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Paltra S, Bostanci I, Nagel K. The effect of mobility reductions on infection growth is quadratic in many cases. Sci Rep 2024; 14:14475. [PMID: 38914583 PMCID: PMC11196635 DOI: 10.1038/s41598-024-64230-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 06/06/2024] [Indexed: 06/26/2024] Open
Abstract
Stay-at-home orders were introduced in many countries during the COVID-19 pandemic, limiting the time people spent outside their home and the attendance of gatherings. In this study, we argue from a theoretical model that in many cases the effect of such stay-at-home orders on incidence growth should be quadratic, and that this statement should also hold beyond COVID-19. That is, a reduction of the out-of-home duration to, say, 70% of its original value should reduce incidence growth and thus the effective R-value to 70 % · 70 % = 49 % of its original value. We then show that this hypothesis can be substantiated from data acquired during the COVID-19 pandemic by using a multiple regression model to fit a combination of the quadratic out-of-home duration and temperature to the COVID-19 growth multiplier. We finally demonstrate that many other models, when brought to the same scale, give similar reductions of the effective R-value, but that none of these models extend plausibly to an out-of-home duration of zero.
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Affiliation(s)
- Sydney Paltra
- Technische Universität Berlin, FG Verkehrssystemplanung und Verkehrstelematik, 10623, Berlin, Germany.
| | | | - Kai Nagel
- Technische Universität Berlin, FG Verkehrssystemplanung und Verkehrstelematik, 10623, Berlin, Germany
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2
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Smith TP, Mishra S, Dorigatti I, Dixit MK, Tristem M, Pearse WD. Differential responses of SARS-CoV-2 variants to environmental drivers during their selective sweeps. Sci Rep 2024; 14:13326. [PMID: 38858479 PMCID: PMC11164892 DOI: 10.1038/s41598-024-64044-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 06/04/2024] [Indexed: 06/12/2024] Open
Abstract
Previous work has shown that environmental variables affect SARS-CoV-2 transmission, but it is unclear whether different strains show similar environmental responses. Here we leverage genetic data on the transmission of three (Alpha, Delta and Omicron BA.1) variants of SARS-CoV-2 throughout England, to unpick the roles that climate and public-health interventions play in the circulation of this virus. We find evidence for enhanced transmission of the virus in colder conditions in the first variant selective sweep (of Alpha, in winter), but limited evidence of an impact of climate in either the second (of Delta, in the summer, when vaccines were prevalent) or third sweep (of Omicron, in the winter, during a successful booster-vaccination campaign). We argue that the results for Alpha are to be expected if the impact of climate is non-linear: we find evidence of an asymptotic impact of temperature on the alpha variant transmission rate. That is, at lower temperatures, the influence of temperature on transmission is much higher than at warmer temperatures. As with the initial spread of SARS-CoV-2, however, the overwhelming majority of variation in disease transmission is explained by the intrinsic biology of the virus and public-health mitigation measures. Specifically, when vaccination rates are high, a major driver of the spread of a new variant is it's ability to evade immunity, and any climate effects are secondary (as evidenced for Delta and Omicron). Climate alone cannot describe the transmission dynamics of emerging SARS-CoV-2 variants.
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Affiliation(s)
- Thomas P Smith
- Georgina Mace Centre for the Living Planet, Department of Life Sciences, Imperial College London, Silwood Park, Ascot, Berkshire, SL5 7PY, UK.
| | - Swapnil Mishra
- Saw Swee Hock School of Public Health and Institute of Data Science, National University of Singapore and National University Health System, 12 Science Dr 2, Singapore, 117549, Singapore
| | - Ilaria Dorigatti
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, 90 Wood Lane, London, W12 OBZ, UK
| | - Mahika K Dixit
- Georgina Mace Centre for the Living Planet, Department of Life Sciences, Imperial College London, Silwood Park, Ascot, Berkshire, SL5 7PY, UK
| | - Michael Tristem
- Georgina Mace Centre for the Living Planet, Department of Life Sciences, Imperial College London, Silwood Park, Ascot, Berkshire, SL5 7PY, UK
| | - William D Pearse
- Georgina Mace Centre for the Living Planet, Department of Life Sciences, Imperial College London, Silwood Park, Ascot, Berkshire, SL5 7PY, UK
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3
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López-Bazo E. The complex link between socioeconomic deprivation and COVID-19. Evidence from small areas of Catalonia. Spat Spatiotemporal Epidemiol 2024; 49:100648. [PMID: 38876561 DOI: 10.1016/j.sste.2024.100648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 01/20/2024] [Accepted: 03/11/2024] [Indexed: 06/16/2024]
Abstract
This ecological study assesses the association between the incidence rate of COVID-19 confirmed cases and socioeconomic deprivation in the Catalan small areas for the first six waves of the pandemic. The association is estimated using Poisson regressions and, in contrast to previous studies, considering that the relationship is not linear but rather depends on the degree of deprivation. The results show that the association between deprivation and incidence varied between waves, not only in intensity but also in its sign. Although it was insignificant in the first, third and fourth waves, the association was positive and significant in the second, becoming significantly negative in the fifth and sixth waves. Interestingly, the evidence suggests that the link between both magnitudes was not homogeneous throughout the distribution of deprivation, the pattern also varying between waves. The results are discussed in view of the role of non-pharmacological interventions and vaccination, as well as potential biases (for example that associated with differences between population groups in the propensity to be tested in each wave).
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Affiliation(s)
- Enrique López-Bazo
- AQR-University of Barcelona, Av. Diagonal 690, Barcelona E-08034, Spain.
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4
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Lo YTE, Mitchell DM, Gasparrini A. Compound mortality impacts from extreme temperatures and the COVID-19 pandemic. Nat Commun 2024; 15:4289. [PMID: 38782899 PMCID: PMC11116452 DOI: 10.1038/s41467-024-48207-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 04/24/2024] [Indexed: 05/25/2024] Open
Abstract
Extreme weather and coronavirus-type pandemics are both leading global health concerns. Until now, no study has quantified the compound health consequences of the co-occurrence of them. We estimate the mortality attributable to extreme heat and cold events, which dominate the UK health burden from weather hazards, in England and Wales in the period 2020-2022, during which the COVID-19 pandemic peaked in terms of mortality. We show that temperature-related mortality exceeded COVID-19 mortality by 8% in South West England. Combined, extreme temperatures and COVID-19 led to 19 (95% confidence interval: 16-22 in North West England) to 24 (95% confidence interval: 20-29 in Wales) excess deaths per 100,000 population during heatwaves, and 80 (95% confidence interval: 75-86 in Yorkshire and the Humber) to 127 (95% confidence interval: 123-132 in East of England) excess deaths per 100,000 population during cold snaps. These numbers are at least ~2 times higher than the previous decade. Society must increase preparedness for compound health crises such as extreme weather coinciding with pandemics.
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Affiliation(s)
- Y T Eunice Lo
- Cabot Institute for the Environment, University of Bristol, Bristol, UK.
- Elizabeth Blackwell Institute for Health Research, University of Bristol, Bristol, UK.
| | - Dann M Mitchell
- Cabot Institute for the Environment, University of Bristol, Bristol, UK
- School of Geographical Sciences, University of Bristol, Bristol, UK
| | - Antonio Gasparrini
- Environment & Health Modelling (EHM) Lab, Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
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5
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Luo Q, Liu W, Liao J, Gu Z, Fan X, Luo Z, Zhang X, Hang J, Ou C. COVID-19 transmission and control in land public transport: A literature review. FUNDAMENTAL RESEARCH 2024; 4:417-429. [PMID: 38933205 PMCID: PMC11197583 DOI: 10.1016/j.fmre.2023.10.013] [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: 09/30/2022] [Revised: 10/18/2023] [Accepted: 10/20/2023] [Indexed: 06/28/2024] Open
Abstract
Land public transport is an important link within and between cities, and how to control the transmission of COVID-19 in land public transport is a critical issue in our daily lives. However, there are still many inconsistent opinions and views about the spread of SARS-CoV-2 in land public transport, which limits our ability to implement effective interventions. The purpose of this review is to overview the literature on transmission characteristics and routes of the epidemic in land public transport, as well as to investigate factors affecting its spread and provide feasible measures to mitigate the infection risk of passengers. We obtained 898 papers by searching the Web of Science, Pubmed, and WHO global COVID database by keywords, and finally selected 45 papers that can address the purpose of this review. Land public transport is a high outbreak area for COVID-19 due to characteristics like crowding, inadequate ventilation, long exposure time, and environmental closure. Different from surface touch transmission and drop spray transmission, aerosol inhalation transmission can occur not only in short distances but also in long distances. Insufficient ventilation is the most important factor influencing long-distance aerosol transmission. Other transmission factors (e.g., interpersonal distance, relative orientation, and ambient conditions) should be noticed as well, which have been summarized in this paper. To address various influencing factors, it is essential to suggest practical and efficient preventive measures. Among these, increased ventilation, particularly the fresh air (i.e., natural ventilation), has proven to effectively reduce indoor infection risk. Many preventive measures are also effective, such as enlarging social distance, avoiding face-to-face orientation, setting up physical partitions, disinfection, avoiding talking, and so on. As research on the epidemic has intensified, people have broken down many perceived barriers, but more comprehensive studies on monitoring systems and prevention measures in land public transport are still needed.
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Affiliation(s)
- Qiqi Luo
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
- Key Laboratory of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
- China Meteorological Administration Xiong'an Atmospheric Boundary Layer Key Laboratory, Xiong'an 070001, China
- Key Laboratory of Tropical Atmosphere-Ocean System (Sun Yat-sen University), Ministry of Education, Zhuhai 519000, China
| | - Wenbing Liu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
| | - Jiayuan Liao
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
| | - Zhongli Gu
- Guangdong Fans-tech Agro Co., Ltd, Yunfu 527300, China
| | - Xiaodan Fan
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
| | - Zhiwen Luo
- Welsh School of Architecture, Cardiff University, Cardiff CF10 3XQ, United Kingdom
| | - Xuelin Zhang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
| | - Jian Hang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
- Key Laboratory of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
- China Meteorological Administration Xiong'an Atmospheric Boundary Layer Key Laboratory, Xiong'an 070001, China
- Key Laboratory of Tropical Atmosphere-Ocean System (Sun Yat-sen University), Ministry of Education, Zhuhai 519000, China
| | - Cuiyun Ou
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
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Lei H, Zhang N, Xiao S, Zhuang L, Yang X, Chen T, Yang L, Wang D, Li Y, Shu Y. Relative Role of Age Groups and Indoor Environments in Influenza Transmission Under Different Urbanization Rates in China. Am J Epidemiol 2024; 193:596-605. [PMID: 37946322 DOI: 10.1093/aje/kwad218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 06/20/2023] [Accepted: 11/01/2023] [Indexed: 11/12/2023] Open
Abstract
Exploring the relative role of different indoor environments in respiratory infections transmission remains unclear, which is crucial for developing targeted nonpharmaceutical interventions. In this study, a total of 2,583,441 influenza-like illness cases tested from 2010 to 2017 in China were identified. An agent-based model was built and calibrated with the surveillance data, to assess the roles of 3 age groups (children <19 years, younger adults 19-60 years, older adults >60 years) and 4 types of indoor environments (home, schools, workplaces, and community areas) in influenza transmission by province with varying urbanization rates. When the urbanization rates increased from 35% to 90%, the proportion of children aged <19 years among influenza cases decreased from 76% to 45%. Additionally, we estimated that infections originating from children decreased from 95.1% (95% confidence interval (CI): 92.7, 97.5) to 59.3% (95% CI: 49.8, 68.7). Influenza transmission in schools decreased from 80.4% (95% CI: 76.5, 84.3) to 36.6% (95% CI: 20.6, 52.5), while transmission in the community increased from 2.4% (95% CI: 1.9, 2.8) to 45.4% (95% CI: 35.9, 54.8). With increasing urbanization rates, community areas and younger adults contributed more to infection transmission. These findings could help the development of targeted public health policies. This article is part of a Special Collection on Environmental Epidemiology. This article is part of a Special Collection on Environmental Epidemiology.
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7
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Jung SM, Loo SL, Howerton E, Contamin L, Smith CP, Carcelén EC, Yan K, Bents SJ, Levander J, Espino J, Lemaitre JC, Sato K, McKee CD, Hill AL, Chinazzi M, Davis JT, Mu K, Vespignani A, Rosenstrom ET, Rodriguez-Cartes SA, Ivy JS, Mayorga ME, Swann JL, España G, Cavany S, Moore SM, Perkins TA, Chen S, Paul R, Janies D, Thill JC, Srivastava A, Aawar MA, Bi K, Bandekar SR, Bouchnita A, Fox SJ, Meyers LA, Porebski P, Venkatramanan S, Adiga A, Hurt B, Klahn B, Outten J, Chen J, Mortveit H, Wilson A, Hoops S, Bhattacharya P, Machi D, Vullikanti A, Lewis B, Marathe M, Hochheiser H, Runge MC, Shea K, Truelove S, Viboud C, Lessler J. Potential impact of annual vaccination with reformulated COVID-19 vaccines: Lessons from the US COVID-19 scenario modeling hub. PLoS Med 2024; 21:e1004387. [PMID: 38630802 PMCID: PMC11062554 DOI: 10.1371/journal.pmed.1004387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 05/01/2024] [Accepted: 03/27/2024] [Indexed: 04/19/2024] Open
Abstract
BACKGROUND Coronavirus Disease 2019 (COVID-19) continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. Here, we present projections of COVID-19 hospitalizations and deaths in the United States for the next 2 years under 2 plausible assumptions about immune escape (20% per year and 50% per year) and 3 possible CDC recommendations for the use of annually reformulated vaccines (no recommendation, vaccination for those aged 65 years and over, vaccination for all eligible age groups based on FDA approval). METHODS AND FINDINGS The COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023 and April 15, 2025 under 6 scenarios representing the intersection of considered levels of immune escape and vaccination. Annually reformulated vaccines are assumed to be 65% effective against symptomatic infection with strains circulating on June 15 of each year and to become available on September 1. Age- and state-specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. State and national projections from 8 modeling teams were ensembled to produce projections for each scenario and expected reductions in disease outcomes due to vaccination over the projection period. From April 15, 2023 to April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November to January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% projection interval (PI) [1,438,000, 4,270,000]) hospitalizations and 209,000 (90% PI [139,000, 461,000]) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% confidence interval (CI) [104,000, 355,000]) fewer hospitalizations and 33,000 (95% CI [12,000, 54,000]) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000-598,000) fewer hospitalizations and 49,000 (95% CI [29,000, 69,000]) fewer deaths. CONCLUSIONS COVID-19 is projected to be a significant public health threat over the coming 2 years. Broad vaccination has the potential to substantially reduce the burden of this disease, saving tens of thousands of lives each year.
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Affiliation(s)
- Sung-mok Jung
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Sara L. Loo
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Emily Howerton
- The Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Lucie Contamin
- University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Claire P. Smith
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Erica C. Carcelén
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Katie Yan
- The Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Samantha J. Bents
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - John Levander
- University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Jessi Espino
- University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Joseph C. Lemaitre
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Koji Sato
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Clifton D. McKee
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Alison L. Hill
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Matteo Chinazzi
- Northeastern University, Boston, Massachusetts, United States of America
| | - Jessica T. Davis
- Northeastern University, Boston, Massachusetts, United States of America
| | - Kunpeng Mu
- Northeastern University, Boston, Massachusetts, United States of America
| | | | - Erik T. Rosenstrom
- North Carolina State University, Raleigh, North Carolina, United States of America
| | | | - Julie S. Ivy
- North Carolina State University, Raleigh, North Carolina, United States of America
| | - Maria E. Mayorga
- North Carolina State University, Raleigh, North Carolina, United States of America
| | - Julie L. Swann
- North Carolina State University, Raleigh, North Carolina, United States of America
| | - Guido España
- University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Sean Cavany
- University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Sean M. Moore
- University of Notre Dame, Notre Dame, Indiana, United States of America
| | - T. Alex Perkins
- University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Shi Chen
- University of North Carolina at Charlotte, Charlotte, North Carolina, United States of America
| | - Rajib Paul
- University of North Carolina at Charlotte, Charlotte, North Carolina, United States of America
| | - Daniel Janies
- University of North Carolina at Charlotte, Charlotte, North Carolina, United States of America
| | - Jean-Claude Thill
- University of North Carolina at Charlotte, Charlotte, North Carolina, United States of America
| | - Ajitesh Srivastava
- University of Southern California, Los Angeles, California, United States of America
| | - Majd Al Aawar
- University of Southern California, Los Angeles, California, United States of America
| | - Kaiming Bi
- University of Texas at Austin, Austin, Texas, United States of America
| | | | - Anass Bouchnita
- University of Texas at El Paso, El Paso, Texas, United States of America
| | - Spencer J. Fox
- University of Georgia, Athens, Georgia, United States of America
| | | | | | | | - Aniruddha Adiga
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Benjamin Hurt
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Brian Klahn
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Joseph Outten
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Jiangzhuo Chen
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Henning Mortveit
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Amanda Wilson
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Stefan Hoops
- University of Virginia, Charlottesville, Virginia, United States of America
| | | | - Dustin Machi
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Anil Vullikanti
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Bryan Lewis
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Madhav Marathe
- University of Virginia, Charlottesville, Virginia, United States of America
| | - Harry Hochheiser
- University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Michael C. Runge
- U.S. Geological Survey, Laurel, Maryland, United States of America
| | - Katriona Shea
- The Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Shaun Truelove
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Justin Lessler
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
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8
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Grover EN, Buchwald AG, Ghosh D, Carlton EJ. Does behavior mediate the effect of weather on SARS-CoV-2 transmission? Evidence from cell-phone data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.26.24304854. [PMID: 38585859 PMCID: PMC10996765 DOI: 10.1101/2024.03.26.24304854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Background There is growing evidence that weather alters SARS-CoV-2 transmission, but it remains unclear what drives the phenomenon. One prevailing hypothesis is that people spend more time indoors in cooler weather, leading to increased spread of SARS-CoV-2 related to time spent in confined spaces and close contact with others. However, the evidence in support of that hypothesis is limited and, at times, conflicting. Objectives We aim to evaluate the extent to which weather impacts COVID-19 via time spent away-from-home in indoor spaces, as compared to a direct effect of weather on COVID-19 hospitalization, independent of mobility. Methods We use a mediation framework, and combine daily weather, COVID-19 hospital surveillance, cellphone-based mobility data and building footprints to estimate the relationship between daily indoor and outdoor weather conditions, mobility, and COVID-19 hospitalizations. We quantify the direct health impacts of weather on COVID-19 hospitalizations and the indirect effects of weather via time spent indoors away-from-home on COVID-19 hospitalizations within five Colorado counties between March 4th 2020 and January 31st 2021. Results We found evidence that changes in 12-day lagged hospital admissions were primarily via the direct effects of weather conditions, rather than via indirect effects by which weather changes time spent indoors away-from-home. Sensitivity analyses evaluating time at home as a mediator were consistent with these conclusions. Discussion Our findings do not support the hypothesis that weather impacted SARS-CoV-2 transmission via changes in mobility patterns during the first year of the pandemic. Rather, weather appears to have impacted SARS-CoV-2 transmission primarily via mechanisms other than human movement. We recommend further analysis of this phenomenon to determine whether these findings generalize to current SARS-CoV-2 transmission dynamics and other seasonal respiratory pathogens.
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Affiliation(s)
- Elise N. Grover
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, USA
| | - Andrea G. Buchwald
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Debashis Ghosh
- Department of Biostatistics & Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, USA
| | - Elizabeth J. Carlton
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, USA
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9
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Andrup L, Krogfelt KA, Stephansen L, Hansen KS, Graversen BK, Wolkoff P, Madsen AM. Reduction of acute respiratory infections in day-care by non-pharmaceutical interventions: a narrative review. Front Public Health 2024; 12:1332078. [PMID: 38420031 PMCID: PMC10899481 DOI: 10.3389/fpubh.2024.1332078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 02/02/2024] [Indexed: 03/02/2024] Open
Abstract
Objective Children who start in day-care have 2-4 times as many respiratory infections compared to children who are cared for at home, and day-care staff are among the employees with the highest absenteeism. The extensive new knowledge that has been generated in the COVID-19 era should be used in the prevention measures we prioritize. The purpose of this narrative review is to answer the questions: Which respiratory viruses are the most significant in day-care centers and similar indoor environments? What do we know about the transmission route of these viruses? What evidence is there for the effectiveness of different non-pharmaceutical prevention measures? Design Literature searches with different terms related to respiratory infections in humans, mitigation strategies, viral transmission mechanisms, and with special focus on day-care, kindergarten or child nurseries, were conducted in PubMed database and Web of Science. Searches with each of the main viruses in combination with transmission, infectivity, and infectious spread were conducted separately supplemented through the references of articles that were retrieved. Results Five viruses were found to be responsible for ≈95% of respiratory infections: rhinovirus, (RV), influenza virus (IV), respiratory syncytial virus (RSV), coronavirus (CoV), and adenovirus (AdV). Novel research, emerged during the COVID-19 pandemic, suggests that most respiratory viruses are primarily transmitted in an airborne manner carried by aerosols (microdroplets). Conclusion Since airborne transmission is dominant for the most common respiratory viruses, the most important preventive measures consist of better indoor air quality that reduces viral concentrations and viability by appropriate ventilation strategies. Furthermore, control of the relative humidity and temperature, which ensures optimal respiratory functionality and, together with low resident density (or mask use) and increased time outdoors, can reduce the occurrence of respiratory infections.
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Affiliation(s)
- Lars Andrup
- The National Research Centre for the Working Environment, Copenhagen, Denmark
| | - Karen A Krogfelt
- Department of Science and Environment, Molecular and Medical Biology, PandemiX Center, Roskilde University, Roskilde, Denmark
| | - Lene Stephansen
- Gladsaxe Municipality, Social and Health Department, Gladsaxe, Denmark
| | | | | | - Peder Wolkoff
- The National Research Centre for the Working Environment, Copenhagen, Denmark
| | - Anne Mette Madsen
- The National Research Centre for the Working Environment, Copenhagen, Denmark
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10
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Auliya AA, Syafarina I, Latifah AL, Wiharto. Significance of weather condition, human mobility, and vaccination on global COVID-19 transmission. Spat Spatiotemporal Epidemiol 2024; 48:100635. [PMID: 38355259 DOI: 10.1016/j.sste.2024.100635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 01/03/2024] [Accepted: 01/15/2024] [Indexed: 02/16/2024]
Abstract
The transmission growth rate of infectious diseases, particularly COVID-19, has forced governments to take immediate control decisions. Previous studies have shown that human mobility, weather condition, and vaccination are potential factors influencing virus transmission. This study investigates the contribution of weather conditions, namely temperature and precipitation, human mobility, and vaccination to coronavirus transmission. Three machine learning models: random forest (RF), XGBoost, and neural networks, are applied to predict the confirmed cases based on three aforementioned variables. All models' prediction are evaluated via spatial and temporal analysis. The spatial analysis observes the model performance over countries on certain times. The temporal analysis looks at the model prediction of each country during the specified period. The models' prediction results effectively indicate the transmission trend. The RF model performs best with a coefficient of determination of up to 89%. Meanwhile, all models confirm that vaccination is most significantly associated with COVID-19 cases.
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Affiliation(s)
- Amandha Affa Auliya
- Research Center for Computing, National Research and Innovation Agency, Jl. Raya Jakarta Bogor KM 46, Cibinong, 16911, Indonesia; Sebelas Maret University, Jl. Ir Sutami No. 36, Surakarta, 57126, Indonesia
| | - Inna Syafarina
- Research Center for Computing, National Research and Innovation Agency, Jl. Raya Jakarta Bogor KM 46, Cibinong, 16911, Indonesia
| | - Arnida L Latifah
- Research Center for Computing, National Research and Innovation Agency, Jl. Raya Jakarta Bogor KM 46, Cibinong, 16911, Indonesia; School of Computing, Telkom University, Jl. Telekomunikasi No. 1, Bandung, 40257, Indonesia.
| | - Wiharto
- Sebelas Maret University, Jl. Ir Sutami No. 36, Surakarta, 57126, Indonesia
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11
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Jung SM, Loo SL, Howerton E, Contamin L, Smith CP, Carcelén EC, Yan K, Bents SJ, Levander J, Espino J, Lemaitre JC, Sato K, McKee CD, Hill AL, Chinazzi M, Davis JT, Mu K, Vespignani A, Rosenstrom ET, Rodriguez-Cartes SA, Ivy JS, Mayorga ME, Swann JL, España G, Cavany S, Moore SM, Perkins A, Chen S, Paul R, Janies D, Thill JC, Srivastava A, Al Aawar M, Bi K, Bandekar SR, Bouchnita A, Fox SJ, Meyers LA, Porebski P, Venkatramanan S, Adiga A, Hurt B, Klahn B, Outten J, Chen J, Mortveit H, Wilson A, Hoops S, Bhattacharya P, Machi D, Vullikanti A, Lewis B, Marathe M, Hochheiser H, Runge MC, Shea K, Truelove S, Viboud C, Lessler J. Potential impact of annual vaccination with reformulated COVID-19 vaccines: lessons from the U.S. COVID-19 Scenario Modeling Hub. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.26.23297581. [PMID: 37961207 PMCID: PMC10635209 DOI: 10.1101/2023.10.26.23297581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Importance COVID-19 continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. Objective To project COVID-19 hospitalizations and deaths from April 2023-April 2025 under two plausible assumptions about immune escape (20% per year and 50% per year) and three possible CDC recommendations for the use of annually reformulated vaccines (no vaccine recommendation, vaccination for those aged 65+, vaccination for all eligible groups). Design The COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023-April 15, 2025 under six scenarios representing the intersection of considered levels of immune escape and vaccination. State and national projections from eight modeling teams were ensembled to produce projections for each scenario. Setting The entire United States. Participants None. Exposure Annually reformulated vaccines assumed to be 65% effective against strains circulating on June 15 of each year and to become available on September 1. Age and state specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. Main outcomes and measures Ensemble estimates of weekly and cumulative COVID-19 hospitalizations and deaths. Expected relative and absolute reductions in hospitalizations and deaths due to vaccination over the projection period. Results From April 15, 2023-April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November-January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% PI: 1,438,000-4,270,000) hospitalizations and 209,000 (90% PI: 139,000-461,000) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% CI: 104,000-355,000) fewer hospitalizations and 33,000 (95% CI: 12,000-54,000) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000-598,000) fewer hospitalizations and 49,000 (95% CI: 29,000-69,000) fewer deaths. Conclusion and Relevance COVID-19 is projected to be a significant public health threat over the coming two years. Broad vaccination has the potential to substantially reduce the burden of this disease.
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Affiliation(s)
- Sung-mok Jung
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Sara L. Loo
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Emily Howerton
- The Pennsylvania State University, State College, Pennsylvania
| | | | - Claire P. Smith
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Erica C. Carcelén
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Katie Yan
- The Pennsylvania State University, State College, Pennsylvania
| | - Samantha J. Bents
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland
| | | | - Jessi Espino
- University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Joseph C. Lemaitre
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Koji Sato
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Clif D. McKee
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Alison L. Hill
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | | | - Kunpeng Mu
- University of Massachusetts Amherst, Amherst, Massachusetts
| | | | | | | | - Julie S. Ivy
- North Carolina State University, Raleigh, North Carolina
| | | | - Julie L. Swann
- North Carolina State University, Raleigh, North Carolina
| | | | - Sean Cavany
- University of Notre Dame, Notre Dame, Indiana
| | | | | | - Shi Chen
- University of North Carolina at Charlotte, Charlotte, North Carolina
| | - Rajib Paul
- University of North Carolina at Charlotte, Charlotte, North Carolina
| | - Daniel Janies
- University of North Carolina at Charlotte, Charlotte, North Carolina
| | - Jean-Claude Thill
- University of North Carolina at Charlotte, Charlotte, North Carolina
| | | | - Majd Al Aawar
- University of Southern California, Los Angeles, California
| | - Kaiming Bi
- University of Texas at Austin, Austin, Texas
| | | | | | | | | | | | | | | | | | - Brian Klahn
- University of Virginia, Charlottesville, Virginia
| | | | | | | | | | - Stefan Hoops
- University of Virginia, Charlottesville, Virginia
| | | | - Dustin Machi
- University of Virginia, Charlottesville, Virginia
| | | | - Bryan Lewis
- University of Virginia, Charlottesville, Virginia
| | | | | | | | - Katriona Shea
- The Pennsylvania State University, State College, Pennsylvania
| | - Shaun Truelove
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland
| | - Justin Lessler
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
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12
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Wood AJ, Sanchez AR, Bessell PR, Wightman R, Kao RR. Assessing the importance of demographic risk factors across two waves of SARS-CoV-2 using fine-scale case data. PLoS Comput Biol 2023; 19:e1011611. [PMID: 38011282 PMCID: PMC10703279 DOI: 10.1371/journal.pcbi.1011611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 12/07/2023] [Accepted: 10/17/2023] [Indexed: 11/29/2023] Open
Abstract
For the long term control of an infectious disease such as COVID-19, it is crucial to identify the most likely individuals to become infected and the role that differences in demographic characteristics play in the observed patterns of infection. As high-volume surveillance winds down, testing data from earlier periods are invaluable for studying risk factors for infection in detail. Observed changes in time during these periods may then inform how stable the pattern will be in the long term. To this end we analyse the distribution of cases of COVID-19 across Scotland in 2021, where the location (census areas of order 500-1,000 residents) and reporting date of cases are known. We consider over 450,000 individually recorded cases, in two infection waves triggered by different lineages: B.1.1.529 ("Omicron") and B.1.617.2 ("Delta"). We use random forests, informed by measures of geography, demography, testing and vaccination. We show that the distributions are only adequately explained when considering multiple explanatory variables, implying that case heterogeneity arose from a combination of individual behaviour, immunity, and testing frequency. Despite differences in virus lineage, time of year, and interventions in place, we find the risk factors remained broadly consistent between the two waves. Many of the observed smaller differences could be reasonably explained by changes in control measures.
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Affiliation(s)
- Anthony J. Wood
- Roslin Institute, University of Edinburgh, Midlothian, United Kingdom
| | - Aeron R. Sanchez
- Roslin Institute, University of Edinburgh, Midlothian, United Kingdom
| | - Paul R. Bessell
- Roslin Institute, University of Edinburgh, Midlothian, United Kingdom
| | - Rebecca Wightman
- Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Rowland R. Kao
- Roslin Institute, University of Edinburgh, Midlothian, United Kingdom
- Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, United Kingdom
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13
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Shi X, Ling GHT, Leng PC, Rusli N, Matusin AMRA. Associations between institutional-social-ecological factors and COVID -19 case-fatality: Evidence from 134 countries using multiscale geographically weighted regression (MGWR). One Health 2023; 16:100551. [PMID: 37153369 PMCID: PMC10141798 DOI: 10.1016/j.onehlt.2023.100551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 03/25/2023] [Accepted: 04/23/2023] [Indexed: 05/09/2023] Open
Abstract
During the period in which the Omicron coronavirus variant was rapidly spreading, the impact of the institutional-social-ecological dimensions on the case-fatality rate was rarely afforded attention. By adopting the diagnostic social-ecological system (SES) framework, the present paper aims to identify the impact of institutional-social-ecological factors on the case-fatality rate of COVID-19 in 134 countries and regions and test their spatial heterogeneity. Using statistical data from the Our World In Data website, the present study collected the cumulative case-fatality rate from 9 November 2021 to 23 June 2022, along with 11 country-level institutional-social-ecological factors. By comparing the goodness of fit of the multiple linear regression model and the multiscale geographically weighted regression (MGWR) model, the study demonstrated that the effects of SES factors exhibit significant spatial heterogeneity in relation to the case-fatality rate of COVID-19. After substituting the data into the MGWR model, six SES factors were identified with an R square of 0.470 based on the ascending effect size: COVID-19 vaccination policy, age dependency ratio, press freedom, gross domestic product (GDP), COVID-19 testing policy, and population density. The GWR model was used to test and confirm the robustness of the research results. Based on the analysis results, it is suggested that the world needs to meet four conditions to restore normal economic activity in the wake of the COVID-19 pandemic: (i) Countries should increase their COVID-19 vaccination coverage and maximize COVID-19 testing expansion. (ii) Countries should increase public health facilities available to provide COVID-19 treatment and subsidize the medical costs of COVID-19 patients. (iii) Countries should strictly review COVID-19 news reports and actively publicize COVID-19 pandemic prevention knowledge to the public through a range of media. (iv) Countries should adopt an internationalist spirit of cooperation and help each other to navigate the COVID-19 pandemic. The study further tests the applicability of the SES framework to the field of COVID-19 prevention and control based on the existing research, offering novel policy insights to cope with the COVID-19 pandemic that coexists with long-term human production and life for a long time.
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Affiliation(s)
- Xuerui Shi
- Department of Urban and Regional Planning, Faculty of Built Environment & Surveying, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia
| | - Gabriel Hoh Teck Ling
- Department of Urban and Regional Planning, Faculty of Built Environment & Surveying, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia
| | - Pau Chung Leng
- Department of Architecture, Faculty of Built Environment & Surveying, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia
| | - Noradila Rusli
- Department of Urban and Regional Planning, Faculty of Built Environment & Surveying, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia
- Centre for Innovative Planning and Development (CIPD), Faculty of Built Environment & Surveying, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia
| | - Ak Mohd Rafiq Ak Matusin
- Department of Urban and Regional Planning, Faculty of Built Environment & Surveying, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia
- Centre for Innovative Planning and Development (CIPD), Faculty of Built Environment & Surveying, Universiti Teknologi Malaysia, 81310 Johor Bahru, Malaysia
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14
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Wang Y, Lyu Y, Tong S, Ding C, Wei L, Zhai M, Xu K, Hao R, Wang X, Li N, Luo Y, Li Y, Wang J. Association between meteorological factors and COVID-19 transmission in low- and middle-income countries: A time-stratified case-crossover study. ENVIRONMENTAL RESEARCH 2023; 231:116088. [PMID: 37169140 PMCID: PMC10166718 DOI: 10.1016/j.envres.2023.116088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 04/23/2023] [Accepted: 05/08/2023] [Indexed: 05/13/2023]
Abstract
BACKGROUND Evidence is limited regarding the association between meteorological factors and COVID-19 transmission in low- and middle-income countries (LMICs). OBJECTIVE To investigate the independent and interactive effects of temperature, relative humidity (RH), and ultraviolet (UV) radiation on the spread of COVID-19 in LMICs. METHODS We collected daily data on COVID-19 confirmed cases, meteorological factors and non-pharmaceutical interventions (NPIs) in 2143 city- and district-level sites from 6 LMICs during 2020. We applied a time-stratified case-crossover design with distributed lag nonlinear model to evaluate the independent and interactive effects of meteorological factors on COVID-19 transmission after controlling NPIs. We generated an overall estimate through pooling site-specific relative risks (RR) using a multivariate meta-regression model. RESULTS There was a positive, non-linear, association between temperature and COVID-19 confirmed cases in all study sites, while RH and UV showed negative non-linear associations. RR of the 90th percentile temperature (28.1 °C) was 1.14 [95% confidence interval (CI): 1.02, 1.28] compared with the 50th percentile temperature (24.4 °C). RR of the10th percentile UV was 1.41 (95% CI: 1.29, 1.54). High temperature and high RH were associated with increased risks in temperate climate but decreased risks in tropical climate, while UV exhibited a consistent, negative association across climate zones. Temperature, RH, and UV interacted to affect COVID-19 transmission. Temperature and RH also showed higher risks in low NPIs sites. CONCLUSION Temperature, RH, and UV appeared to independently and interactively affect the transmission of COVID-19 in LMICs but such associations varied with climate zones. Our results suggest that more attention should be paid to meteorological variation when the transmission of COVID-19 is still rampant in LMICs.
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Affiliation(s)
- Yu Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Yiran Lyu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Shilu Tong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China; Shanghai Children's Medical Center, Shanghai Jiao Tong University, Shanghai, 200025, China; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, 230032, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, 4000, Australia
| | - Cheng Ding
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Lan Wei
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Mengying Zhai
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Kaiqiang Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China; School of Public Health, Hebei University, Hebei, 071000, China
| | - Ruiting Hao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Xiaochen Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Na Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Yueyun Luo
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Yonghong Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China
| | - Jiao Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
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15
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Paireau J, Charpignon ML, Larrieu S, Calba C, Hozé N, Boëlle PY, Thiebaut R, Prague M, Cauchemez S. Impact of non-pharmaceutical interventions, weather, vaccination, and variants on COVID-19 transmission across departments in France. BMC Infect Dis 2023; 23:190. [PMID: 36997873 PMCID: PMC10061408 DOI: 10.1186/s12879-023-08106-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 02/20/2023] [Indexed: 04/01/2023] Open
Abstract
BACKGROUND Multiple factors shape the temporal dynamics of the COVID-19 pandemic. Quantifying their relative contributions is key to guide future control strategies. Our objective was to disentangle the individual effects of non-pharmaceutical interventions (NPIs), weather, vaccination, and variants of concern (VOC) on local SARS-CoV-2 transmission. METHODS We developed a log-linear model for the weekly reproduction number (R) of hospital admissions in 92 French metropolitan departments. We leveraged (i) the homogeneity in data collection and NPI definitions across departments, (ii) the spatial heterogeneity in the timing of NPIs, and (iii) an extensive observation period (14 months) covering different weather conditions, VOC proportions, and vaccine coverage levels. FINDINGS Three lockdowns reduced R by 72.7% (95% CI 71.3-74.1), 70.4% (69.2-71.6) and 60.7% (56.4-64.5), respectively. Curfews implemented at 6/7 pm and 8/9 pm reduced R by 34.3% (27.9-40.2) and 18.9% (12.04-25.3), respectively. School closures reduced R by only 4.9% (2.0-7.8). We estimated that vaccination of the entire population would have reduced R by 71.7% (56.4-81.6), whereas the emergence of VOC (mainly Alpha during the study period) increased transmission by 44.6% (36.1-53.6) compared with the historical variant. Winter weather conditions (lower temperature and absolute humidity) increased R by 42.2% (37.3-47.3) compared to summer weather conditions. Additionally, we explored counterfactual scenarios (absence of VOC or vaccination) to assess their impact on hospital admissions. INTERPRETATION Our study demonstrates the strong effectiveness of NPIs and vaccination and quantifies the role of weather while adjusting for other confounders. It highlights the importance of retrospective evaluation of interventions to inform future decision-making.
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Affiliation(s)
- Juliette Paireau
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, CNRS UMR 2000, Paris, France.
- Infectious Diseases Department, Santé Publique France, Saint Maurice, France.
| | - Marie-Laure Charpignon
- Institute for Data, Systems, and Society (IDSS), Cambridge, MA, USA
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
- University of Bordeaux, Inria Bordeaux Sud-Ouest, Inserm, Bordeaux Population Health Research Center, SISTM Team, UMR1219, Bordeaux, France
| | - Sophie Larrieu
- Regions Department, Regional Office Nouvelle-Aquitaine, Santé publique France, Bordeaux, France
| | - Clémentine Calba
- Regions Department, Regional Office Provence-Alps-French Riviera and Corsica, Santé Publique France, Marseille, France
| | - Nathanaël Hozé
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, CNRS UMR 2000, Paris, France
| | - Pierre-Yves Boëlle
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique, Paris, France
| | - Rodolphe Thiebaut
- University of Bordeaux, Inria Bordeaux Sud-Ouest, Inserm, Bordeaux Population Health Research Center, SISTM Team, UMR1219, Bordeaux, France
| | - Mélanie Prague
- University of Bordeaux, Inria Bordeaux Sud-Ouest, Inserm, Bordeaux Population Health Research Center, SISTM Team, UMR1219, Bordeaux, France
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, CNRS UMR 2000, Paris, France
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16
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Colston JM, Hinson P, Nguyen NLH, Chen YT, Badr HS, Kerr GH, Gardner LM, Martin DN, Quispe AM, Schiaffino F, Kosek MN, Zaitchik BF. Effects of hydrometeorological and other factors on SARS-CoV-2 reproduction number in three contiguous countries of tropical Andean South America: a spatiotemporally disaggregated time series analysis. IJID REGIONS 2023; 6:29-41. [PMID: 36437857 PMCID: PMC9675637 DOI: 10.1016/j.ijregi.2022.11.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 11/14/2022] [Accepted: 11/15/2022] [Indexed: 06/09/2023]
Abstract
Background The COVID-19 pandemic has caused societal disruption globally, and South America has been hit harder than other lower-income regions. This study modeled the effects of six weather variables on district-level SARS-CoV-2 reproduction numbers (Rt ) in three contiguous countries of tropical Andean South America (Colombia, Ecuador, and Peru), adjusting for environmental, policy, healthcare infrastructural and other factors. Methods Daily time-series data on SARS-CoV-2 infections were sourced from the health authorities of the three countries at the smallest available administrative level. Rt values were calculated and merged by date and unit ID with variables from a unified COVID-19 dataset and other publicly available sources for May-December, 2020. Generalized additive models were fitted. Findings Relative humidity and solar radiation were inversely associated with SARS-CoV-2 Rt . Days with radiation above 1000 kJ/m2 saw a 1.3% reduction in Rt , and those with humidity above 50% recorded a 0.9% reduction in Rt . Transmission was highest in densely populated districts, and lowest in districts with poor healthcare access and on days with lowest population mobility. Wind speed, temperature, region, aggregate government policy response, and population age structure had little impact. The fully adjusted model explained 4.3% of Rt variance. Interpretation Dry atmospheric conditions of low humidity increase district-level SARS-CoV-2 reproduction numbers, while higher levels of solar radiation decrease district-level SARS-CoV-2 reproduction numbers - effects that are comparable in magnitude to population factors like lockdown compliance. Weather monitoring could be incorporated into disease surveillance and early warning systems in conjunction with more established risk indicators and surveillance measures. Funding NASA's Group on Earth Observations Work Programme (16-GEO16-0047).
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Affiliation(s)
- Josh M. Colston
- Division of Infectious Diseases and International Health, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA
| | - Patrick Hinson
- College of Arts and Sciences, University of Virginia, VA, USA
| | | | - Yen Ting Chen
- Department of Emergency Medicine, Chi-Mei Medical Center, Tainan, Taiwan
| | - Hamada S. Badr
- Department of Earth and Planetary Sciences, Johns Hopkins Krieger School of Arts and Sciences, Baltimore, MD, 21218, USA
| | - Gaige H. Kerr
- Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, USA
| | - Lauren M. Gardner
- Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - David N. Martin
- Claude Moore Health Sciences Library, University of Virginia School of Medicine, VA, USA
| | | | - Francesca Schiaffino
- Faculty of Veterinary Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru
- Division of Infectious Diseases and International Health and Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA
| | - Margaret N. Kosek
- Division of Infectious Diseases and International Health and Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA
| | - Benjamin F. Zaitchik
- Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, USA
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17
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Li G, Denise H, Diggle P, Grimsley J, Holmes C, James D, Jersakova R, Mole C, Nicholson G, Smith CR, Richardson S, Rowe W, Rowlingson B, Torabi F, Wade MJ, Blangiardo M. A spatio-temporal framework for modelling wastewater concentration during the COVID-19 pandemic. ENVIRONMENT INTERNATIONAL 2023; 172:107765. [PMID: 36709674 PMCID: PMC9847331 DOI: 10.1016/j.envint.2023.107765] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 12/13/2022] [Accepted: 01/17/2023] [Indexed: 06/18/2023]
Abstract
The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentration and COVID-19 case numbers at the catchment areas of sewage treatment works (STWs) over time. However, no attempt has been made to develop a model that predicts wastewater concentration at fine spatio-temporal resolutions covering an entire country, a necessary step towards using wastewater monitoring for the early detection of local outbreaks. We consider weekly averages of flow-normalised viral concentration, reported as the number of SARS-CoV-2N1 gene copies per litre (gc/L) of wastewater available at 303 STWs over the period between 1 June 2021 and 30 March 2022. We specify a spatially continuous statistical model that quantifies the relationship between weekly viral concentration and a collection of covariates covering socio-demographics, land cover and virus associated genomic characteristics at STW catchment areas while accounting for spatial and temporal correlation. We evaluate the model's predictive performance at the catchment level through 10-fold cross-validation. We predict the weekly viral concentration at the population-weighted centroid of the 32,844 lower super output areas (LSOAs) in England, then aggregate these LSOA predictions to the Lower Tier Local Authority level (LTLA), a geography that is more relevant to public health policy-making. We also use the model outputs to quantify the probability of local changes of direction (increases or decreases) in viral concentration over short periods (e.g. two consecutive weeks). The proposed statistical framework can predict SARS-CoV-2 viral concentration in wastewater at high spatio-temporal resolution across England. Additionally, the probabilistic quantification of local changes can be used as an early warning tool for public health surveillance.
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Affiliation(s)
- Guangquan Li
- Applied Statistics Research Group, Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK; Turing-RSS Health Data Lab, UK
| | - Hubert Denise
- Analytics & Data Science Directorate, UK Health Security Agency, Nobel House, Smith Square, London SW1P 3JR, UK
| | - Peter Diggle
- Lancaster University, Lancaster LA1 4YW, UK; Turing-RSS Health Data Lab, UK
| | - Jasmine Grimsley
- Analytics & Data Science Directorate, UK Health Security Agency, Nobel House, Smith Square, London SW1P 3JR, UK
| | - Chris Holmes
- University of Oxford, Oxford, UK; The Alan Turing Institute, London NW1 2DB, UK; Turing-RSS Health Data Lab, UK
| | - Daniel James
- Analytics & Data Science Directorate, UK Health Security Agency, Nobel House, Smith Square, London SW1P 3JR, UK
| | - Radka Jersakova
- The Alan Turing Institute, London NW1 2DB, UK; Turing-RSS Health Data Lab, UK
| | - Callum Mole
- The Alan Turing Institute, London NW1 2DB, UK; Turing-RSS Health Data Lab, UK
| | - George Nicholson
- University of Oxford, Oxford, UK; Turing-RSS Health Data Lab, UK
| | - Camila Rangel Smith
- The Alan Turing Institute, London NW1 2DB, UK; Turing-RSS Health Data Lab, UK
| | - Sylvia Richardson
- MRC Biostatistics Unit, East Forvie Site, Cambridge CB20SR, UK; Turing-RSS Health Data Lab, UK
| | - William Rowe
- Analytics & Data Science Directorate, UK Health Security Agency, Nobel House, Smith Square, London SW1P 3JR, UK
| | - Barry Rowlingson
- Lancaster University, Lancaster LA1 4YW, UK; Turing-RSS Health Data Lab, UK
| | - Fatemeh Torabi
- Swansea University Medical School, Faculty of Medicine, Health Life Science, Swansea SA2 8PP, UK; Turing-RSS Health Data Lab, UK
| | - Matthew J Wade
- Analytics & Data Science Directorate, UK Health Security Agency, Nobel House, Smith Square, London SW1P 3JR, UK
| | - Marta Blangiardo
- MRC Centre for Environment and Health, Imperial College London, St Mary's Campus, Norfolk Place, London W2 1PG, UK; Turing-RSS Health Data Lab, UK
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18
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Duarte I, Ribeiro MC, Pereira MJ, Leite PP, Peralta-Santos A, Azevedo L. Spatiotemporal evolution of COVID-19 in Portugal's Mainland with self-organizing maps. Int J Health Geogr 2023; 22:4. [PMID: 36710328 PMCID: PMC9884330 DOI: 10.1186/s12942-022-00322-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 12/23/2022] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Self-Organizing Maps (SOM) are an unsupervised learning clustering and dimensionality reduction algorithm capable of mapping an initial complex high-dimensional data set into a low-dimensional domain, such as a two-dimensional grid of neurons. In the reduced space, the original complex patterns and their interactions can be better visualized, interpreted and understood. METHODS We use SOM to simultaneously couple the spatial and temporal domains of the COVID-19 evolution in the 278 municipalities of mainland Portugal during the first year of the pandemic. Temporal 14-days cumulative incidence time series along with socio-economic and demographic indicators per municipality were analyzed with SOM to identify regions of the country with similar behavior and infer the possible common origins of the incidence evolution. RESULTS The results show how neighbor municipalities tend to share a similar behavior of the disease, revealing the strong spatiotemporal relationship of the COVID-19 spreading beyond the administrative borders of each municipality. Additionally, we demonstrate how local socio-economic and demographic characteristics evolved as determinants of COVID-19 transmission, during the 1st wave school density per municipality was more relevant, where during 2nd wave jobs in the secondary sector and the deprivation score were more relevant. CONCLUSIONS The results show that SOM can be an effective tool to analysing the spatiotemporal behavior of COVID-19 and synthetize the history of the disease in mainland Portugal during the period in analysis. While SOM have been applied to diverse scientific fields, the application of SOM to study the spatiotemporal evolution of COVID-19 is still limited. This work illustrates how SOM can be used to describe the spatiotemporal behavior of epidemic events. While the example shown herein uses 14-days cumulative incidence curves, the same analysis can be performed using other relevant data such as mortality data, vaccination rates or even infection rates of other disease of infectious nature.
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Affiliation(s)
- Igor Duarte
- grid.9983.b0000 0001 2181 4263Formely: Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisbon, Portugal
| | - Manuel C. Ribeiro
- grid.9983.b0000 0001 2181 4263CERENA/DER, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisbon, Portugal
| | - Maria João Pereira
- grid.9983.b0000 0001 2181 4263CERENA/DER, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisbon, Portugal
| | - Pedro Pinto Leite
- grid.420634.70000 0001 0807 4731Direção de Serviços de Informação e Análise, Direção-Geral da Saúde, Lisbon, Portugal
| | - André Peralta-Santos
- grid.420634.70000 0001 0807 4731Direção de Serviços de Informação e Análise, Direção-Geral da Saúde, Lisbon, Portugal ,grid.10772.330000000121511713NOVA National School of Public Health, Public Health Research Centre, Universidade NOVA de Lisboa, Lisbon, Portugal ,grid.10772.330000000121511713Comprehensive Health Research Centre (CHRC), Universidade NOVA de Lisboa, Lisbon, Portugal
| | - Leonardo Azevedo
- CERENA/DER, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001, Lisbon, Portugal.
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19
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Nottmeyer L, Armstrong B, Lowe R, Abbott S, Meakin S, O'Reilly KM, von Borries R, Schneider R, Royé D, Hashizume M, Pascal M, Tobias A, Vicedo-Cabrera AM, Lavigne E, Correa PM, Ortega NV, Kynčl J, Urban A, Orru H, Ryti N, Jaakkola J, Dallavalle M, Schneider A, Honda Y, Ng CFS, Alahmad B, Carrasco-Escobar G, Holobâc IH, Kim H, Lee W, Íñiguez C, Bell ML, Zanobetti A, Schwartz J, Scovronick N, Coélho MDSZS, Saldiva PHN, Diaz MH, Gasparrini A, Sera F. The association of COVID-19 incidence with temperature, humidity, and UV radiation - A global multi-city analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 854:158636. [PMID: 36087670 PMCID: PMC9450475 DOI: 10.1016/j.scitotenv.2022.158636] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 09/05/2022] [Accepted: 09/05/2022] [Indexed: 05/05/2023]
Abstract
BACKGROUND AND AIM The associations between COVID-19 transmission and meteorological factors are scientifically debated. Several studies have been conducted worldwide, with inconsistent findings. However, often these studies had methodological issues, e.g., did not exclude important confounding factors, or had limited geographic or temporal resolution. Our aim was to quantify associations between temporal variations in COVID-19 incidence and meteorological variables globally. METHODS We analysed data from 455 cities across 20 countries from 3 February to 31 October 2020. We used a time-series analysis that assumes a quasi-Poisson distribution of the cases and incorporates distributed lag non-linear modelling for the exposure associations at the city-level while considering effects of autocorrelation, long-term trends, and day of the week. The confounding by governmental measures was accounted for by incorporating the Oxford Governmental Stringency Index. The effects of daily mean air temperature, relative and absolute humidity, and UV radiation were estimated by applying a meta-regression of local estimates with multi-level random effects for location, country, and climatic zone. RESULTS We found that air temperature and absolute humidity influenced the spread of COVID-19 over a lag period of 15 days. Pooling the estimates globally showed that overall low temperatures (7.5 °C compared to 17.0 °C) and low absolute humidity (6.0 g/m3 compared to 11.0 g/m3) were associated with higher COVID-19 incidence (RR temp =1.33 with 95%CI: 1.08; 1.64 and RR AH =1.33 with 95%CI: 1.12; 1.57). RH revealed no significant trend and for UV some evidence of a positive association was found. These results were robust to sensitivity analysis. However, the study results also emphasise the heterogeneity of these associations in different countries. CONCLUSION Globally, our results suggest that comparatively low temperatures and low absolute humidity were associated with increased risks of COVID-19 incidence. However, this study underlines regional heterogeneity of weather-related effects on COVID-19 transmission.
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Affiliation(s)
- Luise Nottmeyer
- Faculty of Engineering Sciences, Heidelberg University, Heidelberg, Germany.
| | - Ben Armstrong
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Rachel Lowe
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Barcelona Supercomputing Center (BSC), Barcelona, Spain; Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Sam Abbott
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Sophie Meakin
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Kathleen M O'Reilly
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Rochelle Schneider
- Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Φ-Lab, European Space Agency, Frascati, Italy; European Centre for Medium-Range Weather Forecast (ECMWF), Reading, UK
| | - Dominic Royé
- Department of Geography, University of Santiago de Compostela, CIBER of Epidemiology and Public Health (CIBERESP), Spain
| | - Masahiro Hashizume
- Department of Paediatric Infectious Disease, Institute of Tropical Medicine, Nagasaki University, Japan; School of Tropical Medicine and Global Health, Nagasaki University, Japan; Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Mathilde Pascal
- Santé Publique France, Department of Environmental and Occupational Health, French National Public Health Agency, Saint Maurice, France
| | - Aurelio Tobias
- School of Tropical Medicine and Global Health, Nagasaki University, Japan; Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Barcelona, Spain
| | - Ana Maria Vicedo-Cabrera
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland
| | - Eric Lavigne
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada; Air Health Science Division, Health Canada, Ottawa, Canada
| | | | | | - Jan Kynčl
- Department of Infectious Diseases Epidemiology, National Institute of Public Health, Prague, Czech Republic; Department of Epidemiology and Biostatistics, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Aleš Urban
- Institute of Atmospheric Physics of the Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - Hans Orru
- Department of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Niilo Ryti
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland; Medical Research Center Oulu (MRC Oulu), Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Jouni Jaakkola
- Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland; Medical Research Center Oulu (MRC Oulu), Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Marco Dallavalle
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany; Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Yasushi Honda
- School of Tropical Medicine and Global Health, Nagasaki University, Japan; Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan; Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
| | - Chris Fook Sheng Ng
- School of Tropical Medicine and Global Health, Nagasaki University, Japan; Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Barrak Alahmad
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, USA
| | - Gabriel Carrasco-Escobar
- Health Innovation Laboratory, Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - Ho Kim
- Department of Public Health Science, Graduate School of Public Health & Institute of Health and Environment, Seoul National University, Seoul, Republic of Korea
| | - Whanhee Lee
- School of Biomedical Convergence Engineering, College of Information and Biomedical Engineering, Pusan National University, Yangsan, South Korea
| | - Carmen Íñiguez
- Department of Statistics and Computational Research, Universitat de València, València, Spain
| | - Michelle L Bell
- School of the Environment, Yale University, New Haven, CT, USA
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, USA
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, USA
| | | | | | - Magali Hurtado Diaz
- Department of Environmental Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Antonio Gasparrini
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, UK
| | - Francesco Sera
- Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence, Florence, Italy.
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20
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Alaniz AJ, Carvajal MA, Carvajal JG, Vergara PM. Effects of air pollution and weather on the initial COVID-19 outbreaks in United States, Italy, Spain, and China: A comparative study. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2023; 43:8-18. [PMID: 36509703 PMCID: PMC9877606 DOI: 10.1111/risa.14080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 08/03/2022] [Accepted: 11/05/2022] [Indexed: 06/17/2023]
Abstract
Contrasting effects have been identified in association of weather (temperature and humidity) and pollutant gases with COVID-19 infection, which could be derived from the influence of lockdowns and season change. The influence of pollutant gases and climate during the initial phases of the pandemic, before the closures and the change of season in the northern hemisphere, is unknown. Here, we used a spatial-temporal Bayesian zero-inflated-Poisson model to test for short-term associations of weather and pollutant gases with the relative risk of COVID-19 disease in China (first outbreak) and the countries with more cases during the initial pandemic (the United States, Spain and Italy), considering also the effects of season and lockdown. We found contrasting association between pollutant gases and COVID-19 risk in the United States, Italy, and Spain, while in China it was negatively associated (except for SO2 ). COVID-19 risk was positively associated with specific humidity in all countries, while temperature presented a negative effect. Our findings showed that short-term associations of air pollutants with COVID-19 infection vary strongly between countries, while generalized effects of temperature (negative) and humidity (positive) with COVID-19 was found. Our results show novel information about the influence of pollution and weather on the initial outbreaks, which contribute to unravel the mechanisms during the beginning of the pandemic.
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Affiliation(s)
- Alberto J. Alaniz
- Departamento de Ingeniería Geoespacial y Ambiental, Facultad de IngenieríaUniversidad de Santiago de ChileSantiagoChile
- Facultad de Ciencias BiológicasPontificia Universidad Católica de ChileSantiagoChile
- Departamento de Gestión Agraria, Facultad TecnológicaUniversidad de Santiago de ChileSantiagoChile
- Centro de Estudios en Ecología Espacial y Medio AmbienteEcogeografíaSantiagoChile
| | - Mario A. Carvajal
- Facultad de Ciencias BiológicasPontificia Universidad Católica de ChileSantiagoChile
- Departamento de Gestión Agraria, Facultad TecnológicaUniversidad de Santiago de ChileSantiagoChile
| | - Jorge G. Carvajal
- Departamento de Gestión Agraria, Facultad TecnológicaUniversidad de Santiago de ChileSantiagoChile
- Centro de Estudios en Ecología Espacial y Medio AmbienteEcogeografíaSantiagoChile
| | - Pablo M. Vergara
- Departamento de Gestión Agraria, Facultad TecnológicaUniversidad de Santiago de ChileSantiagoChile
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21
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Song Q, Qian G, Mi Y, Zhu J, Cao C. Synergistic influence of air temperature and vaccination on COVID-19 transmission and mortality in 146 countries or regions. ENVIRONMENTAL RESEARCH 2022; 215:114229. [PMID: 36049515 PMCID: PMC9423881 DOI: 10.1016/j.envres.2022.114229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 08/23/2022] [Accepted: 08/26/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVE We aimed to determine the influence of vaccination and air temperature on COVID-19 transmission and severity. METHODS The study data in 146 countries from January 6, 2020 to July 28, 2022 were aggregated into 19,856 weeks. Country-level weekly incidence, time-varying reproduction number (Rt), mortality, and infection-fatality ratio (IFR) were compared among groups of these weeks with different vaccination rates and air temperatures. RESULTS Weeks with <15 °C air temperature and 60% vaccination showed the highest incidence (mean, 604; SD, 855; 95% CI, 553-656, unit, /100,000 persons; N = 1073) and the highest rate of weeks with >1 Rt (mean, 41.6%; SD, 1.49%; 95% CI, 39.2-45.2%; N = 1090), while weeks with >25 °C and <20% showed the lowest incidence (mean, 24; SD, 75; 95% CI, 22-26; N = 5805) and the lowest rate of weeks with >1 Rt (mean, 15.3%; SD, 0.461%; 95% CI, 14.2-16.2%; N = 6122). Mortality in weeks with <15 °C (mean, 2.1; SD, 2.8; 95% CI, 2.0-2.2, unit, /100,000 persons; N = 4365) was five times of the mortality in weeks with >25 °C (mean, 0.44; SD, 1; 95% CI, 0.41-0.46; N = 7741). IFR ranged between 2% and 2.6% (SD, 1.9%-2.4%; 95% CI, 2.0-2.7%) at < 20% vaccination level, 1.8% (SD, 2%-2.2%; 95% CI, 1.7-2.0%) at 20-60% vaccination level, and 0.7%-1% (SD, 1%-1.8%; 95% CI, 0.7-1.1%) at > 60% vaccination level and at all air temperatures (all P < 0.001). CONCLUSIONS Vaccination was insufficient to mitigate the transmission since the significantly elevated weekly incidence and >1 Rt rate in weeks with high vaccination, while IFR was reduced by high vaccination. Countries with long-term low air temperature were affected by high transmission and high mortality.
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Affiliation(s)
- Qifa Song
- Medical Data Center, Ningbo City First Hospital, Ningbo, Zhejiang Province, China.
| | - Guoqing Qian
- Department of General Internal Medicine, Ningbo City First Hospital, Ningbo, Zhejiang Province, China
| | - Yuwei Mi
- Medical Data Center, Ningbo City First Hospital, Ningbo, Zhejiang Province, China
| | - Jianhua Zhu
- Department of Critical Care Medicine, Ningbo City First Hospital, Ningbo, Zhejiang Province, China.
| | - Chao Cao
- Department of Respiratory and Critical Medicine, Ningbo City First Hospital, Ningbo, Zhejiang Province, China.
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22
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Johnsen MG, Christiansen LE, Græsbøll K. Seasonal variation in the transmission rate of covid-19 in a temperate climate can be implemented in epidemic population models by using daily average temperature as a proxy for seasonal changes in transmission rate. MICROBIAL RISK ANALYSIS 2022; 22:100235. [PMID: 36248679 PMCID: PMC9546506 DOI: 10.1016/j.mran.2022.100235] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 09/27/2022] [Accepted: 09/28/2022] [Indexed: 06/16/2023]
Abstract
From march 2020 to march 2022 covid-19 has shown a consistent pattern of increasing infections during the Winter and low infection numbers during the Summer. Understanding the effects of seasonal variation on covid-19 spread is crucial for future epidemic modelling and management. In this study, seasonal variation in the transmission rate of covid-19, was estimated based on an epidemic population model of covid-19 in Denmark, which included changes in national restrictions and introduction of the α -variant covid-19 strain, in the period March 2020 - March 2021. Seasonal variation was implemented as a logistic temperature dependent scaling of the transmission rate, and parameters for the logistic relationship was estimated through rejection-based approximate bayesian computation (ABC). The likelihoods used in the ABC were based on national hospital admission data and seroprevalence data stratified into nine and two age groups, respectively. The seasonally induced reduction in the transmission rate of covid-19 in Denmark was estimated to be 27 % , (95% CI [ 24 % ; 31 % ]), when moving from peak Winter to peak Summer. The reducing effect of seasonality on transmission rate per + 1 ∘ C in daily average temperature were shown to vary based on temperature, and were estimated to be - 2.2 % [ - 2.8 % ; - 1.7 % ] pr. 1 ∘ C around 2 ∘ C; 2 % [ - 2.3 % ; - 1.7 % ] pr. 1 ∘ C around 7 ∘ C; and 1.7 % [ - 2.0 % ; - 1.5 % ] pr. 1 ∘ C around a daily average temperature of 11 ∘ C.
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Affiliation(s)
- Morten Guldborg Johnsen
- DTU Compute, Technical University of Denmark, Building 324, Richard Petersens Plads, 2800 Kgs. Lyngby, Denmark
| | | | - Kaare Græsbøll
- DTU Compute, Technical University of Denmark, Building 324, Richard Petersens Plads, 2800 Kgs. Lyngby, Denmark
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23
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Wang W, Ji S, Wang J, Liao F. Using a novel two-stage strategy to characterize the spatial distribution of associations between temperature and COVID-19: A case study in the continental United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 850:158003. [PMID: 35970465 PMCID: PMC9373535 DOI: 10.1016/j.scitotenv.2022.158003] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 05/27/2023]
Abstract
BACKGROUND Numerous studies have studied the association between daily average temperature (DAT) and daily COVID-19 confirmed cases, which show considerable heterogeneity, even opposite results, among different regions. Such heterogeneity suggests that characterizing the association on a large area scale would ignore the local variation, even obtain false results in some local regions. So, characterizing the spatial distribution of heterogeneous DAT-COVID-19 associations and exploring the causes plays an important role on making temperature-related region-specific intervention measures and early-warning systems. METHODS Aiming to characterize the spatial distribution of associations between DAT and COVID-19 confirmed cases in the continental United States, we proposed a novel two-stage strategy. In the first stage, we used the common stratified distributed lag nonlinear model to obtain the rough state-specific associations. In the second stage, conditional autoregression was used to spatially smooth the rough estimations. Furtherly, based on the idea, two modified strategies were used to investigate the time-varying associations and the modification effects derived from the vaccination campaign. RESULTS Around one-third of states exhibit no significant association between DAT and daily confirmed COVID-19 cases. Most of the remaining states present a low risk at low DAT and a high risk at high DAT, but several states present opposite associations. The average association curve presents a 'S' shape with positive association between -8 - 18 °C and keeping flat out of the range. An increased vaccination coverage rate will increase the risk when DAT < 12 °C, but slightly affect the risk when DAT > 12 °C. CONCLUSION A considerable spatial heterogeneity of DAT-COVID-19 associations exists in America and the average association curve presents a 'S' shape. The vaccination campaign significantly modifies the association when DAT is low, but only make a slight modification when DAT is high.
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Affiliation(s)
- Wei Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Shuming Ji
- Department of Project Design and Statistics, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Jinyu Wang
- Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu 610072, China; Key Laboratory of psychosomatic medicine, Chinese Academy of Medical Sciences, Chengdu 610072, China
| | - Fang Liao
- Sichuan Provincial Center for Mental Health, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu 610072, China; Key Laboratory of psychosomatic medicine, Chinese Academy of Medical Sciences, Chengdu 610072, China.
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24
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Gushchin VA, Pochtovyi AA, Kustova DD, Ogarkova DA, Tarnovetskii IY, Belyaeva ED, Divisenko EV, Vasilchenko LA, Shidlovskaya EV, Kuznetsova NA, Tkachuk AP, Slutskiy EA, Speshilov GI, Komarov AG, Tsibin AN, Zlobin VI, Logunov DY, Gintsburg AL. Dynamics of SARS-CoV-2 Major Genetic Lineages in Moscow in the Context of Vaccine Prophylaxis. Int J Mol Sci 2022; 23:ijms232314670. [PMID: 36498998 PMCID: PMC9736394 DOI: 10.3390/ijms232314670] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 11/16/2022] [Accepted: 11/20/2022] [Indexed: 11/25/2022] Open
Abstract
Findings collected over two and a half years of the COVID-19 pandemic demonstrated that the level immunity resulting from vaccination and infection is insufficient to stop the circulation of new genetic variants. The short-term decline in morbidity was followed by a steady increase. The early identification of new genetic lineages that will require vaccine adaptation in the future is an important research target. In this study, we summarised data on the variability of genetic line composition throughout the COVID-19 pandemic in Moscow, Russia, and evaluated the virological and epidemiological features of dominant variants in the context of selected vaccine prophylaxes. The prevalence of the Omicron variant highlighted the low effectiveness of the existing immune layer in preventing infection, which points to the necessity of optimising the antigens used in vaccines in Moscow. Logistic growth curves showing the rate at which the new variant displaces the previously dominant variants may serve as early indicators for selecting candidates for updated vaccines, along with estimates of efficacy, reduced viral neutralising activity against the new strains, and viral load in previously vaccinated patients.
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Affiliation(s)
- Vladimir A. Gushchin
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
- Department of Virology, Biological Faculty, Lomonosov Moscow State University, 119991 Moscow, Russia
- Correspondence: (V.A.G.); (A.A.P.)
| | - Andrei A. Pochtovyi
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
- Department of Virology, Biological Faculty, Lomonosov Moscow State University, 119991 Moscow, Russia
- Correspondence: (V.A.G.); (A.A.P.)
| | - Daria D. Kustova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
- Department of Virology, Biological Faculty, Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Darya A. Ogarkova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | | | - Elizaveta D. Belyaeva
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | - Elizaveta V. Divisenko
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | - Lyudmila A. Vasilchenko
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | - Elena V. Shidlovskaya
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | - Nadezhda A. Kuznetsova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | - Artem P. Tkachuk
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | | | | | | | | | - Vladimir I. Zlobin
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | - Denis Y. Logunov
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | - Alexander L. Gintsburg
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia
- Department of Infectiology and Virology, Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov, First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), 119435 Moscow, Russia
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25
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Frisina Doetter L, Frisina PG, Preuß B. Pandemic Meets Endemic: The Role of Social Inequalities and Failing Public Health Policies as Drivers of Disparities in COVID-19 Mortality among White, Black, and Hispanic Communities in the United States of America. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:14961. [PMID: 36429679 PMCID: PMC9690946 DOI: 10.3390/ijerph192214961] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 11/04/2022] [Accepted: 11/08/2022] [Indexed: 06/16/2023]
Abstract
The COVID-19 pandemic placed the United States of America (U.S.) under enormous strain, leaving it with higher deaths during the first wave of the outbreak compared to all other advanced economies. Blacks and Hispanics were among those hardest hit by the virus-a fact attributed to enduring problems related to the social determinants of health adversely affecting Communities of Color (CoC). In this study, we ask which distinct factors relating to policy stringency and community vulnerability influenced COVID-19 mortality among Whites, Blacks, and Hispanics during the first year of the pandemic. To address this question, we utilized a mix of correlational and regression analyses. Findings point to the highly divergent impact of public policy and vulnerability on COVID-19 mortality. Specifically, we observed that state-led measures aimed at controlling the spread of the virus only improved mortality for Whites. However, pre-existing social determinants of health (i.e., population density, epidemiological and healthcare system factors) played a significant role in determining COVID-19 outcomes for CoC, even in the face of stringent containment measures by states. This suggests that state-led policy to address present and/or future public health crises need to account for the particular nature of vulnerability affecting Blacks and Hispanics in the U.S.
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Affiliation(s)
- Lorraine Frisina Doetter
- Collaborative Research Centre (CRC) 1342 & Research Center on Inequality and Social Policy (SOCIUM), The University of Bremen, 28359 Bremen, Germany
| | | | - Benedikt Preuß
- Research Center on Inequality and Social Policy (SOCIUM), The University of Bremen, 28359 Bremen, Germany
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26
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Yuan HY, Liang J, Hossain MP. Impacts of social distancing, rapid antigen test and vaccination on the Omicron outbreak during large temperature variations in Hong Kong: a modelling study. J Infect Public Health 2022; 15:1427-1435. [PMID: 36395667 PMCID: PMC9633629 DOI: 10.1016/j.jiph.2022.10.026] [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: 10/08/2022] [Revised: 10/25/2022] [Accepted: 10/30/2022] [Indexed: 11/06/2022] Open
Abstract
Background The impacts of non-pharmaceutical interventions (NPIs) and vaccine boosters on the transmission of the largest outbreak of COVID-19 (the fifth wave) in Hong Kong have not been reported. The outbreak, dominated by the Omicron BA.2 subvariant, began to spread substantially after the Spring Festival in February, 2022, when the temperature varied greatly (e.g. a cold surge event). Tightening social distancing measures did not succeed in containing the outbreak until later with the use of rapid antigen tests (RAT) and increased vaccination rates. Temperature has been previously found to have significant impact on the transmissibility. Understanding how the public health interventions influence the number of infections in this outbreak provide important insights on prevention and control of COVID-19 during different seasons. Methods We developed a transmission model incorporating stratified immunity with vaccine-induced antibody responses and the daily changes in population mobility, vaccination and weather factors (i.e. temperature and relative humidity). We fitted the model to the daily reported cases detected by either PCR or RAT between 1 February and 31 March using Bayesian statistics, and quantified the effects of individual NPIs, vaccination and weather factors on transmission dynamics. Results Model predicted that, with the vaccine uptake, social distancing reduced the cumulative incidence (CI) from 58.2% to 44.5% on average. The use of RAT further reduced the CI to 39.0%. Without vaccine boosters in these two months, the CI increased to 49.1%. While public health interventions are important in reducing the total infections, the outbreak was temporarily driven by the cold surge. If the coldest two days (8.5 °C and 8.8 °C) in February were replaced by the average temperature in that month (15.2 °C), the CI would reduce from 39.0% to 28.2%. Conclusion Preventing and preparing for the transmission of COVID-19 considering the change in temperature appears to be a cost-effective preventive strategy to lead people to return to normal life.
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Affiliation(s)
- Hsiang-Yu Yuan
- Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong SAR, China,Centre for Applied One Health Research and Policy Advice, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong SAR, China,Corresponding author at: Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong SAR, China
| | - Jingbo Liang
- Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong SAR, China
| | - Md Pear Hossain
- Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong SAR, China
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27
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Anzai A, Jung SM, Nishiura H. Go To Travel campaign and the geographic spread of COVID-19 in Japan. BMC Infect Dis 2022; 22:808. [PMID: 36316657 PMCID: PMC9619015 DOI: 10.1186/s12879-022-07799-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 10/25/2022] [Indexed: 11/26/2022] Open
Abstract
Background In 2020, the Japanese government implemented first of two Go To Travel campaigns to promote the tourism sector as well as eating and drinking establishments, especially in remote areas. The present study aimed to explore the relationship between enhanced travel and geographic propagation of COVID-19 across Japan, focusing on the second campaign with nationwide large-scale economic boost in 2020. Methods We carried out an interrupted time-series analysis to identify the possible cause-outcome relationship between the Go To Travel campaign and the spread of infection to nonurban areas in Japan. Specifically, we counted the number of prefectures that experienced a weekly incidence of three, five, and seven COVID-19 cases or more per 100,000 population, and we compared the rate of change before and after the campaign. Results Three threshold values and three different models identified an increasing number of prefectures above the threshold, indicating that the inter-prefectural spread intensified following the launch of the second Go To Travel campaign from October 1st, 2020. The simplest model that accounted for an increase in the rate of change only provided the best fit. We estimated that 0.24 (95% confidence interval 0.15 to 0.34) additional prefectures newly exceeded five COVID-19 cases per 100,000 population per week during the second campaign. Conclusions The enhanced movement resulting from the Go To Travel campaign facilitated spatial spread of COVID-19 from urban to nonurban locations, where health-care capacity may have been limited. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-022-07799-0.
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Affiliation(s)
- Asami Anzai
- grid.258799.80000 0004 0372 2033Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo-Ku, Kyoto, 606-8501 Japan
| | - Sung-mok Jung
- grid.258799.80000 0004 0372 2033Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo-Ku, Kyoto, 606-8501 Japan
| | - Hiroshi Nishiura
- grid.258799.80000 0004 0372 2033Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo-Ku, Kyoto, 606-8501 Japan
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28
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Frère J, Chatzis O, Cremer K, Merckx J, De Keukeleire M, Renard F, Ribesse N, Minner F, Ruelle J, Kabamba B, Rodriguez-Villalobos H, Bearzatto B, Delforge ML, Henin C, Bureau F, Gillet L, Robert A, Van der Linden D. SARS-CoV-2 Transmission in Belgian French-Speaking Primary Schools: An Epidemiological Pilot Study. Viruses 2022; 14:v14102199. [PMID: 36298754 PMCID: PMC9612207 DOI: 10.3390/v14102199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 09/27/2022] [Accepted: 09/28/2022] [Indexed: 01/25/2023] Open
Abstract
Schools have been a point of attention during the pandemic, and their closure one of the mitigating measures taken. A better understanding of the dynamics of the transmission of SARS-CoV-2 in elementary education is essential to advise decisionmakers. We conducted an uncontrolled non-interventional prospective study in Belgian French-speaking schools to describe the role of attending asymptomatic children and school staff in the spread of COVID-19 and to estimate the transmission to others. Each participant from selected schools was tested for SARS-CoV-2 using a polymerase chain reaction (PCR) analysis on saliva sample, on a weekly basis, during six consecutive visits. In accordance with recommendations in force at the time, symptomatic individuals were excluded from school, but per the study protocol, being that participants were blinded to PCR results, asymptomatic participants were maintained at school. Among 11 selected schools, 932 pupils and 242 school staff were included between January and May 2021. Overall, 6449 saliva samples were collected, of which 44 came back positive. Most positive samples came from isolated cases. We observed that asymptomatic positive children remaining at school did not lead to increasing numbers of cases or clusters. However, we conducted our study during a period of low prevalence in Belgium. It would be interesting to conduct the same analysis during a high prevalence period.
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Affiliation(s)
- Julie Frère
- Pediatric Infectious Diseases, Pediatric Department, CHU Liège, 4000 Liège, Belgium
| | - Olga Chatzis
- Pediatric Infectious Diseases, Specialized Pediatric Service, Pediatric Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
| | - Kelly Cremer
- Department of Epidemiology and Biostatistics, Institut de Recherche Expérimentale et Clinique, Faculty of Public Health, UCLouvain, 1200 Brussels, Belgium
| | - Joanna Merckx
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC H3A 1A2, Canada
| | - Mathilde De Keukeleire
- Department of Epidemiology and Biostatistics, Institut de Recherche Expérimentale et Clinique, Faculty of Public Health, UCLouvain, 1200 Brussels, Belgium
| | - Florence Renard
- Office de la Naissance et de l’Enfance (ONE), 1060 Brussels, Belgium
| | - Nathalie Ribesse
- Office de la Naissance et de l’Enfance (ONE), 1060 Brussels, Belgium
| | - Frédéric Minner
- Immunology-Vaccinology Lab of the Faculty of Veterinary Medicine, ULiège, 4000 Liège, Belgium
| | - Jean Ruelle
- Pôle de Microbiologie Médicale (MBLG), UCLouvain, 1200 Brussels, Belgium
- SmartGene Services, EPFL Innovation Park, 1015 Lausanne, Switzerland
| | - Benoit Kabamba
- Department of Epidemiology and Biostatistics, Institut de Recherche Expérimentale et Clinique, Faculty of Public Health, UCLouvain, 1200 Brussels, Belgium
- Pôle de Microbiologie Médicale (MBLG), UCLouvain, 1200 Brussels, Belgium
| | - Hector Rodriguez-Villalobos
- Department of Epidemiology and Biostatistics, Institut de Recherche Expérimentale et Clinique, Faculty of Public Health, UCLouvain, 1200 Brussels, Belgium
- Department of Microbiology, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
| | - Bertrand Bearzatto
- Institut de Recherche Expérimentale et Clinique (IREC), Center for Applied Molecular Technologies (CTMA), UCLouvain, 1200 Brussels, Belgium
| | - Marie-Luce Delforge
- Institut de Biologie Clinique de l’Université Libre de Bruxelles, 1070 Brussels, Belgium
| | - Coralie Henin
- Federal Testing Platform for COVID-19, Université Libre de Bruxelles, 1070 Brussels, Belgium
| | - Fabrice Bureau
- Immunology-Vaccinology Lab of the Faculty of Veterinary Medicine, ULiège, 4000 Liège, Belgium
| | - Laurent Gillet
- Immunology-Vaccinology Lab of the Faculty of Veterinary Medicine, ULiège, 4000 Liège, Belgium
| | - Annie Robert
- Department of Epidemiology and Biostatistics, Institut de Recherche Expérimentale et Clinique, Faculty of Public Health, UCLouvain, 1200 Brussels, Belgium
| | - Dimitri Van der Linden
- Pediatric Infectious Diseases, Specialized Pediatric Service, Pediatric Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
- Correspondence: ; Tel.: +00-32-2764-1714
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29
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Mercier E, D'Aoust PM, Thakali O, Hegazy N, Jia JJ, Zhang Z, Eid W, Plaza-Diaz J, Kabir MP, Fang W, Cowan A, Stephenson SE, Pisharody L, MacKenzie AE, Graber TE, Wan S, Delatolla R. Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak. Sci Rep 2022; 12:15777. [PMID: 36138059 DOI: 10.1101/2022.06.28.22276884] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/08/2022] [Indexed: 05/27/2023] Open
Abstract
Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.
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Affiliation(s)
- Elisabeth Mercier
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Patrick M D'Aoust
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Ocean Thakali
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Nada Hegazy
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Jian-Jun Jia
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Zhihao Zhang
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Walaa Eid
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Julio Plaza-Diaz
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Md Pervez Kabir
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Wanting Fang
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Aaron Cowan
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Sean E Stephenson
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Lakshmi Pisharody
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Alex E MacKenzie
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Tyson E Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Shen Wan
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada.
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30
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Mercier E, D'Aoust PM, Thakali O, Hegazy N, Jia JJ, Zhang Z, Eid W, Plaza-Diaz J, Kabir MP, Fang W, Cowan A, Stephenson SE, Pisharody L, MacKenzie AE, Graber TE, Wan S, Delatolla R. Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak. Sci Rep 2022; 12:15777. [PMID: 36138059 PMCID: PMC9493155 DOI: 10.1038/s41598-022-20076-z] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/08/2022] [Indexed: 11/22/2022] Open
Abstract
Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.
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Affiliation(s)
- Elisabeth Mercier
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Patrick M D'Aoust
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Ocean Thakali
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Nada Hegazy
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Jian-Jun Jia
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Zhihao Zhang
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Walaa Eid
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Julio Plaza-Diaz
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Md Pervez Kabir
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Wanting Fang
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Aaron Cowan
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Sean E Stephenson
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Lakshmi Pisharody
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Alex E MacKenzie
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Tyson E Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, K1H 8L1, Canada
| | - Shen Wan
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada.
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31
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Lamarca AP, de Almeida LGP, Francisco RDS, Cavalcante L, Brustolini O, Gerber AL, Guimarães APDC, de Oliveira TH, dos Santos Nascimento ÉR, Policarpo C, de Souza IV, de Carvalho EM, Ribeiro MS, Carvalho S, Dias da Silva F, de Oliveira Garcia MH, de Souza LM, Da Silva CG, Ribeiro CLP, Cavalcanti AC, de Mello CMB, Tanuri A, Vasconcelos ATRD. Phylodynamic analysis of SARS-CoV-2 spread in Rio de Janeiro, Brazil, highlights how metropolitan areas act as dispersal hubs for new variants. Microb Genom 2022; 8. [DOI: 10.1099/mgen.0.000859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
During the first semester of 2021, all of Brazil has suffered an intense wave of COVID-19 associated with the Gamma variant. In July, the first cases of Delta variant were detected in the state of Rio de Janeiro. In this work, we have employed phylodynamic methods to analyse more than 1 600 genomic sequences of Delta variant collected until September in Rio de Janeiro to reconstruct how this variant has surpassed Gamma and dispersed throughout the state. After the introduction of Delta, it has initially spread mostly in the homonymous city of Rio de Janeiro, the most populous of the state. In a second stage, dispersal occurred to mid- and long-range cities, which acted as new close-range hubs for spread. We observed that the substitution of Gamma by Delta was possibly caused by its higher viral load, a proxy for transmissibility. This variant turnover prompted a new surge in cases, but with lower lethality than was observed during the peak caused by Gamma. We reason that high vaccination rates in the state of Rio de Janeiro were possibly what prevented a higher number of deaths.
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Affiliation(s)
- Alessandra Pavan Lamarca
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Luiz G. P. de Almeida
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | | | - Liliane Cavalcante
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Otávio Brustolini
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | - Alexandra L. Gerber
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Petrópolis, Brazil
| | | | - Thiago Henrique de Oliveira
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Cintia Policarpo
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | | | - Silvia Carvalho
- Secretaria Estadual de Saúde do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | | | | | | | | | - Andréa Cony Cavalcanti
- Departamento de Virologia, Instituto de Microbiologia Paulo de Góes, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
- Laboratório Central de Saúde Pública Noel Nutels, Rio de Janeiro, Brazil
| | | | - Amilcar Tanuri
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
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32
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Al Huraimel K, Alhosani M, Gopalani H, Kunhabdulla S, Stietiya MH. Elucidating the role of environmental management of forests, air quality, solid waste and wastewater on the dissemination of SARS-CoV-2. HYGIENE AND ENVIRONMENTAL HEALTH ADVANCES 2022; 3:100006. [PMID: 37519421 PMCID: PMC9095661 DOI: 10.1016/j.heha.2022.100006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 04/13/2022] [Accepted: 04/30/2022] [Indexed: 11/29/2022]
Abstract
The increasing frequency of zoonotic diseases is amongst several catastrophic repercussions of inadequate environmental management. Emergence, prevalence, and lethality of zoonotic diseases is intrinsically linked to environmental management which are currently at a destructive level globally. The effects of these links are complicated and interdependent, creating an urgent need of elucidating the role of environmental mismanagement to improve our resilience to future pandemics. This review focused on the pertinent role of forests, outdoor air, indoor air, solid waste and wastewater management in COVID-19 dissemination to analyze the opportunities prevailing to control infectious diseases considering relevant data from previous disease outbreaks. Global forest management is currently detrimental and hotspots of forest fragmentation have demonstrated to result in zoonotic disease emergences. Deforestation is reported to increase susceptibility to COVID-19 due to wildfire induced pollution and loss of forest ecosystem services. Detection of SARS-CoV-2 like viruses in multiple animal species also point to the impacts of biodiversity loss and forest fragmentation in relation to COVID-19. Available literature on air quality and COVID-19 have provided insights into the potential of air pollutants acting as plausible virus carrier and aggravating immune responses and expression of ACE2 receptors. SARS-CoV-2 is detected in outdoor air, indoor air, solid waste, wastewater and shown to prevail on solid surfaces and aerosols for prolonged hours. Furthermore, lack of protection measures and safe disposal options in waste management are evoking concerns especially in underdeveloped countries due to high infectivity of SARS-CoV-2. Inadequate legal framework and non-adherence to environmental regulations were observed to aggravate the postulated risks and vulnerability to future waves of pandemics. Our understanding underlines the urgent need to reinforce the fragile status of global environmental management systems through the development of strict legislative frameworks and enforcement by providing institutional, financial and technical supports.
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Affiliation(s)
- Khaled Al Huraimel
- Division of Consultancy, Research & Innovation (CRI), Sharjah Environment Company - Bee'ah, Sharjah, United Arab Emirates
| | - Mohamed Alhosani
- Division of Consultancy, Research & Innovation (CRI), Sharjah Environment Company - Bee'ah, Sharjah, United Arab Emirates
| | - Hetasha Gopalani
- Division of Consultancy, Research & Innovation (CRI), Sharjah Environment Company - Bee'ah, Sharjah, United Arab Emirates
| | - Shabana Kunhabdulla
- Division of Consultancy, Research & Innovation (CRI), Sharjah Environment Company - Bee'ah, Sharjah, United Arab Emirates
| | - Mohammed Hashem Stietiya
- Division of Consultancy, Research & Innovation (CRI), Sharjah Environment Company - Bee'ah, Sharjah, United Arab Emirates
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33
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Appelberg S, Ahlén G, Yan J, Nikouyan N, Weber S, Larsson O, Höglund U, Aleman S, Weber F, Perlhamre E, Apro J, Gidlund E, Tuvesson O, Salati S, Cadossi M, Tegel H, Hober S, Frelin L, Mirazimi A, Sallberg M. A universal
SARS‐CoV DNA
vaccine inducing highly crossreactive neutralizing antibodies and T cells. EMBO Mol Med 2022; 14:e15821. [PMID: 35986481 PMCID: PMC9538582 DOI: 10.15252/emmm.202215821] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 08/16/2022] [Accepted: 08/17/2022] [Indexed: 11/20/2022] Open
Abstract
New variants in the SARS‐CoV‐2 pandemic are more contagious (Alpha/Delta), evade neutralizing antibodies (Beta), or both (Omicron). This poses a challenge in vaccine development according to WHO. We designed a more universal SARS‐CoV‐2 DNA vaccine containing receptor‐binding domain loops from the huCoV‐19/WH01, the Alpha, and the Beta variants, combined with the membrane and nucleoproteins. The vaccine induced spike antibodies crossreactive between huCoV‐19/WH01, Beta, and Delta spike proteins that neutralized huCoV‐19/WH01, Beta, Delta, and Omicron virus in vitro. The vaccine primed nucleoprotein‐specific T cells, unlike spike‐specific T cells, recognized Bat‐CoV sequences. The vaccine protected mice carrying the human ACE2 receptor against lethal infection with the SARS‐CoV‐2 Beta variant. Interestingly, priming of cross‐reactive nucleoprotein‐specific T cells alone was 60% protective, verifying observations from humans that T cells protect against lethal disease. This SARS‐CoV vaccine induces a uniquely broad and functional immunity that adds to currently used vaccines.
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Affiliation(s)
| | - Gustaf Ahlén
- Department of Laboratory Medicine, Karolinska Institutet Sweden
| | - Jingyi Yan
- Department of Laboratory Medicine, Karolinska Institutet Sweden
| | - Negin Nikouyan
- Department of Laboratory Medicine, Karolinska Institutet Sweden
| | | | | | | | - Soo Aleman
- Department of Infectious Disease Karolinska University Hospital and Department of Medicine Huddinge, Karolinska Institutet Sweden
| | - Friedemann Weber
- Institute for Virology FB10‐Veterinary Medicine, Justus‐Liebing University Giessen Germany
| | - Emma Perlhamre
- Karolinska Trial Alliance Karolinska University Hospital Sweden
| | - Johanna Apro
- Karolinska Trial Alliance Karolinska University Hospital Sweden
| | | | | | | | | | - Hanna Tegel
- Department of Protein Science Royal Institute of Technology Stockholm Sweden
| | - Sophia Hober
- Department of Protein Science Royal Institute of Technology Stockholm Sweden
| | - Lars Frelin
- Department of Laboratory Medicine, Karolinska Institutet Sweden
| | - Ali Mirazimi
- Public Health Agency of Sweden Solna Sweden
- Department of Laboratory Medicine, Karolinska Institutet Sweden
| | - Matti Sallberg
- Department of Laboratory Medicine, Karolinska Institutet Sweden
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Hogerwerf L, Post PM, Bom B, van der Hoek W, van de Kassteele J, Stemerding AM, de Vries W, Houthuijs D. Proximity to livestock farms and COVID-19 in the Netherlands, 2020-2021. Int J Hyg Environ Health 2022; 245:114022. [PMID: 35987164 PMCID: PMC9376334 DOI: 10.1016/j.ijheh.2022.114022] [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: 05/10/2022] [Revised: 07/12/2022] [Accepted: 08/08/2022] [Indexed: 12/01/2022]
Abstract
Objectives In the Netherlands, during the first phase of the COVID-19 epidemic, the hotspot of COVID-19 overlapped with the country's main livestock area, while in subsequent phases this distinct spatial pattern disappeared. Previous studies show that living near livestock farms influence human respiratory health and immunological responses. This study aimed to explore whether proximity to livestock was associated with SARS-CoV-2 infection. Methods The study population was the population of the Netherlands excluding the very strongly urbanised areas and border areas, on January 1, 2019 (12, 628, 244 individuals). The cases are the individuals reported with a laboratory-confirmed positive SARS-CoV-2 test with onset before January 1, 2022 (2, 223, 692 individuals). For each individual, we calculated distance to nearest livestock farm (cattle, goat, sheep, pig, poultry, horse, rabbit, mink). The associations between residential (6-digit postal-code) distance to the nearest livestock farm and individuals' SARS-CoV-2 status was studied with multilevel logistic regression models. Models were adjusted for individuals' age categories, the social status of the postal code area, particulate matter (PM10)- and nitrogen dioxide (NO2)-concentrations. We analysed data for the entire period and population as well as separately for eight time periods (Jan–Mar, Apr–Jun, Jul–Sep and Oct–Dec in 2020 and 2021), four geographic areas of the Netherlands (north, east, west and south), and for five age categories (0–14, 15–24, 25–44, 45–64 and > 65 years). Results Over the period 2020–2021, individuals' SARS-CoV-2 status was associated with living closer to livestock farms. This association increased from an Odds Ratio (OR) of 1.01 (95% Confidence Interval [CI] 1.01–1.02) for patients living at a distance of 751–1000 m to a farm to an OR of 1.04 (95% CI 1.04–1.04), 1.07 (95% CI 1.06–1.07) and 1.11 (95% CI 1.10–1.12) for patients living in the more proximate 501–750 m, 251–500m and 0–250 m zones around farms, all relative to patients living further than 1000 m around farms. This association was observed in three out of four quarters of the year in both 2020 and 2021, and in all studied geographic areas and age groups. Conclusions In this exploratory study with individual SARS-CoV-2 notification data and high-resolution spatial data associations were found between living near livestock farms and individuals' SARS-CoV-2 status in the Netherlands. Verification of the results in other countries is warranted, as well as investigations into possible underlying exposures and mechanisms.
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Affiliation(s)
- Lenny Hogerwerf
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA, Bilthoven, the Netherlands.
| | - Pim M Post
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA, Bilthoven, the Netherlands; Department of Natural Resources, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O Box 217, Enschede, 7500 AE, the Netherlands.
| | - Ben Bom
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA, Bilthoven, the Netherlands.
| | - Wim van der Hoek
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA, Bilthoven, the Netherlands.
| | - Jan van de Kassteele
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA, Bilthoven, the Netherlands.
| | | | - Wilco de Vries
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA, Bilthoven, the Netherlands.
| | - Danny Houthuijs
- National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA, Bilthoven, the Netherlands.
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35
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Smith TP, Stemkovski M, Koontz A, Pearse WD. AREAdata: A worldwide climate dataset averaged across spatial units at different scales through time. Data Brief 2022; 43:108438. [PMID: 35845100 PMCID: PMC9278028 DOI: 10.1016/j.dib.2022.108438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 06/22/2022] [Accepted: 06/27/2022] [Indexed: 10/28/2022] Open
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36
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Menon NG, Mohapatra S. The COVID-19 pandemic: Virus transmission and risk assessment. CURRENT OPINION IN ENVIRONMENTAL SCIENCE & HEALTH 2022; 28:100373. [PMID: 35669052 PMCID: PMC9156429 DOI: 10.1016/j.coesh.2022.100373] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
The coronaviruses are the largest known RNA viruses of which SASR-CoV-2 has been spreading continuously due to its repeated mutation triggered by several environmental factors. Multiple human interventions and lessons learned from the SARS 2002 outbreak helped reduce its spread considerably, and thus, the virus was contained but the emerging mutations burdened the medical facility leading to many deaths in the world. As per the world health organization (WHO) droplet mode transmission is the most common mode of SASR-CoV-2 transmission to which environmental factors including temperature and humidity play a major role. This article highlights the responsibility of environmental causes that would affect the distribution and fate of the virus. Recent development in the risk assessment models is also covered in this article.
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Affiliation(s)
- N Gayathri Menon
- Centre for Research in Nanotechnology and Science (CRNTS), Indian Institute of Technology Bombay, India
| | - Sanjeeb Mohapatra
- NUS Environmental Research Institute, National University of Singapore, 1 Create Way, Create Tower, #15-02, Singapore 138602, Singapore
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37
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Gavenčiak T, Monrad JT, Leech G, Sharma M, Mindermann S, Bhatt S, Brauner J, Kulveit J. Seasonal variation in SARS-CoV-2 transmission in temperate climates: A Bayesian modelling study in 143 European regions. PLoS Comput Biol 2022; 18:e1010435. [PMID: 36026483 PMCID: PMC9455844 DOI: 10.1371/journal.pcbi.1010435] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 09/08/2022] [Accepted: 07/25/2022] [Indexed: 01/02/2023] Open
Abstract
Although seasonal variation has a known influence on the transmission of several respiratory viral infections, its role in SARS-CoV-2 transmission remains unclear. While there is a sizable and growing literature on environmental drivers of COVID-19 transmission, recent reviews have highlighted conflicting and inconclusive findings. This indeterminacy partly owes to the fact that seasonal variation relates to viral transmission by a complicated web of causal pathways, including many interacting biological and behavioural factors. Since analyses of specific factors cannot determine the aggregate strength of seasonal forcing, we sidestep the challenge of disentangling various possible causal paths in favor of a holistic approach. We model seasonality as a sinusoidal variation in transmission and infer a single Bayesian estimate of the overall seasonal effect. By extending two state-of-the-art models of non-pharmaceutical intervention (NPI) effects and their datasets covering 143 regions in temperate Europe, we are able to adjust our estimates for the role of both NPIs and mobility patterns in reducing transmission. We find strong seasonal patterns, consistent with a reduction in the time-varying reproduction number R(t) (the expected number of new infections generated by an infectious individual at time t) of 42.1% (95% CI: 24.7%-53.4%) from the peak of winter to the peak of summer. These results imply that the seasonality of SARS-CoV-2 transmission is comparable in magnitude to the most effective individual NPIs but less than the combined effect of multiple interventions.
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Affiliation(s)
- Tomáš Gavenčiak
- Centre for Theoretical Studies, Charles University, Prague, Czech Republic
| | - Joshua Teperowski Monrad
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
- Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Health Policy, London School of Economics and Political Science, London, United Kingdom
| | - Gavin Leech
- Department of Computer Science, University of Bristol, Bristol, United Kingdom
| | - Mrinank Sharma
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
- Department of Statistics, University of Oxford, Oxford, United Kingdom
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Sören Mindermann
- Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Samir Bhatt
- Faculty of Medicine, School of Public Health, Imperial College London, London, United Kingdom
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Jan Brauner
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
- Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Jan Kulveit
- Centre for Theoretical Studies, Charles University, Prague, Czech Republic
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
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38
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Gavenčiak T, Monrad JT, Leech G, Sharma M, Mindermann S, Bhatt S, Brauner J, Kulveit J. Seasonal variation in SARS-CoV-2 transmission in temperate climates: A Bayesian modelling study in 143 European regions. PLoS Comput Biol 2022; 18:e1010435. [PMID: 36026483 DOI: 10.1101/2021.06.10.21258647] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 09/08/2022] [Accepted: 07/25/2022] [Indexed: 05/22/2023] Open
Abstract
Although seasonal variation has a known influence on the transmission of several respiratory viral infections, its role in SARS-CoV-2 transmission remains unclear. While there is a sizable and growing literature on environmental drivers of COVID-19 transmission, recent reviews have highlighted conflicting and inconclusive findings. This indeterminacy partly owes to the fact that seasonal variation relates to viral transmission by a complicated web of causal pathways, including many interacting biological and behavioural factors. Since analyses of specific factors cannot determine the aggregate strength of seasonal forcing, we sidestep the challenge of disentangling various possible causal paths in favor of a holistic approach. We model seasonality as a sinusoidal variation in transmission and infer a single Bayesian estimate of the overall seasonal effect. By extending two state-of-the-art models of non-pharmaceutical intervention (NPI) effects and their datasets covering 143 regions in temperate Europe, we are able to adjust our estimates for the role of both NPIs and mobility patterns in reducing transmission. We find strong seasonal patterns, consistent with a reduction in the time-varying reproduction number R(t) (the expected number of new infections generated by an infectious individual at time t) of 42.1% (95% CI: 24.7%-53.4%) from the peak of winter to the peak of summer. These results imply that the seasonality of SARS-CoV-2 transmission is comparable in magnitude to the most effective individual NPIs but less than the combined effect of multiple interventions.
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Affiliation(s)
- Tomáš Gavenčiak
- Centre for Theoretical Studies, Charles University, Prague, Czech Republic
| | - Joshua Teperowski Monrad
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
- Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Health Policy, London School of Economics and Political Science, London, United Kingdom
| | - Gavin Leech
- Department of Computer Science, University of Bristol, Bristol, United Kingdom
| | - Mrinank Sharma
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
- Department of Statistics, University of Oxford, Oxford, United Kingdom
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Sören Mindermann
- Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Samir Bhatt
- Faculty of Medicine, School of Public Health, Imperial College London, London, United Kingdom
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Jan Brauner
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
- Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Jan Kulveit
- Centre for Theoretical Studies, Charles University, Prague, Czech Republic
- Future of Humanity Institute, University of Oxford, Oxford, United Kingdom
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Wang K, Ho KF, Leung LYT, Chow KM, Cheung YY, Tsang D, Lai RWM, Xu RH, Yeoh EK, Hung CT. Risk of air and surface contamination of SARS-CoV-2 in isolation wards and its relationship with patient and environmental characteristics. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 241:113740. [PMID: 35687998 PMCID: PMC9167918 DOI: 10.1016/j.ecoenv.2022.113740] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 05/24/2022] [Accepted: 06/01/2022] [Indexed: 05/06/2023]
Abstract
Air and surface contamination of the SARS-CoV-2 have been reported by multiple studies. However, the evidence is limited for the change of environmental contamination of this virus in the surrounding of patients with COVID-19 at different time points during the course of disease and under different conditions of the patients. Therefore, this study aims to understand the risk factors associated with the appearance of SARS-CoV-2 through the period when the patients were staying in the isolation wards. In this study, COVID-19 patients admitted to the isolation wards were followed up for up to 10 days for daily collection of air and surface samples in their surroundings. The positivity rate of the environmental samples at different locations was plotted, and multiple multi-level mixed-effect logistic regressions were used to examine the association between the positivity of environmental samples and their daily health conditions and environmental factors. It found 6.6 % of surface samples (133/2031 samples) and 2.1 % of air samples (22/1075 samples) were positive, and the positivity rate reached to peak during 2-3 days after admission to the ward. The virus was more likely to present at bedrail, patients' personal items and medical equipment, while less likely to be detected in the air outside the range of 2 m from the patients. It also revealed that higher positivity rate is associated with lower environmental temperature, fever and cough at the day of sampling, lower Ct values of latest test for respiratory tract samples, and pre-existing respiratory or cardiovascular conditions. The finding can be used to guide the hospital infection control strategies by identifying high-risk areas and patients. Extra personal hygiene precautions and equipment for continuously environmental disinfection can be used for these high-risk areas and patients to reduce the risk of hospital infection.
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Affiliation(s)
- Kailu Wang
- Centre for Health Systems and Policy Research, JCSPHPC, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China; The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China
| | - Kin-Fai Ho
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China
| | - Larry Yung-Tim Leung
- Centre for Health Systems and Policy Research, JCSPHPC, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China; The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China
| | - Kai-Ming Chow
- Department of Medicine and Therapeutics, Prince of Wales Hospital, Shatin, N.T. 999077, Hong Kong, China
| | - Yuk-Yam Cheung
- Public Health Laboratory Centre, Centre for Health Protection, Kowloon 999077, Hong Kong, China
| | - Dominic Tsang
- Public Health Laboratory Centre, Centre for Health Protection, Kowloon 999077, Hong Kong, China
| | - Raymond Wai-Man Lai
- Department of Microbiology, Prince of Wales Hospital, Shatin, N.T. 999077, Hong Kong, China
| | - Richard Huan Xu
- Department of Rehabilitation Science, Faculty of Health and Social Science, The Hong Kong Polytechnic University, Kowloon 999077, Hong Kong, China
| | - Eng-Kiong Yeoh
- Centre for Health Systems and Policy Research, JCSPHPC, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China; The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China
| | - Chi-Tim Hung
- Centre for Health Systems and Policy Research, JCSPHPC, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China; The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T. 999077, Hong Kong, China.
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40
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Zarębska-Michaluk D, Hu C, Brzdęk M, Flisiak R, Rzymski P. COVID-19 Vaccine Booster Strategies for Omicron SARS-CoV-2 Variant: Effectiveness and Future Prospects. Vaccines (Basel) 2022; 10:vaccines10081223. [PMID: 36016111 PMCID: PMC9412973 DOI: 10.3390/vaccines10081223] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/25/2022] [Accepted: 07/28/2022] [Indexed: 12/05/2022] Open
Abstract
In the light of the lack of authorized COVID-19 vaccines adapted to the Omicron variant lineage, the administration of the first and second booster dose is recommended. It remains important to monitor the efficacy of such an approach in order to inform future preventive strategies. The present paper summarizes the research progress on the effectiveness of the first and second booster doses of COVID-19. It also discusses the potential approach in vaccination strategies that could be undertaken to maintain high levels of protection during the waves of SARS-CoV-2 infections. Although this approach can be based, with some shortcomings, on the first-generation vaccines, other vaccination strategies should be explored, including developing multiple antigen-based (multivariant-adapted) booster doses with enhanced durability of immune protection, e.g., through optimization of the half-life of generated antibodies.
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Affiliation(s)
- Dorota Zarębska-Michaluk
- Department of Infectious Diseases, Jan Kochanowski University, 25-369 Kielce, Poland; (D.Z.-M.); (M.B.)
| | - Chenlin Hu
- College of Pharmacy, University of Houston, Houston, TX 77204, USA;
| | - Michał Brzdęk
- Department of Infectious Diseases, Jan Kochanowski University, 25-369 Kielce, Poland; (D.Z.-M.); (M.B.)
| | - Robert Flisiak
- Department of Infectious Diseases and Hepatology, Medical University of Białystok, 15-540 Białystok, Poland;
| | - Piotr Rzymski
- Department of Environmental Medicine, Poznan University of Medical Sciences, 60-806 Poznan, Poland
- Integrated Science Association (ISA), Universal Scientific Education and Research Network (USERN), 60-806 Poznań, Poland
- Correspondence:
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Hayashi K, Kayano T, Anzai A, Fujimoto M, Linton N, Sasanami M, Suzuki A, Kobayashi T, Otani K, Yamauchi M, Suzuki M, Nishiura H. Assessing Public Health and Social Measures Against COVID-19 in Japan From March to June 2021. Front Med (Lausanne) 2022; 9:937732. [PMID: 35903315 PMCID: PMC9315273 DOI: 10.3389/fmed.2022.937732] [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: 05/06/2022] [Accepted: 06/13/2022] [Indexed: 11/13/2022] Open
Abstract
Background Public health and social measures (PHSM) against COVID-19 in Japan involve requesting the public to voluntarily reduce social contact; these measures are not legally binding. The effectiveness of such PHSM has been questioned with emergence of the SARS-CoV-2 Alpha variant (B.1.1.7), which exhibited elevated transmissibility. Materials and Methods We investigated the epidemic dynamics during the fourth epidemic wave in Japan from March to June 2021 involving pre-emergency measures and declaration of a state of emergency (SoE). We estimated the effective reproduction number (Rt) before and after these interventions, and then analyzed the relationship between lower Rt values and each PHSM. Results With implementation of pre-emergency measures (PEM) in 16 prefectures, the Rt was estimated to be < 1 in six prefectures; its average relative reduction ranged from 2 to 19%. During the SoE, 8 of 10 prefectures had an estimated Rt < 1, and the average relative reduction was 26%–39%. No single intervention was identified that uniquely resulted in an Rt value < 1. Conclusion An SoE can substantially reduce the Rt and may be required to curb a surge in cases caused by future SARS-CoV-2 variants of concern with elevated transmissibility. More customized interventions did not reduce the Rt value to < 1 in this study, but that may be partly attributable to the greater transmissibility of the Alpha variant.
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Affiliation(s)
| | - Taishi Kayano
- School of Public Health, Kyoto University, Kyoto, Japan
| | - Asami Anzai
- School of Public Health, Kyoto University, Kyoto, Japan
| | | | | | | | - Ayako Suzuki
- School of Public Health, Kyoto University, Kyoto, Japan
| | | | - Kanako Otani
- National Institute of Infectious Diseases, Tokyo, Japan
| | | | - Motoi Suzuki
- National Institute of Infectious Diseases, Tokyo, Japan
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Redder C. How ventilation behaviour contributes to seasonality in airborne disease transmission. GMS HYGIENE AND INFECTION CONTROL 2022; 17:Doc11. [PMID: 35909652 PMCID: PMC9285111 DOI: 10.3205/dgkh000414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
User behaviour for natural ventilation is known to be strongly corelated to outdoor temperatures. In areas of moderate climate, this leads to an increased fresh air supply in summer, which reduces the exposure level towards airborne pathogens. Modelling of numerous random exposure situations in household, school and various settings, based on the long-term climate data from Berlin, showed that this effect is likely to contribute significantly to the overall seasonality of airborne diseases.
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Affiliation(s)
- Christian Redder
- Delbag GmbH, Herne, Germany,*To whom correspondence should be addressed: Christian Redder, Delbag GmbH, Shamrockring 1, 44623 Herne, Germany, Phone: +49 2323 1476 021, E-mail:
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43
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Bukha KK, Sharif EA, Eldaghayes IM. The One Health concept for the threat of severe acute respiratory syndrome coronavirus-2 to marine ecosystems. INTERNATIONAL JOURNAL OF ONE HEALTH 2022. [DOI: 10.14202/ijoh.2022.48-57] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global health threat. This virus is the causative agent for coronavirus disease 2019 (COVID-19). Pandemic prevention is best addressed through an integrated One Health (OH) approach. Understanding zoonotic pathogen fatality and spillover from wildlife to humans are effective for controlling and preventing zoonotic outbreaks. The OH concept depends on the interface of humans, animals, and their environment. Collaboration among veterinary medicine, public health workers and clinicians, and veterinary public health is necessary for rapid response to emerging zoonotic pathogens. SARS-CoV-2 affects aquatic environments, primarily through untreated sewage. Patients with COVID-19 discharge the virus in urine and feces into residential wastewater. Thus, marine organisms may be infected with SARS-CoV-2 by the subsequent discharge of partially treated or untreated wastewater to marine waters. Viral loads can be monitored in sewage and surface waters. Furthermore, shellfish are vulnerable to SARS-CoV-2 infection. Filter-feeding organisms might be monitored to protect consumers. Finally, the stability of SARS-CoV-2 to various environmental factors aids in viral studies. This article highlights the presence and survival of SARS-CoV-2 in the marine environment and its potential to enter marine ecosystems through wastewater. Furthermore, the OH approach is discussed for improving readiness for successive outbreaks. This review analyzes information from public health and epidemiological monitoring tools to control COVID-19 transmission.
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Affiliation(s)
- Khawla K. Bukha
- Department of Poultry and Fish Diseases, Faculty of Veterinary Medicine, University of Tripoli, Tripoli, Libya
| | - Ehab A. Sharif
- Department of Poultry and Fish Diseases, Faculty of Veterinary Medicine, University of Tripoli, Tripoli, Libya
| | - Ibrahim M. Eldaghayes
- Department of Microbiology and Parasitology, Faculty of Veterinary Medicine, University of Tripoli, Tripoli, Libya
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Necesito IV, Velasco JMS, Jung J, Bae YH, Yoo Y, Kim S, Kim HS. Predicting COVID-19 Cases in South Korea Using Stringency and Niño Sea Surface Temperature Indices. Front Public Health 2022; 10:871354. [PMID: 35719622 PMCID: PMC9204014 DOI: 10.3389/fpubh.2022.871354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
Most coronavirus disease 2019 (COVID-19) models use a combination of agent-based and equation-based models with only a few incorporating environmental factors in their prediction models. Many studies have shown that human and environmental factors play huge roles in disease transmission and spread, but few have combined the use of both factors, especially for SARS-CoV-2. In this study, both man-made policies (Stringency Index) and environment variables (Niño SST Index) were combined to predict the number of COVID-19 cases in South Korea. The performance indicators showed satisfactory results in modeling COVID-19 cases using the Non-linear Autoregressive Exogenous Model (NARX) as the modeling method, and Stringency Index (SI) and Niño Sea Surface Temperature (SST) as model variables. In this study, we showed that the accuracy of SARS-CoV-2 transmission forecasts may be further improved by incorporating both the Niño SST and SI variables and combining these variables with NARX may outperform other models. Future forecasting work by modelers should consider including climate or environmental variables (i.e., Niño SST) to enhance the prediction of transmission and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
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Affiliation(s)
- Imee V. Necesito
- Department of Civil Engineering, Inha University, Incheon, South Korea
- *Correspondence: Imee V. Necesito
| | - John Mark S. Velasco
- Department of Clinical Epidemiology, College of Medicine, University of the Philippines, Manila, Philippines
- Institute of Molecular Biology and Biotechnology, National Institutes of Health, University of the Philippines, Manila, Philippines
| | - Jaewon Jung
- Department of Hydro Science and Engineering Research, Korea Institute of Civil Engineering and Building Technology, Gyeonggi-do, South Korea
| | - Young Hye Bae
- Department of Civil Engineering, Inha University, Incheon, South Korea
| | - Younghoon Yoo
- Department of Civil Engineering, Inha University, Incheon, South Korea
| | - Soojun Kim
- Department of Civil Engineering, Inha University, Incheon, South Korea
| | - Hung Soo Kim
- Department of Civil Engineering, Inha University, Incheon, South Korea
- Hung Soo Kim
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45
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Asif Z, Chen Z, Stranges S, Zhao X, Sadiq R, Olea-Popelka F, Peng C, Haghighat F, Yu T. Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review. SUSTAINABLE CITIES AND SOCIETY 2022; 81:103840. [PMID: 35317188 PMCID: PMC8925199 DOI: 10.1016/j.scs.2022.103840] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 03/10/2022] [Accepted: 03/12/2022] [Indexed: 05/05/2023]
Abstract
COVID-19 is deemed as the most critical world health calamity of the 21st century, leading to dramatic life loss. There is a pressing need to understand the multi-stage dynamics, including transmission routes of the virus and environmental conditions due to the possibility of multiple waves of COVID-19 in the future. In this paper, a systematic examination of the literature is conducted associating the virus-laden-aerosol and transmission of these microparticles into the multimedia environment, including built environments. Particularly, this paper provides a critical review of state-of-the-art modelling tools apt for COVID-19 spread and transmission pathways. GIS-based, risk-based, and artificial intelligence-based tools are discussed for their application in the surveillance and forecasting of COVID-19. Primary environmental factors that act as simulators for the spread of the virus include meteorological variation, low air quality, pollen abundance, and spatial-temporal variation. However, the influence of these environmental factors on COVID-19 spread is still equivocal because of other non-pharmaceutical factors. The limitations of different modelling methods suggest the need for a multidisciplinary approach, including the 'One-Health' concept. Extended One-Health-based decision tools would assist policymakers in making informed decisions such as social gatherings, indoor environment improvement, and COVID-19 risk mitigation by adapting the control measurements.
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Affiliation(s)
- Zunaira Asif
- Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada
| | - Zhi Chen
- Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada
| | - Saverio Stranges
- Department of Epidemiology and Biostatistics, Western University, Ontario, Canada
- Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Xin Zhao
- Department of Animal Science, McGill University, Montreal, Canada
| | - Rehan Sadiq
- School of Engineering (Okanagan Campus), University of British Columbia, Kelowna, BC, Canada
| | | | - Changhui Peng
- Department of Biological Sciences, University of Quebec in Montreal, Canada
| | - Fariborz Haghighat
- Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada
| | - Tong Yu
- Department of Civil and Environmental Engineering, University of Alberta, Canada
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Klein B, Generous N, Chinazzi M, Bhadricha Z, Gunashekar R, Kori P, Li B, McCabe S, Green J, Lazer D, Marsicano CR, Scarpino SV, Vespignani A. Higher education responses to COVID-19 in the United States: Evidence for the impacts of university policy. PLOS DIGITAL HEALTH 2022; 1:e0000065. [PMID: 36812533 PMCID: PMC9931316 DOI: 10.1371/journal.pdig.0000065] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 05/18/2022] [Indexed: 11/19/2022]
Abstract
With a dataset of testing and case counts from over 1,400 institutions of higher education (IHEs) in the United States, we analyze the number of infections and deaths from SARS-CoV-2 in the counties surrounding these IHEs during the Fall 2020 semester (August to December, 2020). We find that counties with IHEs that remained primarily online experienced fewer cases and deaths during the Fall 2020 semester; whereas before and after the semester, these two groups had almost identical COVID-19 incidence. Additionally, we see fewer cases and deaths in counties with IHEs that reported conducting any on-campus testing compared to those that reported none. To perform these two comparisons, we used a matching procedure designed to create well-balanced groups of counties that are aligned as much as possible along age, race, income, population, and urban/rural categories-demographic variables that have been shown to be correlated with COVID-19 outcomes. We conclude with a case study of IHEs in Massachusetts-a state with especially high detail in our dataset-which further highlights the importance of IHE-affiliated testing for the broader community. The results in this work suggest that campus testing can itself be thought of as a mitigation policy and that allocating additional resources to IHEs to support efforts to regularly test students and staff would be beneficial to mitigating the spread of COVID-19 in a pre-vaccine environment.
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Affiliation(s)
- Brennan Klein
- Network Science Institute, Northeastern University, Boston, United States of America
- Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, Massachusetts, United States of America
| | - Nicholas Generous
- Network Science Institute, Northeastern University, Boston, United States of America
- Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, Massachusetts, United States of America
- Biosecurity and Public Health Group, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Matteo Chinazzi
- Network Science Institute, Northeastern University, Boston, United States of America
- Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, Massachusetts, United States of America
| | - Zarana Bhadricha
- Network Science Institute, Northeastern University, Boston, United States of America
- College of Engineering, Northeastern University, Boston, Massachusetts, United States of America
| | - Rishab Gunashekar
- Network Science Institute, Northeastern University, Boston, United States of America
- College of Engineering, Northeastern University, Boston, Massachusetts, United States of America
| | - Preeti Kori
- Network Science Institute, Northeastern University, Boston, United States of America
- College of Engineering, Northeastern University, Boston, Massachusetts, United States of America
| | - Bodian Li
- Network Science Institute, Northeastern University, Boston, United States of America
- College of Professional Studies, Northeastern University, Boston, Massachusetts, United States of America
| | - Stefan McCabe
- Network Science Institute, Northeastern University, Boston, United States of America
| | - Jon Green
- Network Science Institute, Northeastern University, Boston, United States of America
- Shorenstein Center on Media, Politics and Public Policy, Harvard University, Massachusetts, Boston, United States of America
| | - David Lazer
- Network Science Institute, Northeastern University, Boston, United States of America
| | - Christopher R. Marsicano
- Educational Studies Department, Davidson College, Davidson, North Carolina, United States of America
- College Crisis Initiative, Davidson College, Davidson, North Carolina, United States of America
| | - Samuel V. Scarpino
- Network Science Institute, Northeastern University, Boston, United States of America
- Vermont Complex Systems Center, University of Vermont, Burlington, Vermont, United States of America
- Santa Fe Institute, Santa Fe, United States of America
| | - Alessandro Vespignani
- Network Science Institute, Northeastern University, Boston, United States of America
- Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, Massachusetts, United States of America
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Inaida S, Paul RE, Matsuno S. Viral transmissibility of SARS-CoV-2 accelerates in the winter, similarly to influenza epidemics. Am J Infect Control 2022; 50:1070-1076. [PMID: 35605752 PMCID: PMC9121648 DOI: 10.1016/j.ajic.2022.05.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 05/09/2022] [Accepted: 05/13/2022] [Indexed: 02/06/2023]
Abstract
The transmissibility of SARS-CoV-2 is anticipated to increase in the winter because of increased viral survival in cold damp air and thus would exacerbate viral spread in community. Analysis to capture the seasonal trend is needed to be prepared for future epidemics. We compared regression models for the 5-week case prior to each epidemic peak week for both the COVID-19 and influenza epidemics in winter and summer. The weekly case increase ratio was compared, using non-paired t tests between seasons. In order to test the robustness of seasonal transmission patterns, the normalized weekly case numbers of COVID-19 and influenza case rates of all seasons were assessed in a combined quadratic regression analysis. In winter, the weekly case increase ratio accelerated before epidemic peaks, similarly, for both COVID-19 and influenza. The quadratic regression models of weekly cases were observed to be convex curves in the winter and concave curves in the spring/summer for both COVID-19 and influenza. A significant increase of case increase ratio (3.19 [95%CI:0.01-6.37, P = .049]) of the COVID-19 and influenza epidemics was observed in winter as compared to spring/summer before the epidemic peak. The epidemic of COVID-19 was found to mirror that of influenza, suggesting a strong underlying seasonal transmissibility. Influenza epidemics can potentially be a useful reference for the COVID-19 epidemics.
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What Is the Impact of Early and Subsequent Epidemic Characteristics on the Pre-delta COVID-19 Epidemic Size in the United States? Pathogens 2022; 11:pathogens11050576. [PMID: 35631097 PMCID: PMC9147779 DOI: 10.3390/pathogens11050576] [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: 04/06/2022] [Revised: 05/06/2022] [Accepted: 05/11/2022] [Indexed: 11/29/2022] Open
Abstract
It is still uncertain how the epidemic characteristics of COVID-19 in its early phase and subsequent waves contributed to the pre-delta epidemic size in the United States. We identified the early and subsequent characteristics of the COVID-19 epidemic and the correlation between these characteristics and the pre-delta epidemic size. Most (96.1% (49/51)) of the states entered a fast-growing phase before the accumulative number of cases reached (30). The days required for the number of confirmed cases to increase from 30 to 100 was 5.6 (5.1−6.1) days. As of 31 March 2021, all 51 states experienced at least 2 waves of COVID-19 outbreaks, 23.5% (12/51) experienced 3 waves, and 15.7% (8/51) experienced 4 waves, the epidemic size of COVID-19 was 19,275−3,669,048 cases across the states. The pre-delta epidemic size was significantly correlated with the duration from 30 to 100 cases (p = 0.003, r = −0.405), the growth rate of the fast-growing phase (p = 0.012, r = 0.351), and the peak cases in the subsequent waves (K1 (p < 0.001, r = 0.794), K2 (p < 0.001, r = 0.595), K3 (p < 0.001, r = 0.977), and K4 (p = 0.002, r = 0.905)). We observed that both early and subsequent epidemic characteristics contribute to the pre-delta epidemic size of COVID-19. This identification is important to the prediction of the emerging viral infectious diseases in the primary stage.
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Banholzer N, Feuerriegel S, Vach W. Estimating and explaining cross-country variation in the effectiveness of non-pharmaceutical interventions during COVID-19. Sci Rep 2022; 12:7526. [PMID: 35534516 PMCID: PMC9085796 DOI: 10.1038/s41598-022-11362-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 04/22/2022] [Indexed: 12/15/2022] Open
Abstract
To control the COVID-19 pandemic, countries around the world have implemented non-pharmaceutical interventions (NPIs), such as school closures or stay-at-home orders. Previous work has estimated the effectiveness of NPIs, yet without examining variation in NPI effectiveness across countries. Based on data from the first epidemic wave of \documentclass[12pt]{minimal}
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\begin{document}$$n=40$$\end{document}n=40 countries, we estimate country-specific differences in the effectiveness of NPIs via a semi-mechanistic Bayesian hierarchical model. Our estimates reveal substantial variation between countries, indicating that NPIs have been more effective in some countries (e. g. Switzerland, New Zealand, and Iceland) as compared to others (e. g. Singapore, South Africa, and France). We then explain differences in the effectiveness of NPIs through 12 country characteristics (e. g. population age, urbanization, employment, etc.). A positive association with country-specific effectiveness of NPIs was found for government effectiveness, gross domestic product (GDP) per capita, population ages 65+, and health expenditures. Conversely, a negative association with effectiveness of NPIs was found for the share of informal employment, average household size and population density. Overall, the wealth and demographic structure of a country can explain variation in the effectiveness of NPIs.
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50
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D'Amico F, Marmiere M, Righetti B, Scquizzato T, Zangrillo A, Puglisi R, Landoni G. COVID-19 seasonality in temperate countries. ENVIRONMENTAL RESEARCH 2022; 206:112614. [PMID: 34953888 PMCID: PMC8692239 DOI: 10.1016/j.envres.2021.112614] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 12/19/2021] [Accepted: 12/20/2021] [Indexed: 05/14/2023]
Abstract
INTRODUCTION While the beneficial effect of vaccination, restrictive measures, and social distancing in reducing mortality due to SARS-CoV-2 is intuitive and taken for granted, seasonality (predictable fluctuation or pattern that recurs or repeats over a one-year period) is still poorly understood and insufficiently taken into consideration. We aimed to examine SARS-CoV-2 seasonality in countries with temperate climate. METHODS We identified countries with temperate climate and extracted average country temperature data from the National Center for Environmental information and from the Climate Change Knowledge Portal. We obtained mortality and vaccination rates from an open access database. We used the stringency index derived from the Oxford COVID-19 Government Response Tracker to quantify restriction policies. We used Spearman's and rank-correlation non-parametric test coefficients to investigate the association between COVID-19 mortality and temperature values. We employed multivariate regression models to analyze how containment measures, vaccinations, and monthly temperatures affected COVID-19 mortality rates. RESULTS The time series for daily deaths per million inhabitants and average monthly temperatures of European countries and US states with a temperate climate had a negative correlation (p < 0.0001 for all countries, 0.40 < R < 0.86). When running multivariate regression models with country fixed effects, we noted that mortality rates were significantly lower when temperature were higher. Interestingly, when adding an interaction term between monthly temperatures and vaccination rates, we found that as monthly temperatures dropped, the effect of the vaccination campaign on mortality was larger than at higher temperatures. DISCUSSION Deaths attributed to SARS-CoV-2 decreased during the summer period in temperate countries. We found that the effect of vaccination rates on mortality was stronger when temperatures were lower. Stakeholders should consider seasonality in managing SARS-CoV-2 and future pandemics to minimize mortality, limit the pressure on hospitals and intensive care units while maintaining economic and social activities.
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Affiliation(s)
- Filippo D'Amico
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Marilena Marmiere
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Beatrice Righetti
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Tommaso Scquizzato
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy; Faculty of Medicine, Vita-Salute San Raffaele University, Milan, Italy
| | - Alberto Zangrillo
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy; Faculty of Medicine, Vita-Salute San Raffaele University, Milan, Italy
| | - Riccardo Puglisi
- Department of Social and Political Sciences, Università Degli Studi Di Pavia, Pavia, Italy
| | - Giovanni Landoni
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy; Faculty of Medicine, Vita-Salute San Raffaele University, Milan, Italy.
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