ArticlePloS one2022
Mapping HIV prevalence in Nigeria using small area estimates to develop a targeted HIV intervention strategy.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Improving HIV case finding using spatial data infrastructures in Anambra State, Nigeria: a pre-post intervention study.BMC public health · 2025Article
- Spatial analysis and associated risk factors of HIV prevalence in Botswana: insights from the 2021 Botswana AIDS Impact Survey (BAIS V).BMC infectious diseases · 2025Article
- Article
- Investigating the Barriers and Facilitators to Using Antiretroviral Therapy among Women Living with HIV in Plateau State, Nigeria.International journal of environmental research and public health · 2024Article
- Investigating catastrophic health expenditure among people living with HIV and AIDS in South Western Nigeria.Health care science · 2023Article
- Does adherence to antiretroviral therapy differ by place of residence in Nigeria? A systematic review and meta-analysis protocol.BMJ open · 2023Article
- Prevalence and Risk Factors for Mycobacterium tuberculosis Infection among Health Workers in HIV Treatment Centers in North Central, Nigeria.The American journal of tropical medicine and hygiene · 2023Article
- Cervical Epithelial Abnormalities and Associated Factors among HIV-Infected Women in Lagos, Nigeria: A Cytology-Based Study.Acta cytologica · 2023Article
- Spatial Co-Clustering of Tuberculosis and HIV in Ethiopia.Diseases (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
Abstract
objectiveAlthough geographically specific data can help target HIV prevention and treatment strategies, Nigeria relies on national- and state-level estimates for policymaking and intervention planning. We calculated sub-state estimates along the HIV continuum of care in Nigeria.
designUsing data from the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS) (July-December 2018), we conducted a geospatial analysis estimating three key programmatic indicators: prevalence of HIV infection among adults (aged 15-64 years); antiretroviral therapy (ART) coverage among adults living with HIV; and viral load suppression (VLS) rate among adults living with HIV.
methodsWe used an ensemble modeling method called stacked generalization to analyze available covariates and a geostatistical model to incorporate the output from stacking as well as spatial autocorrelation in the modeled outcomes. Separate models were fitted for each indicator. Finally, we produced raster estimates of each indicator on an approximately 5×5-km grid and estimates at the sub-state/local government area (LGA) and state level.
resultsEstimates for all three indicators varied both within and between states. While state-level HIV prevalence ranged from 0.3% (95% uncertainty interval [UI]: 0.3%-0.5%]) to 4.3% (95% UI: 3.7%-4.9%), LGA prevalence ranged from 0.2% (95% UI: 0.1%-0.5%) to 8.5% (95% UI: 5.8%-12.2%). Although the range in ART coverage did not substantially differ at state level (25.6%-76.9%) and LGA level (21.9%-81.9%), the mean absolute difference in ART coverage between LGAs within states was 16.7 percentage points (range, 3.5-38.5 percentage points). States with large differences in ART coverage between LGAs also showed large differences in VLS-regardless of level of effective treatment coverage-indicating that state-level geographic targeting may be insufficient to address coverage gaps.
conclusionGeospatial analysis across the HIV continuum of care can effectively highlight sub-state variation and identify areas that require further attention in order to achieve epidemic control. By generating local estimates, governments, donors, and other implementing partners will be better positioned to conduct targeted interventions and prioritize resource distribution.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.