Trends in knowledge of HIV status and efficiency of HIV testing services in sub-Saharan Africa, 2000-20: a modelling study using survey and HIV testing programme data.

BACKGROUND: Monitoring knowledge of HIV status among people living with HIV is essential for an effective national HIV response. This study estimates progress and gaps in reaching the UNAIDS 2020 target of 90% knowledge of status, and the efficiency of HIV testing services in sub-Saharan Africa, where two thirds of all people living with HIV reside. METHODS: For this modelling study, we used data from 183 population-based surveys (including more than 2·7 million participants) and national HIV testing programme reports (315 country-years) from 40 countries in sub-Saharan Africa as inputs into a mathematical model to examine trends in knowledge of status among people living with HIV, median time from HIV infection to diagnosis, HIV testing positivity, and proportion of new diagnoses among all positive tests, adjusting for retesting. We included data from 2000 to 2019, and projected results to 2020. FINDINGS: Across sub-Saharan Africa, knowledge of status steadily increased from 5·7% (95% credible interval [CrI] 4·6-7·0) in 2000 to 84% (82-86) in 2020. 12 countries and one region, southern Africa, reached the 90% target. In 2020, knowledge of status was lower among men (79%, 95% CrI 76-81) than women (87%, 85-89) across sub-Saharan Africa. People living with HIV aged 15-24 years were the least likely to know their status (65%, 62-69), but the largest gap in terms of absolute numbers was among men aged 35-49 years, with 701 000 (95% CrI 611 000-788 000) remaining undiagnosed. As knowledge of status increased from 2000 to 2020, the median time to diagnosis decreased from 9·6 years (9·1-10) to 2·6 years (1·8-3·5), HIV testing positivity declined from 9·0% (7·7-10) to 2·8% (2·1-3·9), and the proportion of first-time diagnoses among all positive tests dropped from 89% (77-96) to 42% (30-55). INTERPRETATION: On the path towards the next UNAIDS target of 95% diagnostic coverage by 2025, and in a context of declining positivity and yield of first-time diagnoses, disparities in knowledge of status must be addressed. Increasing knowledge of status and treatment coverage among older men could be crucial to reducing HIV incidence among women in sub-Saharan Africa, and by extension, reducing mother-to-child transmission. FUNDING: Steinberg Fund for Interdisciplinary Global Health Research (McGill University); Canadian Institutes of Health Research; Bill & Melinda Gates Foundation; Fonds the recherche du Québec-Santé; UNAIDS; UK Medical Research Council; MRC Centre for Global Infectious Disease Analysis; UK Foreign, Commonwealth & Development Office

Naomi: a new modelling tool for estimating HIV epidemic indicators at the district level in sub-Saharan Africa.

INTRODUCTION: HIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or equivalent subnational administrative level. We developed a Bayesian small-area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five-year age groups. METHODS: Small-area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART. Incidence was modelled by district-level HIV prevalence and ART coverage. Model outputs of counts and rates for each indicator were aggregated to multiple geographic and demographic stratifications of interest. The model was estimated in an empirical Bayes framework, furnishing probabilistic uncertainty ranges for all output indicators. Example results were presented using data from Malawi during 2016-2018. RESULTS: Adult HIV prevalence in September 2018 ranged from 3.2% to 17.1% across Malawi's districts and was higher in southern districts and in metropolitan areas. ART coverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIV was among ages 35 to 39 for both women and men, while the most untreated PLHIV were among ages 25 to 29 for women and 30 to 34 for men. Relative uncertainty was larger for the untreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART at facilities in Lilongwe city, an estimated 71% (95% CI, 61% to 79%) resided in Lilongwe city, 20% (14% to 27%) in Lilongwe district outside the metropolis, and 9% (6% to 12%) in neighbouring Dowa district. Thirty-eight percent (26% to 50%) of Lilongwe rural residents and 39% (27% to 50%) of Dowa residents received treatment at facilities in Lilongwe city. CONCLUSIONS: The Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data

Use of a dwelling-referenced geographic information system to characterize urban tuberculosis

Using ArcView 3.2 software, all active TB cases reported in the former city of Montreal 1996--2000 were precisely geo-coded, that is mapped to the corresponding residential address. For comparison, using a case-cohort approach control dwellings were randomly selected from the municipal dwelling GIS, with a 10:1 ratio. We identified 595 case and 5950 control dwellings. Census tract data from the 1996 Canadian Census as well as dwelling characteristics from the Montreal housing database were attributed to both case and control dwellings. Multivariate logistic regression was used with dwelling status (case vs. control) as the dependant variable, to evaluate the independent influence of crowding and other socio-demographic factors.A high-precision housing GIS complemented census data in pinpointing and characterising the occurrence of TB in Montreal. It provided a more refined assessment of the impact of local crowding, after adjustment for other important factors

Dwellings, crowding, and tuberculosis in Montreal

The association of tuberculosis (TB) with poverty has long been recognized, yet it may reflect not only characteristics of poor individuals, but also housing and neighborhood features which promote airborne spread. We sought to determine whether dwelling and building features, residential density and crowding are independently associated with TB occurrence in a low-incidence setting. We used residential addresses to geocode active TB cases reported in Montreal in 1996-2000. These "case dwellings" were linked to the municipal dwelling geodatabase from 2000, and to Canadian census data from 1996. We compared them with randomly selected Montreal dwellings ("controls," in a 1:10 ratio), using the same data sources. From multivariate logistic regression, the 595 case dwellings were more likely than the 5950 control dwellings to be in buildings >5 stories tall (adjusted odds ratios [OR] 1.6; 95% CI: 1.0-2.5), constructed since 1970 (adjusted OR 2.5; 1.8-3.6), in the lowest quartile for resale valuation (adjusted OR 1.3; 1.0-1.6), and on blocks where lot coverage exceeded the median value (adjusted OR 1.3; 1.0-1.6). Case dwellings were also more often found in census tracts with more persons per room, and a higher proportion of inhabitants who had arrived in Canada within the last 5 years. We conclude that dwelling and building features--notably dwellings in taller and new buildings, with lower resale value, and dwellings on blocks with high residential density--as well as crowding, were associated with TB occurrence, after adjustment for sociodemographic factors.Canada Tuberculosis Housing Crowding Geographic information systems

Enhanced syndromic surveillance for mass gatherings in the Pacific: a case study of the 11th Festival of Pacific Arts in Solomon Islands, 2012

Mass gatherings pose public health challenges to host countries, as they can cause or exacerbate disease outbreaks within the host location or elsewhere. In July 2012, the 11th Festival of Pacific Arts (FOPA), a mass gathering event involving 22 Pacific island states and territories, was hosted by Solomon Islands. An enhanced syndromic surveillance (ESS) system was implemented for the event. Throughout the capital city, Honiara, 15 sentinel sites were established and successfully took part in the ESS system, which commenced one week before the FOPA (25 June) and concluded eight days after the event (22 July). The ESS involved expanding on the existing syndromic surveillance parameters: from one to 15 sentinel sites, from four to eight syndromes, from aggregated to case-based reporting and from weekly to daily reporting. A web-based system was developed to enable data entry, data storage and data analysis. Towards the end of the ESS period, a focus group discussion and series of key informant interviews were conducted. The ESS was considered a success and played an important role in the early detection of possible outbreaks. For the period of the ESS, 1668 patients with syndrome presentations were received across the 15 sentinel sites. There were no major events of public health significance. Several lessons were learnt that are relevant to ESS in mass gathering scenarios, including the importance of having adequate lead in time for engagement and preparation to ensure appropriate policy and institutional frameworks are put in place

Spatio-temporal estimates of HIV risk group proportions for adolescent girls and young women across 13 priority countries in sub-Saharan Africa

The Global AIDS Strategy 2021-2026 identifies adolescent girls and young women (AGYW) as a priority population for HIV prevention, and recommends differentiating intervention portfolios geographically based on local HIV incidence and individual risk behaviours. We estimated prevalence of HIV risk behaviours and associated HIV incidence at health district level among AGYW living in 13 countries in sub-Saharan Africa. We analysed 46 geospatially-referenced national household surveys conducted between 1999-2018 across 13 high HIV burden countries in sub-Saharan Africa. Female survey respondents aged 15-29 years were classified into four risk groups (not sexually active, cohabiting, non-regular or multiple partner[s] and female sex workers [FSW]) based on reported sexual behaviour. We used a Bayesian spatio-temporal multinomial regression model to estimate the proportion of AGYW in each risk group stratified by district, year, and five-year age group. Using subnational estimates of HIV prevalence and incidence produced by countries with support from UNAIDS, we estimated new HIV infections in each risk group by district and age group. We then assessed the efficiency of prioritising interventions according to risk group. Data consisted of 274,970 female survey respondents aged 15-29. Among women aged 20-29, cohabiting (63.1%) was more common in eastern Africa than non-regular or multiple partner(s) (21.3%), while in southern countries non-regular or multiple partner(s) (58.9%) were more common than cohabiting (23.4%). Risk group proportions varied substantially across age groups (65.9% of total variation explained), countries (20.9%), and between districts within each country (11.3%), but changed little over time (0.9%). Prioritisation based on behavioural risk, in combination with location- and age-based prioritisation, reduced the proportion of population required to be reached in order to find half of all expected new infections from 19.4% to 10.6%. FSW were 1.3% of the population but 10.6% of all expected new infections. Our risk group estimates provide data for HIV programmes to set targets and implement differentiated prevention strategies outlined in the Global AIDS Strategy. Successfully implementing this approach would result in more efficiently reaching substantially more of those at risk for infections

Spatio-temporal estimates of HIV risk group proportions for adolescent girls and young women across 13 priority countries in sub-Saharan Africa.

The Global AIDS Strategy 2021-2026 identifies adolescent girls and young women (AGYW) as a priority population for HIV prevention, and recommends differentiating intervention portfolios geographically based on local HIV incidence and individual risk behaviours. We estimated prevalence of HIV risk behaviours and associated HIV incidence at health district level among AGYW living in 13 countries in sub-Saharan Africa. We analysed 46 geospatially-referenced national household surveys conducted between 1999-2018 across 13 high HIV burden countries in sub-Saharan Africa. Female survey respondents aged 15-29 years were classified into four risk groups (not sexually active, cohabiting, non-regular or multiple partner[s] and female sex workers [FSW]) based on reported sexual behaviour. We used a Bayesian spatio-temporal multinomial regression model to estimate the proportion of AGYW in each risk group stratified by district, year, and five-year age group. Using subnational estimates of HIV prevalence and incidence produced by countries with support from UNAIDS, we estimated new HIV infections in each risk group by district and age group. We then assessed the efficiency of prioritising interventions according to risk group. Data consisted of 274,970 female survey respondents aged 15-29. Among women aged 20-29, cohabiting (63.1%) was more common in eastern Africa than non-regular or multiple partner(s) (21.3%), while in southern countries non-regular or multiple partner(s) (58.9%) were more common than cohabiting (23.4%). Risk group proportions varied substantially across age groups (65.9% of total variation explained), countries (20.9%), and between districts within each country (11.3%), but changed little over time (0.9%). Prioritisation based on behavioural risk, in combination with location- and age-based prioritisation, reduced the proportion of population required to be reached in order to find half of all expected new infections from 19.4% to 10.6%. FSW were 1.3% of the population but 10.6% of all expected new infections. Our risk group estimates provide data for HIV programmes to set targets and implement differentiated prevention strategies outlined in the Global AIDS Strategy. Successfully implementing this approach would result in more efficiently reaching substantially more of those at risk for infections

Evaluation of geospatial methods to generate subnational HIV prevalence estimates for local level planning

Objective: There is evidence of substantial subnational variation in the HIV epidemic. However, robust spatial HIV data are often only available at high levels of geographic aggregation and not at the finer resolution needed for decision making. Therefore, spatial analysis methods that leverage available data to provide local estimates of HIV prevalence may be useful. Such methods exist but have not been formally compared when applied to HIV. Design/methods: Six candidate methods - including those used by UNAIDS to generate maps and a Bayesian geostatistical approach applied to other diseases- were used to generate maps and subnational estimates of HIV prevalence across three countries using cluster level data from household surveys. Two approaches were used to assess the accuracy of predictions: (1) internal validation, whereby a proportion of input data is held back (test dataset) to challenge predictions, (2) comparison with location specific data from household surveys in earlier years. Results: Each of the methods can generate usefully accurate predictions of prevalence at unsampled locations, with the magnitude of the error in predictions similar across approaches. However, the Bayesian geostatistical approach consistently gave marginally the strongest statistical performance across countries and validation procedures. Conclusions: Available methods may be able to furnish estimates of HIV prevalence at finer spatial scales than the data currently allow. The subnational variation revealed can be integrated into planning to ensure responsiveness to the spatial features of the epidemic. The Bayesian geostatistical approach is a promising strategy for integrating HIV data to generate robust local estimates