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Smith DRM, Chervet S, Pinettes T, Shirreff G, Jijón S, Oodally A, Jean K, Opatowski L, Kernéis S, Temime L. How have mathematical models contributed to understanding the transmission and control of SARS-CoV-2 in healthcare settings? A systematic search and review. J Hosp Infect 2023; 141:132-141. [PMID: 37734676 DOI: 10.1016/j.jhin.2023.07.028] [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] [Accepted: 07/04/2023] [Indexed: 09/23/2023]
Abstract
Since the onset of the COVID-19 pandemic, mathematical models have been widely used to inform public health recommendations regarding COVID-19 control in healthcare settings. The objective of this study was to systematically review SARS-CoV-2 transmission models in healthcare settings, and to summarize their contributions to understanding nosocomial COVID-19. A systematic search and review of published articles indexed in PubMed was carried out. Modelling studies describing dynamic inter-individual transmission of SARS-CoV-2 in healthcare settings, published by mid-February 2022 were included. Models have mostly focused on acute-care and long-term-care facilities in high-income countries. Models have quantified outbreak risk, showing great variation across settings and pandemic periods. Regarding surveillance, routine testing rather than symptom-based was highlighted as essential for COVID-19 prevention due to high rates of silent transmission. Surveillance impacts depended critically on testing frequency, diagnostic sensitivity, and turn-around time. Healthcare re-organization also proved to have large epidemiological impacts: beyond obvious benefits of isolating cases and limiting inter-individual contact, more complex strategies (staggered staff scheduling, immune-based cohorting) reduced infection risk. Finally, vaccination impact, while highly effective for limiting COVID-19 burden, varied substantially depending on assumed mechanistic impacts on infection acquisition, symptom onset and transmission. Modelling results form an extensive evidence base that may inform control strategies for future waves of SARS-CoV-2 and other viral respiratory pathogens. We propose new avenues for future models of healthcare-associated outbreaks, with the aim of enhancing their efficiency and contributions to decision-making.
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Affiliation(s)
- D R M Smith
- Anti-infective Evasion and Pharmacoepidemiology Team, CESP, Université Paris-Saclay, UVSQ, INSERM U1018, Montigny-le-Bretonneux, France; Institut Pasteur, Université Paris-Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE), F-75015 Paris, France; Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers, F-75003 Paris, France
| | - S Chervet
- Anti-infective Evasion and Pharmacoepidemiology Team, CESP, Université Paris-Saclay, UVSQ, INSERM U1018, Montigny-le-Bretonneux, France; Institut Pasteur, Université Paris-Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE), F-75015 Paris, France; Université Paris-Cité, INSERM, IAME, F-75018, Paris, France
| | - T Pinettes
- Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers, F-75003 Paris, France; Unité PACRI, Institut Pasteur, Conservatoire National des Arts et Métiers, Paris, France
| | - G Shirreff
- Anti-infective Evasion and Pharmacoepidemiology Team, CESP, Université Paris-Saclay, UVSQ, INSERM U1018, Montigny-le-Bretonneux, France; Institut Pasteur, Université Paris-Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE), F-75015 Paris, France; Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers, F-75003 Paris, France
| | - S Jijón
- Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers, F-75003 Paris, France; Unité PACRI, Institut Pasteur, Conservatoire National des Arts et Métiers, Paris, France
| | - A Oodally
- Anti-infective Evasion and Pharmacoepidemiology Team, CESP, Université Paris-Saclay, UVSQ, INSERM U1018, Montigny-le-Bretonneux, France; Institut Pasteur, Université Paris-Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE), F-75015 Paris, France; Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers, F-75003 Paris, France
| | - K Jean
- Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers, F-75003 Paris, France; Unité PACRI, Institut Pasteur, Conservatoire National des Arts et Métiers, Paris, France
| | - L Opatowski
- Anti-infective Evasion and Pharmacoepidemiology Team, CESP, Université Paris-Saclay, UVSQ, INSERM U1018, Montigny-le-Bretonneux, France; Institut Pasteur, Université Paris-Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE), F-75015 Paris, France
| | - S Kernéis
- Université Paris-Cité, INSERM, IAME, F-75018, Paris, France; Equipe de Prévention du Risque Infectieux (EPRI), AP-HP, Hôpital Bichat, F-75018 Paris, France.
| | - L Temime
- Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers, F-75003 Paris, France; Unité PACRI, Institut Pasteur, Conservatoire National des Arts et Métiers, Paris, France
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Ko Y, Mendoza VM, Mendoza R, Seo Y, Lee J, Jung E. Risk estimation of lifted mask mandates and emerging variants using mathematical model. Heliyon 2023; 9:e16841. [PMID: 37303548 PMCID: PMC10246937 DOI: 10.1016/j.heliyon.2023.e16841] [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: 05/09/2023] [Revised: 05/29/2023] [Accepted: 05/30/2023] [Indexed: 06/13/2023] Open
Abstract
Background More than half of the population in Korea had a prior COVID-19 infection. In 2022, most nonpharmaceutical interventions, except mask-wearing indoors, had been lifted. And in 2023, the indoor mask mandates were eased. Methods We developed an age-structured compartmental model that distinguishes vaccination history, prior infection, and medical staff from the rest of the population. Contact patterns among hosts were separated based on age and location. We simulated scenarios with the lifting of the mask mandate all at once or sequentially according to the locations. Furthermore, we investigated the impact of a new variant assuming that it has higher transmissibility and risk of breakthrough infection. Results We found that the peak size of administered severe patients may not exceed 1100 when the mask mandate is lifted everywhere, and 800 if the mask mandate only remains in the hospital. If the mask mandate is lifted in a sequence (except hospital), then the peak size of administered severe patients may not exceed 650. Moreover, if the new variant has both higher transmissibility and immune reduction, the effective reproductive number of the new variant is approximately 3 times higher than that of the current variant, and additional interventions may be needed to keep the administered severe patients from exceeding 2,000, which is the critical level we set. Conclusion Our findings showed that the lifting of the mask mandate, except in hospitals, would be more manageable if implemented sequentially. Considering a new variant, we found that depending on the population immunity and transmissibility of the variant, wearing masks and other interventions may be necessary for controlling the disease.
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Affiliation(s)
- Youngsuk Ko
- Department of Mathematics, Konkuk University, Seoul, South Korea
| | - Victoria May Mendoza
- Department of Mathematics, Konkuk University, Seoul, South Korea
- Institute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines
| | - Renier Mendoza
- Department of Mathematics, Konkuk University, Seoul, South Korea
- Institute of Mathematics, University of the Philippines Diliman, Quezon City, Philippines
| | - Yubin Seo
- Division of Infectious Disease, Department of Internal Medicine, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, South Korea
| | - Jacob Lee
- Division of Infectious Disease, Department of Internal Medicine, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, South Korea
| | - Eunok Jung
- Department of Mathematics, Konkuk University, Seoul, South Korea
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Toor J, Li X, Jit M, Trotter CL, Echeverria-Londono S, Hartner AM, Roth J, Portnoy A, Abbas K, Ferguson NM, Am Gaythorpe K. COVID-19 impact on routine immunisations for vaccine-preventable diseases: Projecting the effect of different routes to recovery. Vaccine 2022; 40:4142-4149. [PMID: 35672179 PMCID: PMC9148934 DOI: 10.1016/j.vaccine.2022.05.074] [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: 01/25/2022] [Revised: 05/13/2022] [Accepted: 05/24/2022] [Indexed: 11/23/2022]
Abstract
Over the past two decades, vaccination programmes for vaccine-preventable diseases (VPDs) have expanded across low- and middle-income countries (LMICs). However, the rise of COVID-19 resulted in global disruption to routine immunisation activities. Such disruptions could have a detrimental effect on public health, leading to more deaths from VPDs, particularly without mitigation efforts. Hence, as routine immunisation activities resume, it is important to estimate the effectiveness of different approaches for recovery. We apply an impact extrapolation method developed by the Vaccine Impact Modelling Consortium to estimate the impact of COVID-19-related disruptions with different recovery scenarios for ten VPDs across 112 LMICs. We focus on deaths averted due to routine immunisations occurring in the years 2020–2030 and investigate two recovery scenarios relative to a no-COVID-19 scenario. In the recovery scenarios, we assume a 10% COVID-19-related drop in routine immunisation coverage in the year 2020. We then linearly interpolate coverage to the year 2030 to investigate two routes to recovery, whereby the immunization agenda (IA2030) targets are reached by 2030 or fall short by 10%. We estimate that falling short of the IA2030 targets by 10% leads to 11.26% fewer fully vaccinated persons (FVPs) and 11.34% more deaths over the years 2020–2030 relative to the no-COVID-19 scenario, whereas, reaching the IA2030 targets reduces these proportions to 5% fewer FVPs and 5.22% more deaths. The impact of the disruption varies across the VPDs with diseases where coverage expands drastically in future years facing a smaller detrimental effect. Overall, our results show that drops in routine immunisation coverage could result in more deaths due to VPDs. As the impact of COVID-19-related disruptions is dependent on the vaccination coverage that is achieved over the coming years, the continued efforts of building up coverage and addressing gaps in immunity are vital in the road to recovery.
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Affiliation(s)
- Jaspreet Toor
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.
| | - Xiang Li
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom
| | - Mark Jit
- London School of Hygiene and Tropical Medicine, London, United Kingdom; University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
| | | | - Susy Echeverria-Londono
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom
| | - Anna-Maria Hartner
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom
| | - Jeremy Roth
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom
| | - Allison Portnoy
- Center for Health Decision Science, Harvard T H Chan School of Public Health, Boston, United States
| | - Kaja Abbas
- London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom
| | - Katy Am Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Jameel Institute, School of Public Health, Imperial College London, London, United Kingdom.
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Smith DRM, Duval A, Zahar JR, Opatowski L, Temime L. Rapid antigen testing as a reactive response to surges in nosocomial SARS-CoV-2 outbreak risk. Nat Commun 2022; 13:236. [PMID: 35017499 PMCID: PMC8752617 DOI: 10.1038/s41467-021-27845-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 12/07/2021] [Indexed: 11/24/2022] Open
Abstract
Healthcare facilities are vulnerable to SARS-CoV-2 introductions and subsequent nosocomial outbreaks. Antigen rapid diagnostic testing (Ag-RDT) is widely used for population screening, but its health and economic benefits as a reactive response to local surges in outbreak risk are unclear. We simulate SARS-CoV-2 transmission in a long-term care hospital with varying COVID-19 containment measures in place (social distancing, face masks, vaccination). Across scenarios, nosocomial incidence is reduced by up to 40-47% (range of means) with routine symptomatic RT-PCR testing, 59-63% with the addition of a timely round of Ag-RDT screening, and 69-75% with well-timed two-round screening. For the latter, a delay of 4-5 days between the two screening rounds is optimal for transmission prevention. Screening efficacy varies depending on test sensitivity, test type, subpopulations targeted, and community incidence. Efficiency, however, varies primarily depending on underlying outbreak risk, with health-economic benefits scaling by orders of magnitude depending on the COVID-19 containment measures in place.
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Affiliation(s)
- David R M Smith
- Institut Pasteur, Epidemiology and Modelling of Antibiotic Evasion (EMAE), Paris, France.
- Université Paris-Saclay, UVSQ, Inserm, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France.
- Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire national des arts et métiers, Paris, France.
| | - Audrey Duval
- Institut Pasteur, Epidemiology and Modelling of Antibiotic Evasion (EMAE), Paris, France
- Université Paris-Saclay, UVSQ, Inserm, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France
- IAME, UMR 1137, Université Paris 13, Sorbonne Paris Cité, Paris, France
| | - Jean Ralph Zahar
- IAME, UMR 1137, Université Paris 13, Sorbonne Paris Cité, Paris, France
- Service de Microbiologie Clinique et Unité de Contrôle et de Prévention du Risque Infectieux, Groupe Hospitalier Paris Seine Saint-Denis, AP-HP, Bobigny, France
| | - Lulla Opatowski
- Institut Pasteur, Epidemiology and Modelling of Antibiotic Evasion (EMAE), Paris, France
- Université Paris-Saclay, UVSQ, Inserm, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France
| | - Laura Temime
- Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire national des arts et métiers, Paris, France
- PACRI unit, Institut Pasteur, Conservatoire national des arts et métiers, Paris, France
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