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Leclerc QJ, Duval A, Guillemot D, Opatowski L, Temime L. Using contact network dynamics to implement efficient interventions against pathogen spread in hospital settings: A modelling study. PLoS Med 2024; 21:e1004433. [PMID: 39078828 PMCID: PMC11341093 DOI: 10.1371/journal.pmed.1004433] [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: 01/10/2024] [Revised: 08/22/2024] [Accepted: 06/24/2024] [Indexed: 08/24/2024] Open
Abstract
BACKGROUND Long-term care facilities (LTCFs) are hotspots for pathogen transmission. Infection control interventions are essential, but the high density and heterogeneity of interindividual contacts within LTCF may hinder their efficacy. Here, we explore how the patient-staff contact structure may inform effective intervention implementation. METHODS AND FINDINGS Using an individual-based model (IBM), we reproduced methicillin-resistant Staphylococcus aureus colonisation transmission dynamics over a detailed contact network recorded within a French LTCF of 327 patients and 263 staff over 3 months. Simulated baseline cumulative colonisation incidence was 21 patients (prediction interval: 11, 31) and 35 staff (prediction interval: 19, 54). We examined the potential impact of 3 types of interventions against transmission (reallocation reducing the number of unique contacts per staff, reinforced contact precautions, and hypothetical vaccination protecting against acquisition), targeted towards specific populations. All 3 interventions were effective when applied to all nurses or healthcare assistants (median reduction in MRSA colonisation incidence up to 35%), but the benefit did not exceed 8% when targeting any other single staff category. We identified "supercontactor" individuals with most contacts ("frequency-based," overrepresented among nurses, porters, and rehabilitation staff) or with the longest cumulative time spent in contact ("duration-based," overrepresented among healthcare assistants and patients in elderly care or persistent vegetative state (PVS)). Targeting supercontactors enhanced interventions against pathogen spread in the LTCF. With contact precautions, targeting frequency-based staff supercontactors led to the highest incidence reduction (20%, 95% CI: 19, 21). Vaccinating a mix of frequency- and duration-based staff supercontactors led to a higher reduction (23%, 95% CI: 22, 24) than all other approaches. Although based on data from a single LTCF, when varying epidemiological parameters to extend to other pathogens, our results suggest that targeting supercontactors is always the most effective strategy, indicating this approach could be applied to prevent transmission of other nosocomial pathogens. CONCLUSIONS By characterising the contact structure in hospital settings and identifying the categories of staff and patients more likely to be supercontactors, with either more or longer contacts than others, interventions against nosocomial spread could be more effective. We find that the most efficient implementation strategy depends on the intervention (reallocation, contact precautions, vaccination) and target population (staff, patients, supercontactors). Importantly, both staff and patients may be supercontactors, highlighting the importance of including patients in measures to prevent pathogen transmission in LTCF.
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Affiliation(s)
- Quentin J. Leclerc
- Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Bacterial Escape to Antimicrobials (EMEA), Paris, France
- INSERM, Université Paris-Saclay, Université de Versailles St-Quentin-en-Yvelines, Team Echappement aux Anti-infectieux et Pharmacoépidémiologie U1018, CESP, Versailles, France
- Laboratoire Modélisation, Epidémiologie et Surveillance des Risques Sanitaires, Conservatoire National des Arts et Métiers, Paris, France
| | - Audrey Duval
- Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Bacterial Escape to Antimicrobials (EMEA), Paris, France
- INSERM, Université Paris-Saclay, Université de Versailles St-Quentin-en-Yvelines, Team Echappement aux Anti-infectieux et Pharmacoépidémiologie U1018, CESP, Versailles, France
- Laboratoire Modélisation, Epidémiologie et Surveillance des Risques Sanitaires, Conservatoire National des Arts et Métiers, Paris, France
| | - Didier Guillemot
- Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Bacterial Escape to Antimicrobials (EMEA), Paris, France
- INSERM, Université Paris-Saclay, Université de Versailles St-Quentin-en-Yvelines, Team Echappement aux Anti-infectieux et Pharmacoépidémiologie U1018, CESP, Versailles, France
- AP-HP, Paris Saclay, Department of Public Health, Medical Information, Clinical Research, Garches, France
| | - Lulla Opatowski
- Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Bacterial Escape to Antimicrobials (EMEA), Paris, France
- INSERM, Université Paris-Saclay, Université de Versailles St-Quentin-en-Yvelines, Team Echappement aux Anti-infectieux et Pharmacoépidémiologie U1018, CESP, Versailles, France
| | - Laura Temime
- Laboratoire Modélisation, Epidémiologie et Surveillance des Risques Sanitaires, Conservatoire National des Arts et Métiers, Paris, France
- Institut Pasteur, Conservatoire National des Arts et Métiers, Unité PACRI, Paris, France
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2
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Investigating healthcare worker mobility and patient contacts within a UK hospital during the COVID-19 pandemic. COMMUNICATIONS MEDICINE 2022; 2:165. [PMID: 36564506 PMCID: PMC9782286 DOI: 10.1038/s43856-022-00229-x] [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: 09/09/2022] [Accepted: 12/08/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Insights into behaviours relevant to the transmission of infections are extremely valuable for epidemiological investigations. Healthcare worker (HCW) mobility and patient contacts within the hospital can contribute to nosocomial outbreaks, yet data on these behaviours are often limited. METHODS Using electronic medical records and door access logs from a London teaching hospital during the COVID-19 pandemic, we derive indicators for HCW mobility and patient contacts at an aggregate level. We assess the spatial-temporal variations in HCW behaviour and, to demonstrate the utility of these behavioural markers, investigate changes in the indirect connectivity of patients (resulting from shared contacts with HCWs) and spatial connectivity of floors (owing to the movements of HCWs). RESULTS Fluctuations in HCW mobility and patient contacts were identified during the pandemic, with the most prominent changes in behaviour on floors handling the majority of COVID-19 patients. The connectivity between floors was disrupted by the pandemic and, while this stabilised after the first wave, the interconnectivity of COVID-19 and non-COVID-19 wards always featured. Daily rates of indirect contact between patients provided evidence for reactive staff cohorting in response to the number of COVID-19 patients in the hospital. CONCLUSIONS Routinely collected electronic records in the healthcare environment provide a means to rapidly assess and investigate behaviour change in the HCW population, and can support evidence based infection prevention and control activities. Integrating frameworks like ours into routine practice will empower decision makers and improve pandemic preparedness by providing tools to help curtail nosocomial outbreaks of communicable diseases.
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Vilches TN, Rafferty E, Wells CR, Galvani AP, Moghadas SM. Economic evaluation of COVID-19 rapid antigen screening programs in the workplace. BMC Med 2022; 20:452. [PMID: 36424587 PMCID: PMC9686464 DOI: 10.1186/s12916-022-02641-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 10/26/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Diagnostic testing has been pivotal in detecting SARS-CoV-2 infections and reducing transmission through the isolation of positive cases. We quantified the value of implementing frequent, rapid antigen (RA) testing in the workplace to identify screening programs that are cost-effective. METHODS To project the number of cases, hospitalizations, and deaths under alternative screening programs, we adapted an agent-based model of COVID-19 transmission and parameterized it with the demographics of Ontario, Canada, incorporating vaccination and waning of immunity. Taking into account healthcare costs and productivity losses associated with each program, we calculated the incremental cost-effectiveness ratio (ICER) with quality-adjusted life year (QALY) as the measure of effect. Considering RT-PCR testing of only severe cases as the baseline scenario, we estimated the incremental net monetary benefits (iNMB) of the screening programs with varying durations and initiation times, as well as different booster coverages of working adults. RESULTS Assuming a willingness-to-pay threshold of CDN$30,000 per QALY loss averted, twice weekly workplace screening was cost-effective only if the program started early during a surge. In most scenarios, the iNMB of RA screening without a confirmatory RT-PCR or RA test was comparable or higher than the iNMB for programs with a confirmatory test for RA-positive cases. When the program started early with a duration of at least 16 weeks and no confirmatory testing, the iNMB exceeded CDN$1.1 million per 100,000 population. Increasing booster coverage of working adults improved the iNMB of RA screening. CONCLUSIONS Our findings indicate that frequent RA testing starting very early in a surge, without a confirmatory test, is a preferred screening program for the detection of asymptomatic infections in workplaces.
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Affiliation(s)
- Thomas N Vilches
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada
| | - Ellen Rafferty
- Institute of Health Economics, Edmonton, Alberta, Canada
| | - Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, USA
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, USA
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada.
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4
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Krylova O, Kazmi O, Wang H, Lam K, Logar-Henderson C, Gapanenko K. Estimating surge in COVID-19 cases, hospital resources and PPE demand with the interactive and locally-informed COVID-19 Health System Capacity Planning Tool. Int J Popul Data Sci 2022; 5:1710. [PMID: 35516164 PMCID: PMC9052960 DOI: 10.23889/ijpds.v5i4.1710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Introduction The COVID-19 pandemic revealed an urgent need for analytic tools to help health system leaders plan for surges in hospital capacity. Our objective was to develop a practical and locally informed Tool to help explore the effects of public health interventions on SARS-CoV-2 transmission and create scenarios to project potential surges in hospital admissions and resource demand. Methods Our Excel-based Tool uses a modified S(usceptible)-E(xposed)-I(nfected)-R(emoved) model with vaccination to simulate the potential spread of COVID-19 cases in the community and subsequent demand for hospitalizations, intensive care unit beds, ventilators, health care workers, and personal protective equipment. With over 40+ customizable parameters, planners can adapt the Tool to their jurisdiction and changes in the pandemic. Results We showcase the Tool using data for Ontario, Canada. Using healthcare utilization data to fit hospitalizations and ICU cases, we illustrate how public health interventions influenced the COVID-19 reproduction number and case counts. We also demonstrate the Tool's ability to project a potential epidemic trajectory and subsequent demand for hospital resources. Using local data, we built three planning scenarios for Ontario for a 3-month period. Our worst-case scenario accurately projected the surge in critical care demand that overwhelmed hospital capacity in Ontario during Spring 2021. Conclusions Our Tool can help different levels of health authorities plan their response to the pandemic. The main differentiators between this Tool and other existing tools include its ease of use, ability to build scenarios, and that it provides immediate outcomes that are ready to share with executive decision makers. The Tool is used by provincial health ministries, public health departments, and hospitals to make operational decisions and communicate possible scenarios to the public. The Tool provides educational value for the healthcare community and can be adapted for existing and emerging diseases.
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Affiliation(s)
- Olga Krylova
- Advanced Analytics, Canadian Institute for Health Information, Ottawa, Ont
| | - Omar Kazmi
- Advanced Analytics, Canadian Institute for Health Information, Ottawa, Ont
| | - Hui Wang
- Advanced Analytics, Canadian Institute for Health Information, Ottawa, Ont
| | - Kelvin Lam
- Advanced Analytics, Canadian Institute for Health Information, Ottawa, Ont
| | | | - Katerina Gapanenko
- Advanced Analytics, Canadian Institute for Health Information, Ottawa, Ont
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5
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Cipriano LE, Haddara WMR, Zaric GS, Enns EA. Impact of university re-opening on total community COVID-19 burden. PLoS One 2021; 16:e0255782. [PMID: 34383796 PMCID: PMC8360395 DOI: 10.1371/journal.pone.0255782] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 07/25/2021] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND University students have higher average number of contacts than the general population. Students returning to university campuses may exacerbate COVID-19 dynamics in the surrounding community. METHODS We developed a dynamic transmission model of COVID-19 in a mid-sized city currently experiencing a low infection rate. We evaluated the impact of 20,000 university students arriving on September 1 in terms of cumulative COVID-19 infections, time to peak infections, and the timing and peak level of critical care occupancy. We also considered how these impacts might be mitigated through screening interventions targeted to students. RESULTS If arriving students reduce their contacts by 40% compared to pre-COVID levels, the total number of infections in the community increases by 115% (from 3,515 to 7,551), with 70% of the incremental infections occurring in the general population, and an incremental 19 COVID-19 deaths. Screening students every 5 days reduces the number of infections attributable to the student population by 42% and the total COVID-19 deaths by 8. One-time mass screening of students prevents fewer infections than 5-day screening, but is more efficient, requiring 196 tests needed to avert one infection instead of 237. INTERPRETATION University students are highly inter-connected with the surrounding off-campus community. Screening targeted at this population provides significant public health benefits to the community through averted infections, critical care admissions, and COVID-19 deaths.
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Affiliation(s)
- Lauren E. Cipriano
- Ivey Business School, Western University, London, Canada
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Wael M. R. Haddara
- Department of Medicine, Schulich School of Medicine & Dentistry, Western University, London, Canada
- Division of Critical Care, London Health Sciences Centre, London, Canada
| | - Gregory S. Zaric
- Ivey Business School, Western University, London, Canada
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Eva A. Enns
- Division of Health Policy and Management, University of Minnesota School of Public Health, Minneapolis, MN, United States of America
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6
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Vilches TN, Nourbakhsh S, Zhang K, Juden-Kelly L, Cipriano LE, Langley JM, Sah P, Galvani AP, Moghadas SM. Multifaceted strategies for the control of COVID-19 outbreaks in long-term care facilities in Ontario, Canada. Prev Med 2021; 148:106564. [PMID: 33878351 PMCID: PMC8053216 DOI: 10.1016/j.ypmed.2021.106564] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 03/31/2021] [Accepted: 04/15/2021] [Indexed: 12/19/2022]
Abstract
The novel coronavirus disease 2019 (COVID-19) has caused severe outbreaks in Canadian long-term care facilities (LTCFs). In Canada, over 80% of COVID-19 deaths during the first pandemic wave occurred in LTCFs. We sought to evaluate the effect of mitigation measures in LTCFs including frequent testing of staff, and vaccination of staff and residents. We developed an agent-based transmission model and parameterized it with disease-specific estimates, temporal sensitivity of nasopharyngeal and saliva testing, results of vaccine efficacy trials, and data from initial COVID-19 outbreaks in LTCFs in Ontario, Canada. Characteristics of staff and residents, including contact patterns, were integrated into the model with age-dependent risk of hospitalization and death. Estimates of infection and outcomes were obtained and 95% credible intervals were generated using a bias-corrected and accelerated bootstrap method. Weekly routine testing of staff with 2-day turnaround time reduced infections among residents by at least 25.9% (95% CrI: 23.3%-28.3%), compared to baseline measures of mask-wearing, symptom screening, and staff cohorting alone. A similar reduction of hospitalizations and deaths was achieved in residents. Vaccination averted 2-4 times more infections in both staff and residents as compared to routine testing, and markedly reduced hospitalizations and deaths among residents by 95.9% (95% CrI: 95.4%-96.3%) and 95.8% (95% CrI: 95.5%-96.1%), respectively, over 200 days from the start of vaccination. Vaccination could have a substantial impact on mitigating disease burden among residents, but may not eliminate the need for other measures before population-level control of COVID-19 is achieved.
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Affiliation(s)
- Thomas N Vilches
- Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Campinas, SP, Brazil.
| | - Shokoofeh Nourbakhsh
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario M3J 1P3, Canada.
| | - Kevin Zhang
- Faculty of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada.
| | - Lyndon Juden-Kelly
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario M3J 1P3, Canada.
| | - Lauren E Cipriano
- Ivey Business School, Department of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, Ontario N6G 0N1, Canada.
| | - Joanne M Langley
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre and Nova Scotia Health Authority, Halifax, Nova Scotia B3K 6R8, Canada.
| | - Pratha Sah
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, USA.
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, USA.
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario M3J 1P3, Canada.
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7
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Ito-Masui A, Kawamoto E, Esumi R, Imai H, Shimaoka M. Sociometric wearable devices for studying human behavior in corporate and healthcare workplaces. Biotechniques 2021; 71:392-399. [PMID: 34164992 DOI: 10.2144/btn-2020-0160] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Wearable sensor technology enables objective data collection of direct human interactions. The authors review sociometric wearable devices (SWD) and their application in healthcare. Human interactions captured by wearable sensors have been shown to correlate with social constructs such as teamwork and productivity in the office. Application of SWD in the field of healthcare requires special considerations: validation studies have shown technological disadvantages in acute medical settings. Application of SWD in healthcare should be considered based on the strengths and weaknesses of the methodology. SWD can also play an important role in investigation of human interaction and epidemic spread. When study designs and methodologies are carefully considered, incorporation of SWD in healthcare research has promising potential for new insights.
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Affiliation(s)
- Asami Ito-Masui
- Emergency & Critical Care Center, Mie University Hospital, Mie, 5148507, Japan.,Department of Emergency & Disaster Medicine, Mie University Graduate School of Medicine, Mie, 5148507, Japan.,Department of Molecular Pathobiology & Cell Adhesion Biology, Mie University Graduate School of Medicine, Mie, 5148507, Japan
| | - Eiji Kawamoto
- Emergency & Critical Care Center, Mie University Hospital, Mie, 5148507, Japan.,Department of Emergency & Disaster Medicine, Mie University Graduate School of Medicine, Mie, 5148507, Japan.,Department of Molecular Pathobiology & Cell Adhesion Biology, Mie University Graduate School of Medicine, Mie, 5148507, Japan
| | - Ryo Esumi
- Emergency & Critical Care Center, Mie University Hospital, Mie, 5148507, Japan.,Department of Emergency & Disaster Medicine, Mie University Graduate School of Medicine, Mie, 5148507, Japan.,Department of Molecular Pathobiology & Cell Adhesion Biology, Mie University Graduate School of Medicine, Mie, 5148507, Japan
| | - Hiroshi Imai
- Emergency & Critical Care Center, Mie University Hospital, Mie, 5148507, Japan.,Department of Emergency & Disaster Medicine, Mie University Graduate School of Medicine, Mie, 5148507, Japan
| | - Motomu Shimaoka
- Department of Molecular Pathobiology & Cell Adhesion Biology, Mie University Graduate School of Medicine, Mie, 5148507, Japan
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8
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Vilches TN, Nourbakhsh S, Zhang K, Juden-Kelly L, Cipriano LE, Langley JM, Sah P, Galvani AP, Moghadas SM. Multifaceted strategies for the control of COVID-19 outbreaks in long-term care facilities in Ontario, Canada. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2020.12.04.20244194. [PMID: 33330884 PMCID: PMC7743093 DOI: 10.1101/2020.12.04.20244194] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The novel coronavirus disease 2019 (COVID-19) has caused severe outbreaks in Canadian long-term care facilities (LTCFs). In Canada, over 80% of COVID-19 deaths during the first pandemic wave occurred in LTCFs. We sought to evaluate the effect of mitigation measures in LTCFs including frequent testing of staff, and vaccination of staff and residents. We developed an agent-based transmission model and parameterized it with disease-specific estimates, temporal sensitivity of nasopharyngeal and saliva testing, results of vaccine efficacy trials, and data from initial COVID-19 outbreaks in LTCFs in Ontario, Canada. Characteristics of staff and residents, including contact patterns, were integrated into the model with age-dependent risk of hospitalization and death. Estimates of infection and outcomes were obtained and 95% credible intervals were generated using a bias-corrected and accelerated bootstrap method. Weekly routine testing of staff with 2-day turnaround time reduced infections among residents by at least 25.9% (95% CrI: 23.3% - 28.3%), compared to baseline measures of mask-wearing, symptom screening, and staff cohorting alone. A similar reduction of hospitalizations and deaths was achieved in residents. Vaccination averted 2-4 times more infections in both staff and residents as compared to routine testing, and markedly reduced hospitalizations and deaths among residents by 95.9% (95% CrI: 95.4% - 96.3%) and 95.8% (95% CrI: 95.5% - 96.1%), respectively, over 200 days from the start of vaccination. Vaccination could have a substantial impact on mitigating disease burden among residents, but may not eliminate the need for other measures before population-level control of COVID-19 is achieved.
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Affiliation(s)
- Thomas N. Vilches
- Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Campinas SP, Brazil
| | - Shokoofeh Nourbakhsh
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3 Canada
| | - Kevin Zhang
- Faculty of Medicine, University of Toronto, Toronto, Ontario, M5S 1A8 Canada
| | - Lyndon Juden-Kelly
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3 Canada
| | - Lauren E. Cipriano
- Ivey Business School and Department of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, Ontario N6G 0N1 Canada
| | - Joanne M. Langley
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre and Nova Scotia Health Authority, Halifax, Nova Scotia, B3K 6R8 Canada
| | - Pratha Sah
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, USA
| | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, USA
| | - Seyed M. Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3 Canada
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9
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Tupper P, Boury H, Yerlanov M, Colijn C. Event-specific interventions to minimize COVID-19 transmission. Proc Natl Acad Sci U S A 2020; 117:32038-32045. [PMID: 33214148 PMCID: PMC7749284 DOI: 10.1073/pnas.2019324117] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
COVID-19 is a global pandemic with over 25 million cases worldwide. Currently, treatments are limited, and there is no approved vaccine. Interventions such as handwashing, masks, social distancing, and "social bubbles" are used to limit community transmission, but it is challenging to choose the best interventions for a given activity. Here, we provide a quantitative framework to determine which interventions are likely to have the most impact in which settings. We introduce the concept of "event R," the expected number of new infections due to the presence of a single infectious individual at an event. We obtain a fundamental relationship between event R and four parameters: transmission intensity, duration of exposure, the proximity of individuals, and the degree of mixing. We use reports of small outbreaks to establish event R and transmission intensity in a range of settings. We identify principles that guide whether physical distancing, masks and other barriers to transmission, or social bubbles will be most effective. We outline how this information can be obtained and used to reopen economies with principled measures to reduce COVID-19 transmission.
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Affiliation(s)
- Paul Tupper
- Department of Mathematics, Simon Fraser University, Burnaby, BC V5A1S6, Canada;
| | - Himani Boury
- Faculty of Health Science, Simon Fraser University, Burnaby, BC V5A1S6, Canada
| | - Madi Yerlanov
- Department of Mathematics, Simon Fraser University, Burnaby, BC V5A1S6, Canada
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University, Burnaby, BC V5A1S6, Canada
- Department of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom
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10
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Vilches TN, Jaberi-Douraki M, Moghadas SM. Risk of influenza infection with low vaccine effectiveness: the role of avoidance behaviour. Epidemiol Infect 2019; 147:e75. [PMID: 30869007 PMCID: PMC6518843 DOI: 10.1017/s0950268818003540] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 10/25/2018] [Accepted: 12/11/2018] [Indexed: 02/07/2023] Open
Abstract
Low vaccine-effectiveness has been recognised as a key factor undermining efforts to improve strategies and uptake of seasonal influenza vaccination. Aiming to prevent disease transmission, vaccination may influence the perceived risk-of-infection and, therefore, alter the individual-level behavioural responses, such as the avoidance of contact with infectious cases. We asked how the avoidance behaviour of vaccinated individuals changes disease dynamics, and specifically the epidemic size, in the context of imperfect vaccination. For this purpose, we developed an agent-based simulation model, and parameterised it with published estimates and relevant databases for population demographics and agent characteristics. Encapsulating an age-stratified structure, we evaluated the per-contact risk-of-infection and estimated the epidemic size. Our results show that vaccination could lead to a larger epidemic size if the level of avoidance behaviour in vaccinated individuals reduces below that of susceptible individuals. Furthermore, the risk-of-infection in vaccinated individuals, which follows the pattern of age-dependent frailty index of the population, increases for older age groups, and may reach, or even exceed, the risk-of-infection in susceptible individuals. Our findings indicate that low engagement in avoidance behaviour can potentially offset the benefits of vaccination even for vaccines with high effectiveness. While highlighting the protective effects of vaccination, seasonal influenza immunisation programmes should enhance strategies to promote avoidance behaviour despite being vaccinated.
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Affiliation(s)
- Thomas N. Vilches
- Department of Biostatistics, Institute of Biosciences, São Paulo State University, Botucatu SP 18618-689, Brazil
| | - Majid Jaberi-Douraki
- Department of Mathematics, and Department of Anatomy and Physiology, Institute of Computational Comparative Medicine, Kansas State University, Manhattan, KS 66506, USA
| | - Seyed M. Moghadas
- Agent-Based modelling Laboratory, York University, Toronto, Ontario M3J 1P3, Canada
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