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Reuben RC, Abunike SA. Marburg virus disease: the paradox of Nigeria's preparedness and priority effects in co-epidemics. Bull Natl Res Cent 2023; 47:10. [PMID: 36721499 PMCID: PMC9880916 DOI: 10.1186/s42269-023-00987-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/19/2023] [Indexed: 05/12/2023]
Abstract
BACKGROUND The recent outbreaks of Marburg virus disease (MVD) in Guinea and Ghana have become a major public health concern not only to the West African sub-region but a threat to global health. MAIN BODY OF THE ABSTRACT Given the poorly elucidated ecological and epidemiological dynamics of the Marburg virus, it would be imprudent to preclude the possibility of another pandemic if urgent efforts are not put in place. However, the prior emergence and impact of COVID-19 and other co-occurring epidemics may add 'noise' to the epidemiological dynamics and public health interventions that may be required in the advent of a MVD outbreak in Nigeria. SHORT CONCLUSION Paying attention to the lessons learned from previous (and current) multiple epidemics including Avian Influenza, Yellow fever, Ebola virus disease, Monkeypox, Lassa fever, and COVID-19 could help avoid a potentially devastating public health catastrophe in Nigeria.
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Affiliation(s)
- Rine Christopher Reuben
- German Centre of Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Puschstraße 4, 04103 Leipzig, Germany
- Institute of Biology, Leipzig University, Puschstraße 4, 04103 Leipzig, Germany
- Department of Biological Science, Anchor University, Lagos, Nigeria
| | - Sarah Adamma Abunike
- Institute for Health and Equity, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226 USA
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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] [What about the content of this article? (0)] [Affiliation(s)] [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.
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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
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Adewoyin Y, Ajaero CK, Odimegwu CO. Contexts, beliefs and health behaviour: Are individuals who engage in risky sexual behaviour likely to wear facemasks against COVID-19? J Public Health Afr 2022; 13:2032. [PMID: 36051515 PMCID: PMC9425937 DOI: 10.4081/jphia.2022.2032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 04/29/2022] [Indexed: 11/22/2022] Open
Abstract
Beside age, underlying comorbidities and availability of sanitation facilities, individual health beliefs and behaviour are critical in combating the sustained prevalence of Covid-19. Behaviour has, however, been shown to be consistent but could be context- dependent based on the individual’s beliefs. To investigate whether or not individuals’ protective behaviour against coronavirus is associated with their behaviour in a previous health context. Facemask usage and engagement in risky sexual behaviour (RSB) were employed as corollaries of Covid-19 protective behaviour and a previous health context respectively. Data on them and other sociodemographic correlates of health behaviour were collected on 522 Nigerians via a web-based survey. The data were analyzed using frequency, Chi Square and Binary Logistics Regression. About 31% of the population wore facemasks in public, 48.1% believed Covid existed and was severe, and 31.6% had engaged in RSB. Individuals who engaged in RSB had lower odds of wearing facemasks in public in both the general population and across the rural-urban divide. The relationship was, however, only statistically significant (OR:0.642, p<0.05) in the adjusted regression model. Other significant determinants of facemask use were gender, place of residence, employment status and beliefs about Covid. The similarity of individual beliefs and behaviours in different health contexts provides an opportunity to model behaviour change communication policies for preventing and combating the spread of coronavirus and other infectious diseases.
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