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Haowei Y, Mahyuddin N, Bin Nik Ghazali NN, Wang Z, Liu Y, Pan S, Badruddin IA. A critical review of research methodologies for COVID-19 transmission in indoor built environment. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024:1-65. [PMID: 38385569 DOI: 10.1080/09603123.2024.2308731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 01/17/2024] [Indexed: 02/23/2024]
Abstract
The Coronavirus Disease 2019 (COVID-19) has caused massive losses for the global economy. Scholars have used different methods to study the transmission mode and influencing factors of the virus to find effective methods to provide people with a healthy built environment. However, these studies arrived at different or even contradictory conclusions. This review presents the main research methodologies utilized in this field, summarizes the main investigation methods, and critically discusses their related conclusions. Data statistical analysis, sample collection, simulation models, and replication transmission scenarios are the main research methods. The summarized conclusion for prevention from all reviewed papers are: adequate ventilation and proper location of return air vents, proper use of personal protective equipment, as well as the reasonable and strict enforcement of policies are the main methods for reducing the transmission. Recommendations including standardized databases, causation clarification, rigorous experiment design, improved simulation accuracy and verification are provided.
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Affiliation(s)
- Yu Haowei
- Centre for Building, Construction & Tropical Architecture (BuCTA), Faculty of Built Environment, University of Malaya, Kuala Lumpur, Malaysia
| | - Norhayati Mahyuddin
- Centre for Building, Construction & Tropical Architecture (BuCTA), Faculty of Built Environment, University of Malaya, Kuala Lumpur, Malaysia
| | - Nik Nazri Bin Nik Ghazali
- Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia
| | - Zeyu Wang
- China Nuclear Power Engineering Co. Ltd, Beijing Institute of Nuclear Engineering, Beijing, China
| | - Yiqiao Liu
- Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia
| | - Song Pan
- Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, China
- Key Laboratory for Comprehensive Energy Saving of Cold Regions Architecture of Ministry of Education, Jilin Jianzhu University, Changchun, PR China
| | - Irfan Anjum Badruddin
- Mechanical Engineering Department, College of Engineering, King Khalid University, Abha, Saudi Arabia
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2
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Pahlow S, Richard-Lacroix M, Hornung F, Köse-Vogel N, Mayerhöfer TG, Hniopek J, Ryabchykov O, Bocklitz T, Weber K, Ehricht R, Löffler B, Deinhardt-Emmer S, Popp J. Simple, Fast and Convenient Magnetic Bead-Based Sample Preparation for Detecting Viruses via Raman-Spectroscopy. BIOSENSORS 2023; 13:594. [PMID: 37366959 DOI: 10.3390/bios13060594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/22/2023] [Accepted: 05/26/2023] [Indexed: 06/28/2023]
Abstract
We introduce a magnetic bead-based sample preparation scheme for enabling the Raman spectroscopic differentiation of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)-positive and -negative samples. The beads were functionalized with the angiotensin-converting enzyme 2 (ACE2) receptor protein, which is used as a recognition element to selectively enrich SARS-CoV-2 on the surface of the magnetic beads. The subsequent Raman measurements directly enable discriminating SARS-CoV-2-positive and -negative samples. The proposed approach is also applicable for other virus species when the specific recognition element is exchanged. A series of Raman spectra were measured on three types of samples, namely SARS-CoV-2, Influenza A H1N1 virus and a negative control. For each sample type, eight independent replicates were considered. All of the spectra are dominated by the magnetic bead substrate and no obvious differences between the sample types are apparent. In order to address the subtle differences in the spectra, we calculated different correlation coefficients, namely the Pearson coefficient and the Normalized cross correlation coefficient. By comparing the correlation with the negative control, differentiating between SARS-CoV-2 and Influenza A virus is possible. This study provides a first step towards the detection and potential classification of different viruses with the use of conventional Raman spectroscopy.
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Affiliation(s)
- Susanne Pahlow
- Abbe Center of Photonics, Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Center for Applied Research, InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena, Germany
- Leibniz Centre for Photonics in Infection Research (LPI), Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany
| | - Marie Richard-Lacroix
- Leibniz Centre for Photonics in Infection Research (LPI), Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany
| | - Franziska Hornung
- Leibniz Centre for Photonics in Infection Research (LPI), Institute of Medical Microbiology, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
| | - Nilay Köse-Vogel
- Leibniz Centre for Photonics in Infection Research (LPI), Institute of Medical Microbiology, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
| | - Thomas G Mayerhöfer
- Abbe Center of Photonics, Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Leibniz Centre for Photonics in Infection Research (LPI), Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany
| | - Julian Hniopek
- Abbe Center of Photonics, Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Center for Applied Research, InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena, Germany
- Leibniz Centre for Photonics in Infection Research (LPI), Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany
| | - Oleg Ryabchykov
- Abbe Center of Photonics, Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Center for Applied Research, InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena, Germany
- Leibniz Centre for Photonics in Infection Research (LPI), Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany
| | - Thomas Bocklitz
- Abbe Center of Photonics, Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Center for Applied Research, InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena, Germany
- Leibniz Centre for Photonics in Infection Research (LPI), Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany
- Physics & Computer Science, Faculty of Mathematics, Institute of Computer Science, University Bayreuth, Universitätsstraße 30, 95447 Bayreuth, Germany
| | - Karina Weber
- Abbe Center of Photonics, Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Center for Applied Research, InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena, Germany
- Leibniz Centre for Photonics in Infection Research (LPI), Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany
| | - Ralf Ehricht
- Abbe Center of Photonics, Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Center for Applied Research, InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena, Germany
- Leibniz Centre for Photonics in Infection Research (LPI), Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany
| | - Bettina Löffler
- Leibniz Centre for Photonics in Infection Research (LPI), Institute of Medical Microbiology, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
| | - Stefanie Deinhardt-Emmer
- Leibniz Centre for Photonics in Infection Research (LPI), Institute of Medical Microbiology, Jena University Hospital, Am Klinikum 1, 07747 Jena, Germany
| | - Jürgen Popp
- Abbe Center of Photonics, Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany
- Center for Applied Research, InfectoGnostics Research Campus Jena, Philosophenweg 7, 07743 Jena, Germany
- Leibniz Centre for Photonics in Infection Research (LPI), Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany
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Vilca-Alosilla JJ, Candia-Puma MA, Coronel-Monje K, Goyzueta-Mamani LD, Galdino AS, Machado-de-Ávila RA, Giunchetti RC, Ferraz Coelho EA, Chávez-Fumagalli MA. A Systematic Review and Meta-Analysis Comparing the Diagnostic Accuracy Tests of COVID-19. Diagnostics (Basel) 2023; 13:diagnostics13091549. [PMID: 37174941 PMCID: PMC10177430 DOI: 10.3390/diagnostics13091549] [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: 03/17/2023] [Revised: 04/06/2023] [Accepted: 04/11/2023] [Indexed: 05/15/2023] Open
Abstract
In this paper, we present a systematic review and meta-analysis that aims to evaluate the reliability of coronavirus disease diagnostic tests in 2019 (COVID-19). This article seeks to describe the scientific discoveries made because of diagnostic tests conducted in recent years during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Between 2020 and 2021, searches for published papers on the COVID-19 diagnostic were made in the PubMed database. Ninety-nine scientific articles that satisfied the requirements were analyzed and included in the meta-analysis, and the specificity and sensitivity of the diagnostic accuracy were assessed. When compared to serological tests such as the enzyme-linked immunosorbent assay (ELISA), chemiluminescence immunoassay (CLIA), lateral flow immunoassay (LFIA), and chemiluminescent microparticle immunoassay (CMIA), molecular tests such as reverse transcription polymerase chain reaction (RT-PCR), reverse transcription loop-mediated isothermal amplification (RT-LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR) performed better in terms of sensitivity and specificity. Additionally, the area under the curve restricted to the false-positive rates (AUCFPR) of 0.984 obtained by the antiviral neutralization bioassay (ANB) diagnostic test revealed significant potential for the identification of COVID-19. It has been established that the various diagnostic tests have been effectively adapted for the detection of SARS-CoV-2; nevertheless, their performance still must be enhanced to contain potential COVID-19 outbreaks, which will also help contain potential infectious agent outbreaks in the future.
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Affiliation(s)
- Juan Jeferson Vilca-Alosilla
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Facultad de Ciencias Farmacéuticas, Bioquímicas y Biotecnológicas, Universidad Católica de Santa María, Arequipa 04000, Peru
| | - Mayron Antonio Candia-Puma
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Facultad de Ciencias Farmacéuticas, Bioquímicas y Biotecnológicas, Universidad Católica de Santa María, Arequipa 04000, Peru
| | - Katiusca Coronel-Monje
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Facultad de Ciencias Farmacéuticas, Bioquímicas y Biotecnológicas, Universidad Católica de Santa María, Arequipa 04000, Peru
| | - Luis Daniel Goyzueta-Mamani
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
- Sustainable Innovative Biomaterials Department, Le Qara Research Center, Arequipa 04000, Peru
| | - Alexsandro Sobreira Galdino
- Laboratório de Biotecnologia de Microrganismos, Universidade Federal São João Del-Rei, Divinópolis 35501-296, MG, Brazil
| | | | - Rodolfo Cordeiro Giunchetti
- Laboratório de Biologia das Interações Celulares, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
- Instituto Nacional de Ciência e Tecnologia em Doenças Tropicais, INCT-DT, Salvador 40015-970, BA, Brazil
| | - Eduardo Antonio Ferraz Coelho
- Programa de Pós-Graduação em Ciências da Saúde: Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
- Departamento de Patologia Clínica, COLTEC, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
| | - Miguel Angel Chávez-Fumagalli
- Computational Biology and Chemistry Research Group, Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04000, Peru
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Askari H, Rabiei F, Lohrasbi F, Ghadir S, Ghasemi-Kasman M. The Latest Cellular and Molecular Mechanisms of COVID-19 on Non-Lung Organs. Brain Sci 2023; 13:brainsci13030415. [PMID: 36979225 PMCID: PMC10046222 DOI: 10.3390/brainsci13030415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 02/24/2023] [Accepted: 02/25/2023] [Indexed: 03/06/2023] Open
Abstract
Understanding the transmission pathways of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will aid in developing effective therapies directed at the virus’s life cycle or its side effects. While severe respiratory distress is the most common symptom of a coronavirus 2019 (COVID-19) infection, the virus is also known to cause damage to almost every major organ and system in the body. However, it is not obvious whether pathological changes in extra-respiratory organs are caused by direct infection, indirect, or combination of these effects. In this narrative review, we first elaborate on the characteristics of SARS-CoV-2, followed by the mechanisms of this virus on various organs such as brain, eye, and olfactory nerve and different systems such as the endocrine and gastrointestinal systems.
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Affiliation(s)
- Hamid Askari
- Student Research Committee, Babol University of Medical Sciences, Babol 47176-47745, Iran
| | - Fatemeh Rabiei
- Student Research Committee, Babol University of Medical Sciences, Babol 47176-47745, Iran
| | - Fatemeh Lohrasbi
- Student Research Committee, Babol University of Medical Sciences, Babol 47176-47745, Iran
| | - Sara Ghadir
- Student Research Committee, Babol University of Medical Sciences, Babol 47176-47745, Iran
| | - Maryam Ghasemi-Kasman
- Cellular and Molecular Biology Research Center, Health Research Institute, Babol University of Medical Sciences, Babol 47176-47745, Iran
- Department of Physiology, School of Medicine, Babol University of Medical Sciences, Babol 47176-47745, Iran
- Correspondence: ; Tel./Fax: +98-11-32190557
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5
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Jiang C, Jiang K, Li X, Zhang N, Zhu W, Meng L, Zhang Y, Lu S. Evaluation of immunoprotection against coronavirus disease 2019: Novel variants, vaccine inoculation, and complications. J Pharm Anal 2023; 13:1-10. [PMID: 36317070 PMCID: PMC9605787 DOI: 10.1016/j.jpha.2022.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 10/19/2022] [Accepted: 10/20/2022] [Indexed: 11/07/2022] Open
Abstract
The strikingly rapidly mutating nature of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome has been a constant challenge during the coronavirus disease 2019 (COVID-19) pandemic. In this study, various techniques, including reverse transcription-quantitative polymerase chain reaction, antigen-detection rapid diagnostic tests, and high-throughput sequencing were analyzed under different scenarios and spectra for the etiological diagnosis of COVID-19 at the population scale. This study aimed to summarize the latest research progress and provide up-to-date understanding of the methodology used for the evaluation of the immunoprotection conditions against future variants of SARS-CoV-2. Our novel work reviewed the current methods for the evaluation of the immunoprotection status of a specific population (endogenous antibodies) before and after vaccine inoculation (administered with biopharmaceutical antibody products). The present knowledge of the immunoprotection status regarding the COVID-19 complications was also discussed. Knowledge on the immunoprotection status of specific populations can help guide the design of pharmaceutical antibody products, inform practice guidelines, and develop national regulations with respect to the timing of and need for extra rounds of vaccine boosters.
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Affiliation(s)
- Congshan Jiang
- National Regional Children's Medical Center (Northwest), Key Laboratory of Precision Medicine to Pediatric Diseases of Shaanxi Province, Xi'an Key Laboratory of Children's Health and Diseases, Shaanxi Institute for Pediatric Diseases, Xi'an Children's Hospital, Affiliated Children's Hospital of Xi'an Jiaotong University, Xi'an, 710003, China
| | - Kaichong Jiang
- National Regional Children's Medical Center (Northwest), Key Laboratory of Precision Medicine to Pediatric Diseases of Shaanxi Province, Xi'an Key Laboratory of Children's Health and Diseases, Shaanxi Institute for Pediatric Diseases, Xi'an Children's Hospital, Affiliated Children's Hospital of Xi'an Jiaotong University, Xi'an, 710003, China
| | - Xiaowei Li
- National Joint Engineering Research Center of Biodiagnostics and Biotherapy, Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Ning Zhang
- National Joint Engineering Research Center of Biodiagnostics and Biotherapy, Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, 710004, China
| | - Wenhua Zhu
- Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University, Xi'an, 710061, China,Institute of Molecular and Translational Medicine (IMTM), and Department of Biochemistry and Molecular Biology, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
| | - Liesu Meng
- Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University, Xi'an, 710061, China,Institute of Molecular and Translational Medicine (IMTM), and Department of Biochemistry and Molecular Biology, Xi'an Jiaotong University Health Science Center, Xi'an, 710061, China
| | - Yanmin Zhang
- National Regional Children's Medical Center (Northwest), Key Laboratory of Precision Medicine to Pediatric Diseases of Shaanxi Province, Xi'an Key Laboratory of Children's Health and Diseases, Shaanxi Institute for Pediatric Diseases, Xi'an Children's Hospital, Affiliated Children's Hospital of Xi'an Jiaotong University, Xi'an, 710003, China,Corresponding author.
| | - Shemin Lu
- National Regional Children's Medical Center (Northwest), Key Laboratory of Precision Medicine to Pediatric Diseases of Shaanxi Province, Xi'an Key Laboratory of Children's Health and Diseases, Shaanxi Institute for Pediatric Diseases, Xi'an Children's Hospital, Affiliated Children's Hospital of Xi'an Jiaotong University, Xi'an, 710003, China,Key Laboratory of Environment and Genes Related to Diseases, Xi'an Jiaotong University, Xi'an, 710061, China,Corresponding author. National Regional Children's Medical Center (Northwest), Key Laboratory of Precision Medicine to Pediatric Diseases of Shaanxi Province, Xi'an Key Laboratory of Children's Health and Diseases, Shaanxi Institute for Pediatric Diseases, Xi'an Children's Hospital, Affiliated Children's Hospital of Xi'an Jiaotong University, Xi'an, 710003, China.
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6
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Application of Nanotechnology in COVID-19 Infection: Findings and Limitations. JOURNAL OF NANOTHERANOSTICS 2022. [DOI: 10.3390/jnt3040014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
There is an urgent need to address the global mortality of the COVID-19 pandemic, as it reached 6.3 million as of July 2022. As such, the experts recommended the mass diagnosis of SARS-CoV-2 infection at an early stage using nanotechnology-based sensitive diagnostic approaches. The development of nanobiosensors for Point-of-Care (POC) sampling of COVID-19 could ensure mass detection without the need for sophisticated laboratories or expert personnel. The use of Artificial Intelligence (AI) techniques for POC detection was also proposed. In addition, the utilization of various antiviral nanomaterials such as Silver Nanoparticles (AgNPs) for the development of masks for personal protection mitigates viral transmission. Nowadays, nano-assisted vaccines have been approved for emergency use, but their safety and effectiveness in the mutant strain of the SARS-CoV-2 virus remain challenging. Methodology: Updated literature was sourced from various research indexing databases such as PubMed, SCOPUS, Science Direct, Research Gate and Google Scholars. Result: We presented the concept of novel nanotechnology researched discovery, including nano-devices, electrochemical biosensing, nano-assisted vaccine, and nanomedicines, for use in recent times, which could be a formidable step for future management of COVID-19.
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Usefulness and Limitations of Anti-S IgG Assay in Detecting Previous SARS-CoV-2 Breakthrough Infection in Fully Vaccinated Healthcare Workers. Diagnostics (Basel) 2022; 12:diagnostics12092152. [PMID: 36140553 PMCID: PMC9497628 DOI: 10.3390/diagnostics12092152] [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: 08/05/2022] [Revised: 09/01/2022] [Accepted: 09/02/2022] [Indexed: 11/17/2022] Open
Abstract
Introduction: The anti-spike (S) IgG assay is the most widely used method to assess the immunological response to COVID-19 vaccination. Several studies showed that subjects with perivaccination infection have higher anti-S IgG titers. However, a cut-off has not yet been identified so far for distinguishing infected subjects after vaccination. This study thus evaluates the performance of the anti-S IgG assay in identifying subjects with breakthrough infections (BIs) and its potential usefulness for screening healthcare workers (HCWs). Methods: Out of 6400 HCWs of the University Hospital of Verona vaccinated with two doses of BNT162b2, 4462 never infected before subjects who had completed primary vaccination were tested for IgG anti-S 6 to 9 months after the second dose. Of these, 59 (1.3%) had a BI. The discriminant power of IgG anti-S in detecting previous breakthrough infection was tested by constructing receiver operating characteristic (ROC) curves. Results: The discriminant power for BI was rather good (area under the curve (AUC), 0.78) and increased with decreasing time elapsed between antibody titer assessment and previous SARS-CoV-2 infection. Accuracy (AUC) sensitivity increased from 0.78 (95% CI 0.70−0.85) for BI in the previous six months to 0.83 (95% CI 0.67−0.99) for those in the previous two months, and from 0.68 to 0.80, respectively. The specificity (0.86) and optimal cut-off (935 BAU/mL) remained unchanged. However, BI were rather rare (1.3%), so the positive predictive value (PPV) was low. Only 40 of the 664 HCWs with antibody titer > 935 BAU/mL had previously confirmed BI, yielding a PPV of only 6.0%. When adopting as cut-off the 90th percentile (1180 BAU/mL), PPV increased to 7.9% (35/441). Conclusions: The anti-S IgG assay displayed good sensitivity and specificity in discriminating subjects with BI, especially in recent periods. However, BIs were rare among HCWs, so that the anti-S IgG assay may have low PPV in this setting, thus limiting the usefulness of this test as a screening tool for HCWs. Further studies are needed to identify more effective markers of a previous infection in vaccinated subjects.
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Zhou Y, Guo M. Isolation in the control of epidemic. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:10846-10863. [PMID: 36124572 DOI: 10.3934/mbe.2022507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Among many epidemic prevention measures, isolation is an important method to control the spread of infectious disease. Scholars rarely study the impact of isolation on disease dissemination from a quantitative perspective. In this paper, we introduce an isolation ratio and establish the corresponding model. The basic reproductive number and its biological explanation are given. The stability conditions of the disease-free and endemic equilibria are obtained by analyzing its distribution of characteristic values. It is shown that the isolation ratio has an important influence on the basic reproductive number and the stability conditions. Taking the COVID-19 in Wuhan as an example, isolating more than 68% of the population can control the spread of the epidemic. This method can provide precise epidemic prevention strategies for government departments. Numerical simulations verify the effectiveness of the results.
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Affiliation(s)
- Yong Zhou
- College of Science, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Minrui Guo
- College of Energy Engineering, Huanghuai University, Zhumadian 463000, China
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9
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Recurrence of Asymptomatic COVID-19 after Recovery among Healthcare Workers. Case Rep Infect Dis 2022; 2022:8787867. [PMID: 35313465 PMCID: PMC8933653 DOI: 10.1155/2022/8787867] [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: 08/19/2021] [Revised: 09/18/2021] [Accepted: 02/24/2022] [Indexed: 11/21/2022] Open
Abstract
We describe five healthcare workers (HCWs) with a recurrence of asymptomatic SARS-CoV-2 infection at Siloam Teaching Hospital, Indonesia. All cases involved nurses, with an average age of 27 years. The RT-PCR assay confirmed the first and second infection episodes. All cases showed negative RT-PCR results in the period between two infection episodes. The median interval time between two infection episodes was 123 days, ranging from 92 to 158 days. The clinical outcomes for all cases were favourable, with no mortality observed among study cases. Further studies will be required to understand the true nature of this phenomenon.
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Aghamirza Moghim Aliabadi H, Eivazzadeh‐Keihan R, Beig Parikhani A, Fattahi Mehraban S, Maleki A, Fereshteh S, Bazaz M, Zolriasatein A, Bozorgnia B, Rahmati S, Saberi F, Yousefi Najafabadi Z, Damough S, Mohseni S, Salehzadeh H, Khakyzadeh V, Madanchi H, Kardar GA, Zarrintaj P, Saeb MR, Mozafari M. COVID-19: A systematic review and update on prevention, diagnosis, and treatment. MedComm (Beijing) 2022; 3:e115. [PMID: 35281790 PMCID: PMC8906461 DOI: 10.1002/mco2.115] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 12/18/2021] [Accepted: 12/19/2021] [Indexed: 01/09/2023] Open
Abstract
Since the rapid onset of the COVID-19 or SARS-CoV-2 pandemic in the world in 2019, extensive studies have been conducted to unveil the behavior and emission pattern of the virus in order to determine the best ways to diagnosis of virus and thereof formulate effective drugs or vaccines to combat the disease. The emergence of novel diagnostic and therapeutic techniques considering the multiplicity of reports from one side and contradictions in assessments from the other side necessitates instantaneous updates on the progress of clinical investigations. There is also growing public anxiety from time to time mutation of COVID-19, as reflected in considerable mortality and transmission, respectively, from delta and Omicron variants. We comprehensively review and summarize different aspects of prevention, diagnosis, and treatment of COVID-19. First, biological characteristics of COVID-19 were explained from diagnosis standpoint. Thereafter, the preclinical animal models of COVID-19 were discussed to frame the symptoms and clinical effects of COVID-19 from patient to patient with treatment strategies and in-silico/computational biology. Finally, the opportunities and challenges of nanoscience/nanotechnology in identification, diagnosis, and treatment of COVID-19 were discussed. This review covers almost all SARS-CoV-2-related topics extensively to deepen the understanding of the latest achievements (last updated on January 11, 2022).
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Affiliation(s)
- Hooman Aghamirza Moghim Aliabadi
- Protein Chemistry LaboratoryDepartment of Medical BiotechnologyBiotechnology Research CenterPasteur Institute of IranTehranIran
- Advance Chemical Studies LaboratoryFaculty of ChemistryK. N. Toosi UniversityTehranIran
| | | | - Arezoo Beig Parikhani
- Department of Medical BiotechnologyBiotechnology Research CenterPasteur InstituteTehranIran
| | | | - Ali Maleki
- Department of ChemistryIran University of Science and TechnologyTehranIran
| | | | - Masoume Bazaz
- Department of Medical BiotechnologyBiotechnology Research CenterPasteur InstituteTehranIran
| | | | | | - Saman Rahmati
- Department of Medical BiotechnologyBiotechnology Research CenterPasteur InstituteTehranIran
| | - Fatemeh Saberi
- Department of Medical BiotechnologySchool of Advanced Technologies in MedicineShahid Beheshti University of Medical SciencesTehranIran
| | - Zeinab Yousefi Najafabadi
- Department of Medical BiotechnologySchool of Advanced Technologies in MedicineTehran University of Medical SciencesTehranIran
- ImmunologyAsthma & Allergy Research InstituteTehran University of Medical SciencesTehranIran
| | - Shadi Damough
- Department of Medical BiotechnologyBiotechnology Research CenterPasteur InstituteTehranIran
| | - Sara Mohseni
- Non‐metallic Materials Research GroupNiroo Research InstituteTehranIran
| | | | - Vahid Khakyzadeh
- Department of ChemistryK. N. Toosi University of TechnologyTehranIran
| | - Hamid Madanchi
- School of MedicineSemnan University of Medical SciencesSemnanIran
- Drug Design and Bioinformatics UnitDepartment of Medical BiotechnologyBiotechnology Research CenterPasteur Institute of IranTehranIran
| | - Gholam Ali Kardar
- Department of Medical BiotechnologySchool of Advanced Technologies in MedicineTehran University of Medical SciencesTehranIran
- ImmunologyAsthma & Allergy Research InstituteTehran University of Medical SciencesTehranIran
| | - Payam Zarrintaj
- School of Chemical EngineeringOklahoma State UniversityStillwaterOklahomaUSA
| | - Mohammad Reza Saeb
- Department of Polymer TechnologyFaculty of ChemistryGdańsk University of TechnologyGdańskPoland
| | - Masoud Mozafari
- Department of Tissue Engineering & Regenerative MedicineIran University of Medical SciencesTehranIran
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11
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Gusev E, Sarapultsev A, Solomatina L, Chereshnev V. SARS-CoV-2-Specific Immune Response and the Pathogenesis of COVID-19. Int J Mol Sci 2022; 23:1716. [PMID: 35163638 PMCID: PMC8835786 DOI: 10.3390/ijms23031716] [Citation(s) in RCA: 101] [Impact Index Per Article: 50.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/31/2022] [Accepted: 02/01/2022] [Indexed: 12/13/2022] Open
Abstract
The review aims to consolidate research findings on the molecular mechanisms and virulence and pathogenicity characteristics of coronavirus disease (COVID-19) causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and their relevance to four typical stages in the development of acute viral infection. These four stages are invasion; primary blockade of antiviral innate immunity; engagement of the virus's protection mechanisms against the factors of adaptive immunity; and acute, long-term complications of COVID-19. The invasion stage entails the recognition of the spike protein (S) of SARS-CoV-2 target cell receptors, namely, the main receptor (angiotensin-converting enzyme 2, ACE2), its coreceptors, and potential alternative receptors. The presence of a diverse repertoire of receptors allows SARS-CoV-2 to infect various types of cells, including those not expressing ACE2. During the second stage, the majority of the polyfunctional structural, non-structural, and extra proteins SARS-CoV-2 synthesizes in infected cells are involved in the primary blockage of antiviral innate immunity. A high degree of redundancy and systemic action characterizing these pathogenic factors allows SARS-CoV-2 to overcome antiviral mechanisms at the initial stages of invasion. The third stage includes passive and active protection of the virus from factors of adaptive immunity, overcoming of the barrier function at the focus of inflammation, and generalization of SARS-CoV-2 in the body. The fourth stage is associated with the deployment of variants of acute and long-term complications of COVID-19. SARS-CoV-2's ability to induce autoimmune and autoinflammatory pathways of tissue invasion and development of both immunosuppressive and hyperergic mechanisms of systemic inflammation is critical at this stage of infection.
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Affiliation(s)
- Evgenii Gusev
- Laboratory of Immunology of Inflammation, Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia
| | - Alexey Sarapultsev
- Laboratory of Immunology of Inflammation, Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia
- Russian-Chinese Education and Research Center of System Pathology, South Ural State University, 454080 Chelyabinsk, Russia
| | - Liliya Solomatina
- Laboratory of Immunology of Inflammation, Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia
| | - Valeriy Chereshnev
- Laboratory of Immunology of Inflammation, Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia
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12
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Konka A, Lejawa M, Gaździcka J, Bochenek A, Fronczek M, Strzelczyk JK. RT-PCR Detection of SARS-CoV-2 among Individuals from the Upper Silesian Region-Analysis of 108,516 Tests. Diagnostics (Basel) 2021; 12:diagnostics12010007. [PMID: 35054172 PMCID: PMC8774892 DOI: 10.3390/diagnostics12010007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/16/2021] [Accepted: 12/17/2021] [Indexed: 02/06/2023] Open
Abstract
Background: The COVID-19 pandemic triggered by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has left a huge mark on everyday lives, introducing restrictions and plunging the global economy. This study aimed to analyze the available epidemiological data from the register of one of the largest laboratories testing for SARS-CoV-2 in the Silesian voivodship of Poland. Methods: This analysis is based upon the epidemiological records collected between 30 March 2020, and 30 April 2021, by the Silesian Park of Medical Technology Kardio-Med Silesia (Zabrze, Poland). In addition, we performed SARS-CoV-2 variant detection in samples from patients reinfected with SARS-CoV-2. Results: Our results confirm that SARS-CoV-2 infections are more common in urban areas. Laboratory-confirmed COVID-19 cases represent 13.21% of all RT-PCR test results during the 13 months of our laboratory diagnostics for SARS-CoV-2 infections. Detection of SARS-CoV-2 variants in samples of potentially reinfected patients showed discrepancies in the results. Conclusions: Due to the higher risk of SARS-CoV-2 infection among the Upper Silesian population, the region is at greater risk of deteriorating economic situation and healthcare as compared to other areas of Poland. RT-PCR methods are inexpensive and suitable for large-scale screening, but they can be untrustworthy so detection of SARS-CoV-2 variants in samples should be confirmed by sequencing.
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Affiliation(s)
- Adam Konka
- Silesian Park of Medical Technology Kardio-Med Silesia, M. Curie-Skłodowskiej 10C, 41-800 Zabrze, Poland; (M.L.); (A.B.); (M.F.)
- Correspondence: ; Tel.: +48-32-705-03-05
| | - Mateusz Lejawa
- Silesian Park of Medical Technology Kardio-Med Silesia, M. Curie-Skłodowskiej 10C, 41-800 Zabrze, Poland; (M.L.); (A.B.); (M.F.)
- Department of Pharmacology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, Jordana 38 Str., 41-808 Zabrze, Poland
| | - Jadwiga Gaździcka
- Department of Medical and Molecular Biology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Jordana 19 Str., 41-808 Zabrze, Poland; (J.G.); (J.K.S.)
| | - Aneta Bochenek
- Silesian Park of Medical Technology Kardio-Med Silesia, M. Curie-Skłodowskiej 10C, 41-800 Zabrze, Poland; (M.L.); (A.B.); (M.F.)
| | - Martyna Fronczek
- Silesian Park of Medical Technology Kardio-Med Silesia, M. Curie-Skłodowskiej 10C, 41-800 Zabrze, Poland; (M.L.); (A.B.); (M.F.)
- Department of Pharmacology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, Jordana 38 Str., 41-808 Zabrze, Poland
| | - Joanna Katarzyna Strzelczyk
- Department of Medical and Molecular Biology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Jordana 19 Str., 41-808 Zabrze, Poland; (J.G.); (J.K.S.)
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13
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Sun Q, Shu C, Shi W, Luo Y, Fan G, Nie J, Bi Y, Wang Q, Qi J, Lu J, Zhou Y, Shen Z, Meng Z, Zhang X, Yu Z, Gao S, Wu L, Ma J, Hu S. VarEPS: an evaluation and prewarning system of known and virtual variations of SARS-CoV-2 genomes. Nucleic Acids Res 2021; 50:D888-D897. [PMID: 34634813 PMCID: PMC8728250 DOI: 10.1093/nar/gkab921] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 09/18/2021] [Accepted: 09/28/2021] [Indexed: 12/17/2022] Open
Abstract
The genomic variations of SARS-CoV-2 continue to emerge and spread worldwide. Some mutant strains show increased transmissibility and virulence, which may cause reduced protection provided by vaccines. Thus, it is necessary to continuously monitor and analyze the genomic variations of SARS-COV-2 genomes. We established an evaluation and prewarning system, SARS-CoV-2 variations evaluation and prewarning system (VarEPS), including known and virtual mutations of SARS-CoV-2 genomes to achieve rapid evaluation of the risks posed by mutant strains. From the perspective of genomics and structural biology, the database comprehensively analyzes the effects of known variations and virtual variations on physicochemical properties, translation efficiency, secondary structure, and binding capacity of ACE2 and neutralizing antibodies. An AI-based algorithm was used to verify the effectiveness of these genomics and structural biology characteristic quantities for risk prediction. This classifier could be further used to group viral strains by their transmissibility and affinity to neutralizing antibodies. This unique resource makes it possible to quickly evaluate the variation risks of key sites, and guide the research and development of vaccines and drugs. The database is freely accessible at www.nmdc.cn/ncovn.
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Affiliation(s)
- Qinglan Sun
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,Chinese National Microbiology Data Center (NMDC), Beijing 100101, China
| | - Chang Shu
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Wenyu Shi
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,Chinese National Microbiology Data Center (NMDC), Beijing 100101, China
| | - Yingfeng Luo
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guomei Fan
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,Chinese National Microbiology Data Center (NMDC), Beijing 100101, China
| | - Jingyi Nie
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuhai Bi
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Qihui Wang
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Jianxun Qi
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Jian Lu
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing 100871, China
| | - Yuanchun Zhou
- Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
| | - Zhihong Shen
- Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
| | - Zhen Meng
- Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
| | - Xinjiao Zhang
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,Chinese National Microbiology Data Center (NMDC), Beijing 100101, China
| | - Zhengfei Yu
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,Chinese National Microbiology Data Center (NMDC), Beijing 100101, China
| | - Shenghan Gao
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Linhuan Wu
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,Chinese National Microbiology Data Center (NMDC), Beijing 100101, China
| | - Juncai Ma
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,Chinese National Microbiology Data Center (NMDC), Beijing 100101, China
| | - Songnian Hu
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
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14
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Laskar R, Ali S. Differential mutation profile of SARS-CoV-2 proteins across deceased and asymptomatic patients. Chem Biol Interact 2021; 347:109598. [PMID: 34303694 PMCID: PMC8299203 DOI: 10.1016/j.cbi.2021.109598] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 07/08/2021] [Accepted: 07/21/2021] [Indexed: 01/18/2023]
Abstract
BACKGROUND The SARS-CoV-2 infection has spread at an alarming rate with many places showing multiple peaks in incidence. Present study analyzes a total of 332 SARS-CoV-2 genome sequences from 114 asymptomatic and 218 deceased patients from twenty-one different countries to assess the mutation profile therein in order to establish the correlation between the clinical status and the observed mutations. METHODS The mining of mutations was carried out using the GISAID CoVSurver (www.gisaid.org/epiflu-applications/covsurver-mutations-app) with the reference sequence 'hCoV-19/Wuhan/WIV04/2019' present in NCBI with Accession number NC-045512.2. The impact of the mutations on SARS-CoV-2 proteins mutation was predicted using PredictSNP1(loschmidt.chemi.muni.cz/predictsnp1) which is a meta-server integrating six predictor tools: SIFT, PhD-SNP, PolyPhen-1, PolyPhen-2, MAPP and SNAP. The iStable integrated server (predictor.nchu.edu.tw/iStable) was used to predict shifts in the protein stability due to mutations. RESULTS A total of 372 variants were observed in the 332 SARS-CoV-2 sequences with several variants present in multiple patients accounting for a total of 1596 incidences. Asymptomatic and deceased specific mutants constituted 32% and 62% of the repertoire respectively indicating their partial exclusivity. However, the most prevalent mutations were those present in both. Though some parts of the genome are more variable than others but there was clear difference between incidence and prevalence. Non-structural protein 3 (NSP3) with 68 variants had a total of only 105 incidences whereas Spike protein had 346 incidences with just 66 variants. Amongst the Deleterious variants, NSP3 had the highest incidence of 25 followed by NSP2 (16), ORF3a (14) and N (14). Spike protein had just 7 Deleterious variants out of 66. CONCLUSION Deceased patients have more Deleterious than Neutral variants as compared to the asymptomatic ones. Further, it appears that the Deleterious variants which decrease protein stability are more significant in pathogenicity of SARS-CoV-2.
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Affiliation(s)
- Rezwanuzzaman Laskar
- Clinical and Applied Genomics (CAG) Laboratory, Department of Biological Sciences, Aliah University, Kolkata, India.
| | - Safdar Ali
- Clinical and Applied Genomics (CAG) Laboratory, Department of Biological Sciences, Aliah University, Kolkata, India.
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