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INTRODUCTION: Rapid initiation of antiretroviral therapy (ART) in early HIV infection is important to limit seeding of the viral reservoir. A number of studies have shown that if ART is commenced prior to seroconversion, the seroconversion may, or may not, occur. We aimed to assess whether seroreversion or no seroconversion occurs using samples collected during an early treatment study in South Africa. METHODS: We tested 10 longitudinal samples collected over three years from 70 blood donors who initiated ART after detection of acute or early HIV infection during donation screening on fourth- and fifth-generation HIV antibody and RNA assays, and three point of care (POC) rapid tests. Donors were allocated to three treatment groups: (1) very early, (2) early, and (3) later. Longitudinal samples were grouped into time bins post-treatment initiation. RESULTS: On all three high-throughput HIV antibody assays, no clear pattern of declining signal intensity was observed over time after ART initiation in any of the treatment initiation groups and 100% detection was obtained. The Abbott Determine POC assay showed 100% detection at all time points with no seroreversion. However, the Abbott ABON HIV1 and OraSure OraQuick POC assays showed lower proportions of detection in all time bins in the very early treated group, ranging from 50.0% (95% CI: 26.8-73.2%) to 83.1% (95% CI: 64.2-93.0%), and moderate detection rates in the early and later-treated groups. CONCLUSION: While our findings are generally reassuring for HIV detection when high-throughput serological screening assays are used, POC assays may have lower sensitivity for detection of HIV infection after early treatment. Findings are relevant for blood safety and other settings where POC assays are used.

BackgroundTens of millions of children are exposed to Mycobacterium tuberculosis globally every year; however, there are no contemporary estimates of the risk of developing tuberculosis in exposed children. The effectiveness of contact investigations and preventive therapy remains poorly understood.MethodsIn this systematic review and meta-analysis, we investigated the development of tuberculosis in children closely exposed to a tuberculosis case and followed for incident disease. We restricted our search to cohort studies published between Jan 1, 1998, and April 6, 2018, in MEDLINE, Web of Science, BIOSIS, and Embase electronic databases. Individual-participant data and a pre-specified list of variables were requested from authors of all eligible studies. These included characteristics of the exposed child, the index case, and environmental characteristics. To be eligible for inclusion in the final analysis, a dataset needed to include: (1) individuals below 19 years of age; (2) follow-up for tuberculosis for a minimum of 6 months; (3) individuals with household or close exposure to an individual with tuberculosis; (4) information on the age and sex of the child; and (5) start and end follow-up dates. Studies assessing incident tuberculosis but without dates or time of follow-up were excluded. Our analysis had two primary aims: (1) estimating the risk of developing tuberculosis by time-period of follow-up, demographics (age, region), and clinical attributes (HIV, tuberculosis infection status, previous tuberculosis); and (2) estimating the effectiveness of preventive therapy and BCG vaccination on the risk of developing tuberculosis. We estimated the odds of prevalent tuberculosis with mixed-effects logistic models and estimated adjusted hazard ratios (HRs) for incident tuberculosis with mixed-effects Poisson regression models. The effectiveness of preventive therapy against incident tuberculosis was estimated through propensity score matching. The study protocol is registered with PROSPERO (CRD42018087022).FindingsIn total, study groups from 46 cohort studies in 34 countries-29 (63%) prospective studies and 17 (37%) retrospective-agreed to share their data and were included in the final analysis. 137 647 tuberculosis-exposed children were evaluated at baseline and 130 512 children were followed for 429 538 person-years, during which 1299 prevalent and 999 incident tuberculosis cases were diagnosed. Children not receiving preventive therapy with a positive result for tuberculosis infection had significantly higher 2-year cumulative tuberculosis incidence than children with a negative result for tuberculosis infection, and this incidence was greatest among children below 5 years of age (19·0% [95% CI 8·4-37·4]). The effectiveness of preventive therapy was 63% (adjusted HR 0·37 [95% CI 0·30-0·47]) among all exposed children, and 91% (adjusted HR 0·09 [0·05-0·15]) among those with a positive result for tuberculosis infection. Among all children

Given the high global seroprevalence of SARS-CoV-2, understanding the risk of reinfection has become increasingly important. Models developed to track trends in reinfection risk should be robust against possible biases arising from imperfect data observation processes. We performed simulation-based validation of an existing catalytic model designed to detect changes in the risk of reinfection by SARS-CoV-2. The catalytic model assumes the risk of reinfection is proportional to observed infections. Validation involved using simulated primary infections, consistent with the number of observed infections in South Africa. To assess the performance of the catalytic model, we simulated reinfection datasets that incorporated different processes that may bias inference, including imperfect observation and mortality. A Bayesian approach was used to fit the model to simulated data, assuming a negative binomial distribution around the expected number of reinfections, and model projections were compared to the simulated data using different magnitudes of change in reinfection risk. We assessed the model's ability to accurately detect changes in reinfection risk when included in the simulations, as well as the occurrence of false positives when reinfection risk remained constant. The model parameters converged in most scenarios leading to model outputs aligning with anticipated outcomes. The model successfully detected changes in the risk of reinfection when such a change was introduced to the data. Low observation probabilities (10%) of both primary- and reinfections resulted in low numbers of observed cases from the simulated data and poor convergence. The model's performance was assessed on simulated data representative of the South African SARS-CoV-2 epidemic, reflecting its timing of waves and outbreak magnitude. Model performance under similar scenarios may be different in settings with smaller epidemics (and therefore smaller numbers of reinfections). Ensuring model parameter convergence is essential to avoid false-positive detection of shifts in reinfection risk. While the model is robust in most scenarios of imperfect observation and mortality, further simulation-based validation for regions experiencing smaller outbreaks is recommended. Caution must be exercised in directly extrapolating results across different epidemiological contexts without additional validation efforts. Author summary: Most people have been infected with SARS-CoV-2, which increases interest in understanding the risk of reinfection. Our research focuses on the development of robust models that track reinfection trends, specifically emphasizing their resilience against biases from imperfect data observations. This study involves a simulation-based validation, which includes generating datasets under real-world scenarios of observation bias, to assess the reliability of an existing catalytic model designed to detect changes in the risk of SARS-CoV-2 reinfection in South Africa. In our investigations, we found that the model parameters converged in most scenarios, aligning the model outputs with anticipated outcomes. Notably, the model successfully identified changes in reinfection risk when introduced to the data. However, challenges arose in scenarios that led to low numbers of observed cases, leading to poor parameter convergence. This study underscores the significance of ensuring model parameter convergence to avoid false-positive detection of shifts in reinfection risk. While our model demonstrates robustness in scenarios of imperfect observation and mortality, additional simulation-based validation is recommended in regions with smaller outbreaks. [ABSTRACT FROM AUTHOR]

Background: Monitoring trends in multiple infections with SARS-CoV-2, following several pandemic waves, provides insight into the biological characteristics of new variants, but also necessitates methods to understand the risk of multiple reinfections. Objectives: We generalised a catalytic model designed to detect increases in the risk of SARS-CoV-2 reinfection, to assess the population-level risk of multiple reinfections. Methods: The catalytic model assumes the risk of reinfection is proportional to observed infections and uses a Bayesian approach to fit model parameters to the number of nth infections among individuals that occur at least 90 days after a previous infection. Using a posterior draw from the fitted model parameters, a 95% projection interval of daily nth infections is calculated under the assumption of a constant nth infection hazard coefficient. An additional model parameter was incorporated for the increased reinfection risk detected during the Omicron wave. The generalised model's performance was then assessed using simulation-based validation. Key findings: No additional increase in the risk of third infection was detected after the increase detected during the Omicron wave. Using simulation-based validation, we show that the model can successfully detect increases in the risk of third infections under different scenarios. Limitations: Even though the generalised model is intended to detect the risk of nth infections, it is validated specifically for third infections, with its applicability for four or more infections being unconfirmed. Furthermore, the method's sensitivity to low counts of nth infections, limits application in settings with small epidemics, limited testing coverage or early in an outbreak. Conclusions: The catalytic model was successfully adapted to detect increases in the risk of nth infections, enhancing our capacity to identify future changes in the risk of nth infections by SARS-CoV-2 or other similar pathogens. [ABSTRACT FROM AUTHOR]

Introduction: Identifying strategies to further reduce AIDS‐related mortality requires accurate estimates of the extent to which mortality among people living with HIV (PLHIV) is due to AIDS‐related or non‐AIDS‐related causes. Existing approaches to estimating AIDS‐related mortality have quantified AIDS‐related mortality as total mortality among PLHIV in excess of age‐ and sex‐matched mortality in populations without HIV. However, recent evidence suggests that, with high antiretroviral therapy (ART) coverage, a growing proportion of excess mortality among PLHIV is non‐AIDS‐related. Methods: We searched Embase on 22/09/2023 for English language studies that contained data on AIDS‐related mortality rates among adult PLHIV and age‐matched comparator all‐cause mortality rates among people without HIV. We extracted data on the number and rates of all‐cause and AIDS‐related deaths, demographics, ART use and AIDS‐related mortality definitions. We calculated the proportion of excess mortality among PLHIV that is AIDS‐related. The proportion of excess mortality due to AIDS was pooled using random‐effects meta‐analysis. Results: Of 4485 studies identified by the initial search, eight were eligible, all from high‐income settings: five from Europe, one from Canada, one from Japan and one from South Korea. No studies reported on mortality among only untreated PLHIV. One study included only PLHIV on ART. In all studies, most PLHIV were on ART by the end of follow‐up. Overall, 1,331,742 person‐years and 17,471 deaths were included from PLHIV, a mortality rate of 13.1 per 1000 person‐years. Of these deaths, 7721 (44%) were AIDS‐related, an overall AIDS‐related mortality rate of 5.8 per 1000 person‐years. The mean overall mortality rate among the general population was 2.8 (95% CI: 1.8–4.0) per 1000 person‐years. The meta‐analysed percentage of excess mortality that was AIDS‐related was 53% (95% CI: 45–61%); 52% (43–60%) in Western and Central Europe and North America, and 71% (69–74%) in the Asia‐Pacific region. Discussion: Although we searched all regions, we only found eligible studies from high‐income countries, mostly European, so, the generalizability of these results to other regions and epidemic settings is unknown. Conclusions: Around half of the excess mortality among PLHIV in high‐income regions was non‐AIDS‐related. An emphasis on preventing and treating comorbidities linked to non‐AIDS mortality among PLHIV is required. [ABSTRACT FROM AUTHOR]

The accuracy of the indirectly measured tuberculosis (TB) case detection rate is uncertain. A directly measurable indicator for TB case detection has been proposed (1) and subsequently used in analyses [...]

Objectives: Cohort studies have shown significant increased risk of HIV acquisition following human papillomavirus (HPV) detection and increased risk of new HPV detection in individuals with HIV infection, after adjusting for behavioural risk factors. This study uses an individual-based model to assess whether confounding sexual behaviour factors and network level effects can explain these associations between HIV and HPV infection status, without biological interactions.Methods: The model simulates infection with 13 oncogenic HPV types and HIV. It allows for different relationship types, with heterogeneity in probabilities of concurrency and rates of partner change. No effect of prevalent HPV infection on HIV acquisition is assumed and vice versa. The model is calibrated to South African HIV and type-specific HPV prevalence data using a Bayesian approach. The model is used to simulate cohorts with quarterly HIV and HPV testing from 2000 to 2002. These simulated data are analysed using proportional hazard models.Results: The mean of the unadjusted HRs of HIV acquisition following detection of an oncogenic HPV type calculated for each simulated cohort is 2.6 (95% CI 2.2 to 3.1). The mean of the unadjusted HRs for the effect of HIV on newly detected HPV is 2.5 (95% CI 2.2 to 2.8). Simulated associations between HIV and HPV infection status are similar to corresponding empirical estimates. In sensitivity analyses in which HIV and HPV were assumed to increase each other's transmission risk, simulated associations were stronger but not inconsistent with empirical estimates.Conclusions: Although we cannot rule out the possibility that associations between HIV and HPV transmission may be due in part to biological interactions, these results suggest that observed associations could be explained entirely by residual confounding by behavioural factors and network-level effects that observational studies cannot account for. [ABSTRACT FROM AUTHOR]

In the context of polio eradication efforts, accurate assessment of vaccination programme effectiveness is essential to public health planning and decision making. Such assessments are often based on zero-dose children, estimated using the number of children who did not receive the first dose of the Diphtheria-Tetanus-Pertussis containing vaccine as a proxy. Our study introduces a novel approach to directly estimate the number of children susceptible to poliovirus type 2 (PV2) and uses this approach to provide district-level estimates for South Africa of susceptible children born between 2017 and 2022. We used district-level data on annual doses of inactivated poliovirus vaccine (IPV) administered, live births, and population sizes, from 2017 through 2022. We imputed missing vaccination data, implemented flexible assumptions regarding dose distribution in the eligible population, and used estimated efficacy values for one, two, three, and four doses of IPV, to compute the number of susceptible and immune children by birth year. We validated our approach by comparing an intermediary output with zero-dose children (ZDC) estimated using data reported by WHO/UNICEF Estimates of National Immunization Coverage (WUENIC). Our results indicate high heterogeneity in susceptibility to PV2 across South Africa's 52 districts as of the end of 2022. In children under 5 years, PV2 susceptibility ranged from approximately 30 % in districts including Xhariep (31.9 %), Ekurhuleni (30.1 %), and Central Karoo (29.8 %), to less than 4 % in Sarah Baartman (1.9 %), Buffalo City (2.1 %), and eThekwini (3.2 %). Our susceptibility estimates were consistently higher than ZDC over the timeframe. We estimated that ZDC decreased nationally from 155,168 (152,737–158,523) in 2017 to 108,593 in 2021, and increased to 127,102 in 2022, a trend consistent with ZDC derived from data reported by WUENIC. While our approach provides a more comprehensive profile of PV2 susceptibility, our susceptibility and ZDC estimates generally agree in the ranking of districts according to risk. [ABSTRACT FROM AUTHOR]

Background: Of women with cervical cancer (CC) and HIV, 85% live in sub-Saharan Africa, where 21% of all CC cases are attributable to HIV infection. We aimed to generate internationally acceptable facility-based indicators to monitor and guide scale up of CC prevention and care services offered on-site or off-site by HIV clinics., Methods: We reviewed the literature and extracted relevant indicators, grouping them into domains along the CC control continuum. From February 2021 to March 2022, we conducted a three-round, online Delphi process to reach consensus on indicators. We invited 106 experts to participate. Through an anonymous, iterative process, participants adapted the indicators to their context (round 1), then rated them for 5 criteria on a 5-point Likert-type scale (rounds 2 and 3) and then ranked their importance (round 3)., Results: We reviewed 39 policies from 21 African countries and 7 from international organizations; 72 experts from 15 sub-Saharan Africa countries or international organizations participated in our Delphi process. Response rates were 34% in round 1, 40% in round 2, and 44% in round 3. Experts reached consensus for 17 indicators in the following domains: primary prevention (human papillomavirus prevention, n = 2), secondary prevention (screening, triage, treatment of precancerous lesions, n = 11), tertiary prevention (CC diagnosis and care, n = 2), and long-term impact of the program and linkage to HIV service (n = 2)., Conclusion: We recommend that HIV clinics that offer CC control services in sub-Saharan Africa implement the 17 indicators stepwise and adapt them to context to improve monitoring along the CC control cascade., Competing Interests: S.L.A. received the Swiss Government Excellence Scholarship, No 2019.0741. The remaining authors have no funding or conflicts of interest to disclose., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

Abstract: Each year, supported by the Joint United Nations Programme on HIV/AIDS (UNAIDS), country teams across the globe produce estimates that chart the state of their HIV epidemics. In 2023, HIV estimates were available for 174 countries, accounting for 99% of the global population, of which teams from 150 countries actively engaged in this process. The methods used to derive these estimates are developed under the guidance of the UNAIDS Reference Group on Estimates, Modeling, and Projections (www.epidem.org). Updates to these methods and epidemiological analyses that inform parameters and assumptions are documented in this supplement., Competing Interests: The authors have no funding or conflicts of interest to disclose., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

For 45 African countries/territories already reporting COVID-19 cases before 23 March 2020, we estimate the dates of reporting 1,000 and 10,000 cases. Assuming early epidemic trends without interventions, all 45 were likely to exceed 1,000 confirmed cases by the end of April 2020, with most exceeding 10,000 a few weeks later.