4 research outputs found

    Seroprevalence of SARS-CoV-2 in four states of Nigeria in October 2020: A population-based household survey

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    The observed epidemiology of SARS-CoV-2 in sub-Saharan Africa has varied greatly from that in Europe and the United States, with much lower reported incidence. Population-based studies are needed to estimate true cumulative incidence of SARS-CoV-2 to inform public health interventions. This study estimated SARS-CoV-2 seroprevalence in four selected states in Nigeria in October 2020. We implemented a two-stage cluster sample household survey in four Nigerian states (Enugu, Gombe, Lagos, and Nasarawa) to estimate age-stratified prevalence of SARS-CoV-2 antibodies. All individuals in sampled households were eligible for interview, blood draw, and nasal/oropharyngeal swab collection. We additionally tested participants for current/recent malaria infection. Seroprevalence estimates were calculated accounting for the complex survey design. Across all four states, 10,629 (96·5%) of 11,015 interviewed individuals provided blood samples. The seroprevalence of SARS-CoV-2 antibodies was 25·2% (95% CI 21·8–28·6) in Enugu State, 9·3% (95% CI 7·0–11·5) in Gombe State, 23·3% (95% CI 20·5–26·4) in Lagos State, and 18·0% (95% CI 14·4–21·6) in Nasarawa State. Prevalence of current/recent malaria infection ranged from 2·8% in Lagos to 45·8% in Gombe and was not significantly related to SARS-CoV-2 seroprevalence. The prevalence of active SARS-CoV-2 infection in the four states during the survey period was 0·2% (95% CI 0·1–0·4). Approximately eight months after the first reported COVID-19 case in Nigeria, seroprevalence indicated infection levels 194 times higher than the 24,198 officially reported COVID-19 cases across the four states; however, most of the population remained susceptible to COVID-19 in October 2020

    COVID-19 mortality rate and its associated factors during the first and second waves in Nigeria

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    COVID-19 mortality rate has not been formally assessed in Nigeria. Thus, we aimed to address this gap and identify associated mortality risk factors during the first and second waves in Nigeria. This was a retrospective analysis of national surveillance data from all 37 States in Nigeria between February 27, 2020, and April 3, 2021. The outcome variable was mortality amongst persons who tested positive for SARS-CoV-2 by Reverse-Transcriptase Polymerase Chain Reaction. Incidence rates of COVID-19 mortality was calculated by dividing the number of deaths by total person-time (in days) contributed by the entire study population and presented per 100,000 person-days with 95% Confidence Intervals (95% CI). Adjusted negative binomial regression was used to identify factors associated with COVID-19 mortality. Findings are presented as adjusted Incidence Rate Ratios (aIRR) with 95% CI. The first wave included 65,790 COVID-19 patients, of whom 994 (1∙51%) died; the second wave included 91,089 patients, of whom 513 (0∙56%) died. The incidence rate of COVID-19 mortality was higher in the first wave [54∙25 (95% CI: 50∙98–57∙73)] than in the second wave [19∙19 (17∙60–20∙93)]. Factors independently associated with increased risk of COVID-19 mortality in both waves were: age ≥45 years, male gender [first wave aIRR 1∙65 (1∙35–2∙02) and second wave 1∙52 (1∙11–2∙06)], being symptomatic [aIRR 3∙17 (2∙59–3∙89) and 3∙04 (2∙20–4∙21)], and being hospitalised [aIRR 4∙19 (3∙26–5∙39) and 7∙84 (4∙90–12∙54)]. Relative to South-West, residency in the South-South and North-West was associated with an increased risk of COVID-19 mortality in both waves. In conclusion, the rate of COVID-19 mortality in Nigeria was higher in the first wave than in the second wave, suggesting an improvement in public health response and clinical care in the second wave. However, this needs to be interpreted with caution given the inherent limitations of the country’s surveillance system during the study

    Akwa Ibom AIDS indicator survey: Key findings and lessons learnt.

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    BackgroundThe burden of HIV/AIDS epidemic is huge, but this varies widely by population in Nigeria. Data that could be used to guide the scale up of HIV prevention and control strategies has significant gaps. The study sought to estimate the prevalence of HIV and its associated determinants in Akwa Ibom state.MethodsAkwa Ibom AIDS Indicator Survey (AKAIS) is a population based cross-sectional survey, with a two-stage probability sampling. The survey had both behavioural and biological components. Tablet-based questionnaire was used to collect data on participant's household information, demographics, socio-economic, and behavioral risk factors associated with HIV; while the biological component involved collection of venous blood samples for participants who were over 19months. For children aged 18months on less, capillary blood from finger prick sample was used. Participants were tested for HIV. Other biomarker tests for HIV positive participants included CD4, HIV-1 RNA viral load and incidence assays.ResultsIn all 15,609 people (8,963 adults aged 15 years and older (55% females), 6,646 individuals less than 15 years (51% males), from 4,313 households, participated in AKAIS. Overall, 2.8% (423 persons; 422 HIV-1 and 1 HIV-2) were found to be HIV positive. HIV prevalence was 4.8% in adults (15 years and above) and 0.4% in pediatric (ConclusionsHIV prevalence among adults was 4.8% with an overall incidence of 0.41%. These estimates are essential to inform strategic control and prevention of HIV epidemic in Akwa Ibom state targeting the affected populations

    Implementation of data triangulation and dashboard development for COVID-19 vaccine adverse event following immunisation (AEFI) data in Nigeria

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    Nigeria began administering COVID-19 vaccines on 5 March 2021 and is working towards the WHO’s African regional goal to fully vaccinate 70% of their eligible population by December 2022. Nigeria’s COVID-19 vaccination information system includes a surveillance system for COVID-19 adverse events following immunisation (AEFI), but as of April 2021, AEFI data were being collected and managed by multiple groups and lacked routine analysis and use for action. To fill this gap in COVID-19 vaccine safety monitoring, between April 2021 and June 2022, the US Centers for Disease Control and Prevention, in collaboration with other implementing partners led by the Institute of Human Virology Nigeria, supported the Government of Nigeria to triangulate existing COVID-19 AEFI data. This paper describes the process of implementing published draft guidelines for data triangulation for COVID-19 AEFI data in Nigeria. Here, we focus on the process of implementing data triangulation rather than analysing the results and impacts of triangulation. Work began by mapping the flow of COVID-19 AEFI data, engaging stakeholders and building a data management system to intake and store all shared data. These datasets were used to create an online dashboard with key indicators selected based on existing WHO guidelines and national guidance. The dashboard went through an iterative review before dissemination to stakeholders. This case study highlights a successful example of implementing data triangulation for rapid use of AEFI data for decision-making and emphasises the importance of stakeholder engagement and strong data governance structures to make data triangulation successful
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