Sexual behaviour change in countries with generalised HIV epidemics? Evidence from population-based cohort studies in sub-Saharan Africa

International audienceEditorial for sexual behaviour supplement

Non-disclosure of HIV testing history in population-based surveys: implications for estimating a UNAIDS 90-90-90 target

Background: HIV/AIDS programmes and organisations around the world use routinely updated estimates of the UNAIDS 90-90-90 targets to track progress and prioritise further programme implementation. Any bias in these estimates has the potential to mislead organisations on where gaps exist in HIV testing and treatment programmes. Objective: To measure the extent of undisclosed HIV testing history and its impact on estimating the proportion of people living with HIV (PLHIV) who know their HIV status (the ‘first 90’ of the UNAIDS 90-90-90 targets). Methods: We conducted a retrospective cohort study using population-based HIV serological surveillance conducted between 2010 and 2016 and linked, directly observed HIV testing records in Kisesa, Tanzania. Generalised estimating equations logistic regression models were used to detect associations with non-disclosure of HIV testing history adjusting for demographic, behavioural, and clinical characteristics. We compared estimates of the ‘first 90’ using self-reported survey data only and augmented estimates using information from linked records to quantify the absolute and relative impact of undisclosed HIV testing history. Results: Numbers of participants in each of the survey rounds ranged from 7171 to 7981 with an average HIV prevalence of 6.9%. Up to 33% of those who tested HIV-positive and 34% of those who tested HIV-negative did not disclose their HIV testing history. The proportion of PLHIV who reported knowing their status increased from 34% in 2010 to 65% in 2016. Augmented estimates including information from directly observed testing history resulted in an absolute impact of 6.7 percentage points and relative impact of 12.4%. Conclusions: In this population, self-reported testing history in population-based HIV serological surveys under-estimated the percentage of HIV positives that are diagnosed by a relative factor of 12%. Research should be employed in other surveillance systems that benefit from linked data to investigate how bias may vary across settings

Should data from demographic surveillance systems be made more widely available to researchers?

BACKGROUND TO THE DEBATE: Demographic surveillance--the process of monitoring births, deaths, causes of deaths, and migration in a population over time--is one of the cornerstones of public health research, particularly in investigating and tackling health disparities. An international network of demographic surveillance systems (DSS) now operates, mostly in sub-Saharan Africa and Asia. Thirty-eight DSS sites are coordinated by the International Network for the Continuous Demographic Evaluation of Populations and Their Health (INDEPTH). In this debate, Daniel Chandramohan and colleagues argue that DSS data in the INDEPTH database should be made available to all researchers worldwide, not just to those within the INDEPTH Network. Basia Zaba and colleagues argue that the major obstacles to DSS sites sharing data are technical, managerial, and financial rather than proprietorial concerns about analysis and publication. This debate is further discussed in this month's Editorial

Estimating the need for antiretroviral treatment and an assessment of a simplified HIV/AIDS case definition in rural Malawi.

BACKGROUND: Surveillance in the era of antiretroviral therapy (ART) requires estimates of HIV prevalence as well as the proportion eligible for ART. We estimated HIV prevalence and assessed field staging of individuals to estimate the burden of HIV disease needing treatment in rural Malawi. METHODS: Adults aged 18-59 years in a demographic surveillance system were interviewed, examined, and HIV counselled and tested. Staging that used a simplified version of the WHO criteria ('field checklist') was compared with staging by a medical assistant using a 'clinic checklist' and to CD4 cell results. RESULTS: A total of 2129 of 2303 eligible adults (92.4%) were traced, and 2047 (96.1%) participated. Of the 1443 participants (70.5%) tested, 11.6% were HIV positive. ART eligibility classification by the field and clinic checklists were concordant in 122 of 133 HIV-positive individuals. Compared with the clinic checklist, the field checklist had a sensitivity of 50% and a specificity of 96%. Including those already known to be on ART, staging by the field and clinic checklists estimated ART eligibility at 16.3 and 17.7% of HIV-positive individuals, respectively. Using CD4 cell count under 250 cells/mul or WHO stage III/IV, the Malawi national programme criteria, 38% of HIV-positive individuals were eligible for ART, compared with 31% based on the 2006 WHO criteria of CD4 cell count under 200 cells/mul or WHO stage IV or CD4 cell count of 200-350 cells/mul and WHO stage III. CONCLUSION: The field checklist was not a suitable tool for individual staging. Criteria for ART eligibility based on clinical staging alone missed two-thirds of those eligible by clinical staging and CD4 cell count

Age-specific mortality patterns in HIV-infected individuals: a comparative analysis of African community study data

Objectives: Describe age-specific mortality patterns of HIV-infected adults in African communities before introduction of HAART. Methods: Mortality data (deaths and person-years observed) for HIV-positive subjects aged 15–65 from six African community studies in five different countries were pooled, combining information from 1793 seroconverters and 8534 HIV positive when first tested. Age-specific mortality hazards were modelled using parametric regression based on the Weibull distribution, to investigate effects of sex, and site-specific measures of mean age at incidence, crude mortality rate of uninfected, and measures of epidemic maturity. Results: The combined studies yielded a total of 31 777 person-years of observation for HIV-positive subjects, during which time 2602 deaths were recorded. Mortality rates rose almost linearly with age, from below 50/1000 at ages < 20 years, up to 150/1000 at 50 years +. There was no significant difference between men and women in level or age pattern of mortality. Weibull regression analysis suggested that intersite variation could be explained by HIV prevalence trend, and by the ratio of HIV proportional mortality to current HIV prevalence. A model representation was constructed with a common age pattern of mortality, but allowing the level to be adjusted by specifying HIV prevalence indicators. Conclusion: The linear age trend of mortality in HIV-infected populations was satisfactorily represented by a Weibull function providing a parametric model adaptable for representing different levels of HIV-related mortality. This model might be simpler to use in demographic projections of HIV-affected populations than models based on survival post-infection

Estimating 'net' HIV-related mortality and the importance of background mortality rates.

OBJECTIVES: To estimate mortality directly attributable to HIV in HIV-infected adults in low and middle income countries and discuss appropriate methodology. DESIGN: : Illustrative analysis of pooled data from six studies across sub-Saharan Africa and Thailand with data on individuals with known dates of seroconversion to HIV. METHODS: Five of the studies also had data from HIV-negative subjects and one had verbal autopsies. Data for HIV-negative cohorts were weighted by the initial age and sex distribution of the seroconverters. Using the survival of the HIV-negative group to represent the background mortality, net survival from HIV was calculated for the seroconverters using competing risk methods. Mortality from all causes and 'net' mortality were modelled using piecewise exponential regression. Alternative approaches are explored in the dataset without information on mortality of uninfected individuals. RESULTS: The overall effect of the net mortality adjustment was to increase survivorship proportionately by 2 to 5% at 6 years post-infection. The increase ranged from 2% at ages 15-24 to 22% in those 55 and over. Mortality rate ratios between sites were similar to corresponding ratios for all-cause mortality. CONCLUSION: Differences between HIV mortality in different populations and age groups are not explained by differences in background mortality, although this does appear to contribute to the excess at older ages. In the absence of data from uninfected individuals in the same population, model life tables can be used to calculate background rates

Time from HIV seroconversion to death: a collaborative analysis of eight studies in six low and middle-income countries before highly active antiretroviral therapy.

OBJECTIVES: To estimate survival patterns after HIV infection in adults in low and middle-income countries. DESIGN: An analysis of pooled data from eight different studies in six countries. METHODS: HIV seroconverters were included from eight studies (three population-based, two occupational, and three clinic cohorts) if they were at least 15 years of age, and had no more than 4 years between the last HIV-negative and subsequent HIV-positive test. Four strata were defined: East African cohorts; South African miners cohort; Thai cohorts; Haitian clinic cohort. Kaplan-Meier functions were used to estimate survival patterns, and Weibull distributions were used to model and extend survival estimates. Analyses examined the effect of site, age, and sex on survival. RESULTS: From 3823 eligible seroconverters, 1079 deaths were observed in 19 671 person-years of follow-up. Survival times varied by age and by study site. Adjusting to age 25-29 years at seroconversion, the median survival was longer in South African miners: 11.6 years [95% confidence interval (CI) 9.8-13.7] and East African cohorts: 11.1 years (95% CI 8.7-14.2) than in Haiti: 8.3 years (95% CI 3.2-21.4) and Thailand: 7.5 years (95% CI 5.4-10.4). Survival was similar for men and women, after adjustment for age at seroconversion and site. CONCLUSION: Without antiretroviral therapy, overall survival after HIV infection in African cohorts was similar to survival in high-income countries, with a similar pattern of faster progression at older ages at seroconversion. Survival appears to be significantly worse in Thailand where other, unmeasured factors may affect progression