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BACKGROUND: The global campaign for Undetectable equals Untransmittable (U = U) seeks to spread awareness of HIV treatment as prevention, aiming to enhance psychological well-being and diminish stigma. Despite its potential benefits, U = U faces challenges in Sub-Saharan Africa, with low awareness and hesitancy to endorse it. We sought to develop a U = U communications intervention to support HIV counselling in primary healthcare settings in South Africa. METHODS: We used Intervention Mapping (IM), a theory-based framework to develop the Undetectable and You intervention for the South African context. The six steps of the IM protocol were systematically applied to develop the intervention including a needs assessment consisting of a systematic review and qualitative research including focus group discussions (FGD) and key informant (KI) interviews. Program objectives and target population were determined before designing the intervention components and implementation plan. RESULTS: The needs assessment indicated low global U = U awareness, especially in Africa, and scepticism about its effectiveness. Lay counsellors and clinic managers stressed the need for a simple and standardized presentation of U = U addressing both patients needs for encouragement and modelling of U = U success but also clear guidance toward ART adherence behaviour. Findings from each step of the process informed successive steps. Our final intervention consisted of personal testimonials of PLHIV role models and their partners, organized as an App to deliver U = U information to patients in primary healthcare settings. CONCLUSIONS: We outline an intervention development strategy, currently in evaluation stage, utilizing IM with formative research and input from key U = U stakeholders and people living with HIV (PLHIV).

Rationale: In critically ill patients, a hemoglobin transfusion threshold of 20% absolute increase in transfusion rates in all three cohorts. Transfusion was associated with increases in hemoglobin concentration in the subsequent 24-72 hours (MIMIC-IV, 2.4 [95% confidence interval (CI), 1.1 to 3.6] g/dl; eICU, 0.7 [95% CI, 0.3 to 1.2] g/dl; Premier Inc., 1.9 [95% CI, 1.5 to 2.2] g/dl) but not with improvement in organ dysfunction (MIMIC-IV, 4.6 [95% CI, -1.2 to 10] points; eICU, 4.4 [95% CI, 0.9 to 7.8] points; Premier Inc., 1.1 [95% CI, -0.2 to 2.3] points) compared with no transfusion. Conclusions: Transfusion was not associated with improved organ dysfunction compared with no transfusion at a hemoglobin threshold of 7.0 g/dl, suggesting that evaluation of transfusion targets other than a hemoglobin threshold of 7.0 g/dl may be warranted.

People on HIV treatment with undetectable virus cannot transmit HIV sexually (Undetectable = Untransmittable, U = U). However, the science of treatment-as-prevention (TasP) may not be widely understood by people with and without HIV who could benefit from this information. We systematically reviewed the global literature on knowledge and attitudes related to TasP and interventions providing TasP or U = U information. We included studies of providers, patients, and communities from all regions of the world, published 2008-2020. We screened 885 papers and abstracts and identified 72 for inclusion. Studies in high-income settings reported high awareness of TasP but gaps in knowledge about the likelihood of transmission with undetectable HIV. Greater knowledge was associated with more positive attitudes towards TasP. Extant literature shows low awareness of TasP in Africa where 2 in 3 people with HIV live. The emerging evidence on interventions delivering information on TasP suggests beneficial impacts on knowledge, stigma, HIV testing, and viral suppression.Review was pre-registered at PROSPERO: CRD42020153725.

ObjectivesThe Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 and other cross-sectional metrics can lead to potentially counterintuitive conclusions when used to evaluate health systems' performance. This study demonstrates how time and population dynamics impact UNAIDS 90-90-90 metrics in comparison with a longitudinal analogue.DesignA simplified simulation representing a hypothetical population was used to estimate and compare inference from UNAIDS 90-90-90 metrics and longitudinal metrics based on Kaplan-Meier-estimated 2-year probability of transition between stages.MethodsWe simulated a large cohort over 15 years. Everyone started out at risk for HIV, and then transitioned through the HIV care continuum based on fixed daily probabilities of acquiring HIV, learning status, entering care, initiating antiretroviral therapy (ART), and becoming virally suppressed, or dying. We varied the probability of ART initiation over three five-year periods (low, high, and low). We repeated the simulation with an increased probability of death.ResultsThe cross-sectional probability of being on ART among persons who were diagnosed responded relatively slowly to changes in the rate of ART initiation. Increases in ART initiation rates caused apparent declines in the cross-sectional probability of being virally suppressed among persons who had initiated ART, despite no changes in the rate of viral suppression. In some cases, higher mortality resulted in the cross-sectional metrics implying improved healthcare system performance. The longitudinal continuum was robust to these issues.ConclusionThe UNAIDS 90-90-90 care continuum may lead to incorrect inference when used to evaluate health systems performance. We recommend that evaluation of HIV care delivery include longitudinal care continuum metrics wherever possible.

Background: Under South Africa's Universal Test and Treat (UTT) policy, CD4 counts are no longer required to determine HIV treatment eligibility. However, CD4 count at presentation remains an important marker of disease progression. We assessed whether CD4 testing declined in the UTT era and, if so, by how much. Methods: We analysed CD4 count data from the National Health Laboratory Service (NHLS) National HIV Cohort and TIER.Net database for individuals in HIV care across five South African provinces. "First CD4 count" was defined as the first CD4 test recorded for each patient. In TIER.Net, "date of presentation" was the earliest date of HIV testing, CD4 measurement, or clinic visit. Trends in first CD4 testing volumes (2004–2018) were analyzed, with interrupted time-series analyses assessing the impact of UTT (September 2016). Results: Data included 5,274,218 (NHLS) and 2,265,557 (TIER.Net) individuals with a first CD4 count. In NHLS, first CD4 counts increased from 47,604 in 2004 to 383,705 in 2010 and then declined. Lower volumes were recorded in TIER.Net. Adjusting for prior trends, first CD4 counts increased slightly after UTT, by 32 individuals/day in NHLS (95% CI: − 6 to 61) and 88 individuals/day in TIER.Net (95% CI: 30 to 148). Among TIER.Net patients, the percentage with a CD4 count decreased by 4.3% (95% CI: − 5.2 to − 3.0%). Conclusions: We found no major decline in CD4 testing at presentation following UTT, contrasting findings from resource-constrained settings with greater reliance on external donors. [ABSTRACT FROM AUTHOR]

South Africa has a high tuberculosis (TB) prevalence, complicated by multidrug resistance to rifampin and isoniazid (1). In 2018, multidrug-resistant (MDR) and rifampin-resistant (RR) TB accounted for 3.4% of new [...]

Introduction: Policies for Universal Test & Treat (UTT) and same-day initiation (SDI) of antiretroviral therapy (ART) were instituted in South Africa in September 2016 and 2017 respectively. However, there is limited evidence on whether these changes have improved patient retention after HIV diagnosis. Methods: We enrolled three cohorts of newly diagnosed HIV-infected adults from two primary health clinics in Johannesburg from April to November 2015 (Pre-UTT, N = 144), May-September 2017 (UTT, N = 178) and October-December 2017 (SDI, N = 88). A baseline survey was administered immediately after HIV diagnosis after which follow-up using clinical records (paper charts, electronic health records and laboratory data) ensued for 12 months. The primary outcome was patient loss to follow-up (being >90 days late for the last scheduled appointment) at 12 months post-HIV diagnosis. We modelled attrition across HIV policy periods with Cox proportional hazard regression. Results: Overall, 410 of 580 screened HIV-positive patients were enrolled. Overall, attrition at 12 months was 30% lower in the UTT guideline period (38.2%) compared to pre-UTT (47.2%, aHR 0.7, 95% CI: 0.5 to 1.0). However, the total attrition was similar between the SDI (47.7%) and pre-UTT cohorts (aHR 1.0, 95% CI: 0.7 to 1.5). Older age at HIV diagnosis (aHR 0.5 for [greater than or equal to]40 vs. 25 to 29 years, 95% CI: 0.3 to 0.8) and being in a non-marital relationship (aHR 0.5 vs. being single, 95% CI: 0.3 to 0.8) protected against LTFU at 12 months, whereas LTFU rates increased with longer travel time to the diagnosing clinic (aHR 1.8 for [greater than or equal to]30 minutes vs. [less than or equal to]15 minutes, 95% CI: 1.1 to 3.1). In analyses adjusted for the time-varying ART initiation status, compared to the pre-ART period of care, the hazard of on-ART LTFU was 90% higher among participants diagnosed under the SDI policy compared to pre-UTT (aHR 1.9, 95% CI: 1.1 to 2.9). Conclusions: Overall, nearly two-fifths of HIV positive patients are likely to disengage from care by 12 months after HIV diagnosis under the new SDI policy. Furthermore, the increase in on-ART patient attrition after the introduction of the SDI policy is cause for concern. Further research is needed to determine the best way for rapidly initiating patients on ART and also reducing long-term attrition from care. Keywords: HIV; attrition from HIV care; ART adherence; Universal Test and Treat; same-day initiation of ART; HIV; ART access; attrition from HIV care; ART adherence; Universal Test and Treat; same-day initiation of ART, 1 | INTRODUCTION South Africa has experienced a dramatic increase in the number of patients initiating antiretroviral therapy (ART) since the start of the national HIV treatment programme in 2004. [...]

Background Inequities in Coronavirus Disease 2019 (COVID-19) vaccine and booster coverage may contribute to future disparities in morbidity and mortality within and between Massachusetts (MA) communities. Methods and findings We conducted a population-based cross-sectional study of primary series vaccination and booster coverage 18 months into the general population vaccine rollout. We obtained public-use data on residents vaccinated and boosted by ZIP code (and by age group: 5 to 19, 20 to 39, 40 to 64, 65+) from MA Department of Public Health, as of October 10, 2022. We constructed population denominators for postal ZIP codes by aggregating census tract population estimates from the 2015-2019 American Community Survey. We excluded nonresidential ZIP codes and the smallest ZIP codes containing 1% of the state's population. We mapped variation in ZIP code-level primary series vaccine and booster coverage and used regression models to evaluate the association of these measures with ZIP code-level socioeconomic and demographic characteristics. Because age is strongly associated with COVID-19 severity and vaccine access/uptake, we assessed whether observed socioeconomic and racial/ethnic inequities persisted after adjusting for age composition and plotted age-specific vaccine and booster coverage by deciles of ZIP code characteristics. We analyzed data on 418 ZIP codes. We observed wide geographic variation in primary series vaccination and booster rates, with marked inequities by ZIP code-level education, median household income, essential worker share, and racial/ethnic composition. In age-stratified analyses, primary series vaccine coverage was very high among the elderly. However, we found large inequities in vaccination rates among younger adults and children, and very large inequities in booster rates for all age groups. In multivariable regression models, each 10 percentage point increase in 'percent college educated' was associated with a 5.1 (95% confidence interval (CI) 3.9 to 6.3, p < 0.001) percentage point increase in primary series vaccine coverage and a 5.4 (95% CI 4.5 to 6.4, p < 0.001) percentage point increase in booster coverage. Although ZIP codes with higher 'percent Black/Latino/Indigenous' and higher 'percent essential workers' had lower vaccine coverage (-0.8, 95% CI -1.3 to -0.3, p < 0.01; -5.5, 95% CI -7.3 to -3.8, p < 0.001), these associations became strongly positive after adjusting for age and education (1.9, 95% CI 1.0 to 2.8, p < 0.001; 4.8, 95% CI 2.6 to 7.1, p < 0.001), consistent with high demand for vaccines among Black/Latino/Indigenous and essential worker populations within age and education groups. Strong positive associations between 'median household income' and vaccination were attenuated after adjusting for age. Limitations of the study include imprecision of the estimated population denominators, lack of individual-level sociodemographic data, and potential for residential ZIP code misreporting in vaccination data. Conclusions Eighteen months into MA's general population vaccine rollout, there remained large inequities in COVID-19 primary series vaccine and booster coverage across MA ZIP codes, particularly among younger age groups. Disparities in vaccination coverage by racial/ethnic composition were statistically explained by differences in age and education levels, which may mediate the effects of structural racism on vaccine uptake. Efforts to increase booster coverage are needed to limit future socioeconomic and racial/ethnic disparities in COVID-19 morbidity and mortality., Author(s): Jacob Bor 1,2,*, Sabrina A. Assoumou 3,4, Kevin Lane 5, Yareliz Diaz 6, Bisola O. Ojikutu 7, Julia Raifman 6, Jonathan I. Levy 5 Introduction Vaccination against Coronavirus Disease [...]

Background Hypertension represents one of the major risk factors for cardiovascular morbidity and mortality globally. Early detection and treatment of this condition is vital to prevent complications. However, hypertension often goes undetected, and even if detected, not every patient receives adequate treatment. Identifying simple and effective interventions is therefore crucial to fight this problem and allow more patients to receive the treatment they need. Therefore, we aim at investigating the impact of a population-based blood pressure (BP) screening and the subsequent 'low-threshold' information treatment on long-term cardiovascular disease (CVD) morbidity and mortality. Methods and findings We examined the impact of a BP screening embedded in a population-based cohort study in Germany and subsequent personalized 'light touch' information treatment, including a hypertension diagnosis and a recommendation to seek medical attention. We pooled four waves of the KORA study, carried out between 1984 and 1996 (N = 14,592). Using a sharp multivariate regression discontinuity (RD) design, we estimated the impact of the information treatment on CVD mortality and morbidity over 16.9 years. Additionally, we investigated potential intermediate outcomes, such as hypertension awareness, BP, and behavior after 7 years. No evidence of effect of BP screening was observed on CVD mortality (hazard ratio (HR) = 1.172 [95% confidence interval (CI): 0.725, 1.896]) or on any (fatal or nonfatal) long-term CVD event (HR = 1.022 [0.636, 1.641]) for individuals just above (versus below) the threshold for hypertension. Stratification for previous self-reported diagnosis of hypertension at baseline did not reveal any differential effect. The intermediate outcomes, including awareness of hypertension, were also unaffected by the information treatment. However, these results should be interpreted with caution since the analysis might not be sufficiently powered to detect a potential intervention effect. Conclusions The study does not provide evidence of an effect of the assessed BP screening and subsequent information treatment on BP, health behavior, or long-term CVD mortality and morbidity. Future studies should consider larger datasets to detect possible effects and a shorter follow-up for the intermediate outcomes (i.e., BP and behavior) to detect short-, medium-, and long-term effects of the intervention along the causal pathway., Author(s): Sara Pedron 1,2,3,*, Michael Hanselmann 1, Jacob Burns 1,4,5, Alexander Rich 2,4,5, Annette Peters 6, Margit Heier 6,7, Lars Schwettmann 2,8, Jacob H. Bor 9,10, Till Bärnighausen 11,12,13, Michael [...]

Introduction: In South Africa, HIV patients with an elevated viral load (VL) should receive repeat VL testing after adherence counselling. We set out to use a national HIV Cohort to describe time to repeat viral load testing across South Africa and identify predictors of time to repeat testing. Methods: We conducted a cohort study of prospectively collected laboratory data. HIV treatment guidelines have changed over time in South Africa, but call for repeat VL testing within six months if 400 to 1000 copies/mL and two to three months if >1000 copies/mL. We included patients with suppressed viral loads (indicating they are on ART) and a first elevated VL (>400 copies/mL) between April 2004 and December 2014. Follow-up began at first elevated VL and continued until repeat testing, loss to follow-up or December 2016. We calculated adjusted hazard ratios (aHR) using Cox proportional hazard models. Results: Of 371,648 patients with a VL > 400, 83.9% (311,790) had a repeat VL, in a median (IQR) of 7.0 (4.1 to 12.2) months. Of those with a first viral load 400 to 1000 copies/mL, 56.4% had a repeat VL within guideline recommended six months (defined as up to nine months), whereas among those >1000 copies/mL only 47.7% had a repeat viral load within guideline recommended two to three months (defined as up to six months). We found a small increase in repeat testing associated with higher VL value (aHR 1.11; 95% CI: 1.10 to 1.12 comparing >1000 vs 400 to 1000 copies/mL) and very low CD4 counts at first elevated VL (aHR 1.16; 95% CI: 1.13 to 1.19 comparing CD4 < 50 vs Conclusions: Median time to repeat viral load testing for those with an elevated viral load was longer than guidelines recommend. Future work should identify whether delays are due to patient or provider factors. Keywords: viral load; viral suppression; monitoring; retention; laboratory testing; cohort; HIV, 1 | INTRODUCTION After patients initiate antiretroviral therapy (ART) for treatment of HIV, laboratory monitoring of patient progress is critical to ensuring treatment success. For individual patients, this means reaching [...]

Background Coronavirus Disease 2019 (COVID-19) excess deaths refer to increases in mortality over what would normally have been expected in the absence of the COVID-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to COVID-19. In this study, we take advantage of county-level variation in COVID-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to COVID-19 varies across subsets of counties defined by sociodemographic and health characteristics. Methods and findings In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct COVID-19 and all-cause mortality occurring in US counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a 10-week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more COVID-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black, and 59.6% non-Hispanic White. A total of 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and COVID-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to COVID-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than COVID-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to COVID-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of COVID-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to COVID-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics. Conclusions In this study, we found that direct COVID-19 death counts in the US in 2020 substantially underestimated total excess mortality attributable to COVID-19. Racial and socioeconomic inequities in COVID-19 mortality also increased when excess deaths not assigned to COVID-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic., Author(s): Andrew C. Stokes 1,*, Dielle J. Lundberg 1, Irma T. Elo 2, Katherine Hempstead 3, Jacob Bor 1,4, Samuel H. Preston 2 Introduction The novel Coronavirus Disease 2019 (COVID-19) [...]

Background Despite widespread availability of HIV treatment, patient outcomes differ across facilities. We propose and evaluate an approach to measure quality of HIV care at health facilities in South Africa's national HIV program using routine laboratory data. Methods and findings Data were extracted from South Africa's National Health Laboratory Service (NHLS) Corporate Data Warehouse. All CD4 counts, viral loads (VLs), and other laboratory tests used in HIV monitoring were linked, creating a validated patient identifier. We constructed longitudinal HIV care cascades for all patients in the national HIV program, excluding data from the Western Cape and very small facilities. We then estimated for each facility in each year (2011 to 2015) the following cascade measures identified a priori as reflecting quality of HIV care: median CD4 count among new patients; retention 12 months after presentation; 12-month retention among patients established in care; viral suppression; CD4 recovery; monitoring after an elevated VL. We used factor analysis to identify an underlying measure of quality of care, and we assessed the persistence of this quality measure over time. We then assessed spatiotemporal variation and facility and population predictors in a multivariable regression context. We analyzed data on 3,265 facilities with a median (IQR) annual size of 441 (189 to 988) lab-monitored HIV patients. Retention 12 months after presentation increased from 42% to 47% during the study period, and viral suppression increased from 66% to 79%, although there was substantial variability across facilities. We identified an underlying measure of quality of HIV care that correlated with all cascade measures except median CD4 count at presentation. Averaging across the 5 years of data, this quality score attained a reliability of 0.84. Quality was higher for clinics (versus hospitals), in rural (versus urban) areas, and for larger facilities. Quality was lower in high-poverty areas but was not independently associated with percent Black. Quality increased by 0.49 (95% CI 0.46 to 0.53) standard deviations from 2011 to 2015, and there was evidence of geospatial autocorrelation (p < 0.001). The study's limitations include an inability to fully adjust for underlying patient risk, reliance on laboratory data which do not capture all relevant domains of quality, potential for errors in record linkage, and the omission of Western Cape. Conclusions We observed persistent differences in HIV care and treatment outcomes across South African facilities. Targeting low-performing facilities for additional support could reduce overall burden of disease., Author(s): Jacob Bor 1,2,3,*, Anna Gage 4, Dorina Onoya 2, Mhairi Maskew 2, Yorghos Tripodis 5, Matthew P. Fox 1,2,3, Adrian Puren 6, Sergio Carmona 6, Koleka Mlisana 6, William [...]

Introduction: We sought to understand the Undetectable = Untransmittable (U = U) communication needs of persons living with HIV (PLHIV) and barriers to U = U communication among healthcare providers (HCPs) in South Africa. Methods: We conducted five focus group discussions (FGDs) with HCPs (N = 42) including nurses and counsellors from primary healthcare clinics (PHCs) in the Gauteng and Free State Provinces of South Africa, three FGDs (N = 27) with PLHIV recruited by snowball sampling from civil society organizations, and 27 in-depth interviews (IDIs) with recently diagnosed PLHIV in Johannesburg. IDIs and FGDs were audio recorded, transcribed, translated to English, and analysed thematically. Results: PLHIV were largely unaware and sceptical of U = U as the message appeared to contradict the mainstream HIV prevention clinical guidance. The low viral load (VL) knowledge further reduced confidence in U = U. PLHIV need support and guidance on the best approaches for sharing U = U information and disclosing their VL status to their partners, highlighting the central role of community understanding of U = U and VL to mediate the desired stigma reduction, social acceptance and emotional benefits of U = U for PLHIV. HCPs were uneasy about sharing U = U due to concerns about risk compensation and ART non-adherence and worried about enabling any ensuing HIV transmission. HCPs also need a simple, unambiguous, and consistent narrative for U = U, integrated with other HIV prevention messages. PLHIV and HCPs alike recommended a patient-centred approach to communicating U = U, focusing primarily on attaining viral suppression and emphasizing that condomless sex is only safe during periods of ART adherence. Conclusions: These data highlight the need for simple U = U communication support targeting both HCP and PLHIV. Culturally appropriate communication materials, with training and ongoing mentorship of the clinic staff, are essential to improve patient-centred U = U communication in clinics. [ABSTRACT FROM AUTHOR]