The risks and benefits of providing HIV services during the COVID-19 pandemic

INTRODUCTION: The COVID-19 pandemic has caused widespread disruptions including to health services. In the early response to the pandemic many countries restricted population movements and some health services were suspended or limited. In late 2020 and early 2021 some countries re-imposed restrictions. Health authorities need to balance the potential harms of additional SARS-CoV-2 transmission due to contacts associated with health services against the benefits of those services, including fewer new HIV infections and deaths. This paper examines these trade-offs for select HIV services. METHODS: We used four HIV simulation models (Goals, HIV Synthesis, Optima HIV and EMOD) to estimate the benefits of continuing HIV services in terms of fewer new HIV infections and deaths. We used three COVID-19 transmission models (Covasim, Cooper/Smith and a simple contact model) to estimate the additional deaths due to SARS-CoV-2 transmission among health workers and clients. We examined four HIV services: voluntary medical male circumcision, HIV diagnostic testing, viral load testing and programs to prevent mother-to-child transmission. We compared COVID-19 deaths in 2020 and 2021 with HIV deaths occurring now and over the next 50 years discounted to present value. The models were applied to countries with a range of HIV and COVID-19 epidemics. RESULTS: Maintaining these HIV services could lead to additional COVID-19 deaths of 0.002 to 0.15 per 10,000 clients. HIV-related deaths averted are estimated to be much larger, 19-146 discounted deaths per 10,000 clients. DISCUSSION: While there is some additional short-term risk of SARS-CoV-2 transmission associated with providing HIV services, the risk of additional COVID-19 deaths is at least 100 times less than the HIV deaths averted by those services. Ministries of Health need to take into account many factors in deciding when and how to offer essential health services during the COVID-19 pandemic. This work shows that the benefits of continuing key HIV services are far larger than the risks of additional SARS-CoV-2 transmission

Sociodemographic differences in symptom severity and duration among women referred to secondary care for menorrhagia in England and Wales: a cohort study from the National Heavy Menstrual Bleeding Audit

Objective: To examine symptom severity and duration at time of referral to secondary care for heavy menstrual bleeding (HMB) by socioeconomic deprivation, age and ethnicity. / Design: Cohort analysis of data from the National HMB Audit linked to Hospital Episode Statistics data. / Setting: English and Welsh National Health Services (secondary care): February 2011 to January 2012. / Participants: 15 325 women aged 18–60 years in England and Wales who had a new referral for HMB to a gynaecology outpatient department. / Methods: Multivariable linear regression to calculate adjusted differences in mean symptom severity and quality of life scores at first outpatient visit. Multivariable logistic regression to calculate adjusted ORs. Adjustment for body mass index, parity and comorbidities. / Primary outcome measures: Mean symptom severity score (0=best, 100=worst), mean condition-specific quality of life score (0=worst, 100=best) and symptom duration (≥1 year). / Results: Women were on average 42 years old and 12% reported minority ethnic backgrounds. Mean symptom severity and condition-specific quality of life scores were 61.8 and 34.7. Almost three-quarters of women (74%) reported having had symptoms for ≥1 year. Women from more deprived areas had more severe symptoms at their first outpatient visit (difference −6.1; 95% CI−7.2 to −4.9, between least and most deprived quintiles) and worse condition-specific quality of life (difference 6.3; 95% CI 5.1 to 7.5). Symptom severity declined with age while quality of life improved. / Conclusions: Women living in more deprived areas reported more severe HMB symptoms and poorer quality of life at the start of treatment in secondary care. Providers should examine referral practices to explore if these differences reflect women’s health-seeking behaviour or how providers decide whether or not to refer

Transmission reduction, health benefits, and upper-bound costs of interventions to improve retention on antiretroviral therapy: a combined analysis of three mathematical models

BACKGROUND: In this so-called treat-all era, antiretroviral therapy (ART) interruptions contribute to an increasing proportion of HIV infections and deaths. Many strategies to improve retention on ART cost more than standard of care. In this study, we aimed to estimate the upper-bound costs at which such interventions should be adopted. METHODS: In this combined analysis, we compared the infections averted, disability-adjusted life-years (DALYs) averted, and upper-bound costs of interventions that improve ART retention in three HIV models with diverse structures, assumptions, and baseline settings: EMOD in South Africa, Optima in Malawi, and Synthesis in sub-Saharan African low-income and middle-income countries (LMICs). We modelled estimates over a 40-year time horizon, from a baseline of Jan 1, 2022, when interventions would be implemented, to Jan 1, 2062. We varied increment of ART retention (25%, 50%, 75%, and 100% retention), the extent to which interventions could be targeted towards individuals at risk of interrupting ART, and cost-effectiveness thresholds in each setting. FINDINGS: Despite simulating different settings and epidemic trends, all three models produced consistent estimates of health benefit (ie, DALYs averted) and transmission reduction per increment in retention. The range of estimates was 1·35-3·55 DALYs and 0·12-0·20 infections averted over the 40-year time horizon per additional person-year retained on ART. Upper-bound costs varied by setting and intervention effectiveness. Improving retention by 25% among all people receiving ART, regardless of risk of ART interruption, gave an upper-bound cost per person-year of US$2-6 in Optima (Malawi),$43-68 in Synthesis (LMICs in sub-Saharan Africa), and $28-180 in EMOD (South Africa). A maximally targeted and effective retention intervention had an upper-bound cost per person-year of US$93-223 in Optima (Malawi), $871-1389 in Synthesis (LMICs in sub-Saharan Africa), and$1013-6518 in EMOD (South Africa). INTERPRETATION: Upper-bound costs that could improve ART retention vary across sub-Saharan African settings and are likely to be similar to or higher than was estimated before the start of the treat-all era. Upper-bound costs could be increased by targeting interventions to those most at risk of interrupting ART. FUNDING: Bill & Melinda Gates Foundation

90‐90‐90 by 2020? Estimation and projection of the adult HIV epidemic and ART programme in Zimbabwe – 2017 to 2020

INTRODUCTION: The 90-90-90 targets set by the United Nations aspire to 73% of people living with HIV (PLHIV) being virally suppressed by 2020. Using the HIV Synthesis Model, we aim to mimic the epidemic in Zimbabwe and make projections to assess whether Zimbabwe is on track to meet the 90-90-90 targets and assess whether recently proposed UNAIDS HIV transition metrics are likely to be met. METHODS: We used an approximate Bayesian computation approach to identify model parameter values which result in model outputs consistent with observed data, evaluated using a calibration score. These parameter values were then used to make projections to 2020 to compare with the 90-90-90 targets and other key indicators. We also calculated HIV transition metrics proposed by UNAIDS (percentage reduction in new HIV infections and AIDS-related mortality from 2010 to 2020, absolute rate of new infections and AIDS-related mortality, incidence-mortality ratio and incidence-prevalence ratios). RESULTS: After calibration, there was general agreement between modelled and observed data. The median predicted outcomes in 2020 were: proportion of PLHIV (aged 15 to 65) diagnosed 0.91 (90% uncertainty range 0.87, 0.94) (0.84 men, 0.95 women); of those diagnosed, proportion on treatment 0.92 (0.90, 0.93); of those receiving treatment, proportion with viral suppression 0.86 (0.81, 0.91). This results in 72% of PLHIV having viral suppression in 2020. We estimated a percentage reduction of 36.5% (13.7% increase to 67.4% reduction) in new infections from 2010 to 2020, and of 30.4% (9.7% increase to 56.6% reduction) in AIDS-related mortality (UNAIDS target 75%). The modelled absolute rates of HIV incidence and AIDS-related mortality in 2020 were 5.48 (2.26, 9.24) and 1.93 (1.31, 2.71) per 1000 person-years respectively. The modelled incidence-mortality ratio and incidence-prevalence ratios in 2020 were 1.05 (0.46, 1.66) and 0.009 (0.004, 0.013) respectively. CONCLUSIONS: Our model was able to produce outputs that are simultaneously consistent with an array of observed data and predicted that while the 90-90-90 targets are within reach in Zimbabwe, increased efforts are required in diagnosing men in particular. Calculation of the HIV transition metrics suggest increased efforts are needed to bring the HIV epidemic under control

Cost-per-diagnosis as a metric for monitoring cost effectiveness of HIV testing programmes in low income settings in southern Africa : health economic and modelling analysis

Introduction: As prevalence of undiagnosed HIV declines, it is unclear whether testing programmes will be cost effective. To guide their HIV testing programmes,countries require appropriatemetrics that can be measured. The cost-per-diagnosisis potentially a useful metric. Methods:We simulated a series of setting-scenarios for adult HIV epidemics and ART programmes typical of settings in southern Africa using an individual-based model and projected forward from 2018 under two policies: (i) a minimum package of “core” testing (i.e. testing in pregnant women, for diagnosis of symptoms, in sex workers, and in men coming forward for circumcision) is conducted, and (ii) “core” testing as above plus “additional-testing”, for which we specify different rates of testing and various degrees to which those with HIV are more likely to test than thosewithout HIV. We also considered a plausible range of unit test costs. The aim was to assess the relationship between cost-per-diagnosisand the incremental cost-effectiveness ratio(ICER) of the additional-testingpolicy. Discount rate 3%; costs in 2018 $US. Results:There was a strong graded relationship between the cost-per-diagnosisand the ICER. Overall, the ICERwas below$500 per-DALY-averted (the cost effectiveness threshold used in primary analysis) so long as thecost-per-diagnosiswas below $315. This thresholdcost-per-diagnosiswas similar according to epidemic and programmatic features including the prevalence of undiagnosed HIV, the HIV incidence and a measure of HIV programme quality (the proportion of HIV diagnosed people having a viral load <1000 copies/mL). However, restrictingto women, additional-testingdid not appear cost-effective even at acost-per-diagnosisof below$50, while restrictingto men additional-testingwas cost effective up to a cost-per-diagnosisof $585. Thethreshold cost for testing in men fell to$256 when the cost effectiveness threshold was $300instead of$500, and to $81 when considering a discount rate of 10% perannum.Conclusions:For testing programmesin low income settings in southern African there is an extremely strong relationship between the cost-per-diagnosisand the cost per DALY averted, indicating that the cost-per-diagnosiscan be used to monitor the cost effectiveness of testing programmes

Integrase Strand Transfer Inhibitor Use and Cancer Incidence in a Large Cohort Setting

Background: Limited data exist examining the association between incident cancer and cumulative integrase inhibitor (INSTI) exposure. Methods: Participants were followed from baseline (latest of local cohort enrollment or January 1, 2012) until the earliest of first cancer, final follow-up, or December 31, 2019. Negative binomial regression was used to assess associations between cancer incidence and time-updated cumulative INSTI exposure, lagged by 6 months. Results: Of 29 340 individuals, 74% were male, 24% were antiretroviral treatment (ART)-naive, and median baseline age was 44 years (interquartile range [IQR], 36-51). Overall, 13 950 (48%) individuals started an INSTI during follow-up. During 160 657 person-years of follow-up ([PYFU] median 6.2; IQR, 3.9-7.5), there were 1078 cancers (incidence rate [IR] 6.7/1000 PYFU; 95% confidence interval [CI], 6.3-7.1). The commonest cancers were non-Hodgkin lymphoma (n=113), lung cancer (112), Kaposi's sarcoma (106), and anal cancer (103). After adjusting for potential confounders, there was no association between cancer risk and INSTI exposure (≤6 months vs no exposure IR ratio: 1.15 [95% CI, 0.89-1.49], &gt;6-12 months; 0.97 [95% CI, 0.71-1.32], &gt;12-24 months; 0.84 [95% CI, 0.64-1.11], &gt;24-36 months; 1.10 [95% CI, 0.82-1.47], &gt;36 months; 0.90 [95% CI, 0.65-1.26] [P=.60]). In ART-naive participants, cancer incidence decreased with increasing INSTI exposure, mainly driven by a decreasing incidence of acquired immune deficiency syndrome cancers; however, there was no association between INSTI exposure and cancer for those ART-experienced (interaction P&lt;.0001). Conclusions: Cancer incidence in each INSTI exposure group was similar, despite relatively wide CIs, providing reassuring early findings that increasing INSTI exposure is unlikely to be associated with an increased cancer risk, although longer follow-up is needed to confirm this finding

Contemporary antiretrovirals and body-mass index: a prospective study of the RESPOND cohort consortium

BACKGROUND: Weight gain effects of individual antiretroviral drugs are not fully understood. We investigated associations between a prespecified clinically significant increase (>7%) in body-mass index (BMI) and contemporary antiretroviral use. METHODS: The International Cohort Consortium of Infectious Diseases (RESPOND) is a prospective, multicohort collaboration, including data from 17 well established cohorts and over 29 000 people living with HIV. People with HIV under prospective follow-up from Jan 1, 2012, and older than 18 years were eligible for inclusion. Each cohort contributed a predefined minimum number of participants related to the size of the specific cohort (with a minimum of 1000 participants). Participants were required to have CD4 cell counts and HIV viral load measurement in the 12 months before or within 3 months after baseline. For all antiretroviral drugs received at or after RESPOND entry, changes from pre-antiretroviral BMI levels (baseline) were considered at each BMI measurement during antiretroviral treatment. We used logistic regression to identify individual antiretrovirals that were associated with first occurrence of a more than 7% increase in BMI from pre-antiretroviral BMI. We adjusted analyses for time on antiretrovirals, pre-antiretroviral BMI, demographics, geographical region, CD4 cell count, viral load, smoking status, and AIDS at baseline. RESULTS: 14 703 people were included in this study, of whom 7863 (53·5%) had a more than 7% increase in BMI. Compared with lamivudine, use of dolutegravir (odds ratio [OR] 1·27, 95% CI 1·17-1·38), raltegravir (1·37, 1·20-1·56), and tenofovir alafenamide (1·38, 1·22-1·35) was significantly associated with a more than 7% BMI increase, as was low pre-antiretroviral BMI (2·10, 1·91-2·31 for underweight vs healthy weight) and Black ethnicity (1·61, 1·47-1·76 vs White ethnicity). Higher CD4 count was associated with a reduced risk of BMI increase (0·97, 0·96-0·98 per 100 cells per μL increase). Relative to lamivudine, dolutegravir without tenofovir alafenamide (OR 1·21, 95% CI 1·19-1·32) and tenofovir alafenamide without dolutegravir (1·33, 1·15-1·53) remained independently associated with a more than 7% increase in BMI; the associations were higher when dolutegravir and tenofovir alafenamide were used concomitantly (1·79, 1·52-2·11, and 1·70, 1·44-2·01, respectively). INTERPRETATION: Clinicians and people with HIV should be aware of associations between weight gain and use of dolutegravir, tenofovir alafenamide, and raltegravir, particularly given the potential consequences of weight gain, such as insulin resistance, dyslipidaemia, and hypertension. FUNDING: The CHU St Pierre Brussels HIV Cohort, The Austrian HIV Cohort Study, The Australian HIV Observational Database, The AIDS Therapy Evaluation in the Netherlands national observational HIV cohort, The EuroSIDA cohort, The Frankfurt HIV Cohort Study, The Georgian National AIDS Health Information System, The Nice HIV Cohort, The ICONA Foundation, The Modena HIV Cohort, The PISCIS Cohort Study, The Swiss HIV Cohort Study, The Swedish InfCare HIV Cohort, The Royal Free HIV Cohort Study, The San Raffaele Scientific Institute, The University Hospital Bonn HIV Cohort and The University of Cologne HIV Cohorts, ViiV Healthcare, and Gilead Sciences