1
|
Kwok KO, Wei WI, Mcneil EB, Tang A, Tang JWT, Wong SYS, Yeoh EK. Comparative analysis of symptom profile and risk of death associated with infection by SARS-CoV-2 and its variants in Hong Kong. J Med Virol 2024; 96:e29326. [PMID: 38345166 DOI: 10.1002/jmv.29326] [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: 06/14/2023] [Revised: 11/19/2023] [Accepted: 12/07/2023] [Indexed: 02/15/2024]
Abstract
The recurrent multiwave nature of coronavirus disease 2019 (COVID-19) necessitates updating its symptomatology. We characterize the effect of variants on symptom presentation, identify the symptoms predictive and protective of death, and quantify the effect of vaccination on symptom development. With the COVID-19 cases reported up to August 25, 2022 in Hong Kong, an iterative multitier text-matching algorithm was developed to identify symptoms from free text. Multivariate regression was used to measure associations between variants, symptom development, death, and vaccination status. A least absolute shrinkage and selection operator technique was used to identify a parsimonious set of symptoms jointly associated with death. Overall, 70.9% (54 450/76 762) of cases were symptomatic with 102 symptoms identified. Intrinsically, the wild-type and delta variant caused similar symptoms among unvaccinated symptomatic cases, whereas the wild-type and omicron BA.2 subvariant had heterogeneous patterns, with seven symptoms (fatigue, fever, chest pain, runny nose, sputum production, nausea/vomiting, and sore throat) more frequent in the BA.2 cohort. With ≥2 vaccine doses, BA.2 was more likely than delta to cause fever among symptomatic cases. Fever, blocked nose, pneumonia, and shortness of breath remained jointly predictive of death among unvaccinated symptomatic elderly in the wild-type-to-omicron transition. Number of vaccine doses required for reducing occurrence varied by symptoms. We substantiate that omicron has a different clinical presentation compared to previous variants. Syndromic surveillance can be bettered with reduced reliance on symptom-based case identification, increased weighing on symptoms predictive of death in outcome prediction, individual-based risk assessment in care homes, and incorporating free-text symptom reporting.
Collapse
Affiliation(s)
- Kin On Kwok
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Stanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Asia-Pacific Studies, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Wan In Wei
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Edward B Mcneil
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Arthur Tang
- School of Science, Engineering and Technology, RMIT University, Ho Chi Minh City, Vietnam
| | - Julian W-T Tang
- Department of Respiratory Sciences, University of Leicester, Leicester, United Kingdom
- Department of Clinical Microbiology, Leicester Royal Infirmary, Leicester, United Kingdom
| | - Samuel Y S Wong
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Eng Kiong Yeoh
- Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| |
Collapse
|
2
|
Lewis HC, Ware H, Whelan M, Subissi L, Li Z, Ma X, Nardone A, Valenciano M, Cheng B, Noel K, Cao C, Yanes-Lane M, Herring BL, Talisuna A, Ngoy N, Balde T, Clifton D, Van Kerkhove MD, Buckeridge D, Bobrovitz N, Okeibunor J, Arora RK, Bergeri I. SARS-CoV-2 infection in Africa: a systematic review and meta-analysis of standardised seroprevalence studies, from January 2020 to December 2021. BMJ Glob Health 2022; 7:e008793. [PMID: 35998978 PMCID: PMC9402450 DOI: 10.1136/bmjgh-2022-008793] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 06/28/2022] [Indexed: 01/08/2023] Open
Abstract
INTRODUCTION Estimating COVID-19 cumulative incidence in Africa remains problematic due to challenges in contact tracing, routine surveillance systems and laboratory testing capacities and strategies. We undertook a meta-analysis of population-based seroprevalence studies to estimate SARS-CoV-2 seroprevalence in Africa to inform evidence-based decision making on public health and social measures (PHSM) and vaccine strategy. METHODS We searched for seroprevalence studies conducted in Africa published 1 January 2020-30 December 2021 in Medline, Embase, Web of Science and Europe PMC (preprints), grey literature, media releases and early results from WHO Unity studies. All studies were screened, extracted, assessed for risk of bias and evaluated for alignment with the WHO Unity seroprevalence protocol. We conducted descriptive analyses of seroprevalence and meta-analysed seroprevalence differences by demographic groups, place and time. We estimated the extent of undetected infections by comparing seroprevalence and cumulative incidence of confirmed cases reported to WHO. PROSPERO CRD42020183634. RESULTS We identified 56 full texts or early results, reporting 153 distinct seroprevalence studies in Africa. Of these, 97 (63%) were low/moderate risk of bias studies. SARS-CoV-2 seroprevalence rose from 3.0% (95% CI 1.0% to 9.2%) in April-June 2020 to 65.1% (95% CI 56.3% to 73.0%) in July-September 2021. The ratios of seroprevalence from infection to cumulative incidence of confirmed cases was large (overall: 100:1, ranging from 18:1 to 954:1) and steady over time. Seroprevalence was highly heterogeneous both within countries-urban versus rural (lower seroprevalence for rural geographic areas), children versus adults (children aged 0-9 years had the lowest seroprevalence)-and between countries and African subregions. CONCLUSION We report high seroprevalence in Africa suggesting greater population exposure to SARS-CoV-2 and potential protection against COVID-19 severe disease than indicated by surveillance data. As seroprevalence was heterogeneous, targeted PHSM and vaccination strategies need to be tailored to local epidemiological situations.
Collapse
Affiliation(s)
- Hannah C Lewis
- Emergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo
- WHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland
| | - Harriet Ware
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Mairead Whelan
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Lorenzo Subissi
- WHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland
| | - Zihan Li
- Faculty of Engineering, University of Waterloo, Waterloo, Ontario, Canada
| | - Xiaomeng Ma
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Anthony Nardone
- WHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland
- Department of Epidemiology, Epiconcept, Paris, France
| | - Marta Valenciano
- WHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland
- Department of Epidemiology, Epiconcept, Paris, France
| | - Brianna Cheng
- WHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland
- School of Population and Global Health, McGill University, Montreal, Québec, Canada
| | - Kim Noel
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada
| | - Christian Cao
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Mercedes Yanes-Lane
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada
- COVID-19 Immunity Task Force Secreteriat, McGill University, Montreal, Québec, Canada
| | - Belinda L Herring
- Emergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo
| | - Ambrose Talisuna
- Emergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo
| | - Nsenga Ngoy
- Emergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo
| | - Thierno Balde
- Emergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo
| | - David Clifton
- Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Maria D Van Kerkhove
- WHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland
| | - David Buckeridge
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada
- Division of Infectious Diseases and Medical Microbiology, McGill University Health Centre, Montreal, Québec, Canada
| | - Niklas Bobrovitz
- Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Joseph Okeibunor
- Emergency Preparedness and Response Programme, World Health Organization, Regional Office for Africa, Brazzaville, Congo
| | - Rahul K Arora
- Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Isabel Bergeri
- WHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland
| |
Collapse
|
3
|
Prevalence of Post-Traumatic Stress Disorder (PTSD) in University Students during the COVID-19 Pandemic: A Meta-Analysis Attending SDG 3 and 4 of the 2030 Agenda. SUSTAINABILITY 2022. [DOI: 10.3390/su14137914] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background: Most universities around the world have been heavily affected by the COVID-19 pandemic, as declared by the World Health Organization (WHO) in March 2020. Many students were isolated at home and underwent a forced transition from face-to-face learning to e-learning, at least in the first few months. The subsequent months and years were typically characterised by a slow return to normal learning under COVID-19 protocols and restrictions. A potential consequence of the lockdowns, social restrictions and changes to learning is the development of PTSD (post-traumatic stress disorder) in university students, affecting their health and well-being (SDG3) and quality of education (SDG4). Materials and Methods: Medline was searched through PubMed for studies on the prevalence of PTSD in university students from 1 December 2019 to 31 December 2021. The pooled prevalence of PTSD was calculated with random-effects models. Results: A total of six studies were included, across which the prevalence of PTSD among university students was 23%. Meta-regression showed that the prevalence of PTSD was significantly higher with older age, but independent of the percentage of women in a study or its methodological quality. Conclusions: Our results suggest that students suffer from PTSD at a moderate rate. Measures are needed to address the mental health issues of university students that have arisen during COVID-19 all around the world.
Collapse
|