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Larsen AC, Roos EM, Möller S, Juhl C, Storm LK, Kongsted A, Møller M. Health Problems in Danish Adolescent Handball Players: Findings From the One-Season Health and Performance Promotion in Youth Sport (HAPPY) Study of 945 Players Aged 11-17 Years. Scand J Med Sci Sports 2025; 35:e70048. [PMID: 40202073 PMCID: PMC11979877 DOI: 10.1111/sms.70048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2025] [Revised: 03/24/2025] [Accepted: 03/26/2025] [Indexed: 04/10/2025]
Abstract
We aimed to assess the in-season weekly average prevalence proportion, the incidence rate, and burden (the product of incidence rate and duration of injury in weeks) of health problems among Danish youth handball community players aged 11-17. In this 30-week prospective cohort study, players self-reported health problems, including all injuries and illnesses, regardless of time loss or medical attention, and handball exposure using weekly web-based surveys (OSTRC-H2). Sex differences were estimated using Poisson regression (incidence rates) and binomial regression (weekly average prevalence proportions) with clustered robust standard errors. We included 945 players (age: 14.5 ± 1.5 years; 55% female) from 20 clubs across Denmark. The response proportion to the weekly questionnaires was 63% (range: 42%-79%). The average prevalence proportion of health problems was 23% (95% CI 21%-25%), with 17% (95% CI 15%-19%) attributable to injuries and 6% (95% CI 5%-7%) to illnesses. The overall incidence rate was 14.9 (95% CI 13.9-15.9)/1000 h. Female players aged 13-15 showed a higher incidence rate (15.9 [95% CI 14.2-17.8]/1000 h) compared to age-matched males (13.2 [95% CI 11.5-15.1]/1000 h), with an incidence rate ratio of 1.21 [95% CI 1.0-1.4], and had a higher weekly average prevalence proportion (23% [95% CI 19%-27%]) than age-matched males (12% [95% CI 10%-15%]), corresponding to a difference of 10% points [95% CI 6%-15% points]. COVID-19 infection accounted for 36% of reported illnesses. Our findings highlight the need for injury prevention initiatives to address both sudden-onset and gradual-onset injuries in youth handball players. Sex differences in injury measures and the potential link between illness and injury risk warrant further investigation.
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Grants
- University of Southern Denmark, the Danish Handball Federation, Team Denmark, Danish Gymnastics and Sports Associations, Minestry of Culture in Denmark research funding (grant number FPK.2018-0067), Østifterne (grant number 2020-0277), The Foundation for Advancement of Chiropractic Research and Postgraduate Education (Grant number A3488).
- University of Southern Denmark, the Danish Handball Federation, Team Denmark, Danish Gymnastics and Sports Associations, Minestry of Culture in Denmark research funding (grant number FPK.2018‐0067), Østifterne (grant number 2020‐0277), The Foundation for Advancement of Chiropractic Research and Postgraduate Education (Grant number A3488).
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Affiliation(s)
- Anders Christer Larsen
- Research Unit of Musculoskeletal Function and Physiotherapy, Department of Sports Science and Clinical Biomechanics, the Faculty of Health SciencesUniversity of Southern DenmarkOdenseDenmark
- Department of Public HealthUniversity of Southern DenmarkOdenseDenmark
- Hospital Pharmacy FunenOdense University HospitalOdenseDenmark
| | - Ewa Maria Roos
- Research Unit of Musculoskeletal Function and Physiotherapy, Department of Sports Science and Clinical Biomechanics, the Faculty of Health SciencesUniversity of Southern DenmarkOdenseDenmark
| | - Sören Möller
- Department of Clinical ResearchUniversity of Southern DenmarkOdenseDenmark
- Open Patient Data Explorative NetworkOdense University HospitalOdenseDenmark
| | - Carsten Juhl
- Research Unit of Musculoskeletal Function and Physiotherapy, Department of Sports Science and Clinical Biomechanics, the Faculty of Health SciencesUniversity of Southern DenmarkOdenseDenmark
- Department of Physiotherapy and Occupational TherapyCopenhagen University HospitalHerlevGentofteDenmark
| | - Louise Kamuk Storm
- Research Unit of Psychology of Sport, Excellence and Health, Department of Sports Science and Clinical Biomechanics, The Faculty of Health SciencesUniversity of Southern DenmarkOdenseDenmark
| | - Alice Kongsted
- Research Unit of Clinical Biomechanics, Department of Sports Science and Clinical Biomechanics, The Faculty of Health SciencesUniversity of Southern DenmarkOdenseDenmark
- The Chiropractic Knowledge HubOdenseDenmark
| | - Merete Møller
- Research Unit of Musculoskeletal Function and Physiotherapy, Department of Sports Science and Clinical Biomechanics, the Faculty of Health SciencesUniversity of Southern DenmarkOdenseDenmark
- Department of Sports Medicine, Oslo Sports Trauma Research CenterNorwegian School of Sport SciencesOsloNorway
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Farzana R, Harbarth SJ, Yu LM, Carretto E, Moore CE, Feasey NA, Gales AC, Galal U, Ergonul O, Yong D, Yusuf MA, Veeraraghavan B, Iregbu KC, van Santen JA, Ribeiro ACDS, Fankhauser CM, Chilupsya CJ, Dolecek C, Ferreira DB, Pinarlik F, Jang J, Gücer LS, Cavazzuti L, Sultana M, Haque MDN, Haddad MG, Medugu N, Nwajiobi-Princewill PI, Marrollo R, Zhao R, Baskaran VB, Peter JV, Chandy SJ, Bakthavatchalam YD, Walsh TR. The impact of the COVID-19 pandemic on antimicrobial usage: an international patient-level cohort study. JAC Antimicrob Resist 2025; 7:dlaf037. [PMID: 40151230 PMCID: PMC11945301 DOI: 10.1093/jacamr/dlaf037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2025] [Accepted: 02/26/2025] [Indexed: 03/29/2025] Open
Abstract
Background This study aimed to evaluate the trends in antimicrobial prescription during the first 1.5 years of COVID-19 pandemic. Methods This was an observational, retrospective cohort study using patient-level data from Bangladesh, Brazil, India, Italy, Malawi, Nigeria, South Korea, Switzerland and Turkey from patients with pneumonia and/or acute respiratory distress syndrome and/or sepsis, regardless of COVID-19 positivity, who were admitted to critical care units or COVID-19 specialized wards. The changes of antimicrobial prescription between pre-pandemic and pandemic were estimated using logistic or linear regression. Pandemic effects on month-wise antimicrobial usage were evaluated using interrupted time series analyses (ITSAs). Results Antimicrobials for which prescriptions significantly increased during the pandemic were as follows: meropenem in Bangladesh (95% CI: 1.94-4.07) with increased prescribed daily dose (PDD) (95% CI: 1.17-1.58) and Turkey (95% CI: 1.09-1.58), moxifloxacin in Bangladesh (95% CI: 4.11-11.87) with increased days of therapy (DOT) (95% CI: 1.14-2.56), piperacillin/tazobactam in Italy (95% CI: 1.07-1.48) with increased DOT (95% CI: 1.01-1.25) and PDD (95% CI: 1.05-1.21) and azithromycin in Bangladesh (95% CI: 3.36-21.77) and Brazil (95% CI: 2.33-8.42). ITSA showed a significant drop in azithromycin usage in India (95% CI: -8.38 to -3.49 g/100 patients) and South Korea (95% CI: -2.83 to -1.89 g/100 patients) after WHO guidelines v1 release and increased meropenem usage (95% CI: 93.40-126.48 g/100 patients) and moxifloxacin (95% CI: 5.40-13.98 g/100 patients) in Bangladesh and sulfamethoxazole/trimethoprim in India (95% CI: 0.92-9.32 g/100 patients) following the Delta variant emergence. Conclusions This study reinforces the importance of developing antimicrobial stewardship in the clinical settings during inter-pandemic periods.
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Affiliation(s)
- Refath Farzana
- Department of Biology, Ineos Oxford Institute for Antimicrobial Research, University of Oxford, Oxford, UK
| | - Stephan Jürgen Harbarth
- Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland
- WHO Collaborating Center for Antimicrobial Resistance and Infection Control, Geneva, Switzerland
| | - Ly-Mee Yu
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Edoardo Carretto
- Clinical Microbiology Laboratory, IRCCS Azienda Unità Sanitaria Locale, Reggio Emilia, Italy
| | - Catrin E Moore
- Institute for Infection and Immunity, St George’s, University of London, London, UK
| | - Nicholas Alexander Feasey
- School of Medicine, University of St Andrews, St Andrews, Fife, UK
- Malawi Liverpool Wellcome Programme, Kamuzu University of Health Sciences, Blantyre, Malawi
| | - Ana C Gales
- Division of Infectious Diseases, Universidade Federal de São Paulo, São Paulo, Brazil
- Antimicrobial Resistance Institute of São Paulo (ARIES), São Paulo, Brazil
| | - Ushma Galal
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Onder Ergonul
- Koc University İşbank Center for Infectious Diseases, Koc University, Istanbul, Türkiye
- School of Medicine, Koç University, Istanbul, Türkiye
| | - Dongeun Yong
- Department of Laboratory Medicine and Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, South Korea
| | - Md Abdullah Yusuf
- Department of Microbiology, National Institute of Neurosciences and Hospital, Dhaka, Bangladesh
| | | | - Kenneth Chukwuemeka Iregbu
- Department of Microbiology, University of Abuja, Abuja, Nigeria
- Department of Microbiology, National Hospital Abuja, Abuja, Nigeria
| | | | - Aghata Cardoso da Silva Ribeiro
- Division of Infectious Diseases, Universidade Federal de São Paulo, São Paulo, Brazil
- Antimicrobial Resistance Institute of São Paulo (ARIES), São Paulo, Brazil
| | | | | | - Christiane Dolecek
- Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
| | - Diogo Boldim Ferreira
- Division of Infectious Diseases, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Fatihan Pinarlik
- Koc University İşbank Center for Infectious Diseases, Koc University, Istanbul, Türkiye
- Graduate School of Health Sciences, Koc University, Istanbul, Türkiye
| | - Jaehyeok Jang
- Department of Laboratory Medicine and Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, South Korea
| | - Lal Sude Gücer
- Koc University İşbank Center for Infectious Diseases, Koc University, Istanbul, Türkiye
- School of Medicine, Koç University, Istanbul, Türkiye
| | - Laura Cavazzuti
- Hospital Hygiene Unit, IRCCS Azienda Unità Sanitaria Locale, Reggio Emilia, Italy
| | - Marufa Sultana
- Department of Microbiology, National Institute of Neurosciences and Hospital, Dhaka, Bangladesh
- Administration, Dhaka Medical College Hospital, Dhaka, Bangladesh
| | - M D Nazmul Haque
- Administration, Dhaka Medical College Hospital, Dhaka, Bangladesh
- Combined Military Hospital, Jashore Cantonment, Jashore, Bangladesh
| | | | - Nubwa Medugu
- Department of Microbiology, National Hospital Abuja, Abuja, Nigeria
- Department of Microbiology, Nile University of Nigeria, Abuja, Nigeria
| | | | - Roberta Marrollo
- Clinical Microbiology Laboratory, IRCCS Azienda Unità Sanitaria Locale, Reggio Emilia, Italy
| | - Rui Zhao
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - J V Peter
- Medical Intensive Care Unit, Christian Medical College, Vellore, India
| | - Sujith J Chandy
- Department of Pharmacology & Clinical Pharmacology, Christian Medical College, Vellore, India
| | | | - Timothy R Walsh
- Department of Biology, Ineos Oxford Institute for Antimicrobial Research, University of Oxford, Oxford, UK
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Gao LP, Zheng CJ, Tian TT, Brima Tia A, Abdulai MK, Xiao K, Chen C, Liang DL, Shi Q, Liu ZG, Dong XP. Spatiotemporal prevalence of COVID-19 and SARS-CoV-2 variants in Africa. Front Public Health 2025; 13:1526727. [PMID: 40051513 PMCID: PMC11882590 DOI: 10.3389/fpubh.2025.1526727] [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: 11/12/2024] [Accepted: 02/03/2025] [Indexed: 03/09/2025] Open
Abstract
Introduction The coronavirus disease 2019 (COVID-19) pandemic has caused significant public health and socioeconomic crises across Africa; however, the prevalent patterns of COVID-19 and the circulating characteristics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in the continent remain insufficiently documented. Methods In this study, national data on case numbers, infection incidences, mortality rates, the circulation of SARS-CoV-2 variants, and key health indexes were collected from various official and professional sources between January 2020 and December 2023 were analyzed with SaTScan and geographically weighted regression (GWR). Results The prevalent profiles and circulating features of SARS-CoV-2 across the African continent, including its five regions and all African countries, were analyzed. Four major waves of the epidemic were observed. The first wave was closely associated with the introduction of the early SARS-CoV-2 strain while the subsequent waves were linked to the emergence of specific variants, including variants of concern (VOCs) Alpha, Beta, variants of interest (VOIs) Eta (second wave), VOC Delta (third wave), and VOC Omicron (fourth wave). SaTScan analysis identified four large spatiotemporal clusters that affected various countries. A significant number of countries (50 out of 56) reported their first cases during February 2020 and March 2020, predominantly involving individuals with confirmed cross-continental travel histories, mainly from Europe. In total, 12 distinct SARS-CoV-2 VOCs and VOIs were identified, with the most prevalent being VOCs Omicron, Delta, Beta, Alpha, and VOI Eta. Unlike the dominance of VOC Delta during the third wave and Omicron during the fourth wave, VOC Alpha was relatively rare in the Southern regions but more common in the other four regions. At the same time, Beta predominated in the Southern region and Eta in the Western region during the second wave. Additionally, relatively higher COVID-19 case incidences and mortalities were reported in the Southern and Northern African regions. Spearman rank correlation and geographically weighted regression (GWR) analyses of COVID-19 incidences against health indexes in 52 African countries indicate that countries with higher national health expenditures and better personnel indexes tended to report higher case incidences. Discussion This study offers a detailed overview of the COVID-19 pandemic in Africa. Strengthening the capacity of health institutions across African countries is essential for the timely detection of new SARS-CoV-2 variants and, consequently, for preparedness against future COVID-19 pandemics and other potentially infectious disease outbreaks.
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Affiliation(s)
- Li-Ping Gao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Can-Jun Zheng
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ting-Ting Tian
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Alie Brima Tia
- Sierra Leone-China Friendship Biological Safety Laboratory, Freetown, Sierra Leone
| | - Michael K. Abdulai
- Sierra Leone-China Friendship Biological Safety Laboratory, Freetown, Sierra Leone
| | - Kang Xiao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Cao Chen
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Dong-Lin Liang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qi Shi
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhi-Guo Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiao-Ping Dong
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Shanghai Institute of Infectious Disease and Biosafety, Shanghai, China
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4
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Cerrai S, Carreras G, Monti F, Stival C, Lugo A, Bosetti C, Biagioni S, Fanucchi T, Gorini G, Amerio A, Mastrobattista L, Mortali C, Odone A, Molinaro S, Smits L, Gallus S. Changes in Alcohol Consumption During and After the Covid-19 Pandemic From 2020 to 2023 in a Prospective Cohort of Italian Adults. J Epidemiol 2025; 35:63-70. [PMID: 39694502 PMCID: PMC11706678 DOI: 10.2188/jea.je20230340] [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: 12/01/2023] [Accepted: 03/14/2024] [Indexed: 12/20/2024] Open
Abstract
BACKGROUND The lockdowns imposed by the government during coronavirus disease 2019 (COVID-19) pandemic have had a significant impact on the Italian population habits. METHODS LOckdown and lifeSTyles in Italy and in Tuscany studies collected data on a representative sample of the Italian adult population in 2020 (n = 6,003) followed up through 2023 via four additional surveys (3,000 ≤ n ≤ 6,600) through an online self-administered questionnaire. The Alcohol Use Disorders Identification Test-Concise was used to identify at-risk drinkers. Considering the cohort of individuals who took part to the first and at least one other wave (n = 5,378), a multilevel logistic model was used to derive odds ratios (ORs) and corresponding 95% confidence intervals (CIs) of being at-risk drinkers. RESULTS The prevalence of at-risk drinkers was 26.4% before, 23.4% during the first lockdown, and stabilized around 30.0% thereafter. Being at-risk alcohol consumers decreased with decreasing economic status (P for trend <0.001), was less frequent among middle-aged compared to younger (OR 0.73; 95% CI, 0.60-0.89) and among divorced/separated (OR 0.77; 95% CI, 0.60-0.99) or single (OR 0.75; 95% CI, 0.64-0.89) compared to married individuals. It was more frequent among individuals with anxiety or depressive symptoms (OR 1.24; 95% CI, 1.12-1.37), those using psychotropic drugs (OR 1.99; 95% CI, 1.69-2.35) and users of conventional and/or alternative nicotine products (OR 3.67; 95% CI, 3.00-4.48). CONCLUSION The long-term trends in alcohol consumption after the COVID-19 pandemic are unfavorable in Italy. The results point to an increased vulnerability for at-risk alcohol consumption among younger individuals, women with higher economic status, and married individuals. At-risk drinking is strongly related to mental health symptoms and nicotine consumption.
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Affiliation(s)
- Sonia Cerrai
- National Research Council, Institute of Clinical Physiology (CNR-IFC), Pisa, Italy
- Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Giulia Carreras
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Filippo Monti
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Chiara Stival
- Department of Medical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Alessandra Lugo
- Department of Medical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Cristina Bosetti
- Department of Medical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Silvia Biagioni
- National Research Council, Institute of Clinical Physiology (CNR-IFC), Pisa, Italy
- Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy
| | - Tiziana Fanucchi
- Unit of Health Promotion, Epidemiology, and Government of Territorial Demand, ASST Fatebenefratelli Sacco, Milan, Italy
| | - Giuseppe Gorini
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | | | | | | | - Anna Odone
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy
| | - Sabrina Molinaro
- National Research Council, Institute of Clinical Physiology (CNR-IFC), Pisa, Italy
| | - Luc Smits
- Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Silvano Gallus
- Department of Medical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - the “Lost in Italy” and “Lost in Toscana” Study Investigators*
- National Research Council, Institute of Clinical Physiology (CNR-IFC), Pisa, Italy
- Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
- Department of Medical Epidemiology, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
- Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy
- Unit of Health Promotion, Epidemiology, and Government of Territorial Demand, ASST Fatebenefratelli Sacco, Milan, Italy
- University of Genoa, Genoa, Italy
- Istituto Superiore di Sanità, Rome, Italy
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy
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Phang P, Ling CYF, Liew SH, Razak FA, Wiwatanapataphee B. Nonlinear time series analysis of state-wise COVID-19 in Malaysia using wavelet and persistent homology. Sci Rep 2024; 14:27562. [PMID: 39528569 PMCID: PMC11555112 DOI: 10.1038/s41598-024-79002-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 11/05/2024] [Indexed: 11/16/2024] Open
Abstract
The nonlinear progression of COVID-19 positive cases, their fluctuations, the correlations in amplitudes and phases across different regions, along with seasonality or periodicity, pose challenges to thoroughly examining the data for revealing similarities or detecting anomalous trajectories. To address this, we conducted a nonlinear time series analysis combining wavelet and persistent homology to detect the qualitative properties underlying COVID-19 daily infection numbers at the state level from the pandemic's onset to June 2024 in Malaysia. The first phase involved investigating the evolution of daily confirmed cases by state in the time-frequency domain using wavelets. Subsequently, a topological feature-based time series clustering is performed by reconstructing a higher-dimensional phase space through a delay embedding method. Our findings reveal a prominent 7-day periodicity in case numbers from mid-2021 to the end of 2022. The state-wise daily cases are moderately correlated in both amplitudes and phases during the Delta and Omicron waves. Biweekly averaged data significantly enhances the detection of topological loops associated with these waves. Selangor demonstrates unique case trajectories, while Pahang shows the highest similarity with other states. This methodological framework provides a more detailed understanding of epidemiological time series data, offering valuable insights for preparing for future public health crises.
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Affiliation(s)
- Piau Phang
- Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300, Kota Samarahan, Sarawak, Malaysia.
| | - Carey Yu-Fan Ling
- Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300, Kota Samarahan, Sarawak, Malaysia
| | - Siaw-Hong Liew
- Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300, Kota Samarahan, Sarawak, Malaysia
| | - Fatimah Abdul Razak
- Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia
| | - Benchawan Wiwatanapataphee
- School of Electrical Engineering, Computing and Mathematical Science, Curtin University, Perth, WA, 6845, Australia
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Edrees WH, Abdullah QY, Al-Shehari WA, Alrahabi LM, Khardesh AAF. COVID-19 pandemic in Taiz Governorate, Yemen, between 2020 and 2023. BMC Infect Dis 2024; 24:739. [PMID: 39060993 PMCID: PMC11282764 DOI: 10.1186/s12879-024-09650-0] [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: 01/29/2024] [Accepted: 07/23/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND The coronavirus disease 2019 (COVID-19) is highly contagious and causes a series of health problems, particularly in Yemen, which has a fragile healthcare system and cannot handle public health emergencies. AIMS This analysis aimed to determine the epidemiological status of COVID-19 in the Taiz governorate between April 2020 and December 2023. METHODS A retrospective study based on surveillance data from the Taiz governorate was used. The required data were gathered from the Ministry of Health and Population in Aden and analyzed using SPSS. RESULTS Out of 5826 suspected of COVID-19 cases, 1933 (33.18%) cases were positive for COVID-19 infection. The high rates of COVID-19 cases were reported at 35.40% in males, 37.80% in people aged 35-44 years, 47.20% in 2020, 72.73% in Dhubab district, and 27.78% in March 2021. The overall incidence rate of cases was reported at 6.2 per 10,000 people in Taiz governorate (8.85 in males and 3.80 in females). In addition, the high incidence rate of COVID-19 was observed among age groups ≥ 65 years, in 2021, and in Al-Mukha districts. In total, the rate of fatality cases was 14.12%, the higher rate of fatality cases was 15.46% among males and 32.23% among individuals aged ≥ 65 years, and 26.97% in 2020. CONCLUSION In this finding, the incidence rate of COVID-19 is high. It is necessary to increase the public's awareness of the transmission and prevention methods of COVID-19, as well as implement appropriate strategies to protect populations from infectious diseases.
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Affiliation(s)
- Wadhah Hassan Edrees
- Medical Microbiology Department, Faculty of Applied Sciences, Hajjah University, Hajjah, Yemen.
- Medical Laboratory Department, Faculty of Medical Sciences, Al-Razi University, Sana'a, Yemen.
| | - Qais Yusuf Abdullah
- Microbiology/Biological Sciences, Faculty of Sciences, Sana'a University, Sana'a, Yemen
| | | | - Lutf Mohammed Alrahabi
- Medical Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Sana'a University, Sana'a, Yemen
- Dental Department, Faculty of Medical Sciences, Queen Arwa University, Sana'a, Yemen
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Javed H, Khaliq A, Mirza S, Khan R, Fatima W. Evolution of COVID-19 infection in Punjab; trends during five waves of infection in the province of Punjab. BMC Infect Dis 2024; 24:348. [PMID: 38528471 DOI: 10.1186/s12879-024-09157-8] [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: 09/18/2023] [Accepted: 02/20/2024] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND Pakistan witnessed five waves of COVID-19 infections during the pandemic. Punjab, the largest province of Pakistan, remained the epicentre due to a high infection rate. Administrative data for five waves of the pandemic was analyzed to determine the rate of infections and the significance of pharmacological and non-pharmacological interventions on the severity and duration of infection. METHODOLOGY COVID-19 data from March 2020 to May 2023 was obtained from the Provincial Public Health Reference Laboratory (PPHRL), Punjab AIDS Control Program, Lahore. The data included samples from index cases, contacts, and recovered patients. A total of 36,252,48 cases were screened for COVID-19, and 90,923 (2.50%) were detected positive by RT-PCR, accounting for 5.69% of the cases reported positive throughout the country. RESULTS Among the positive cases, 50.86% (n = 46,244) cases were new cases (registered for the first time), 40.41% (n = 36751) were the contact cases traced from the newly identified cases and 8.62% (n = 7842) repeated cases. The positivity rates among index cases were reported to be 2.37%, 2.34%, 4.61%, 2.09%, and 1.19%, respectively, for the five respective COVID-19 pandemic waves. Distribution by gender indicated that 64% of males and 35% of females were infected during the pandemic. The age factor demonstrated the most susceptibility to infection in women aged 19-29 years, whereas most males between the ages of 29-39 had an infection. Susceptibility to COVID-19 infection was observed to be equally likely between males and females; however, clinical outcomes indicated that infections in males were more severe and often resulted in fatalities as compared to those in females. This trend was also reflected in the viral titer as measured by the Ct values, where 40% of males had Ct values < 25 (an indicator of high viral titers) compared to 30% of females with Ct values < 25. CONCLUSION Overall, our data indicated that infection rates remained stable throughout the pandemic except for 3rd wave, which showed a higher incidence of infection rate of 4%. Additionally, data showed a positive impact of masking, social distancing, and immunization, as indicated by the shorter window of high infection rates.
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Affiliation(s)
- Hasnain Javed
- Provincial Public Health Reference Laboratory, Punjab AIDS Control Program, Lahore, Pakistan
| | - Aasia Khaliq
- Department of Life Sciences, Lahore University of Management Sciences (LUMS), Lahore, Pakistan
| | - Shaper Mirza
- Department of Life Sciences, Lahore University of Management Sciences (LUMS), Lahore, Pakistan.
| | - Rimsha Khan
- Provincial Public Health Reference Laboratory, Punjab AIDS Control Program, Lahore, Pakistan
- Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | - Warda Fatima
- Institute of Microbiology and Molecular Genetics, University of the Punjab, Lahore, Pakistan
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8
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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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9
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Shafiee A, Jafarabady K, Rajai S, Mohammadi I, Mozhgani SH. Sleep disturbance increases the risk of severity and acquisition of COVID-19: a systematic review and meta-analysis. Eur J Med Res 2023; 28:442. [PMID: 37853444 PMCID: PMC10583304 DOI: 10.1186/s40001-023-01415-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 09/30/2023] [Indexed: 10/20/2023] Open
Abstract
BACKGROUND Understanding the association between sleep quality and COVID-19 outcomes is crucial for effective preventive strategies and patient management. This systematic review aims to evaluate the impact of sleep quality as a risk factor for acquiring COVID-19 infection and the severity of the disease. METHODS A comprehensive search of electronic databases was conducted to identify relevant studies published from the inception of the COVID-19 pandemic which was 31st of December 2019 until 30 April 2023. Studies investigating the relationship between sleep quality and COVID-19 infection, or disease severity were included. Random effect meta-analysis was performed with odds ratios (OR) and their 95% confidence intervals (95% CI) as effect measures. RESULTS Out of the initial 1,132 articles identified, 12 studies met the inclusion criteria. All studies were observational studies (cohort, case-control, and cross-sectional). The association between sleep quality and COVID-19 infection risk was examined in 6 studies, The results of our meta-analysis showed that participants with poor sleep quality showed a 16% increase regarding the risk of COVID-19 acquisition (OR 1.16; 95% CI 1.03, 1.32; I2 = 65.2%, p = 0.02). Our results showed that participants with poor sleep quality showed a 51% increase in the incidence of primary composite outcome (OR 1.51; 95% CI 1.25, 1.81; I2 = 57.85%, p < 0.001). The result of our subgroup analysis also showed significantly increased risk of mortality (RR 0.67; 95% CI 0.50, 0.90; I2 = 31%, p = 0.008), and disease severity (OR 1.47; 95% CI 1.19, 1.80; I2 = 3.21%, p < 0.001) when comparing poor sleep group to those with good sleep quality. CONCLUSION This study highlights a significant association between poor sleep quality and an increased risk of COVID-19 infection as well as worse disease clinical outcomes.
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Affiliation(s)
- Arman Shafiee
- Department of Psychiatry and Mental Health, Alborz University of Medical Sciences, Karaj, Iran.
- Student Research Committee, School of Medicine, Alborz University of Medical Sciences, Karaj, Iran.
| | - Kyana Jafarabady
- Student Research Committee, School of Medicine, Alborz University of Medical Sciences, Karaj, Iran
| | - Shahryar Rajai
- School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Ida Mohammadi
- School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Sayed-Hamidreza Mozhgani
- Department of Microbiology, School of Medicine, Alborz University of Medical Sciences, Karaj, Iran.
- Non-Communicable Diseases Research Center, Alborz University of Medical, Sciences, Karaj, Iran.
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10
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Phang P, Labadin J, Suhaila J, Aslam S, Hazmi H. Exploration of spatiotemporal heterogeneity and socio-demographic determinants on COVID-19 incidence rates in Sarawak, Malaysia. BMC Public Health 2023; 23:1396. [PMID: 37474904 PMCID: PMC10357875 DOI: 10.1186/s12889-023-16300-8] [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: 03/16/2023] [Accepted: 07/12/2023] [Indexed: 07/22/2023] Open
Abstract
BACKGROUND In Sarawak, 252 300 coronavirus disease 2019 (COVID-19) cases have been recorded with 1 619 fatalities in 2021, compared to only 1 117 cases in 2020. Since Sarawak is geographically separated from Peninsular Malaysia and half of its population resides in rural districts where medical resources are limited, the analysis of spatiotemporal heterogeneity of disease incidence rates and their relationship with socio-demographic factors are crucial in understanding the spread of the disease in Sarawak. METHODS The spatial dependence of district-wise incidence rates is investigated using spatial autocorrelation analysis with two orders of contiguity weights for various pandemic waves. Nine determinants are chosen from 14 covariates of socio-demographic factors via elastic net regression and recursive partitioning. The relationships between incidence rates and socio-demographic factors are examined using ordinary least squares, spatial lag and spatial error models, and geographically weighted regression. RESULTS In the first 8 months of 2021, COVID-19 severely affected Sarawak's central region, which was followed by the southern region in the next 2 months. In the third wave, based on second-order spatial weights, the incidence rate in a district is most strongly influenced by its neighboring districts' rate, although the variance of incidence rates is best explained by local regression coefficient estimates of socio-demographic factors in the first wave. It is discovered that the percentage of households with garbage collection facilities, population density and the proportion of male in the population are positively associated with the increase in COVID-19 incidence rates. CONCLUSION This research provides useful insights for the State Government and public health authorities to critically incorporate socio-demographic characteristics of local communities into evidence-based decision-making for altering disease monitoring and response plans. Policymakers can make well-informed judgments and implement targeted interventions by having an in-depth understanding of the spatial patterns and relationships between COVID-19 incidence rates and socio-demographic characteristics. This will effectively help in mitigating the spread of the disease.
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Affiliation(s)
- Piau Phang
- Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, 94300, Sarawak, Malaysia.
| | - Jane Labadin
- Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, 94300, Sarawak, Malaysia
| | - Jamaludin Suhaila
- Department of Mathematical Science, Faculty of Science, Universiti Teknologi Malaysia, Skudai, 81310, Johor, Malaysia
| | - Saira Aslam
- Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, 94300, Sarawak, Malaysia
| | - Helmy Hazmi
- Faculty of Medicine and Health Science, Universiti Malaysia Sarawak, Kota Samarahan, 94300, Sarawak, Malaysia
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11
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Wang J, Huang L, Guo N, Yao YP, Zhang C, Xu R, Jiao YM, Li YQ, Song YR, Wang FS, Fan X. Dynamics of SARS-CoV-2 Antibody Responses up to 9 Months Post-Vaccination in Individuals with Previous SARS-CoV-2 Infection Receiving Inactivated Vaccines. Viruses 2023; 15:v15040917. [PMID: 37112897 PMCID: PMC10145073 DOI: 10.3390/v15040917] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/20/2023] [Accepted: 03/24/2023] [Indexed: 04/07/2023] Open
Abstract
Humoral immunity confers protection against COVID-19. The longevity of antibody responses after receiving an inactivated vaccine in individuals with previous SARS-CoV-2 infection is unclear. Plasma samples were collected from 58 individuals with previous SARS-CoV-2 infection and 25 healthy donors (HDs) who had been vaccinated with an inactivated vaccine. The neutralizing antibodies (NAbs) and S1 domain-specific antibodies against the SARS-CoV-2 wild-type and Omicron strains and nucleoside protein (NP)-specific antibodies were measured using a chemiluminescent immunoassay. Statistical analysis was performed using clinical variables and antibodies at different timepoints after SARS-CoV-2 vaccination. NAbs targeting the wild-type or Omicron strain were detected in individuals with previous SARS-CoV-2 infection at 12 months after infection (wild-type: 81%, geometric mean (GM): 20.3 AU/mL; Omicron: 44%, GM: 9.4 AU/mL), and vaccination provided further enhancement of these antibody levels (wild-type: 98%, GM: 53.3 AU/mL; Omicron: 75%, GM: 27.8 AU/mL, at 3 months after vaccination), which were significantly higher than those in HDs receiving a third dose of inactivated vaccine (wild-type: 85%, GM: 33.6 AU/mL; Omicron: 45%, GM: 11.5 AU/mL). The level of NAbs in individuals with previous infection plateaued 6 months after vaccination, but the NAb levels in HDs declined continuously. NAb levels in individuals with previous infection at 3 months post-vaccination were strongly correlated with those at 6 months post-vaccination, and weakly correlated with those before vaccination. NAb levels declined substantially in most individuals, and the rate of antibody decay was negatively correlated with the neutrophil-to-lymphocyte ratio in the blood at discharge. These results suggest that the inactivated vaccine induced robust and durable NAb responses in individuals with previous infection up to 9 months after vaccination.
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Affiliation(s)
- Jing Wang
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
- Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China
| | - Lei Huang
- Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China
| | - Nan Guo
- Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China
- Chinese PLA Medical School, Beijing 100853, China
| | - Ya-Ping Yao
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
- Senior Department of Infectious Diseases, Fifth Medical Center of Chinese PLA General Hospital, Beijing 100039, China
| | - Chao Zhang
- Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China
| | - Ruonan Xu
- Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China
| | - Yan-Mei Jiao
- Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China
| | - Ya-Qun Li
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
- Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China
| | - Yao-Ru Song
- Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China
- Chinese PLA Medical School, Beijing 100853, China
| | - Fu-Sheng Wang
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
- Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China
| | - Xing Fan
- Department of Infectious Diseases, The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing 100039, China
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12
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Olaiz G, Bertozzi SM, Juárez-Flores A, Borja-Aburto VH, Vicuña F, Ascencio-Montiel IJ, Gutiérrez JP. Evolution of differences in clinical presentation across epidemic waves among patients with COVID-like-symptoms who received care at the Mexican Social Security Institute. Front Public Health 2023; 11:1102498. [PMID: 36923037 PMCID: PMC10009173 DOI: 10.3389/fpubh.2023.1102498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 02/07/2023] [Indexed: 03/02/2023] Open
Abstract
Background Timely monitoring of SARS-CoV-2 variants is crucial to effectively managing both prevention and treatment efforts. In this paper, we aim to describe demographic and clinical patterns of individuals with COVID-19-like symptoms during the first three epidemic waves in Mexico to identify changes in those patterns that may reflect differences determined by virus variants. Methods We conducted a descriptive analysis of a large database containing records for all individuals who sought care at the Mexican Social Security Institute (IMSS) due to COVID-19-like symptoms from March 2020 to October 2021 (4.48 million records). We described the clinical and demographic profile of individuals tested (3.38 million, 32% with PCR and 68% with rapid test) by test result (positives and negatives) and untested, and among those tested, and the changes in those profiles across the first three epidemic waves. Results Individuals with COVID-19-like symptoms were older in the first wave and younger in the third one (the mean age for those positive was 46.6 in the first wave and 36.1 in the third wave; for negatives and not-tested, the mean age was 41 and 38.5 in the first wave and 34.3 and 33.5 in the third wave). As the pandemic progressed, an increasing number of individuals sought care for suspected COVID-19. The positivity rate decreased over time but remained well over the recommended 5%. The pattern of presenting symptoms changed over time, with some of those symptoms decreasing over time (dyspnea 40.6 to 14.0%, cough 80.4 to 76.2%, fever 77.5 to 65.2%, headache 80.3 to 78.5%), and some increasing (odynophagia 48.7 to 58.5%, rhinorrhea 28.6 to 47.5%, anosmia 11.8 to 23.2%, dysgeusia 11.2 to 23.2%). Conclusion During epidemic surges, the general consensus was that any individual presenting with respiratory symptoms was a suspected COVID-19 case. However, symptoms and signs are dynamic, with clinical patterns changing not only with the evolution of the virus but also with demographic changes in the affected population. A better understanding of these changing patterns is needed to improve preparedness for future surges and pandemics.
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Affiliation(s)
- Gustavo Olaiz
- Center for Policy, Population and Health Research, School of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - Stefano M. Bertozzi
- School of Public Health, University of California, Berkeley, Berkeley, CA, United States
- Department of Global Health, University of Washington, Seattle, WA, United States
- National Institute of Public Health, Mexico (INSP), Cuernavaca, Mexico
| | - Arturo Juárez-Flores
- Center for Policy, Population and Health Research, School of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | | | - Félix Vicuña
- Center for Policy, Population and Health Research, School of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - Iván J. Ascencio-Montiel
- Coordination of Epidemiological Surveillance, Mexican Institute of Social Security, Mexico City, Mexico
| | - Juan Pablo Gutiérrez
- Center for Policy, Population and Health Research, School of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
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13
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Peng S, Tian Y, Meng L, Fang R, Chang W, Yang Y, Li S, Shen Q, Ni J, Zhu W. The safety of COVID-19 vaccines in patients with myasthenia gravis: A scoping review. Front Immunol 2022; 13:1103020. [PMID: 36618419 PMCID: PMC9812949 DOI: 10.3389/fimmu.2022.1103020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Accepted: 12/06/2022] [Indexed: 12/24/2022] Open
Abstract
Background COVID-19 vaccines are required for individuals with myasthenia gravis (MG), as these patients are more likely to experience severe pneumonia, myasthenia crises, and higher mortality rate. However, direct data on the safety of COVID-19 vaccines in patients with MG are lacking, which results in hesitation in vaccination. This scoping was conducted to collect and summarize the existing evidence on this issue. Methods PubMed, Cochrane Library, and Web of Science were searched for studies using inclusion and exclusion criteria. Article titles, authors, study designs, demographics of patients, vaccination information, adverse events (AEs), significant findings, and conclusions of included studies were recorded and summarized. Results Twenty-nine studies conducted in 16 different countries in 2021 and 2022 were included. Study designs included case report, case series, cohort study, cross-sectional study, survey-based study, chart review, and systemic review. A total of 1347 patients were included. The vaccines used included BNT162b2, mRNA-1273, ChAdOx1 nCoV-19, inactivated vaccines, and recombinant subunit vaccines. Fifteen case studies included 48 patients reported that 23 experienced new-onset, and five patients experienced flare of symptoms. Eleven other types of studies included 1299 patients reported that nine patients experienced new-onset, and 60 participants experienced flare of symptoms. Common AEs included local pain, fatigue, asthenia, cephalalgia, fever, and myalgia. Most patients responded well to treatment without severe sequelae. Evidence gaps include limited strength of study designs, type and dose of vaccines varied, inconsistent window of risk and exacerbation criteria, limited number of participants, and lack of efficacy evaluation. Conclusion COVID-19 vaccines may cause new-onset or worsening of MG in a small proportion of population. Large-scale, multicenter, prospective, and rigorous studies are required to verify their safety.
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Affiliation(s)
- Siyang Peng
- Department of Acupuncture, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yukun Tian
- Department of Acupuncture, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Linghao Meng
- Department of Acupuncture, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ruiying Fang
- Department of Acupuncture, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Weiqian Chang
- Department of Acupuncture, Guang’anmen Hospital, Chinese Academy of Traditional Chinese Medicine Ji’nan Hospital (Ji’nan Hospital of Traditional Chinese Medicine), Shandong, China
| | - Yajing Yang
- Department of Traditional Chinese Medicine, Yuyuantan Community Health Center, Beijing, China
| | - Shaohong Li
- Treatment Center of Traditional Chinese Medicine, Beijing Bo’ai Hospital, China Rehabilitation Research Center, Beijing, China
- Treatment Center of Traditional Chinese Medicine, School of Rehabilitation, Capital Medical University, Beijing, China
| | - Qiqi Shen
- Department of Acupuncture, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jinxia Ni
- Department of Acupuncture, Dongzhimen Hospital of Beijing University of Traditional Chinese Medicine, Beijing, China
| | - Wenzeng Zhu
- Department of Acupuncture, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
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