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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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Nilsson MG, Santana Cordeiro MDC, Gonçalves ACA, Dos Santos Conzentino M, Huergo LF, Vicentini F, Reis JBL, Biondo AW, Kmetiuk LB, da Silva AV. High seroprevalence for SARS-CoV-2 infection in dogs: Age as risk factor for infection in shelter and foster home animals. Prev Vet Med 2024; 222:106094. [PMID: 38103433 DOI: 10.1016/j.prevetmed.2023.106094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 11/30/2023] [Accepted: 12/02/2023] [Indexed: 12/19/2023]
Abstract
SARS-CoV-2 has caused 775 outbreaks in 29 animal species across 36 countries, including dogs, cats, ferrets, minks, non-human primates, white-tailed deer, and lions. Although transmission from owners to dogs has been extensively described, no study to date has also compared sheltered, foster home and owner dogs and associated risk factors. This study aimed to identify SARS-CoV-2 infection and anti-SARS-CoV-2 antibodies from sheltered, fostered, and owned dogs, associated with environmental and management risk factors. Serum samples and swabs were collected from each dog, and an epidemiological questionnaire was completed by the shelter manager, foster care, and owner. A total of 111 dogs, including 222 oropharyngeal and rectal swabs, tested negative by RT-qPCR. Overall, 18/89 (20.22%) dogs presented IgG antibodies against the N protein of SARS-CoV-2 by magnetic ELISA, while none showed a reaction to the Spike protein. SARS-CoV-2 antibodies showed an age-related association, with 4.16 chance of positivity in adult dogs when compared with young ones. High population density among dogs and humans, coupled with repeated COVID-19 exposure, emerged as potential risk factors in canine virus epidemiology. Dogs exhibited higher seropositivity rates in these contexts. Thus, we propose expanded seroepidemiological and molecular studies across species and scenarios, including shelter dogs.
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Affiliation(s)
- Mariana Guimarães Nilsson
- Graduate College of Animal Science in the Tropics, Federal University of Bahia (UFBA), 40170-110 Salvador, Bahia, Brazil.
| | | | | | | | | | - Fernando Vicentini
- Health Sciences Center, Federal University of the Recôncavo of Bahia (UFRB), 44430-622 Santo Antônio de Jesus, Bahia, Brazil
| | - Jeiza Botelho Leal Reis
- Health Sciences Center, Federal University of the Recôncavo of Bahia (UFRB), 44430-622 Santo Antônio de Jesus, Bahia, Brazil
| | - Alexander Welker Biondo
- Graduate College of Cellular and Molecular Biology, Federal University of Paraná (UFPR), 81531-970 Curitiba, Paraná, Brazil
| | - Louise Bach Kmetiuk
- Carlos Chagas Institute, Oswaldo Cruz Foundation, Curitiba, Paraná 81310-020, Brazil
| | - Aristeu Vieira da Silva
- Zoonosis and Public Health Research Group, Earth and Environmental Science Modelling Graduate, State University of Feira de Santana (UEFS), 44036-900 Feira de Santana, Bahia, Brazil.
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The real seroprevalence of SARS-CoV-2 in France and its consequences for virus dynamics. Sci Rep 2021; 11:12597. [PMID: 34131234 PMCID: PMC8206100 DOI: 10.1038/s41598-021-92131-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 06/03/2021] [Indexed: 01/12/2023] Open
Abstract
The SARS-CoV-2 virus has spread world-wide since December 2019, killing more than 2.9 million of people. We have adapted a statistical model from the SIR epidemiological models to predict the spread of SARS-CoV-2 in France. Our model is based on several parameters and assumed a 4.2% seroprevalence in Occitania after the first lockdown. The recent use of serological tests to measure the effective seroprevalence of SARS-CoV-2 in the population of Occitania has led to a seroprevalence around 2.4%. This implies to review the parameters of our model to conclude at a lower than expected virus transmission rate, which may be due to infectivity varying with the patient’s symptoms or to a constraint due to an uneven population geographical distribution.
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Dimeglio C, Milhes M, Loubes JM, Ranger N, Mansuy JM, Trémeaux P, Jeanne N, Latour J, Nicot F, Donnadieu C, Izopet J. Influence of SARS-CoV-2 Variant B.1.1.7, Vaccination, and Public Health Measures on the Spread of SARS-CoV-2. Viruses 2021; 13:898. [PMID: 34066231 PMCID: PMC8151774 DOI: 10.3390/v13050898] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 05/06/2021] [Accepted: 05/07/2021] [Indexed: 12/11/2022] Open
Abstract
The spread of SARS-CoV-2 and the resulting disease COVID-19 has killed over 2.6 million people as of 18 March 2021. We have used a modified susceptible, infected, recovered (SIR) epidemiological model to predict how the spread of the virus in regions of France will vary depending on the proportions of variants and on the public health strategies adopted, including anti-COVID-19 vaccination. The proportion of SARS-CoV-2 variant B.1.1.7, which was not detected in early January, increased to become 60% of the forms of SARS-CoV-2 circulating in the Toulouse urban area at the beginning of February 2021, but there was no increase in positive nucleic acid tests. Our prediction model indicates that maintaining public health measures and accelerating vaccination are efficient strategies for the sustained control of SARS-CoV-2.
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Affiliation(s)
- Chloé Dimeglio
- INSERM UMR1291—CNRS UMR5051, Toulouse Institute for Infectious and Inflammatory Diseases (INFINITy), 31300 Toulouse, France;
- Virology Laboratory, Centre Hospitalier Universitaire de Toulouse, Hôpital Purpan, 31300 Toulouse, France; (N.R.); (J.-M.M.); (P.T.); (N.J.); (J.L.); (F.N.)
| | - Marine Milhes
- Genotoul-Genome & Transcriptome—Plateforme Génomique (GeT-PlaGe), US INRAe 1426, 31326 Castanet-Tolosan, France; (M.M.); (C.D.)
| | - Jean-Michel Loubes
- Institut de Mathématiques de Toulouse, Université de Toulouse, 31400 Toulouse, France;
| | - Noémie Ranger
- Virology Laboratory, Centre Hospitalier Universitaire de Toulouse, Hôpital Purpan, 31300 Toulouse, France; (N.R.); (J.-M.M.); (P.T.); (N.J.); (J.L.); (F.N.)
| | - Jean-Michel Mansuy
- Virology Laboratory, Centre Hospitalier Universitaire de Toulouse, Hôpital Purpan, 31300 Toulouse, France; (N.R.); (J.-M.M.); (P.T.); (N.J.); (J.L.); (F.N.)
| | - Pauline Trémeaux
- Virology Laboratory, Centre Hospitalier Universitaire de Toulouse, Hôpital Purpan, 31300 Toulouse, France; (N.R.); (J.-M.M.); (P.T.); (N.J.); (J.L.); (F.N.)
| | - Nicolas Jeanne
- Virology Laboratory, Centre Hospitalier Universitaire de Toulouse, Hôpital Purpan, 31300 Toulouse, France; (N.R.); (J.-M.M.); (P.T.); (N.J.); (J.L.); (F.N.)
| | - Justine Latour
- Virology Laboratory, Centre Hospitalier Universitaire de Toulouse, Hôpital Purpan, 31300 Toulouse, France; (N.R.); (J.-M.M.); (P.T.); (N.J.); (J.L.); (F.N.)
| | - Florence Nicot
- Virology Laboratory, Centre Hospitalier Universitaire de Toulouse, Hôpital Purpan, 31300 Toulouse, France; (N.R.); (J.-M.M.); (P.T.); (N.J.); (J.L.); (F.N.)
| | - Cécile Donnadieu
- Genotoul-Genome & Transcriptome—Plateforme Génomique (GeT-PlaGe), US INRAe 1426, 31326 Castanet-Tolosan, France; (M.M.); (C.D.)
| | - Jacques Izopet
- INSERM UMR1291—CNRS UMR5051, Toulouse Institute for Infectious and Inflammatory Diseases (INFINITy), 31300 Toulouse, France;
- Virology Laboratory, Centre Hospitalier Universitaire de Toulouse, Hôpital Purpan, 31300 Toulouse, France; (N.R.); (J.-M.M.); (P.T.); (N.J.); (J.L.); (F.N.)
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Dimeglio C, Miedougé M, Loubes JM, Mansuy JM, Izopet J. Side effect of a 6 p.m curfew for preventing the spread of SARS-CoV-2: A modeling study from Toulouse, France. J Infect 2021; 82:186-230. [PMID: 33535066 PMCID: PMC7847700 DOI: 10.1016/j.jinf.2021.01.021] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 01/29/2021] [Indexed: 11/29/2022]
Abstract
The spread of SARS-CoV-2 and the resulting disease Covid-19 has killed over 2 million people as of January 22, 2021. We have designed a model and used it to quantify the effect of a 6 p.m curfew on the SARS-CoV-2 epidemic in Toulouse, France. The data show that this measure can lead to the opposite effect from that intended due to larger groups of people on the authorized hours.
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Affiliation(s)
- Chloé Dimeglio
- UMR Inserm, U1043; UMR CNRS, U5282, Centre de Physiopathologie de Toulouse Purpan (CPTP), Toulouse 31300, France; CHU Toulouse, Hôpital Purpan, Virology Laboratory, 31300 France.
| | - Marcel Miedougé
- CHU Toulouse, Hôpital Purpan, Virology Laboratory, 31300 France
| | - Jean-Michel Loubes
- Université de Toulouse, Institut de Mathématiques de Toulouse, Toulouse 31400, France
| | | | - Jacques Izopet
- UMR Inserm, U1043; UMR CNRS, U5282, Centre de Physiopathologie de Toulouse Purpan (CPTP), Toulouse 31300, France; CHU Toulouse, Hôpital Purpan, Virology Laboratory, 31300 France
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