Associations with HIV testing in Uganda: an analysis of the Lot Quality Assurance Sampling database 2003–2012

Abstract

Beginning in 2003, Uganda used Lot Quality Assurance Sampling (LQAS) to assist district managers collect and use data to improve their human immunodeficiency virus (HIV)/AIDS program. Uganda's LQAS-database (2003-2012) covers up to 73 of 112 districts. Our multidistrict analysis of the LQAS data-set at 2003-2004 and 2012 examined gender variation among adults who ever tested for HIV over time, and attributes associated with testing. Conditional logistic regression matched men and women by community with seven model effect variables. HIV testing prevalence rose from 14% (men) and 12% (women) in 2003-2004 to 62% (men) and 80% (women) in 2012. In 2003-2004, knowing the benefits of testing (Odds Ratio [OR] = 6.09, 95% CI = 3.01-12.35), knowing where to get tested (OR = 2.83, 95% CI = 1.44-5.56), and secondary education (OR = 3.04, 95% CI = 1.19-7.77) were significantly associated with HIV testing. By 2012, knowing the benefits of testing (OR = 3.63, 95% CI = 2.25-5.83), where to get tested (OR = 5.15, 95% CI = 3.26-8.14), primary education (OR = 2.01, 95% CI = 1.39-2.91), being female (OR = 3.03, 95% CI = 2.53-3.62), and being married (OR = 1.81, 95% CI = 1.17-2.8) were significantly associated with HIV testing. HIV testing prevalence in Uganda has increased dramatically, more for women than men. Our results concurred with other authors that education, knowledge of HIV, and marriage (women only) are associated with testing for HIV and suggest that couples testing is more prevalent than other authors.

Unsafe Injection Is Associated with Higher HIV Testing after Bayesian Adjustment for Unmeasured Confounding

“…The approach can be used as a post-hoc correction when experts, peer-reviewers, or other emerging data deem that biases are possible or likely, as in the present case. 10 The negative effect of unsafe injection on NBT can be explained by the notion that people with unsafe injection are more reactive to receiving knowledge about the transmission routes of HIV which in turn encourages them to refer more for HIV testing. In this sense, the unmeasured variable HIV knowledge mediates the effect of unsafe injection on NBT.…”

“…8 The decision to seek HIV testing among PWID depends on knowledge of the risk for HIV through unsafe injection 8 and testing coverage varies by age, 9 gender, education, and marital status. 10 We hypothesize that part of the controversy surrounding the relation between unsafe injection among PWID and not being tested (NBT) for HIV may be explained by confounding variables as represented by the causal diagram [11][12][13] in Figure 1. Several studies have identified confounders for the effect of unsafe injection on NBT for HIV, including male gender, lower education, and lower knowledge about HIV transmission by increasing the chance of unsafe injection and decreasing the chance of voluntary HIV testing.…”

“… 8 The decision to seek HIV testing among PWID depends on knowledge of the risk for HIV through unsafe injection 8 and testing coverage varies by age, 9 gender, education, and marital status. 10 …”

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

“…A study combining national population survey and routine data found a 28 improvement in the precision of the estimates [5]. General population censuses, on the other hand, are conducted decennially and do not capture information in the interim or information about HIV/AIDS risk factors such as number of sexual partners or condom use during last high-risk sex [6][7][8][9][10][11][12], rendering these censuses unsuitable for assessing outcomes that change rapidly. Annual HIV risk factor surveys with adequate level of precision, such as in the community Lot Quality Assurance Surveys (LQAS) conducted annually in Uganda districts, help generate timely and reliable estimates of districtlevel HIV prevalence.…”