Spatial clustering of all-cause and HIV-related mortality in a rural South African population (2000-2006)

Spatiotemporal Analysis of HIV/AIDS Incidence in China From 2009 to 2019 and Its Association With Socioeconomic Factors: Geospatial Study

BACKGROUND

The Joint United Nations Program on HIV/AIDS (UNAIDS) has set the "95-95-95" targets to ensure that 95% of all people living with HIV will know their HIV status, 95% of all people living with HIV will receive sustained antiretroviral therapy (ART), and 95% of all people receiving ART will achieve viral suppression (<1000 copies/mL). However, few countries have currently achieved these targets, posing challenges to the realization of the UNAIDS goal to eliminate the global HIV/AIDS epidemic by 2030. The Chinese government has implemented corresponding policies for HIV/AIDS prevention and control; however, it still faces the challenge of a large number of HIV/AIDS cases. Existing research predominantly focuses on the study of a particular region or population in China, and there is relatively limited research on the macro-level analysis of the spatiotemporal distribution of HIV/AIDS across China and its association with socioeconomic factors.

OBJECTIVE

This study seeks to identify the impact of these factors on the spatiotemporal distribution of HIV/AIDS incidence in China, aiming to provide scientific recommendations for future policy development.

METHODS

This study employed ArcGIS 10.2 (Esri) for spatial analysis, encompassing measures such as the imbalance index, geographical concentration index, spatial autocorrelation analysis (Moran I), and hot spot analysis (Getis-Ord Gi*). These methods were used to unveil the spatiotemporal distribution characteristics of HIV/AIDS incidence in 31 provinces of China from 2009 to 2019. Geographical Detector was used for ecological detection, risk area detection, factor detection, and interaction detection. The analysis focused on 9 selected socioeconomic indicators to further investigate the influence of socioeconomic factors on HIV/AIDS incidence in China.

RESULTS

The spatiotemporal distribution analysis of HIV/AIDS incidence in China from 2009 to 2019 revealed distinct patterns. The spatial distribution type of HIV/AIDS incidence in China was random in 2009-2010. However, from 2011 to 2019, the distribution pattern evolved toward a clustered arrangement, with the degree of clustering increasing each year. Notably, from 2012 onwards, there was a significant and rapid growth in the aggregation of cold and hot spot clusters of HIV/AIDS incidence in China, stabilizing only by the year 2016. An analysis of the impact of socioeconomic factors on HIV/AIDS incidence in China highlighted the "urbanization rate" and "urban basic medical insurance fund expenditure" as the primary factors influencing the spatial distribution of HIV/AIDS incidence. Additionally, among social factors, indicators related to medical resources exerted a crucial influence on HIV/AIDS incidence.

CONCLUSIONS

From 2009 to 2019, HIV/AIDS incidence in China was influenced by various socioeconomic factors. In the future, it is imperative to optimize the combination of different socioeconomic indicators based on regional incidence patterns. This optimization will facilitate the formulation of corresponding policies to address the challenges posed by the HIV/AIDS epidemic.

Geographic variation in 5-year mortality following HIV diagnosis: implications for clinical interventions

Characterizing spatial distribution of HIV outcomes is vital for targeting interventions to areas most at risk. We performed spatial analysis to identify geographic clusters and factors associated with mortality in KwaZulu-Natal, South Africa. We utilized Sizanani trial (NCT01188941) data, which enrolled participants August 2010-January 2013 and obtained vital status at 5.8 (IQR 5.0-6.4) years of follow-up. We mapped geocoded addresses to 2011 Census-defined small area layer (SAL) centroids, used Kulldorff's spatial scan statistic to identify mortality clusters, and compared socio-demographic factors for SALs within and outside mortality clusters. We assigned 1,143 participants living with HIV (260 [23%] of whom died during follow-up) to 677 SALs. One lower mortality cluster (n = 90, RR = 0.23, p = 0.022) was identified near a hospital outside Durban. SALs in the cluster were younger (24y vs 25y, p < 0.001); had fewer bedrooms/household (3 vs 4, p < 0.001); had more females (52% vs 51%, p = 0.013) and residents with no schooling past age 20 (4% vs 3%, p < 0.001) or no education at all (4% vs 3%, p < 0.001); had fewer residents with income >3,200 ZAR/month (5% vs 9%, p < 0.001); and had reduced access to piped water (p < 0.001), refuse disposal (p < 0.001), and toilets (p < 0.001). Targeted interventions may improve outcomes in areas with similar characteristics.

Role of social organization engagement in high-risk groups intervention against HIV/AIDS: a case study from 176 cities of China

BACKGROUND

A high-risk prevention strategy is an effective way to fight against human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS). The China AIDS Fund for Non-Governmental Organizations (CAFNGO) was established in 2015 to help social organizations intervene to protect high-risk populations in 176 cities. This study aimed to evaluate the role of social organizations in high-risk population interventions against HIV/AIDS.

METHODS

This study was based on the CAFNGO program from 2016 to 2020. The collected data included the number and types of social organizations participating in high-risk group interventions and the amount of funds obtained by these organizations each year. We explored the factors influencing the number of newly diagnosed AIDS cases using a spatial econometric model. Furthermore, we evaluated the effectiveness of intervention activities by comparing the percentages of the individuals who initially tested positive, and the individuals who took the confirmatory test, as well as those who retested positive and underwent the treatment.

RESULTS

Overall, from 2016 to 2020, the number of social organizations involved in interventions to protect HIV/AIDS high-risk populations increased from 441 to 532, and the invested fund increased from $3.98 to $10.58 million. The number of newly diagnosed cases decreased from 9128 to 8546 during the same period. Although the number of cities with overall spatial correlations decreased, the spatial agglomeration effect persisted in the large cities. City-wise, the number of social organizations (direct effect 19.13), the permanent resident population (direct effect 0.12), GDP per capita (direct effect 17.58; indirect effect - 15.38), and passenger turnover volume (direct effect 5.50; indirect effect - 8.64) were the major factors influencing new positive cases confirmed through the testing interventions performed by the social organizations. The initial positive test rates among high-risk populations were below 5.5%, the retesting rates among those who initially tested positive were above 60%, and the treatment rates among diagnosed cases were above 70%.

CONCLUSIONS

The spatial effect of social organizations participating in interventions targeting high-risk populations funded by CAFNGO is statistically significant. Nevertheless, despite the achievements of these social organizations in tracking new cases and encouraging treatment, a series of measures should be taken to further optimize the use of CAFNGO. Working data should be updated from social organizations to CAFNGO more frequently by establishing a data monitoring system to help better track newly diagnosed AIDS cases. Multichannel financing should be expanded as well.

Spatial analysis of the AIDS mortality rate among young people in a province of the Brazilian Amazon: An ecological study

Worldwide, policies to combat human immunodeficiency virus (HIV) have led to a small decrease in the acquired immunodeficiency syndrome (AIDS) mortality rate among young people. For greater policy efficacy, it is necessary to determine the influence of social determinants of health (SDHs) in each territory. The objective of this study was to spatially analyse the AIDS mortality rate among young people in a province of the Brazilian Amazon and the spatial variability of the rate promoted by SDHs. All reports of AIDS deaths between 2007 and 2018 among young people living in the state of Pará were included in the study. The mortality rate was analysed using spatial distribution and autocorrelation, spatial scanning, and geographically weighted regression (GWR). During the study period, there were 1,372 deaths from AIDS among young people with a territorial expansion. The spatial autocorrelation showed two high-high clusters in the period from 2007 to 2010, one formed by municipalities in south-eastern Pará and one in the metropolitan region of Belém, with only the latter remaining between 2011 and 2018. This region showed a higher spatial risk for AIDS mortality and was the only cluster with spatiotemporal risk in the 2013-2018 period. Spatial variability was promoted by the i) the youth homicide rate, ii) the elementary school dropout rate and iii) the number of families registered in the Unified Registry for Social Programs (CadÚnico). This study provides support for the implementation of effective focal policies to combat HIV and reduce the mortality rate among young people in Pará.

Characterizing Unusual Spatial Clusters of Male Mental Health Emergencies Occurring During the First National COVID-19 "Lockdown" in the East Midlands Region, UK: A Geospatial Analysis of Ambulance 999 Data

The widespread psychological effects of contagion mitigation measures associated with the novel coronavirus disease 2019 (COVID-19) are well known. Phases of "lockdown" have increased levels of anxiety and depression globally. Most research uses methods such as self-reporting that highlight the greater impact of the pandemic on the mental health of females. Emergency medical data from ambulance services may be a better reflection of male mental health. We use ambulance data to identify unusual clusters of high rates of male mental health emergencies occurring in the East Midlands of the United Kingdom during the first national "lockdown" and to explore factors that may explain clusters. Analysis of more than 5,000 cases of male mental health emergencies revealed 19 unusual spatial clusters. Binary logistic regression analysis (χ2 = 787.22, df = 20, p ≤ .001) identified 16 factors that explained clusters, including proximity to "healthy" features of the physical landscape, urban and rural dynamics, and socioeconomic condition. Our findings suggest that the factors underlying vulnerability of males to severe mental health conditions during "lockdown" vary within and between rural and urban spaces, and that the wider "hinterland" surrounding clusters influences the social and physical access of males to services that facilitate mental health support. Limitations on social engagement to mitigate effects of the pandemic are likely to continue. Our approach could inform delivery of emergency services and the development of community-level services to support vulnerable males during periods of social isolation.

An exploration of factors characterising unusual spatial clusters of COVID-19 cases in the East Midlands region, UK: A geospatial analysis of ambulance 999 data

Complex interactions between physical landscapes and social factors increase vulnerability to emerging infections and their sequelae. Relative vulnerability to severe illness and/or death (VSID) depends on risk and extent of exposure to a virus and underlying health susceptibility. Identifying vulnerable communities and the regions they inhabit in real time is essential for effective rapid response to a new pandemic, such as COVID-19. In the period between first confirmed cases and the introduction of widespread community testing, ambulance records of suspected severe illness from COVID-19 could be used to identify vulnerable communities and regions and rapidly appraise factors that may explain VSID. We analyse the spatial distribution of more than 10,000 suspected severe COVID-19 cases using records of provisional diagnoses made by trained paramedics attending medical emergencies. We identify 13 clusters of severe illness likely related to COVID-19 occurring in the East Midlands of the UK and present an in-depth analysis of those clusters, including urban and rural dynamics, the physical characteristics of landscapes, and socio-economic conditions. Our findings suggest that the dynamics of VSID vary depending on wider geographic location. Vulnerable communities and regions occur in more deprived urban centres as well as more affluent peri-urban and rural areas. This methodology could contribute to the development of a rapid national response to support vulnerable communities during emerging pandemics in real time to save lives.

A Spatial Approach for Ending the Human Immunodeficiency Virus Epidemic for the United States-A DC Model

BACKGROUND

Mode of transmission-based hotspots is a smart approach to HIV mitigation, yet remains poorly evaluated and implemented in the United States. The primary aim was to identifying mode of transmission-based hotspots and populations at risk of lower viral suppression to assist in targeted planning and implementation of programs.

METHODS

We implemented spatial statistics to identify global-local hotspots and regression analysis to find populations at risk of lower viral suppression within hotspots. Data were obtained from the District of Columbia's (DC's) active surveillance system, which were geocoded based on current residence address.

RESULTS

The analysis identified 6001 HIV-positive men who have sex with men (MSM) and 6077 HIV-positive non-MSM (N = 12 078) living in DC at the end of 2018. The hotspots for MSM were central DC and non-MSM in south DC. Trends of viral suppression within MSM hotspots showed plateauing and, among non-MSM, showed decline. Regression analysis showed MSM aged 21-25 (RR: 3.199; 95% CI: 1.832-5.586) and not linked to care (8.592; 2.907-25.398) were at higher risk of being virally unsuppressed within the hotspots. For non-MSM we found those aged 12-18 (9.025; 3.314-2.581) and with unknown linkages (6.087; 3.346-13.848) were at higher risk of being virally unsuppressed within the hotspots.

CONCLUSIONS

Our analysis provides a model that may be used by other jurisdictions to identify areas of priority and plan treatment-adherence programs using surveillance data. Attaining viral suppression is crucial in reducing new diagnoses; a spatial approach can be an important tool in Ending the HIV Epidemic.

County-level predictors of retention in care status among people living with HIV in South Carolina from 2010 to 2016: a data-driven approach

OBJECTIVE

The aim of this study was to examine the geospatial variation of retention in care (RIC) across the counties in South Carolina (SC) from 2010 to 2016 and identify the relevant county-level predictors.

DESIGN

Aggregated data on county-level RIC among HIV patients from 2010 to 2016 were retrieved from an electronic HIV/AIDS reporting system in SC Department of Health and Environmental Control. Sociological framework of health was used to select potential county-level predictors from multiple public datasets.

METHODS

Geospatial mapping was used to display the spatial heterogeneity of county-level RIC rate in SC. Generalized linear mixed effect regression with least absolute shrinkage and selection operator (LASSO) was employed to identify county-level predictors related to the change of RIC status over time. Confusion matrix and area under the curve statistics were used to evaluate model performance.

RESULTS

More than half of the counties had their RIC rates lower than the national average. The change of county-level RIC rate from 2010 to 2016 was not significant, and spatial heterogeneity in RIC rate was identified. A total of 22 of the 31 county-level predictors were selected by LASSO for predicting county-level RIC status. Counties with lower collective efficacy, larger proportions of men and/or persons with high education were more likely to have their RIC rates lower than the national average. In contrast, numbers of accessible mental health centres were positively related to county-level RIC status.

CONCLUSION

Spatial variation in RIC could be identified, and county-level factors associated with accessible healthcare facilities and social capital significantly contributed to these variations. Structural and individual interventions targeting these factors are needed to improve the county-level RIC and reduce the spatial variation in HIV care.

Looking Back and Moving Forward: The Evolution and Potential Opportunities for the Future of Alcohol Outlet Density Measurement

The literature consistently finds that areas with greater density of alcohol outlets (places that sell alcohol) tend to have higher levels of public health harms. However, conflicting findings arise when researchers drill down to identify the type(s) of alcohol outlets with the strongest associations with harms and the mechanisms that explain these associations. These disagreements could be a result of the outdated methods commonly used to quantify the alcohol environment: counts of the number of outlets in an area. This manuscript reviews the events and ideas that shaped the literature on the physical alcohol environment. It then defines the three main methods used to measure alcohol outlet density, conducts an exploratory factor analysis to explore the constructs underlying each method, and presents a novel conceptual framework that summarizes the three methods, their respective underlying constructs, and the setting(s) in which each may be most appropriate. The framework proposes that counts of alcohol outlets measure availability, proximity to the nearest outlet measures accessibility, and spatial access measures measure access, which comprises both availability and accessibility. We argue that researchers should consider using proximity and spatial access measures when possible and outline how doing so may present opportunities to advance theory and the design and implementation of alcohol outlet zoning regulations. Finally, this manuscript draws on research from other areas of the built environment to suggest opportunities to use novel methods to overcome common hurdles (e.g., separating subtypes of outlets, ecologic designs) and a new challenge on the horizon: home delivery.

A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa

Spatial analysis has become an increasingly used analytic approach to describe and analyze spatial characteristics of disease burden, but the depth and coverage of its usage for health surveys data in Sub-Saharan Africa are not well known. The objective of this scoping review was to conduct an evaluation of studies using spatial statistics approaches for national health survey data in the SSA region. An organized literature search for studies related to spatial statistics and national health surveys was conducted through PMC, PubMed/Medline, Scopus, NLM Catalog, and Science Direct electronic databases. Of the 4,193 unique articles identified, 153 were included in the final review. Spatial smoothing and prediction methods were predominant (n = 108), followed by spatial description aggregation (n = 25), and spatial autocorrelation and clustering (n = 19). Bayesian statistics methods and lattice data modelling were predominant (n = 108). Most studies focused on malaria and fever (n = 47) followed by health services coverage (n = 38). Only fifteen studies employed nonstandard spatial analyses (e.g., spatial model assessment, joint spatial modelling, accounting for survey design). We recommend that for future spatial analysis using health survey data in the SSA region, there must be an improve recognition and awareness of the potential dangers of a naïve application of spatial statistical methods. We also recommend a wide range of applications using big health data and the future of data science for health systems to monitor and evaluate impacts that are not well understood at local levels.

Geographic Information Systems, spatial analysis, and HIV in Africa: A scoping review

INTRODUCTION

Geographic Information Systems (GIS) and spatial analysis are emerging tools for global health, but it is unclear to what extent they have been applied to HIV research in Africa. To help inform researchers and program implementers, this scoping review documents the range and depth of published HIV-related GIS and spatial analysis research studies conducted in Africa.

METHODS

A systematic literature search for articles related to GIS and spatial analysis was conducted through PubMed, EMBASE, and Web of Science databases. Using pre-specified inclusion criteria, articles were screened and key data were abstracted. Grounded, inductive analysis was conducted to organize studies into meaningful thematic areas.

RESULTS AND DISCUSSION

The search returned 773 unique articles, of which 65 were included in the final review. 15 different countries were represented. Over half of the included studies were published after 2014. Articles were categorized into the following non-mutually exclusive themes: (a) HIV geography, (b) HIV risk factors, and (c) HIV service implementation. Studies demonstrated a broad range of GIS and spatial analysis applications including characterizing geographic distribution of HIV, evaluating risk factors for HIV, and assessing and improving access to HIV care services.

CONCLUSIONS

GIS and spatial analysis have been widely applied to HIV-related research in Africa. The current literature reveals a diversity of themes and methodologies and a relatively young, but rapidly growing, evidence base.

Identifying 'corridors of HIV transmission' in a severely affected rural South African population: a case for a shift toward targeted prevention strategies

Background

In the context of a severe generalized African HIV epidemic, the value of geographically targeted prevention interventions has only recently been given serious consideration. However, to date no study has performed a population-based analysis of the micro-geographical clustering of HIV incident infections, limiting the evidential support for such a strategy.

Methods

We followed 17 984 HIV-uninfected individuals aged 15–54 in a population-based cohort in rural KwaZulu-Natal, South Africa, and observed individual HIV sero-conversions between 2004 and 2014. We geo-located all individuals to an exact homestead of residence (accuracy <2 m). We then employed a two-dimensional Gaussian kernel of radius 3 km to produce robust estimates of HIV incidence which vary across continuous geographical space. We also applied Tango's flexibly shaped spatial scan statistic to identify irregularly shaped clusters of high HIV incidence.

Results

Between 2004 and 2014, we observed a total of 2 311 HIV sero-conversions over 70 534 person-years of observation, at an overall incidence of 3.3 [95% confidence interval (CI), 3.1-3.4] per 100 person-years. Three large irregularly-shaped clusters of new HIV infections (relative risk = 1.6, 1.7 and 2.3) were identified in two adjacent peri-urban communities near the National Road (P = 0.001, 0.015) as well as in a rural node bordering a recent coal mine development (P = 0.020), respectively. Together the clusters had a significantly higher age-sex standardized incidence of 5.1 (95% CI, 4.7-5.6) per 100 person-years compared with a standardized incidence of 3.0 per 100 person-years (95% CI, 2.9-3.2) in the remainder of the study area. Though these clusters comprise just 6.8% of the study area, they account for one out of every four sero-conversions observed over the study period.

Conclusions

Our study has revealed clear ‘corridors of transmission’ in this typical rural, hyper-endemic population. Even in a severely affected rural African population, an approach that seeks to provide preventive interventions to the most vulnerable geographies could be more effective and cost-effective in reducing the overall rate of new HIV infections. There is an urgent need to develop and test such interventions as part of an overall combination prevention approach.

Space-time variations in child mortality in a rural South African population with high HIV prevalence (2000-2014)

Objective

The aim of the study was to identify the key determinants of child mortality ‘hot-spots’ in space and time.

Methods

Comprehensive population-based mortality data collected between 2000 and 2014 by the Africa Centre Demographic Information System located in the UMkhanyakude District of KwaZulu-Natal Province, South Africa, was analysed. We assigned all mortality events and person-time of observation for children <5 years of age to an exact homestead of residence (mapped to <2m accuracy as part of the DSA platform). Using these exact locations, both the Kulldorff and Tango spatial scan statistics for regular and irregular shaped cluster detection were used to identify clusters of childhood mortality events in both space and time.

Findings

Of the 49 986 children aged < 5 years who resided in the study area between 2000 and 2014, 2010 (4.0%) died. Childhood mortality decreased by 80% over the period from >20 per 1000 person-years in 2001–2003 to 4 per 1000 person-years in 2014. The two scanning spatial techniques identified two high-risk clusters for child mortality along the eastern border of the study site near the national highway, with a relative risk of 2.10 and 1.91 respectively.

Conclusions

The high-risk communities detected in this work, and the differential risk factor profile of these communities, can assist public health professionals to identify similar populations in other parts of rural South Africa. Identifying child mortality hot-spots will potentially guide policy interventions in rural, resource-limited settings.

Space-time patterns in maternal and mother mortality in a rural South African population with high HIV prevalence (2000-2014): results from a population-based cohort

Background

International organs such as, the African Union and the South African Government view maternal health as a dominant health prerogative. Even though most countries are making progress, maternal mortality in South Africa (SA) significantly increased between 1990 and 2015, and prevented the country from achieving Millennium Development Goal 5. Elucidating the space-time patterns and risk factors of maternal mortality in a rural South African population could help target limited resources and policy guidelines to high-risk areas for the greatest impact, as more generalized interventions are costly and often less effective.

Methods

Population-based mortality data from 2000 to 2014 for women aged 15–49 years from the Africa Centre Demographic Information System located in the Umkhanyakude district of KwaZulu-Natal Province, South Africa were analysed. Our outcome was classified into two definitions: Maternal mortality; the death of a woman while pregnant or within 42 days of cessation of pregnancy, regardless of the duration and site of the pregnancy, from any cause related to or exacerbated by the pregnancy or its management but not from unexpected or incidental causes; and ‘Mother death’; death of a mother whilst child is less than 5 years of age. Both the Kulldorff and Tango spatial scan statistics for regular and irregular shaped cluster detection respectively were used to identify clusters of maternal mortality events in both space and time.

Results

The overall maternal mortality ratio was 650 per 100,000 live births, and 1204 mothers died while their child was less than or equal to 5 years of age, of a mortality rate of 370 per 100,000 children. Maternal mortality declined over the study period from approximately 600 per 100,000 live births in 2000 to 400 per 100,000 live births in 2014. There was no strong evidence of spatial clustering for maternal mortality in this rural population. However, the study identified a significant spatial cluster of mother deaths in childhood (p = 0.022) in a peri-urban community near the national road. Based on our multivariable logistic regression model, HIV positive status (Adjusted odds ratio [aOR] = 2.5, CI 95%: [1.5–4.2]; primary education or less (aOR = 1.97, CI 95%: [1.04–3.74]) and parity (aOR = 1.42, CI 95%: [1.24–1.63]) were significant predictors of maternal mortality.

Conclusions

There has been an overall decrease in maternal and mother death between 2000 and 2014. The identification of a clear cluster of mother deaths shows the possibility of targeting intervention programs in vulnerable communities, as population-wide interventions may be ineffective and too costly to implement.

Spatial analysis of HIV infection and associated individual characteristics in Burundi: indications for effective prevention

Background

Adequate resource allocation is critical in the battle against HIV/AIDS, especially in Africa. The determination of the location and nature of HIV services to implement must comply with the geographic, social and behavioral characteristics of patients. We therefore investigated the spatial heterogeneity of HIV prevalence in Burundi and then assessed the association of social and behavioral characteristics with HIV infection accounting for the spatial heterogeneity.

Methods

We used data from the 2010 Demographic and Health Survey. We analyzed these data with a geostatistical approach (which takes into account spatial autocorrelation) by i) interpolating HIV data using the kernel density estimation, ii) identifying the spatial clusters with high and low HIV prevalence using the Kulldorff spatial scan statistics, and then iii) performing a multivariate spatial logistic regression.

Results

Overall HIV prevalence was 1.4 %. The interpolated data showed the great spatial heterogeneity of HIV prevalence (from 0 to 10 %), independently of administrative boundaries. A cluster with high HIV prevalence was found in the capital city and adjacent areas (3.9 %; relative risk 3.7, p < 0.001) whereas a cluster with low prevalence straddled two southern provinces (0 %; p = 0.02). By multivariate spatial analysis, HIV infection was significantly associated with the female sex (posterior odds ratio [POR] 1.36, 95 % credible interval [CrI] 1.13-1.64), an older age (POR 1.97, 95 % CrI 1.26-3.08), the level of education (POR 1.50, 95 % CrI 1.22-1.84), the marital status (POR 1.86, 95 % CrI 1.23-2.80), a higher wealth index (POR 2.11, 95 % CrI 1.77-2.51), the sexual activity (POR 1.76, 95 % CrI 1.04-2.96), and a history of sexually transmitted infection (POR 2.03, 95 % CrI 1.56-2.64).

Conclusions

Our study, which shows where and towards which populations HIV resources should be allocated, could help national health policy makers develop an effective HIV intervention in Burundi. Our findings support the strategy of the Joint United Nations Programme on HIV/AIDS (UNAIDS) for country-specific, in-depth analyses of HIV epidemics to tailor national prevention responses.

Geographic Variations in Retention in Care among HIV-Infected Adults in the United States

Objective

To understand geographic variations in clinical retention, a central component of the HIV care continuum and key to improving individual- and population-level HIV outcomes.

Design

We evaluated retention by US region in a retrospective observational study.

Methods

Adults receiving care from 2000–2010 in 12 clinical cohorts of the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) contributed data. Individuals were assigned to Centers for Disease Control and Prevention (CDC)-defined regions by residential data (10 cohorts) and clinic location as proxy (2 cohorts). Retention was ≥2 primary HIV outpatient visits within a calendar year, >90 days apart. Trends and regional differences were analyzed using modified Poisson regression with clustering, adjusting for time in care, age, sex, race/ethnicity, and HIV risk, and stratified by baseline CD4+ count.

Results

Among 78,993 adults with 444,212 person-years of follow-up, median time in care was 7 years (Interquartile Range: 4–9). Retention increased from 2000 to 2010: from 73% (5,000/6,875) to 85% (7,189/8,462) in the Northeast, 75% (1,778/2,356) to 87% (1,630/1,880) in the Midwest, 68% (8,451/12,417) to 80% (9,892/12,304) in the South, and 68% (5,147/7,520) to 72% (6,401/8,895) in the West. In adjusted analyses, retention improved over time in all regions (p<0.01, trend), although the average percent retained lagged in the West and South vs. the Northeast (p<0.01).

Conclusions

In our population, retention improved, though regional differences persisted even after adjusting for demographic and HIV risk factors. These data demonstrate regional differences in the US which may affect patient care, despite national care recommendations.

Evidence for localised HIV related micro-epidemics associated with the decentralised provision of antiretroviral treatment in rural South Africa: a spatio-temporal analysis of changing mortality patterns (2007-2010)

Background

In this study we analysed the spatial and temporal changes in patterns of mortality over a period when antiretroviral therapy (ART) was rolled out in a rural region of north–eastern South Africa. Previous studies have identified localised concentrated HIV related sub–epidemics and recommended that micro–level analyses be carried out in order to direct focused interventions.

Methods

Data from an ongoing health and socio–demographic surveillance study was used in the analysis. The follow–up was divided into two periods, 2007–2008 and 2009–2010, representing the times immediately before and after the effects on mortality of the decentralised ART provision from a newly established local health centre would be expected to be evident. The study population at the start of the analysis was approximately 73 000 individuals. Data were aggregated by village and also using a 2 × 2 km grid. We identified villages, grid squares and regions in the site where mortality rates within each time period or rate ratios between the periods differed significantly from the overall trends. We used clustering techniques to identify cause–specific mortality hotspots.

Findings

Comparing the two periods, there was a 30% decrease in age and gender standardised adult HIV–related and TB (HIV/TB) mortality with no change in mortality due to other causes. There was considerable spatial heterogeneity in the mortality patterns. Areas separated by 2 to 4 km with very different epidemic trajectories were identified. There was evidence that the impact of ART in reducing HIV/TB mortality was greatest in communities with higher mortality rates in the earlier period.

Conclusions

This study shows the value of conducting high resolution spatial analyses in order to understand how local micro–epidemics contribute to changes seen over a wider area. Such analyses can support targeted interventions.