1
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Zhang GH, Zhu QH, Zhang L, Li L, Fu J, Wang SL, Yuan WL, He L, Tao GH. Bio-based ionic liquid filter with enhanced electrostatic attraction for outside filtration and inside collection of viral aerosols. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133480. [PMID: 38219589 DOI: 10.1016/j.jhazmat.2024.133480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 12/26/2023] [Accepted: 01/07/2024] [Indexed: 01/16/2024]
Abstract
Hazardous biological pathogens in the air pose a significant public environmental health concern as infected individuals emit virus-laden aerosols (VLAs) during routine respiratory activities. Mask-wearing is a key preventive measure, but conventional filtration methods face challenges, particularly in high humidity conditions, where electrostatic charge decline increases the risk of infection. This study introduces a bio-based air filter comprising glycine ionic liquids (GILs) and malleable polymer composite (GILP) with high polarity and functional group density, which are wrapped around a melamine-formaldehyde (MF) resin skeleton, forming a conductive, porous GIL functionized ionic network air filter (GILP@MF). When subjected to low voltage, the GILP@MF composite efficiently captures VLAs including nanoscale virus particles through the enhanced electrostatic attraction, especially in facing high humidity bioaerosols exhaled by human body. The filtration/collection efficiency and quality factor can reach 98.3% and 0.264 Pa-1 at 0.1 m s-1, respectively. This innovative filter provides effective VLA protection and offers potential for non-invasive respiratory virus sampling, advancing medical diagnosis efforts.
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Affiliation(s)
- Guo-Hao Zhang
- College of Chemistry, Sichuan University, Chengdu 610064, China; School of National Defence Science and Technology, Southwest University of Science and Technology, Mianyang 621010, China
| | - Qiu-Hong Zhu
- College of Chemistry, Sichuan University, Chengdu 610064, China; School of National Defence Science and Technology, Southwest University of Science and Technology, Mianyang 621010, China
| | - Lei Zhang
- College of Chemistry, Sichuan University, Chengdu 610064, China
| | - Lei Li
- MGI Tech. Co., Ltd., Shenzhen 518083, China
| | - Jie Fu
- College of Chemistry, Sichuan University, Chengdu 610064, China
| | | | - Wen-Li Yuan
- College of Chemistry, Sichuan University, Chengdu 610064, China
| | - Ling He
- College of Chemistry, Sichuan University, Chengdu 610064, China.
| | - Guo-Hong Tao
- College of Chemistry, Sichuan University, Chengdu 610064, China.
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2
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Svenson O, Isohanni F, Salo I, Lindholm T. Airborne SARS-CoV2 virus exposure, interpersonal distance, face mask and perceived risk of infection. Sci Rep 2024; 14:2285. [PMID: 38280918 PMCID: PMC10821858 DOI: 10.1038/s41598-024-52711-2] [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: 12/29/2022] [Accepted: 01/23/2024] [Indexed: 01/29/2024] Open
Abstract
Participants judged the risk of an infection during a face to face conversation at different interpersonal distances from a SARS-CoV-2 infected person who wore a face mask or not, and in the same questionnaire answered questions about Corona related issues. Keeping a distance to an infected person serves as a protective measure against an infection. When an infected person moves closer, risk of infection increases. Participants were aware of this fact, but underestimated the rate at which the risk of infection increases when getting closer to an infected person, e.g., from 1.5 to 0.5 m (perceived risk increase = 3.33 times higher, objective = 9.00 times higher). This is alarming because it means that people can take risks of infection that they are not aware of or want to take, when they approach another possibly virus infected person. Correspondingly, when an infected person moves away the speed of risk decrease was underestimated, meaning that people are not aware of how much safer they will be if they move away from an infected person. The perceived risk reducing effects of a face mask were approximately correct. Judgments of infection risk at different interpersonal distances (with or without a mask) were unrelated to how often a person used a mask, avoided others or canceled meetings during the COVID-19 pandemic. Greater worry in general and in particular over COVID-19, correlated positively with more protective behavior during the pandemic, but not with judgments of infection risk at different interpersonal distances. Participants with higher scores on a cognitive numeracy test judged mask efficiency more correctly, and women were more worried and risk avoiding than men. The results have implications for understanding behavior in a pandemic, and are relevant for risk communications about the steep increase in risk when approaching a person who may be infected with an airborne virus.
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Affiliation(s)
- Ola Svenson
- Department of Psychology, Stockholm University, Stockholm, Sweden.
- Decision Research, Eugene, OR, USA.
| | - Freja Isohanni
- Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Ilkka Salo
- Department of Psychology, Lund University, Lund, Sweden
| | - Torun Lindholm
- Department of Psychology, Stockholm University, Stockholm, Sweden
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3
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Zhu R, Yu ZY, Han L. Insights on the possibility of SARS-CoV-2 transmission through the eyes. Int J Ophthalmol 2022; 15:1857-1863. [PMID: 36404966 PMCID: PMC9631193 DOI: 10.18240/ijo.2022.11.18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Accepted: 08/26/2022] [Indexed: 12/12/2022] Open
Abstract
A novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or 2019-nCOV), causing coronavirus disease 2019 (COVID-19), has rapidly spread to most countries and regions worldwide since it broke out at the end of 2019. Epidemic of the virus produces a tremendous pressure on the global health systems. With progressive insight into SARS-CoV-2, the role of eye tissue has attracted wide attention in the spread of COVID-19. Whether SARS-CoV-2 can enter the human body through eyes and cause infection? The fact that unprotected exposure of the eyes to 2019-nCoV might have allowed the virus to infect the body implies that 2019-nCOV can invade eye tissue and set foot in organism. Facing the severe challenge of preventing spread of the COVID-19, combined with the high-risk environment of ophthalmology, it is crucial to investigate ocular tropism of coronavirus. This paper explores the possibility of coronavirus transmission through the eye from aspects of probable mechanisms, clinical cases, detection of coronavirus; and puts forward precautions for ophthalmologists and nurses. Consequently, this review reveals our understanding of ocular tropism of coronavirus and contributes to determining risk of ocular transmission, raising awareness of necessary eye protection among medical workers and reducing further prevalence of SARS-CoV-2.
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Affiliation(s)
- Rui Zhu
- Department of Ophthalmology, the Fourth Affiliated Hospital of China Medical University, Shenyang 110005, Liaoning Province, China,Eye Hospital of China Medical University, Shenyang 110005, Liaoning Province, China,Key Lens Research Laboratory of Liaoning Province, Shenyang 110005, Liaoning Province, China,China Medical University, Shenyang 110122, Liaoning Province, China
| | - Zi-Yan Yu
- Department of Ophthalmology, the Fourth Affiliated Hospital of China Medical University, Shenyang 110005, Liaoning Province, China,Eye Hospital of China Medical University, Shenyang 110005, Liaoning Province, China,Key Lens Research Laboratory of Liaoning Province, Shenyang 110005, Liaoning Province, China
| | - Lin Han
- Department of Ophthalmology, the Fourth Affiliated Hospital of China Medical University, Shenyang 110005, Liaoning Province, China,Eye Hospital of China Medical University, Shenyang 110005, Liaoning Province, China,Key Lens Research Laboratory of Liaoning Province, Shenyang 110005, Liaoning Province, China
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4
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Tang SGH, Hadi MHH, Arsad SR, Ker PJ, Ramanathan S, Afandi NAM, Afzal MM, Yaw MW, Krishnan PS, Chen CP, Tiong SK. Prerequisite for COVID-19 Prediction: A Review on Factors Affecting the Infection Rate. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:12997. [PMID: 36293576 PMCID: PMC9602751 DOI: 10.3390/ijerph192012997] [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: 08/22/2022] [Revised: 09/24/2022] [Accepted: 09/29/2022] [Indexed: 06/16/2023]
Abstract
Since the year 2020, coronavirus disease 2019 (COVID-19) has emerged as the dominant topic of discussion in the public and research domains. Intensive research has been carried out on several aspects of COVID-19, including vaccines, its transmission mechanism, detection of COVID-19 infection, and its infection rate and factors. The awareness of the public related to the COVID-19 infection factors enables the public to adhere to the standard operating procedures, while a full elucidation on the correlation of different factors to the infection rate facilitates effective measures to minimize the risk of COVID-19 infection by policy makers and enforcers. Hence, this paper aims to provide a comprehensive and analytical review of different factors affecting the COVID-19 infection rate. Furthermore, this review analyses factors which directly and indirectly affect the COVID-19 infection risk, such as physical distance, ventilation, face masks, meteorological factor, socioeconomic factor, vaccination, host factor, SARS-CoV-2 variants, and the availability of COVID-19 testing. Critical analysis was performed for the different factors by providing quantitative and qualitative studies. Lastly, the challenges of correlating each infection risk factor to the predicted risk of COVID-19 infection are discussed, and recommendations for further research works and interventions are outlined.
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Affiliation(s)
- Shirley Gee Hoon Tang
- Center for Toxicology and Health Risk Studies (CORE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, Kuala Lumpur 50300, Malaysia
| | - Muhamad Haziq Hasnul Hadi
- Institute of Sustainable Energy, Department of Electrical & Electronics, Universiti Tenaga Nasional, Kajang 43000, Malaysia
| | - Siti Rosilah Arsad
- Institute of Sustainable Energy, Department of Electrical & Electronics, Universiti Tenaga Nasional, Kajang 43000, Malaysia
| | - Pin Jern Ker
- Institute of Sustainable Energy, Department of Electrical & Electronics, Universiti Tenaga Nasional, Kajang 43000, Malaysia
| | - Santhi Ramanathan
- Faculty of Business, Multimedia University, Jalan Ayer Keroh Lama, Malacca 75450, Malaysia
| | - Nayli Aliah Mohd Afandi
- Institute of Sustainable Energy, Department of Electrical & Electronics, Universiti Tenaga Nasional, Kajang 43000, Malaysia
| | - Madihah Mohd Afzal
- Center for Toxicology and Health Risk Studies (CORE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, Kuala Lumpur 50300, Malaysia
| | - Mei Wyin Yaw
- Institute of Sustainable Energy, Department of Electrical & Electronics, Universiti Tenaga Nasional, Kajang 43000, Malaysia
| | - Prajindra Sankar Krishnan
- Institute of Sustainable Energy, Department of Electrical & Electronics, Universiti Tenaga Nasional, Kajang 43000, Malaysia
| | - Chai Phing Chen
- Institute of Sustainable Energy, Department of Electrical & Electronics, Universiti Tenaga Nasional, Kajang 43000, Malaysia
| | - Sieh Kiong Tiong
- Institute of Sustainable Energy, Department of Electrical & Electronics, Universiti Tenaga Nasional, Kajang 43000, Malaysia
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5
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Bobrin V, Chen SPR, Grandes Reyes CF, Smith T, Purcell DFJ, Armstrong J, McAuley JL, Monteiro MJ. Surface Inactivation of Highly Mutated SARS-CoV-2 Variants of Concern: Alpha, Delta, and Omicron. Biomacromolecules 2022; 23:3960-3967. [PMID: 35994316 PMCID: PMC9454278 DOI: 10.1021/acs.biomac.2c00801] [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: 06/27/2022] [Revised: 08/04/2022] [Indexed: 11/28/2022]
Abstract
Continued SARS-CoV-2 transmission among the human population has meant the evolution of the virus to produce variants of increased infectiousness and virulence, coined variants of concern (VOCs). The last wave of pandemic infections was driven predominantly by the delta VOC, but because of continued transmission and adaptive mutations, the more highly transmissible omicron variant emerged and is now dominant. However, due to waning immunity and emergence of new variants, vaccines alone cannot control the pandemic. The application of an antiviral coating to high-touch surfaces and physical barriers such as masks are an effective means to inactivate the virus and their spread. Here, we demonstrate an environmentally friendly water-borne polymer coating that can completely inactivate SARS-CoV-2 independent of the infectious variant. The polymer was designed to target the highly glycosylated spike protein on the virion surface and inactivate the virion by disruption of the viral membrane through a nano-mechanical process. Our findings show that, even with low amounts of coating on the surface (1 g/m2), inactivation of alpha, delta, and omicron VOCs and degradation of their viral genome were complete. Furthermore, our data shows that the polymer induces little to no skin sensitization in mice and is non-toxic upon oral ingestion in rats. We anticipate that our transparent polymer coating can be applied to face masks and many other surfaces to capture and inactivate the virus, aiding in the reduction of SARS-CoV-2 transmission and evolution of new variants of concern.
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Affiliation(s)
- Valentin
A. Bobrin
- Australian
Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Sung-Po R. Chen
- Australian
Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD 4072, Australia
| | | | - Tim Smith
- Department
of Microbiology and Immunology, The University
of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne 3000, Australia
| | - Damian F. J. Purcell
- Department
of Microbiology and Immunology, The University
of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne 3000, Australia
| | - Jason Armstrong
- Boeing
Research and Technology Australia, Level 2, Hawken building (50), Staff House Rd, Brisbane, QLD 4072, Australia
| | - Julie L. McAuley
- Department
of Microbiology and Immunology, The University
of Melbourne at the Peter Doherty Institute for Infection and Immunity, Melbourne 3000, Australia
| | - Michael J. Monteiro
- Australian
Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD 4072, Australia
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6
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Hamill V, Noll L, Lu N, Tsui WNT, Porter EP, Gray M, Sebhatu T, Goerl K, Brown S, Palinski R, Thomason S, Almes K, Retallick J, Bai J. Molecular detection of SARS-CoV-2 strains and differentiation of Delta variant strains. Transbound Emerg Dis 2022; 69:2879-2889. [PMID: 34964565 PMCID: PMC9240106 DOI: 10.1111/tbed.14443] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 12/03/2021] [Accepted: 12/22/2021] [Indexed: 12/20/2022]
Abstract
The Delta variant of SARS-CoV-2 has now become the predominant strain in the global COVID-19 pandemic. Strain coverage of some detection assays developed during the early pandemic stages has declined due to periodic mutations in the viral genome. We have developed a real-time RT-PCR (RT-qPCR) for SARS-CoV-2 detection that provides nearly 100% strain coverage, and differentiation of highly transmissible Delta variant strains. All full or nearly full (≥28 kb) SARS-CoV-2 genomes (n = 403,812), including 6422 Delta and 280 Omicron variant strains, were collected from public databases at the time of analysis and used for assay design. The two amino acid deletions in the spike gene (S-gene, Δ156-157) that is characteristic of the Delta variant were targeted during the assay design. Although strain coverage for the Delta variant was very high (99.7%), detection coverage for non-Delta wild-type strains was 93.9%, mainly due to the confined region of design. To increase strain coverage of the assay, the design for CDC N1 target was added to the assay. In silico analysis of 403,812 genomes indicated a 95.4% strain coverage for the CDC N1 target, however, in combination with our new non-Delta S-gene target, total coverage for non-Delta wild-type strains increased to 99.8%. A human 18S rRNA gene was also analyzed and used as an internal control. The final four-plex RT-qPCR assay generated PCR amplification efficiencies between 95.4% and 102.0% with correlation coefficients (R2 ) of >0.99 for cloned positive controls; Delta and non-Delta human clinical samples generated PCR efficiencies of 93.4%-97.0% and R2 > 0.99. The assay also detects 98.6% of 280 Omicron sequences. Assay primers and probes have no match to other closely related human coronaviruses, and did not produce a signal from samples positive to selected animal coronaviruses. Genotypes of selected clinical samples identified by the RT-qPCR were confirmed by Sanger sequencing.
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Affiliation(s)
- Vaughn Hamill
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Lance Noll
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
- Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, United States
| | - Nanyan Lu
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
- Division of Biology, Kansas State University, Manhattan, KS 66506, United States
| | - Wai Ning Tiffany Tsui
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Elizabeth Poulsen Porter
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Mark Gray
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Tesfaalem Sebhatu
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Kyle Goerl
- Lafene Health Center, Kansas State University, Manhattan, KS 66506, United States
| | - Susan Brown
- Division of Biology, Kansas State University, Manhattan, KS 66506, United States
| | - Rachel Palinski
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
- Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, United States
| | - Sasha Thomason
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
- Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, United States
| | - Kelli Almes
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
- Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, United States
| | - Jamie Retallick
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
- Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, United States
| | - Jianfa Bai
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
- Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, United States
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7
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von Wintersdorff CJH, Dingemans J, van Alphen LB, Wolffs PFG, van der Veer BMJW, Hoebe CJPA, Savelkoul PHM. Infections with the SARS-CoV-2 Delta variant exhibit fourfold increased viral loads in the upper airways compared to Alpha or non-variants of concern. Sci Rep 2022; 12:13922. [PMID: 35978025 PMCID: PMC9382600 DOI: 10.1038/s41598-022-18279-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/09/2022] [Indexed: 12/29/2022] Open
Abstract
There has been a growing body of evidence that the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant (B.1.617.2) shows enhanced transmissibility and increased viral loads compared to other variants. A recent study has even suggested that respiratory samples from people infected with the Delta variant can harbor up to 1000 times higher viral loads compared to samples with variants that are more closely related to the original Wuhan strain, although the sample size of this study (n = 125) was very limited. Here, we have compared the viral load in 16,185 samples that were obtained in periods during which non-VOC, the Alpha (B.1.1.7) or Delta variant (B.1.617.2) were dominant as evidenced by genomic surveillance. We found that the Delta variant contained about fourfold higher viral loads across all age groups compared to the non-VOC or Alpha variants, which is significantly lower than reported earlier. Interestingly, the increased viral load for the Delta variant seemed to be age-dependent, regardless of sex, as the viral load was about 14-fold higher for Delta compared to the non-VOC or Alpha variant in age group 0–20 years and fourfold higher in age group 21–40 years, while there was no difference in viral load between variants in age groups 41–60 and 61+ years, most likely as a consequence of a higher degree of vaccination in the older age groups.
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Affiliation(s)
- Christian J H von Wintersdorff
- Department of Medical Microbiology, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+ (MUMC+), P. Debyelaan 25, 6229 HX, Maastricht, The Netherlands
| | - Jozef Dingemans
- Department of Medical Microbiology, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+ (MUMC+), P. Debyelaan 25, 6229 HX, Maastricht, The Netherlands.
| | - Lieke B van Alphen
- Department of Medical Microbiology, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+ (MUMC+), P. Debyelaan 25, 6229 HX, Maastricht, The Netherlands
| | - Petra F G Wolffs
- Department of Medical Microbiology, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+ (MUMC+), P. Debyelaan 25, 6229 HX, Maastricht, The Netherlands
| | - Brian M J W van der Veer
- Department of Medical Microbiology, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+ (MUMC+), P. Debyelaan 25, 6229 HX, Maastricht, The Netherlands
| | - Christian J P A Hoebe
- Department of Sexual Health, Infectious Diseases and Environment, South Limburg Public Health Service, Heerlen, The Netherlands
| | - Paul H M Savelkoul
- Department of Medical Microbiology, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+ (MUMC+), P. Debyelaan 25, 6229 HX, Maastricht, The Netherlands
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8
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Mao Y, Luo Y, Zhang W, Ding P, Li X, Deng F, Xu K, Hou M, Ding C, Wang Y, Dong Z, MacIntyre R, Yao X, Tang S, Xu D. Independent and Interactive Effects of Environmental Conditions on Aerosolized Surrogate SARS-CoV-2 - Beijing, China, June to September 2020. China CDC Wkly 2022; 4:565-569. [PMID: 35919454 PMCID: PMC9339358 DOI: 10.46234/ccdcw2022.123] [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: 05/06/2022] [Accepted: 06/16/2022] [Indexed: 12/03/2022] Open
Abstract
What is already known about this topic? Environmental factors such as temperature and humidity play important roles in the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via droplets/aerosols. What is added by this report? Higher relative humidity (61%–80%), longer spreading time (120 min), and greater dispersal distance (1 m) significantly reduced SARS-CoV-2 pseudovirus loads. There was an interaction effect between relative humidity and spreading time. What are the implications for public health practice? The findings contribute to our understanding of the impact of environmental factors on the transmission of SARS-CoV-2 via airborne droplets/aerosols.
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Affiliation(s)
- Yixin Mao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yueyun Luo
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenda Zhang
- University of South Carolina, Columbia, SC, USA
| | - Pei Ding
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xia Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Fuchang Deng
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 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, China
| | - Min Hou
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Cheng Ding
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Youbin Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhaomin Dong
- School of Space and Environment, Beihang University, Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China
| | - Raina MacIntyre
- The Kirby Institute, Faculty of Medicine, The University of New South Wales, Sydney, NSW, Australia
| | - Xiaoyuan Yao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Song Tang
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Dongqun Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
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9
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Ortega MA, García-Montero C, Fraile-Martinez O, Colet P, Baizhaxynova A, Mukhtarova K, Alvarez-Mon M, Kanatova K, Asúnsolo A, Sarría-Santamera A. Recapping the Features of SARS-CoV-2 and Its Main Variants: Status and Future Paths. J Pers Med 2022; 12:995. [PMID: 35743779 PMCID: PMC9225183 DOI: 10.3390/jpm12060995] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/06/2022] [Accepted: 06/16/2022] [Indexed: 12/14/2022] Open
Abstract
Over the two years that we have been experiencing the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic, our challenges have been the race to develop vaccines and the difficulties in fighting against new variants due to the rapid ability of the virus to evolve. In this sense, different organizations have identified and classified the different variants that have been emerging, distinguishing between variants of concern (VOC), variants of interest (VOI), or variants under monitoring (VUM). The following review aims to describe the latest updates focusing on VOC and already de-escalated variants, as well as to describe the impact these have had on the global situation. Understanding the intrinsic properties of SARS-CoV-2 and its interaction with the immune system and vaccination is essential to make out the underlying mechanisms that have led to the appearance of these variants, helping to determine the next steps for better public management of this pandemic.
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Affiliation(s)
- Miguel A. Ortega
- Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcala de Henares, Spain; (M.A.O.); (C.G.-M.); (O.F.-M.); (M.A.-M.)
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain
| | - Cielo García-Montero
- Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcala de Henares, Spain; (M.A.O.); (C.G.-M.); (O.F.-M.); (M.A.-M.)
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain
| | - Oscar Fraile-Martinez
- Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcala de Henares, Spain; (M.A.O.); (C.G.-M.); (O.F.-M.); (M.A.-M.)
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain
| | - Paolo Colet
- Department of Medicine, Nazarbayev University School of Medicine, Nur-Sultan 010000, Kazakhstan; (P.C.); (A.B.); (K.M.); (K.K.)
| | - Ardak Baizhaxynova
- Department of Medicine, Nazarbayev University School of Medicine, Nur-Sultan 010000, Kazakhstan; (P.C.); (A.B.); (K.M.); (K.K.)
| | - Kymbat Mukhtarova
- Department of Medicine, Nazarbayev University School of Medicine, Nur-Sultan 010000, Kazakhstan; (P.C.); (A.B.); (K.M.); (K.K.)
| | - Melchor Alvarez-Mon
- Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcala de Henares, Spain; (M.A.O.); (C.G.-M.); (O.F.-M.); (M.A.-M.)
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain
- Immune System Diseases-Rheumatology, Oncology Service an Internal Medicine (CIBEREHD), University Hospital Príncipe de Asturias, 28806 Alcala de Henares, Spain
| | - Kaznagul Kanatova
- Department of Medicine, Nazarbayev University School of Medicine, Nur-Sultan 010000, Kazakhstan; (P.C.); (A.B.); (K.M.); (K.K.)
| | - Angel Asúnsolo
- Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain
- Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcala de Henares, Spain
| | - Antonio Sarría-Santamera
- Department of Medicine, Nazarbayev University School of Medicine, Nur-Sultan 010000, Kazakhstan; (P.C.); (A.B.); (K.M.); (K.K.)
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10
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Wei Y, Dong Z, Fan W, Xu K, Tang S, Wang Y, Wu F. A narrative review on the role of temperature and humidity in COVID-19: Transmission, persistence, and epidemiological evidence. ECO-ENVIRONMENT & HEALTH (ONLINE) 2022; 1:73-85. [PMID: 38013745 PMCID: PMC9181277 DOI: 10.1016/j.eehl.2022.04.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 03/30/2022] [Accepted: 04/28/2022] [Indexed: 12/11/2022]
Abstract
Since December 2019, the 2019 coronavirus disease (COVID-19) outbreak has become a global pandemic. Understanding the role of environmental conditions is important in impeding the spread of COVID-19. Given that airborne spread and contact transmission are considered the main pathways for the spread of COVID-19, this narrative review first summarized the role of temperature and humidity in the airborne trajectory of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Meanwhile, we reviewed the persistence of the virus in aerosols and on inert surfaces and summarized how the persistence of SARS-CoV-2 is affected by temperature and humidity. We also examined the existing epidemiological evidence and addressed the limitations of these epidemiological studies. Although uncertainty remains, more evidence may support the idea that high temperature is slightly and negatively associated with COVID-19 growth, while the conclusion for humidity is still conflicting. Nonetheless, the spread of COVID-19 appears to have been controlled primarily by government interventions rather than environmental factors.
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Affiliation(s)
- Yuan Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Zhaomin Dong
- School of Space and Environment, Beihang University, Beijing 102206, China
| | - Wenhong Fan
- School of Space and Environment, Beihang University, Beijing 102206, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100083, 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
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Ying Wang
- School of Space and Environment, Beihang University, Beijing 102206, China
| | - Fengchang Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
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11
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Jiao J, Shi L, Chen H, Wang X, Yang M, Yang J, Liu M, Yi X, Sun G. Containment strategy during the COVID-19 pandemic among three Asian low and middle-income countries. J Glob Health 2022; 12:05016. [PMID: 35596570 PMCID: PMC9123341 DOI: 10.7189/jogh.12.05016] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Background COVID-19 has not been effectively controlled, seriously threatening people’s health and socioeconomic development. This study aims to summarise the successful experiences and lessons in containment strategy learned from Asian Low- and Middle-Income Countries (LMICs) during the COVID-19 pandemic and analyse the effectiveness of their measures to provide lessons for LMICs in general. Methods This is a retrospective study on the effectiveness of China, India, and Vietnam’s containment strategies. The objective was to assess the effectiveness of measures taken for COVID-19 and provide lessons for wider LMICs in controlling and preventing the COVID-19 pandemic. Results As of June 16, 2021, the Indian epidemic was in the declining part of the rebound stage, with a total of 21 521.900 cases per million and 276.740 deaths per million – both the highest among the three countries. Entering the normalised prevention and control stage, China stably remained at a total of 63. 615 cases per million and 3.211 deaths per million. Vietnam's number of new cases per million was very low in the first stage and almost stagnant except for cluster epidemics. In May 2021, the number of new cases per million started to rapidly increase, but the total of deaths per million was at the low level of 0.627. Conclusions A high attention to epidemics at early stages, strict border control measures, and synchronization of government and population on COVID-19 prevention and control opinions and behaviours play important roles in designing containment strategies. In addition, rapid close contact tracing and large-scale nucleic testing are good options for response to cluster epidemics.
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Affiliation(s)
- Jun Jiao
- Department of Health Management, School of Health Management, Southern Medical University, Guangzhou, Guangdong, China
| | - Leiyu Shi
- Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - Haiqian Chen
- Department of Health Management, School of Health Management, Southern Medical University, Guangzhou, Guangdong, China
| | - Xiaohan Wang
- Department of Health Management, School of Health Management, Southern Medical University, Guangzhou, Guangdong, China
| | - Manfei Yang
- Department of Health Management, School of Health Management, Southern Medical University, Guangzhou, Guangdong, China
| | - Junyan Yang
- Department of Health Management, School of Health Management, Southern Medical University, Guangzhou, Guangdong, China
| | - Meiheng Liu
- Department of Health Management, School of Health Management, Southern Medical University, Guangzhou, Guangdong, China
| | - Xianchun Yi
- Yichun Hospital of Traditional Chinese Medicine, Yichun, Jiangxi, China
| | - Gang Sun
- Department of Health Management, School of Health Management, Southern Medical University, Guangzhou, Guangdong, China.,Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
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12
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Wassenaar TM, Wanchai V, Buzard G, Ussery DW. The first three waves of the Covid-19 pandemic hint at a limited genetic repertoire for SARS-CoV-2. FEMS Microbiol Rev 2022; 46:fuac003. [PMID: 35076068 PMCID: PMC9075578 DOI: 10.1093/femsre/fuac003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/17/2021] [Accepted: 01/13/2022] [Indexed: 11/22/2022] Open
Abstract
The genomic diversity of SARS-CoV-2 is the result of a relatively low level of spontaneous mutations introduced during viral replication. With millions of SARS-CoV-2 genome sequences now available, we can begin to assess the overall genetic repertoire of this virus. We find that during 2020, there was a global wave of one variant that went largely unnoticed, possibly because its members were divided over several sublineages (B.1.177 and sublineages B.1.177.XX). We collectively call this Janus, and it was eventually replaced by the Alpha (B.1.1.7) variant of concern (VoC), next replaced by Delta (B.1.617.2), which itself might soon be replaced by a fourth pandemic wave consisting of Omicron (B.1.1.529). We observe that splitting up and redefining variant lineages over time, as was the case with Janus and is now happening with Alpha, Delta and Omicron, is not helpful to describe the epidemic waves spreading globally. Only ∼5% of the 30 000 nucleotides of the SARS-CoV-2 genome are found to be variable. We conclude that a fourth wave of the pandemic with the Omicron variant might not be that different from other VoCs, and that we may already have the tools in hand to effectively deal with this new VoC.
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Affiliation(s)
- Trudy M Wassenaar
- Molecular Microbiology and Genomics Consultants, Tannenstrasse 7, 55576 Zotzenheim, Germany
| | - Visanu Wanchai
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR 772205, USA
| | | | - David W Ussery
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR 772205, USA
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13
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Comparison of CO-RADS Scores Based on Visual and Artificial Intelligence Assessments in a Non-Endemic Area. Diagnostics (Basel) 2022; 12:diagnostics12030738. [PMID: 35328290 PMCID: PMC8946998 DOI: 10.3390/diagnostics12030738] [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: 01/26/2022] [Revised: 03/08/2022] [Accepted: 03/11/2022] [Indexed: 11/17/2022] Open
Abstract
In this study, we first developed an artificial intelligence (AI)-based algorithm for classifying chest computed tomography (CT) images using the coronavirus disease 2019 Reporting and Data System (CO-RADS). Subsequently, we evaluated its accuracy by comparing the calculated scores with those assigned by radiologists with varying levels of experience. This study included patients with suspected SARS-CoV-2 infection who underwent chest CT imaging between February and October 2020 in Japan, a non-endemic area. For each chest CT, the CO-RADS scores, determined by consensus among three experienced chest radiologists, were used as the gold standard. Images from 412 patients were used to train the model, whereas images from 83 patients were tested to obtain AI-based CO-RADS scores for each image. Six independent raters (one medical student, two residents, and three board-certified radiologists) evaluated the test images. Intraclass correlation coefficients (ICC) and weighted kappa values were calculated to determine the inter-rater agreement with the gold standard. The mean ICC and weighted kappa were 0.754 and 0.752 for the medical student and residents (taken together), 0.851 and 0.850 for the diagnostic radiologists, and 0.913 and 0.912 for AI, respectively. The CO-RADS scores calculated using our AI-based algorithm were comparable to those assigned by radiologists, indicating the accuracy and high reproducibility of our model. Our study findings would enable accurate reading, particularly in areas where radiologists are unavailable, and contribute to improvements in patient management and workflow.
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14
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Lau Z, Griffiths IM, English A, Kaouri K. Predicting the spatio-temporal infection risk in indoor spaces using an efficient airborne transmission model. Proc Math Phys Eng Sci 2022; 478:20210383. [PMID: 35310953 PMCID: PMC8924953 DOI: 10.1098/rspa.2021.0383] [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: 05/11/2021] [Accepted: 02/14/2022] [Indexed: 12/19/2022] Open
Abstract
We develop a spatially dependent generalization to the Wells–Riley model, which determines the infection risk due to airborne transmission of viruses. We assume that the infectious aerosol concentration is governed by an advection–diffusion–reaction equation with the aerosols advected by airflow, diffused due to turbulence, emitted by infected people, and removed due to ventilation, inactivation of the virus and gravitational settling. We consider one asymptomatic or presymptomatic infectious person breathing or talking, with or without a mask, and model a quasi-three-dimensional set-up that incorporates a recirculating air-conditioning flow. We derive a semi-analytic solution that enables fast simulations and compare our predictions to three real-life case studies—a courtroom, a restaurant, and a hospital ward—demonstrating good agreement. We then generate predictions for the concentration and the infection risk in a classroom, for four different ventilation settings. We quantify the significant reduction in the concentration and the infection risk as ventilation improves, and derive appropriate power laws. The model can be easily updated for different parameter values and can be used to make predictions on the expected time taken to become infected, for any location, emission rate, and ventilation level. The results have direct applicability in mitigating the spread of the COVID-19 pandemic.
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Affiliation(s)
- Zechariah Lau
- School of Mathematics, Cardiff University, CF24 4AG Cardiff, UK.,Mathematical Institute, University of Oxford, OX1 6GG Oxford, UK
| | - Ian M Griffiths
- Mathematical Institute, University of Oxford, OX1 6GG Oxford, UK
| | - Aaron English
- School of Mathematics, Cardiff University, CF24 4AG Cardiff, UK.,Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, M13 9PL Manchester, UK
| | - Katerina Kaouri
- School of Mathematics, Cardiff University, CF24 4AG Cardiff, UK
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15
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Tsui WNT, Hamill V, Noll L, Lu N, Porter EP, Harbidge D, Cox E, Richardson C, Gray M, Sebhatu T, Goerl K, Brown S, Hanzlicek G, Retallick J, Bai J. Molecular detverection of SARS-CoV-2 and differentiation of Omicron and Delta variant strains. Transbound Emerg Dis 2022; 69:e1618-e1631. [PMID: 35218683 PMCID: PMC9115370 DOI: 10.1111/tbed.14497] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 02/23/2022] [Accepted: 02/24/2022] [Indexed: 12/04/2022]
Abstract
The SARS‐CoV‐2 virus is the causative agent of COVID‐19 and has undergone continuous mutations throughout the pandemic. The more transmissible Omicron variant has quickly spread and is replacing the Delta variant as the most prevalent strain globally, including in the United States. A new molecular assay that can detect and differentiate both the Delta and Omicron variants was developed. A collection of 660,035 SARS‐CoV‐2 full‐ or near‐full genomes, including 169,454 Delta variant and 24,202 Omicron variant strains, were used for primer and probe designs. In silico data analysis predicted an assay coverage of >99% of all strains, including >99% of the Delta and >99% of Omicron strains. The Omicron variant differential test was designed based on the Δ31‐33 aa deletion in the N‐gene, which is present in the original B.1.1.529 main genotype, BA.1, as well as in BA.2 and BA.3 subtypes. Therefore, the assay should detect the majority of all Omicron variant strains. Standard curves generated with human clinical samples indicated that the PCR amplification efficiencies were 104%, 90.7% and 90.4% for the Omicron, Delta, and non‐Delta/non‐Omicron wild‐type genotypes, respectively. Correlation coefficients of the standard curves were all >0.99. The detection limit of the assay was 14.3, 32.0, and 21.5 copies per PCR reaction for Omicron, Delta, and wild‐type genotypes, respectively. The assay was designed to specifically detect SAR‐CoV‐2 strains. Selected samples with Omicron, Delta and wild‐type genotypes identified by the RT‐qPCR assay were also confirmed by sequencing. The assay did not detect any animal coronavirus‐positive samples that were tested. Human nasal swab samples that previously tested positive (n = 182) or negative (n = 42) for SARS‐CoV‐2 by the ThermoFisher TaqPath COVID‐19 Combo Kit, produced the same result with the new assay. Among positive samples, 55.5% (101/182), 23.1% (42/182), and 21.4% (39/182) were identified as Omicron, Delta, and non‐Omicron/non‐Delta wild‐type genotypes, respectively.
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Affiliation(s)
- Wai Ning Tiffany Tsui
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Vaughn Hamill
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Lance Noll
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States.,Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, United States
| | - Nanyan Lu
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States.,Division of Biology, Kansas State University, Manhattan, KS 66506, United States
| | - Elizabeth Poulsen Porter
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Donald Harbidge
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Emily Cox
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Claire Richardson
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Mark Gray
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Tesfaalem Sebhatu
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States
| | - Kyle Goerl
- Lafene Health Center, Kansas State University, Manhattan, KS 66506, United States
| | - Susan Brown
- Division of Biology, Kansas State University, Manhattan, KS 66506, United States
| | - Gregg Hanzlicek
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States.,Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, United States
| | - Jamie Retallick
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States.,Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, United States
| | - Jianfa Bai
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS 66506, United States.,Department of Diagnostic Medicine/Pathobiology, Kansas State University, Manhattan, KS 66506, United States
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16
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Smallwood N, Harrex W, Rees M, Willis K, Bennett CM. COVID-19 infection and the broader impacts of the pandemic on healthcare workers. Respirology 2022; 27:411-426. [PMID: 35048469 DOI: 10.1111/resp.14208] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 12/05/2021] [Accepted: 12/12/2021] [Indexed: 12/14/2022]
Abstract
The severe acute respiratory syndrome coronavirus (SARS-CoV-2) disease or COVID-19 pandemic is associated with more than 230 million cases and has challenged healthcare systems globally. Many healthcare workers (HCWs) have acquired the infection, often through their workplace, with a significant number dying. The epidemiology of COVID-19 infection in HCWs continues to be explored, with manifold exposure risks identified, leading to COVID-19 being recognised as an occupational disease for HCWs. The physical illness due to COVID-19 in HCWs is similar to the general population, with some HCWs experiencing a long-term illness, which may impact their ability to return to work. HCWs have also been affected by the immense workplace and psychosocial disruption caused by the pandemic. The impacts on the psychological well-being of HCWs globally have been profound, with high prevalence estimates for mental health symptoms, including emotional exhaustion. Globally, governments, healthcare organisations and employers have key responsibilities, including: to be better prepared for crises with comprehensive disaster response management plans, and to protect and preserve the health workforce from the physical and psychological impacts of the pandemic. While prioritising HCWs in vaccine rollouts globally has been critical, managing exposures and outbreaks occurring in healthcare settings remains challenging and continues to lead to substantial disruption to the health workforce. Safeguarding healthcare workforces during crises is critical as we move forward on the new path of 'COVID normal'.
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Affiliation(s)
- Natasha Smallwood
- Department of Respiratory Medicine, The Alfred Hospital, Prahran, Victoria, Australia.,Department of Allergy, Immunology and Respiratory Medicine, Central Clinical School, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia
| | - Warren Harrex
- Consultant Occupational & Environmental Physician, Woden, Australian Capital Territory, Australia
| | - Megan Rees
- Department of Respiratory and Sleep Disorders Medicine, The Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Medicine, RMH, Faculty of Medicine, Dentistry and Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Karen Willis
- Public Health, College of Health and Biomedicine, Victoria University, Melbourne, Victoria, Australia.,Division of Critical Care and Investigative Services, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Catherine M Bennett
- Institute for Health Transformation, Deakin University, Burwood, Victoria, Australia
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17
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Lee BU. A high attack rate of 90% of SARS-CoV-2 Delta variant infections in crew personnel on a single navy ship. J Travel Med 2021; 28:6404468. [PMID: 34668534 DOI: 10.1093/jtm/taab168] [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: 09/13/2021] [Revised: 09/27/2021] [Accepted: 10/12/2021] [Indexed: 11/14/2022]
Abstract
A total of 272 soldiers out of the 301 soldiers (90.4%) were infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant of concern (VOC) on a single navy ship. This outbreak provides three lessons for the pandemic. This incident clearly demonstrates the transmission characteristics of the SARS-CoV-2 Delta VOC.
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Affiliation(s)
- Byung Uk Lee
- Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea
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18
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Correction: Lee, B.U. Minimum Sizes of Respiratory Particles Carrying SARS-CoV-2 and the Possibility of Aerosol Generation. Int. J. Environ. Res. Public Health 2020, 17, 6960. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182211738. [PMID: 34832025 PMCID: PMC8622922 DOI: 10.3390/ijerph182211738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 10/28/2021] [Indexed: 11/21/2022]
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