IntroductionA broad range of community‐centred care models for patients stable on anti‐retroviral therapy (ART) have been proposed by the World Health Organization to better respond to patient needs and alleviate pressure on health systems caused by rapidly growing patient numbers. Where available, often a single alternative care model is offered in addition to routine clinical care. We operationalized several community‐centred ART delivery care models in one public sector setting. Here, we compare retention in care and on ART and identify predictors of disengagement with care.MethodsPatients on ART were enrolled into three community‐centred ART delivery care models in the rural Shiselweni region (Swaziland), from 02/2015 to 09/2016: Community ART Groups (CAGs), comprehensive outreach care and treatment clubs. We used Kaplan–Meier estimates to describe crude retention in care model and retention on ART (including patients who returned to clinical care). Multivariate Cox proportional hazard models were used to determine factors associated with all‐cause attrition from care model and disengagement with ART.ResultsA total of 918 patients were enrolled. CAGs had the most participants with 531 (57.8%). Median age was 44.7 years (IQR 36.3 to 54.4), 71.8% of patients were female, and 62.6% fulfilled eligibility criteria for community ART. The 12‐month retention in ART was 93.7% overall; it was similar between model types (p = 0.52). A considerable proportion of patients returned from community ART to clinical care, resulting in lower 12 months retention in care model (82.2% overall); retention in care model was lowest in CAGs at 70.4%, compared with 86.3% in outreach and 90.4% in treatment clubs (p < 0.001). In multivariate Cox regression models, patients in CAGs had a higher risk of disengaging from care model (aHR 3.15, 95% CI 2.01 to 4.95, p < 0.001) compared with treatment clubs. We found, however, no difference in attrition in ART between alternative model types.ConclusionsConcurrent implementation of three alternative community‐centred ART models in the same region was feasible. Although a considerable proportion of patients returned back to clinical care, overall ART retention was high and should encourage programme managers to offer community‐centred care models adapted to their specific setting.
Background Cervical cancer is among the most common preventable cancers with the highest morbidity and mortality. The World Health Organization (WHO) recommends visual inspection of the cervix with acetic acid (VIA) as cervical cancer screening strategy in resource-poor settings. However, there are barriers to the sustainability of VIA programs including declining providers’ VIA competence without mentorship and quality assurances and challenges of integration into primary healthcare. This study seeks to evaluate the impact of smartphone-based strategies in improving reliability, reproducibility, and quality of VIA in humanitarian settings. Methods and findings We implemented smartphone-based VIA that included standard VIA training, adapted refresher, and 6-month mHealth mentorship, sequentially, in the rural Shiselweni region of Eswatini. A remote expert reviewer provided diagnostic and management feedback on patients’ cervical images, which were reviewed weekly by nurses. Program’s outcomes, VIA image agreement rates, and Kappa statistic were compared before, during, and after training. From September 1, 2016 to December 31, 2018, 4,247 patients underwent screening; 247 were reviewed weekly by a VIA diagnostic expert. Of the 247, 128 (49%) were HIV–positive; mean age was 30.80 years (standard deviation [SD]: 7.74 years). Initial VIA positivity of 16% (436/2,637) after standard training gradually increased to 25.1% (293/1,168), dropped to an average of 9.7% (143/1,469) with a lowest of 7% (20/284) after refresher in 2017 (p = 0.001), increased again to an average of 9.6% (240/2,488) with a highest of 17% (17/100) before the start of mentorship, and dropped to an average of 8.3% (134/1,610) in 2018 with an average of 6.3% (37/591) after the start of mentorship (p = 0.019). Overall, 88% were eligible for and 68% received cryotherapy the same day: 10 cases were clinically suspicious for cancer; however, only 5 of those cases were confirmed using punch biopsy. Agreement rates with the expert reviewer for positive and negative cases were 100% (95% confidence interval [CI]: 79.4% to 100%) and 95.7% (95% CI: 92.2% to 97.9%), respectively, with negative predictive value (NPV) (100%), positive predictive value (PPV) (63.5%), and area under the curve of receiver operating characteristics (AUC ROC) (0.978). Kappa statistic was 0.74 (95% CI; 0.58 to 0.89); 0.64 and 0.79 at 3 and 6 months, respectively. In logistic regression, HIV and age were associated with VIA positivity (adjusted Odds Ratio [aOR]: 3.53, 95% CI: 1.10 to 11.29; p = 0.033 and aOR: 1.06, 95% CI: 1.0004 to 1.13; p = 0.048, respectively). We were unable to incorporate a control arm due to logistical constraints in routine humanitarian settings. Conclusions Our findings suggest that smartphone mentorship provided experiential learning to improve nurses’ competencies and VIA reliability and reproducibility, reduced false positive, and introduced peer-to-peer education and quality control services. Local collaboration; extending services to remote populations; decreasing unnecessary burden to screened women, providers, and tertiary centers; and capacity building through low-tech high-yield screening are promising strategies for scale-up of VIA programs.
ObjectivesTo assess long‐term antiretroviral therapy (ART) outcomes during rapid HIV programme expansion in the public sector of Eswatini (formerly Swaziland).MethodsThis is a retrospectively established cohort of HIV‐positive adults (≥16 years) who started first‐line ART in 25 health facilities in Shiselweni (Eswatini) between 01/2006 and 12/2014. Temporal trends in ART attrition, treatment expansion and ART coverage were described over 9 years. We used flexible parametric survival models to assess the relationship between time to ART attrition and covariates.ResultsOf 24 772 ART initiations, 6% (n = 1488) occurred in 2006, vs. 13% (n = 3192) in 2014. Between these years, median CD4 cell count at ART initiation increased (113–265 cells/mm3). The active treatment cohort expanded 8.4‐fold, ART coverage increased 8.0‐fold (7.1% in 2006 vs. 56.8% in 2014) and 12‐month crude ART retention improved from 71% to 86%. Compared with the pre‐decentralisation period (2006–2007), attrition decreased by 5% (adjusted hazard ratio [aHR] 0.95, 95% confidence interval 0.88–1.02) during HIV‐TB service decentralisation (2008–2010), by 17% (aHR 0.83, 0.75–0.92) during service consolidation (2011–2012), and by 20% (aHR 0.80, 0.71–0.90) during further treatment expansion (2013–2014). The risk of attrition was higher for young age, male sex, pathological baseline haemoglobin and biochemistry results, more toxic drug regimens, WHO III/IV staging and low CD4 cell count; access to a telephone was protective.ConclusionsProgrammatic outcomes improved during large expansion of the treatment cohort and increased ART coverage. Changes in ART programming may have contributed to better outcomes.
objectives WHO recommends HIV self-testing (HIVST) as an additional approach to HIV testing services. The study describes the strategies used during phase-in of HIVST under routine conditions in Eswatini (formerly Swaziland). oral HIVST was offered at HIV testing services (HTS) sites to people aged ≥ 16 years. Additional support tools were available, including a telephone hotline answered 24/7, HIVST demonstration videos and printed educational information about HIV prevention and care services. Demographic characteristics of HIVST users were described and compared with standard blood-based HTS in the community. HIVST results were monitored with follow-up phone calls and the hotline.results During the 9-month period, 1895 people accessed HIVST and 2415 HIVST kits were distributed. More people accessed HIVST kits in the community (n = 1365, 72.0%) than at health facilities (n = 530, 28.0%). The proportion of males and median age among those accessing HIVST and standard HTS in the community were similar (49.3%, 29 years HIVST vs. 48.7%, 27 years standard HTS). In total, 34 (3.9%) reactive results were reported from 938 people with known HIVST results; 32.4% were males, and median age was 30 years (interquartile range 25-36). Twenty-one (62%) patients were known to have received confirmatory blood-based HTS; of these, 20 (95%) had concordant reactive results and 19 (95%) were linked to HIV care at a clinic.conclusion Integration of HIVST into existing HIV facility-and community-based testing strategies in Eswatini was found to be feasible, and HIVST has been adopted by national testing bodies in Eswatini. keywords HIV, Eswatini, HTS, undiagnosedSustainable Development Goals (SDGs): SDG 3 (good health and well-being), SDG 10 (reduced inequalities), SDG 17 (partnerships for the goals)
Objectives This paper assesses patient‐ and population‐level trends in TB notifications during rapid expansion of antiretroviral therapy in Eswatini which has an extremely high incidence of both TB and HIV. Methods Patient‐ and population‐level predictors and rates of HIV‐associated TB were examined in the Shiselweni region in Eswatini from 2009 to 2016. Annual population‐level denominators obtained from projected census data and prevalence estimates obtained from population‐based surveys were combined with individual‐level TB treatment data. Patient‐ and population‐level predictors of HIV‐associated TB were assessed with multivariate logistic and multivariate negative binomial regression models. Results Of 11 328 TB cases, 71.4% were HIV co‐infected and 51.8% were women. TB notifications decreased fivefold between 2009 and 2016, from 1341 to 269 cases per 100 000 person‐years. The decline was sixfold in PLHIV vs. threefold in the HIV‐negative population. Main patient‐level predictors of HIV‐associated TB were recurrent TB treatment (adjusted odds ratio [aOR] 1.40, 95% confidence interval [CI]: 1.19–1.65), negative (aOR 1.31, 1.15–1.49) and missing (aOR 1.30, 1.11–1.53) bacteriological status and diagnosis at secondary healthcare level (aOR 1.18, 1.06–1.33). Compared with 2009, the probability of TB decreased for all years from 2011 (aOR 0.69, 0.58–0.83) to 2016 (aOR 0.54, 0.43–0.69). The most pronounced population‐level predictor of TB was HIV‐positive status (adjusted incidence risk ratio 19.47, 14.89–25.46). Conclusions This high HIV‐TB prevalence setting experienced a rapid decline in TB notifications, most pronounced in PLHIV. Achievements in HIV‐TB programming were likely contributing factors.
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