HIV transmission dynamics and population-wide drug resistance in rural South Africa

Despite the scale-up of antiretroviral therapy (ART) in South Africa, HIV-1 incidence remains high. The anticipated use of potent integrase strand transfer inhibitors and long-acting injectables aims to enhance viral suppression at the population level and diminish transmission. Nevertheless, pre-existing drug resistance could impede the efficacy of long-acting injectable ART combinations, such as rilpivirine (an NNRTI) and cabotegravir (an INSTI). Consequently, a thorough understanding of transmission networks and geospatial distributions is vital for tailored interventions, including pre-exposure prophylaxis with long-acting injectables. However, empirical data on background resistance and transmission networks remain limited. In a community-based study in rural KwaZulu-Natal (2018-2019), prior to the widespread use of integrase inhibitor-based first-line ART, we performed HIV testing with reflex HIV-1 RNA viral load quantification on 18,025 participants. From this cohort, 6,096 (33.9%) tested positive for HIV via ELISA, with 1,323 (21.7%) exhibiting detectable viral loads (> 40 copies/mL). Of those with detectable viral loads, 62.1% were ART-naïve, and the majority of the treated were on an efavirenz + cytosine analogue + tenofovir regimen. Deep sequencing analysis, with a variant abundance threshold of 20%, revealed NRTI resistance mutations such as M184V in 2% of ART-naïve and 32% of treated individuals. Tenofovir resistance mutations K65R and K70E were found in 12% and 5% of ART-experienced individuals, respectively, and in less than 1% of ART-naïve individuals. Integrase inhibitor resistance mutations were notably infrequent (< 1%). Prevalence of pre-treatment drug resistance to NNRTIs was 10%, predominantly consisting of the K103N mutation. Among those with viraemic ART, NNRTI resistance was 50%, with rilpivirine-associated mutations observed in 9% of treated and 6% of untreated individuals. Cluster analysis revealed that 20% (205/1,050) of those sequenced were part of a cluster. We identified 171 groups with at least two linked participants; three quarters of clusters had only two individuals, and a quarter had 3-6 individuals. Integrating phylogenetic with geospatial analyses, we revealed a complex transmission network with significant clustering in specific regions, notably peripheral and rural areas. These findings derived from population scale genomic analyses are encouraging in terms of the limited resistance to DTG, but indicate that transitioning to long-acting cabotegravir + rilpivirine for transmission reduction should be accompanied by prior screening for rilpivirine resistance. Whole HIV-1 genome sequencing allowed identification of significant proportions of clusters with multiple individuals, and geospatial analyses suggesting decentralised networks can inform targeting public health interventions to effectively curb HIV-1 transmission.

Changes of Grocery Shopping Frequencies and Associations with Food Deserts during the COVID-19 Pandemic in the United States

The COVID-19 pandemic has dramatically altered people's lives in multiple aspects, including grocery shopping behaviors. Yet, the changing trend of grocery shopping frequencies during the COVID-19 and its associations with food deserts remain unclear. We aimed to (1) examine variations of grocery shopping frequencies at county level in the USA during the COVID-19 pandemic from March 2020 to December 2021; (2) investigate associations between grocery shopping frequencies and food deserts during the COVID-19 pandemic; and (3) explore heterogeneity in grocery shopping frequencies-food desert associations across urban and rural areas. The county-level grocery shopping frequencies were derived from a grocery pattern dataset obtained from SafeGraph. We divided the 22-month period into 5 stages and employed the growth curve modeling to estimate the trajectories of grocery shopping frequencies and the associations between grocery shopping frequencies and food deserts in each stage, separately. Results revealed that grocery shopping frequencies experienced a "W-shaped" pattern from March 2020 to December 2021. Counties with the least percent of food deserts had slower decrease in grocery shopping frequencies at the initial stage and recovered more rapidly at later stages. Counties with the highest percent of food deserts were subject to deprivation amplification as a result of the pandemic. We also found differences existed in the grocery shopping frequencies-food desert associations between metropolitan counties and rural counties. Our findings suggest the impacts of COVID-19 on grocery shopping frequencies varied across different time periods, shedding light on designing different strategies to reduce the risk of contagion while shopping inside of grocery stores. Further, our findings highlight an urgent need to help people living in food deserts (especially in rural counties) to procure healthy foods safely during health emergencies like COVID-19 pandemic which disrupt mobility and social behaviors.

The met and unmet health needs for HIV, hypertension, and diabetes in rural KwaZulu-Natal, South Africa: analysis of a cross-sectional multimorbidity survey

BACKGROUND

The convergence of infectious diseases and non-communicable diseases in South Africa is challenging to health systems. In this analysis, we assessed the multimorbidity health needs of individuals and communities in rural KwaZulu-Natal and established a framework to quantify met and unmet health needs for individuals living with infectious and non-communicable diseases.

METHODS

We analysed data collected between May 25, 2018, and March 13, 2020, from participants of a large, community-based, cross-sectional multimorbidity survey (Vukuzazi) that offered community-based HIV, hypertension, and diabetes screening to all residents aged 15 years or older in a surveillance area in the uMkhanyakude district in KwaZulu-Natal, South Africa. Data from the Vukuzazi survey were linked with data from demographic and health surveillance surveys with a unique identifier common to both studies. Questionnaires were used to assess the diagnosed health conditions, treatment history, general health, and sociodemographic characteristics of an individual. For each condition (ie, HIV, hypertension, and diabetes), individuals were defined as having no health needs (absence of condition), met health needs (condition that is well controlled), or one or more unmet health needs (including diagnosis, engagement in care, or treatment optimisation). We analysed met and unmet health needs for individual and combined conditions and investigated their geospatial distribution.

FINDINGS

Of 18 041 participants who completed the survey (12 229 [67·8%] were female and 5812 [32·2%] were male), 9898 (54·9%) had at least one of the three chronic diseases measured. 4942 (49·9%) of these 9898 individuals had at least one unmet health need (1802 [18·2%] of 9898 needed treatment optimisation, 1282 [13·0%] needed engagement in care, and 1858 [18·8%] needed a diagnosis). Unmet health needs varied by disease; 1617 (93·1%) of 1737 people who screened positive for diabetes, 2681 (58·2%) of 4603 people who screened positive for hypertension, and 1321 (21·7%) of 6096 people who screened positive for HIV had unmet health needs. Geospatially, met health needs for HIV were widely distributed and unmet health needs for all three conditions had specific sites of concentration; all three conditions had an overlapping geographical pattern for the need for diagnosis.

INTERPRETATION

Although people living with HIV predominantly have a well controlled condition, there is a high burden of unmet health needs for people living with hypertension and diabetes. In South Africa, adapting current, widely available HIV care services to integrate non-communicable disease care is of high priority.

FUNDING

Fogarty International Center and the National Institutes of Health, the Bill & Melinda Gates Foundation, the South African Department of Science and Innovation, the South African Medical Research Council, the South African Population Research Infrastructure Network, and the Wellcome Trust.

TRANSLATION

For the isiZulu translation of the abstract see Supplementary Materials section.

Quantifying met and unmet health needs for HIV, hypertension and diabetes in rural KwaZulu-Natal, South Africa

The convergence of infectious and non-communicable diseases (NCDs) in South Africa poses a challenge to health systems. Here we establish a framework to quantify met and unmet health needs for individuals living with infectious and NCDs. In this study, we screened adult residents >15 years of age within the uMkhanyakude district in KwaZulu- Natal, South Africa for HIV, hypertension (HPTN) and diabetes mellitus (DM). For each condition, individuals were defined as having no unmet health needs (absence of condition), met health need (condition that is well controlled), or one or more unmet health needs (including diagnosis, engagement in care, or treatment optimization). We analyzed met and unmet health needs for individual and combined conditions and investigated their geospatial distribution. We found that of 18,041 participants, 9,898 (55%) had at least one chronic condition. 4,942 (50%) of these individuals had at least one unmet health need (18% needed treatment optimization, 13% needed engagement in care, and 19% needed diagnosis). Unmet health needs varied by disease: 93% of people with DM, 58% of people with HPTN and 21% of people with HIV had unmet health needs. Geospatially, met health needs for HIV were widely distributed, unmet health needs had specific sites of concentration whilst the need for diagnosis for all three conditions was co-located. Whilst people living with HIV are predominantly well-controlled, there is a high burden of unmet health needs for people living with HPTN and DM. Adaptation of HIV models of care to integrate HIV and NCD services is of high priority.

Predicting the Risk of Hiv-1 Acquisition in Rural South Africa Using Geospatial Data

Background

Accurate human immunodeficiency virus (HIV) risk assessment can guide optimal HIV prevention. We evaluated the performance of risk prediction models incorporating geospatial measures.

Methods

We developed and validated HIV risk prediction models in a population-based cohort in South Africa. Individual-level covariates included demographic and sexual behavior measures, and geospatial covariates included community HIV prevalence and viral load estimates. We trained models on 2012–2015 data using LASSO Cox models and validated predictions in 2016–2019 data. We compared full models to simpler models restricted to only individual-level covariates or only age and geospatial covariates. We compared the spatial distribution of predicted risk to that of high incidence areas (≥ 3/100 person-years).

Results

Our analysis included 19 556 individuals contributing 44 871 person-years and 1308 seroconversions. Incidence among the highest predicted risk quintile using the full model was 6.6/100 person-years (women) and 2.8/100 person-years (men). Models using only age group and geospatial covariates had similar performance (women: AUROC = 0.65, men: AUROC = 0.71) to the full models (women: AUROC = 0.68, men: AUROC = 0.72). Geospatial models more accurately identified high incidence regions than individual-level models; 20% of the study area with the highest predicted risk accounted for 60% of the high incidence areas when using geospatial models but only 13% using models with only individual-level covariates.

Conclusions

Geospatial models with no individual measures other than age group predicted HIV risk nearly as well as models that included detailed behavioral data. Geospatial models may help guide HIV prevention efforts to individuals and geographic areas at highest risk.

HIV status, knowledge and prevention of cervical cancer amongst adolescent girls and women: a secondary data analysis

Introduction

the objective of this manuscript was to describe the knowledge profiles and determinants of cervical cancer screening among HIV positive and negative adolescent girls and women in Zimbabwe.

Methods

we conducted secondary statistical data analysis to explore the determinants of cervical cancer screening among HIV positive and negative adolescent girls and women using Zimbabwe Demographic Health survey for 2015-16.

Results

a total of 9054 adolescent girls aged 15-19, and women aged 20-49 were included in the analysis and the majority (63%) of them resided in rural areas. More than two-thirds (65.9%) had attained secondary level of education. The majority (41.3%) of the adolescent girls and women belonged to the Apostolic sect. A number of key determinants have been identified for being ever screened for cervical cancer. The odds of being ever being screened increased by age, OR(CI) 4.38 (3.22-5.94), p<0.001 for women who are 40 years and older when compared to adolescent and young woman who are between 15-24 years.

Conclusion

our study reports significant programmatic gaps in the provision of cervical cancer screening and treatment services in the country. The nascent Zimbabwe cervical cancer screening and treatment progamme will benefit from expansion of the number of facilities offering the services and the provision of more efficient health education to adolescent women and girls.

The geography and inter-community configuration of new sexual partnership formation in a rural South African population over fourteen years (2003-2016)

Understanding spatial configuration of sexual network structure is critical for effective use of HIV preventative interventions in a community. However, this has never been described at the population level for any setting in sub-Saharan Africa. We constructed the comprehensive geospatial sexual network among new heterosexual partnerships in rural KwaZulu-Natal, South Africa. In the Africa Health Research Institute (AHRI)'s population-based surveillance, we identified stable sexual partnerships among individuals (≥15 years) from 2003 to 2016. Sexual partnerships and residency were recorded via household surveys (every 4-6 months). We geolocated residents and migration events and mapped the geospatial linkages of sexual partners at the start of sexual partnerships. In a grid composed by 108 cells (nodes; 3kmx3km per cell) covering the surveillance area (438km2), we calculated the degree of connectivity and centrality of the nodes and examined their association with HIV prevalence and incidence per cell. Of 2401 new sexual partnerships, 21% (n = 495) had both partners living within the surveillance area at the start of sexual partnerships, and 76% (376/495) were linked to the geographic HIV cluster with high HIV prevalence identified in a peri-urban community. Overall, 57 nodes had at least one connection to another node. The nodes in the peri-urban cluster had higher connectivity (mean = 19, range: 9-32), compared to outside the cluster (6, range: 1-16). The node's degree of connectivity was positively associated with HIV prevalence of the cell (Pearson correlation coefficient = 0.67; p <0.005). The peri-urban cluster contained nine of the 10 nodes that composed of a single large central module in the community. About 17% of sexual partnerships (n = 421) were formed between a resident and a non-resident partner who out-migrated. Most of these non-resident partners lived in KwaZulu-Natal (86.7%), followed by Gauteng (9.7%), and the median distance between a resident and a non-resident partner was 50.1km (IQR: 23.2-177.2). We found that the peri-urban HIV cluster served as the highly connected central node of the network for sexual partnership formation. The network was also connected beyond the surveillance area across South Africa. Understanding spatial sexual network can improve the provision of spatially targeted and effective interventions.

Optimising COVID-19 Vaccination Policy to Mitigate SARS-CoV-2 Transmission within Schools in Zimbabwe

The COVID-19 pandemic has disrupted the learning of millions of children across the world. Since March 2020 when the first cases of COVID-19 were reported in Zimbabwe, the country, like many others, has gone through periods of closing and re-opening of schools as part of the national COVID-19 control and mitigation measures. Schools promote the social, mental, physical, and moral development of children. With this viewpoint, the authors argue that schools should not be closed to provide a measured and efficient response to the threats posed by the COVID-19 epidemic. Rather, infection prevention and control strategies, including vaccination of learners and teachers, and surveillance in schools should be heightened. The use of multiple prevention strategies discussed in this viewpoint has shown that when outbreaks in school settings are adequately managed, the transmission usually is low. The information presented here suggests that schools should remain open due to the preponderance of evidence indicating the overriding positive impacts of this policy on the health, development, and wellbeing of children.

Associations of diarrhea episodes and seeking medical treatment among children under five years: Insights from the Zimbabwe Demographic Health Survey (2015-2016)

Diarrhea is a significant pediatric public health concern globally and places a significant burden on healthcare systems. In resource-limited settings, the problems of diarrhea could be worse than reported. Continuously monitoring and understanding the changing epidemiology of diarrhea, including risk factors, remain an important aspect necessary to design effective public health interventions to reduce the incidence, outcomes and strain on healthcare resources caused by diarrheal illness. We, therefore, undertook this study to understand the factors associated with diarrhea as well as describe determinants for seeking medical treatment in children under-five in Zimbabwe using the Zimbabwe Demographic and Health Survey 2015-2016 Data. Children with recent diarrhea were on average younger (mean age 22 months), compared to those who did not have an episode of diarrhea (mean age 30 months) p = .001. Incidence of recent diarrhea was lower among female children compared to their male counterparts (16% vs. 19%), p = .013. Incidence of diarrhea decreased with increasing maternal education level and so was the same for increasing wealth quintile. Those with unimproved sources of drinking water had a higher incidence of diarrhea. The wealth quintile remained the only factor associated with seeking medical attention for a recent diarrhea episode among children less than 6 years, with those in the highest wealth quintile being 2.49 times likely to do so, p = .031. The results are useful in informing pediatric public health policies and strategies for them to be successful in significantly reducing the incidence, morbidity, mortality and significant healthcare costs and burden to society associated with caring for children with diarrheal illnesses.

A year of genomic surveillance reveals how the SARS-CoV-2 pandemic unfolded in Africa

The progression of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in Africa has so far been heterogeneous, and the full impact is not yet well understood. In this study, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations predominantly from Europe, which diminished after the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1, and C.1.1. Although distorted by low sampling numbers and blind spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a source for new variants.

Convergence of infectious and non-communicable disease epidemics in rural South Africa: a cross-sectional, population-based multimorbidity study

BACKGROUND

There has been remarkable progress in the treatment of HIV throughout sub-Saharan Africa, but there are few data on the prevalence and overlap of other significant causes of disease in HIV endemic populations. Our aim was to identify the prevalence and overlap of infectious and non-communicable diseases in such a population in rural South Africa.

METHODS

We did a cross-sectional study of eligible adolescents and adults from the Africa Health Research Institute demographic surveillance area in the uMkhanyakude district of KwaZulu-Natal, South Africa. The participants, who were 15 years or older, were invited to participate at a mobile health camp. Medical history for HIV, tuberculosis, hypertension, and diabetes was established through a questionnaire. Blood pressure measurements, chest x-rays, and tests of blood and sputum were taken to estimate the population prevalence and geospatial distribution of HIV, active and lifetime tuberculosis, elevated blood glucose, elevated blood pressure, and combinations of these.

FINDINGS

17 118 adolescents and adults were recruited from May 25, 2018, to Nov 28, 2019, and assessed. Overall, 52·1% (95% CI 51·3-52·9) had at least one active disease. 34·2% (33·5-34·9) had HIV, 1·4% (1·2-1·6) had active tuberculosis, 21·8% (21·2-22·4) had lifetime tuberculosis, 8·5% (8·1-8·9) had elevated blood glucose, and 23·0% (22·4-23·6) had elevated blood pressure. Appropriate treatment and optimal disease control was highest for HIV (78·1%), and lower for elevated blood pressure (42·5%), active tuberculosis (29·6%), and elevated blood glucose (7·1%). Disease prevalence differed notably by sex, across age groups, and geospatially: men had a higher prevalence of active and lifetime tuberculosis, whereas women had a substantially high prevalence of HIV at 30-49 years and an increasing prevalence of multiple and poorly controlled non-communicable diseases when older than 50 years.

INTERPRETATION

We found a convergence of infectious and non-communicable disease epidemics in a rural South African population, with HIV well treated relative to all other diseases, but tuberculosis, elevated blood glucose, and elevated blood pressure poorly diagnosed and treated. A public health response that expands the successes of the HIV testing and treatment programme to provide multidisease care targeted to specific populations is required to optimise health in such settings in sub-Saharan Africa.

FUNDING

Wellcome Trust, Bill & Melinda Gates Foundation, the South African Department of Science and Innovation, South African Medical Research Council, and South African Population Research Infrastructure Network.

TRANSLATION

For the isiZulu translation of the abstract see Supplementary Materials section.

Understanding HIV and associated risk factors among religious groups in Zimbabwe

BACKGROUND

The influence of religion and belief systems is widely recognized as an important factor in understanding of health risk perception and myths in the general fight against the HIV pandemic. This study compares the understanding of HIV risk factors and utilization of some HIV services among religious groups in Zimbabwe.

METHODS

We conducted secondary data statistical analysis to investigate the understanding of HIV and associated risk factors among religious groups in Zimbabwe using 2015-2016 Zimbabwe Demographic and Health Survey (ZDHS) data. We began by investigating associations between understanding of HIV and associated risk factors among religious groups. A multivariate stepwise backward elimination method was carried out to explore factors determining understanding of HIV risk after controlling for confounding factors using the most recent ZDHS data (2015-2016).

RESULTS

The results from the three surveys showed that, in general apostolic sector had low understanding of HIV and associated risk factors compared to other religious groups. Analysis of the 2015-2016 ZDHS data showed that women belonging to the apostolic sector were less likely to know where to get an HIV test odds ratio (OR) and 95% confidence interval, 0.665 (0.503-0.880) and to know that male circumcision reduces HIV transmission OR 0.863 (0.781-0.955). Women from this group had no knowledge that circumcised men can be infected if they do not use condoms OR 0.633 (0.579-0.693), nor that it is possible for a healthy-looking person to have HIV, OR 0.814 (0.719-0.921). They would not buy vegetables from a vendor with HIV OR 0.817 (0.729-0.915) and were less likely to support that HIV positive children should be allowed to attend school with HIV negative children OR 0.804 (0.680-0.950). Similar results were obtained for men in the apostolic sector. These men also did not agree that women were justified to use condoms if the husband has an Sexually Transmitted Infection (STI) OR 0.851 (0.748-0.967).

CONCLUSIONS

Our results suggest that apostolic sector lack adequate knowledge of HIV and associated risk factors than other religious groups. Targeting HIV prevention programmes by religious groups could be an efficient approach for controlling HIV in Zimbabwe.

Safeguarding gains in the sexual and reproductive health and AIDS response amidst COVID-19: The role of African civil society

This article outlines the role of African civil society in safeguarding gains registered to date in sexual and reproductive health and the response to HIV. The case is made for why civil society organizations (CSOs) must be engaged vigilantly in the COVID-19 response in Africa. Lockdown disruptions and the rerouting of health funds to the pandemic have impeded access to essential sexual and reproductive health (SRH) and social protection services. Compounded by pre-existing inequalities faced by vulnerable populations, the poor SRH outcomes amid COVID-19 call for CSOs to intensify demand for the accountability of governments. CSOs should also continue to persevere in their aim to rapidly close community-health facility gaps and provide safety nets to mitigate the gendered impact of COVID-19.

HIV incidence declines in a rural South African population: a G-imputation approach for inference

BACKGROUND

Ad hoc assumptions about the unobserved infection event, which is known only to occur between the latest-negative and earliest-positive test dates, can lead to biased HIV incidence rate estimates. Using a G-imputation approach, we infer the infection dates from covariate data to estimate the HIV incidence rate in a hyper-endemic South African setting.

METHODS

A large demographic surveillance system has annually tested a cohort of HIV-uninfected participants living in the KwaZulu-Natal province. Using this data, we estimated a cumulative baseline hazard function and the effects of time-dependent covariates on the interval censored infection dates. For each HIV-positive participant in the cohort, we derived a cumulative distribution function and sampled multiple infection dates conditional on the unique covariate values. We right censored the data at the imputed dates, calculated the annual HIV incidence rate per 100 person-years, and used Rubin's rules to obtain the 95% confidence intervals.

RESULTS

A total of 20,011 uninfected individuals with a repeat HIV test participated in the incidence cohort between 2005 and 2018. We observed 2,603 infections per 58,769 person-years of follow-up among women and 845 infections per 41,178 person-years of follow-up among men. Conditional on age and circumcision status (men only), the female HIV incidence rate declined by 25%, from 5.0 to 3.7 infections per 100 person-years between 2014 and 2018. During this period, the HIV incidence rate among men declined from 2.1 to 1.1 infections per 100 person-years-a reduction of 49%. We observed similar reductions in male and female HIV incidence conditional on condom-use, marital status, urban residential status, migration history, and the HIV prevalence in the surrounding community.

CONCLUSION

We have followed participants in one of the world's largest and longest running HIV cohorts to estimate long-term trends in the population-wide incidence of infection. Using a G-imputation approach, we present further evidence for HIV incidence rate declines in this hyper-endemic South African setting.

The state of the HIV epidemic in rural KwaZulu-Natal, South Africa: a novel application of disease metrics to assess trajectories and highlight areas for intervention

BACKGROUND

South Africa is at the epicentre of the HIV pandemic, with the world's highest number of new infections and the largest treatment programme. Using metrics proposed by the Joint United Nations Programme on AIDS (UNAIDS), we evaluate progress toward epidemic control and highlight areas for intervention in a hyperendemic South African setting.

METHODS

The Africa Health Research Institute (AHRI) maintains a comprehensive population-based surveillance system in the Hlabisa sub-district of KwaZulu-Natal. Between 2005 and 2017, we tested 39 735 participants (aged 15-49 years) for HIV and followed 22 758 HIV-negative and 13 460 HIV-positive participants to identify new infections and all-cause AIDS-related deaths, respectively. Using these data, we estimated the percentage reduction in incidence, the absolute incidence rate, the incidence-mortality ratio and the incidence-prevalence ratio over place and time.

RESULTS

We observed a 62% reduction in the number of new infections among men between 2012 and 2017 and a 34% reduction among women between 2014 and 2017. Among men, the incidence-mortality ratio peaked at 4.1 in 2013 and declined to 3.1 in 2017, and among women it fell from a high of 6.4 in 2014 to 4.3 in 2017. Between 2012 and 2017, the female-incidence/male-prevalence ratio declined from 0.24 to 0.13 and the male-incidence/female-prevalence ratio from 0.05 to 0.02.

CONCLUSIONS

Using data from a population-based cohort study, we report impressive progress toward HIV epidemic control in a severely affected South African setting. However, overall progress is off track for 2020 targets set by the UNAIDS. Spatial estimates of the metrics, which demonstrate remarkable heterogeneity over place and time, indicate areas that could benefit from additional or optimized HIV prevention services.

Impact of community piped water coverage on re-infection with urogenital schistosomiasis in rural South Africa

Previously, we demonstrated that coverage of piped water in the seven years preceding a parasitological survey was strongly predictive of Schistosomiasis haematobium infection in a nested cohort of 1976 primary school children (Tanser, 2018). Here, we report on the prospective follow up of infected members of this nested cohort (N = 333) for two successive rounds following treatment. Using a negative binomial regression fitted to egg count data, we found that every percentage point increase in piped water coverage was associated with 4.4% decline in intensity of re-infection (incidence rate ratio = 0.96, 95% CI: 0.93–0.98, p=0.004) among the treated children. We therefore provide further compelling evidence in support of the scaleup of piped water as an effective control strategy against Schistosoma haematobium transmission.

Estimating trends in the incidence rate with interval censored data and time-dependent covariates

We propose a multiple imputation method for estimating the incidence rate with interval censored data and time-dependent (and/or time-independent) covariates. The method has two stages. First, we use a semi-parametric G-transformation model to estimate the cumulative baseline hazard function and the effects of the time-dependent (and/or time-independent covariates) on the interval censored infection times. Second, we derive the participant's unique cumulative distribution function and impute infection times conditional on the covariate values. To assess performance, we simulated infection times from a Cox proportional hazards model and induced interval censoring by varying the testing rate, e.g., participants test 100%, 75%, 50% of the time, etc. We then compared the incidence rate estimates from our G-imputation approach with single random-point and mid-point imputation. By comparison, our G-imputation approach gave more accurate incidence rate estimates and appropriate standard errors for models with time-independent covariates only, time-dependent covariates only, and a mixture of time-dependent and time-independent covariates across various testing rates. We demonstrate, for the first time, a multiple imputation approach for incidence rate estimation with interval censored data and time-dependent (and/or time-independent) covariates.

Effect of population viral load on prospective HIV incidence in a hyperendemic rural African community

Monitoring HIV population viral load (PVL) has been advocated as an important means of inferring HIV transmission potential and predicting the future rate of new HIV infections (HIV incidence) in a particular community. However, the relationship between PVL measures and directly measured HIV incidence has not been quantified in any setting and, most importantly, in a hyperendemic sub-Saharan African setting. We assessed this relationship using one of Africa's largest population-based prospective population cohorts in rural KwaZulu-Natal, South Africa in which we followed 8732 HIV-uninfected participants between 2011 and 2015. Despite clear evidence of spatial clustering of high viral loads in some communities, our results demonstrate that PVL metrics derived from aggregation of viral load data only from the HIV-positive members of a particular community did not predict HIV incidence in this typical hyperendemic, rural African population. Only once we used modified PVL measures, which combined viral load information with the underlying spatial variation in the proportion of the population infected (HIV prevalence), did we find a consistently strong relationship with future risk of HIV acquisition. For example, every 1% increase in the overall proportion of a population having detectable virus (PDV _P ) was independently associated with a 6.3% increase in an individual's risk of HIV acquisition (P = 0.001). In hyperendemic African populations, these modified PVL indices could play a key role in targeting and monitoring interventions in the most vulnerable communities where the future rate of new HIV infections is likely to be highest.

Proximity to healthcare clinic and depression risk in South Africa: geospatial evidence from a nationally representative longitudinal study

Proximity to primary healthcare facilities may be a serious barrier to accessing mental health services in resource-limited settings. In this study, we examined whether the distance to the primary healthcare clinic (PHCC) was associated with risk of depression in KwaZulu-Natal Province, South Africa. Depressive symptoms and household coordinates data were accessed from the nationally representative South African National Income Dynamics Study. Distances between households and their nearest PHCCs were calculated and mixed-effects logistic regression models fitted to the data. Participants residing <6 km from a PHCC (aOR = 0.608, 95% CI 0.42-0.87) or 6-14.9 km (aOR = 0. 612, 95% CI 0.44-0.86) had a lower depression risk compared to those residing ≥15 km from the nearest PHCC. Distance to the PHCC was independently associated with increased depression risk, even after controlling for key socioeconomic determinants. Minimizing the distance to PHCC through mobile health clinics and technology could improve mental health.

Green environment and incident depression in South Africa: a geospatial analysis and mental health implications in a resource-limited setting

BACKGROUND

Unprecedented levels of habitat transformation and rapid urbanisation are changing the way individuals interrelate with the natural environment in developing countries with high economic disparities. Although the potential benefit of green environments for mental health has been recognised, population-level evidence to this effect is scarce. We investigated the effect of green living environment in potentially countering incident depression in a nationally representative survey in South Africa.

METHODS

We used panel data from the South African National Income Dynamics Study (SA-NIDS). Our study used SA-NIDS data from three waves: wave 1 (2008), wave 2 (2010), and wave 3 (2012). Households were sampled on the basis of a stratified two-stage cluster design. In the first stage, 400 primary sampling units were selected for inclusion. In the second stage, two clusters of 12 dwelling units each were drawn from within each primary sampling unit (or 24 dwelling units per unit). Household and individual adult questionnaires were administered to participants. The main outcome, incident depression (ie, incident cohort of 11 156 study participants without significant depression symptoms at their first entry into SA-NIDS), was assessed in the adult survey via a ten item version of the Center for Epidemiologic Studies Depression Scale; a total score of ten or higher was used as a cutoff to indicate significant depressive symptoms. Each participant was assigned a value for green living space via a satellite-derived normalised difference vegetation index (NDVI) based on the GPS coordinates of their household location.

FINDINGS

Overall, we found uneven benefit of NDVI on incident depression among our study participants. Although the green living environment showed limited benefit across the study population as a whole, our final analysis based on logistic regression models showed that higher NDVI was a predictor of lower incident depression among middle-income compared with low-income participants (adjusted odds ratio [aOR] 0·98, 0·97-0·99, p<0·0001), although when this analysis was broken down by race, its positive effect was particularly evident amongst African individuals. Living in rural areas was linked to lower odds of incident depression (aOR 0·71, 0·55-0·92, p=0·011) compared with study participants residing in urban informal areas that often lack formal planning.

INTERPRETATION

Our results imply the importance of green environments for mental wellbeing in sub-Saharan African settings experiencing rapid urbanisation, economic and epidemiological transition, reaffirming the need to incorporate environmental services and benefits for sustainable socioeconomic development.

FUNDING

South African Medical Research Council, National Institutes of Health, and Academy of Finland.