Syndemics of intimate partner violence among women in HIV endemic South Africa: geospatial analysis of nationally representative data

This is the final version. Available from Nature Research via the DOI in this record. Despite some improvement in lowering HIV incidence, HIV-related challenges, such as intimate partner violence (IPV), remain unacceptably high among women in South Africa. For decades, researchers and activists have pointed to the complex and intertwined reality of the substance abuse, violence and AIDS (SAVA) syndemic that endangers women. However, more recent systematic review/meta-analysis evidence points to inconclusive association between IPV and alcohol use. Furthermore, much of the evidence is often non-population-based that focuses on the co-occurrence rather than synergistic SAVA interaction. In this study, using the latest data from the South Africa Demographic and Health Survey (SA-DHS), we identified geographic synergistic clustering of IPV associated with HIV and substance abuse in South Africa as a measure of population-level interactions among these factors. The SA-DHS is a nationally representative sample that includes wide-ranging data on health, social challenges and household geo-locations of 5,874 women who participated in the domestic violence module. First, geographical IPV, harmful alcohol use (as the substance abuse measure available in SA-DHS) and HIV clusters were identified using the Kulldorff spatial scan statistic in SaTScan. Second, synergistic interactions related to recent IPV (i.e. recent physical, sexual, emotional violence during the last 12 months) with harmful alcohol use and HIV challenge were measured using RERI [Relative excess risk due to interaction], AP [attributable proportion] and S [Synergy index]. In our results, we spatially identified geographical physical IPV syndemic interactions in parts of the Eastern Cape/Free State Provinces (RERI = 4.42 [95% CI: 2.34–6.51], AP = 0.56 [95% CI: 0.44–0.68], S = 2.77 [95% CI: 2.01–3.84], but not in other forms of IPV. Although IPV, based on decade old concept of SAVA syndemic, was less common/widespread than expected from the national scale population-based data, we identified population-level physical violence syndemic occurring in South Africa. Our study highlights the need to prioritize public health response targeting vulnerable populations residing in these high-risk areas of syndemic mechanisms linking these synergistic epidemics that women face in South Africa.UK Global Challenge Research Fun

Spatial clustering of codeine use and its association with depression: a geospatial analysis of nationally representative South African data

This is the final version. Available on open access from Elsevier via the DOI in this recordBackground There is an alarming trend in sub-Saharan Africa in the use of codeine-containing pharmaceuticals, but its risk of common comorbidities, such as mental health, remains unquantified at a national-level. We investigated the relationship between codeine use and onset of depression in South Africa at a population-level. Methods We used nationally representative panel data from the South Africa National Income Dynamic Study to investigate the relationship between exposure to codeine use in the community (i.e. residing in a codeine hotspot) and onset of depression. Geographical hotspots of codeine use were identified using Kulldorff spatial scan statistic in SaTScan. We quantified depression onset at Wave 5 (year 2017) between individuals residing inside and outside a codeine hotspot who were depression-free at enrolment (Wave 4: 2015) using generalised estimating equation (GEE) regression models. Results We identified four statistically significant hotspots of codeine use, mostly located at the northern part of the country. Among 13,020 participants who were depression-free at enrolment, residing within a codeine use hotspot was significantly associated with higher subsequent onset of depression (aRR=1.21, 95% CI:1.08-1.44). Limitations Data on diagnosis of depressive disorder were not available. Conclusion South Africa, a resource scarce nation with chronically limited mental health services, is not spared from the global opioid epidemic and its impact on depression. Targeted scale-up access to agonist therapy to effectively treat (opioid) addiction in communities at risk for high exposure to codeine use could reduce the risk of subsequent mental health challenges

No Evidence of Association between HIV-1 and Malaria in Populations with Low HIV-1 Prevalence

The geographic overlap between HIV-1 and malaria has generated much interest in their potential interactions. A variety of studies have evidenced a complex HIV-malaria interaction within individuals and populations that may have dramatic effects, but the causes and implications of this co-infection at the population level are still unclear. In a previous publication, we showed that the prevalence of malaria caused by the parasite Plasmodium falciparum is associated with HIV infection in eastern sub-Saharan Africa. To complement our knowledge of the HIV-malaria co-infection, the objective of this work was to assess the relationship between malaria and HIV prevalence in the western region of sub-Saharan Africa.Population-based cross-sectional data were obtained from the HIV/AIDS Demographic and Health Surveys conducted in Burkina Faso, Ghana, Guinea, Mali, Liberia and Cameroon, and the malaria atlas project. Using generalized linear mixed models, we assessed the relationship between HIV-1 and Plasmodium falciparum parasite rate (PfPR) adjusting for important socio-economic and biological cofactors. We found no evidence that individuals living in areas with stable malaria transmission (PfPR>0.46) have higher odds of being HIV-positive than individuals who live in areas with PfPR≤0.46 in western sub-Saharan Africa (estimated odds ratio 1.14, 95% confidence interval 0.86-1.50). In contrast, the results suggested that PfPR was associated with being infected with HIV in Cameroon (estimated odds ratio 1.56, 95% confidence interval 1.23-2.00).Contrary to our previous research on eastern sub-Saharan Africa, this study did not identify an association between PfPR and infection with HIV in western sub-Saharan Africa, which suggests that malaria might not play an important role in the spread of HIV in populations where the HIV prevalence is low. Our work highlights the importance of understanding the epidemiologic effect of co-infection and the relevant factors involved in this relationship for the implementation of effective control strategies

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 the Joint United Nations Programme on HIV/AIDS 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: internal validation, whereby a proportion of input data is held back (test dataset) to challenge predictions; and 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

Variable effect of co-infection on the HIV infectivity: Within-host dynamics and epidemiological significance

<p>Abstract</p> <p>Background</p> <p>Recent studies have implicated viral characteristics in accounting for the variation in the HIV set-point viral load (spVL) observed among individuals. These studies have suggested that the spVL might be a heritable factor. The spVL, however, is not in an absolute equilibrium state; it is frequently perturbed by immune activations generated by co-infections, resulting in a significant amplification of the HIV viral load (VL). Here, we postulated that if the HIV replication capacity were an important determinant of the spVL, it would also determine the effect of co-infection on the VL. Then, we hypothesized that viral factors contribute to the variation of the effect of co-infection and introduce variation among individuals.</p> <p>Methods</p> <p>We developed a within-host deterministic differential equation model to describe the dynamics of HIV and malaria infections, and evaluated the effect of variations in the viral replicative capacity on the VL burden generated by co-infection. These variations were then evaluated at population level by implementing a between-host model in which the relationship between VL and the probability of HIV transmission per sexual contact was used as the within-host and between-host interface.</p> <p>Results</p> <p>Our within-host results indicated that the combination of parameters generating low spVL were unable to produce a substantial increase in the VL in response to co-infection. Conversely, larger spVL were associated with substantially larger increments in the VL. In accordance, the between-host model indicated that co-infection had a negligible impact in populations where the virus had low replicative capacity, reflected in low spVL. Similarly, the impact of co-infection increased as the spVL of the population increased.</p> <p>Conclusion</p> <p>Our results indicated that variations in the viral replicative capacity would influence the effect of co-infection on the VL. Therefore, viral factors could play an important role driving several virus-related processes such as the increment of the VL induced by co-infections. These results raise the possibility that biological differences could alter the effect of co-infection and underscore the importance of identifying these factors for the implementation of control interventions focused on co-infection.</p

Bi-galileon theory II: phenomenology

We continue to introduce bi-galileon theory, the generalisation of the single galileon model introduced by Nicolis et al. The theory contains two coupled scalar fields and is described by a Lagrangian that is invariant under Galilean shifts in those fields. This paper is the second of two, and focuses on the phenomenology of the theory. We are particularly interesting in models that admit solutions that are asymptotically self accelerating or asymptotically self tuning. In contrast to the single galileon theories, we find examples of self accelerating models that are simultaneously free from ghosts, tachyons and tadpoles, able to pass solar system constraints through Vainshtein screening, and do not suffer from problems with superluminality, Cerenkov emission or strong coupling. We also find self tuning models and discuss how Weinberg's no go theorem is evaded by breaking Poincar\'e invariance in the scalar sector. Whereas the galileon description is valid all the way down to solar system scales for the self-accelerating models, unfortunately the same cannot be said for self tuning models owing to the scalars backreacting strongly on to the geometry

Effect of variable transmission rate on the dynamics of HIV in sub-Saharan Africa

<p>Abstract</p> <p>Background</p> <p>The cause of the high HIV prevalence in sub-Saharan Africa is incompletely understood, with heterosexual penile-vaginal transmission proposed as the main mechanism. Heterosexual HIV transmission has been estimated to have a very low probability; but effects of cofactors that vary in space and time may substantially alter this pattern.</p> <p>Methods</p> <p>To test the effect of individual variation in the HIV infectiousness generated by co-infection, we developed and analyzed a mathematical sexual network model that simulates the behavioral components of a population from Malawi, as well as the dynamics of HIV and the co-infection effect caused by other infectious diseases, including herpes simplex virus type-2, gonorrhea, syphilis and malaria.</p> <p>Results</p> <p>The analysis shows that without the amplification effect caused by co-infection, no epidemic is generated, and HIV prevalence decreases to extinction. But the model indicates that an epidemic can be generated by the amplification effect on HIV transmission caused by co-infection.</p> <p>Conclusion</p> <p>The simulated sexual network demonstrated that a single value for HIV infectivity fails to describe the dynamics of the epidemic. Regardless of the low probability of heterosexual transmission per sexual contact, the inclusion of individual variation generated by transient but repeated increases in HIV viral load associated with co-infections may provide a biological basis for the accelerated spread of HIV in sub-Saharan Africa. Moreover, our work raises the possibility that the natural history of HIV in sub-Saharan Africa cannot be fully understood if individual variation in infectiousness is neglected.</p

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Geographic variation and associated covariates of diabetes prevalence in India

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