Assessing the impact of the COVID-19 restrictions on HIV testing services in Malawi: an interrupted time series analysis.

Background: Restrictions on public gatherings and movement to mitigate the spread of COVID-19 may have disrupted access and availability of HIV services in Malawi. We quantified the impact of these restrictions on HIV testing services in Malawi.Methods: We conducted an interrupted time series analysis of routine aggregated programme data from 808 public and private, adult and paediatric health facilities across rural and urban communities in Malawi between January 2018 and March 2020 (pre-restrictions) and April to December 2020 (post restrictions), with April 2020 as the month restrictions took effect. Positivity rates were expressed as the proportion of new diagnoses per 100 persons tested. Data were summarised using counts and median monthly tests stratified by sex, age, type of health facility and service delivery points at health facilities. The immediate effect of restriction and post-lockdown outcomes trends were quantified using negative binomial segmented regression models adjusted for seasonality and autocorrelation.Results: The median monthly number of HIV tests and diagnosed people living with HIV (PLHIV) declined from 261 979 (interquartile range [IQR] 235 654-283 293) and 7 929 (IQR 6 590-9 316) before the restrictions, to 167 307 (IQR 161 122-185 094) and 4 658 (IQR 4 535-5 393) respectively, post restriction. Immediately after restriction, HIV tests declined by 31.9% (incidence rate ratio [IRR] 0.681; 95% CI 0.619-0.750), the number of PLHIV diagnosed declined by 22.8% (IRR 0.772; 95% CI 0.695-0.857), while positivity increased by 13.4% (IRR 1.134; 95% CI 1.031-1.247). As restrictions eased, total HIV testing outputs and the number of new diagnoses increased by an average of 2.3% each month (slope change: 1.023; 95% CI 1.010-1.037) and 2.5% (slope change:1.025; 95% CI 1.012-1.038) respectively. Positivity remained similar (slope change: 1.001; 95% CI 0.987-1.015). Unlike general trends noted, while HIV testing services among children aged <12 months declined 38.8% (IRR 0.351; 95% CI 0.351-1.006) with restrictions, recovery has been minimal (slope change: 1.008; 95% CI 0.946-1.073).Conclusion: COVID-19 restrictions were associated with significant but short-term declines in HIV testing services in Malawi, with differential recovery in these services among population subgroups, especially infants. While efforts to restore HIV testing services are commendable, more nuanced strategies that promote equitable recovery of HIV testing services can ensure no subpopulations are left behind.

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

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.

Evaluation of accuracy and performance of self-reported HIV and antiretroviral therapy status in the Nigeria AIDS Indicator and Impact Survey (2018).

BACKGROUND: Data on awareness of HIV status among people living with HIV (PLHIV) are critical to estimating progress toward epidemic control. To ascertain the accuracy of self-reported HIV status and antiretroviral drug (ARV) use in the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS), we compared self-reported HIV status with HIV rapid diagnostic test (RDT) results and self-reported ARV use with detectable blood ARV levels. METHODS: On the basis of responses and test results, participants were categorized by HIV status and ARV use. Self-reported HIV status and ARV use performance characteristics were determined by estimating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Proportions and other analyses were weighted to account for complex survey design. RESULTS: During NAIIS, 186,405 participants consented for interview out of which 58,646 reported knowing their HIV status. Of the 959 (weighted, 1.5%) who self-reported being HIV-positive, 849 (92.1%) tested HIV positive and 64 (7.9%) tested HIV negative via RDT and polymerase chain reaction test for discordant positive results. Of the 849 who tested HIV positive, 743 (89.8%) reported using ARV and 72 (10.2%) reported not using ARV. Of 57,687 who self-reported being HIV negative, 686 (1.2%) tested HIV positive via RDT, with ARV biomarkers detected among 195 (25.1%). ARV was detected among 94.5% of those who self-reported using ARV and among 42.0% of those who self-reported not using ARV. Overall, self-reported HIV status had sensitivity of 52.7% (95% confidence interval [CI]: 49.4%-56.0%) with specificity of 99.9% (95% CI: 99.8%-99.9%). Self-reported ARV use had sensitivity of 95.2% (95% CI: 93.6%-96.7%) and specificity of 54.5% (95% CI: 48.8%-70.7%). CONCLUSIONS: Self-reported HIV status and ARV use screening tests were found to be low-validity measures during NAIIS. Laboratory tests to confirm self-reported information may be necessary to determine accurate HIV and clinical status for HIV studies in Nigeria.

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

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.

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.

Epidemiological comparison of the first and second waves of the COVID-19 pandemic in Nigeria, February 2020-April 2021.

BACKGROUND: With reports of surges in COVID-19 case numbers across over 50 countries, country-level epidemiological analysis is required to inform context-appropriate response strategies for containment and mitigation of the outbreak. We aimed to compare the epidemiological features of the first and second waves of COVID-19 in Nigeria. METHODS: We conducted a retrospective analysis of the Surveillance Outbreak Response Management and Analysis System data of the first and second epidemiological waves, which were between 27 February and 24 October 2020, and 25 October 2020 to 3 April 2021, respectively. Descriptive statistical measures including frequencies and percentages, test positivity rate (TPR), cumulative incidence (CI) and case fatality rates (CFRs) were compared. A p value of <0.05 was considered statistically significant. All statistical analyses were carried out in STATA V.13. RESULTS: There were 802 143 tests recorded during the study period (362 550 and 439 593 in the first and second waves, respectively). Of these, 66 121 (18.2%) and 91 644 (20.8%) tested positive in the first and second waves, respectively. There was a 21.3% increase in the number of tests conducted in the second wave with TPR increasing by 14.3%. CI during the first and second waves were 30.3/100 000 and 42.0/100 000 respectively. During the second wave, confirmed COVID-19 cases increased among females and people 30 years old or younger and decreased among urban residents and individuals with travel history within 14 days of sample collection (p value <0.001). Most confirmed cases were asymptomatic at diagnosis during both waves: 74.9% in the first wave; 79.7% in the second wave. CFR decreased during the second wave (0.7%) compared with the first wave (1.8%). CONCLUSION: Nigeria experienced a larger but less severe second wave of COVID-19. Continued implementation of public health and social measures is needed to mitigate the resurgence of another wave.

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

BACKGROUND: The 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. METHODS: Akwa 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. RESULTS: In 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 (< = 14 years) participants. HIV prevalence was significantly higher in females (5.6%) than males (3.7%) aged 15 years and older (p <0.001). Overall HIV incidence was 0.41. CONCLUSIONS: HIV 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.