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David J, Bragazzi NL, Scarabel F, McCarthy Z, Wu J. Non-pharmaceutical intervention levels to reduce the COVID-19 attack ratio among children. ROYAL SOCIETY OPEN SCIENCE 2022; 9:211863. [PMID: 35308622 PMCID: PMC8924746 DOI: 10.1098/rsos.211863] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 02/25/2022] [Indexed: 05/03/2023]
Abstract
The attack ratio in a subpopulation is defined as the total number of infections over the total number of individuals in this subpopulation. Using a methodology based on an age-stratified transmission dynamics model, we estimated the attack ratio of COVID-19 among children (individuals 0-11 years) when a large proportion of individuals eligible for vaccination (age 12 and above) are vaccinated to contain the epidemic among this subpopulation, or the effective herd immunity (with additional physical distancing measures). We describe the relationship between the attack ratio among children, the time to remove infected individuals from the transmission chain and the children-to-children daily contact rate while considering the increased transmissibility of virus variants (using the Delta variant as an example). We illustrate the generality and applicability of the methodology established by performing an analysis of the attack ratio of COVID-19 among children in the population of Canada and in its province of Ontario. The clinical attack ratio, defined as the number of symptomatic infections over the total population, can be informed from the attack ratio and both can be reduced substantially via a combination of reduced social mixing and rapid testing and isolation of the children.
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Affiliation(s)
- Jummy David
- Fields-CQAM Laboratory of Mathematics for Public Health (MfPH), York University, Toronto, Ontario, Canada
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario, Canada
| | - Nicola Luigi Bragazzi
- Fields-CQAM Laboratory of Mathematics for Public Health (MfPH), York University, Toronto, Ontario, Canada
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario, Canada
| | - Francesca Scarabel
- Department of Mathematics, The University of Manchester, Manchester, UK
- Joint UNIversities Pandemic and Epidemiological Research (JUNIPER), UK
- CDLab - Computational Dynamics Laboratory, Department of Mathematics, Computer Science and Physics, University of Udine, Italy
| | - Zachary McCarthy
- Fields-CQAM Laboratory of Mathematics for Public Health (MfPH), York University, Toronto, Ontario, Canada
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario, Canada
| | - Jianhong Wu
- Fields-CQAM Laboratory of Mathematics for Public Health (MfPH), York University, Toronto, Ontario, Canada
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario, Canada
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202
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Abstract
With the recent licensure of mRNA vaccines against COVID-19 in the 5- to 11-year-old age group, the public health impact of a childhood immunization campaign is of interest. Using a mathematical epidemiological model, we project that childhood vaccination carries minimal risk and yields modest public health benefits. These include large relative reductions in child morbidity and mortality, although the absolute reduction is small because these events are rare. Furthermore, the model predicts "altruistic" absolute reductions in adult cases, hospitalizations, and mortality. However, vaccinating children to benefit adults should be considered from an ethical as well as a public health perspective. From a global health perspective, an additional ethical consideration is the justice of giving priority to children in high-income settings at low risk of severe disease while vaccines have not been made available to vulnerable adults in low-income settings. IMPORTANCE Countries have recently begun implementation of childhood vaccination against SARS-CoV-2 with the Pfizer/BioNTech mRNA vaccine in children 5 to 11 years of age. Because SARS-CoV-2 disease severity is remarkably age dependent, vaccinating children may have modest public health benefits, relative to the unequivocal benefit of vaccinating vulnerable older adults. Furthermore, vaccinating children to "altruistically" increase herd immunity should be considered from an ethical as well as a public health perspective. An additional question is related to global social justice: should priority be given to vaccinating children in high-income settings while older adult populations in low-resource settings have limited access to vaccine? To address the risks and benefits of childhood vaccination, we provide a balanced commentary, supported by a mathematical epidemiological model, using Australia and Alberta, Canada, as case studies. We give highlights of the modeling findings in the commentary and include details in the supplemental materials for interested readers.
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203
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Gandolfi A, Aspri A, Beretta E, Jamshad K, Jiang M. A new threshold reveals the uncertainty about the effect of school opening on diffusion of Covid-19. Sci Rep 2022; 12:3012. [PMID: 35194065 PMCID: PMC8863853 DOI: 10.1038/s41598-022-06540-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 02/02/2022] [Indexed: 12/11/2022] Open
Abstract
Studies on the effects of school openings or closures during the Covid-19 pandemic seem to reach contrasting conclusions even in similar contexts. We aim at clarifying this controversy. A mathematical analysis of compartmental models with subpopulations has been conducted, starting from the SIR model, and progressively adding features modeling outbreaks or upsurge of variants, lockdowns, and vaccinations. We find that in all cases, the in-school transmission rates only affect the overall course of the pandemic above a certain context dependent threshold. We provide rigorous proofs and computations of the thresdhold through linearization. We then confirm our theoretical findings through simulations and the review of data-driven studies that exhibit an often unnoticed phase transition. Specific implications are: awareness about the threshold could inform choice of data collection, analysis and release, such as in-school transmission rates, and clarify the reason for divergent conclusions in similar studies; schools may remain open at any stage of the Covid-19 pandemic, including variants upsurge, given suitable containment rules; these rules would be extremely strict and hardly sustainable if only adults are vaccinated, making a compelling argument for vaccinating children whenever possible.
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Affiliation(s)
- Alberto Gandolfi
- Division of Science, New York University Abu Dhabi, Abu Dhabi, 129188, UAE.
| | | | - Elena Beretta
- Division of Science, New York University Abu Dhabi, Abu Dhabi, 129188, UAE
| | - Khola Jamshad
- Division of Science, New York University Abu Dhabi, Abu Dhabi, 129188, UAE
| | - Muyan Jiang
- Division of Science, New York University Abu Dhabi, Abu Dhabi, 129188, UAE
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204
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Lovell-Read FA, Shen S, Thompson RN. Estimating local outbreak risks and the effects of non-pharmaceutical interventions in age-structured populations: SARS-CoV-2 as a case study. J Theor Biol 2022; 535:110983. [PMID: 34915042 PMCID: PMC8670853 DOI: 10.1016/j.jtbi.2021.110983] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 12/02/2021] [Accepted: 12/07/2021] [Indexed: 12/12/2022]
Abstract
During the COVID-19 pandemic, non-pharmaceutical interventions (NPIs) including school closures, workplace closures and social distancing policies have been employed worldwide to reduce transmission and prevent local outbreaks. However, transmission and the effectiveness of NPIs depend strongly on age-related factors including heterogeneities in contact patterns and pathophysiology. Here, using SARS-CoV-2 as a case study, we develop a branching process model for assessing the risk that an infectious case arriving in a new location will initiate a local outbreak, accounting for the age distribution of the host population. We show that the risk of a local outbreak depends on the age of the index case, and we explore the effects of NPIs targeting individuals of different ages. Social distancing policies that reduce contacts outside of schools and workplaces and target individuals of all ages are predicted to reduce local outbreak risks substantially, whereas school closures have a more limited impact. In the scenarios considered here, when different NPIs are used in combination the risk of local outbreaks can be eliminated. We also show that heightened surveillance of infectious individuals reduces the level of NPIs required to prevent local outbreaks, particularly if enhanced surveillance of symptomatic cases is combined with efforts to find and isolate nonsymptomatic infected individuals. Our results reflect real-world experience of the COVID-19 pandemic, during which combinations of intense NPIs have reduced transmission and the risk of local outbreaks. The general modelling framework that we present can be used to estimate local outbreak risks during future epidemics of a range of pathogens, accounting fully for age-related factors.
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Affiliation(s)
| | - Silvia Shen
- Mathematical Institute, University of Oxford, Oxford, United Kingdom; Pembroke College, University of Oxford, Oxford, United Kingdom
| | - Robin N Thompson
- Mathematics Institute, University of Warwick, Coventry, United Kingdom; The Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom
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205
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Roles of Economic Development Level and Other Human System Factors in COVID-19 Spread in the Early Stage of the Pandemic. SUSTAINABILITY 2022. [DOI: 10.3390/su14042342] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
We identified four distinct clusters of 151 countries based on COVID-19 prevalence rate from 1 February 2020 to 29 May 2021 by performing nonparametric K-means cluster analysis (KmL). We forecasted future development of the clusters by using a nonlinear 3-parameter logistic (3PL) model, and found that peak points of development are the latest for Cluster I and earliest for Cluster IV. Based on partial least squares structural equation modeling (PLS-SEM) for the first twenty weeks after 1 February 2020, we found that the prevalence rate of COVID-19 has been significantly influenced by major elements of human systems. Better health infrastructure, more restriction of human mobility, higher urban population density, and less urban environmental degradation are associated with lower levels of prevalence rate (PR) of COVID-19. The most striking discovery of this study is that economic development hindered the control of COVID-19 spread among countries in the early stage of the pandemic. Highlights: While richer countries have advantages in health and other urban infrastructures that may alleviate the prevalence rate of COVID-19, the combination of high economic development level and low restriction on human mobility has led to faster spread of the virus in the first 20 weeks after 1 February 2020.
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206
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Steyn N, Plank MJ, Binny RN, Hendy SC, Lustig A, Ridings K. A COVID-19 vaccination model for Aotearoa New Zealand. Sci Rep 2022; 12:2720. [PMID: 35177804 PMCID: PMC8854696 DOI: 10.1038/s41598-022-06707-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 02/01/2022] [Indexed: 12/16/2022] Open
Abstract
We develop a mathematical model to estimate the effect of New Zealand's vaccine rollout on the potential spread and health impacts of COVID-19. The main purpose of this study is to provide a basis for policy advice on border restrictions and control measures in response to outbreaks that may occur during the vaccination roll-out. The model can be used to estimate the theoretical population immunity threshold, which represents a point in the vaccine rollout at which border restrictions and other controls could be removed and only small, occasional outbreaks would take place. We find that, with a basic reproduction number of 6, approximately representing the Delta variant of SARS-CoV-2, and under baseline vaccine effectiveness assumptions, reaching the population immunity threshold would require close to 100% of the total population to be vaccinated. Since this coverage is not likely to be achievable in practice, relaxing controls completely would risk serious health impacts. However, the higher vaccine coverage is, the more collective protection the population has against adverse health outcomes from COVID-19, and the easier it will become to control outbreaks. There remains considerable uncertainty in model outputs, in part because of the potential for the evolution of new variants. If new variants arise that are more transmissible or vaccine resistant, an increase in vaccine coverage will be needed to provide the same level of protection.
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Affiliation(s)
- Nicholas Steyn
- Te Pūnaha Matatini: the Centre for Complex Systems and Networks, Auckland, New Zealand
- Department of Physics, University of Auckland, Auckland, New Zealand
- School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
| | - Michael J Plank
- Te Pūnaha Matatini: the Centre for Complex Systems and Networks, Auckland, New Zealand.
- School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand.
| | - Rachelle N Binny
- Te Pūnaha Matatini: the Centre for Complex Systems and Networks, Auckland, New Zealand
- Manaaki Whenua, Lincoln, New Zealand
| | - Shaun C Hendy
- Te Pūnaha Matatini: the Centre for Complex Systems and Networks, Auckland, New Zealand
- Department of Physics, University of Auckland, Auckland, New Zealand
| | - Audrey Lustig
- Te Pūnaha Matatini: the Centre for Complex Systems and Networks, Auckland, New Zealand
- Manaaki Whenua, Lincoln, New Zealand
| | - Kannan Ridings
- Te Pūnaha Matatini: the Centre for Complex Systems and Networks, Auckland, New Zealand
- Department of Physics, University of Auckland, Auckland, New Zealand
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207
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Lyngse FP, Kirkeby C, Halasa T, Andreasen V, Skov RL, Møller FT, Krause TG, Mølbak K. Nationwide study on SARS-CoV-2 transmission within households from lockdown to reopening, Denmark, 27 February 2020 to 1 August 2020. EURO SURVEILLANCE : BULLETIN EUROPEEN SUR LES MALADIES TRANSMISSIBLES = EUROPEAN COMMUNICABLE DISEASE BULLETIN 2022; 27. [PMID: 35144726 PMCID: PMC8832519 DOI: 10.2807/1560-7917.es.2022.27.6.2001800] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background The COVID-19 pandemic is one of the most serious global public health threats of recent times. Understanding SARS-CoV-2 transmission is key for outbreak response and to take action against the spread of disease. Transmission within the household is a concern, especially because infection control is difficult to apply within this setting. Aim The objective of this observational study was to investigate SARS-CoV-2 transmission in Danish households during the early stages of the COVID-19 pandemic. Methods We used comprehensive administrative register data from Denmark, comprising the full population and all COVID-19 tests from 27 February 2020 to 1 August 2020, to estimate household transmission risk and attack rate. Results We found that the day after receiving a positive test result within the household, 35% (788/2,226) of potential secondary cases were tested and 13% (98/779) of these were positive. In 6,782 households, we found that 82% (1,827/2,226) of potential secondary cases were tested within 14 days and 17% (371/2,226) tested positive as secondary cases, implying an attack rate of 17%. We found an approximate linear increasing relationship between age and attack rate. We investigated the transmission risk from primary cases by age, and found an increasing risk with age of primary cases for adults (aged ≥ 15 years), while the risk seems to decrease with age for children (aged < 15 years). Conclusions Although there is an increasing attack rate and transmission risk of SARS-CoV-2 with age, children are also able to transmit SARS-CoV-2 within the household.
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Affiliation(s)
- Frederik Plesner Lyngse
- Statens Serum Institut, Copenhagen, Denmark.,Danish Ministry of Health, Copenhagen, Denmark.,Department of Economics & Center for Economic Behaviour and Inequality, University of Copenhagen, Copenhagen, Denmark
| | - Carsten Kirkeby
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tariq Halasa
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Viggo Andreasen
- Department of Science, Roskilde University, Roskilde, Denmark
| | | | | | | | - Kåre Mølbak
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Statens Serum Institut, Copenhagen, Denmark
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208
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Frey K, Hagedorn B, McCarthy KA, Hutubessy R, Wang SA. Modeling anticipated changes in numbers of SARS-CoV-2 infections within communities due to immunization campaigns. Gates Open Res 2022; 6:7. [PMID: 36299735 PMCID: PMC9576906 DOI: 10.12688/gatesopenres.13448.1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/31/2022] [Indexed: 09/07/2024] Open
Abstract
Background: As SARS-CoV-2 spread in early 2020, uncertainty about the scope, duration, and impact of the unfolding outbreaks caused numerous countries to interrupt many routine activities, including health services. Because immunization is an essential health service, modeling changes in SARS-CoV-2 infections among communities and health workers due to different vaccination activities was undertaken to understand the risks and to inform approaches to resume services. Methods: Agent-based modeling examined the impact of Supplemental Immunization Activities (SIAs) delivery strategies on SARS-CoV-2 transmission in communities and health workers for six countries capturing various demographic profiles and health system performance: Angola, Ecuador, Lao PDR, Nepal, Pakistan, and Ukraine. Results: Urban, fixed-post SIAs during periods of high SARS-CoV-2 prevalence increased infections within the community by around 28 [range:0-79] per 1000 vaccinations. House-to-house SIAs in mixed urban and rural contexts may import infections into previously naïve communities. Infections are elevated by around 60 [range:0-230] per 1000 vaccinations, but outcomes are sensitive to prevalence in health workers and SIA timing relative to peak. Conclusions: Younger populations experience lower transmission intensity and fewer excess infections per childhood vaccine delivered. Large rural populations have lower transmission intensity but face a greater risk of introduction of SARS-CoV-2 during an SIA.
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Affiliation(s)
- Kurt Frey
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, 98109, USA
| | - Brittany Hagedorn
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, 98109, USA
| | - Kevin A. McCarthy
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, 98109, USA
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209
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Bisanzio D, Reithinger R, Alqunaibet A, Almudarra S, Alsukait RF, Dong D, Zhang Y, El-Saharty S, Herbst CH. Estimating the effect of non-pharmaceutical interventions to mitigate COVID-19 spread in Saudi Arabia. BMC Med 2022; 20:51. [PMID: 35125108 PMCID: PMC8818364 DOI: 10.1186/s12916-022-02232-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 01/03/2022] [Indexed: 02/17/2023] Open
Abstract
BACKGROUND The Kingdom of Saudi Arabia (KSA) quickly controlled the spread of SARS-CoV-2 by implementing several non-pharmaceutical interventions (NPIs), including suspension of international and national travel, local curfews, closing public spaces (i.e., schools and universities, malls and shops), and limiting religious gatherings. The KSA also mandated all citizens to respect physical distancing and to wear face masks. However, after relaxing some restrictions during June 2020, the KSA is now planning a strategy that could allow resuming in-person education and international travel. The aim of our study was to evaluate the effect of NPIs on the spread of the COVID-19 and test strategies to open schools and resume international travel. METHODS We built a spatial-explicit individual-based model to represent the whole KSA population (IBM-KSA). The IBM-KSA was parameterized using country demographic, remote sensing, and epidemiological data. A social network was created to represent contact heterogeneity and interaction among age groups of the population. The IBM-KSA also simulated the movement of people across the country based on a gravity model. We used the IBM-KSA to evaluate the effect of different NPIs adopted by the KSA (physical distancing, mask-wearing, and contact tracing) and to forecast the impact of strategies to open schools and resume international travels. RESULTS The IBM-KSA results scenarios showed the high effectiveness of mask-wearing, physical distancing, and contact tracing in controlling the spread of the disease. Without NPIs, the KSA could have reported 4,824,065 (95% CI: 3,673,775-6,335,423) cases by June 2021. The IBM-KSA showed that mandatory mask-wearing and physical distancing saved 39,452 lives (95% CI: 26,641-44,494). In-person education without personal protection during teaching would have resulted in a high surge of COVID-19 cases. Compared to scenarios with no personal protection, enforcing mask-wearing and physical distancing in schools reduced cases, hospitalizations, and deaths by 25% and 50%, when adherence to these NPIs was set to 50% and 70%, respectively. The IBM-KSA also showed that a quarantine imposed on international travelers reduced the probability of outbreaks in the country. CONCLUSIONS This study showed that the interventions adopted by the KSA were able to control the spread of SARS-CoV-2 in the absence of a vaccine. In-person education should be resumed only if NPIs could be applied in schools and universities. International travel can be resumed but with strict quarantine rules. The KSA needs to keep strict NPIs in place until a high fraction of the population is vaccinated in order to reduce hospitalizations and deaths.
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Affiliation(s)
- Donal Bisanzio
- RTI International, Washington, D.C., USA. .,Epidemiology and Public Health Division, School of Medicine, University of Nottingham, Nottingham, UK.
| | | | | | | | - Reem F Alsukait
- College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.,World Bank, Washington, D.C., USA
| | - Di Dong
- World Bank, Washington, D.C., USA
| | - Yi Zhang
- World Bank, Washington, D.C., USA
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210
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Voigt A, Omholt S, Almaas E. Comparing the impact of vaccination strategies on the spread of COVID-19, including a novel household-targeted vaccination strategy. PLoS One 2022; 17:e0263155. [PMID: 35108311 PMCID: PMC8809548 DOI: 10.1371/journal.pone.0263155] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 01/12/2022] [Indexed: 12/18/2022] Open
Abstract
With limited availability of vaccines, an efficient use of the limited supply of vaccines in order to achieve herd immunity will be an important tool to combat the wide-spread prevalence of COVID-19. Here, we compare a selection of strategies for vaccine distribution, including a novel targeted vaccination approach (EHR) that provides a noticeable increase in vaccine impact on disease spread compared to age-prioritized and random selection vaccination schemes. Using high-fidelity individual-based computer simulations with Oslo, Norway as an example, we find that for a community reproductive number in a setting where the base pre-vaccination reproduction number R = 2.1 without population immunity, the EHR method reaches herd immunity at 48% of the population vaccinated with 90% efficiency, whereas the common age-prioritized approach needs 89%, and a population-wide random selection approach requires 61%. We find that age-based strategies have a substantially weaker impact on epidemic spread and struggle to achieve herd immunity under the majority of conditions. Furthermore, the vaccination of minors is essential to achieving herd immunity, even for ideal vaccines providing 100% protection.
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Affiliation(s)
- André Voigt
- Department of Biotechnology and Food Science, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
| | - Stig Omholt
- Department of Circulation and Medical Imaging, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
| | - Eivind Almaas
- Department of Biotechnology and Food Science, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- K.G. Jebsen Center for Genetic Epidemiology, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
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211
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Lyngse FP, Kirkeby C, Halasa T, Andreasen V, Skov RL, Møller FT, Krause TG, Mølbak K. Nationwide study on SARS-CoV-2 transmission within households from lockdown to reopening, Denmark, 27 February 2020 to 1 August 2020. Euro Surveill 2022. [PMID: 35144726 DOI: 10.1101/2020.09.09.20191239] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/23/2023] Open
Abstract
BackgroundThe COVID-19 pandemic is one of the most serious global public health threats of recent times. Understanding SARS-CoV-2 transmission is key for outbreak response and to take action against the spread of disease. Transmission within the household is a concern, especially because infection control is difficult to apply within this setting.AimThe objective of this observational study was to investigate SARS-CoV-2 transmission in Danish households during the early stages of the COVID-19 pandemic.MethodsWe used comprehensive administrative register data from Denmark, comprising the full population and all COVID-19 tests from 27 February 2020 to 1 August 2020, to estimate household transmission risk and attack rate.ResultsWe found that the day after receiving a positive test result within the household, 35% (788/2,226) of potential secondary cases were tested and 13% (98/779) of these were positive. In 6,782 households, we found that 82% (1,827/2,226) of potential secondary cases were tested within 14 days and 17% (371/2,226) tested positive as secondary cases, implying an attack rate of 17%. We found an approximate linear increasing relationship between age and attack rate. We investigated the transmission risk from primary cases by age, and found an increasing risk with age of primary cases for adults (aged ≥ 15 years), while the risk seems to decrease with age for children (aged < 15 years).ConclusionsAlthough there is an increasing attack rate and transmission risk of SARS-CoV-2 with age, children are also able to transmit SARS-CoV-2 within the household.
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Affiliation(s)
- Frederik Plesner Lyngse
- Department of Economics & Center for Economic Behaviour and Inequality, University of Copenhagen, Copenhagen, Denmark
- Danish Ministry of Health, Copenhagen, Denmark
- Statens Serum Institut, Copenhagen, Denmark
| | - Carsten Kirkeby
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tariq Halasa
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Viggo Andreasen
- Department of Science, Roskilde University, Roskilde, Denmark
| | | | | | | | - Kåre Mølbak
- Statens Serum Institut, Copenhagen, Denmark
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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212
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Voirin N, Virlogeux V, Demont C, Kieffer A. Potential Impact of Nirsevimab on RSV Transmission and Medically Attended Lower Respiratory Tract Illness Caused by RSV: A Disease Transmission Model. Infect Dis Ther 2022; 11:277-292. [PMID: 34813073 PMCID: PMC8847469 DOI: 10.1007/s40121-021-00566-9] [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: 08/23/2021] [Accepted: 11/09/2021] [Indexed: 10/31/2022] Open
Abstract
INTRODUCTION Respiratory syncytial virus (RSV) is associated with significant morbidity worldwide, especially among infants. We evaluated the potential impact of prophylactic nirsevimab, a monoclonal antibody, in infants experiencing their first RSV season, and the number of medically-attended lower respiratory tract infection episodes caused by RSV (RSV-MALRTI) in the USA. METHODS We developed an age-structured, dynamic, deterministic compartmental model reflecting RSV natural history, incorporating USA demographic data and an age-specific contact matrix. We assumed either no effect of nirsevimab on transmission (scenario 1) or a 50% reduction of viral shedding (scenario 2). Model outcomes were RSV-MALRTIs, ICD-9 coded in the Marketscan® database by month. We focused on age groups corresponding to the first 2 years of life, during seven RSV seasons (2008-2015). RESULTS Scenario 1 illustrated the direct individual benefit when a universal immunization strategy is applied to all infants. In scenario 2, herd protection was observed across age groups, with 15.5% of all avoided cases due to reduced transmission; the greatest impact was in the youngest age group and a benefit was observed in those aged 65+ years. CONCLUSION These preliminary data suggest that single-dose nirsevimab will benefit infants experiencing their first RSV season, with a potential increase in effectiveness dependent on nirsevimab's mechanism of action.
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Affiliation(s)
- Nicolas Voirin
- Epidemiology and Modelling in Infectious Diseases (EPIMOD), Lent, France
| | - Victor Virlogeux
- Epidemiology and Modelling in Infectious Diseases (EPIMOD), Lent, France
- Hospices Civils de Lyon, Lyon, France
| | - Clarisse Demont
- Vaccine and Epidemiology Modelling, Sanofi Pasteur, Lyon, France
| | - Alexia Kieffer
- Health Economics and Value Assessment, Sanofi Pasteur, Siège Mondial, 14 Espace Henry Vallée, 69007, Lyon, France.
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213
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Mohsin M, Jamil K, Naseem S, Sarfraz M, Ivascu L. Elongating Nexus Between Workplace Factors and Knowledge Hiding Behavior: Mediating Role of Job Anxiety. Psychol Res Behav Manag 2022; 15:441-457. [PMID: 35250318 PMCID: PMC8888195 DOI: 10.2147/prbm.s348467] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 02/10/2022] [Indexed: 12/30/2022] Open
Abstract
Purpose The study objective is to investigate the relationship between workplace ostracism, workplace incivility, and knowledge hiding behavior (evasive hiding, playing dumb, rationalized hiding) while considering the mediating role of job anxiety. Methods The study collected data through structured questionnaires from 275 participants (ie, employees) working in the small to medium-sized enterprise of five big cities of Pakistan. The study adopted a structured equation modeling technique for data analysis. Results Significantly, the study results suggest a positive effect of workplace ostracism and workplace incivility on employees’ knowledge hiding behavior, and job anxiety significantly mediates the relationship between workplace ostracism, workplace incivility, and knowledge hiding behavior of employees. Conclusion The present study highlights the need to examine the personality disposition for understanding the relationship between the variables (eg, workplace ostracism, workplace incivility, knowledge hiding behavior). Employees’ inappropriate behavior had suppressed by initiating a campaign for a realistic job preview, setting an exceptional example. The study significantly contributes to the current literature on knowledge hiding behavior by presenting valuable insight into organizational and individual variables, subsequently influencing the knowledge hiding behavior of individuals. Indeed, this study is the first to investigate the predictive effect of the proposed variables.
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Affiliation(s)
- Muhammad Mohsin
- School of Business, Hunan University of Humanities, Science and Technology, Loudi, Hunan, 417000, People’s Republic of China
| | - Khalid Jamil
- School of Economics and Management North China Electric Power University, Beijing, 102206, People’s Republic of China
| | - Sobia Naseem
- School of Economics and Management, Shijiazhuang Tiedao University, Shijiazhuang, Hebei, 050043, People’s Republic of China
| | - Muddassar Sarfraz
- Department of Commerce & Business, Government College University Faisalabad, Layyah Campus, Layyah, 31200, Pakistan
- College of International Students, Wuxi University, 214105, Wuxi, Jiangsu, People’s Republic of China
- Correspondence: Muddassar Sarfraz, Email
| | - Larisa Ivascu
- Faculty of Management in Production and Transportation, Politehnica University of Timisoara, Timisoara, Romania
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214
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Hagens A, Cordova-Pozo K, Postma M, Wilschut J, Zino L, van der Schans J. Reconstructing the Effectiveness of Policy Measures to Avoid Next-Wave COVID-19 Infections and Deaths Using a Dynamic Simulation Model: Implications for Health Technology Assessment. FRONTIERS IN MEDICAL TECHNOLOGY 2022; 3:666581. [PMID: 35156083 PMCID: PMC8825500 DOI: 10.3389/fmedt.2021.666581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 12/15/2021] [Indexed: 11/24/2022] Open
Abstract
Objective The goal of this study was to dynamically model next-wave scenarios to observe the impact of different lockdown measures on the infection rates (IR) and mortality for two different prototype countries, mimicking the 1st year of the COVID-19 pandemic in Europe. Methods A dynamic simulation SIRD model was designed to assess the effectiveness of policy measures on four next-wave scenarios, each preceded by two different lockdowns. The four scenarios were (1) no-measures, (2) uniform measures, (3) differential measures based on isolating > 60 years of age group, and (4) differential measures with additional contact reduction measures for the 20–60 years of age group. The dynamic simulation model was prepared for two prototype European countries, Northwestern (NW) and Southern (S) country. Both prototype countries were characterized based on age composition and contact matrix. Results The results show that the outcomes of the next-wave scenarios depend on number of infections of previous lockdowns. All scenarios reduce the incremental deaths compared with a no-measures scenario. Differential measures show lower number of deaths despite an increase of infections. Additionally, prototype S shows overall more deaths compared with prototype NW due to a higher share of older citizens. Conclusion This study shows that differential measures are a worthwhile option for controlling the COVID-19 epidemic. This may also be the case in situations where relevant parts of the population have taken up vaccination. Additionally, the effectiveness of interventions strongly depends on the number of previously infected individuals. The results of this study may be useful when planning and forecasting the impact of non-pharmacological interventions and vaccination campaigns.
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Affiliation(s)
- Arnold Hagens
- Department of Health Sciences, University of Groningen (RUG), University Medical Center Groningen, Groningen, Netherlands
- *Correspondence: Arnold Hagens
| | - Kathya Cordova-Pozo
- Department of Health Sciences, University of Groningen (RUG), University Medical Center Groningen, Groningen, Netherlands
- Institute for Management Research, Radboud University, Nijmegen, Netherlands
| | - Maarten Postma
- Department of Health Sciences, University of Groningen (RUG), University Medical Center Groningen, Groningen, Netherlands
- Department of Economics, Econometrics and Finance, Faculty of Economics and Business, University of Groningen, Groningen, Netherlands
- Center of Excellence in Higher Education for Pharmaceutical Care Innovation, Universitas Padjadjaran, Bandung, Indonesia
- Department of Pharmacology & Therapy, Universitas Airlangga, Surabaya, Indonesia
| | - Jan Wilschut
- Department of Medical Microbiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Lorenzo Zino
- Faculty of Science and Engineering, University of Groningen, Groningen, Netherlands
| | - Jurjen van der Schans
- Department of Health Sciences, University of Groningen (RUG), University Medical Center Groningen, Groningen, Netherlands
- Department of Economics, Econometrics and Finance, Faculty of Economics and Business, University of Groningen, Groningen, Netherlands
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Hupert N, Marín-Hernández D, Gao B, Águas R, Nixon DF. Heterologous vaccination interventions to reduce pandemic morbidity and mortality: Modeling the US winter 2020 COVID-19 wave. Proc Natl Acad Sci U S A 2022; 119:e2025448119. [PMID: 35012976 PMCID: PMC8784160 DOI: 10.1073/pnas.2025448119] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 12/02/2021] [Indexed: 12/12/2022] Open
Abstract
COVID-19 remains a stark health threat worldwide, in part because of minimal levels of targeted vaccination outside high-income countries and highly transmissible variants causing infection in vaccinated individuals. Decades of theoretical and experimental data suggest that nonspecific effects of non-COVID-19 vaccines may help bolster population immunological resilience to new pathogens. These routine vaccinations can stimulate heterologous cross-protective effects, which modulate nontargeted infections. For example, immunization with Bacillus Calmette-Guérin, inactivated influenza vaccine, oral polio vaccine, and other vaccines have been associated with some protection from SARS-CoV-2 infection and amelioration of COVID-19 disease. If heterologous vaccine interventions (HVIs) are to be seriously considered by policy makers as bridging or boosting interventions in pandemic settings to augment nonpharmaceutical interventions and specific vaccination efforts, evidence is needed to determine their optimal implementation. Using the COVID-19 International Modeling Consortium mathematical model, we show that logistically realistic HVIs with low (5 to 15%) effectiveness could have reduced COVID-19 cases, hospitalization, and mortality in the United States fall/winter 2020 wave. Similar to other mass drug administration campaigns (e.g., for malaria), HVI impact is highly dependent on both age targeting and intervention timing in relation to incidence, with maximal benefit accruing from implementation across the widest age cohort when the pandemic reproduction number is >1.0. Optimal HVI logistics therefore differ from optimal rollout parameters for specific COVID-19 immunizations. These results may be generalizable beyond COVID-19 and the US to indicate how even minimally effective heterologous immunization campaigns could reduce the burden of future viral pandemics.
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Affiliation(s)
- Nathaniel Hupert
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065;
- Division of General Internal Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY 10065
- Cornell Institute for Disease and Disaster Preparedness, Cornell University, New York, NY 10065
| | - Daniela Marín-Hernández
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065
| | - Bo Gao
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Ricardo Águas
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Douglas F Nixon
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, NY 10065
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216
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Al-Zoughool M, Oraby T, Vainio H, Gasana J, Longenecker J, Al Ali W, AlSeaidan M, Elsaadany S, Tyshenko MG. Using a stochastic continuous-time Markov chain model to examine alternative timing and duration of the COVID-19 lockdown in Kuwait: what can be done now? Arch Public Health 2022; 80:22. [PMID: 34998438 PMCID: PMC8742165 DOI: 10.1186/s13690-021-00778-y] [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: 02/08/2021] [Accepted: 12/21/2021] [Indexed: 11/18/2022] Open
Abstract
Background Kuwait had its first COVID-19 in late February, and until October 6, 2020 it recorded 108,268 cases and 632 deaths. Despite implementing one of the strictest control measures-including a three-week complete lockdown, there was no sign of a declining epidemic curve. The objective of the current analyses is to determine, hypothetically, the optimal timing and duration of a full lockdown in Kuwait that would result in controlling new infections and lead to a substantial reduction in case hospitalizations. Methods The analysis was conducted using a stochastic Continuous-Time Markov Chain (CTMC), eight state model that depicts the disease transmission and spread of SARS-CoV 2. Transmission of infection occurs between individuals through social contacts at home, in schools, at work, and during other communal activities. Results The model shows that a lockdown 10 days before the epidemic peak for 90 days is optimal but a more realistic duration of 45 days can achieve about a 45% reduction in both new infections and case hospitalizations. Conclusions In the view of the forthcoming waves of the COVID19 pandemic anticipated in Kuwait using a correctly-timed and sufficiently long lockdown represents a workable management strategy that encompasses the most stringent form of social distancing with the ability to significantly reduce transmissions and hospitalizations. Supplementary Information The online version contains supplementary material available at 10.1186/s13690-021-00778-y.
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Affiliation(s)
- Mustafa Al-Zoughool
- Department of Environmental and Occupational Health Faculty of Public Health, University of Kuwait, Kuwait City, Kuwait.
| | - Tamer Oraby
- School of Mathematical and Statistical Sciences, University of Texas Rio Grande Valley, Edinburg, TX, 78539, USA
| | - Harri Vainio
- Department of Environmental and Occupational Health Faculty of Public Health, University of Kuwait, Kuwait City, Kuwait
| | - Janvier Gasana
- Department of Environmental and Occupational Health Faculty of Public Health, University of Kuwait, Kuwait City, Kuwait
| | - Joseph Longenecker
- Department of Environmental and Occupational Health Faculty of Public Health, University of Kuwait, Kuwait City, Kuwait
| | - Walid Al Ali
- Department of Epidemiology and Biostatistics, Faculty of Public Health, University of Kuwait, 13110, Safat, Kuwait
| | - Mohammad AlSeaidan
- Department of Occupational Health, Ministry of Health, Kuwait City, Kuwait
| | - Susie Elsaadany
- Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, K1H 8M5, Canada
| | - Michael G Tyshenko
- McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, Ottawa, ON, K1N 6N5, Canada
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217
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Crawford FW, Jones SA, Cartter M, Dean SG, Warren JL, Li ZR, Barbieri J, Campbell J, Kenney P, Valleau T, Morozova O. Impact of close interpersonal contact on COVID-19 incidence: Evidence from 1 year of mobile device data. SCIENCE ADVANCES 2022; 8:eabi5499. [PMID: 34995121 PMCID: PMC8741180 DOI: 10.1126/sciadv.abi5499] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 11/17/2021] [Indexed: 05/06/2023]
Abstract
Close contact between people is the primary route for transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). We quantified interpersonal contact at the population level using mobile device geolocation data. We computed the frequency of contact (within 6 feet) between people in Connecticut during February 2020 to January 2021 and aggregated counts of contact events by area of residence. When incorporated into a SEIR-type model of COVID-19 transmission, the contact rate accurately predicted COVID-19 cases in Connecticut towns. Contact in Connecticut explains the initial wave of infections during March to April, the drop in cases during June to August, local outbreaks during August to September, broad statewide resurgence during September to December, and decline in January 2021. The transmission model fits COVID-19 transmission dynamics better using the contact rate than other mobility metrics. Contact rate data can help guide social distancing and testing resource allocation.
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Affiliation(s)
- Forrest W. Crawford
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
- Yale School of Management, New Haven, CT, USA
| | - Sydney A. Jones
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA
- Infectious Diseases Section, Connecticut Department of Public Health, Hartford, CT, USA
| | - Matthew Cartter
- Infectious Diseases Section, Connecticut Department of Public Health, Hartford, CT, USA
| | - Samantha G. Dean
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Joshua L. Warren
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Zehang Richard Li
- Department of Statistics, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | | | | | | | - Olga Morozova
- Program in Public Health and Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
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218
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Temerev A, Rozanova L, Keiser O, Estill J. Geospatial model of COVID-19 spreading and vaccination with event Gillespie algorithm. NONLINEAR DYNAMICS 2022; 109:239-248. [PMID: 35095197 PMCID: PMC8783199 DOI: 10.1007/s11071-021-07186-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 12/08/2021] [Indexed: 05/07/2023]
Abstract
We have developed a mathematical model and stochastic numerical simulation for the transmission of COVID-19 and other similar infectious diseases that accounts for the geographic distribution of population density, detailed down to the level of location of individuals, and age-structured contact rates. Our analytical framework includes a surrogate model optimization process to rapidly fit the parameters of the model to the observed epidemic curves for cases, hospitalizations, and deaths. This toolkit (the model, the simulation code, and the optimizer) is a useful tool for policy makers and epidemic response teams, who can use it to forecast epidemic development scenarios in local settings (at the scale of cities to large countries) and design optimal response strategies. The simulation code also enables spatial visualization, where detailed views of epidemic scenarios are displayed directly on maps of population density. The model and simulation also include the vaccination process, which can be tailored to different levels of efficiency and efficacy of different vaccines. We used the developed framework to generate predictions for the spread of COVID-19 in the canton of Geneva, Switzerland, and validated them by comparing the calculated number of cases and recoveries with data from local seroprevalence studies.
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Affiliation(s)
- Alexander Temerev
- Institute of Global Health, University of Geneva, Geneva, Switzerland
| | - Liudmila Rozanova
- Institute of Global Health, University of Geneva, Geneva, Switzerland
| | - Olivia Keiser
- Institute of Global Health, University of Geneva, Geneva, Switzerland
| | - Janne Estill
- Institute of Global Health, University of Geneva, Geneva, Switzerland
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219
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Retrospectively modeling the effects of increased global vaccine sharing on the COVID-19 pandemic. Nat Med 2022; 28:2416-2423. [PMID: 36302894 PMCID: PMC9671807 DOI: 10.1038/s41591-022-02064-y] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 09/29/2022] [Indexed: 01/14/2023]
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused considerable morbidity and mortality worldwide. The protection provided by vaccines and booster doses offered a method of mitigating severe clinical outcomes and mortality. However, by the end of 2021, the global distribution of vaccines was highly heterogeneous, with some countries gaining over 90% coverage in adults, whereas others reached less than 2%. In this study, we used an age-structured model of SARS-CoV-2 dynamics, matched to national data from 152 countries in 2021, to investigate the global impact of different potential vaccine sharing protocols that attempted to address this inequity. We quantified the effects of implemented vaccine rollout strategies on the spread of SARS-CoV-2, the subsequent global burden of disease and the emergence of novel variants. We found that greater vaccine sharing would have lowered the total global burden of disease, and any associated increases in infections in previously vaccine-rich countries could have been mitigated by reduced relaxation of non-pharmaceutical interventions. Our results reinforce the health message, pertinent to future pandemics, that vaccine distribution proportional to wealth, rather than to need, may be detrimental to all.
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220
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Favas C, Jarrett P, Ratnayake R, Watson OJ, Checchi F. Country differences in transmissibility, age distribution and case-fatality of SARS-CoV-2: a global ecological analysis. Int J Infect Dis 2022; 114:210-218. [PMID: 34749011 PMCID: PMC8571103 DOI: 10.1016/j.ijid.2021.11.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 09/27/2021] [Accepted: 11/01/2021] [Indexed: 12/15/2022] Open
Abstract
Objectives The first COVID-19 pandemic waves in many low-income countries appeared milder than initially forecasted. We conducted a country-level ecological study to describe patterns in key SARS-CoV-2 outcomes by country and region and explore associations with potential explanatory factors, including population age structure and prior exposure to endemic parasitic infections. Methods We collected publicly available data and compared them using standardisation techniques. We then explored the association between exposures and outcomes using random forest and linear regression. We adjusted for potential confounders and plausible effect modifications. Results While mean time-varying reproduction number was highest in the European and Americas regions, median age of death was lower in the Africa region, with a broadly similar case-fatality ratio. Population age was strongly associated with mean (β=0.01, 95% CI, 0.005, 0.011) and median age of cases (β=-0.40, 95% CI, -0.53, -0.26) and deaths (β= 0.40, 95% CI, 0.17, 0.62). Conclusions Population age seems an important country-level factor explaining both transmissibility and age distribution of observed cases and deaths. Endemic infections seem unlikely, from this analysis, to be key drivers of the variation in observed epidemic trends. Our study was limited by the availability of outcome data and its causally uncertain ecological design.
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Affiliation(s)
- Caroline Favas
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel St, Bloomsbury, London, WC1E 7HT, United Kingdom.
| | - Prudence Jarrett
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel St, Bloomsbury, London, WC1E 7HT, United Kingdom
| | - Ruwan Ratnayake
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel St, Bloomsbury, London, WC1E 7HT, United Kingdom
| | - Oliver J Watson
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Francesco Checchi
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel St, Bloomsbury, London, WC1E 7HT, United Kingdom
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221
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Reguly IZ, Csercsik D, Juhász J, Tornai K, Bujtár Z, Horváth G, Keömley-Horváth B, Kós T, Cserey G, Iván K, Pongor S, Szederkényi G, Röst G, Csikász-Nagy A. Microsimulation based quantitative analysis of COVID-19 management strategies. PLoS Comput Biol 2022; 18:e1009693. [PMID: 34982766 PMCID: PMC8759654 DOI: 10.1371/journal.pcbi.1009693] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 01/14/2022] [Accepted: 11/29/2021] [Indexed: 12/11/2022] Open
Abstract
Pandemic management requires reliable and efficient dynamical simulation to predict and control disease spreading. The COVID-19 (SARS-CoV-2) pandemic is mitigated by several non-pharmaceutical interventions, but it is hard to predict which of these are the most effective for a given population. We developed the computationally effective and scalable, agent-based microsimulation framework PanSim, allowing us to test control measures in multiple infection waves caused by the spread of a new virus variant in a city-sized societal environment using a unified framework fitted to realistic data. We show that vaccination strategies prioritising occupational risk groups minimise the number of infections but allow higher mortality while prioritising vulnerable groups minimises mortality but implies an increased infection rate. We also found that intensive vaccination along with non-pharmaceutical interventions can substantially suppress the spread of the virus, while low levels of vaccination, premature reopening may easily revert the epidemic to an uncontrolled state. Our analysis highlights that while vaccination protects the elderly from COVID-19, a large percentage of children will contract the virus, and we also show the benefits and limitations of various quarantine and testing scenarios. The uniquely detailed spatio-temporal resolution of PanSim allows the design and testing of complex, specifically targeted interventions with a large number of agents under dynamically changing conditions.
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Affiliation(s)
- István Z. Reguly
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- Cytocast Kft., Vecsés, Hungary
| | - Dávid Csercsik
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - János Juhász
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- Institute of Medical Microbiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary
| | - Kálmán Tornai
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Zsófia Bujtár
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Gergely Horváth
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Bence Keömley-Horváth
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- Cytocast Kft., Vecsés, Hungary
| | - Tamás Kós
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - György Cserey
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Kristóf Iván
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Sándor Pongor
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Gábor Szederkényi
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Gergely Röst
- Bolyai Institute, University of Szeged, Szeged, Hungary
| | - Attila Csikász-Nagy
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- Cytocast Kft., Vecsés, Hungary
- Randall Centre for Cell and Molecular Biophysics, King’s College London, London, United Kingdom
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222
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Knight J, Ma H, Ghasemi A, Hamilton M, Brown K, Mishra S. Adaptive data-driven age and patch mixing in contact networks with recurrent mobility. MethodsX 2021; 9:101614. [PMID: 35004190 PMCID: PMC8719332 DOI: 10.1016/j.mex.2021.101614] [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: 10/01/2021] [Accepted: 12/21/2021] [Indexed: 11/26/2022] Open
Abstract
Infectious disease transmission models often stratify populations by age and geographic patches. Contact patterns between age groups and patches are key parameters in such models. Arenas et al. (2020) develop an approach to simulate contact patterns associated with recurrent mobility between patches, such as due to work, school, and other regular travel. Using their approach, mixing between patches is greater than mobility data alone would suggest, because individuals from patches A and B can form contacts if they meet in patch C. We build upon their approach to address three potential gaps that remain, outlined in the bullets below. We describe the steps required to implement our approach in detail, and present step-wise results of an example application to generate contact matrices for SARS-CoV-2 transmission modelling in Ontario, Canada. We also provide methods for deriving the mobility matrix based on GPS mobility data (appendix). • Our approach includes a distribution of contacts by age that is responsive to the underlying age distributions of the mixing populations. • Our approach maintains different age mixing patterns by contact type, such that changes to the numbers of different types of contacts are appropriately reflected in changes to overall age mixing patterns. • Our approach distinguishes between two mixing pools associated with each patch, with possible implications for the overall connectivity of the population: the home pool, in which contacts can only be formed with other individuals residing in the same patch, and the travel pool, in which contacts can be formed with some residents of, and any other visitors to the patch.
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Affiliation(s)
- Jesse Knight
- MAP Centre for Urban Health Solutions, Unity Health Toronto, Canada.,Institute of Medical Science, University of Toronto, Canada
| | - Huiting Ma
- MAP Centre for Urban Health Solutions, Unity Health Toronto, Canada
| | - Amir Ghasemi
- Communications Research Centre Canada, Ottawa, Canada
| | | | - Kevin Brown
- Public Health Ontario, Canada.,Dalla Lana School of Public Health, University of Toronto, Canada
| | - Sharmistha Mishra
- MAP Centre for Urban Health Solutions, Unity Health Toronto, Canada.,Institute of Medical Science, University of Toronto, Canada.,Dalla Lana School of Public Health, University of Toronto, Canada.,Division of Infectious Diseases, Department of Medicine, University of Toronto, Canada
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223
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Pageaud S, Pothier C, Rigotti C, Eyraud-Loisel A, Bertoglio JP, Bienvenüe A, Leboisne N, Ponthus N, Gauchon R, Gueyffier F, Vanhems P, Iwaz J, Loisel S, Roy P. Expected Evolution of COVID-19 Epidemic in France for Several Combinations of Vaccination Strategies and Barrier Measures. Vaccines (Basel) 2021; 9:1462. [PMID: 34960207 PMCID: PMC8708137 DOI: 10.3390/vaccines9121462] [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: 10/20/2021] [Revised: 11/23/2021] [Accepted: 12/02/2021] [Indexed: 11/30/2022] Open
Abstract
The outbreak of the SARS-CoV-2 virus, enhanced by rapid spreads of variants, has caused a major international health crisis, with serious public health and economic consequences. An agent-based model was designed to simulate the evolution of the epidemic in France over 2021 and the first six months of 2022. The study compares the efficiencies of four theoretical vaccination campaigns (over 6, 9, 12, and 18 months), combined with various non-pharmaceutical interventions. In France, with the emergence of the Alpha variant, without vaccination and despite strict barrier measures, more than 600,000 deaths would be observed. An efficient vaccination campaign (i.e., total coverage of the French population) over six months would divide the death toll by 10. A vaccination campaign of 12, instead of 6, months would slightly increase the disease-related mortality (+6%) but require a 77% increase in ICU bed-days. A campaign over 18 months would increase the disease-related mortality by 17% and require a 244% increase in ICU bed-days. Thus, it seems mandatory to vaccinate the highest possible percentage of the population within 12, or better yet, 9 months. The race against the epidemic and virus variants is really a matter of vaccination strategy.
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Affiliation(s)
- Simon Pageaud
- Université de Lyon, F-69000 Lyon, France; (S.P.); (F.G.); (J.I.)
- Université Claude Bernard Lyon 1, F-69100 Villeurbanne, France
- CNRS UMR 5558, Laboratoire de Biométrie et Biologie Évolutive, F-69100 Villeurbanne, France
- Service de Biostatistique-Bioinformatique, Pôle Santé Publique, Hospices Civils de Lyon, F-69003 Lyon, France
- Laboratoire de Sciences Actuarielle et Financière (LSAF), Institut de Science Financière et d’Assurances (ISFA), Université Claude Bernard Lyon 1, F-69007 Lyon, France; (A.E.-L.); (A.B.); (N.L.); (R.G.); (S.L.)
- Fondation du Risque, Groupe Louis Bachelier, F-75002 Paris, France
| | - Catherine Pothier
- CNRS UMR 5205, Laboratoire d’InfoRmatique en Image et Systèmes d’Information (LIRIS), F-69621 Villeurbanne, France; (C.P.); (C.R.)
- Institut National des Sciences Appliquées de Lyon (INSA), F-69621 Villeurbanne, France
| | - Christophe Rigotti
- CNRS UMR 5205, Laboratoire d’InfoRmatique en Image et Systèmes d’Information (LIRIS), F-69621 Villeurbanne, France; (C.P.); (C.R.)
- Institut National des Sciences Appliquées de Lyon (INSA), F-69621 Villeurbanne, France
- INRIA Grenoble-Rhône-Alpes, F-38334 Montbonnot, France
| | - Anne Eyraud-Loisel
- Laboratoire de Sciences Actuarielle et Financière (LSAF), Institut de Science Financière et d’Assurances (ISFA), Université Claude Bernard Lyon 1, F-69007 Lyon, France; (A.E.-L.); (A.B.); (N.L.); (R.G.); (S.L.)
| | - Jean-Pierre Bertoglio
- CNRS UMR 5509, Laboratoire de Mécanique des Fluides et d’Acoustique (LMFA), F-69130 Ecully, France;
- École Centrale de Lyon, F-69130 Lyon, France;
| | - Alexis Bienvenüe
- Laboratoire de Sciences Actuarielle et Financière (LSAF), Institut de Science Financière et d’Assurances (ISFA), Université Claude Bernard Lyon 1, F-69007 Lyon, France; (A.E.-L.); (A.B.); (N.L.); (R.G.); (S.L.)
| | - Nicolas Leboisne
- Laboratoire de Sciences Actuarielle et Financière (LSAF), Institut de Science Financière et d’Assurances (ISFA), Université Claude Bernard Lyon 1, F-69007 Lyon, France; (A.E.-L.); (A.B.); (N.L.); (R.G.); (S.L.)
| | - Nicolas Ponthus
- École Centrale de Lyon, F-69130 Lyon, France;
- CNRS UMR 5513, Laboratoire de Tribologie et Dynamique des Systèmes (LTDS), F-69130 Ecully, France
- École Nationale des Travaux Publics de l’État (ENTPE), F-69120 Vaulx-en-Velin, France
| | - Romain Gauchon
- Laboratoire de Sciences Actuarielle et Financière (LSAF), Institut de Science Financière et d’Assurances (ISFA), Université Claude Bernard Lyon 1, F-69007 Lyon, France; (A.E.-L.); (A.B.); (N.L.); (R.G.); (S.L.)
| | - François Gueyffier
- Université de Lyon, F-69000 Lyon, France; (S.P.); (F.G.); (J.I.)
- Université Claude Bernard Lyon 1, F-69100 Villeurbanne, France
- CNRS UMR 5558, Laboratoire de Biométrie et Biologie Évolutive, F-69100 Villeurbanne, France
- Service de Biostatistique-Bioinformatique, Pôle Santé Publique, Hospices Civils de Lyon, F-69003 Lyon, France
| | - Philippe Vanhems
- Service d’Hygiène, Épidémiologie, Infectiovigilance et Prévention, Hôpital Edouard Herriot, Hospices Civils de Lyon, F-69003 Lyon, France;
- Centre International de Recherche en Infectiologie (CIRI: Inserm U1111, CNRS UMR 5308, École Nationale Supérieure de Lyon), F-69007 Lyon, France
| | - Jean Iwaz
- Université de Lyon, F-69000 Lyon, France; (S.P.); (F.G.); (J.I.)
- Université Claude Bernard Lyon 1, F-69100 Villeurbanne, France
- CNRS UMR 5558, Laboratoire de Biométrie et Biologie Évolutive, F-69100 Villeurbanne, France
- Service de Biostatistique-Bioinformatique, Pôle Santé Publique, Hospices Civils de Lyon, F-69003 Lyon, France
| | - Stéphane Loisel
- Laboratoire de Sciences Actuarielle et Financière (LSAF), Institut de Science Financière et d’Assurances (ISFA), Université Claude Bernard Lyon 1, F-69007 Lyon, France; (A.E.-L.); (A.B.); (N.L.); (R.G.); (S.L.)
| | - Pascal Roy
- Université de Lyon, F-69000 Lyon, France; (S.P.); (F.G.); (J.I.)
- Université Claude Bernard Lyon 1, F-69100 Villeurbanne, France
- CNRS UMR 5558, Laboratoire de Biométrie et Biologie Évolutive, F-69100 Villeurbanne, France
- Service de Biostatistique-Bioinformatique, Pôle Santé Publique, Hospices Civils de Lyon, F-69003 Lyon, France
- CNRS UMR 5513, Laboratoire de Tribologie et Dynamique des Systèmes (LTDS), F-69130 Ecully, France
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224
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Kumar M, Abbas S. Age-Structured SIR Model for the Spread of Infectious Diseases Through Indirect Contacts. MEDITERRANEAN JOURNAL OF MATHEMATICS 2021; 19:14. [PMID: 38624724 PMCID: PMC8650539 DOI: 10.1007/s00009-021-01925-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 09/10/2021] [Accepted: 11/03/2021] [Indexed: 06/15/2023]
Abstract
In this article, we discuss an age-structured SIR model in which disease spread not only through direct person-to-person contacts, but also spread through indirect contacts. It is evident that age also plays a crucial role in SARS virus infection including COVID-19 infection. We formulate our model as an abstract semilinear Cauchy problem in an appropriate Banach space to show the existence of solution and also show the existence of steady states. In this study, it is assumed that the population is in a demographic stationary state and we show that there is no disease-free equilibrium point as long as there is a transmission of infection due to the indirect contacts in the environment. We also solved our model numerically to study the effect of indirect contacts on the density of infected individuals.
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Affiliation(s)
- Manoj Kumar
- School of Basic Sciences, Indian Institute of Technology Mandi, Kamand, Himachal Pradesh 175005 India
| | - Syed Abbas
- School of Basic Sciences, Indian Institute of Technology Mandi, Kamand, Himachal Pradesh 175005 India
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225
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Jaouimaa FZ, Dempsey D, Van Osch S, Kinsella S, Burke K, Wyse J, Sweeney J. An age-structured SEIR model for COVID-19 incidence in Dublin, Ireland with framework for evaluating health intervention cost. PLoS One 2021; 16:e0260632. [PMID: 34874981 PMCID: PMC8651129 DOI: 10.1371/journal.pone.0260632] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 11/13/2021] [Indexed: 11/19/2022] Open
Abstract
Strategies adopted globally to mitigate the threat of COVID-19 have primarily involved lockdown measures with substantial economic and social costs with varying degrees of success. Morbidity patterns of COVID-19 variants have a strong association with age, while restrictive lockdown measures have association with negative mental health outcomes in some age groups. Reduced economic prospects may also afflict some age cohorts more than others. Motivated by this, we propose a model to describe COVID-19 community spread incorporating the role of age-specific social interactions. Through a flexible parameterisation of an age-structured deterministic Susceptible Exposed Infectious Removed (SEIR) model, we provide a means for characterising different forms of lockdown which may impact specific age groups differently. Social interactions are represented through age group to age group contact matrices, which can be trained using available data and are thus locally adapted. This framework is easy to interpret and suitable for describing counterfactual scenarios, which could assist policy makers with regard to minimising morbidity balanced with the costs of prospective suppression strategies. Our work originates from an Irish context and we use disease monitoring data from February 29th 2020 to January 31st 2021 gathered by Irish governmental agencies. We demonstrate how Irish lockdown scenarios can be constructed using the proposed model formulation and show results of retrospective fitting to incidence rates and forward planning with relevant "what if / instead of" lockdown counterfactuals. Uncertainty quantification for the predictive approaches is described. Our formulation is agnostic to a specific locale, in that lockdown strategies in other regions can be straightforwardly encoded using this model.
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Affiliation(s)
| | - Daniel Dempsey
- School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland
| | - Suzanne Van Osch
- Kemmy Business School, University of Limerick, Limerick, Ireland
| | - Stephen Kinsella
- Kemmy Business School, University of Limerick, Limerick, Ireland
| | - Kevin Burke
- Department of Mathematics & Statistics, University of Limerick, Limerick, Ireland
| | - Jason Wyse
- School of Computer Science & Statistics, Trinity College Dublin, Dublin, Ireland
| | - James Sweeney
- Department of Mathematics & Statistics, University of Limerick, Limerick, Ireland
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226
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Kadelka C, McCombs A. Effect of homophily and correlation of beliefs on COVID-19 and general infectious disease outbreaks. PLoS One 2021; 16:e0260973. [PMID: 34855929 PMCID: PMC8639064 DOI: 10.1371/journal.pone.0260973] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 11/20/2021] [Indexed: 12/14/2022] Open
Abstract
Contact between people with similar opinions and characteristics occurs at a higher rate than among other people, a phenomenon known as homophily. The presence of clusters of unvaccinated people has been associated with increased incidence of infectious disease outbreaks despite high population-wide vaccination rates. The epidemiological consequences of homophily regarding other beliefs as well as correlations among beliefs or circumstances are poorly understood, however. Here, we use a simple compartmental disease model as well as a more complex COVID-19 model to study how homophily and correlation of beliefs and circumstances in a social interaction network affect the probability of disease outbreak and COVID-19-related mortality. We find that the current social context, characterized by the presence of homophily and correlations between who vaccinates, who engages in risk reduction, and individual risk status, corresponds to a situation with substantially worse disease burden than in the absence of heterogeneities. In the presence of an effective vaccine, the effects of homophily and correlation of beliefs and circumstances become stronger. Further, the optimal vaccination strategy depends on the degree of homophily regarding vaccination status as well as the relative level of risk mitigation high- and low-risk individuals practice. The developed methods are broadly applicable to any investigation in which node attributes in a graph might reasonably be expected to cluster or exhibit correlations.
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Affiliation(s)
- Claus Kadelka
- Department of Mathematics, Iowa State University, Ames, IA, United States of America
- * E-mail:
| | - Audrey McCombs
- Department of Statistics, Iowa State University, Ames, IA, United States of America
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227
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Kraay ANM, Nelson KN, Zhao CY, Demory D, Weitz JS, Lopman BA. Modeling serological testing to inform relaxation of social distancing for COVID-19 control. Nat Commun 2021; 12:7063. [PMID: 34862373 PMCID: PMC8642547 DOI: 10.1038/s41467-021-26774-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 10/19/2021] [Indexed: 01/24/2023] Open
Abstract
Serological testing remains a passive component of the public health response to the COVID-19 pandemic. Using a transmission model, we examine how serological testing could have enabled seropositive individuals to increase their relative levels of social interaction while offsetting transmission risks. We simulate widespread serological testing in New York City, South Florida, and Washington Puget Sound and assume seropositive individuals partially restore their social contacts. Compared to no intervention, our model suggests that widespread serological testing starting in late 2020 would have averted approximately 3300 deaths in New York City, 1400 deaths in South Florida and 11,000 deaths in Washington State by June 2021. In all sites, serological testing blunted subsequent waves of transmission. Findings demonstrate the potential benefit of widespread serological testing, had it been implemented in the pre-vaccine era, and remain relevant now amid the potential for emergence of new variants.
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Affiliation(s)
- Alicia N M Kraay
- Rollins School of Public Health, Emory University, Atlanta, GA, USA.
| | - Kristin N Nelson
- Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Conan Y Zhao
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
- Interdisciplinary Graduate Program in Quantitative Biosciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - David Demory
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Joshua S Weitz
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
- School of Physics, Georgia Institute of Technology, Atlanta, GA, USA
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228
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Otomaru H, Sornillo JBT, Kamigaki T, Bado SLP, Okamoto M, Saito-Obata M, Inobaya MT, Segubre-Mercado E, Alday PP, Saito M, Tallo VL, Quiambao BP, Oshitani H, Cook AR. Risk of Transmission and Viral Shedding From the Time of Infection for Respiratory Syncytial Virus in Households. Am J Epidemiol 2021; 190:2536-2543. [PMID: 34216204 PMCID: PMC8634588 DOI: 10.1093/aje/kwab181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 06/07/2021] [Accepted: 06/16/2021] [Indexed: 11/12/2022] Open
Abstract
Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection worldwide, but reports of temporal changes in the risk of transmission among close contacts has been scarce. This study aimed to examine an association between the viral load trajectory and transmission risk to develop a better control strategy for the disease spread. We conducted a household-based prospective cohort study in Biliran Province, the Philippines, and enrolled 451 participants to observe the development of acute respiratory infection. Including the cases found at the health-care facility, we analyzed the data of viral loads with symptom records obtained from 172 followed participants who had household member positive for RSV with a rapid test during an RSV outbreak in 2018-2019. We developed a model estimating a temporal change in the viral shedding from the infection and evaluated transmission dynamics. We found that most transmission events occurred within approximately 7 days of the household exposure, including potential presymptomatic transmissions. The inferred risk of infection among those younger than 5 years was 3.5 times higher than that of those older than 5 years. This finding suggested that the initial week after the household exposure is particularly important for preventing RSV spread.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | - Alex R Cook
- Correspondence to Dr. Alex Cook, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, 12 Science Drive 2, Singapore, Singapore 117549 (e-mail: )
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229
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Davis JT, Chinazzi M, Perra N, Mu K, Pastore Y Piontti A, Ajelli M, Dean NE, Gioannini C, Litvinova M, Merler S, Rossi L, Sun K, Xiong X, Longini IM, Halloran ME, Viboud C, Vespignani A. Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave. Nature 2021; 600:127-132. [PMID: 34695837 PMCID: PMC8636257 DOI: 10.1038/s41586-021-04130-w] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 10/13/2021] [Indexed: 11/24/2022]
Abstract
Considerable uncertainty surrounds the timeline of introductions and onsets of local transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) globally1-7. Although a limited number of SARS-CoV-2 introductions were reported in January and February 2020 (refs.8,9), the narrowness of the initial testing criteria, combined with a slow growth in testing capacity and porous travel screening10, left many countries vulnerable to unmitigated, cryptic transmission. Here we use a global metapopulation epidemic model to provide a mechanistic understanding of the early dispersal of infections and the temporal windows of the introduction of SARS-CoV-2 and onset of local transmission in Europe and the USA. We find that community transmission of SARS-CoV-2 was likely to have been present in several areas of Europe and the USA by January 2020, and estimate that by early March, only 1 to 4 in 100 SARS-CoV-2 infections were detected by surveillance systems. The modelling results highlight international travel as the key driver of the introduction of SARS-CoV-2, with possible introductions and transmission events as early as December 2019 to January 2020. We find a heterogeneous geographic distribution of cumulative infection attack rates by 4 July 2020, ranging from 0.78% to 15.2% across US states and 0.19% to 13.2% in European countries. Our approach complements phylogenetic analyses and other surveillance approaches and provides insights that can be used to design innovative, model-driven surveillance systems that guide enhanced testing and response strategies.
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Affiliation(s)
- Jessica T Davis
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA
| | - Matteo Chinazzi
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA
| | - Nicola Perra
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA
- Networks and Urban Systems Centre, University of Greenwich, London, UK
| | - Kunpeng Mu
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA
| | - Ana Pastore Y Piontti
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA
| | - Marco Ajelli
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA
| | - Natalie E Dean
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
| | | | - Maria Litvinova
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA
| | | | | | - Kaiyuan Sun
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | - Xinyue Xiong
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA
| | - Ira M Longini
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - M Elizabeth Halloran
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Cécile Viboud
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | - Alessandro Vespignani
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
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230
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Zheng Z, Pitzer VE, Shapiro ED, Bont LJ, Weinberger DM. Estimation of the Timing and Intensity of Reemergence of Respiratory Syncytial Virus Following the COVID-19 Pandemic in the US. JAMA Netw Open 2021; 4:e2141779. [PMID: 34913973 PMCID: PMC8678706 DOI: 10.1001/jamanetworkopen.2021.41779] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 11/08/2021] [Indexed: 12/21/2022] Open
Abstract
Importance Respiratory syncytial virus (RSV) is a leading cause of hospitalizations in young children. RSV largely disappeared in 2020 owing to precautions taken because of the COVID-19 pandemic. Estimating the timing and intensity of the reemergence of RSV and the age groups affected is crucial for planning for the administration of prophylactic antibodies and anticipating hospital capacity. Objective To examine the association of different factors, including mitigation strategies, duration of maternal-derived immunity, and importation of external infections, with the dynamics of reemergent RSV epidemics. Design, Setting, and Participants This simulation modeling study used mathematical models to reproduce the annual epidemics of RSV before the COVID-19 pandemic in New York and California. These models were modified to project the trajectory of RSV epidemics from 2020 to 2025 under different scenarios with varying stringency of mitigation measures for SARS-CoV-2. Simulations also evaluated factors likely to affect the reemergence of RSV epidemics, including introduction of the virus from out-of-state sources and decreased transplacentally acquired immunity in infants. Models using parameters fitted to similar inpatient data sets from Colorado and Florida were used to illustrate these associations in populations with biennial RSV epidemics and year-round RSV circulation, respectively. Statistical analysis was performed from February to October 2021. Main Outcomes and Measures The primary outcome of this study was defined as the estimated number of RSV hospitalizations each month in the entire population. Secondary outcomes included the age distribution of hospitalizations among children less than 5 years of age, incidence of any RSV infection, and incidence of RSV lower respiratory tract infection. Results Among a simulated population of 19.45 million people, virus introduction from external sources was associated with the emergence of the spring and summer epidemic in 2021. There was a tradeoff between the intensity of the spring and summer epidemic in 2021 and the intensity of the epidemic in the subsequent winter. Among children 1 year of age, the estimated incidence of RSV hospitalizations was 707 per 100 000 children per year in the 2021 and 2022 RSV season, compared with 355 per 100 000 children per year in a typical RSV season. Conclusions and Relevance This simulation modeling study found that virus introduction from external sources was associated with the spring and summer epidemics in 2021. These findings suggest that pediatric departments should be alert to large RSV outbreaks in the coming seasons, the intensity of which could depend on the size of the spring and summer epidemic in that location. Enhanced surveillance is recommended for both prophylaxis administration and hospital capacity management.
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Affiliation(s)
- Zhe Zheng
- Public Health Modeling Unit, Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut
| | - Virginia E. Pitzer
- Public Health Modeling Unit, Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut
| | - Eugene D. Shapiro
- Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut
| | - Louis J. Bont
- Department of Pediatrics, Department of Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- ReSViNET Foundation, Zeist, the Netherlands
| | - Daniel M. Weinberger
- Public Health Modeling Unit, Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut
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231
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Mousa A, Winskill P, Watson OJ, Ratmann O, Monod M, Ajelli M, Diallo A, Dodd PJ, Grijalva CG, Kiti MC, Krishnan A, Kumar R, Kumar S, Kwok KO, Lanata CF, le Polain de Waroux O, Leung K, Mahikul W, Melegaro A, Morrow CD, Mossong J, Neal EF, Nokes DJ, Pan-Ngum W, Potter GE, Russell FM, Saha S, Sugimoto JD, Wei WI, Wood RR, Wu J, Zhang J, Walker P, Whittaker C. Social contact patterns and implications for infectious disease transmission: a systematic review and meta-analysis of contact surveys. eLife 2021; 10:70294. [PMID: 34821551 PMCID: PMC8765757 DOI: 10.7554/elife.70294] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 11/24/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focused on high-income settings. Methods: Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys, we explored how contact characteristics (number, location, duration, and whether physical) vary across income settings. Results: Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, with low-income settings characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income strata on the frequency, duration, and type of contacts individuals made. Conclusions: These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens and the effectiveness of different non-pharmaceutical interventions. Funding: This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1). Infectious diseases, particularly those caused by airborne pathogens like SARS-CoV-2, spread by social contact, and understanding how people mix is critical in controlling outbreaks. To explore these patterns, researchers typically carry out large contact surveys. Participants are asked for personal information (such as gender, age and occupation), as well as details of recent social contacts, usually those that happened in the last 24 hours. This information includes, the age and gender of the contact, where the interaction happened, how long it lasted, and whether it involved physical touch. These kinds of surveys help scientists to predict how infectious diseases might spread. But there is a problem: most of the data come from high-income countries, and there is evidence to suggest that social contact patterns differ between places. Therefore, data from these countries might not be useful for predicting how infections spread in lower-income regions. Here, Mousa et al. have collected and combined data from 27 contact surveys carried out before the COVID-19 pandemic to see how baseline social interactions vary between high- and lower-income settings. The comparison revealed that, in higher-income countries, the number of daily contacts people made decreased with age. But, in lower-income countries, younger and older individuals made similar numbers of contacts and mixed with all age groups. In higher-income countries, more contacts happened at work or school, while in low-income settings, more interactions happened at home and people were also more likely to live in larger, intergenerational households. Mousa et al. also found that gender affected how long contacts lasted and whether they involved physical contact, both of which are key risk factors for transmitting airborne pathogens. These findings can help researchers to predict how infectious diseases might spread in different settings. They can also be used to assess how effective non-medical restrictions, like shielding of the elderly and workplace closures, will be at reducing transmissions in different parts of the world.
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Affiliation(s)
- Andria Mousa
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
| | - Peter Winskill
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
| | - Oliver John Watson
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
| | - Oliver Ratmann
- Department of Mathematics, Imperial College London, London, United Kingdom
| | - Mélodie Monod
- Department of Mathematics, Imperial College London, London, United Kingdom
| | - Marco Ajelli
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, United States
| | - Aldiouma Diallo
- VITROME, Institut de Recherche pour le Developpement, Dakar, Senegal
| | - Peter J Dodd
- School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom
| | - Carlos G Grijalva
- Division of Pharmacoepidemiology, Department of Health Policy, Vanderbilt University Medical Center, Nashville, United States
| | | | - Anand Krishnan
- Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Rakesh Kumar
- Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Supriya Kumar
- Bill and Melinda Gates Foundation, Seattle, WA, United States
| | - Kin O Kwok
- JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
| | | | | | - Kathy Leung
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
| | - Wiriya Mahikul
- Faculty of Medicine and Public Health, HRH Princess Chulabhorn College of Medical Science, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Alessia Melegaro
- Dondena Centre for Research on Social Dynamics and Public Policy, Department of Social and Political Sciences, Bocconi University, Milano, Italy
| | - Carl D Morrow
- Desmond Tutu HIV Centre, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | | | - Eleanor Fg Neal
- Infection and Immunity, Murdoch Children's Research Institute, Victoria, Australia
| | - D James Nokes
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | | | - Gail E Potter
- National Institute for Allergies and Infectious Diseases, National Institutes of Health, Rockville, United States
| | - Fiona M Russell
- Infection and Immunity, Murdoch Children's Research Institute, Victoria, Australia
| | - Siddhartha Saha
- US Centers for Disease Control and Prevention, New Delhi, India
| | - Jonathan D Sugimoto
- Seattle Epidemiologic Research and Information Center, United States Department of Veterans Affairs, Seattle, United States
| | - Wan In Wei
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Robin R Wood
- Desmond Tutu HIV Centre, Department of Medicine, University of Cape Town, Cape Town, South Africa
| | - Joseph Wu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
| | - Juanjuan Zhang
- School of Public Health, Fudan University, Shanghai, China
| | - Patrick Walker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
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Avraam D, Obradovich N, Pescetelli N, Cebrian M, Rutherford A. The network limits of infectious disease control via occupation-based targeting. Sci Rep 2021; 11:22855. [PMID: 34819577 PMCID: PMC8613398 DOI: 10.1038/s41598-021-02226-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 11/08/2021] [Indexed: 01/08/2023] Open
Abstract
Policymakers commonly employ non-pharmaceutical interventions to reduce the scale and severity of pandemics. Of non-pharmaceutical interventions, physical distancing policies-designed to reduce person-to-person pathogenic spread - have risen to recent prominence. In particular, stay-at-home policies of the sort widely implemented around the globe in response to the COVID-19 pandemic have proven to be markedly effective at slowing pandemic growth. However, such blunt policy instruments, while effective, produce numerous unintended consequences, including potentially dramatic reductions in economic productivity. In this study, we develop methods to investigate the potential to simultaneously contain pandemic spread while also minimizing economic disruptions. We do so by incorporating both occupational and contact network information contained within an urban environment, information that is commonly excluded from typical pandemic control policy design. The results of our methods suggest that large gains in both economic productivity and pandemic control might be had by the incorporation and consideration of simple-to-measure characteristics of the occupational contact network. We find evidence that more sophisticated, and more privacy invasive, measures of this network do not drastically increase performance.
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Affiliation(s)
- Demetris Avraam
- Centre for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany
- Population Health Sciences Institute, Newcastle University, Newcastle, UK
| | - Nick Obradovich
- Centre for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany
| | - Niccolò Pescetelli
- Centre for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany
| | - Manuel Cebrian
- Centre for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany.
| | - Alex Rutherford
- Centre for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany.
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Muylaert RL, Davidson B, Ngabirano A, Kalema-Zikusoka G, MacGregor H, Lloyd-Smith JO, Fayaz A, Knox MA, Hayman DTS. Community health and human-animal contacts on the edges of Bwindi Impenetrable National Park, Uganda. PLoS One 2021; 16:e0254467. [PMID: 34818325 PMCID: PMC8612581 DOI: 10.1371/journal.pone.0254467] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 11/01/2021] [Indexed: 01/03/2023] Open
Abstract
Cross-species transmission of pathogens is intimately linked to human and environmental health. With limited healthcare and challenging living conditions, people living in poverty may be particularly susceptible to endemic and emerging diseases. Similarly, wildlife is impacted by human influences, including pathogen sharing, especially for species in close contact with people and domesticated animals. Here we investigate human and animal contacts and human health in a community living around the Bwindi Impenetrable National Park (BINP), Uganda. We used contact and health survey data to identify opportunities for cross-species pathogen transmission, focusing mostly on people and the endangered mountain gorilla. We conducted a survey with background questions and self-reported diaries to investigate 100 participants' health, such as symptoms and behaviours, and contact patterns, including direct contacts and sightings over a week. Contacts were revealed through networks, including humans, domestic, peri-domestic, and wild animal groups for 1) contacts seen in the week of background questionnaire completion, and 2) contacts seen during the diary week. Participants frequently felt unwell during the study, reporting from one to 10 disease symptoms at different intensity levels, with severe symptoms comprising 6.4% of the diary records and tiredness and headaches the most common symptoms. After human-human contacts, direct contact with livestock and peri-domestic animals were the most common. The contact networks were moderately connected and revealed a preference in contacts within the same taxon and within their taxa groups. Sightings of wildlife were much more common than touching. However, despite contact with wildlife being the rarest of all contact types, one direct contact with a gorilla with a timeline including concerning participant health symptoms was reported. When considering all interaction types, gorillas mostly exhibited intra-species contact, but were found to interact with five other species, including people and domestic animals. Our findings reveal a local human population with recurrent symptoms of illness in a location with intense exposure to factors that can increase pathogen transmission, such as direct contact with domestic and wild animals and proximity among animal species. Despite significant biases and study limitations, the information generated here can guide future studies, such as models for disease spread and One Health interventions.
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Affiliation(s)
- Renata L. Muylaert
- Molecular Epidemiology and Public Health Laboratory, Hopkirk Research Institute, Massey University, Palmerston North, New Zealand
| | - Ben Davidson
- Molecular Epidemiology and Public Health Laboratory, Hopkirk Research Institute, Massey University, Palmerston North, New Zealand
| | - Alex Ngabirano
- Conservation Through Public Health, Uring Crescent, Entebbe, Uganda
- Bwindi Development Network, Buhoma, Kanungu, Uganda
| | | | - Hayley MacGregor
- Institute of Development Studies, University of Sussex and STEPS, Brighton, United Kingdom
| | - James O. Lloyd-Smith
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, United States of America
| | - Ahmed Fayaz
- Molecular Epidemiology and Public Health Laboratory, Hopkirk Research Institute, Massey University, Palmerston North, New Zealand
| | - Matthew A. Knox
- Molecular Epidemiology and Public Health Laboratory, Hopkirk Research Institute, Massey University, Palmerston North, New Zealand
| | - David T. S. Hayman
- Molecular Epidemiology and Public Health Laboratory, Hopkirk Research Institute, Massey University, Palmerston North, New Zealand
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234
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Islam MR, Oraby T, McCombs A, Chowdhury MM, Al-Mamun M, Tyshenko MG, Kadelka C. Evaluation of the United States COVID-19 vaccine allocation strategy. PLoS One 2021; 16:e0259700. [PMID: 34788345 PMCID: PMC8598051 DOI: 10.1371/journal.pone.0259700] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 10/23/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Anticipating an initial shortage of vaccines for COVID-19, the Centers for Disease Control (CDC) in the United States developed priority vaccine allocations for specific demographic groups in the population. This study evaluates the performance of the CDC vaccine allocation strategy with respect to multiple potentially competing vaccination goals (minimizing mortality, cases, infections, and years of life lost (YLL)), under the same framework as the CDC allocation: four priority vaccination groups and population demographics stratified by age, comorbidities, occupation and living condition (congested or non-congested). METHODS AND FINDINGS We developed a compartmental disease model that incorporates key elements of the current pandemic including age-varying susceptibility to infection, age-varying clinical fraction, an active case-count dependent social distancing level, and time-varying infectivity (accounting for the emergence of more infectious virus strains). The CDC allocation strategy is compared to all other possibly optimal allocations that stagger vaccine roll-out in up to four phases (17.5 million strategies). The CDC allocation strategy performed well in all vaccination goals but never optimally. Under the developed model, the CDC allocation deviated from the optimal allocations by small amounts, with 0.19% more deaths, 4.0% more cases, 4.07% more infections, and 0.97% higher YLL, than the respective optimal strategies. The CDC decision to not prioritize the vaccination of individuals under the age of 16 was optimal, as was the prioritization of health-care workers and other essential workers over non-essential workers. Finally, a higher prioritization of individuals with comorbidities in all age groups improved outcomes compared to the CDC allocation. CONCLUSION The developed approach can be used to inform the design of future vaccine allocation strategies in the United States, or adapted for use by other countries seeking to optimize the effectiveness of their vaccine allocation strategies.
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Affiliation(s)
- Md Rafiul Islam
- Department of Mathematics, Iowa State University, Ames, IA, United States of America
| | - Tamer Oraby
- School of Mathematical and Statistical Sciences, The University of Texas Rio Grande Valley, Edinburg, TX, United States of America
| | - Audrey McCombs
- Department of Statistics, Iowa State University, Ames, IA, United States of America
| | - Mohammad Mihrab Chowdhury
- Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX, United States of America
| | - Mohammad Al-Mamun
- Department of Pharmaceutical Systems and Policy, West Virginia University, Morgantown, WV, United States of America
| | - Michael G. Tyshenko
- McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Claus Kadelka
- Department of Mathematics, Iowa State University, Ames, IA, United States of America
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235
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Fu H, Abbas K, Klepac P, van Zandvoort K, Tanvir H, Portnoy A, Jit M. Effect of evidence updates on key determinants of measles vaccination impact: a DynaMICE modelling study in ten high-burden countries. BMC Med 2021; 19:281. [PMID: 34784922 PMCID: PMC8594955 DOI: 10.1186/s12916-021-02157-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 10/07/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Model-based estimates of measles burden and the impact of measles-containing vaccine (MCV) are crucial for global health priority setting. Recently, evidence from systematic reviews and database analyses have improved our understanding of key determinants of MCV impact. We explore how representations of these determinants affect model-based estimation of vaccination impact in ten countries with the highest measles burden. METHODS Using Dynamic Measles Immunisation Calculation Engine (DynaMICE), we modelled the effect of evidence updates for five determinants of MCV impact: case-fatality risk, contact patterns, age-dependent vaccine efficacy, the delivery of supplementary immunisation activities (SIAs) to zero-dose children, and the basic reproduction number. We assessed the incremental vaccination impact of the first (MCV1) and second (MCV2) doses of routine immunisation and SIAs, using metrics of total vaccine-averted cases, deaths, and disability-adjusted life years (DALYs) over 2000-2050. We also conducted a scenario capturing the effect of COVID-19 related disruptions on measles burden and vaccination impact. RESULTS Incorporated with the updated data sources, DynaMICE projected 253 million measles cases, 3.8 million deaths and 233 million DALYs incurred over 2000-2050 in the ten high-burden countries when MCV1, MCV2, and SIA doses were implemented. Compared to no vaccination, MCV1 contributed to 66% reduction in cumulative measles cases, while MCV2 and SIAs reduced this further to 90%. Among the updated determinants, shifting from fixed to linearly-varying vaccine efficacy by age and from static to time-varying case-fatality risks had the biggest effect on MCV impact. While varying the basic reproduction number showed a limited effect, updates on the other four determinants together resulted in an overall reduction of vaccination impact by 0.58%, 26.2%, and 26.7% for cases, deaths, and DALYs averted, respectively. COVID-19 related disruptions to measles vaccination are not likely to change the influence of these determinants on MCV impact, but may lead to a 3% increase in cases over 2000-2050. CONCLUSIONS Incorporating updated evidence particularly on vaccine efficacy and case-fatality risk reduces estimates of vaccination impact moderately, but its overall impact remains considerable. High MCV coverage through both routine immunisation and SIAs remains essential for achieving and maintaining low incidence in high measles burden settings.
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Affiliation(s)
- Han Fu
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Kaja Abbas
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- Public Health Foundation of India, New Delhi, India
- International Vaccine Institute, Seoul, South Korea
| | - Petra Klepac
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK
| | - Kevin van Zandvoort
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Hira Tanvir
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Allison Portnoy
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Mark Jit
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- Modelling and Economics Unit, Public Health England, London, UK
- School of Public Health, University of Hong Kong, Hong Kong, SAR China
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Chen X, Gong W, Wu X, Zhao W. Estimating Economic Losses Caused by COVID-19 under Multiple Control Measure Scenarios with a Coupled Infectious Disease-Economic Model: A Case Study in Wuhan, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182211753. [PMID: 34831508 PMCID: PMC8621982 DOI: 10.3390/ijerph182211753] [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] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 10/27/2021] [Accepted: 11/01/2021] [Indexed: 12/17/2022]
Abstract
Background: The outbreak of the COVID-19 epidemic has caused an unprecedented public health crisis and drastically impacted the economy. The relationship between different control measures and economic losses becomes a research hotspot. Methods: In this study, the SEIR infectious disease model was revised and coupled with an economic model to quantify this nonlinear relationship in Wuhan. The control measures were parameterized into two factors: the effective number of daily contacts (people) (r); the average waiting time for quarantined patients (day) (g). Results: The parameter r has a threshold value that if r is less than 5 (people), the number of COVID-19 infected patients is very close to 0. A “central valley” around r = 5~6 can be observed, indicating an optimal control measure to reduce economic losses. A lower value of parameter g is beneficial to stop COVID-19 spread with a lower economic cost. Conclusion: The simulation results demonstrate that implementing strict control measures as early as possible can stop the spread of COVID-19 with a minimal economic impact. The quantitative assessment method in this study can be applied in other COVID-19 pandemic areas or countries.
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Affiliation(s)
- Xingtian Chen
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; (X.C.); (W.Z.)
- Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Wei Gong
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; (X.C.); (W.Z.)
- Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
- Correspondence: (W.G.); (X.W.)
| | - Xiaoxu Wu
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
- Correspondence: (W.G.); (X.W.)
| | - Wenwu Zhao
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; (X.C.); (W.Z.)
- Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
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237
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Brankston G, Merkley E, Fisman DN, Tuite AR, Poljak Z, Loewen PJ, Greer AL. Quantifying contact patterns in response to COVID-19 public health measures in Canada. BMC Public Health 2021; 21:2040. [PMID: 34749676 PMCID: PMC8574152 DOI: 10.1186/s12889-021-12080-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 10/20/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND A variety of public health measures have been implemented during the COVID-19 pandemic in Canada to reduce contact between individuals. The objective of this study was to provide empirical contact pattern data to evaluate the impact of public health measures, the degree to which social contacts rebounded to normal levels, as well as direct public health efforts toward age- and location-specific settings. METHODS Four population-based cross-sectional surveys were administered to members of a paid panel representative of Canadian adults by age, gender, official language, and region of residence during May (Survey 1), July (Survey 2), September (Survey 3), and December (Survey 4) 2020. A total of 4981 (Survey 1), 2493 (Survey 2), 2495 (Survey 3), and 2491 (Survey 4) respondents provided information about the age and setting for each direct contact made in a 24-h period. Contact matrices were constructed and contacts for those under the age of 18 years imputed. The next generation matrix approach was used to estimate the reproduction number (Rt) for each survey. Respondents with children under 18 years estimated the number of contacts their children made in school and extracurricular settings. RESULTS Estimated Rt values were 0.49 (95% CI: 0.29-0.69) for May, 0.48 (95% CI: 0.29-0.68) for July, 1.06 (95% CI: 0.63-1.52) for September, and 0.81 (0.47-1.17) for December. The highest proportion of reported contacts occurred within the home (51.3% in May), in 'other' locations (49.2% in July) and at work (66.3 and 65.4% in September and December). Respondents with children reported an average of 22.7 (95% CI: 21.1-24.3) (September) and 19.0 (95% CI 17.7-20.4) (December) contacts at school per day per child in attendance. CONCLUSION The skewed distribution of reported contacts toward workplace settings in September and December combined with the number of reported school-related contacts suggest that these settings represent important opportunities for transmission emphasizing the need to support and ensure infection control procedures in both workplaces and schools.
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Affiliation(s)
| | - Eric Merkley
- Munk School of Global Affairs & Public Policy, University of Toronto, Toronto, Canada
| | - David N Fisman
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Ashleigh R Tuite
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Zvonimir Poljak
- Department of Population Medicine, University of Guelph, Guelph, Canada
| | - Peter J Loewen
- Munk School of Global Affairs & Public Policy, University of Toronto, Toronto, Canada
| | - Amy L Greer
- Department of Population Medicine, University of Guelph, Guelph, Canada.
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.
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238
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Del Fava E, Adema I, Kiti MC, Poletti P, Merler S, Nokes DJ, Manfredi P, Melegaro A. Individual's daily behaviour and intergenerational mixing in different social contexts of Kenya. Sci Rep 2021; 11:21589. [PMID: 34732732 PMCID: PMC8566563 DOI: 10.1038/s41598-021-00799-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 10/15/2021] [Indexed: 12/20/2022] Open
Abstract
We investigated contact patterns in diverse social contexts in Kenya and the daily behaviours that may play a pivotal role in infection transmission to the most vulnerable leveraging novel data from a 2-day survey on social contacts and time use (TU) from a sample of 1407 individuals (for a total of 2705 person days) from rural, urban formal, and informal settings. We used TU data to build six profiles of daily behaviour based on the main reported activities, i.e., Homestayers (71.1% of person days), Workers (9.3%), Schoolers (7.8%), or locations at increasing distance from home, i.e., Walkers (6.6%), Commuters (4.6%), Travelers (0.6%). In the rural setting, we observed higher daily contact numbers (11.56, SD 0.23) and percentages of intergenerational mixing with older adults (7.5% of contacts reported by those younger than 60 years vs. less than 4% in the urban settings). Overall, intergenerational mixing with older adults was higher for Walkers (7.3% of their reported contacts), Commuters (8.7%), and Homestayers (5.1%) than for Workers (1.5%) or Schoolers (3.6%). These results could be instrumental in defining effective interventions that acknowledge the heterogeneity in social contexts and daily routines, either in Kenya or other demographically and culturally similar sub-Saharan African settings.
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Affiliation(s)
- Emanuele Del Fava
- Carlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milan, Italy
- Max Planck Institute for Demographic Research, Rostock, Germany
| | - Irene Adema
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Moses C Kiti
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
| | | | | | - D James Nokes
- KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya
- School of Life Sciences and Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER), University of Warwick, Coventry, UK
| | | | - Alessia Melegaro
- Carlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milan, Italy.
- Department of Social and Political Sciences, Bocconi University, Milan, Italy.
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Klimek P. Why we may need to rethink future SARS-CoV-2 vaccination strategies. THE LANCET REGIONAL HEALTH. EUROPE 2021; 10:100214. [PMID: 34541566 PMCID: PMC8433029 DOI: 10.1016/j.lanepe.2021.100214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Peter Klimek
- Section for Science of Complex Systems; CeMSIIS; Medical University of Vienna. Spitalgasse 23, A-1090 Vienna, Austria
- Complexity Science Hub Vienna. Josefstädter Strasse 39, A-1080 Vienna, Austria
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240
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Liu CY, Berlin J, Kiti MC, Del Fava E, Grow A, Zagheni E, Melegaro A, Jenness SM, Omer SB, Lopman B, Nelson K. Rapid Review of Social Contact Patterns During the COVID-19 Pandemic. Epidemiology 2021; 32:781-791. [PMID: 34392254 PMCID: PMC8478104 DOI: 10.1097/ede.0000000000001412] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 08/02/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Physical distancing measures aim to reduce person-to-person contact, a key driver of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. In response to unprecedented restrictions on human contact during the coronavirus disease 2019 (COVID-19) pandemic, studies measured social contact patterns under the implementation of physical distancing measures. This rapid review synthesizes empirical data on the changing social contact patterns during the COVID-19 pandemic. METHOD We conducted a systematic review using PubMed, Medline, Embase, and Google Scholar following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We descriptively compared the distribution of contacts observed during the pandemic to pre-COVID data across countries to explore changes in contact patterns during physical distancing measures. RESULTS We identified 12 studies reporting social contact patterns during the COVID-19 pandemic. Eight studies were conducted in European countries and eleven collected data during the initial mitigation period in the spring of 2020 marked by government-declared lockdowns. Some studies collected additional data after relaxation of initial mitigation. Most study settings reported a mean of between 2 and 5 contacts per person per day, a substantial reduction compared to pre-COVID rates, which ranged from 7 to 26 contacts per day. This reduction was pronounced for contacts outside of the home. Consequently, levels of assortative mixing by age substantially declined. After relaxation of initial mitigation, mean contact rates increased but did not return to pre-COVID levels. Increases in contacts post-relaxation were driven by working-age adults. CONCLUSION Information on changes in contact patterns during physical distancing measures can guide more realistic representations of contact patterns in mathematical models for SARS-CoV-2 transmission.
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Affiliation(s)
- Carol Y. Liu
- From the Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA
| | - Juliette Berlin
- From the Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA
| | - Moses C. Kiti
- From the Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA
| | - Emanuele Del Fava
- Laboratory of Digital and Computational Demography, Max Planck Institute for Demographic Research, Rostock, Germany
| | - André Grow
- Laboratory of Digital and Computational Demography, Max Planck Institute for Demographic Research, Rostock, Germany
| | - Emilio Zagheni
- Laboratory of Digital and Computational Demography, Max Planck Institute for Demographic Research, Rostock, Germany
| | - Alessia Melegaro
- Department of Social and Political Sciences, Centre for Research on Social Dynamics and Public Policy and Covid Crisis Lab, Bocconi University, Milan, Italy
| | - Samuel M. Jenness
- From the Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA
| | - Saad B. Omer
- Department of Epidemiology of Microbial Diseases, Yale Institute of Global Health, Yale University, CT
| | - Benjamin Lopman
- From the Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA
| | - Kristin Nelson
- From the Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA
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Chadsuthi S, Modchang C. Modelling the effectiveness of intervention strategies to control COVID-19 outbreaks and estimating healthcare demand in Germany. PUBLIC HEALTH IN PRACTICE 2021; 2:100121. [PMID: 33899039 PMCID: PMC8054549 DOI: 10.1016/j.puhip.2021.100121] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 01/08/2023] Open
Abstract
OBJECTIVES An outbreak of the novel coronavirus in December 2019 caused a worldwide pandemic. This disease also impacts European countries, including Germany. Without effective medicines or vaccines, non-pharmaceutical interventions are the best strategy to reduce the number of cases. STUDY DESIGN A deterministic model was simulated to evaluate the number of infectious and healthcare demand. METHOD Using an age-structured SEIR model for the COVID-19 transmission, we project the COVID-19-associated demand for hospital and ICU beds within Germany. We estimated the effectiveness of different control measures, including active case-finding and quarantining of asymptomatic persons, self-isolation of people who had contact with an infectious person, and physical distancing, as well as a combination of these control measures. RESULTS We found that contact tracing could reduce the peak of ICU beds as well as mass testing. The time delay between diagnosis and self-isolation influences the control measures. Physical distancing to limit the contact rate would delay the peak of the outbreak, which results in the demand for ICU beds being below the capacity during the early outbreak. CONCLUSIONS Our study analyzed several scenarios in order to provide policymakers that face the pandemic of COVID-19 with insights into the different measures available. We highlight that the individuals who have had contact with a virus-positive person must be quarantined as soon as possible to reduce contact with possible infectious cases and to reduce transmission. Keeping physical distance and having fewer contacts should be implemented to prevent overwhelming ICU demand.
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Affiliation(s)
- Sudarat Chadsuthi
- Department of Physics, Research Center for Academic Excellence in Applied Physics, Faculty of Science, Naresuan University, Phitsanulok, 65000, Thailand
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand
- Centre of Excellence in Mathematics, CHE, 328, Si Ayutthaya Road, Bangkok, 10400, Thailand
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Fotsa-Mbogne DJ, Tchoumi SY, Kouakep-Tchaptchie Y, Kamla VC, Kamgang JC, Houpa-Danga DE, Bowong-Tsakou S, Bekolle D. Estimation and optimal control of the multiscale dynamics of Covid-19: a case study from Cameroon. NONLINEAR DYNAMICS 2021; 106:2703-2738. [PMID: 34697521 PMCID: PMC8528969 DOI: 10.1007/s11071-021-06920-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 09/18/2021] [Indexed: 05/31/2023]
Abstract
This work aims at a better understanding and the optimal control of the spread of the new severe acute respiratory corona virus 2 (SARS-CoV-2). A multi-scale model giving insights on the virus population dynamics, the transmission process and the infection mechanism is proposed first. Indeed, there are human to human virus transmission, human to environment virus transmission, environment to human virus transmission and self-infection by susceptible individuals. The global stability of the disease-free equilibrium is shown when a given threshold T 0 is less or equal to 1 and the basic reproduction number R 0 is calculated. A convergence index T 1 is also defined in order to estimate the speed at which the disease extincts and an upper bound to the time of infectious extinction is given. The existence of the endemic equilibrium is conditional and its description is provided. Using Partial Rank Correlation Coefficient with a three levels fractional experimental design, the sensitivity of R 0 , T 0 and T 1 to control parameters is evaluated. Following this study, the most significant parameter is the probability of wearing mask followed by the probability of mobility and the disinfection rate. According to a functional cost taking into account economic impacts of SARS-CoV-2, optimal fighting strategies are determined and discussed. The study is applied to real and available data from Cameroon with a model fitting. After several simulations, social distancing and the disinfection frequency appear as the main elements of the optimal control strategy against SARS-CoV-2.
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Affiliation(s)
- David Jaurès Fotsa-Mbogne
- Department of Mathematics and Computer Science, ENSAI, The University of Ngaoundere, P.O. Box 455, Ngaoundere, Cameroon
| | - Stéphane Yanick Tchoumi
- Department of Mathematics and Computer Science, ENSAI, The University of Ngaoundere, P.O. Box 455, Ngaoundere, Cameroon
| | - Yannick Kouakep-Tchaptchie
- Department of Fundamental Science and Engineering, EGCIM, The University of Ngaoundere, P.O. Box 454, Ngaoundere, Cameroon
| | - Vivient Corneille Kamla
- Department of Mathematics and Computer Science, ENSAI, The University of Ngaoundere, P.O. Box 455, Ngaoundere, Cameroon
| | - Jean-Claude Kamgang
- Department of Mathematics and Computer Science, ENSAI, The University of Ngaoundere, P.O. Box 455, Ngaoundere, Cameroon
| | - Duplex Elvis Houpa-Danga
- Department of Mathematics and Computer Science, FS, The University of Ngaoundere, P.O. Box 454, Ngaoundere, Cameroon
| | - Samuel Bowong-Tsakou
- Department of Mathematics and Computer Science, FS, The University of Douala, P.O. Box 24157, Douala, Cameroon
| | - David Bekolle
- Department of Mathematics and Computer Science, FS, The University of Ngaoundere, P.O. Box 454, Ngaoundere, Cameroon
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Di Lauro F, Berthouze L, Dorey MD, Miller JC, Kiss IZ. The Impact of Contact Structure and Mixing on Control Measures and Disease-Induced Herd Immunity in Epidemic Models: A Mean-Field Model Perspective. Bull Math Biol 2021; 83:117. [PMID: 34654959 PMCID: PMC8518901 DOI: 10.1007/s11538-021-00947-8] [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: 07/14/2020] [Accepted: 09/27/2021] [Indexed: 11/27/2022]
Abstract
The contact structure of a population plays an important role in transmission of infection. Many 'structured models' capture aspects of the contact pattern through an underlying network or a mixing matrix. An important observation in unstructured models of a disease that confers immunity is that once a fraction [Formula: see text] has been infected, the residual susceptible population can no longer sustain an epidemic. A recent observation of some structured models is that this threshold can be crossed with a smaller fraction of infected individuals, because the disease acts like a targeted vaccine, preferentially immunising higher-risk individuals who play a greater role in transmission. Therefore, a limited 'first wave' may leave behind a residual population that cannot support a second wave once interventions are lifted. In this paper, we set out to investigate this more systematically. While networks offer a flexible framework to model contact patterns explicitly, they suffer from several shortcomings: (i) high-fidelity network models require a large amount of data which can be difficult to harvest, and (ii) very few, if any, theoretical contact network models offer the flexibility to tune different contact network properties within the same framework. Therefore, we opt to systematically analyse a number of well-known mean-field models. These are computationally efficient and provide good flexibility in varying contact network properties such as heterogeneity in the number contacts, clustering and household structure or differentiating between local and global contacts. In particular, we consider the question of herd immunity under several scenarios. When modelling interventions as changes in transmission rates, we confirm that in networks with significant degree heterogeneity, the first wave of the epidemic confers herd immunity with significantly fewer infections than equivalent models with less or no degree heterogeneity. However, if modelling the intervention as a change in the contact network, then this effect may become much more subtle. Indeed, modifying the structure disproportionately can shield highly connected nodes from becoming infected during the first wave and therefore make the second wave more substantial. We strengthen this finding by using an age-structured compartmental model parameterised with real data and comparing lockdown periods implemented either as a global scaling of the mixing matrix or age-specific structural changes. Overall, we find that results regarding (disease-induced) herd immunity levels are strongly dependent on the model, the duration of the lockdown and how the lockdown is implemented in the model.
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Affiliation(s)
- Francesco Di Lauro
- Department of Mathematics, School of Mathematical and Physical Sciences, University of Sussex, Falmer, Brighton, BN1 9QH, UK
| | - Luc Berthouze
- Department of Informatics, School of Engineering and Informatics, University of Sussex, Falmer, Brighton, BN1 9QH, UK
| | - Matthew D Dorey
- Public Health and Social Research Unit, West Sussex County Council, Tower Street, Chichester, P019 1RQ, UK
| | - Joel C Miller
- Department of Mathematics and Statistics, School of Engineering and Mathematical Sciences, La Trobe University, Bundoora, Australia
| | - István Z Kiss
- Department of Mathematics, School of Mathematical and Physical Sciences, University of Sussex, Falmer, Brighton, BN1 9QH, UK.
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244
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Raina MacIntyre C, Costantino V, Chanmugam A. The use of face masks during vaccine roll-out in New YorkCity and impact on epidemic control. Vaccine 2021; 39:6296-6301. [PMID: 34538699 PMCID: PMC8443976 DOI: 10.1016/j.vaccine.2021.08.102] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 08/23/2021] [Accepted: 08/30/2021] [Indexed: 12/21/2022]
Abstract
Face masks were mandated in New York during the first wave in 2020, and in 2021 the first vaccine programs have commenced. We aimed to examine the impact of face mask and other NPIs use with a gradual roll out of vaccines in NYC on the epidemic trajectory. A SEIR mathematical model of SARS-CoV-2 transmission was developed for New York City (NYC), which accounted for decreased mobility for lockdown, testing and tracing. Varied mask’s usage and efficacy were tested, along with a gradual increase in vaccine uptake over five months. The model has been calibrated using notification data in NYC from March first to June 29. Masks and other NPIs result in immediate impact on the epidemic, while vaccination has a delayed impact, especially when implemented over a long period of time. A pre-emptive, early mandate for masks is more effective than late mask use, but even late mask mandates will reduce cases and deaths by over 20%. The epidemic curve is suppressed by at least 50% of people wearing a mask from the start of the outbreak but surges when mask wearing drops to 30% or less. With a slow roll out of vaccines over five months at uptake levels of 20–70%, NPIs use will still be needed and has a greater impact on epidemic control. When vaccine roll out is slow or partial in cities experiencing local transmission of COVID-19, masks and other NPIs will be necessary to mitigate transmission until vaccine coverage is high and complete. Vaccine alone cannot rapidly control an epidemic because of the time lag to two-dose immunity. Even after high coverage, the ongoing need for NPIs is unknown and will depend on long-term duration of vaccine efficacy, the use of boosters and optimized dosage scheduling and variants of concern.
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Affiliation(s)
- C Raina MacIntyre
- The Biosecurity Program, The Kirby Institute, University of New South Wales, Australia; College of Health Solutions, Arizona State University, AZ, USA; Watts College of Public Affairs and Community Solutions, Arizona State University, AZ, USA
| | - Valentina Costantino
- The Biosecurity Program, The Kirby Institute, University of New South Wales, Australia.
| | - Arjun Chanmugam
- Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, MND, USA
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Pearson CAB, Bozzani F, Procter SR, Davies NG, Huda M, Jensen HT, Keogh-Brown M, Khalid M, Sweeney S, Torres-Rueda S, Eggo RM, Vassall A, Jit M. COVID-19 vaccination in Sindh Province, Pakistan: A modelling study of health impact and cost-effectiveness. PLoS Med 2021; 18:e1003815. [PMID: 34606520 PMCID: PMC8523052 DOI: 10.1371/journal.pmed.1003815] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 10/18/2021] [Accepted: 09/14/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Multiple Coronavirus Disease 2019 (COVID-19) vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh Province, Pakistan (population: 48 million). METHODS AND FINDINGS We fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalisation outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability-adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario. We project that 1 year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70% efficacy and 2.5-year duration of protection is likely to avert around 0.9 (95% credible interval (CrI): 0.9, 1.0) million cases, 10.1 (95% CrI: 10.1, 10.3) thousand deaths, and 70.1 (95% CrI: 69.9, 70.6) thousand DALYs, with an ICER of $27.9 per DALY averted from the health system perspective. Under a broad range of alternative scenarios, we find that initially prioritising the older (65+) population generally prevents more deaths. However, unprioritised distribution has almost the same cost-effectiveness when considering all outcomes, and both prioritised and unprioritised programmes can be cost-effective for low per-dose costs. High vaccine prices ($10/dose), however, may not be cost-effective, depending on the specifics of vaccine performance, distribution programme, and future pandemic trends. The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age-specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses. This study is limited by model approximations, available data, and future uncertainty. Because the model is a single-population compartmental model, detailed impacts of nonpharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritising groups like healthcare or other essential workers. The model is only fitted to the reported case and death data, which are incomplete and not disaggregated by, e.g., age. Finally, because the future impact and implementation cost of NPIs are uncertain, how these would interact with vaccination remains an open question. CONCLUSIONS COVID-19 vaccination can have a considerable health impact and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact. However, the advantage of prioritising older, high-risk populations is smaller in generally younger populations. This reduction is especially true in populations with more past transmission, and if the vaccine is likely to further impede transmission rather than just disease. Those conditions are typical of many low- and middle-income countries.
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Affiliation(s)
- Carl A. B. Pearson
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
- South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, Republic of South Africa
| | - Fiammetta Bozzani
- Centre for Health Economics in London, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Simon R. Procter
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Centre for Health Economics in London, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Nicholas G. Davies
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Maryam Huda
- Aga Khan University Hospital, Karachi, Sindh, Pakistan
| | - Henning Tarp Jensen
- Centre for Health Economics in London, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Marcus Keogh-Brown
- Centre for Health Economics in London, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Muhammad Khalid
- Ministry of National Health Services Regulations & Coordination Islamabad, Pakistan
| | - Sedona Sweeney
- Centre for Health Economics in London, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Sergio Torres-Rueda
- Centre for Health Economics in London, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - CHiL COVID-19 Working Group
- Centre for Health Economics in London, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - CMMID COVID-19 Working Group
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Rosalind M. Eggo
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Anna Vassall
- Centre for Health Economics in London, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Mark Jit
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Centre for Health Economics in London, London School of Hygiene and Tropical Medicine, London, United Kingdom
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Dyson L, Hill EM, Moore S, Curran-Sebastian J, Tildesley MJ, Lythgoe KA, House T, Pellis L, Keeling MJ. Possible future waves of SARS-CoV-2 infection generated by variants of concern with a range of characteristics. Nat Commun 2021; 12:5730. [PMID: 34593807 PMCID: PMC8484271 DOI: 10.1038/s41467-021-25915-7] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 09/08/2021] [Indexed: 11/09/2022] Open
Abstract
Viral reproduction of SARS-CoV-2 provides opportunities for the acquisition of advantageous mutations, altering viral transmissibility, disease severity, and/or allowing escape from natural or vaccine-derived immunity. We use three mathematical models: a parsimonious deterministic model with homogeneous mixing; an age-structured model; and a stochastic importation model to investigate the effect of potential variants of concern (VOCs). Calibrating to the situation in England in May 2021, we find epidemiological trajectories for putative VOCs are wide-ranging and dependent on their transmissibility, immune escape capability, and the introduction timing of a postulated VOC-targeted vaccine. We demonstrate that a VOC with a substantial transmission advantage over resident variants, or with immune escape properties, can generate a wave of infections and hospitalisations comparable to the winter 2020-2021 wave. Moreover, a variant that is less transmissible, but shows partial immune-escape could provoke a wave of infection that would not be revealed until control measures are further relaxed.
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Affiliation(s)
- Louise Dyson
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom.
- Joint Universities Pandemic and Epidemiological Research, .
| | - Edward M Hill
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Joint Universities Pandemic and Epidemiological Research
| | - Sam Moore
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Joint Universities Pandemic and Epidemiological Research
| | - Jacob Curran-Sebastian
- Joint Universities Pandemic and Epidemiological Research
- Department of Mathematics, University of Manchester, Manchester, United Kingdom
| | - Michael J Tildesley
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Joint Universities Pandemic and Epidemiological Research
| | - Katrina A Lythgoe
- Big Data Institute, Old Road Campus, University of Oxford, Oxford, United Kingdom
| | - Thomas House
- Joint Universities Pandemic and Epidemiological Research
- Department of Mathematics, University of Manchester, Manchester, United Kingdom
- IBM Research, Hartree Centre, Daresbury, United Kingdom
- The Alan Turing Institute for Data Science and Artificial Intelligence, London, United Kingdom
| | - Lorenzo Pellis
- Joint Universities Pandemic and Epidemiological Research
- Department of Mathematics, University of Manchester, Manchester, United Kingdom
- The Alan Turing Institute for Data Science and Artificial Intelligence, London, United Kingdom
| | - Matt J Keeling
- The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, United Kingdom
- Joint Universities Pandemic and Epidemiological Research
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247
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Dorélien AM, Ramen A, Swanson I, Hill R. Analyzing the demographic, spatial, and temporal factors influencing social contact patterns in U.S. and implications for infectious disease spread. BMC Infect Dis 2021; 21:1009. [PMID: 34579645 PMCID: PMC8474922 DOI: 10.1186/s12879-021-06610-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 08/12/2021] [Indexed: 11/18/2022] Open
Abstract
Background Diseases such as COVID-19 are spread through social contact. Reducing social contacts is required to stop disease spread in pandemics for which vaccines have not yet been developed. However, existing data on social contact patterns in the United States (U.S.) is limited. Method We use American Time Use Survey data from 2003–2018 to describe and quantify the age-pattern of disease-relevant social contacts. For within-household contacts, we construct age-structured contact duration matrices (who spends time with whom, by age). For both within-household and non-household contacts, we also estimate the mean number and duration of contact by location. We estimate and test for differences in the age-pattern of social contacts based on demographic, temporal, and spatial characteristics. Results The mean number and duration of social contacts vary by age. The biggest gender differences in the age-pattern of social contacts are at home and at work; the former appears to be driven by caretaking responsibilities. Non-Hispanic Blacks have a shorter duration of contact and fewer social contacts than non-Hispanic Whites. This difference is largely driven by fewer and shorter contacts at home. Pre-pandemic, non-Hispanic Blacks have shorter durations of work contacts. Their jobs are more likely to require close physical proximity, so their contacts are riskier than those of non-Hispanic Whites. Hispanics have the highest number of household contacts and are also more likely to work in jobs requiring close physical proximity than non-Hispanic Whites. With the exceptions of work and school contacts, the duration of social contact is higher on weekends than on weekdays. Seasonal differences in the total duration of social contacts are driven by school-aged respondents who have significantly shorter contacts during the summer months. Contact patterns did not differ by metro status. Age patterns of social contacts were similar across regions. Conclusion Social contact patterns differ by age, race and ethnicity, and gender. Other factors besides contact patterns may be driving seasonal variation in disease incidence if school-aged individuals are not an important source of transmission. Pre-pandemic, there were no spatial differences in social contacts, but this finding has likely changed during the pandemic. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-06610-w.
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248
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Sunohara S, Asakura T, Kimura T, Ozawa S, Oshima S, Yamauchi D, Tamakoshi A. Effective vaccine allocation strategies, balancing economy with infection control against COVID-19 in Japan. PLoS One 2021; 16:e0257107. [PMID: 34473809 PMCID: PMC8412346 DOI: 10.1371/journal.pone.0257107] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 08/23/2021] [Indexed: 12/02/2022] Open
Abstract
Due to COVID-19, many countries including Japan have implemented a suspension of economic activities for infection control. It has contributed to reduce the transmission of COVID-19 but caused severe economic losses. Today, several promising vaccines have been developed and are already being distributed in some countries. Therefore, we evaluated various vaccine and intensive countermeasure strategies with constraint of economic loss using SEIR model to obtain knowledge of how to balance economy with infection control in Japan. Our main results were that the vaccination strategy that prioritized younger generation was better in terms of deaths when a linear relationship between lockdown intensity and acceptable economic loss was assumed. On the other hand, when a non-linearity relationship was introduced, implying that the strong lockdown with small economic loss was possible, the old first strategies were best in the settings of small basic reproduction number. These results indicated a high potential of remote work when prioritizing vaccination for the old generation. When focusing on only the old first strategies as the Japanese government has decided to do, the strategy vaccinating the young next to the old was superior to the others when a non-linear relationship was assumed due to sufficient reduction of contact with small economic loss.
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Affiliation(s)
| | | | - Takashi Kimura
- Public Health, Faculty of Medicine, Hokkaido University, Sapporo, Japan
- * E-mail:
| | - Shun Ozawa
- School of Medicine, Hokkaido University, Sapporo, Japan
| | | | | | - Akiko Tamakoshi
- Public Health, Faculty of Medicine, Hokkaido University, Sapporo, Japan
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249
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Kirwin E, Rafferty E, Harback K, Round J, McCabe C. A Net Benefit Approach for the Optimal Allocation of a COVID-19 Vaccine. PHARMACOECONOMICS 2021; 39:1059-1073. [PMID: 34138458 PMCID: PMC8209775 DOI: 10.1007/s40273-021-01037-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/23/2021] [Indexed: 05/26/2023]
Abstract
OBJECTIVE The objective of this study was to implement a model-based approach to identify the optimal allocation of a coronavirus disease 2019 (COVID-19) vaccine in the province of Alberta, Canada. METHODS We developed an epidemiologic model to evaluate allocation strategies defined by age and risk target groups, coverage, effectiveness and cost of vaccine. The model simulated hypothetical immunisation scenarios within a dynamic context, capturing concurrent public health strategies and population behavioural changes. RESULTS In a scenario with 80% vaccine effectiveness, 40% population coverage and prioritisation of those over the age of 60 years at high risk of poor outcomes, active cases are reduced by 17% and net monetary benefit increased by $263 million dollars, relative to no vaccine. Concurrent implementation of policies such as school closure and senior contact reductions have similar impacts on incremental net monetary benefit ($352 vs $292 million, respectively) when there is no prioritisation given to any age or risk group. When older age groups are given priority, the relative benefit of school closures is much larger ($214 vs $118 million). Results demonstrate that the rank ordering of different prioritisation options varies by prioritisation criteria, vaccine effectiveness and coverage, and concurrently implemented policies. CONCLUSIONS Our results have three implications: (i) optimal vaccine allocation will depend on the public health policies in place at the time of allocation and the impact of those policies on population behaviour; (ii) outcomes of vaccine allocation policies can be greatly supported with interventions targeting contact reduction in critical sub-populations; and (iii) identification of the optimal strategy depends on which outcomes are prioritised.
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Affiliation(s)
- Erin Kirwin
- Institute of Health Economics, #1200, 10405 Jasper Avenue, Edmonton, AB, T5J 3N4, Canada.
- Health Organisation, Policy, and Economics, School of Health Sciences, University of Manchester, Manchester, UK.
| | - Ellen Rafferty
- Institute of Health Economics, #1200, 10405 Jasper Avenue, Edmonton, AB, T5J 3N4, Canada
| | - Kate Harback
- Institute of Health Economics, #1200, 10405 Jasper Avenue, Edmonton, AB, T5J 3N4, Canada
| | - Jeff Round
- Institute of Health Economics, #1200, 10405 Jasper Avenue, Edmonton, AB, T5J 3N4, Canada
- School of Public Health, University of Alberta, Edmonton, AB, Canada
| | - Christopher McCabe
- Institute of Health Economics, #1200, 10405 Jasper Avenue, Edmonton, AB, T5J 3N4, Canada
- Department of Emergency Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada
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250
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Fields R, Humphrey L, Flynn-Primrose D, Mohammadi Z, Nahirniak M, Thommes E, Cojocaru M. Age-stratified transmission model of COVID-19 in Ontario with human mobility during pandemic's first wave. Heliyon 2021; 7:e07905. [PMID: 34514179 PMCID: PMC8419869 DOI: 10.1016/j.heliyon.2021.e07905] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 04/10/2021] [Accepted: 08/27/2021] [Indexed: 12/15/2022] Open
Abstract
In this work, we employ a data-fitted compartmental model to visualize the progression and behavioral response to COVID-19 that match provincial case data in Ontario, Canada from February to June of 2020. This is a "rear-view mirror" glance at how this region has responded to the 1st wave of the pandemic, when testing was sparse and NPI measures were the only remedy to stave off the pandemic. We use an SEIR-type model with age-stratified subpopulations and their corresponding contact rates and asymptomatic rates in order to incorporate heterogeneity in our population and to calibrate the time-dependent reduction of Ontario-specific contact rates to reflect intervention measures in the province throughout lockdown and various stages of social-distancing measures. Cellphone mobility data taken from Google, combining several mobility categories, allows us to investigate the effects of mobility reduction and other NPI measures on the evolution of the pandemic. Of interest here is our quantification of the effectiveness of Ontario's response to COVID-19 before and after provincial measures and our conclusion that the sharp decrease in mobility has had a pronounced effect in the first few weeks of the lockdown, while its effect is harder to infer once other NPI measures took hold.
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Affiliation(s)
- R. Fields
- Department of Mathematics and Statistics, University of Guelph, Canada
| | - L. Humphrey
- Department of Mathematics and Statistics, University of Guelph, Canada
| | - D. Flynn-Primrose
- Department of Mathematics and Statistics, University of Guelph, Canada
| | - Z. Mohammadi
- Department of Mathematics and Statistics, University of Guelph, Canada
| | - M. Nahirniak
- Department of Mathematics and Statistics, University of Guelph, Canada
| | | | - M.G. Cojocaru
- Department of Mathematics and Statistics, University of Guelph, Canada
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