2 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

    Effectiveness of three delivery models for promoting access to pre-exposure prophylaxis in HIV-1 serodiscordant couples in Nigeria.

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    OBJECTIVES: To evaluate the effectiveness of three models for pre-exposure prophylaxis (PrEP) service delivery to HIV-1 serodiscordant couples in Nigeria. METHODS: 297 heterosexual HIV-1 serodiscordant couples were recruited into three PrEP delivery models and followed up for 18 months. The models were i) Outpatient clinic model providing PreP in routine outpatient care; ii) Antiretroviral therapy (ART) clinic model providing PrEP in ART clinics; and iii) Decentralized care model providing PrEP through primary and secondary care centres linked to a tertiary care centre. The primary effectiveness endpoint was incident HIV-1 infection. The HIV incidence before and after the study was compared and the incidence rate ratio computed for each model. Survival analysis was conducted, Cox regression analysis was used to compare the factors that influenced couple retention in each of the models. Kaplan-Meier survival analysis was used to estimate the median retention time (in months) of the study participants in each of the study models, and log-rank test for equality of survival functions was conducted to test for significant differences among the three models. RESULTS: There was no significant difference (p>0.05) in the couple retention rates among the three models. At months 3, 6 and 9, adherence of the HIV-1-infected partners to ART was highest in the decentralized model, whereas at months 9 and 12, the outpatient model had the highest proportion of HIV-1- uninfected partners adhering to PrEP (p<0.001). The HIV incidence per 100 person-years was zero in the general outpatient clinic and ART clinic models and 1.6 (95% CI: 0.04-9.1) in the decentralized clinic model. The difference in the observed and expected incidence rate was 4.3 (95% CI: 0.44-39.57) for the decentralized clinic model. CONCLUSION: Although incidence of HIV seroconversion was highest in the decentralized clinic model, this difference may be due to the higher sexual risk behavior among study participants in the decentralized model rather than the type of service delivery. The study findings imply that any of the models can effectively deliver PrEP services
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