Browsing by Author "Schwartz S"

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Intimate partner violence polyvictimisation and HIV among coupled women in Zambia: Analysis of a population-based survey.
(2020-Apr) Beres LK; Merrill KG; McGready J; Denison JA; Schwartz S; Sikazwe I; Decker MR; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.; Center for Public Health & Human Rights, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.; Department of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
Women in sub-Saharan Africa are disproportionately at risk for the dual epidemics of intimate partner violence (IPV) and HIV. Little is known about how specific violence profiles affect women's HIV risk, limiting effective intervention. We analysed couples' data from the Zambia Demographic and Health Survey 2013-2014 to evaluate relationships among IPV, male partner HIV status and women's HIV status. We considered the individual and combined effects of physical, sexual, emotional, and high controlling behaviour violence and accumulated violence exposure, respectively. Among partnered women, 48.9% (
Patterns and Predictors of Incident Return to HIV Care Among Traced, Disengaged Patients in Zambia: Analysis of a Prospective Cohort.
(2021-Mar-01) Beres LK; Schwartz S; Simbeza S; McGready J; Eshun-Wilson I; Mwamba C; Sikombe K; Topp SM; Somwe P; Mody A; Mukamba N; Ehrenkranz PD; Padian N; Pry J; Moore CB; Holmes CB; Sikazwe I; Denison JA; Geng E; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.; Department of Medicine, Georgetown University, Washington, DC.; The Bill & Melinda Gates Foundation, Seattle, WA.; Division of Infectious Diseases, University of Alabama at Birmingham, Birmingham, AL.; Division of Epidemiology, University of California Berkeley, Berkeley, CA; and.; Division of Infectious Diseases, Washington University School of Medicine, University of Washington, St. Louis, St. Louis, MO.; College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Australia.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
BACKGROUND: Dynamic movement of patients in and out of HIV care is prevalent, but there is limited information on patterns of patient re-engagement or predictors of return to guide HIV programs to better support patient engagement. METHODS: From a probability-based sample of lost to follow-up, adult patients traced by peer educators from 31 Zambian health facilities, we prospectively followed disengaged HIV patients for return clinic visits. We estimated the cumulative incidence of return and the time to return using Kaplan-Meier methods. We used univariate and multivariable Cox proportional hazards regression to conduct a risk factor analysis identifying predictors of incident return across a social ecological framework. RESULTS: Of the 556 disengaged patients, 73.0% [95% confidence interval (CI): 61.0 to 83.8] returned to HIV care. The median follow-up time from disengagement was 32.3 months (interquartile range: 23.6-38.9). The rate of return decreased with time postdisengagement. Independent predictors of incident return included a previous gap in care [adjusted Hazard Ratio (aHR): 1.95, 95% CI: 1.23 to 3.09] and confronting a stigmatizer once in the past year (aHR: 2.14, 95% CI: 1.25 to 3.65). Compared with a rural facility, patients were less likely to return if they sought care from an urban facility (aHR: 0.68, 95% CI: 0.48 to 0.96) or hospital (aHR: 0.52, 95% CI: 0.33 to 0.82). CONCLUSIONS: Interventions are needed to hasten re-engagement in HIV care. Early and differential interventions by time since disengagement may improve intervention effectiveness. Patients in urban and tertiary care settings may need additional support. Improving patient resilience, outreach after a care gap, and community stigma reduction may facilitate return. Future re-engagement research should include causal evaluation of identified factors.
Profiles of HIV Care Disruptions Among Adult Patients Lost to Follow-up in Zambia: A Latent Class Analysis.
(2021-Jan-01) Mody A; Sikombe K; Beres LK; Simbeza S; Mukamba N; Eshun-Wilson I; Schwartz S; Pry J; Padian N; Holmes CB; Bolton-Moore C; Sikazwe I; Geng EH; Division of Epidemiology, University of California, Berkeley, Berkeley, CA.; Centre for Infectious Diseases Research in Zambia, Lusaka, Zambia.; Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO.; Division of Infectious Diseases, University of Alabama, Birmingham, AL.; Department of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD.; Department of Public Health Environments and Society, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom.; Department of Medicine, Georgetown University, Washington, DC; and.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
BACKGROUND: Patients report varied barriers to HIV care across multiple domains, but specific barrier patterns may be driven by underlying, but unobserved, behavioral profiles. METHODS: We traced a probability sample of patients lost to follow-up (>90 days late) as of July 31, 2015 from 64 clinics in Zambia. Among those found alive, we ascertained patient-reported reasons for care disruptions. We performed latent class analysis to identify patient subgroups with similar patterns of reasons reported and assessed the association between class membership and care status (ie, disengaged versus silently transferred to a new site). RESULTS: Among 547 patients, we identified 5 profiles of care disruptions: (1) "Livelihood and Mobility" (30.6% of the population) reported work/school obligations and mobility/travel as reasons for care disruptions; (2) "Clinic Accessibility" (28.9%) reported challenges with attending clinic; (3) "Mobility and Family" (21.9%) reported family obligations, mobility/travel, and transport-related reasons; (4) "Doubting Need for HIV care" (10.2%) reported uncertainty around HIV status or need for clinical care, and (5) "Multidimensional Barriers to Care" (8.3%) reported numerous (mean 5.6) reasons across multiple domains. Patient profiles were significantly associated with care status. The "Doubting Need for HIV Care" class were mostly disengaged (97.9%), followed by the "Multidimensional Barriers to Care" (62.8%), "Clinic Accessibility" (62.4%), "Livelihood and Mobility" (43.6%), and "Mobility and Family" (23.5%) classes. CONCLUSION: There are distinct HIV care disruption profiles that are strongly associated with patients' current engagement status. Interventions targeting these unique profiles may enable more effective and tailored strategies for improving HIV treatment outcomes.
The effect of tracer contact on return to care among adult, "lost to follow-up" patients living with HIV in Zambia: an instrumental variable analysis.
(2021-Dec) Beres LK; Mody A; Sikombe K; Nicholas LH; Schwartz S; Eshun-Wilson I; Somwe P; Simbeza S; Pry JM; Kaumba P; McGready J; Holmes CB; Bolton-Moore C; Sikazwe I; Denison JA; Geng EH; Division of Infectious Disease, Johns Hopkins University School of Medicine, Baltimore, MD, USA.; Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.; Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.; Center for Innovation in Global Health, Georgetown University, Washington, DC, USA.; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.; Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, USA.; Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
INTRODUCTION: Tracing patients lost to follow-up (LTFU) from HIV care is widely practiced, yet we have little knowledge of its causal effect on care engagement. In a prospective, Zambian cohort, we examined the effect of tracing on return to care within 2 years of LTFU. METHODS: We traced a stratified, random sample of LTFU patients who had received HIV care between August 2013 and July 2015. LTFU was defined as a gap of >90 days from last scheduled appointment in the routine electronic medical record. Extracting 2 years of follow-up visit data through 2017, we identified patients who returned. Using random selection for tracing as an instrumental variable (IV), we used conditional two-stage least squares regression to estimate the local average treatment effect of tracer contact on return. We examined the observational association between tracer contact and return among patient sub-groups self-confirmed as disengaged from care. RESULTS: Of the 24,164 LTFU patients enumerated, 4380 were randomly selected for tracing and 1158 were contacted by a tracer within a median of 14.8 months post-loss. IV analysis found that patients contacted by a tracer because they were randomized to tracing were no more likely to return than those not contacted (adjusted risk difference [aRD]: 3%, 95% CI: -2%, 8%, p = 0.23). Observational data showed that among contacted, disengaged patients, the rate of return was higher in the week following tracer contact (IR 5.74, 95% CI: 3.78-8.71) than in the 2 weeks to 1-month post-contact (IR 2.28, 95% CI: 1.40-3.72). There was a greater effect of tracing among patients lost for >6 months compared to those contacted within 3 months of loss. CONCLUSIONS: Overall, tracer contact did not causally increase LTFU patient return to HIV care, demonstrating the limited impact of tracing in this program, where contact occurred months after patients were LTFU. However, observational data suggest that tracing may speed return among some LTFU patients genuinely out-of-care. Further studies may improve tracing effectiveness by examining the mechanisms underlying the impact of tracing on return to care, the effect of tracing at different times-since-loss and using more accurate identification of patients who are truly disengaged to target tracing.