Population impacts of conditional financial incentives and a male-targeted digital decision support application on the HIV treatment cascade in rural KwaZulu Natal: findings from the HITS cluster randomized clinical trial.

INTRODUCTION: In South Africa, the HIV care cascade remains suboptimal. We investigated the impact of small conditional financial incentives (CFIs) and male-targeted HIV-specific decision-support application (EPIC-HIV) on the HIV care cascade. METHODS: In 2018, in uMkhanyakude district, 45 communities were randomly assigned to one of four arms: (i) CFI for home-based HIV testing and linkage to care within 6 weeks (R50 [US$3] food voucher each); (ii) EPIC-HIV which are based on self-determination theory; (iii) both CFI and EPIC-HIV; and (iv) standard of care. EPIC-HIV consisted of two components: EPIC-HIV 1, provided to men through a tablet before home-based HIV testing, and EPIC-HIV 2, offered 1 month later to men who tested positive but had not yet linked to care. Linking HITS trial data to national antiretroviral treatment (ART) programme data and HIV surveillance programme data, we estimated HIV status awareness after the HITS trial implementation, ART status 3 month after the trial and viral load suppression 1 year later. Analysis included all known individuals living with HIV in the study area including those who did not participated in the HITS trial. RESULTS: Among the 33,778 residents in the study area, 2763 men and 7266 women were identified as living with HIV by the end of the intervention period and included in the analysis. After the intervention, awareness of HIV-positive status was higher in the CFI arms compared to non-CFI arms (men: 793/908 [87.3%] vs. 1574/1855 [84.9%], RR = 1.03 [95% CI: 0.99-1.07]; women: 2259/2421 [93.3%] vs. 4439/4845 [91.6%], RR = 1.02 [95% CI: 1.00-1.04]). Three months after the intervention, no differences were found for linkage to ART between arms. One year after the intervention, only 1829 viral test results were retrieved. Viral suppression was higher but not significant in the EPIC-HIV intervention arms among men (65/99 [65.7%] vs. 182/308 [59.1%], RR = 1.11 [95% CI: 0.88-1.40]). CONCLUSIONS: Small CFIs can contribute to achieve the first step of the HIV care cascade. However, neither CFIs nor EPIC-HIV was sufficient to increase the number of people on ART. Additional evidence is needed to confirm the impact of EPIC-HIV on viral suppression.

The impact of a conditional financial incentive on linkage to HIV care: Findings from the HITS cluster randomized clinical trial in rural South Africa.

Introduction: HIV elimination requires innovative approaches to ensure testing and immediate treatment provision. We investigated the effectiveness of conditional financial incentives on increasing linkage to HIV care in a 2×2 factorial cluster randomized controlled trial-Home-Based Intervention to Test and Start (HITS) - in rural South Africa. Methods: Of 45 communities in uMkhanyakude, KwaZulu-Natal, 16 communities were randomly assigned to the arms to receive financial incentives for home-based HIV counseling and testing (HBHCT) and linkage to care within 6 weeks (R50 [US$3] food voucher each) and 29 communities to the arms without financial incentives. We examined linkage to care (i.e., initiation or resumption of antiretroviral therapy after >3 months of care interruption) at local clinics within 6 weeks of a home visit, the eligibility period to receive the second financial incentive. Linkage to care was ascertained from individual clinical records. Intention-to-treat analysis (ITT) was performed using modified Poisson regression with adjustment for receiving another intervention (i.e., male-targeted HIV-specific decision support app) and clustering of standard errors at the community level. Results: Among 13,894 eligible men (i.e., ≥15 years and resident in the 45 communities), 20.7% received HBHCT, which resulted in 122 HIV-positive tests. Of these, 27 linked to care within 6 weeks of HBHCT. Additionally, of eligible men who did not receive HBHCT, 66 linked to care. In the ITT analysis, the proportion of linkage to care among men did not differ in the arms which received financial incentives and those without financial incentives (adjusted Risk Ratio [aRR]=0.78, 95% CI: 0.51-1.21). Among 19,884 eligible women, 29.1% received HBHCT, which resulted in 375 HIV-positive tests. Of these, 75 linked to care. Among eligible women who did not receive HBHCT, 121 linked to care within 6 weeks. Women in the financial incentive arms had a significantly higher probability of linkage to care, compared to those in the arms without financial incentives (aRR=1.50; 95% CI: 1.03-2.21). Conclusion: While a small once-off financial incentive did not increase linkage to care among men during the eligibility period of 6 weeks, it significantly improved linkage to care among women over the same period. Clinical Trial Number: ClinicalTrials.gov # NCT03757104.

Can a conditional financial incentive (CFI) reduce socio-demographic inequalities in home-based HIV testing uptake? A secondary analysis of the HITS clinical trial intervention in rural South Africa.

In sub-Saharan Africa, home-based HIV testing interventions are designed to reach sub-populations with low access to HIV testing such as men, younger or less educated people. Combining these interventions with conditional financial incentives (CFI) has been shown to be effective to increase testing uptake. CFI are effective for one-off health behaviour change but whether they operate differentially on different socio-demographic groups is less clear. Using data from the HITS trial in South Africa, we investigated whether a CFI was able to reduce existing home-based HIV testing uptake inequalities observed by socio-demographic groups. Residents aged ≥15 years in the study area were assigned to an intervention arm (16 clusters) or a control arm (29 clusters). In the intervention arm, individuals received a food voucher (∼3.5 US dollars) if they accepted to take a home-based HIV test. Testing uptake differences were considered for socio-demographic (sex, age, education, employment status, marital status, household asset index) and geographical (urban/rural living area, distance from clinic) characteristics. Among the 37,028 residents, 24,793 (9290 men, 15,503 women) were included in the analysis. CFI increased significantly testing uptake among men (39.2% vs 25.2%, p < 0.001) and women (45.9% vs 32.0%, p < 0.001) with similar absolute increase between men and women. Uptake was higher amongst the youngest or least educated individuals, and amongst single (vs in union) or unemployed men. Absolute uptake increase was also significantly higher amongst these groups resulting in increasing socio-demographic differentials for home-based HIV testing uptake. However, because these groups are known to have less access to other public HIV testing services, CFI could reduce inequalities for HIV testing access in our specific context. Although CFI significantly increased home-based HIV testing uptake, it did not do so differentially by socio-demographic group. Future interventions using CFI should make sure that the intervention alone does not increase existing health inequities.

Effects of Osteoarthritis Pain and Concurrent Insomnia and Depression on Health Care Use in a Primary Care Population of Older Adults.

OBJECTIVE: To examine independent and combined effects of pain with concurrent insomnia and depression symptoms on the use of health care services in older adults with osteoarthritis (OA). METHODS: Patients were Group Health Cooperative (GHC) patients with a primary diagnosis of OA (n = 2,976). We used survey data on pain (Graded Chronic Pain Scale), insomnia (Insomnia Severity Index), and depression (Patient Health Questionnaire-8), and health care use extracted from GHC electronic health records (office visits, length of stay, outpatient and inpatient costs, and hip or knee replacement) for 3 years after the survey. Negative binomial, logistic, and generalized linear models were used to assess predictors of health care use. RESULTS: Approximately 34% and 29% of patients displayed at least subclinical insomnia and at least subclinical depression symptoms, respectively, in addition to moderate-to-severe pain. Pain had the greatest independent effects on increasing all types of health care use, followed by depression (moderate effects) on increased office visits, length of stay, outpatient and inpatient costs, and insomnia (mild effects) on decreased length of stay. No synergistic effects of the 3 symptoms on use of health care services were observed. The combined effects of pain plus insomnia and pain plus depression were significant for all types of health care use and increased greatly with increasing severity of insomnia and depression, except for hip/knee replacement. CONCLUSION: Pain is the main driver for health care use in patients with OA. In addition to pain, insomnia plus depression jointly increased diverse types of health care use, and these combined effects increased greatly with increasing severity of insomnia and depression. These findings indicate the important role that concurrent symptomatic conditions may play in increasing use of health care services.

Measures of Human Mobility Using Mobile Phone Records Enhanced with GIS Data.

In the past decade, large scale mobile phone data have become available for the study of human movement patterns. These data hold an immense promise for understanding human behavior on a vast scale, and with a precision and accuracy never before possible with censuses, surveys or other existing data collection techniques. There is already a significant body of literature that has made key inroads into understanding human mobility using this exciting new data source, and there have been several different measures of mobility used. However, existing mobile phone based mobility measures are inconsistent, inaccurate, and confounded with social characteristics of local context. New measures would best be developed immediately as they will influence future studies of mobility using mobile phone data. In this article, we do exactly this. We discuss problems with existing mobile phone based measures of mobility and describe new methods for measuring mobility that address these concerns. Our measures of mobility, which incorporate both mobile phone records and detailed GIS data, are designed to address the spatial nature of human mobility, to remain independent of social characteristics of context, and to be comparable across geographic regions and time. We also contribute a discussion of the variety of uses for these new measures in developing a better understanding of how human mobility influences micro-level human behaviors and well-being, and macro-level social organization and change.

Bayes computation for ecological inference.

Ecological data are available at the level of the group, rather than at the level of the individual. The use of ecological data in spatial epidemiological investigations is particularly common. Although the computational methods described are more generally applicable, this paper concentrates on the situation in which the margins of 2 × 2 tables are observed in each of n geographical areas, with a Bayesian approach to inference. We consider auxiliary schemes that impute the missing data, and compare with a previously suggested normal approximation. The analysis of ecological data is subject to ecological bias, with the only reliable means of removing such bias being the addition of auxiliary individual-level information. Various schemes have been suggested for this supplementation, and we illustrate how the computational methods may be applied to the analysis of such enhanced data. The methods are illustrated using simulated data and two examples. In the first example, the ecological data are supplemented with a simple random sample of individual-level data, and in this example the normal approximation fails. In the second example case-control sampling provides the additional information.

Monte Carlo algorithms for Hardy-Weinberg proportions.

The Hardy-Weinberg law is among the most important principles in the study of biological systems. Given its importance, many tests have been devised to determine whether a finite population follows Hardy-Weinberg proportions. Because asymptotic tests can fail, Guo and Thompson developed an exact test; unfortunately, the Monte Carlo method they proposed to evaluate their test has a running time that grows linearly in the size of the population N. Here, we propose a new algorithm whose expected running time is linear in the size of the table produced, and completely independent of N. In practice, this new algorithm can be considerably faster than the original method.