Estimation of HIV prevalence and burden in Nigeria: a Bayesian predictive modelling study.

Background: The cost of population-based surveys is high and obtaining funding for a national population-based survey may take several years, with follow-up surveys taking up to five years. Survey-based prevalence estimates are prone to bias owing to survey non-participation, as not all individuals eligible to participate in a survey may be reached, and some of those who are contacted do not consent to HIV testing. This study describes how Bayesian statistical modeling may be used to estimate HIV prevalence at the state level in a reliable and timely manner. Methods: We analysed national HIV testing services (HTS) data for Nigeria from October 1, 2020, to September 30, 2021, to derive state-level HIV seropositivity rates. We used a Bayesian linear model with normal prior distribution and Markov Chain Monte Carlo approach to estimate HIV state-level prevalence for the 36 states +1 FCT in Nigeria. Our outcome variable was the HIV seropositivity rates and we adjusted for demographic, economic, biological, and societal covariates collected from the 2018 Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS), 2018 Nigeria Demographic and Health Survey (NDHS) and 2016-17 Multiple Indicator Cluster Surveys (MICS). The estimated population of 15-49 years olds in each state was multiplied by estimates from the estimated prevalence to generate state-level HIV burden. Findings: Our estimated national HIV prevalence was 2.1% (95% CI: 1.5-2.7%) among adults aged 15-49 years in Nigeria, which corresponds to approximately 2 million people living with HIV, compared to previous national HIV prevalence estimates of 1.4% from the 2018 NAIIS and UNAIDS estimation and projection package PLHIV estimation of 1.8 million in 2022. Our modelled HIV prevalence in Nigeria varies by state, with Benue (5.7%, 95% CI: 5.0-6.3) having the highest prevalence, followed by Rivers (5.2%, 95% CI: 4.6-5.8%), Akwa Ibom (3.5%, 95% CI: 2.9-4.1%), Edo (3.4%, 95% CI: 2.9-4.0%) and Taraba (3.0%, 95% CI: 2.6-3.7%) placing fourth and fifth, respectively. Jigawa had the lowest HIV prevalence (0.3%), which was consistent with prior estimates. Interpretation: This model provides a comprehensive and flexible use of evidence to estimate state-level HIV seroprevalence for Nigeria using program data and adjusting for explanatory variables. Thus, investment in program data for HIV surveillance will provide reliable estimates for HIV sub-national monitoring and improve planning and interventions for epidemiologic control. Funding: This article was made possible by the support of the American people through the United States Agency for International Development (USAID) under the U.S. President's Emergency Plan for AIDS Relief (PEPFAR).

Effect of Test and Treat on clinical outcomes in Nigeria: A national retrospective study.

BACKGROUND: In Nigeria, results from the pilot of the Test and Treat strategy showed higher loss to follow up (LTFU) among people living with HIV compared to before its implementation. The aim of this evaluation was to assess the effects of antiretroviral therapy (ART) initiation within 14 days on LTFU at 12 months and viral suppression. METHODS: We conducted a retrospective cohort study using routinely collected de-identified patient-level data hosted on the Nigeria National Data Repository from 1,007 facilities. The study population included people living with HIV age ≥15. We used multivariable Cox proportional frailty hazard models to assess time to LTFU comparing ART initiation strategy and multivariable log-binomial regression for viral suppression. RESULTS: Overall, 26,937 (38.13%) were LTFU at 12 months. Among individuals initiated within 14 days, 38.4% were LTFU by 12 months compared to 35.4% for individuals initiated >14 days (p<0.001). In the adjusted analysis, individuals who were initiated ≤14 days after HIV diagnosis had a higher hazard of being LTFU (aHR 1.15, 95% CI 1.10-1.20) than individuals initiated after 14 days of HIV diagnosis. Among individuals with viral load results, 86.2% were virally suppressed. The adjusted risk ratio for viral suppression among individuals who were initiated ≤14 days compared to >14 days was not statistically significant. CONCLUSION: LTFU was higher among individuals who were initiated within 14 days compared to greater than 14 days after HIV diagnosis. There was no difference for viral suppression. The provision of early tailored interventions to support newly diagnosed people living may contribute to reducing LTFU.

A cholera outbreak in a rural north central Nigerian community: an unmatched case-control study.

BACKGROUND: Cholera remains a disease of public health importance in Nigeria associated with high morbidity and mortality. In November 2014, the Nigeria Field Epidemiology and Laboratory Training Programme (NFELTP) was notified of an increase in suspected cholera cases in Gomani, Kwali Local Government Area. NFELTP residents were deployed to investigate the outbreak with the objectives of verifying the diagnosis, identifying risk factors and instituting appropriate control measures to control the outbreak. METHODS: We conducted an unmatched case-control study. We defined a cholera case as any person aged ≥5 years with acute watery diarrhea in Gomani community. We identified community controls. A total of 43 cases and 68 controls were recruited. Structured questionnaires were administered to both cases and controls. Four stool samples from case-patients and two water samples from the community water source were collected for laboratory investigation. We performed univariate and bivariate analysis using Epi-Info version 7.1.3.10. RESULTS: The mean age of cases and controls was 20.3 years and 25.4 respectively (p value 0.09). Females constituted 58.1% (cases) and 51.5%(controls). The attack rate was 4.3% with a case fatality rate of 13%. Four stool (100%) specimen tested positive for Vibrio cholerae. The water source and environment were polluted by indiscriminate defecation. Compared to controls, cases were more likely to have drank from Zamani river (OR 14.2, 95% CI: 5.5-36.8) and living in households(HH) with more than 5 persons/HH (OR 5.9, 95% CI: 1.3-27.2). Good hand hygiene was found to be protective (OR 0.3, 95% CI: 0.1-0.7). CONCLUSION: Vibrio cholerae was the cause of the outbreak in Gomani. Drinking water from Zamani river, living in overcrowded HH and poor hand hygiene were significantly associated with the outbreak. We initiated hand hygiene and water treatment to control the outbreak.