahmud
- Department of Mathematics, Iowa State University, 411 Morrill Rd, Ames, 50011, IA, USA
| | - Claus Kadelka
- Department of Mathematics, Iowa State University, 411 Morrill Rd, Ames, 50011, IA, USA
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Park HJ, Gonsalves GS, Tan ST, Kelly JD, Rutherford GW, Wachter RM, Schechter R, Paltiel AD, Lo NC. Comparing frequency of booster vaccination to prevent severe COVID-19 by risk group in the United States. Nat Commun 2024; 15:1883. [PMID: 38448400 PMCID: PMC10917753 DOI: 10.1038/s41467-024-45549-9] [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: 07/01/2023] [Accepted: 01/26/2024] [Indexed: 03/08/2024] Open
Abstract
There is a public health need to understand how different frequencies of COVID-19 booster vaccines may mitigate the risk of severe COVID-19, while accounting for waning of protection and differential risk by age and immune status. By analyzing United States COVID-19 surveillance and seroprevalence data in a microsimulation model, here we show that more frequent COVID-19 booster vaccination (every 6-12 months) in older age groups and the immunocompromised population would effectively reduce the burden of severe COVID-19, while frequent boosters in the younger population may only provide modest benefit against severe disease. In persons 75+ years, the model estimated that annual boosters would reduce absolute annual risk of severe COVID-19 by 199 (uncertainty interval: 183-232) cases per 100,000 persons, compared to a one-time booster vaccination. In contrast, for persons 18-49 years, the model estimated that annual boosters would reduce this risk by 14 (10-19) cases per 100,000 persons. Those with prior infection had lower benefit of more frequent boosting, and immunocompromised persons had larger benefit. Scenarios with emerging variants with immune evasion increased the benefit of more frequent variant-targeted boosters. This study underscores the benefit of considering key risk factors to inform frequency of COVID-19 booster vaccines in public health guidance and ensuring at least annual boosters in high-risk populations.
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Affiliation(s)
- Hailey J Park
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Gregg S Gonsalves
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA
| | - Sophia T Tan
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, USA
| | - J Daniel Kelly
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- F.I. Proctor Foundation, University of California, San Francisco, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Institute for Global Health Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - George W Rutherford
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Institute for Global Health Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Robert M Wachter
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - A David Paltiel
- Department of Health Policy and Management and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA
| | - Nathan C Lo
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, USA.
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Falguera CC, Tandinco FD, Labarda CE, Rosaldo AG, Firmo CN, Varona RN. A Mixed-Method Study on Rural Community's Response to Public Health Emergency in the Philippines: Lessons from the First Wave of the COVID-19 Pandemic. ACTA MEDICA PHILIPPINA 2024; 58:16-26. [PMID: 38966153 PMCID: PMC11219550 DOI: 10.47895/amp.vi0.6169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/06/2024]
Abstract
Background People from rural communities are not spared from COVID-19. But implementing preventive measures and strategies can be made to control the spread. Objective This study was conducted to describe the epidemiologic situation and the healthcare capacity of the locality, determine the responses and strategies implemented in the control of COVID-19, and explain the activities performed in relation to the epidemiologic situation in Tarangnan, Samar - a low-income class municipality in the Philippines. Methods A mixed qualitative-quantitative design was employed in this study. Descriptive documentary research design through review of records from March to October 2020 was utilized. For the qualitative context, a case study design was employed whereby focus group discussions and key informant interviews using open-ended questions were performed. Results A total of 66 individuals were recorded as having COVID-19 in the municipality from March to October 2020. The first recorded confirmed cases of COVID-19 in Eastern Visayas were two adults in Tarangnan, Samar, in March 2020. Since then, additional confirmed cases have been recorded every month, but confirmed COVID-19 dramatically reduced from August to October 2020. Qualitative analysis revealed stringent COVID-19 preventive measures reflected in the confirmed case numbers. The tailwinds of the COVID-19 response include: the SARS pandemic precedent, coordination and communication, outpouring of support from other government and non-government partners, and innovative community-based approaches. The headwinds of COVID-19 response were challenges in imposing minimum health and safety precautions, stigmatization, and discrimination. Conclusion Even if challenges have arisen in implementing measures against the spread of the disease, good outcomes have been achieved through persistent good practice, positive modifications, and community-based innovations.
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Affiliation(s)
- Charlie C. Falguera
- Midwifery Department, School of Health Sciences, University of the Philippines Manila, Palo, Leyte, Philippines
| | - Filedito D. Tandinco
- Department of Medicine, School of Health Sciences, University of the Philippines Manila, Palo, Leyte, Philippines
| | - Charlie E. Labarda
- Department of Medicine, School of Health Sciences, University of the Philippines Manila, Palo, Leyte, Philippines
| | - Adelaida G. Rosaldo
- Department of Medicine, School of Health Sciences, University of the Philippines Manila, Palo, Leyte, Philippines
| | - Carmen N. Firmo
- Nursing Department, School of Health Sciences, University of the Philippines Manila, Palo, Leyte, Philippines
| | - Robelita N. Varona
- Extension Campus in South Cotabato, School of Health Sciences, University of the Philippines Manila, Koronadal City, South Cotabato, Philippines
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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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Hamilton K, Phipps DJ, Schmidt P, Bamberg S, Ajzen I. First test of the theory of reasoned goal pursuit: predicting physical activity. Psychol Health 2024; 39:24-41. [PMID: 35156467 DOI: 10.1080/08870446.2022.2026946] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 01/04/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE This study applied the theory of reasoned goal pursuit (TRGP) in predicting physical activity among Australian undergraduate students, providing the first empirical test of the model.Methods: The research comprised an elicitation study (N = 25; MAge= 25.76, SDAge= 11.33, 20 female, 5 male) to identify readily accessible procurement and approval goal beliefs and behavioural, normative, and control beliefs; and, a two-wave prospective online survey study (N = 109; MAge = 21.88, SDAge = 7.04, 63 female, 46 male) to test the tenets of the TRGP in relation to meeting World Health Organization physical activity guidelines during the COVID-19 pandemic among first year university students.Results: A linear PLS-SEM model displayed good fit-to-data, predicting 38%, 74%, and 48% of the variance in motivation, intention, and physical activity, respectively. The model supported the majority of hypothesised pattern of effects among theory constructs; in particular, the proposition that beliefs corresponding to procurement and approval goals would be more consequential to people's motivation and, thus, their intentions and behaviour, than other behavioural and normative beliefs, respectively.Conclusions: Results lend support for the TRGP and sets the agenda for future research to systematically test the proposed direct, indirect, and moderation effects for different health behaviours, populations, and contexts. Supplemental data for this article is available online at https://doi.org/10.1080/08870446.2022.2026946 .
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Affiliation(s)
- K Hamilton
- School of Applied Psychology, Griffith University, Brisbane, Australia
- Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia
- Health Sciences Research Institute, University of California, Merced, Merced, USA
| | - D J Phipps
- School of Applied Psychology, Griffith University, Brisbane, Australia
- Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia
| | - P Schmidt
- Department of Psychosomatic Medicine, University of Mainz, Mainz, Germany
- Centre for International Development and Environmental Research (ZEU), University of Giessen, Giessen, Germany
| | - S Bamberg
- Department of Social Sciences, University of Applied Sciences, Bielefeld, Germany
| | - I Ajzen
- Department of Psychological and Brain Sciences, University of Massachusetts, Amherst, Massachusetts, USA
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De Gaetano A, Bajardi P, Gozzi N, Perra N, Perrotta D, Paolotti D. Behavioral Changes Associated With COVID-19 Vaccination: Cross-National Online Survey. J Med Internet Res 2023; 25:e47563. [PMID: 37906219 PMCID: PMC10646669 DOI: 10.2196/47563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 06/05/2023] [Accepted: 09/29/2023] [Indexed: 11/02/2023] Open
Abstract
BACKGROUND During the initial phases of the vaccination campaign worldwide, nonpharmaceutical interventions (NPIs) remained pivotal in the fight against the COVID-19 pandemic. In this context, it is important to understand how the arrival of vaccines affected the adoption of NPIs. Indeed, some individuals might have seen the start of mass vaccination campaigns as the end of the emergency and, as a result, relaxed their COVID-safe behaviors, facilitating the spread of the virus in a delicate epidemic phase such as the initial rollout. OBJECTIVE The aim of this study was to collect information about the possible relaxation of protective behaviors following key events of the vaccination campaign in four countries and to analyze possible associations of these behavioral tendencies with the sociodemographic characteristics of participants. METHODS We developed an online survey named "COVID-19 Prevention and Behavior Survey" that was conducted between November 26 and December 22, 2021. Participants were recruited using targeted ads on Facebook in four different countries: Brazil, Italy, South Africa, and the United Kingdom. We measured the onset of relaxation of protective measures in response to key events of the vaccination campaign, namely personal vaccination and vaccination of the most vulnerable population. Through calculation of odds ratios (ORs) and regression analysis, we assessed the strength of association between compliance with NPIs and sociodemographic characteristics of participants. RESULTS We received 2263 questionnaires from the four countries. Participants reported the most significant changes in social activities such as going to a restaurant or the cinema and visiting relatives and friends. This is in good agreement with validated psychological models of health-related behavioral change such as the Health Belief Model, according to which activities with higher costs and perceived barriers (eg, social activities) are more prone to early relaxation. Multivariate analysis using a generalized linear model showed that the two main determinants of the drop of social NPIs were (1) having previously tested positive for COVID-19 (after the second vaccine dose: OR 2.46, 95% CI 1.73-3.49) and (2) living with people at risk (after the second vaccine dose: OR 1.57, 95% CI 1.22-2.03). CONCLUSIONS This work shows that particular caution has to be taken during vaccination campaigns. Indeed, people might relax their safe behaviors regardless of the dynamics of the epidemic. For this reason, it is crucial to maintain high compliance with NPIs to avoid hindering the beneficial effects of the vaccine.
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Affiliation(s)
- Alessandro De Gaetano
- ISI Foundation, Turin, Italy
- Aix Marseille Univ, Université de Toulon, CNRS, CPT, Marseille, France
| | - Paolo Bajardi
- ISI Foundation, Turin, Italy
- CENTAI Institute, Turin, Italy
| | - Nicolò Gozzi
- ISI Foundation, Turin, Italy
- Networks and Urban Systems Centre, University of Greenwich, London, United Kingdom
| | - Nicola Perra
- Networks and Urban Systems Centre, University of Greenwich, London, United Kingdom
- School of Mathematical Sciences, Queen Mary University of London, London, United Kingdom
| | - Daniela Perrotta
- Laboratory of Digital and Computational Demography, Max Planck Institute for Demographic Research, Rostock, Germany
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11
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Cho G, Kim YJ, Seo SH, Jang G, Lee H. Cost-effectiveness analysis of COVID-19 variants effects in an age-structured model. Sci Rep 2023; 13:15844. [PMID: 37739967 PMCID: PMC10516971 DOI: 10.1038/s41598-023-41876-x] [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: 04/29/2023] [Accepted: 09/01/2023] [Indexed: 09/24/2023] Open
Abstract
This study analyzes the impact of COVID-19 variants on cost-effectiveness across age groups, considering vaccination efforts and nonpharmaceutical interventions in Republic of Korea. We aim to assess the costs needed to reduce COVID-19 cases and deaths using age-structured model. The proposed age-structured model analyzes COVID-19 transmission dynamics, evaluates vaccination effectiveness, and assesses the impact of the Delta and Omicron variants. The model is fitted using data from the Republic of Korea between February 2021 and November 2022. The cost-effectiveness of interventions, medical costs, and the cost of death for different age groups are evaluated through analysis. The impact of different variants on cases and deaths is also analyzed, with the Omicron variant increasing transmission rates and decreasing case-fatality rates compared to the Delta variant. The cost of interventions and deaths is higher for older age groups during both outbreaks, with the Omicron outbreak resulting in a higher overall cost due to increased medical costs and interventions. This analysis shows that the daily cost per person for both the Delta and Omicron variants falls within a similar range of approximately $10-$35. This highlights the importance of conducting cost-effect analyses when evaluating the impact of COVID-19 variants.
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Affiliation(s)
- Giphil Cho
- Department of Artificial Intelligence and Software, Kangwon National University, Chuncheon, Gangwon, 25913, Republic of Korea
| | - Young Jin Kim
- Division of Data Analysis, Center for Global R&D Data Analysis, Korea Institute of Science and Technology Information (KISTI), Seoul, 02456, Republic of Korea
| | - Sang-Hyup Seo
- National Institute for Mathematical Sciences, Daejeon, 34047, Republic of Korea
| | - Geunsoo Jang
- Nonlinear Dynamics and Mathematical Application Center, Kyungpook National University, Daegu, 41566, Republic of Korea
| | - Hyojung Lee
- Department of Statistics, Kyungpook National University, Daegu, 41566, Republic of Korea.
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12
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Liu H, Han X, Lin X, Zhu X, Wei Y. Impact of vaccine measures on the transmission dynamics of COVID-19. PLoS One 2023; 18:e0290640. [PMID: 37624833 PMCID: PMC10464839 DOI: 10.1371/journal.pone.0290640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 08/12/2023] [Indexed: 08/27/2023] Open
Abstract
In many nations, efforts to prevent and control COVID-19 have been significantly impeded by the SARS-CoV-2 virus ongoing mutation. The Omicron strain, a more recent and prevalent strain, has had more significant detrimental effects in countries worldwide. To investigate the impact of the Omicron BA.2 strain on vaccine efficacy, we proposed a model with vaccination and immunological decline in this research. Then, we fitted our model based on the number of daily new instances reported by the government in Jilin and Shanghai, China. We estimated the effective reproduction number Re = 4.71 for the Jilin and Re = 3.32 for Shanghai. Additionally, we do sensitivity analysis to identify the critical factors affecting the effective reproduction number Re. It was found that vaccination rate, effectiveness rate, and declining rate had a significant effect on Re. Further, we investigate the relevant parameter thresholds that make Re lower than unity. Finally, rich numerical experiments were then carried out. We observed that even when vaccine efficiency was not high, increasing vaccination rates had a significant effect on early disease transmission, that limiting social distance was the most economical and rational measure to control the spread of disease, and that for a short period, reducing immune decline was not significant in curbing disease transmission.
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Affiliation(s)
- Hua Liu
- School of Mathematics and Computer Science, Northwest Minzu University, Lanzhou, Gansu, China
| | - Xiaotao Han
- School of Ecology and Environmental Sciences, Yunnan University, Kunming, Yunnan, China
| | - Xiaofen Lin
- School of Mathematics and Computer Science, Northwest Minzu University, Lanzhou, Gansu, China
| | - Xinjie Zhu
- School of Mathematics and Computer Science, Northwest Minzu University, Lanzhou, Gansu, China
| | - Yumei Wei
- Experimental Teaching Department, Northwest Minzu University, Lanzhou, Gansu, China
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13
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Wambua J, Loedy N, Jarvis CI, Wong KLM, Faes C, Grah R, Prasse B, Sandmann F, Niehus R, Johnson H, Edmunds W, Beutels P, Hens N, Coletti P. The influence of COVID-19 risk perception and vaccination status on the number of social contacts across Europe: insights from the CoMix study. BMC Public Health 2023; 23:1350. [PMID: 37442987 PMCID: PMC10347859 DOI: 10.1186/s12889-023-16252-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 07/06/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND The SARS-CoV-2 transmission dynamics have been greatly modulated by human contact behaviour. To curb the spread of the virus, global efforts focused on implementing both Non-Pharmaceutical Interventions (NPIs) and pharmaceutical interventions such as vaccination. This study was conducted to explore the influence of COVID-19 vaccination status and risk perceptions related to SARS-CoV-2 on the number of social contacts of individuals in 16 European countries. METHODS We used data from longitudinal surveys conducted in the 16 European countries to measure social contact behaviour in the course of the pandemic. The data consisted of representative panels of participants in terms of gender, age and region of residence in each country. The surveys were conducted in several rounds between December 2020 and September 2021 and comprised of 29,292 participants providing a total of 111,103 completed surveys. We employed a multilevel generalized linear mixed effects model to explore the influence of risk perceptions and COVID-19 vaccination status on the number of social contacts of individuals. RESULTS The results indicated that perceived severity played a significant role in social contact behaviour during the pandemic after controlling for other variables (p-value < 0.001). More specifically, participants who had low or neutral levels of perceived severity reported 1.25 (95% Confidence intervals (CI) 1.13 - 1.37) and 1.10 (95% CI 1.00 - 1.21) times more contacts compared to those who perceived COVID-19 to be a serious illness, respectively. Additionally, vaccination status was also a significant predictor of contacts (p-value < 0.001), with vaccinated individuals reporting 1.31 (95% CI 1.23 - 1.39) times higher number of contacts than the non-vaccinated. Furthermore, individual-level factors played a more substantial role in influencing contact behaviour than country-level factors. CONCLUSION Our multi-country study yields significant insights on the importance of risk perceptions and vaccination in behavioral changes during a pandemic emergency. The apparent increase in social contact behaviour following vaccination would require urgent intervention in the event of emergence of an immune escaping variant.
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Affiliation(s)
- James Wambua
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Neilshan Loedy
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Christopher I. Jarvis
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK
| | - Kerry L. M. Wong
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK
| | - Christel Faes
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Rok Grah
- European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden
| | - Bastian Prasse
- European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden
| | - Frank Sandmann
- European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden
| | - Rene Niehus
- European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden
| | - Helen Johnson
- European Centre for Disease Prevention and Control (ECDC), Gustav III:s Boulevard 40, 169 73 Solna, Sweden
- Current Address: Health Emergency Preparedness and Response Authority (HERA), European Commission, 1049, Brussels, Belgium
| | - W.John Edmunds
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT London, UK
| | - Philippe Beutels
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
- The University of New South Wales, School of Public Health and Community Medicine, Sydney, NSW 2033 Australia
| | - Niel Hens
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Pietro Coletti
- Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
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14
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Mendes JM, Coelho PS. The effect of non-pharmaceutical interventions on COVID-19 outcomes: A heterogeneous age-related generalisation of the SEIR model. Infect Dis Model 2023; 8:S2468-0427(23)00044-1. [PMID: 37366483 PMCID: PMC10287188 DOI: 10.1016/j.idm.2023.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 05/26/2023] [Accepted: 05/29/2023] [Indexed: 06/28/2023] Open
Abstract
Successive generalisations of the basic SEIR model have been proposed to accommodate the different needs of the organisations handling the SARS-CoV-2 epidemic and the assessment of the public health measures adopted and named under the common umbrella of Non-Pharmaceutical Interventions (NPIs). So far, these generalisations have not been able to assess the ability of these measures to avoid infection by the SARS-CoV-2 and thus their contribution to contain the spread of the disease. This work proposes a new generalisation of SEIR model and includes a heterogeneous and age-related generation of infections that depends both on a probability that a contact generates the transmission of the disease and a contact rate. The results show (1) thanks to the universal wearing of facial coverings, the probability that a contact provokes the transmission of the disease was reduced by at least 50% and (2) the impact of the other NPI is so significant that otherwise Portugal would have gone into a non-sustainable situation of having 80% of its population infected in the first 300 days of the pandemic. This situation would have led to a number of deaths almost twenty times higher than the number that was actually recorded by December 26th, 2020. Moreover, the results suggest that even if the requirement of universal wearing of facial coverings was adopted sooner jointly with closing workplaces and resorting to teleworking would have postponed the peak of the incidence, altought the epidemic path would have result in a number of infections hardly managed by the National Health System. Complementary, results confirm that (3) the health authorities adopted a conservative approach on the criteria to consider an infected individual not infective any longer; and (4) the most effective NPIs and stringency levels either impacting on self-protection against infection or reducing the contacts that would eventually result in infection are, in decreasing order of importance, the use of Facial coverings, Workplace closing and Stay at home requirements.
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Affiliation(s)
- Jorge M. Mendes
- NOVA Information Management School (NOVAIMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312, Lisbon, Portugal
- NOVA Cairo at the Knowledge Hub Universities, New Admnistrative Capital, Cairo, Egypt
| | - Pedro S. Coelho
- NOVA Information Management School (NOVAIMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312, Lisbon, Portugal
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15
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N'konzi JPN, Chukwu CW, Nyabadza F. Effect of time-varying adherence to non-pharmaceutical interventions on the occurrence of multiple epidemic waves: A modeling study. Front Public Health 2022; 10:1087683. [PMID: 36605240 PMCID: PMC9807866 DOI: 10.3389/fpubh.2022.1087683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 11/29/2022] [Indexed: 12/24/2022] Open
Abstract
Non-pharmaceutical interventions (NPIs) play a central role in infectious disease outbreak response and control. Their usefulness cannot be overstated, especially during the early phases of a new epidemic when vaccines and effective treatments are not available yet. These interventions can be very effective in curtailing the spread of infectious diseases when adequately implemented and sufficiently adopted by the public. However, NPIs can be very disruptive, and the socioeconomic and cultural hardships that come with their implementation interfere with both the ability and willingness of affected populations to adopt such interventions. This can lead to reduced and unsteady adherence to NPIs, making disease control more challenging to achieve. Deciphering this complex interaction between disease dynamics, NPI stringency, and NPI adoption would play a critical role in informing disease control strategies. In this work, we formulate a general-purpose model that integrates government-imposed control measures and public adherence into a deterministic compartmental epidemic model and study its properties. By combining imitation dynamics and the health belief model to encode the unsteady nature of NPI adherence, we investigate how temporal variations in NPI adherence levels affect the dynamics and control of infectious diseases. Among the results, we note the occurrence of multiple epidemic waves as a result of temporal variations in NPI adherence and a trade-off between the stringency of control measures and adherence. Additionally, our results suggest that interventions that aim at increasing public adherence to NPIs are more beneficial than implementing more stringent measures. Our findings highlight the necessity of taking the socioeconomic and cultural realities of affected populations into account when devising public health interventions.
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Affiliation(s)
- Joel-Pascal Ntwali N'konzi
- African Institute for Mathematical Sciences, Kigali, Rwanda,Maxwell Institute for Mathematical Sciences, University of Edinburgh, Heriot-Watt University, Edinburgh, United Kingdom,*Correspondence: Joel-Pascal Ntwali N'konzi
| | - Chidozie Williams Chukwu
- Department of Mathematics and Applied Mathematics, University of Johannesburg, Johannesburg, South Africa
| | - Farai Nyabadza
- Department of Mathematics and Applied Mathematics, University of Johannesburg, Johannesburg, South Africa
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16
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Najem S, Monni S, Hatoum R, Sweidan H, Faour G, Abdallah C, Ghosn N, Hassan H, Touma J. A framework for reconstructing transmission networks in infectious diseases. APPLIED NETWORK SCIENCE 2022; 7:85. [PMID: 36567737 PMCID: PMC9761645 DOI: 10.1007/s41109-022-00525-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
In this paper, we propose a general framework for the reconstruction of the underlying cross-regional transmission network contributing to the spread of an infectious disease. We employ an autoregressive model that allows to decompose the mean number of infections into three components that describe: intra-locality infections, inter-locality infections, and infections from other sources such as travelers arriving to a country from abroad. This model is commonly used in the identification of spatiotemporal patterns in seasonal infectious diseases and thus in forecasting infection counts. However, our contribution lies in identifying the inter-locality term as a time-evolving network, and rather than using the model for forecasting, we focus on the network properties without any assumption on seasonality or recurrence of the disease. The topology of the network is then studied to get insight into the disease dynamics. Building on this, and particularly on the centrality of the nodes of the identified network, a strategy for intervention and disease control is devised.
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Affiliation(s)
- Sara Najem
- Department of Physics, American University of Beirut, Beirut, Lebanon
- Center for Advanced Mathematical Sciences, American University of Beirut, Beirut, Lebanon
| | - Stefano Monni
- Department of Physics, American University of Beirut, Beirut, Lebanon
- Department of Mathematics, American University of Beirut, Beirut, Lebanon
| | - Rola Hatoum
- Center for Advanced Mathematical Sciences, American University of Beirut, Beirut, Lebanon
| | - Hawraa Sweidan
- Epidemiological Surveillance Program, Ministry of Public Health, Beirut, Lebanon
| | - Ghaleb Faour
- National Center for Remote Sensing, National Council for Scientific Research (CNRS), Beirut, Lebanon
| | - Chadi Abdallah
- National Center for Remote Sensing, National Council for Scientific Research (CNRS), Beirut, Lebanon
| | - Nada Ghosn
- Epidemiological Surveillance Program, Ministry of Public Health, Beirut, Lebanon
| | - Hamad Hassan
- Faculty of Public Health, Lebanese University, Beirut, Lebanon
| | - Jihad Touma
- Department of Physics, American University of Beirut, Beirut, Lebanon
- Center for Advanced Mathematical Sciences, American University of Beirut, Beirut, Lebanon
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17
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Wang H, Ibuka Y, Nakamura R. Mixing age and risk groups for accessing COVID-19 vaccines: a modelling study. BMJ Open 2022; 12:e061139. [PMID: 36523241 PMCID: PMC9748520 DOI: 10.1136/bmjopen-2022-061139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 11/21/2022] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE To characterise the optimal targeting of age and risk groups for COVID-19 vaccines. DESIGN Motivated by policies in Japan and elsewhere, we consider rollouts that target a mix of age and risk groups when distributing the vaccines. We identify the optimal group mix for three policy objectives: reducing deaths, reducing cases and reducing severe cases. SETTING Japan, a country where the rollout occurred over multiple stages targeting a mix of age and risk groups in each stage. PRIMARY OUTCOMES We use official statistics on COVID-19 deaths to quantify the virus transmission patterns in Japan. We then search over all possible group mix across rollout stages to identify the optimal strategies under different policy objectives and virus and vaccination conditions. RESULTS Low-risk young adults can be targeted together with the high-risk population and the elderly to optimally reduce deaths, cases and severe cases under high virus transmissibility. Compared with targeting the elderly or the high-risk population only, applying optimal group mix can further reduce deaths and severe cases by over 60%. High-efficacy vaccines can mitigate the health loss under suboptimal targeting in the rollout. CONCLUSIONS Mixing age and risk groups outperforms targeting individual groups separately, and optimising the group mix can substantially increase the health benefits of vaccines. Additional policy measures boosting vaccine efficacy are necessary under outbreaks of transmissible variants.
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Affiliation(s)
- Hongming Wang
- Hitotsubashi Institute for Advanced Study, Hitotsubashi University, Kunitachi, Japan
| | - Yoko Ibuka
- Faculty of Economics, Keio University, Minato-ku, Japan
| | - Ryota Nakamura
- Hitotsubashi Institute for Advanced Study, Hitotsubashi University, Kunitachi, Japan
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18
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Teslya A, Rozhnova G, Pham TM, van Wees DA, Nunner H, Godijk NG, Bootsma M, Kretzschmar ME. The importance of sustained compliance with physical distancing during COVID-19 vaccination rollout. COMMUNICATIONS MEDICINE 2022; 2:146. [PMID: 36402924 PMCID: PMC9675824 DOI: 10.1038/s43856-022-00207-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 10/26/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Increasing vaccination coverage against SARS-CoV-2 enabled relaxation of lockdowns in many countries in Europe. As the vaccination rollouts progressed, the public health authorities were seeking recommendations on the continuation of physical distancing measures during ongoing vaccination rollouts. Compliance with these measures was declining while more transmissible virus variants have emerged. METHODS We used a SARS-CoV-2 transmission model to investigate the feedback between compliance, infection incidence, and vaccination coverage. We quantified our findings in terms of cumulative number of new hospitalisations three and six months after the start of vaccination. RESULTS Our results suggest that the combination of fast waning compliance in non-vaccinated individuals, low compliance in vaccinated individuals, low vaccine efficacy against infection and more transmissible virus variants may result in a higher cumulative number of new hospitalisations than in a situation without vaccination. These adverse effects can be alleviated by deploying behavioural interventions that should preferably target both vaccinated and non-vaccinated individuals. The choice of the most appropriate intervention depends on vaccination rate and vaccine efficacy against infection. CONCLUSIONS Supplementary behavioural interventions aiming to boost compliance to physical distancing measures can improve the outcome of vaccination programmes, until vaccination coverage is sufficiently high. For optimal results, these interventions should be selected based on the vaccine efficacy against infection and expected vaccination rate. While we considered the dynamics of SARS-CoV-2, the qualitative effects of the interplay between infectious disease spread and behavior on the outcomes of a vaccination programme can be used as guidance in a future similar pandemic.
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Affiliation(s)
- Alexandra Teslya
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Ganna Rozhnova
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
- BioISI-Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.
- Centre for Complex System Studies (CCSS), Utrecht University, Utrecht, The Netherlands.
| | - Thi Mui Pham
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Daphne A van Wees
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Hendrik Nunner
- Centre for Complex System Studies (CCSS), Utrecht University, Utrecht, The Netherlands
- Department of Sociology / ICS, Utrecht University, Utrecht, The Netherlands
| | - Noortje G Godijk
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Martin Bootsma
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Mathematics, Faculty of Sciences, Utrecht University, Utrecht, The Netherlands
| | - Mirjam E Kretzschmar
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Centre for Complex System Studies (CCSS), Utrecht University, Utrecht, The Netherlands
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19
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Kim YR, Choi YJ, Min Y. A model of COVID-19 pandemic with vaccines and mutant viruses. PLoS One 2022; 17:e0275851. [PMID: 36279292 PMCID: PMC9591069 DOI: 10.1371/journal.pone.0275851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 09/23/2022] [Indexed: 11/07/2022] Open
Abstract
This paper proposes a compartment model (SVEIHRM model) based on a system of ordinary differential equations to simulate the pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).Emergence of mutant viruses gave rise to multiple peaks in the number of confirmed cases. Vaccine developers and WHO suggest individuals to receive multiple vaccinations (the primary and the secondary vaccinations and booster shots) to mitigate transmission of COVID-19. Taking this into account, we include compartments for multiple vaccinations and mutant viruses of COVID-19 in the model. In particular, our model considers breakthrough infection according to the antibody formation rate following multiple vaccinations. We obtain the effective reproduction numbers of the original virus, the Delta, and the Omicron variants by fitting this model to data in Korea. Additionally, we provide various simulations adjusting the daily vaccination rate and the timing of vaccination to investigate the effects of these two vaccine-related measures on the number of infected individuals. We also show that starting vaccinations early is the key to reduce the number of infected individuals. Delaying the start date requires increasing substantially the rate of vaccination to achieve similar target results. In the sensitivity analysis on the vaccination rate of Korean data, it is shown that a 10% increase (decrease) in vaccination rates can reduce (increase) the number of confirmed cases by 35.22% (82.82%), respectively.
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Affiliation(s)
- Young Rock Kim
- Major in Mathematics Education, Graduate School of Education, Hankuk University of Foreign Studies, Seoul, Republic of Korea
| | - Yong-Jae Choi
- Economics Division, Hankuk University of Foreign Studies, Seoul, Republic of Korea
| | - Youngho Min
- Major in Mathematics Education, Graduate School of Education, Hankuk University of Foreign Studies, Seoul, Republic of Korea
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20
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Pastor-Satorras R, Castellano C. The advantage of self-protecting interventions in mitigating epidemic circulation at the community level. Sci Rep 2022; 12:15950. [PMID: 36153354 PMCID: PMC9509388 DOI: 10.1038/s41598-022-20152-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 09/09/2022] [Indexed: 12/03/2022] Open
Abstract
Protecting interventions of many types (both pharmaceutical and non-pharmaceutical) can be deployed against the spreading of a communicable disease, as the worldwide COVID-19 pandemic has dramatically shown. Here we investigate in detail the effects at the population level of interventions that provide an asymmetric protection between the people involved in a single interaction. Masks of different filtration types, either protecting mainly the wearer or the contacts of the wearer, are a prominent example of these interventions. By means of analytical calculations and extensive simulations of simple epidemic models on networks, we show that interventions protecting more efficiently the adopter (e.g the mask wearer) are more effective than interventions protecting primarily the contacts of the adopter in reducing the prevalence of the disease and the number of concurrently infected individuals (“flattening the curve”). This observation is backed up by the study of a more realistic epidemic model on an empirical network representing the patterns of contacts in the city of Portland. Our results point out that promoting wearer-protecting face masks and other self-protecting interventions, though deemed selfish and inefficient, can actually be a better strategy to efficiently curtail pandemic spreading.
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Althobaity Y, Wu J, Tildesley MJ. Non-pharmaceutical interventions and their relevance in the COVID-19 vaccine rollout in Saudi Arabia and Arab Gulf countries. Infect Dis Model 2022; 7:545-560. [PMID: 36035780 PMCID: PMC9391232 DOI: 10.1016/j.idm.2022.08.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 08/11/2022] [Accepted: 08/11/2022] [Indexed: 11/20/2022] Open
Abstract
In the early stages of the pandemic, Saudi Arabia and other countries in the Arab Gulf region relied on non-pharmaceutical therapies to limit the effect of the pandemic, much like other nations across the world. In comparison to other nations in the area or globally, these interventions were successful at lowering the healthcare burden. This was accomplished via the deterioration of the economy, education, and a variety of other societal activities. By the end of 2020, the promise of effective vaccinations against SARS-CoV-2 have been realized, and vaccination programs have begun in developed countries, followed by the rest of the world. Despite this, there is still a long way to go in the fight against the disease. In order to explore disease transmission, vaccine rollout and prioritisation, as well as behavioural dynamics, we relied on an age-structured compartmental model. We examine how individual and social behaviour changes in response to the initiation of vaccination campaigns and the relaxation of non-pharmacological treatments. Overall, vaccination remains the most effective method of containing the disease and resuming normal life. Additionally, we evaluate several vaccination prioritisation schemes based on age group, behavioural responses, vaccine effectiveness, and vaccination rollout speed. We applied our model to four Arab Gulf nations (Saudi Arabia, Bahrain, the United Arab Emirates, and Oman), which were chosen for their low mortality rate compared to other countries in the region or worldwide, as well as their demographic and economic settings. We fitted the model using actual pandemic data in these countries. Our results suggest that vaccinations focused on the elderly and rapid vaccine distribution are critical for reducing disease resurgence. Our result also reinforces the cautious note that early relaxation of safety measures may compromise the vaccine's short-term advantages.
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Affiliation(s)
- Yehya Althobaity
- The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7AL, United Kingdom
- Department of Mathematics, Taif University, Taif, P. O. Box 11099, Saudi Arabia
| | - Jianhong Wu
- Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, Ontario, M3J 1P3, Canada
| | - Michael J. Tildesley
- The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, CV4 7AL, United Kingdom
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22
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Duan M, Jin Z. The heterogeneous mixing model of COVID-19 with interventions. J Theor Biol 2022; 553:111258. [PMID: 36041504 PMCID: PMC9420055 DOI: 10.1016/j.jtbi.2022.111258] [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] [Received: 06/30/2022] [Revised: 08/17/2022] [Accepted: 08/18/2022] [Indexed: 12/15/2022]
Abstract
The emergence of mutant strains of COVID-19 reduces the effectiveness of vaccines in preventing infection, but remains effective in preventing severe illness and death. This paper established a heterogeneous mixing model of age groups with pharmaceutical and non-pharmaceutical interventions by analyzing the transmission mechanism of breakthrough infection caused by the heterogeneity of protection period under the action of vaccine-preventable infection with the original strain. The control reproduction number Rc of the system is analyzed, and the existence and stability of equilibrium are given by the comparison principle. Numerical simulation was conducted to evaluate the vaccination program and intervention measures in the customized scenario, demonstrating that the group-3 coverage rate p3 plays a key role in Rc. It is proposed that accelerating the rate of admission and testing is conducive to epidemic control by further fitting data of COVID-19 transmission in real scenarios. The findings provide a general modeling idea for the emergence of new vaccines to prevent infection by mutant strains, as well as a solid theoretical foundation for mainland China to formulate future vaccination strategies for new vaccines. This manuscript was submitted as part of a theme issue on “Modelling COVID-19 and Preparedness for Future Pandemics”.
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Affiliation(s)
- Moran Duan
- School of Data Science and Technology, North University of China, Taiyuan 030051, Shanxi, China; Complex Systems Research Center, Shanxi University, Taiyuan 030006, Shanxi, China
| | - Zhen Jin
- Complex Systems Research Center, Shanxi University, Taiyuan 030006, Shanxi, China; Shanxi Key Laboratory of Mathematical Technique and Big Data Analysis on Disease Control and Prevention, Taiyuan 030006, Shanxi, China.
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23
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Tibbels NJ, Dosso A, Kra KW, Gbeke KD, Coffi G, Ngoran AR, Niamke JL, Nana M, Benié W, Hendrickson ZM, Naugle DA. "In our culture, if you quarantine someone, you stigmatize them": Qualitative insights on barriers to observing COVID-19 prevention behaviors in Côte d'Ivoire. PLOS GLOBAL PUBLIC HEALTH 2022; 2:e0000489. [PMID: 36962697 PMCID: PMC10022382 DOI: 10.1371/journal.pgph.0000489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 07/13/2022] [Indexed: 11/19/2022]
Abstract
While vaccines are now authorized for use against the SARS-CoV2 virus, they remain inaccessible for much of the world and widespread hesitancy persists. Ending the COVID-19 pandemic depends on continued prevention behaviors such as mask wearing, distancing, hand hygiene, and limiting large gatherings. Research in low- and middle-income countries has focused on the prevalence of adherence and demographic determinants, but there is a need for a nuanced understanding of why people do or do not practice a given prevention behavior. The Breakthrough ACTION project led by Johns Hopkins Center for Communication Programs conducted a qualitative study in November 2020 in Côte d'Ivoire to explore people's experience with and perceptions of the COVID-19 pandemic. We conducted 24 focus group discussions and 29 in-depth interviews with members of the general population and health providers. This analysis explores barriers and facilitators to seven recommended prevention behaviors with a particular focus on response efficacy, self-efficacy, and social norms. We found these constructs to be salient for participants who generally felt that the behaviors were useful for preventing COVID-19 but were difficult to practice for a variety of reasons. The perception that COVID-19 prevention behaviors were anti-social emerged as a key theme. Behavior change interventions must reframe the recommended behaviors as pro-social, while making them very easy to practice by removing social and structural barriers such as the expense or inaccessibility of masks and hand sanitizer.
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Affiliation(s)
- Natalie Jean Tibbels
- Center for Communication Programs, Health, Behavior & Society Department, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Abdul Dosso
- Center for Communication Programs-Côte d’Ivoire, Johns Hopkins Bloomberg School of Public Health, Abidjan, Côte d’Ivoire
| | - Kouamé Walter Kra
- Department of Sociology, Université Alassane Ouattara, Bouaké, Côte d’Ivoire
| | | | - Gervais Coffi
- Department of Sociology, Université Alassane Ouattara, Bouaké, Côte d’Ivoire
| | - Alex Romeo Ngoran
- Department of Sociology, Université Alassane Ouattara, Bouaké, Côte d’Ivoire
| | - Jean Louis Niamke
- Department of Sociology, Université de Cocody, Abidjan, Côte d’Ivoire
| | - Marjorie Nana
- Center for Communication Programs, Health, Behavior & Society Department, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - William Benié
- Center for Communication Programs-Côte d’Ivoire, Johns Hopkins Bloomberg School of Public Health, Abidjan, Côte d’Ivoire
| | - Zoé Mistrale Hendrickson
- Center for Communication Programs, Health, Behavior & Society Department, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Danielle Amani Naugle
- Center for Communication Programs, Health, Behavior & Society Department, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
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24
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Swart LA, Taliep N, Ismail G, van Niekerk A. The converging influence of social, economic and psychological factors on public responsiveness to the COVID-19 pandemic in South Africa. BMC Public Health 2022; 22:1451. [PMID: 35907812 PMCID: PMC9338645 DOI: 10.1186/s12889-022-13845-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 07/18/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND This study assessed the influence of social, economic, and psychological factors on South African's responsiveness to the COVID-19 pandemic. Although the South African government responded quickly to manage the pandemic, the strict lockdown placed a significant burden on the population. Understanding the converging influence of social, economic, and psychological factors on the population's responsiveness is important for improving people's cooperation in controlling COVID-19 and for supporting individuals and communities during the ongoing and future pandemics. METHODS Using data collected from a national telephonic survey (December 2020 to March 2021), we assessed whether selected social, economic and psychological factors were related to: 1) adoption of COVID-19 behavioural measures (hand hygiene, wearing of face masks, and physical distancing), and 2) adherence to government restrictions on movement. RESULTS South Africans were highly responsive to the pandemic with respondents generally reporting that they very often engaged in the protective behaviours and often to very often adhered to government restriction on movement. However, those from the white population group; with a higher education; living in uncrowded households; who perceived less vulnerability to contracting COVID-19; supported the measures; trusted the scientists; thought the measures by government were implemented fairly and fairly enforced by the police; felt more anxious, sad, hopeless, isolated, angry or had trouble sleeping; inclined to engage in coping behaviour, were more likely to adopt COVID-19 protective behaviours. Furthermore, females, those with a lower education, those less likely to have experienced poverty since the beginning of lockdown; who perceived greater vulnerability to COVID-19, trusted government, and were more supportive of the behavioural measures were more likely to adhere to the restrictions of movement. CONCLUSIONS Strengthening the South African population's responsiveness to the pandemic requires supporting those living in poor socioeconomic circumstances, promoting trust in the scientific evidence, and ensuring that the measures by government are perceived to be fairly implemented and fairly enforced by the police. Due to the impact on livelihoods, restrictions of movement should only be considered if necessary, and this will require trust and confidence in government and strategies to support those experiencing financial hardship.
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Affiliation(s)
- Lu-Anne Swart
- Institute for Social and Health Sciences, University of South Africa, Johannesburg, South Africa.
- Masculinity and Health Research Unit, South African Medical Research Council and University of South Africa, Cape Town, South Africa.
| | - Naiema Taliep
- Institute for Social and Health Sciences, University of South Africa, Johannesburg, South Africa
- Masculinity and Health Research Unit, South African Medical Research Council and University of South Africa, Cape Town, South Africa
| | - Ghouwa Ismail
- Institute for Social and Health Sciences, University of South Africa, Johannesburg, South Africa
- Masculinity and Health Research Unit, South African Medical Research Council and University of South Africa, Cape Town, South Africa
| | - Ashley van Niekerk
- Institute for Social and Health Sciences, University of South Africa, Johannesburg, South Africa
- Masculinity and Health Research Unit, South African Medical Research Council and University of South Africa, Cape Town, South Africa
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25
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Riding the Pandemic Waves—Lessons to Be Learned from the COVID-19 Crisis Management in Romania. Trop Med Infect Dis 2022; 7:tropicalmed7070122. [PMID: 35878134 PMCID: PMC9316926 DOI: 10.3390/tropicalmed7070122] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 06/26/2022] [Accepted: 06/27/2022] [Indexed: 12/04/2022] Open
Abstract
In our analysis, we assessed how Romania dealt with the numerous challenges presented by the COVID-19 pandemic during 2021. In that year, the government had to deal with two waves of COVID-19 pandemics caused by the new variants, the low vaccination rate of the population, the overload of the healthcare system and political instability at the same time. Based on publicly available databases and international literature, we evaluated government measures aimed at reducing the spread of the pandemic and ensure the operation of the healthcare workforce and infrastructure. In addition, we evaluated measures to provide health services effectively and the government’s pandemic responses regarding excess mortality in 2021. In the absence of a complex monitoring system, limited information was available on the spread of the pandemic or the various risk factors at play. Due to incomplete and inadequate management systems, the government was unable to implement timely and adequate measures. Our analysis concludes that the management of a pandemic can only be successful if data are collected and evaluated using complex systems in a timely manner, and if members of society adhere to clearly communicated government measures due to high levels of trust in the government.
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26
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Zhang Z, Liu C, Nunkoo R, Sunnassee VA, Chen X. Rethinking Lockdown Policies in the Pre-Vaccine Era of COVID-19: A Configurational Perspective. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:7142. [PMID: 35742409 PMCID: PMC9223109 DOI: 10.3390/ijerph19127142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/04/2022] [Accepted: 06/08/2022] [Indexed: 12/10/2022]
Abstract
The significance of lockdown policies for controlling the COVID-19 pandemic is widely recognized. However, most studies have focused on individual lockdown measures. The effectiveness of lockdown policy combinations has not been examined from a configurational perspective. This research applies fuzzy-set qualitative comparative analysis (fsQCA) to examine different lockdown policy combinations associated with high-epidemic situations in 84 countries. A high-epidemic situation can occur through three different "weak-confined" patterns of lockdown policy combinations. The findings demonstrate that a combination of lockdown policies is more successful than any single lockdown policy, whereas the absence of several key measures in policy combinations can lead to a high-epidemic situation. The importance of international travel controls can become obscured when they are the only measures adopted, and a high-epidemic situation can still arise where restrictions are placed on international travel but not on public transport or when workplaces are closed but schools remain open.
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Affiliation(s)
- Ziang Zhang
- School of Geography, Nanjing Normal University, Nanjing 210023, China;
| | - Chao Liu
- Faculty of Hospitality & Tourism Management, Macau University of Science and Technology, Taipa, Macau 999078, China
| | - Robin Nunkoo
- Department of Management, University of Mauritius, Reduit MU 80837, Mauritius;
- School of Tourism and Hospitality, University of Johannesburg, P.O. Box 524, Auckland Park 2006, South Africa
- Griffith Institute for Tourism, Griffith University, Gold Coast, QLD 4222, Australia
- Copenhagen Business School, Porcelaenshaven 18A, DK-2000 Frederiksberg, Denmark
| | - Vivek A. Sunnassee
- Westminster Business School, University of Westminster, 35 Marylebone Road, London NW1 5LS, UK;
| | - Xiaoyan Chen
- School of Humanities, Jiangsu University of Technology, Changzhou 213001, China;
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27
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Coccia M. COVID-19 pandemic over 2020 (withlockdowns) and 2021 (with vaccinations): similar effects for seasonality and environmental factors. ENVIRONMENTAL RESEARCH 2022; 208:112711. [PMID: 35033552 PMCID: PMC8757643 DOI: 10.1016/j.envres.2022.112711] [Citation(s) in RCA: 65] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/04/2022] [Accepted: 01/06/2022] [Indexed: 05/19/2023]
Abstract
How is the dynamics of Coronavirus Disease 2019 (COVID-19) in 2020 with an health policy of full lockdowns and in 2021 with a vast campaign of vaccinations? The present study confronts this question here by developing a comparative analysis of the effects of COVID-19 pandemic between April-September 2020 (based upon strong control measures) and April-September 2021 (focused on health policy of vaccinations) in Italy, which was one of the first European countries to experience in 2020 high numbers of COVID-19 related infected individuals and deaths and in 2021 Italy has a high share of people fully vaccinated against COVID-19 (>89% of population aged over 12 years in January 2022). Results suggest that over the period under study, the arithmetic mean of confirmed cases, hospitalizations of people and admissions to Intensive Care Units (ICUs) in 2020 and 2021 is significantly equal (p-value<0.01), except fatality rate. Results suggest in December 2021 lower hospitalizations, admissions to ICUs, and fatality rate of COVID-19 than December 2020, though confirmed cases and mortality rates are in 2021 higher than 2020, and likely converging trends in the first quarter of 2022. These findings reveal that COVID-19 pandemic is driven by seasonality and environmental factors that reduce the negative effects in summer period, regardless control measures and/or vaccination campaigns. These findings here can be of benefit to design health policy responses of crisis management considering the growth of COVID-19 pandemic in winter months having reduced temperatures and low solar radiations ( COVID-19 has a behaviour of influenza-like illness). Hence, findings here suggest that strategies of prevention and control of infectious diseases similar to COVID-19 should be set up in summer months and fully implemented during low-solar-irradiation periods (autumn and winter period).
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Affiliation(s)
- Mario Coccia
- CNR, National Research Council of Italy - Via Real Collegio, n. 30 (Collegio Carlo Alberto), 10024, Moncalieri (TO), Italy.
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28
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Vickers DM, Baral S, Mishra S, Kwong JC, Sundaram M, Katz A, Calzavara A, Maheu-Giroux M, Buckeridge DL, Williamson T. Stringency of containment and closures on the growth of SARS-CoV-2 in Canada prior to accelerated vaccine roll-out. Int J Infect Dis 2022; 118:73-82. [PMID: 35202783 PMCID: PMC8863413 DOI: 10.1016/j.ijid.2022.02.030] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 02/12/2022] [Accepted: 02/14/2022] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Many studies have examined the effectiveness of non-pharmaceutical interventions (NPIs) on SARS-CoV-2 transmission worldwide. However, less attention has been devoted to understanding the limits of NPIs across the course of the pandemic and along a continuum of their stringency. In this study, we explore the relationship between the growth of SARS-CoV-2 cases and an NPI stringency index across Canada before the accelerated vaccine roll-out. METHODS We conducted an ecological time-series study of daily SARS-CoV-2 case growth in Canada from February 2020 to February 2021. Our outcome was a back-projected version of the daily growth ratio in a stringency period (i.e., a 10-point range of the stringency index) relative to the last day of the previous period. We examined the trends in case growth using a linear mixed-effects model accounting for stringency period, province, and mobility in public domains. RESULTS Case growth declined rapidly by 20-60% and plateaued within the first month of the first wave, irrespective of the starting values of the stringency index. When stringency periods increased, changes in case growth were not immediate and were faster in the first wave than in the second. In the first wave, the largest decreasing trends from our mixed effects model occurred in both early and late stringency periods, depending on the province, at a geometric mean index value of 30⋅1 out of 100. When compared with the first wave, the stringency periods in the second wave possessed little association with case growth. CONCLUSIONS The minimal association in the first wave, and the lack thereof in the second, is compatible with the hypothesis that NPIs do not, per se, lead to a decline in case growth. Instead, the correlations we observed might be better explained by a combination of underlying behaviors of the populations in each province and the natural dynamics of SARS-CoV-2. Although there exist alternative explanations for the equivocal relationship between NPIs and case growth, the onus of providing evidence shifts to demonstrating how NPIs can consistently have flat association, despite incrementally high stringency.
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Affiliation(s)
- David M. Vickers
- Centre for Health Informatics and Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada,Corresponding author: David M. Vickers, PhD, Centre for Health Informatics, 5th Floor, TRW Building, University of Calgary, 3280 Hospital Drive NW, Calgary, AB, T2N 4Z6, Canada, Phone: +001 403 771 6893
| | - Stefan Baral
- Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, United States
| | - Sharmistha Mishra
- MAP Centre for Urban Health Solutions, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada,Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jeffrey C. Kwong
- ICES, Toronto, ON, Canada,Public Health Ontario, ON, Canada,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada,Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, ON, Canada,Department of Family and Community Medicine, University of Toronto, ON, Canada
| | - Maria Sundaram
- ICES, Toronto, ON, Canada,Centre for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Alan Katz
- Departments of Community Health Sciences and Family Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | | | - Mathieu Maheu-Giroux
- Department of Epidemiology, Biostatistics, and Occupational Health, School of Population and Global Health, McGill University, Montréal, QC, Canada
| | - David L. Buckeridge
- Department of Epidemiology, Biostatistics, and Occupational Health, School of Population and Global Health, McGill University, Montréal, QC, Canada
| | - Tyler Williamson
- Centre for Health Informatics and Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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29
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Delussu F, Tizzoni M, Gauvin L. Evidence of pandemic fatigue associated with stricter tiered COVID-19 restrictions. PLOS DIGITAL HEALTH 2022; 1:e0000035. [PMID: 36812519 PMCID: PMC9931343 DOI: 10.1371/journal.pdig.0000035] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Accepted: 04/04/2022] [Indexed: 11/18/2022]
Abstract
Despite the availability of effective vaccines against SARS-CoV-2, non-pharmaceutical interventions remain an important part of the effort to reduce viral circulation caused by emerging variants with the capability of evading vaccine-induced immunity. With the aim of striking a balance between effective mitigation and long-term sustainability, several governments worldwide have adopted systems of tiered interventions, of increasing stringency, that are calibrated according to periodic risk assessments. A key challenge remains in quantifying temporal changes in adherence to interventions, which can decrease over time due to pandemic fatigue, under such kind of multilevel strategies. Here, we examine whether there was a reduction in adherence to tiered restrictions that were imposed in Italy from November 2020 through May 2021, and in particular we assess whether temporal trends in adherence depended on the intensity of the restrictions adopted. We analyzed daily changes in movements and in residential time, combining mobility data with the restriction tier enforced in the Italian regions. Through mixed-effects regression models, we identified a general trend of reduction in adherence and an additional effect of faster waning associated with the most stringent tier. We estimated both effects being of the same order of magnitude, suggesting that adherence decreased twice as fast during the strictest tier as in the least stringent one. Our results provide a quantitative measure of behavioral responses to tiered interventions-a metric of pandemic fatigue-that can be integrated into mathematical models to evaluate future epidemic scenarios.
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30
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BUONOMO BRUNO, DELLA MARCA ROSSELLA, SHARBAYTA SILESHISINTAYEHU. A BEHAVIORAL CHANGE MODEL TO ASSESS VACCINATION-INDUCED RELAXATION OF SOCIAL DISTANCING DURING AN EPIDEMIC. J BIOL SYST 2022. [DOI: 10.1142/s0218339022500085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The success of mass vaccination campaigns may be jeopardized by human risky behaviors. For example, high level of vaccination coverage may induce early relaxation of social distancing. In this paper, we focus on the mutual influence between the decline in prevalence, due to the rise in the overall immunization coverage, and the consequent decrease in the compliance to social distancing measures. We consider an epidemic model where both the vaccination rate and the disease transmission rate are influenced by human behavior, which in turn depends on the current and past information about the spread of the disease. We highlight the impact of the information-related parameters on the transient and asymptotic behavior of the system that is on the early stage of the epidemic and its final outcome. Among the main results, we evidence that sustained oscillations may be triggered by the behavioral memory in the prevalence-dependent vaccination rate. However, the relaxation of social distancing may induce a switch from a cyclic regime to damped oscillations.
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Affiliation(s)
- BRUNO BUONOMO
- Department of Mathematics and Applications, University of Naples Federico II, via Cintia, I-80126 Naples, Italy
| | - ROSSELLA DELLA MARCA
- Mathematics Area, SISSA – International School for Advanced Studies, via Bonomea 265, I-34136 Trieste, Italy
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31
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Faucher B, Assab R, Roux J, Levy-Bruhl D, Tran Kiem C, Cauchemez S, Zanetti L, Colizza V, Boëlle PY, Poletto C. Agent-based modelling of reactive vaccination of workplaces and schools against COVID-19. Nat Commun 2022; 13:1414. [PMID: 35301289 PMCID: PMC8931017 DOI: 10.1038/s41467-022-29015-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 02/17/2022] [Indexed: 12/30/2022] Open
Abstract
With vaccination against COVID-19 stalled in some countries, increasing vaccine accessibility and distribution could help keep transmission under control. Here, we study the impact of reactive vaccination targeting schools and workplaces where cases are detected, with an agent-based model accounting for COVID-19 natural history, vaccine characteristics, demographics, behavioural changes and social distancing. In most scenarios, reactive vaccination leads to a higher reduction in cases compared with non-reactive strategies using the same number of doses. The reactive strategy could however be less effective than a moderate/high pace mass vaccination program if initial vaccination coverage is high or disease incidence is low, because few people would be vaccinated around each case. In case of flare-ups, reactive vaccination could better mitigate spread if it is implemented quickly, is supported by enhanced test-trace-isolate and triggers an increased vaccine uptake. These results provide key information to plan an adaptive vaccination rollout.
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Affiliation(s)
- Benjamin Faucher
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris, France
| | - Rania Assab
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris, France
| | - Jonathan Roux
- Univ Rennes, EHESP, CNRS, ARENES-UMR 6051, F-35000, Rennes, France
| | | | - Cécile Tran Kiem
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université de Paris, UMR2000, CNRS, Paris, France
- Collège Doctoral, Sorbonne Université, Paris, France
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université de Paris, UMR2000, CNRS, Paris, France
| | | | - Vittoria Colizza
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris, France
- Tokyo Tech World Research Hub Initiative (WRHI), Tokyo Institute of Technology, Tokyo, Japan
| | - Pierre-Yves Boëlle
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris, France
| | - Chiara Poletto
- Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris, France.
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32
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Large B, Gandhi S. The Importance of Theories and Models in the Prevention and Control of COVID-19. AMERICAN JOURNAL OF HEALTH EDUCATION 2022. [DOI: 10.1080/19325037.2021.2019623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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33
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d’Andrea V, Gallotti R, Castaldo N, De Domenico M. Individual risk perception and empirical social structures shape the dynamics of infectious disease outbreaks. PLoS Comput Biol 2022; 18:e1009760. [PMID: 35171901 PMCID: PMC8849607 DOI: 10.1371/journal.pcbi.1009760] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 12/15/2021] [Indexed: 12/20/2022] Open
Abstract
The dynamics of a spreading disease and individual behavioral changes are entangled processes that have to be addressed together in order to effectively manage an outbreak. Here, we relate individual risk perception to the adoption of a specific set of control measures, as obtained from an extensive large-scale survey performed via Facebook-involving more than 500,000 respondents from 64 countries-showing that there is a "one-to-one" relationship between perceived epidemic risk and compliance with a set of mitigation rules. We then develop a mathematical model for the spreading of a disease-sharing epidemiological features with COVID-19-that explicitly takes into account non-compliant individual behaviors and evaluates the impact of a population fraction of infectious risk-deniers on the epidemic dynamics. Our modeling study grounds on a wide set of structures, including both synthetic and more than 180 real-world contact patterns, to evaluate, in realistic scenarios, how network features typical of human interaction patterns impact the spread of a disease. In both synthetic and real contact patterns we find that epidemic spreading is hindered for decreasing population fractions of risk-denier individuals. From empirical contact patterns we demonstrate that connectivity heterogeneity and group structure significantly affect the peak of hospitalized population: higher modularity and heterogeneity of social contacts are linked to lower peaks at a fixed fraction of risk-denier individuals while, at the same time, such features increase the relative impact on hospitalizations with respect to the case where everyone correctly perceive the risks.
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Affiliation(s)
| | | | | | - Manlio De Domenico
- CoMuNe Lab, Fondazione Bruno Kessler, Trento, Italy
- Department of Physics and Astronomy “G. Galilei”, University of Padova, Padova, Italy
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Cuschieri S, Hatziyianni A, Kantaris M, Kontemeniotis A, Theodorou M, Pallari E. Same Pandemic Yet Different COVID-19 Vaccination Roll-Out Rates in Two Small European Islands: A Comparison between Cyprus and Malta. Healthcare (Basel) 2022; 10:222. [PMID: 35206836 PMCID: PMC8872547 DOI: 10.3390/healthcare10020222] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 01/04/2022] [Accepted: 01/12/2022] [Indexed: 12/02/2022] Open
Abstract
A mass vaccination strategy is estimated to be the long-term solution to control COVID-19. Different European countries have committed to vaccination strategies with variable population inoculation rates. We sought to investigate the extent to which the COVID-19 vaccination strategies, inoculation rate, and COVID-19 outcome differ between Cyprus and Malta. Data were obtained from the Ministry of Health websites and COVID-19 dashboards, while vaccination data were obtained from the European Centre for Disease Prevention and Control until mid-June, 2021. Comparative assessments were performed between the two countries using Microsoft® Excel for Mac, Version 16.54. Both islands took part in the European Union's advanced purchase agreement and received their first batch of vaccines on 27 December 2020. The positivity rate and mortality between December and June differs between the two countries (average positivity rate Cyprus 1.34, Malta 3.37 p ≤ 0.01; average mortality Cyprus 7.29, Malta 9.68 p ≤ 0.01). Both the positivity rate and mortality for Cyprus declined due to strict public health measures and vaccination roll-out in early January (positivity rate by 95% and mortality by 58%). In contrast, for Malta, there was a sharp increase (64% p ≤ 0.01) with almost no public health restrictions in place and soaring cases during the Christmas and Carnival period until March, when lockdown measures were re-introduced. A distinctive difference between Cyprus and Malta in positivity rate (14 per 100,000 population; p ≤ 0.01) can also be observed between January and mid-April 2021. However, from April onwards it is evident that the positivity rate and mortality decline (positivity rate Cyprus by 82%, Malta by 95%; mortality Cyprus by 90%, Malta by 95%, p ≤ 0.01, respectively) in both countries as the vaccination roll-outs progressed, covering about 58.93% of the Maltese population, while Cyprus had fully inoculated about 38.03% of its population. The vaccine strategies and vaccination rates were similar for both countries; yet Malta had the fastest vaccine roll-out. Reluctancy to get vaccinated, significant differences in the vaccination appointment scheduling system, and the freedom of vaccination choice for the citizens in Cyprus may have contributed to a delayed vaccination roll-out. These potential contributing factors should be acknowledged and considered for future vaccination programs and potential COVID-19 boosters.
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Affiliation(s)
- Sarah Cuschieri
- Department of Anatomy, Faculty of Medicine and Surgery, University of Malta, MSD 2080 Msida, Malta;
| | - Amalia Hatziyianni
- Ammochostos General Hospital, 25 Christou Kkeli, Paralimni 5310, Cyprus;
| | - Marios Kantaris
- Health & Social Services Research Centre, American University of Cyprus, Larnaca 6019, Cyprus;
| | | | - Mamas Theodorou
- Health Policy, Open University of Cyprus, Latsia 2220, Cyprus;
| | - Elena Pallari
- MRC Clinical Trials Unit, University College London, London WC1V 6LJ, UK
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35
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Vasiliauskaite V, Antulov-Fantulin N, Helbing D. On some fundamental challenges in monitoring epidemics. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2022; 380:20210117. [PMID: 34802270 PMCID: PMC8607144 DOI: 10.1098/rsta.2021.0117] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 07/13/2021] [Indexed: 05/22/2023]
Abstract
Epidemic models often reflect characteristic features of infectious spreading processes by coupled nonlinear differential equations considering different states of health (such as susceptible, infectious or recovered). This compartmental modelling approach, however, delivers an incomplete picture of the dynamics of epidemics, as it neglects stochastic and network effects, and the role of the measurement process, on which the estimation of epidemiological parameters and incidence values relies. In order to study the related issues, we combine established epidemiological spreading models with a measurement model of the testing process, considering the problems of false positives and false negatives as well as biased sampling. Studying a model-generated ground truth in conjunction with simulated observation processes (virtual measurements) allows one to gain insights into the fundamental limitations of purely data-driven methods when assessing the epidemic situation. We conclude that epidemic monitoring, simulation, and forecasting are wicked problems, as applying a conventional data-driven approach to a complex system with nonlinear dynamics, network effects and uncertainty can be misleading. Nevertheless, some of the errors can be corrected for, using scientific knowledge of the spreading dynamics and the measurement process. We conclude that such corrections should generally be part of epidemic monitoring, modelling and forecasting efforts. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.
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Affiliation(s)
| | | | - Dirk Helbing
- Computational Social Science, ETH Zürich, Zürich, Switzerland
- Complexity Science Hub Vienna, Wien, Austria
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36
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van Goudoever JB, Spatz DL, Hoban R, Dumitriu D, Gyamfi-Bannerman C, Berns M, McKechnie L, Davanzo R. Updating Clinical Practices to Promote and Protect Human Milk and Breastfeeding in a COVID-19 Era. Front Pediatr 2022; 10:867540. [PMID: 35558372 PMCID: PMC9086708 DOI: 10.3389/fped.2022.867540] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 03/30/2022] [Indexed: 12/23/2022] Open
Abstract
The COVID-19 pandemic has impacted breastfeeding and lactation globally, with clinical practices implemented early in the pandemic being mostly anti-breastfeeding, e.g., separation of mothers from their infants, and not evidence based. As the pandemic has progressed, evidence has emerged reconfirming the value of human milk and the importance of protecting and supporting breastfeeding, especially the initiation of lactation. However, it is clear that COVID-19 has changed the clinical care paradigm around breastfeeding and lactation support and, as such, it is imperative that practices adapt and evolve to maintain the emphasis on lactation support. We participated in a round table conference aiming to rescue and develop protocols and practices that support breastfeeding during the COVID-19 pandemic. One key area to target will be to maximize the use of the antenatal period. The early identification of lactation risk factors together with the development of person-centered methods to deliver breastfeeding information and education to parents-to-be will be critical. In addition, the establishment of a hospital culture that values breastfeeding and prioritizes the use of human milk will be integral for the motivation of health care professionals. That culture will also support active management of the initiation of lactation and the development of a 'back-up plan' toolkit to support the mother experiencing lactation difficulties. Post-discharge support will also be crucial with the development of both in-person and virtual lactation support programs, in particular for the immediate post-discharge period to benefit mothers who experience an early discharge process. These measures will allow for a new, adapted framework of practice that acknowledges the current COVID-19 paradigm and maintains the emphasis on the need to protect and support breastfeeding and the use of human milk.
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Affiliation(s)
| | - Diane L Spatz
- University of Pennsylvania School of Nursing & Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Rebecca Hoban
- The Hospital for Sick Children (SickKids), University of Toronto, Toronto, ON, Canada
| | - Dani Dumitriu
- Columbia University Irving Medical Center, New York, NY, United States
| | | | - Monika Berns
- Charité - Universitätsmedizin, Klink für Neonatologie, Berlin, Germany
| | - Liz McKechnie
- Leeds Centre for Newborn Care, Leeds Teaching Hospitals, Leeds, United Kingdom
| | - Riccardo Davanzo
- Institute for Maternal and Child Health Institute, IRCCS "Burlo Garofolo", Trieste, Italy
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37
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Saadi N, Chi YL, Ghosh S, Eggo RM, McCarthy CV, Quaife M, Dawa J, Jit M, Vassall A. Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review. BMC Med 2021; 19:318. [PMID: 34847950 PMCID: PMC8632563 DOI: 10.1186/s12916-021-02190-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 11/17/2021] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND How best to prioritise COVID-19 vaccination within and between countries has been a public health and an ethical challenge for decision-makers globally. We reviewed epidemiological and economic modelling evidence on population priority groups to minimise COVID-19 mortality, transmission, and morbidity outcomes. METHODS We searched the National Institute of Health iSearch COVID-19 Portfolio (a database of peer-reviewed and pre-print articles), Econlit, the Centre for Economic Policy Research, and the National Bureau of Economic Research for mathematical modelling studies evaluating the impact of prioritising COVID-19 vaccination to population target groups. The first search was conducted on March 3, 2021, and an updated search on the LMIC literature was conducted from March 3, 2021, to September 24, 2021. We narratively synthesised the main study conclusions on prioritisation and the conditions under which the conclusions changed. RESULTS The initial search identified 1820 studies and 36 studies met the inclusion criteria. The updated search on LMIC literature identified 7 more studies. 43 studies in total were narratively synthesised. 74% of studies described outcomes in high-income countries (single and multi-country). We found that for countries seeking to minimise deaths, prioritising vaccination of senior adults was the optimal strategy and for countries seeking to minimise cases the young were prioritised. There were several exceptions to the main conclusion, notably that reductions in deaths could be increased if groups at high risk of both transmission and death could be further identified. Findings were also sensitive to the level of vaccine coverage. CONCLUSION The evidence supports WHO SAGE recommendations on COVID-19 vaccine prioritisation. There is, however, an evidence gap on optimal prioritisation for low- and middle-income countries, studies that included an economic evaluation, and studies that explore prioritisation strategies if the aim is to reduce overall health burden including morbidity.
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Affiliation(s)
- Nuru Saadi
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK.
| | - Y-Ling Chi
- International Decision Support Initiative, Center for Global Development, London, UK
| | - Srobana Ghosh
- International Decision Support Initiative, Center for Global Development, London, UK
| | - Rosalind M Eggo
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Ciara V McCarthy
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Matthew Quaife
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Jeanette Dawa
- Washington State University - Global Health Program, Nairobi, Kenya
- Center for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya
| | - Mark Jit
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Anna Vassall
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK
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38
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Galanis G, Di Guilmi C, Bennett DL, Baskozos G. The effectiveness of Non-pharmaceutical interventions in reducing the COVID-19 contagion in the UK, an observational and modelling study. PLoS One 2021; 16:e0260364. [PMID: 34843552 PMCID: PMC8629270 DOI: 10.1371/journal.pone.0260364] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 11/08/2021] [Indexed: 11/24/2022] Open
Abstract
Epidemiological models used to inform government policies aimed to reduce the contagion of COVID-19, assume that the reproduction number is reduced through Non-Pharmaceutical Interventions (NPIs) leading to physical distancing. Available data in the UK show an increase in physical distancing before the NPIs were implemented and a fall soon after implementation. We aimed to estimate the effect of people’s behaviour on the epidemic curve and the effect of NPIs taking into account this behavioural component. We have estimated the effects of confirmed daily cases on physical distancing and we used this insight to design a behavioural SEIR model (BeSEIR), simulated different scenaria regarding NPIs and compared the results to the standard SEIR. Taking into account behavioural insights improves the description of the contagion dynamics of the epidemic significantly. The BeSEIR predictions regarding the number of infections without NPIs were several orders of magnitude less than the SEIR. However, the BeSEIR prediction showed that early measures would still have an important influence in the reduction of infections. The BeSEIR model shows that even with no intervention the percentage of the cumulative infections within a year will not be enough for the epidemic to resolve due to a herd immunity effect. On the other hand, a standard SEIR model significantly overestimates the effectiveness of measures. Without taking into account the behavioural component, the epidemic is predicted to be resolved much sooner than when taking it into account and the effectiveness of measures are significantly overestimated.
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Affiliation(s)
- Giorgos Galanis
- Institute of Management Studies, Goldsmiths, University of London, London, United Kingdom
| | - Corrado Di Guilmi
- Department of Economics, University of Technology Sydney, Sydney, Australia
| | - David L. Bennett
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Georgios Baskozos
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
- * E-mail:
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39
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Getz WM, Salter R, Luisa Vissat L, Koopman JS, Simon CP. A runtime alterable epidemic model with genetic drift, waning immunity and vaccinations. J R Soc Interface 2021; 18:20210648. [PMID: 34814729 PMCID: PMC8611333 DOI: 10.1098/rsif.2021.0648] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
We present methods for building a Java Runtime-Alterable-Model Platform (RAMP) of complex dynamical systems. We illustrate our methods by building a multivariant SEIR (epidemic) RAMP. Underlying our RAMP is an individual-based model that includes adaptive contact rates, pathogen genetic drift, waning and cross-immunity. Besides allowing parameter values, process descriptions and scriptable runtime drivers to be easily modified during simulations, our RAMP can used within R-Studio and other computational platforms. Process descriptions that can be runtime altered within our SEIR RAMP include pathogen variant-dependent host shedding, environmental persistence, host transmission and within-host pathogen mutation and replication. They also include adaptive social distancing and adaptive application of vaccination rates and variant-valency of vaccines. We present simulation results using parameter values and process descriptions relevant to the current COVID-19 pandemic. Our results suggest that if waning immunity outpaces vaccination rates, then vaccination rollouts may fail to contain the most transmissible variants, particularly if vaccine valencies are not adapted to deal with escape mutations. Our SEIR RAMP is designed for easy use by others. More generally, our RAMP concept facilitates construction of highly flexible complex systems models of all types, which can then be easily shared as stand-alone application programs.
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Affiliation(s)
- Wayne M Getz
- Department ESPM, UC Berkeley, Berkeley, CA 94720-3114, USA.,School of Mathematical Sciences, University of KwaZulu-Natal, Durban, South Africa.,Numerus, 850 Iron Point Rd., Folsom, CA 95630, USA
| | - Richard Salter
- Numerus, 850 Iron Point Rd., Folsom, CA 95630, USA.,Computer Science Department, Oberlin College, Oberlin, OH 44074, USA
| | | | - James S Koopman
- School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.,Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI 48109, USA
| | - Carl P Simon
- Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI 48109, USA.,Gerald R. Ford School of Public Policy, University of Michigan, Ann Arbor, MI 48109, USA.,Department of Mathematics, University of Michigan, Ann Arbor, MI 48109, USA
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40
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Nascimento de Lima P, Lempert R, Vardavas R, Baker L, Ringel J, Rutter CM, Ozik J, Collier N. Reopening California: Seeking robust, non-dominated COVID-19 exit strategies. PLoS One 2021; 16:e0259166. [PMID: 34699570 PMCID: PMC8547648 DOI: 10.1371/journal.pone.0259166] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 10/13/2021] [Indexed: 12/14/2022] Open
Abstract
The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty.
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Affiliation(s)
- Pedro Nascimento de Lima
- RAND Corporation, Santa Monica, CA, United States of America
- Pardee RAND Graduate School, Santa Monica, CA, United States of America
- Argonne National Laboratory, Lemont, IL, United States of America
| | - Robert Lempert
- RAND Corporation, Santa Monica, CA, United States of America
- Pardee RAND Graduate School, Santa Monica, CA, United States of America
| | - Raffaele Vardavas
- RAND Corporation, Santa Monica, CA, United States of America
- Pardee RAND Graduate School, Santa Monica, CA, United States of America
| | - Lawrence Baker
- RAND Corporation, Santa Monica, CA, United States of America
- Pardee RAND Graduate School, Santa Monica, CA, United States of America
| | - Jeanne Ringel
- RAND Corporation, Santa Monica, CA, United States of America
- Pardee RAND Graduate School, Santa Monica, CA, United States of America
| | - Carolyn M. Rutter
- RAND Corporation, Santa Monica, CA, United States of America
- Pardee RAND Graduate School, Santa Monica, CA, United States of America
| | - Jonathan Ozik
- Argonne National Laboratory, Lemont, IL, United States of America
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A solution scan of societal options to reduce transmission and spread of respiratory viruses: SARS-CoV-2 as a case study. JOURNAL OF BIOSAFETY AND BIOSECURITY 2021; 3:84-90. [PMID: 34541465 PMCID: PMC8440234 DOI: 10.1016/j.jobb.2021.08.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 08/04/2021] [Accepted: 08/05/2021] [Indexed: 11/29/2022] Open
Abstract
Societal biosecurity – measures built into everyday society to minimize risks from pests and diseases – is an important aspect of managing epidemics and pandemics. We aimed to identify societal options for reducing the transmission and spread of respiratory viruses. We used SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) as a case study to meet the immediate need to manage the COVID-19 pandemic and eventually transition to more normal societal conditions, and to catalog options for managing similar pandemics in the future. We used a ‘solution scanning’ approach. We read the literature; consulted psychology, public health, medical, and solution scanning experts; crowd-sourced options using social media; and collated comments on a preprint. Here, we present a list of 519 possible measures to reduce SARS-CoV-2 transmission and spread. We provide a long list of options for policymakers and businesses to consider when designing biosecurity plans to combat SARS-CoV-2 and similar pathogens in the future. We also developed an online application to help with this process. We encourage testing of actions, documentation of outcomes, revisions to the current list, and the addition of further options.
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42
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Cuschieri S, Agius S, Souness J, Brincat A, Grech V. The fastest national COVID vaccination in Europe - Malta's strategies. HEALTH SCIENCES REVIEW (OXFORD, ENGLAND) 2021; 1:100001. [PMID: 34977913 PMCID: PMC8687735 DOI: 10.1016/j.hsr.2021.100001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND COVID-19 vaccines reduce morbidity and mortality, but mass vaccination faces multiple challenges leading to different vaccination rates in different countries. Malta, a small European country, has achieved a very rapid vaccination rollout. This paper presents a narrative review of Malta's vaccination strategy and its impact on the country's COVID-19 situation. METHODS Data was obtained through a literature review of Maltese newspapers and from Malta's COVID-19 government dashboard. A comprehensive summary of vaccination operations was provided by Malta's COVID-19 vaccination team. RESULTS Malta comprised part of the European Commission joint procurement and obtained the maximum vaccines that were eligible from all manufacturers. Four tier priority population groups were set up, with both vaccine doses (where applicable) allocated and stored for each individual. Multiple hubs were set up to simultaneously administer first and eventually second doses accordingly. To date (August 9, 2021) 398,128 of the population are fully vaccinated and 405,073 received the first dose, with both morbidity and mortality declining progressively as vaccination coverage progressed. CONCLUSION Malta has successfully implemented a COVID-19 strategy that rapidly covered a substantial proportion of the population over a short period of time, with herd immunity reached by end of May 2021. Low population vaccination hesitancy and high vaccine doses availability were two major factors in this success.
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Affiliation(s)
- Sarah Cuschieri
- Faculty of Medicine & Surgery, University of Malta, Msida, Malta,Corresponding author at: RM425 Biomedical building, University of Malta, Msida, MSD2080, Malta
| | - Steve Agius
- Chief Operations Officer, Mater Dei Hospital, Msida, Malta
| | - Jorgen Souness
- Vaccination Logistics’ officer, Mater Dei Hospital, Msida, Malta
| | - Andre Brincat
- Applied Data Science and Analytics, Scientific Officer, Mater Dei Hospital, Msida, Malta
| | - Victor Grech
- Department of Paediatric, Mater Dei Hospital, Msida, Malta
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