Difference in HIV prevalence by testing venue: results from population level survey in Uganda

Prevalence of HIV in slums area: a systematic review and meta-analysis

BACKGROUND

Human Immunodeficiency Virus (HIV) remains a significant global health burden, particularly affecting vulnerable populations residing in slum areas which is characterized by overcrowding, poverty, and limited access to healthcare services, create an environment conducive to the transmission and spread of HIV. Despite the recognition of this issue, there is a lack of comprehensive understanding regarding the prevalence of HIV in slums. The aim of this study was to systematically synthesize the existing global evidence on HIV prevalence in slum populations.

METHODS

A rigorous systematic literature review was conducted by searching multiple electronic databases, including Medline via PubMed, Scopus, Embase, Web of Sciences, and Directory of Open Access Journals (DOAJ), covering the period from January 1, 1990, to March 31, 2023. The quality and risk of bias for each included study were assessed using the Newcastle-Ottawa Scale. The pooled prevalence with its corresponding 95% confidence interval (CI) was calculated using a random-effects model with the Freeman-Tukey double arcsine transformation. The degree of heterogeneity among the studies was evaluated using the I2 test. Publication bias was also assessed using Egger's test. Additionally, subgroup analysis was performed to explore potential factors contributing to the observed heterogeneity.

RESULTS

A systematic examination of the relevant literature resulted in the inclusion of a total of 22 studies for the purpose of this meta-analysis. These studies collectively assessed a sizable cohort consisting of 52,802 participants. Utilizing a random-effects model, an estimation of the overall prevalence of HIV in the slum area was determined to be 10% (95% CI: 7-13%). Further delineation through subgroup analysis based on the gender revealed a higher prevalence of HIV among women, standing at 13% (95% CI: 8-19%, 18 studies: I2 = 98%), as opposed to men, where the prevalence was found to be 8% (95% CI: 6-12%, 16 studies: I2 = 95%). A geographical breakdown of the included studies revealed that Africa exhibited the highest prevalence, with a figure of 11% (95% CI: 9-13%, 18 studies: I2 = 98%). Subsequently, studies conducted in the American continent reported a prevalence of 9% (95% CI: 7-11%, 2 studies: I2 = 57%). The Asian continent, on the other hand, displayed the lowest prevalence of 1% (95% CI: 0-3%, 2 studies: I2 = 94%). Notably, studies employing rapid tests indicated a prevalence of 13% (95% CI: 9-17%, 6 studies: I2 = 94%), while those relying on self-reported data reported a lower prevalence of 8% (95% CI: 5-11%, 6 studies: I2 = 99%). Moreover, studies utilizing ELISA reported a prevalence of 9% (95% CI: 6-12%, 10 studies: I2 = 96%). Finally, it was determined that studies conducted in upper-middle-income countries reported a higher prevalence of 20% (95% CI: 16-24%, 5 studies: I2 = 45%), whereas studies conducted in lower- and middle-income countries reported a prevalence of 8% (95% CI: 6-10%, 12 studies: I2 = 98%).

CONCLUSION

The current study elucidates the troublingly high prevalence of HIV infection within slums area. Also, this finding underscores the urgent necessity for targeted and tailored interventions specifically aimed at curtailing the spread of HIV within slums. Policymakers must take cognizance of these results and devote their efforts towards the implementation of effective strategies to mitigate gender disparities, address poverty alleviation, and empower the inhabitants of these marginalized areas.

Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda

Background

Model-based small area estimation methods can help generate parameter estimates at the district level, where planned population survey sample sizes are not large enough to support direct estimates of HIV prevalence with adequate precision. We computed district-level HIV prevalence estimates and their 95% confidence intervals for districts in Uganda.

Methods

Our analysis used direct survey and model-based estimation methods, including Fay-Herriot (area-level) and Battese-Harter-Fuller (unit-level) small area models. We used regression analysis to assess for consistency in estimating HIV prevalence. We use a ratio analysis of the mean square error and the coefficient of variation of the estimates to evaluate precision. The models were applied to Uganda Population-Based HIV Impact Assessment 2016/2017 data with auxiliary information from the 2016 Lot Quality Assurance Sampling survey and antenatal care data from district health information system datasets for unit-level and area-level models, respectively.

Results

Estimates from the model-based and the direct survey methods were similar. However, direct survey estimates were unstable compared with the model-based estimates. Area-level model estimates were more stable than unit-level model estimates. The correlation between unit-level and direct survey estimates was (β₁ = 0.66, r² = 0.862), and correlation between area-level model and direct survey estimates was (β₁ = 0.44, r² = 0.698). The error associated with the estimates decreased by 37.5% and 33.1% for the unit-level and area-level models, respectively, compared to the direct survey estimates.

Conclusions

Although the unit-level model estimates were less precise than the area-level model estimates, they were highly correlated with the direct survey estimates and had less standard error associated with estimates than the area-level model. Unit-level models provide more accurate and reliable data to support local decision-making when unit-level auxiliary information is available.