Improving analysis of the size and dynamics of AIDS epidemics

HIV estimates through 2018: data for decision-making

BACKGROUND

Global targets call for a 75% reduction in new HIV infections and AIDS deaths between 2010 and 2020. UNAIDS supports countries to measure progress towards these targets. In 2019, this effort resulted in revised national, regional and global estimates reflecting the best available data.

METHODS

Spectrum software was used to develop estimates for 170 countries. Country teams from 151 countries developed HIV estimates directly and estimates for an additional 19 country were developed by UNAIDS based on available evidence. 107 countries employed models using HIV prevalence data from sentinel surveillance, routinely collected HIV testing and household surveys while the remaining 63 countries applied models using HIV case surveillance and/or reported AIDS deaths. Model parameters were informed by the UNAIDS Reference Group on Estimates, Modeling and Projections.

RESULTS

HIV estimates were available for 170 countries representing 99% of the global population. An estimated 37.9 million (uncertainty bounds 32.7-44.0 million) people were living with HIV in 2018. There were 1.7 million (1.4-2.3 million) new infections and 770 000 (570 000-1.1 million) AIDS-related deaths. New HIV infections declined in five of eight regions and AIDS deaths were declining in six of eight regions between 2010 and 2018.

CONCLUSION

The estimates demonstrate progress towards ending the AIDS epidemic by 2030, however, through 2018 declines in new HIV infections and AIDS-related deaths were not sufficient to meet global interim targets. The UNAIDS estimates have made important contributions to guide decisions about the HIV response at global, regional and country level.

Producing HIV estimates: from global advocacy to country planning and impact measurement

BACKGROUND

The development of global HIV estimates has been critical for understanding, advocating for and funding the HIV response. The process of generating HIV estimates has been cited as the gold standard for public health estimates.

OBJECTIVE

This paper provides important lessons from an international scientific collaboration and provides a useful model for those producing public health estimates in other fields.

DESIGN

Through the compilation and review of published journal articles, United Nations reports, other documents and personal experience we compiled historical information about the estimates and identified potential lessons for other public health estimation efforts.

RESULTS

Through the development of core partnerships with country teams, implementers, demographers, mathematicians, epidemiologists and international organizations, UNAIDS has led a process to develop the capacity of country teams to produce internationally comparable HIV estimates. The guidance provided by these experts has led to refinements in the estimated numbers of people living with HIV, new HIV infections and AIDS-related deaths over the past 20 years. A number of important updates to the methods since 1997 resulted in fluctuations in the estimated levels, trends and impact of HIV. The largest correction occurred between the 2005 and 2007 rounds with the additions of household survey data into the models. In 2001 the UNAIDS models at that time estimated there were 40 million people living with HIV. In 2016, improved models estimate there were 30 million (27.6-32.7 million) people living with HIV in 2001.

CONCLUSIONS

Country ownership of the estimation tools has allowed for additional uses of the results than had the results been produced by researchers or a team in Geneva. Guidance from a reference group and input from country teams have led to critical improvements in the models over time. Those changes have improved countries' and stakeholders' understanding of the HIV epidemic.

Estimating the Sizes of Populations At Risk of HIV Infection From Multiple Data Sources Using a Bayesian Hierarchical Model

In most countries in the world outside of sub-Saharan Africa, HIV is largely concentrated in sub-populations whose behavior puts them at higher risk of contracting and transmitting HIV, such as people who inject drugs, sex workers and men who have sex with men. Estimating the size of these sub-populations is important for assessing overall HIV prevalence and designing effective interventions. We present a Bayesian hierarchical model for estimating the sizes of local and national HIV key affected populations. The model incorporates multiple commonly used data sources including mapping data, surveys, interventions, capture-recapture data, estimates or guesstimates from organizations, and expert opinion. The proposed model is used to estimate the numbers of people who inject drugs in Bangladesh.

Mapping HIV/STI behavioural surveillance in Europe

BACKGROUND

Used in conjunction with biological surveillance, behavioural surveillance provides data allowing for a more precise definition of HIV/STI prevention strategies. In 2008, mapping of behavioural surveillance in EU/EFTA countries was performed on behalf of the European Centre for Disease prevention and Control.

METHOD

Nine questionnaires were sent to all 31 member States and EEE/EFTA countries requesting data on the overall behavioural and second generation surveillance system and on surveillance in the general population, youth, men having sex with men (MSM), injecting drug users (IDU), sex workers (SW), migrants, people living with HIV/AIDS (PLWHA), and sexually transmitted infection (STI) clinics patients. Requested data included information on system organisation (e.g. sustainability, funding, institutionalisation), topics covered in surveys and main indicators.

RESULTS

Twenty-eight of the 31 countries contacted supplied data. Sixteen countries reported an established behavioural surveillance system, and 13 a second generation surveillance system (combination of biological surveillance of HIV/AIDS and STI with behavioural surveillance). There were wide differences as regards the year of survey initiation, number of populations surveyed, data collection methods used, organisation of surveillance and coordination with biological surveillance. The populations most regularly surveyed are the general population, youth, MSM and IDU. SW, patients of STI clinics and PLWHA are surveyed less regularly and in only a small number of countries, and few countries have undertaken behavioural surveys among migrant or ethnic minorities populations. In many cases, the identification of populations with risk behaviour and the selection of populations to be included in a BS system have not been formally conducted, or are incomplete. Topics most frequently covered are similar across countries, although many different indicators are used. In most countries, sustainability of surveillance systems is not assured.

CONCLUSION

Although many European countries have established behavioural surveillance systems, there is little harmonisation as regards the methods and indicators adopted. The main challenge now faced is to build and maintain organised and functional behavioural and second generation surveillance systems across Europe, to increase collaboration, to promote robust, sustainable and cost-effective data collection methods, and to harmonise indicators.

Steep HIV prevalence declines among young people in selected Zambian communities: population-based observations (1995-2003)

BACKGROUND

Understanding the epidemiological HIV context is critical in building effective setting-specific preventive strategies. We examined HIV prevalence patterns in selected communities of men and women aged 15-59 years in Zambia.

METHODS

Population-based HIV surveys in 1995 (n = 3158), 1999 (n = 3731) and 2003 (n = 4751) were conducted in selected communities using probability proportional to size stratified random-cluster sampling. Multivariate logistic regression and trend analyses were stratified by residence, sex and age group. Absence, <30% in men and <15% in women in all rounds, was the most important cause of non-response. Saliva was used for HIV testing, and refusal was <10%.

RESULTS

Among rural groups aged 15-24 years, prevalence declined by 59.2% (15.7% to 6.4%, P < 0.001) in females and by 44.6% (5.6% to 3.1%, P < 0.001) in males. In age-group 15-49 years, declines were less than 25%. In the urban groups aged 15-24, prevalence declined by 47% (23.4% to 12.4%, P < 0.001) among females and 57.3% (7.5% to 3.2%, P = 0.001) among males but were 32% and 27% in men and women aged 15-49, respectively. Higher educated young people in 2003 had lower odds of infection than in 1995 in both urban [men: AOR 0.29(95% CI 0.14-0.60); women: AOR 0.38(95% CI 0.19-0.79)] and rural groups [men: AOR 0.16(95% CI 0.11-0.25), women: AOR 0.10(95% CI 0.01-7.34)]. Although higher mobility was associated with increased likelihood of infection in men overall, AOR, 1.71(95% CI 1.34-2.19), prevalence declined in mobile groups also (OR 0.52 95% CI 0.31-0.88). In parallel, urban young people with > or =11 school years were more likely to use condoms during the last casual sex (OR 2.96 95% CI 1.93-4.52) and report less number of casual sexual partners (AOR 0.33 95% CI 0.19-0.56) in the last twelve months than lower educated groups.

CONCLUSION

Steep HIV prevalence declines in young people, suggesting continuing declining incidence, were masked by modest overall declines. The concentration of declines in higher educated groups suggests a plausible association with behavioural change.