The Kanyakla study: Randomized controlled trial of a microclinic social network intervention for promoting engagement and retention in HIV care in rural western Kenya

BACKGROUND: Existing social relationships are a potential source of social capital that can enhance support for sustained retention in HIV care. A previous pilot study of a social network-based \u27microclinic\u27 intervention, including group health education and facilitated HIV status disclosure, reduced disengagement from HIV care. We conducted a pragmatic randomized trial to evaluate microclinic effectiveness. METHODS: In nine rural health facilities in western Kenya, we randomized HIV-positive adults with a recent missed clinic visit to either participation in a microclinic or usual care (NCT02474992). We collected visit data at all clinics where participants accessed care and evaluated intervention effect on disengagement from care (≥90-day absence from care after a missed visit) and the proportion of time patients were adherent to clinic visits (\u27time-in-care\u27). We also evaluated changes in social support, HIV status disclosure, and HIV-associated stigma. RESULTS: Of 350 eligible patients, 304 (87%) enrolled, with 154 randomized to intervention and 150 to control. Over one year of follow-up, disengagement from care was similar in intervention and control (18% vs 17%, hazard ratio 1.03, 95% CI 0.61-1.75), as was time-in-care (risk difference -2.8%, 95% CI -10.0% to +4.5%). The intervention improved social support for attending clinic appointments (+0.4 units on 5-point scale, 95% CI 0.08-0.63), HIV status disclosure to close social supports (+0.3 persons, 95% CI 0.2-0.5), and reduced stigma (-0.3 units on 5-point scale, 95% CI -0.40 to -0.17). CONCLUSIONS: The data from our pragmatic randomized trial in rural western Kenya are compatible with the null hypothesis of no difference in HIV care engagement between those who participated in a microclinic intervention and those who did not, despite improvements in proposed intervention mechanisms of action. However, some benefit or harm cannot be ruled out because the confidence intervals were wide. Results differ from a prior quasi-experimental pilot study, highlighting important implementation considerations when evaluating complex social interventions for HIV care. TRIAL REGISTRATION: Clinical trial number: NCT02474992

Genotype imputation for the prediction of genomic breeding values in non-genotyped and low-density genotyped individuals

<p>Abstract</p> <p>Background</p> <p>There is wide interest in calculating genomic breeding values (GEBVs) in livestock using dense, genome-wide SNP data. The general framework for genomic selection assumes all individuals are genotyped at high-density, which may not be true in practice. Methods to add additional genotypes for individuals not genotyped at high density have the potential to increase GEBV accuracy with little or no additional cost. In this study a long haplotype library was created using a long range phasing algorithm and used in combination with segregation analysis to impute dense genotypes for non-genotyped dams in the training dataset (S1) and for non-genotyped or low-density genotyped individuals in the prediction dataset (S2), using the 14^th QTL-MAS Workshop dataset. Alternative low-density scenarios were evaluated for accuracy of imputed genotypes and prediction of GEBVs.</p> <p>Results</p> <p>In S1, females in the training population were not genotyped and prediction individuals were either not genotyped or genotyped at low-density (evenly spaced at 2, 5 or 10 Mb). The proportion of correctly imputed genotypes for training females did not change when genotypes were added for individuals in the prediction set whereas the number of correctly imputed genotypes in the prediction set increased slightly (S1). The S2 scenario assumed the complete training set was genotyped for all SNPs and the prediction set was not genotyped or genotyped at low-density. The number of correctly imputed genotypes increased with genotyping density in the prediction set. Accuracy of genomic breeding values for the prediction set in each scenario were the correlation of GEBVs with true breeding values and were used to evaluate the potential loss in accuracy with reduced genotyping. For both S1 and S2 the GEBV accuracies were similar when the prediction set was not genotyped and increased with the addition of low-density genotypes, with the increase larger for S2 than S1.</p> <p>Conclusions</p> <p>Genotype imputation using a long haplotype library and segregation analysis is promising for application in sparsely-genotyped pedigrees. The results of this study suggest that dense genotypes can be imputed for selection candidates with some loss in genomic breeding value accuracy, but with levels of accuracy higher than traditional BLUP estimated breeding values. Accurate genotype imputation would allow for a single low-density SNP panel to be used across traits.</p

Potential of genotyping-by-sequencing for genomic selection in livestock populations

International audienceBackground Next-generation sequencing techniques, such as genotyping-by-sequencing (GBS), provide alternatives to single nucleotide polymorphism (SNP) arrays. The aim of this work was to evaluate the potential of GBS compared to SNP array genotyping for genomic selection in livestock populations.MethodsThe value of GBS was quantified by simulation analyses in which three parameters were varied: (i) genome-wide sequence read depth (x) per individual from 0.01x to 20x or using SNP array genotyping; (ii) number of genotyped markers from 3000 to 300 000; and (iii) size of training and prediction sets from 500 to 50 000 individuals. The latter was achieved by distributing the total available x of 1000x, 5000x, or 10 000x per genotyped locus among the varying number of individuals. With SNP arrays, genotypes were called from sequence data directly. With GBS, genotypes were called from sequence reads that varied between loci and individuals according to a Poisson distribution with mean equal to x. Simulated data were analyzed with ridge regression and the accuracy and bias of genomic predictions and response to selection were quantified under the different scenarios.ResultsAccuracies of genomic predictions using GBS data or SNP array data were comparable when large numbers of markers were used and x per individual was ~1x or higher. The bias of genomic predictions was very high at a very low x. When the total available x was distributed among the training individuals, the accuracy of prediction was maximized when a large number of individuals was used that had GBS data with low x for a large number of markers. Similarly, response to selection was maximized under the same conditions due to increasing both accuracy and selection intensity.ConclusionsGBS offers great potential for developing genomic selection in livestock populations because it makes it possible to cover large fractions of the genome and to vary the sequence read depth per individual. Thus, the accuracy of predictions is improved by increasing the size of training populations and the intensity of selection is increased by genotyping a larger number of selection candidates

Effect of a patient-centered hypertension delivery strategy on all-cause mortality: Secondary analysis of SEARCH, a community-randomized trial in rural Kenya and Uganda

Background Hypertension treatment reduces morbidity and mortality yet has not been broadly implemented in many low-resource settings, including sub-Saharan Africa (SSA). We hypothesized that a patient-centered integrated chronic disease model that included hypertension treatment and leveraged the HIV care system would reduce mortality among adults with uncontrolled hypertension in rural Kenya and Uganda. Methods and findings This is a secondary analysis of the SEARCH trial (NCT:01864603), in which 32 communities underwent baseline population-based multidisease testing, including hypertension screening, and were randomized to standard country-guided treatment or to a patient-centered integrated chronic care model including treatment for hypertension, diabetes, and HIV. Patient-centered care included on-site introduction to clinic staff at screening, nursing triage to expedite visits, reduced visit frequency, flexible clinic hours, and a welcoming clinic environment. The analytic population included nonpregnant adults (≥18 years) with baseline uncontrolled hypertension (blood pressure ≥140/90 mm Hg). The primary outcome was 3-year all-cause mortality with comprehensive population-level assessment. Secondary outcomes included hypertension control assessed at a population level at year 3 (defined per country guidelines as at least 1 blood pressure measure \u3c140/90 mm Hg on 3 repeated measures). Between-arm comparisons used cluster-level targeted maximum likelihood estimation. Among 86,078 adults screened at study baseline (June 2013 to July 2014), 10,928 (13%) had uncontrolled hypertension. Median age was 53 years (25th to 75th percentile 40 to 66); 6,058 (55%) were female; 677 (6%) were HIV infected; and 477 (4%) had diabetes mellitus. Overall, 174 participants (3.2%) in the intervention group and 225 participants (4.1%) in the control group died during 3 years of follow-up (adjusted relative risk (aRR) 0.79, 95% confidence interval (CI) 0.64 to 0.97, p = 0.028). Among those with baseline grade 3 hypertension (≥180/110 mm Hg), 22 (4.9%) in the intervention group and 42 (7.9%) in the control group died during 3 years of follow-up (aRR 0.62, 95% CI 0.39 to 0.97, p = 0.038). Estimated population-level hypertension control at year 3 was 53% in intervention and 44% in control communities (aRR 1.22, 95% CI 1.12 to 1.33, p \u3c 0.001). Study limitations include inability to identify specific causes of death and control conditions that exceeded current standard hypertension care. Conclusions In this cluster randomized comparison where both arms received population-level hypertension screening, implementation of a patient-centered hypertension care model was associated with a 21% reduction in all-cause mortality and a 22% improvement in hypertension control compared to standard care among adults with baseline uncontrolled hypertension. Patient-centered chronic care programs for HIV can be leveraged to reduce the overall burden of cardiovascular mortality in SSA

A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation

<p>Abstract</p> <p>Background</p> <p>Efficient, robust, and accurate genotype imputation algorithms make large-scale application of genomic selection cost effective. An algorithm that imputes alleles or allele probabilities for all animals in the pedigree and for all genotyped single nucleotide polymorphisms (SNP) provides a framework to combine all pedigree, genomic, and phenotypic information into a single-stage genomic evaluation.</p> <p>Methods</p> <p>An algorithm was developed for imputation of genotypes in pedigreed populations that allows imputation for completely ungenotyped animals and for low-density genotyped animals, accommodates a wide variety of pedigree structures for genotyped animals, imputes unmapped SNP, and works for large datasets. The method involves simple phasing rules, long-range phasing and haplotype library imputation and segregation analysis.</p> <p>Results</p> <p>Imputation accuracy was high and computational cost was feasible for datasets with pedigrees of up to 25 000 animals. The resulting single-stage genomic evaluation increased the accuracy of estimated genomic breeding values compared to a scenario in which phenotypes on relatives that were not genotyped were ignored.</p> <p>Conclusions</p> <p>The developed imputation algorithm and software and the resulting single-stage genomic evaluation method provide powerful new ways to exploit imputation and to obtain more accurate genetic evaluations.</p

Impacts of acoustic and gravity waves on the ionosphere

The impact of regional-scale neutral atmospheric waves has been demonstrated to have profound effects on the ionosphere, but the circumstances under which they generate ionospheric disturbances and seed plasma instabilities are not well understood. Neutral atmospheric waves vary from infrasonic waves of <20 Hz to gravity waves with periods on the order of 10 min, for simplicity, hereafter they are combined under the common term Acoustic and Gravity Waves (AGWs). There are other longer period waves like planetary waves from the lower and middle atmosphere, whose effects are important globally, but they are not considered here. The most ubiquitous and frequently observed impact of AGWs on the ionosphere are Traveling Ionospheric Disturbances (TIDs), but AGWs also affect the global ionosphere/thermosphere circulation and can trigger ionospheric instabilities (e.g., Perkins, Equatorial Spread F). The purpose of this white paper is to outline additional studies and observations that are required in the coming decade to improve our understanding of the impact of AGWs on the ionosphere

Impacts of acoustic and gravity waves on the ionosphere

The impact of regional-scale neutral atmospheric waves has been demonstrated to have profound effects on the ionosphere, but the circumstances under which they generate ionospheric disturbances and seed plasma instabilities are not well understood. Neutral atmospheric waves vary from infrasonic waves of &lt;20 Hz to gravity waves with periods on the order of 10 min, for simplicity, hereafter they are combined under the common term Acoustic and Gravity Waves (AGWs). There are other longer period waves like planetary waves from the lower and middle atmosphere, whose effects are important globally, but they are not considered here. The most ubiquitous and frequently observed impact of AGWs on the ionosphere are Traveling Ionospheric Disturbances (TIDs), but AGWs also affect the global ionosphere/thermosphere circulation and can trigger ionospheric instabilities (e.g., Perkins, Equatorial Spread F). The purpose of this white paper is to outline additional studies and observations that are required in the coming decade to improve our understanding of the impact of AGWs on the ionosphere.</p

Impacts of acoustic and gravity waves on the ionosphere

The impact of regional-scale neutral atmospheric waves has been demonstrated to have profound effects on the ionosphere, but the circumstances under which they generate ionospheric disturbances and seed plasma instabilities are not well understood. Neutral atmospheric waves vary from infrasonic waves of <20 Hz to gravity waves with periods on the order of 10 min, for simplicity, hereafter they are combined under the common term Acoustic and Gravity Waves (AGWs). There are other longer period waves like planetary waves from the lower and middle atmosphere, whose effects are important globally, but they are not considered here. The most ubiquitous and frequently observed impact of AGWs on the ionosphere are Traveling Ionospheric Disturbances (TIDs), but AGWs also affect the global ionosphere/thermosphere circulation and can trigger ionospheric instabilities (e.g., Perkins, Equatorial Spread F). The purpose of this white paper is to outline additional studies and observations that are required in the coming decade to improve our understanding of the impact of AGWs on the ionosphere

Thermohaline structure in the California Current System : observations and modeling of spice variance

Author Posting. © American Geophysical Union, 2012. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 117 (2012): C02008, doi:10.1029/2011JC007589.Upper ocean thermohaline structure in the California Current System is investigated using sustained observations from autonomous underwater gliders and a numerical state estimate. Both observations and the state estimate show layers distinguished by the temperature and salinity variability along isopycnals (i.e., spice variance). Mesoscale and submesoscale spice variance is largest in the remnant mixed layer, decreases to a minimum below the pycnocline near 26.3 kg m−3, and then increases again near 26.6 kg m−3. Layers of high (low) meso- and submesoscale spice variance are found on isopycnals where large-scale spice gradients are large (small), consistent with stirring of large-scale gradients to produce smaller scale thermohaline structure. Passive tracer adjoint calculations in the state estimate are used to investigate possible mechanisms for the formation of the layers of spice variance. Layers of high spice variance are found to have distinct origins and to be associated with named water masses; high spice variance water in the remnant mixed layer has northerly origin and is identified as Pacific Subarctic water, while the water in the deeper high spice variance layer has southerly origin and is identified as Equatorial Pacific water. The layer of low spice variance near 26.3 kg m−3 lies between the named water masses and does not have a clear origin. Both effective horizontal diffusivity, κh, and effective diapycnal diffusivity, κv, are elevated relative to the diffusion coefficients set in the numerical simulation, but changes in κh and κv with depth are not sufficient to explain the observed layering of thermohaline structure.We gratefully acknowledge funding from the Gordon and Betty Moore Foundation, the Coastal Ocean Currents Monitoring Project (COCMP), and NOAA. R. E. Todd was partially supported by the Postdoctoral Scholar Program at the Woods Hole Oceanographic Institution, with funding provided by the Cooperative Institute for the North Atlantic Region.2012-08-0