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Paudel KP, Samuel R, Jha R, Pandey BD, Edirisuriya C, Shrestha NL, Gyawali P, Pokhrel A, Shrestha L, Mahato RK, Hossain SS, Arunkumar G, Bose AS, Dhimal M, Gautam D, Neupane S, Thakur N, Shrestha S, Bhusal N, Jha P, Gupta BP, Rayamajhi RB, Subedi KC, Kandel S, Poudel M, Thapa LB, Sharma GN, Gocotano AE, Sunny AK, Gautam R, Bhatta DR, Awale BK, Roka B, Ojha HC, Baral P, Adhikari MD, Lohani GR, Shrestha M, Singh DR, Aryal L, Pandav RS, Pokhrel R. Seroprevalence of SARS-CoV-2 infection in the general population of Nepal during the first and second generalized waves of the COVID-19 pandemic-2020-2021. Influenza Other Respir Viruses 2023; 17:e13234. [PMID: 38149926 PMCID: PMC10752246 DOI: 10.1111/irv.13234] [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: 07/11/2023] [Revised: 11/07/2023] [Accepted: 11/20/2023] [Indexed: 12/28/2023] Open
Abstract
Few seroprevalence studies have been conducted on coronavirus disease (COVID-19) in Nepal. Here, we aimed to estimate seroprevalence and assess risk factors for infection in the general population of Nepal by conducting two rounds of sampling. The first round was in October 2020, at the peak of the first generalized wave of COVID-19, and the second round in July-August 2021, following the peak of the wave caused by the delta variant of SARS-CoV-2. We used cross-sectional probability-to-size (PPS)-based multistage cluster sampling to estimate the seroprevalence in the general population of Nepal at the national and provincial levels. We tested for anti-SARS-CoV-2 total antibody using the WANTAI SARS-CoV-2 Ab ELISA kit. In Round 1, the overall national seroprevalence was 14.4%, with provincial estimates ranging from 5.3% in Sudurpaschim to 27.3% in Madhesh Province. In Round 2, the estimated national seroprevalence was 70.7%, with the highest in the Madhesh Province (84.8%) and the lowest in the Gandaki Province (62.9%). Seroprevalence was comparable between males and females (Round 1, 15.8% vs. 12.2% and Round 2, 72.3% vs. 68.7%). The seroprevalence in the ecozones-Terai, hills, and mountains-was 76.3%, 65.3%, and 60.5% in Round 2 and 17.7%, 11.7%, and 4.6% in Round 1, respectively. In Nepal, COVID-19 vaccination was introduced in January 2021. At the peak of the first generalized wave of COVID-19, most of the population of Nepal remained unexposed to SARS-CoV-2. Towards the end of the second generalized wave in April 2021, two thirds of the population was exposed.
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Affiliation(s)
- Krishna Prasad Paudel
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | | | - Runa Jha
- National Public Health LaboratoryMinistry of Health and PopulationKathmanduNepal
| | - Basu Dev Pandey
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
- DEJIMA Infectious Disease Research Alliance (DIDA)Nagasaki UniversityNagasakiJapan
| | | | | | | | - Amrit Pokhrel
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | - Lilee Shrestha
- National Public Health LaboratoryMinistry of Health and PopulationKathmanduNepal
| | - Ram Kumar Mahato
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | | | | | | | | | | | | | - Nishant Thakur
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | | | | | - Priya Jha
- WHO Country Office for NepalKathmanduNepal
| | | | | | - Koshal Chandra Subedi
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | - Shashi Kandel
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | - Mukesh Poudel
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | - Lila Bikram Thapa
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | | | | | | | | | | | - Bal Krishna Awale
- National Public Health LaboratoryMinistry of Health and PopulationKathmanduNepal
| | - Bhola Roka
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | - Hemant Chandra Ojha
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | - Phanindra Baral
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
| | - Mahendra Dhose Adhikari
- Epidemiology and Disease Control Division, Department of Health ServicesMinistry of Health and PopulationKathmanduNepal
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Axfors C, Pezzullo AM, Contopoulos-Ioannidis DG, Apostolatos A, Ioannidis JPA. Differential COVID-19 infection rates in children, adults, and elderly: Systematic review and meta-analysis of 38 pre-vaccination national seroprevalence studies. J Glob Health 2023; 13:06004. [PMID: 36655924 PMCID: PMC9850866 DOI: 10.7189/jogh.13.06004] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Background Debate exists about whether extra protection of elderly and other vulnerable individuals is feasible in COVID-19. We aimed to assess the relative infection rates in the elderly vs the non-elderly and, secondarily, in children vs adults. Methods We performed a systematic review and meta-analysis of seroprevalence studies conducted in the pre-vaccination era. We identified representative national studies without high risk of bias through SeroTracker and PubMed searches (last updated May 17, 2022). We noted seroprevalence estimates for children, non-elderly adults, and elderly adults, using cut-offs of 20 and 60 years (or as close to these ages, if they were unavailable) and compared them between different age groups. Results We included 38 national seroprevalence studies from 36 different countries comprising 826 963 participants. Twenty-six of these studies also included pediatric populations and twenty-five were from high-income countries. The median ratio of seroprevalence in elderly vs non-elderly adults (or non-elderly in general, if pediatric and adult population data were not offered separately) was 0.90-0.95 in different analyses, with large variability across studies. In five studies (all in high-income countries), we observed significant protection of the elderly with a ratio of <0.40, with a median of 0.83 in high-income countries and 1.02 elsewhere. The median ratio of seroprevalence in children vs adults was 0.89 and only one study showed a significant ratio of <0.40. The main limitation of our study is the inaccuracies and biases in seroprevalence studies. Conclusions Precision shielding of elderly community-dwelling populations before the availability of vaccines was indicated in some high-income countries, but most countries failed to achieve any substantial focused protection. Registration Open Science Framework (available at: https://osf.io/xvupr).
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Affiliation(s)
- Cathrine Axfors
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA,Department for Women’s and Children’s Health, Uppsala University, Uppsala, Sweden
| | - Angelo Maria Pezzullo
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA,Section of Hygiene, Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Despina G Contopoulos-Ioannidis
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA,Division of Infectious Diseases, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA
| | - Alexandre Apostolatos
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA,Faculty of Medicine, Université de Montréal, Montreal, Canada
| | - John PA Ioannidis
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, USA,Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, Stanford University, Stanford, California, USA
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Pezzullo AM, Axfors C, Contopoulos-Ioannidis DG, Apostolatos A, Ioannidis JPA. Age-stratified infection fatality rate of COVID-19 in the non-elderly population. ENVIRONMENTAL RESEARCH 2023; 216:114655. [PMID: 36341800 PMCID: PMC9613797 DOI: 10.1016/j.envres.2022.114655] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 10/21/2022] [Accepted: 10/22/2022] [Indexed: 05/02/2023]
Abstract
The largest burden of COVID-19 is carried by the elderly, and persons living in nursing homes are particularly vulnerable. However, 94% of the global population is younger than 70 years and 86% is younger than 60 years. The objective of this study was to accurately estimate the infection fatality rate (IFR) of COVID-19 among non-elderly people in the absence of vaccination or prior infection. In systematic searches in SeroTracker and PubMed (protocol: https://osf.io/xvupr), we identified 40 eligible national seroprevalence studies covering 38 countries with pre-vaccination seroprevalence data. For 29 countries (24 high-income, 5 others), publicly available age-stratified COVID-19 death data and age-stratified seroprevalence information were available and were included in the primary analysis. The IFRs had a median of 0.034% (interquartile range (IQR) 0.013-0.056%) for the 0-59 years old population, and 0.095% (IQR 0.036-0.119%) for the 0-69 years old. The median IFR was 0.0003% at 0-19 years, 0.002% at 20-29 years, 0.011% at 30-39 years, 0.035% at 40-49 years, 0.123% at 50-59 years, and 0.506% at 60-69 years. IFR increases approximately 4 times every 10 years. Including data from another 9 countries with imputed age distribution of COVID-19 deaths yielded median IFR of 0.025-0.032% for 0-59 years and 0.063-0.082% for 0-69 years. Meta-regression analyses also suggested global IFR of 0.03% and 0.07%, respectively in these age groups. The current analysis suggests a much lower pre-vaccination IFR in non-elderly populations than previously suggested. Large differences did exist between countries and may reflect differences in comorbidities and other factors. These estimates provide a baseline from which to fathom further IFR declines with the widespread use of vaccination, prior infections, and evolution of new variants.
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Affiliation(s)
- Angelo Maria Pezzullo
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA; Sezione di Igiene, Dipartimento di Scienze della Vita e Sanità Pubblica, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Cathrine Axfors
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA
| | - Despina G Contopoulos-Ioannidis
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA; Division of Infectious Diseases, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Alexandre Apostolatos
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA; Faculty of Medicine, Université de Montréal, Montreal, Canada
| | - John P A Ioannidis
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA; Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, Stanford University, Stanford, CA, USA.
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Rahman M, Khan SR, Alamgir ASM, Kennedy DS, Hakim F, Evers ES, Afreen N, Alam AN, Islam MS, Paul D, Bhuiyan R, Islam R, Moureen A, Salimuzzaman M, Billah MM, Sharif AR, Akter MK, Sultana S, Khan MH, von Harbou K, Zaman MM, Shirin T, Flora MS. Seroprevalence of SARS-CoV-2 antibodies among Forcibly Displaced Myanmar Nationals in Cox's Bazar, Bangladesh 2020: a population-based cross-sectional study. BMJ Open 2022; 12:e066653. [PMID: 36410810 PMCID: PMC9679871 DOI: 10.1136/bmjopen-2022-066653] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 11/01/2022] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVES The study aimed to determine the seroprevalence, the fraction of asymptomatic infections, and risk factors of SARS-CoV-2 infections among the Forcibly Displaced Myanmar Nationals (FDMNs). DESIGN It was a population-based two-stage cross-sectional study at the level of households. SETTING The study was conducted in December 2020 among household members of the FDMN population living in the 34 camps of Ukhia and Teknaf Upazila of Cox's Bazar district in Bangladesh. PARTICIPANTS Among 860 697 FDMNs residing in 187 517 households, 3446 were recruited for the study. One individual aged 1 year or older was randomly selected from each targeted household. PRIMARY AND SECONDARY OUTCOME MEASURES Blood samples from respondents were tested for total antibodies for SARS-CoV-2 using Wantai ELISA kits, and later positive samples were validated by Kantaro kits. RESULTS More than half (55.3%) of the respondents were females, aged 23 median (IQR 14-35) years and more than half (58.4%) had no formal education. Overall, 2090 of 3446 study participants tested positive for SARS-CoV-2 antibody. The weighted and test adjusted seroprevalence (95% CI) was 48.3% (45.3% to 51.4%), which did not differ by the sexes. Children (aged 1-17 years) had a significantly lower seroprevalence 38.6% (95% CI 33.8% to 43.4%) compared with adults (58.1%, 95% CI 55.2% to 61.1%). Almost half (45.7%, 95% CI 41.9% to 49.5%) of seropositive individuals reported no relevant symptoms since March 2020. Antibody seroprevalence was higher in those with any comorbidity (57.8%, 95% CI 50.4% to 64.5%) than those without (47.2%, 95% CI 43.9% to 50.4%). Multivariate logistic regression analysis of all subjects identified increasing age and education as risk factors for seropositivity. In children (≤17 years), only age was significantly associated with the infection. CONCLUSIONS In December 2020, about half of the FDMNs had antibodies against SARS-CoV-2, including those who reported no history of symptoms. Periodic serosurveys are necessary to recommend appropriate public health measures to limit transmission.
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Affiliation(s)
- Mahbubur Rahman
- Epidemiology, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
| | - Samsad Rabbani Khan
- Epidemiology, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
| | - A S M Alamgir
- Virology, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
| | - David S Kennedy
- WHO Emergency Sub-Office, World Health Organization, Cox's Bazar, Bangladesh
| | - Ferdous Hakim
- Research and Publication, World Health Organization Bangladesh, Dhaka, Bangladesh
| | - Egmond Samir Evers
- WHO Emergency Sub-Office, World Health Organization, Cox's Bazar, Bangladesh
| | - Nawroz Afreen
- Epidemiology, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
| | - Ahmed Nawsher Alam
- Virology, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
| | - Md Sahidul Islam
- Research and Publication, World Health Organization Bangladesh, Dhaka, Bangladesh
| | - Debashish Paul
- WHO Emergency Sub-Office, World Health Organization, Cox's Bazar, Bangladesh
| | - Rijwan Bhuiyan
- Co-ordination Center, Ministry of Health and Family Welfare, Cox's Bazar, Bangladesh
| | - Raisul Islam
- WHO Emergency Sub-Office, World Health Organization, Cox's Bazar, Bangladesh
| | - Adneen Moureen
- IEDCR Field Laboratory, World Health Organization, Cox's Bazar, Bangladesh
| | - M Salimuzzaman
- Zoonosis, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
| | - Mallick Masum Billah
- Epidemiology, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
| | - Ahmed Raihan Sharif
- Epidemiology, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
| | - Mst Khaleda Akter
- Research and Publication, World Health Organization Bangladesh, Dhaka, Bangladesh
| | - Sharmin Sultana
- Virology, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
| | - Manjur Hossain Khan
- Virology, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
| | - Kai von Harbou
- WHO Emergency Sub-Office, World Health Organization, Cox's Bazar, Bangladesh
| | | | - Tahmina Shirin
- Director, Institute of Epidemiology Disease Control and Research, Dhaka, Bangladesh
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