Estimating and projecting the number of new HIV diagnoses and incidence in Spectrum's case surveillance and vital registration tool.

OBJECTIVE: The United Nations Program on HIV/AIDS-supported Spectrum software package is used by most countries worldwide to monitor the HIV epidemic. In Spectrum, HIV incidence trends among adults (aged 15-49 years) are derived by either fitting to seroprevalence surveillance and survey data or generating curves consistent with case surveillance and vital registration data, such as historical trends in the number of newly diagnosed infections or AIDS-related deaths. This article describes development and application of the case surveillance and vital registration (CSAVR) tool for United Nations Program on HIV/AIDS' 2019 estimate round. METHODS: Incidence in CSAVR is either estimated directly using single logistic, double logistic, or spline functions, or indirectly via the 'r-logistic' model, which represents the (log-transformed) per-capita transmission rate using a logistic function. The propensity to get diagnosed is assumed to be monotonic, following a Gamma cumulative distribution function and proportional to mortality as a function of time since infection. Model parameters are estimated from a combination of historical surveillance data on newly reported HIV cases, mean CD4 at HIV diagnosis and estimates of AIDS-related deaths from vital registration systems. Bayesian calibration is used to identify the best fitting incidence trend and uncertainty bounds. RESULTS: We used CSAVR to estimate HIV incidence, number of new diagnoses, mean CD4 at diagnosis and the proportion undiagnosed in 31 European, Latin American, Middle Eastern, and Asian-Pacific countries. The spline model appeared to provide the best fit in most countries (45%), followed by the r-logistic (25%), double logistic (25%), and single logistic models. The proportion of HIV-positive people who knew their status increased from about 0.31 [interquartile range (IQR): 0.10-0.45] in 1990 to about 0.77 (IQR: 0.50-0.89) in 2017. The mean CD4 at diagnosis appeared to be stable, decreasing from 410 cells/μl (IQR: 224-567) in 1990 to 373 cells/μl (IQR: 174-475) by 2017. CONCLUSION: Robust case surveillance and vital registration data are routinely available in many middle-income and high-income countries while HIV seroprevalence surveillance and survey data may be scarce. In these countries, the CSAVR offers a simpler, improved approach to estimating and projecting trends in both HIV incidence and knowledge of HIV status

Updates to Spectrum’s Case Surveillance and Vital Registration tool for HIV estimates and projections

Introduction: The Case Surveillance and Vital Registration (CSAVR) model within Spectrum estimates HIV incidence trends from surveillance data on numbers of new HIV diagnoses and HIV-related deaths. This article describes developments of the CSAVR tool to more flexibly model diagnosis rates over time, estimate incidence patterns by sex and age group, and by key population group. Methods: We modelled HIV diagnosis rate trends as a mixture of three factors, including temporal and opportunistic infection components. The tool was expanded to estimate incidence rate ratios by sex and age for countries with disaggregated reporting of new HIV diagnoses and AIDS deaths, and to account for information on key populations such as men who have sex with men (MSM), males who inject drugs (MWID), female sex workers (FSW) and females who inject drugs (FWID). We used a Bayesian framework to calibrate the tool in 71 high-income or low HIV burden countries. Results: Across countries, an estimated median 89% (interquartile range [IQR] 78%-96%) of HIV-positive adults knew their status in 2019. Mean CD4 counts at diagnosis were stable over time, with a median of 456 cells/μl (IQR: 391-508) across countries in 2019. In European countries reporting new HIV diagnoses among key populations median estimated proportions of males that are MSM and MWID was 1.3% (IQR: 0.9%- 2.0%) and 0.56% (IQR: 0.51%- 0.64%), respectively. The median estimated proportions of females that are FSW and FWID were 0.36% (IQR: 0.27%-0.45%) and 0.14 (IQR: 0.13%- 0.15%), respectively. HIV incidence per 100 person-year increased among MSM with median estimates reaching 0.43 (IQR: 0.29-1.73) in 2019, but remained stable in MWID, FSW and FWID, at around 0.12 (IQR: 0.04-1.9), 0.09 (IQR: 0.06-0.69) and 0.13% (IQR: 0.08%-0.91%) in 2019, respectively. Knowledge of HIV status among HIV-positive adults gradually increased since the early 1990s to exceed 75% in more than 75% of countries in 2019 among each key population. Conclusions: CSAVR offers an approach to using routine surveillance and vital registration data to estimate and project trends in both HIV incidence and knowledge of HIV status

Disease progression and mortality with untreated HIV infection: evidence synthesis of HIV seroconverter cohorts, antiretroviral treatment clinical cohorts, and population-based survey data

Background: Model-based estimates of key HIV indicators depend on past epidemic trends that are derived based on assumptions about HIV disease progression and mortality in the absence of antiretroviral treatment (ART). Population-based HIV Impact Assessment (PHIA) household surveys conducted between 2015 and 2018 found substantial numbers of respondents living with untreated HIV infection. CD4 cell counts measured in these individuals provide novel information to estimate HIV disease progression and mortality rates off ART. Methods: We used Bayesian multi-parameter evidence synthesis to combine data on i) cross-sectional CD4 cell counts among untreated adults living with HIV from ten PHIA surveys, ii) survival after HIV seroconversion in East African seroconverter cohorts, and iii) post-seroconversion CD4 counts and iv) mortality rates by CD4 count predominantly from European, North American, and Australian seroconverter cohorts. We used Incremental Mixture Importance Sampling to estimate HIV natural history and ART uptake parameters used in the Spectrum software. We validated modeled trends in CD4 count at ART initiation against ART initiator cohorts in sub-Saharan Africa. Results: Median untreated HIV survival decreased with increasing age at seroconversion, from 12.5 years (95% credible interval [CrI]: 12.1-12.7) at ages 15-24 to 7.2 years (95% CrI: 7.1-7.7) at ages 45-54. Older age was associated with lower initial CD4 counts, faster CD4 count decline and higher HIV-related mortality rates. Our estimates suggested a weaker association between ART uptake and HIV-related mortality rates than previously assumed in Spectrum. Modeled CD4 counts in untreated people living with HIV matched recent household survey data well, though some intercountry variation in frequencies of CD4 counts above 500 cells/mm3 was not explained. Trends in CD4 counts at ART initiation were comparable to data from ART initiator cohorts. An alternate model that stratified progression and mortality rates by sex did not improve model fit appreciably. Conclusions: Synthesis of multiple data sources results in similar overall survival as previous Spectrum parameter assumptions but implies more rapid progression and longer survival in lower CD4 categories. New natural history parameter values improve consistency of model estimates with recent cross-sectional CD4 data and trends in CD4 counts at ART initiation

Potential effects of disruption to HIV programmes in sub-Saharan Africa caused by COVID-19: results from multiple mathematical models

Background: The COVID-19 epidemic could lead to the disruptions to provision of HIV services for people living with HIV and those at risk of acquiring HIV in sub-Saharan Africa, where UNAIDS estimates that more than two thirds of the 37.9 million (32.7-44.0 million) people living with HIV reside in 2018. We set out to predict the potential effects of such disruptions on HIV-related deaths and new infections. Methods: Five well-described models of HIV epidemics (Goals, Optima HIV, HIV Synthesis, Imperial College model, EMOD) were each used to estimate the effect of various potential disruptions to HIV prevention, testing and treatment services on HIV-related deaths and new infections in sub-Saharan Africa lasting 6 months from 1 April 2020. Disruptions affecting 20%, 50% and 100% of the population were considered. In further analyses shorter term disruptions and the possibility of reductions in sexual activity during disruptions were considered. Findings: A six-month interruption of supply of antiretroviral (ARV) drugs across 50% of the population of people living with HIV on treatment would be expected to lead to a 1.63-fold (median across models; range 1.39 to 1.87) increase in HIV-related deaths over a one year period compared to with no disruption. In sub-Saharan Africa this amounts to an excess of 296,000 (median over model estimates, range 229,000 – 420,000) HIV deaths should such a high level of disruption occur. There would also be an approximately 1.6-fold increase in mother to child transmission of HIV. While an interruption of supply of ARV drug would have by far the largest impact of any potential disruptions, effects of poorer clinical care due to over-stretched health facilities, interruptions of supply of other drugs such as cotrimoxazole and suspension of HIV testing would all have significant population-level impact on mortality. Interruption to condom supplies and peer education would make populations more vulnerable to increases in HIV incidence, although physical distancing measures could lead to reductions in risky sex. Interpretation: During the COVID-19 pandemic the primary priority for governments, donors, suppliers and communities should focus on maintaining uninterrupted supply of ARV drugs for people with HIV to avoid additional HIV-related deaths. The provision of other HIV prevention measures is also important to prevent any increase in HIV incidence