Declines in HIV incidence among men and women in a South African population-based cohort

Over the past decade, there has been a massive scale-up of primary and secondary prevention services to reduce the population-wide incidence of HIV. However, the impact of these services on HIV incidence has not been demonstrated using a prospectively followed, population-based cohort from South Africa—the country with the world’s highest rate of new infections. To quantify HIV incidence trends in a hyperendemic population, we tested a cohort of 22,239 uninfected participants over 92,877 person-years of observation. We report a 43% decline in the overall incidence rate between 2012 and 2017, from 4.0 to 2.3 seroconversion events per 100 person-years. Men experienced an earlier and larger incidence decline than women (59% vs. 37% reduction), which is consistent with male circumcision scale-up and higher levels of female antiretroviral therapy coverage. Additional efforts are needed to get more men onto consistent, suppressive treatment so that new HIV infections can be reduced among women

Capturing the spatial variability of HIV epidemics in South Africa and Tanzania using routine healthcare facility data

Background: Large geographical variations in the intensity of the HIV epidemic in sub-Saharan Africa call for geographically targeted resource allocation where burdens are greatest. However, data available for mapping the geographic variability of HIV prevalence and detecting HIV ‘hotspots’ is scarce, and population-based surveillance data are not always available. Here, we evaluated the viability of using clinic-based HIV prevalence data to measure the spatial variability of HIV in South Africa and Tanzania. Methods: Population-based and clinic-based HIV data from a small HIV hyper-endemic rural community in South Africa as well as for the country of Tanzania were used to map smoothed HIV prevalence using kernel interpolation techniques. Spatial variables were included in clinic-based models using co-kriging methods to assess whether cofactors improve clinic-based spatial HIV prevalence predictions. Clinic- and population-based smoothed prevalence maps were compared using partial rank correlation coefficients and residual local indicators of spatial autocorrelation. Results: Routinely-collected clinic-based data captured most of the geographical heterogeneity described by population-based data but failed to detect some pockets of high prevalence. Analyses indicated that clinic-based data could accurately predict the spatial location of so-called HIV ‘hotspots’ in > 50% of the high HIV burden areas. Conclusion: Clinic-based data can be used to accurately map the broad spatial structure of HIV prevalence and to identify most of the areas where the burden of the infection is concentrated (HIV ‘hotspots’). Where population-based data are not available, HIV data collected from health facilities may provide a second-best option to generate valid spatial prevalence estimates for geographical targeting and resource allocation

Large age shifts in HIV-1 incidence patterns in KwaZulu-Natal, South Africa

HIV incidence has recently been in decline across some of the most intense epidemics in sub-Saharan Africa due to the scale-up of prevention and transmission-blocking treatments. Understanding whether declines in incidence are being felt equally across age and gender can help prioritize demographic groups where more effort is needed to lower transmission. We found that HIV incidence has declined disproportionately in the youngest men and women in a population with the highest HIV prevalence in the world. Shifts in the age distribution of risk may be the consequence of aging prevalence, prioritized prevention to younger individuals, and delays in age at infection from reduced overall force of infection. Our results highlight the need to expand age targets for HIV prevention

Genetic Assignment Methods for Gaining Insight into the Management of Infectious Disease by Understanding Pathogen, Vector, and Host Movement

For many pathogens with environmental stages, or those carried by vectors or intermediate hosts, disease transmission is strongly influenced by pathogen, host, and vector movements across complex landscapes, and thus quantitative measures of movement rate and direction can reveal new opportunities for disease management and intervention. Genetic assignment methods are a set of powerful statistical approaches useful for establishing population membership of individuals. Recent theoretical improvements allow these techniques to be used to cost-effectively estimate the magnitude and direction of key movements in infectious disease systems, revealing important ecological and environmental features that facilitate or limit transmission. Here, we review the theory, statistical framework, and molecular markers that underlie assignment methods, and we critically examine recent applications of assignment tests in infectious disease epidemiology. Research directions that capitalize on use of the techniques are discussed, focusing on key parameters needing study for improved understanding of patterns of disease

Geographic Distribution of HIV-Stigma Among Women Of Child-Bearing Age In Rural Kenya

Thesis (Master's)--University of Washington, 2012Background: HIV-stigma is considered to be a major driver of the HIV/AIDS pandemic, yet there is a limited understanding of its epidemiology, especially at the structural/community level. Here we describe geographic patterns of two types of HIV-stigma in a population of women of child-bearing age: internalized-stigma (associated with shame) and externalized stigma (associated with blame), and explore whether individuals with similar attitudes towards people living with HIV are more likely to reside in the same geographic area. Methods: A cross-sectional sample of 405 women who gave birth within a one year period between January - December, 2010 was surveyed from the constituency of Gem, Kenya, one of three regions in the Western Kenya Health and Demographic Surveillance Area (HDSA), a 13 x 20 km region with a population of 220,000. Two forms of HIV-related stigma, self-reported HIV status, and other demographic variables were measured using a standardized, validated questionnaire. Latitude/Longitude coordinates of participants' residences were obtained with GPS devices. Residential locations of participants were compared with respect to whether or not individuals reported each form of stigma at different spatial scales using the K-function, a second order spatial data analysis used to measure spatial clustering of binary outcomes. Generalized additive models (GAMs) were used to assess whether spatial clustering of each stigma indicator occurred beyond that explained by the spatial patterns of individual-level characteristics such as age, income, education, and other socio-economic variables. Results: Among 373 women surveyed with complete GPS data, the median age was 25 years (IQR, 22-30 years), 12% self-reported positive HIV status, 45.5% reported at least one of three indicators of harboring internalized HIV-stigma (an indicator of shame) and 89.4% reported at least one of four indicators of harboring externalized stigma (an indicator of blame). There was strong evidence for a geographic trend in rates of externalized stigma among the respondents, with those who reported no form of externalized HIV-stigma being more likely to reside in the Southwestern portion of Gem compared to the Northeastern portion of the region, controlling for individual-level factors (p = 0.02). In contrast to blame, we did not observe spatial clustering for internalized stigma (shame) beyond that of complete spatial randomness (p = 0.36). Conclusions: The spatial trend observed for rates of externalized stigma compared to the random spatial distribution of internalized stigma may point to differences in the underlying social processes leading to each form of stigma. Externalized stigma may be driven more by dominant cultural beliefs disseminated within communities (i.e., churches, health facilities, or other leaders), whereas internalized stigma may be the result of individual-level characteristics outside the domain of community influence. Geographic studies of stigma can indicate higher risk areas and provide a first step in generating hypotheses as to potential community-level etiologies of stigma. Further data and hypothesis-testing is needed on community-level attributes that might promote lower rates of externalized stigma or `high tolerance' areas. These data may inform community-level interventions to decrease HIV-related stigma

Host, pathogen, and geographic drivers of major Salmonella serovars in rural and urban Kenya

Thesis (Ph.D.)--University of Washington, 2015Introduction: Salmonella serotypes are among the leading causes of bacterial infections in Africa, contributing to both diarrheal and blood stream disease. This dissertation comprises two studies to address the clinical epidemiology of non-typhoidal Salmonella (NTS) in rural Kenya (Aim 1) and the spatial and environmental epidemiology of typhoid fever in a slum in urban Kenya (Aim 2). Methods: Both studies involved data from large community-based and clinic surveys. For Aim 1, we selected a sub-cohort of individuals with NTS in whom we compared characteristics of those with NTS bacteremia to those with NTS diarrhea using logistic regression models. Cofactors assessed included those related to host immunity and co-infection (HIV status, malaria, malnutrition, and age) and pathogen-related risk factors (drug resistance, serotype, and multi-locus sequence type). NTS isolates were genotyped to investigate genetic differences in strains causing diarrheal versus bacteremic infection. For Aim 2 we conducted a spatial case-control study to determine host and geographic risk factors for typhoid fever among individuals residing in an informal urban settlement (Kibera) in Nairobi, Kenya. We used both logistic regression and spatial regression models to test whether differences in topography, a proxy for the downstream flow and accumulation of fecal contamination, explain the observed geographic pattern in risk of typhoid fever. Results: For Aim 1 we found that multi-drug resistant (MDR) non-typhoidal Salmonella (NTS) was associated with NTS bacteremia compared to NTS diarrhea, controlling for host-cofactors. NTS bacteremia was also associated with younger age and HIV infection. The association of MDR with NTS bacteremia was present in stratified analyses of HIV-infected and uninfected individuals, with a stronger association among HIV negative individuals. We observed presence of STS313 in both NTS bacteremia and diarrhea. For Aim 2 we found that the risk of typhoid fever was geographically heterogeneous across a small area within the Kibera informal settlement, with greater risk in the lower elevation areas compared to high elevation areas. The association with low elevation was seen in children but not adults. Conclusion: Our findings from Aim 1 suggest that multi-drug resistance is a key driver of NTS invasiveness, beyond the effects of host-immune function. Whether certain MDR resistant NTS lineages are, in fact, more virulent will need to be confirmed in further study. Our observation of STS313 in diarrhea cases is novel and merits evaluation in a larger group of individuals with NTS diarrhea. Our findings from Aim 2 suggest environmental transmission of typhoid fever in children, but not adults, likely due to more frequent exposure to environmental pathogens. Further investigation is needed to differentiate between possible sources of environmental risk, such as contaminated drinking water versus direct contact with contaminated environmental media like open sewers