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Mosadegh M, Jalili S, Pourmand MR, Erfani Y, Panji M. Evaluating the efficiency of ELISA, monoplex and multiplex probe-based real-time reverse-transcription PCR assays in the detection of SARS-CoV-2 (COVID-19) and influenza A and B viruses: A cross-sectional study. Health Sci Rep 2024; 7:e2140. [PMID: 38915351 PMCID: PMC11194474 DOI: 10.1002/hsr2.2140] [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: 10/09/2023] [Revised: 03/26/2024] [Accepted: 05/06/2024] [Indexed: 06/26/2024] Open
Abstract
Background and Aims The current study aimed to evaluate the efficiency of Enzyme-linked immunosorbent assay (ELISA) assay and monoplex and multiplex real-time reverse-transcription PCR (rRT-PCR) in the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A and B viruses (Flu A and Flu B). Methods The SARS-CoV-2 -specific IgG and IgM antibodies, as well as, Flu A (H1N1 and H3N2 serotypes) and Flu B virus antibodies were determined by ELISA assay. The one-step qRT-PCR method was used to detect the SARS-CoV-2 in nasopharyngeal swab samples. Furthermore, the presence of Flu A and B viruses was evaluated using probe-based RT-PCR. Simultaneous detection of SARS-CoV-2, Flu A and B viruses was performed by multiplex rRT-PCR assay. Results SARS CoV-2 IgM and IgG antibodies were detected in 33.3% and 58.3% of patients, respectively. In contrast, the SARS CoV-2 genome was detected in 50% of patients using the one-step monoplex RT-PCR assay. Flu A serotypes H1N1 and H3N2 were found in 16.7% and 8.3% of patients. Probe-based RT-PCR revealed that 39.3% of patients were positive for the Flu A virus. Multiplex rRT-PCR detect the SARS-CoV-2, Flu A, and Flu B in 50%, 39.3%, and 19% of samples, respectively. The sensitivity and specificity of multiplex rRT-PCR assay in comparison to monoplex RT-PCR were 100% and 55%, respectively. Coinfection with SARS-CoV-2, Flu A, and Flu B viruses was found in 9.5% of patients. Conclusion Multiplex rRT-PCR can be used as a repaid, cost-effective and suitable tool for molecular surveillance of SARS-CoV-2 and Flu A/B viruses.
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Affiliation(s)
- Mehrdad Mosadegh
- Department of Pathobiology, School of Public HealthTehran University of Medical SciencesTehranIran
| | - Shirin Jalili
- Institute of Police Equipment and TechnologiesPolicing Sciences and Social Studies Research InstituteTehranIran
| | - Mohammad Reza Pourmand
- Department of Pathobiology, School of Public HealthTehran University of Medical SciencesTehranIran
| | - Yousef Erfani
- Department of Medical Laboratory Sciences, School of Allied Medical SciencesTehran University of Medical SciencesTehranIran
| | - Mohammad Panji
- Research Center for Life and Health Sciences and Biotechnology for the Police, Directorate of Health, Rescue and TreatmentPolice HeadquarterTehranIran
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Liang J, Wang Y, Lin Z, He W, Sun J, Li Q, Zhang M, Chang Z, Guo Y, Zeng W, Liu T, Zeng Z, Yang Z, Hon C. Influenza and COVID-19 co-infection and vaccine effectiveness against severe cases: a mathematical modeling study. Front Cell Infect Microbiol 2024; 14:1347710. [PMID: 38500506 PMCID: PMC10945002 DOI: 10.3389/fcimb.2024.1347710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 02/01/2024] [Indexed: 03/20/2024] Open
Abstract
Background Influenza A virus have a distinctive ability to exacerbate SARS-CoV-2 infection proven by in vitro studies. Furthermore, clinical evidence suggests that co-infection with COVID-19 and influenza not only increases mortality but also prolongs the hospitalization of patients. COVID-19 is in a small-scale recurrent epidemic, increasing the likelihood of co-epidemic with seasonal influenza. The impact of co-infection with influenza virus and SARS-CoV-2 on the population remains unstudied. Method Here, we developed an age-specific compartmental model to simulate the co-circulation of COVID-19 and influenza and estimate the number of co-infected patients under different scenarios of prevalent virus type and vaccine coverage. To decrease the risk of the population developing severity, we investigated the minimum coverage required for the COVID-19 vaccine in conjunction with the influenza vaccine, particularly during co-epidemic seasons. Result Compared to the single epidemic, the transmission of the SARS-CoV-2 exhibits a lower trend and a delayed peak when co-epidemic with influenza. Number of co-infection cases is higher when SARS-CoV-2 co-epidemic with Influenza A virus than that with Influenza B virus. The number of co-infected cases increases as SARS-CoV-2 becomes more transmissible. As the proportion of individuals vaccinated with the COVID-19 vaccine and influenza vaccines increases, the peak number of co-infected severe illnesses and the number of severe illness cases decreases and the peak time is delayed, especially for those >60 years old. Conclusion To minimize the number of severe illnesses arising from co-infection of influenza and COVID-19, in conjunction vaccinations in the population are important, especially priority for the elderly.
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Affiliation(s)
- Jingyi Liang
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, China
| | - Yangqianxi Wang
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, China
| | - Zhijie Lin
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, China
| | - Wei He
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, China
| | - Jiaxi Sun
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Qianyin Li
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Mingyi Zhang
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Zichen Chang
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Yinqiu Guo
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Wenting Zeng
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Tie Liu
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
| | - Zhiqi Zeng
- Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, KingMed School of Laboratory Medicine, Guangzhou Medical University, Guangzhou, China
- Guangzhou Laboratory, Guangzhou, Guangdong, China
| | - Zifeng Yang
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, China
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
- Guangzhou Laboratory, Guangzhou, Guangdong, China
| | - Chitin Hon
- Department of Engineering Science, Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa, Macao SAR, China
- Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macao, Macao SAR, China
- Guangzhou Laboratory, Guangzhou, Guangdong, China
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Sabastin M, Mone K, Manivel A, Cherayi Padinakarai A, Krishnasamy K. Epidemic profile of common respiratory viruses in association SARS CoV-2 among SARI and ARI-two year study. Mol Biol Rep 2024; 51:156. [PMID: 38252354 DOI: 10.1007/s11033-023-09084-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/30/2023] [Indexed: 01/23/2024]
Abstract
BACKGROUND COVID-19/SARS CoV-2 continue to pose a threat to human health and placed millions of livelihoods at risk. Surveillance for the other circulating seasonal viruses during this pandemic is necessary to understand the manifestations of the CoV-2 pandemic and their incidence. METHODS A detailed study survey was performed on subjects with acute respiratory infections (ARI) and severe acute respiratory infection (SARI) in the King Institute of Preventive Medicine and Research, Chennai from April 2020 to March 2022. A total of 1480 patients presenting with either SARI (41.8%) or ARI (58.1%) were screened for SARS CoV-2 and other respiratory viruses. The SARS CoV-2 real-time PCR was carried out using ICMR-approved kits and other respiratory viruses were detected using the commercially available real-time kit. RESULTS Out of the 620 SARI patients, 198 (31.9%) were positive for SARS CoV-2 RNA. Out of the 860 ARI patients, 352 (40.9%) were positive for SARS CoV-2 RNA. Among the 550 patients positive for SARS CoV-2, 7 (1.2%) were positive coexistent with other respiratory viruses. Among the 930 patients with negative SARS CoV-2, 222 (23.8%) were positive for other common respiratory viruses (p = 0.001). Influenza viruses (36.9%) predominated followed by RSV (31.9%) and Parainfluenza virus (13.5%). CONCLUSION This study suggests that viral coinfections are significantly higher among SARS CoV-2 negative individuals (23.8 vs. 1.2%). It is possibly due to viral interference and the competitive advantage of SARS CoV-2 in modulating the host immunity. Continuous surveillance is necessary for understanding the viral co-infection mechanisms.
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Affiliation(s)
- Merlin Sabastin
- Department of Virology, King Institute of Preventive Medicine and Research, Chennai, Tamil Nadu, India
| | - Kiruthiga Mone
- Department of Virology, King Institute of Preventive Medicine and Research, Chennai, Tamil Nadu, India
| | - ArunKumar Manivel
- Department of Virology, King Institute of Preventive Medicine and Research, Chennai, Tamil Nadu, India
| | | | - Kaveri Krishnasamy
- Department of Virology, King Institute of Preventive Medicine and Research, Chennai, Tamil Nadu, India.
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Wu CY, Tseng YC, Kao SE, Wu LY, Hou JT, Yang YC, Hsiao PW, Chen JR. Monoglycosylated SARS-CoV-2 receptor binding domain fused with HA stem-scaffolded protein vaccine confers broad protective immunity against SARS-CoV-2 and influenza viruses. Antiviral Res 2023; 220:105759. [PMID: 37984568 DOI: 10.1016/j.antiviral.2023.105759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 11/13/2023] [Accepted: 11/15/2023] [Indexed: 11/22/2023]
Abstract
The SARS-CoV-2 and influenza pandemics have posed a devastating threat to global public health. The best strategy for preventing the further spread of these respiratory viruses worldwide is to administer a vaccine capable of targeting both viruses. Here, we show that a novel monoglycosylated vaccine designed based on the influenza virus HAstem conserved domain fused with the SARS-CoV-2 spike-RBD domain (HSSRmg) can present proper antigenicity that elicits sufficient neutralization efficacy against various SARS-CoV-2 variants while simultaneously providing broad protection against H1N1 viruses in mice. Compared with the fully glycosylated HSSR (HSSRfg), HSSRmg induced higher ELISA titers targeting HAstem and spike-RBD and exhibited significantly enhanced neutralization activity against the Wuhan pseudovirus. The enhanced immune responses raised by JR300-adjuvanted HSSRmg compared to HSSRmg alone include more anti-HAstem and anti-spike-RBD antibodies that provide cross-protection against H1N1 challenges and cross-neutralization of SARS-CoV-2 pseudoviruses. Furthermore, the enhanced immune response raised by JR300-adjuvanted-HSSRmg skews toward a more balanced Th1/Th2 response than that raised by HSSRmg alone. Notably, HSSRmg elicited more plasma B cells and memory B cells, and higher IL-4 and IFN-γ cytokine immune responses than spike (S-2P) in mice with preexisting influenza-specific immunity, suggesting that B-cell activation most likely occurs through CD4+ T-cell stimulation. This study demonstrated that HSSRmg produced using a monoglycosylation process and combined with the JR300 adjuvant elicits superior cross-strain immune responses against SARS-CoV-2 and influenza viruses in mice compared with S-2P. JR300-adjuvanted HSSRmg has great potential as a coronavirus-influenza vaccine that provides dual protection against SARS-CoV-2 and influenza infections.
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Affiliation(s)
| | | | - Shao-En Kao
- RuenHuei Biopharmaceuticals Inc. Taipei, Taiwan
| | - Li-Yang Wu
- RuenHuei Biopharmaceuticals Inc. Taipei, Taiwan
| | - Jen-Tzu Hou
- RuenHuei Biopharmaceuticals Inc. Taipei, Taiwan
| | - Yu-Chih Yang
- Agricultural Biotechnology Research Center, Academia Sinica, Taipei, Taiwan
| | - Pei-Wen Hsiao
- Agricultural Biotechnology Research Center, Academia Sinica, Taipei, Taiwan
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Evaluation of the Diagnostic Performance of a SARS-CoV-2 and Influenza A/B Combo Rapid Antigen Test in Respiratory Samples. Diagnostics (Basel) 2023; 13:diagnostics13050972. [PMID: 36900116 PMCID: PMC10000510 DOI: 10.3390/diagnostics13050972] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 03/01/2023] [Accepted: 03/03/2023] [Indexed: 03/08/2023] Open
Abstract
This study aimed to evaluate the performance characteristics of a rapid antigen test developed to detect SARS-CoV-2 (COVID-19), influenza A virus (IAV), and influenza B virus (IBV) (flu) compared with those of the real-time reverse transcription-polymerase chain reaction (rRT-PCR) method. One hundred SARS-CoV-2, one hundred IAV, and twenty-four IBV patients whose diagnoses were confirmed by clinical and laboratory methods were included in the patient group. Seventy-six patients, who were negative for all respiratory tract viruses, were included as the control group. The Panbio™ COVID-19/Flu A&B Rapid Panel test kit was used in the assays. The sensitivity values of the kit were 97.5%, 97.9%, and 33.33% for SARS-CoV-2, IAV, and IBV, respectively, in samples with a viral load below 20 Ct values. The sensitivity values of the kit were 16.7%, 36.5%, and 11.11% for SARS-CoV-2, IAV, and IBV, respectively, in samples with a viral load above 20 Ct. The kit's specificity was 100%. In conclusion, this kit demonstrated high sensitivity to SARS-CoV-2 and IAV for viral loads below 20 Ct values, but the sensitivity values were not compatible with PCR positivity for lower viral loads over 20 Ct values. Rapid antigen tests may be preferred as a routine screening tool in communal environments, especially in symptomatic individuals, when diagnosing SARS-CoV-2, IAV, and IBV with high caution.
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