Development and testing of an efficient micropollutant monitoring strategy across a large watershed.

In recent decades, extensive monitoring programmes have been conducted at the national, international, and project levels with the objective of expanding our understanding of the contamination of surface waters with micropollutants, which are often referred to as hazardous substances (HS). It has been demonstrated that HS enter surface waters via a number of pathways, including groundwater, atmospheric deposition, soil erosion, and urban systems. Given the ever-growing list of substances and the high resource demand associated with laboratory analysis, it is common practice to quantify the listed pathways based on emission factors derived from temporally and spatially constrained monitoring programmes. The derivation calculations are subject to high uncertainties, and substantial knowledge gaps remain regarding the relative importance of the unique pathways, territories, and periods. This publication presents a monitoring method designed to quantify the unique emission pathways of HS in large geographical areas characterized by differences in land use, population, and economic development. The method will be tested for a wide range of HS (ubiquitous organic and inorganic pollutants, pesticides, pharmaceuticals) throughout small sub-catchments located on tributaries. The results of the test application demonstrate a high diversity of both emission loads and instream concentrations throughout different regions for numerous substances. Riverine concentrations are found to be highly dependent on the flow status. Soil concentration levels of polycyclic aromatic hydrocarbons (PAH) and perfluoroalkyl substances (PFAS) are found to be in proportion, whereas that of potentially toxic elements (PTE) in a reverse relationship with economic development. In many instances, concentration levels are also contingent upon land use. The findings of this study reinforce the necessity for the implementation of harmonised and concerted HS monitoring programmes, which should encompass a diverse range of substances, emission sources, pathways and geographical areas. This is essential for the reliable development of emission factors.

Self-Sampling by Adolescents at Home: Assessment of the Feasibility to Successfully Collect Blood Microsamples by Inexperienced Individuals.

Blood microsampling has increasingly attracted interest in the past decades as a more patient-centric sampling approach, offering the possibility to collect a minimal volume of blood following a finger or arm prick at home. In addition to conventional dried blood spots (DBS), many different devices allowing self-sampling of blood have become available. Obviously, the success of home-sampling can only be assured when (inexperienced) users collect samples of good quality. Therefore, the feasibility of six different microsampling devices to collect capillary blood by inexperienced adolescents at home was evaluated. Participants (n = 95) were randomly assigned to collect blood (dried or liquid) at different time points using four of six different self-sampling devices (i.e., DBS, Mitra volumetric absorptive microsampling (VAMS), Capitainer B, Tasso M20, Minicollect tube and Tasso+ serum separator tube (SST)). The quality of the samples was visually inspected and analytically determined. Moreover, the participants' satisfaction was assessed via questionnaires. Although a majority succeeded based on the visual inspection, the success rate differed largely between the different devices. In general, the lowest success rate was obtained for the Minicollect tubes, although there is an opportunity and need for improvement for the other self-sampling devices as well. Hence, this also emphasizes the importance to assess the quality of samples collected by the target population prior to study initiation. In addition, visual classification by a trained individual was confirmed based on assessment of the analytical variability between replicates. Finally, self-sampling at home was overall (very) positively received by the participants.

Efficient risk-based collection of biospecimens in cohort studies: Designing a prospective study of diagnostic performance for multicancer detection tests.

In cohort studies, it can be infeasible to collect specimens on an entire cohort. For example, to estimate sensitivity of multiple Multi-Cancer Detection (MCD) assays, we desire an extra 80mL of cell-free DNA (cfDNA) blood, but this much extra blood is too expensive for us to collect on everyone. We propose a novel epidemiologic study design that efficiently oversamples those at highest baseline disease risk from whom to collect specimens, to increase the number of future cases with cfDNA blood collection. The variance reduction ratio from our risk-based subsample versus a simple random (sub)sample (SRS) depends primarily on the ratio of risk model sensitivity to the fraction of the cohort selected for specimen collection subject to constraining the risk model specificity. In a simulation where we chose 34% of Prostate, Lung, Colorectal, and Ovarian Screening Trial cohort at highest risk of lung cancer for cfDNA blood collection, we could enrich the number of lung cancers 2.42-fold and the standard deviation of lung-cancer MCD sensitivity was 31-33% reduced versus SRS. Risk-based collection of specimens on a subsample of the cohort could be a feasible and efficient approach to collecting extra specimens for molecular epidemiology.

Computer-Vision-Oriented Adaptive Sampling in Compressive Sensing.

Compressive sensing (CS) is recognized for its adeptness at compressing signals, making it a pivotal technology in the context of sensor data acquisition. With the proliferation of image data in Internet of Things (IoT) systems, CS is expected to reduce the transmission cost of signals captured by various sensor devices. However, the quality of CS-reconstructed signals inevitably degrades as the sampling rate decreases, which poses a challenge in terms of the inference accuracy in downstream computer vision (CV) tasks. This limitation imposes an obstacle to the real-world application of existing CS techniques, especially for reducing transmission costs in sensor-rich environments. In response to this challenge, this paper contributes a CV-oriented adaptive CS framework based on saliency detection to the field of sensing technology that enables sensor systems to intelligently prioritize and transmit the most relevant data. Unlike existing CS techniques, the proposal prioritizes the accuracy of reconstructed images for CV purposes, not only for visual quality. The primary objective of this proposal is to enhance the preservation of information critical for CV tasks while optimizing the utilization of sensor data. This work conducts experiments on various realistic scenario datasets collected by real sensor devices. Experimental results demonstrate superior performance compared to existing CS sampling techniques across the STL10, Intel, and Imagenette datasets for classification and KITTI for object detection. Compared with the baseline uniform sampling technique, the average classification accuracy shows a maximum improvement of 26.23%, 11.69%, and 18.25%, respectively, at specific sampling rates. In addition, even at very low sampling rates, the proposal is demonstrated to be robust in terms of classification and detection as compared to state-of-the-art CS techniques. This ensures essential information for CV tasks is retained, improving the efficacy of sensor-based data acquisition systems.

Enhancing Cervical Cancer Screening with 7-Type HPV mRNA E6/E7 Testing on Self-Collected Samples: Multicentric Insights from Mexico.

Cervical cancer remains a significant public health issue, particularly in regions with low screening uptake. This study evaluates the effectiveness of self-sampling and the 7-type HPV mRNA E6/E7 test in improving cervical cancer screening outcomes among a referral population in Mexico. A cohort of 418 Mexican women aged 25 to 65, referred for colposcopy and biopsy due to abnormal cytology results (ASC-US+), participated in this study. Self-samples were analyzed using both the 14-type HPV DNA test and the 7-type HPV mRNA E6/E7 test. The study assessed the sensitivity, specificity, positive predictive value (PPV), and the necessity of colposcopies to detect CIN3+ lesions. Participant acceptability of self-sampling was also evaluated through a questionnaire. The 7-type HPV mRNA E6/E7 test demonstrated equivalent sensitivity but significantly higher specificity (77.0%) and PPV for CIN3+ detection compared to the 14-type HPV DNA test (specificity: 45.8%, p < 0.001). The use of the HPV mRNA test as a triage tool reduced the number of colposcopies needed per CIN3+ case detected from 16.6 to 7.6 (p < 0.001). Self-sampling was highly accepted among participants, with the majority reporting confidence in performing the procedure, minimal discomfort, and willingness to undertake self-sampling at home. Self-sampling combined with the 7-type HPV mRNA E6/E7 testing offers a promising strategy to enhance cervical cancer screening by improving accessibility and ensuring precise diagnostics. Implementing these app roaches could lead to a significant reduction in cervical cancer morbidity and mortality, especially in underserved populations. Future research should focus on the long-term impact of integrating these methods into national screening programs and explore the cost-effectiveness of widespread implementation.

The spatial extent and the dispersal strategy of species shape the occupancy frequency distribution of stream insect assemblages.

Several theoretical models have been proposed as the underlying mechanisms behind occupancy frequency distribution (OFD) patterns. For instance, the metapopulation dynamic model predicts bimodal OFD pattern indicating the dominance of dispersal processes in structuring the assemblages, while the niche-based model predicts unimodal right-skewed OFD pattern, and thus assemblages are driven mostly by niche processes. However, it is well known that the observed OFD pattern reflects the interplay of several other factors (e.g. habitat heterogeneity, species specificity and sampling protocol parameters). It follows that the individual contribution of each factor to the OFD pattern is rather complicated to explore. Our main objective was to examine the role of the spatial extent of the sampling and the dispersal strategies of species in shaping OFD pattern. For this, we collected samples of stream insect assemblages inhabiting near-natural streams in the Pannon Ecoregion. We formed groups of species representing contrasting dispersal strategies (referred to as dispersal groups). Applying a computer program algorithm, we produced samples with different spatial extent. We found that with increasing spatial extent, the OFD pattern changed from bimodal to unimodal for active dispersers. Insect groups with different dispersal strategies differed in the strength of support for OFD patterns within all spatial extent. Furthermore, the strength of support for OFD patterns varied across dispersal groups differently as the spatial extent increased. Our results reflected underlying changes in mechanisms structuring assemblages along an increasing spatial extent. We also assumed that the stream insect dispersal strategy influences the relative role of dispersal and niche processes particularly as spatial extent increases from stream reaches to the extent of adjacent valleys. We could define spatial extents and dispersal strategies within which unique metacommunity processes could underlie the organisation of assemblages.

Microplastic pollution in the North-east Atlantic Ocean surface water: How the sampling approach influences the extent of the issue.

A lack of standardization in monitoring protocols has hindered the accurate evaluation of microplastic (MP) pollution in the open sea and its potential impacts. As sampling techniques significantly influence the amounts of MPs contained in the sample, the aim of this study was to compare two sampling methods: Manta trawl (size selective approach) and grab sampling (volume selective approach). Both approaches were applied in the open sea surface waters of the North-east Atlantic Ocean. Onshore sample processing was carried out using the innovative tape lifting technique, which affords a series of advantages, including prevention of airborne contamination during analysis, without compromising integrity of the results. The results obtained indicated an MP concentration over four orders of magnitude higher using grab sampling compared to the Manta net approach (mean values equal to 0.24 and 4050 items/m3, respectively). Consequently, the sole quantification of MPs using results obtained with the Manta trawl resulted in a marked underestimation of abundance. Nevertheless, the grab sampling technique is intricately linked to a risk of collecting non-representative water volumes, consequently leading to an overestimation of MPs abundance and a significant inter-sample variability. Moreover, the latter method is unsuitable for use in sampling larger MPs or in areas with low concentrations of MP pollution. The optimal sampling method therefore is dependent on the specific objectives of the study, often resulting in a combination of size and volume selective methods. The results of this study have the potential to contribute to the standardization of monitoring protocols for microplastics, both during the sampling phase and sample processing.

Population size and structure of beisa oryx and gerenuk in Geralle National Park, southeastern Ethiopia.

The study was conducted to determine the population size of endangered Oryx beisa (Rüppell, 1835), and near-threatened Litocranius walleri (Brooke, 1878) of uncertain global population estimates in Geralle National Park, southeastern Ethiopia. Systematic line transects were established with a transect length range of 2.3 to 6.8 km long (a total of 165.4 km long with a sighting distance of 150 m after truncation). The combination of AIC and chi-square p-values was used as model selection criteria for density/population size estimation in distance sampling software. The lowest AIC, ∆AIC (close to zero), and Chi-square tests (p-value > .05) were selected with adequate model fit. The minimum observation was 67 individuals of beisa oryx in the dry season. The maximum observation was 349 individuals of gerenuk during the wet season. The minimum detection probability of oryx was in the wet season (p â = 76 ± 26), and the minimum detection probability of gerenuk was (p â = 75 ± 1) in both seasons. The two-season pooled density analyzed for studied species indicated (0.85 ± 0.34, 1.24 ± 0.47, beisa oryx/km2), and (3.82 ± 0.6, 4.88 ± 0.7 gerenuk/km2) in dry and wet seasons, respectively. It can be concluded from the results of the study that GNP is home to previously undiscovered healthy populations of the endangered beisa oryx and near-threatened gerenuk. So it is recommended to undergo in-depth population studies, including other species available in the national park and their habitat components, so as to design sound, sustainable conservation measures for the wildlife resources in the area.

Endocannabinoid analysis in GlucoEXACT plasma: Method validation and sample handling recommendations.

Endocannabinoids (ECs), such as anandamide and 2-arachidonyl glycerol (2-AG), contribute to the pathology of inflammatory, malignant, cardiovascular, metabolic and mental diseases. The reliability of quantitative analyses in biological fluids of ECs and endocannabinoid-like (EC-like) substances depends on pre-analytical conditions such as temperature and "time-to-centrifugation". Standardization of these parameters is critical for valid quantification and implementation in clinical research. In this study, we compared concentrations obtained with GlucoEXACT blood collection tubes versus K3EDTA tubes and employed the optimized procedure to assess ECs profiles in patients with inflammatory skin disease and healthy controls. A UHPLC-MS/MS method was validated for human plasma from GlucoEXACT blood collection tubes according to EMA and FDA guidelines, and pre-analytical conditions were systematically modified to assess analyte stability and optimize the procedures. The results showed significantly lower concentrations of ECs and EC-like substance concentrations with GlucoEXACT tubes compared with K3EDTA tubes, and GlucoEXACT extended the time window of stable concentrations. The strongest method-disagreement occurred for 1/2-AG suggesting that GlucoEXACT delayed ex vivo isomer rearrangement. Hence, GlucoExact tubes were superior in terms of stability and reliability. However, although absolute concentrations obtained with GlucoExact and K3EDTA differed, linear regression studies showed high agreement (except for 1/2-AG), and both methods showed similar EC profiles and similar disease-dependent pro-inflammatory patterns in dermatology patients. Hence, despite the obstacles in EC analyses, implementation of optimized pre-analytical blood collection and sample processing procedures provide reliable insight into peripheral ECs.

Reducing discrepancies between actual and ideal affect across adulthood: the roles of activity flow conduciveness, pleasantness, and familiarity.

Previous findings demonstrate that people often do not feel how they want to feel, supporting the distinction between "actual affect" and "ideal affect." But are there certain activities that reduce the discrepancy between actual and ideal affect? Based on flow theory and socioemotional selectivity theory, we examined whether the discrepancy between people's actual and ideal positive affect would be smaller during activities that were more conducive to flow (a state of intense absorption and concentration), pleasant, and familiar. In Study 1, U.S. participants aged 17-79 (N = 393) reported their ideal affect and how they felt during activities with varying degrees of challenges and skills. For both low-arousal positive affect (LAP) and high-arousal positive affect (HAP), participants reported smaller actual-ideal affect discrepancies during flow-conducive activities (when skills matched challenges). Study 2 was a 14-day experience sampling study, in which Hong Kong participants aged 18-83 (Nindividual = 109) reported their momentary actual and ideal affect, and how pleasant and familiar their activities were (Nexperience = 3,815). Greater activity familiarity was associated with smaller discrepancies in actual-ideal LAP, while greater activity pleasantness was associated with smaller discrepancies in actual-ideal HAP. These findings provide insights on the activities that help people achieve their ideal affect more easily.

Experiences and perspectives regarding human papillomavirus self-sampling in sub-Saharan Africa: A systematic review of qualitative evidence.

Introduction: Cervical cancer screening coverage remains low in sub-Saharan Africa (SSA) due to limited access and low uptake of available services by women. The use of HPV-based self-sampling intervention for cervical cancer screening has the potential to increase screening coverage in the region. This study aimed to analyse qualitative evidence on the experiences and perspectives of women, healthcare workers, and policymakers regarding HPV self-sampling. Methods: We reviewed qualitative studies from January 2011 to March 2023 in PubMed, Scopus, Medline Ovid, Cochrane, and WEB of Science databases for articles with qualitative data on HPV self-sampling from different countries in SSA. The socio-ecological model was used to guide data analysis and the study findings. Results: Thirteen qualitative studies were included for analysis, and they revealed themes under the intrapersonal, interpersonal, community, and health systems constructs of the Socio-ecological model. Intrapersonal themes included the acceptability of self-sampling, self-efficacy, and the perceived value of self-sampling. The interpersonal construct had themes such as women's spousal relationships, peer support, and the health worker's relationship with the women. The community construct had two themes: social stigma and misinformation, and the influence of cultural norms and religion. Finally, the health systems construct had themes such as the setting for self-sampling, follow-up availability of treatment services and education and awareness. Conclusion: This study highlights the factors influencing the acceptability and uptake of an HPV-based self-sampling intervention for cervical cancer screening in SSA. Considering these findings when designing interventions in SSA is crucial to ensure acceptance and demand among end-users. Self-sampling interventions offer the potential to reach many unscreened women and increase cervical cancer screening coverage in SSA, which is an essential strategy towards achieving the World Health Organisation's cervical cancer elimination targets by the close of the century.

Salinity influence correction for zinc ion seawater quality criteria and ecological risk assessment in Chinese seas.

The increasing prevalence of zinc pollution in marine ecosystems, primarily from industrial sources, has become a global environmental concern. This study addresses zinc toxicity in Chinese coastal waters, emphasizing the importance of considering environmental factors like salinity and temperature in establishing water quality criteria (WQC). Data collected from various marine regions underwent meticulous analysis, incorporating salinity corrections to derive more precise criteria values. The short-term water quality criteria for the Bohai Sea, Yellow Sea, East China Sea, and South China Sea were 94.0, 77.6, 84.2, and 118 µg/L under the salinity correction, respectively, and the long-term criteria was 4.10 µg/L. Ecological risk assessments employing diverse methodologies revealed varying levels of risk across sea areas, underscoring the nuanced nature of zinc pollution's impact on marine ecosystems. Greater acute and chronic risk of zinc ions observed in the Yellow Sea region. These findings highlight the necessity for tailored management strategies to safeguard local marine life against zinc-induced environmental threats. These findings underscore the imperative need for tailored management strategies to protect local marine life from the environmental threats posed by zinc.

Development of a sequential sampling plan for classifying Thrips tabaci (Thysanoptera: Thripidae) populations in onion fields.

Onion thrips, Thrips tabaci Lindeman, is a global pest of onion crops, causing substantial economic damage by diminishing bulb yields and transmitting plant pathogens. Insecticides are used to manage T. tabaci infestations with control decisions traditionally based on action thresholds that require visually counting thrips on a fixed, predetermined number of onion plants per field. However, this approach for treatment decisions is inefficient when thrips populations are well above or below the action threshold. The aim of this research was to develop a sequential sampling plan that would provide a rapid and reliable classification of thrips populations in commercial onion fields above or below prespecified management thresholds. The study was conducted in a total of 24 commercial onion fields in New York in 2021 and 2022. Taylor's power law and Wald's Sequential Probability Ratio Test were used in concert to develop each sampling plan. Simulated and historical field data of thrips populations were used to further validate the efficacy of each sampling plan. Results demonstrated the sequential sampling plan required an average of 78% fewer samples to make a control decision compared with the traditional fixed-sampling approach. Treatment decisions were reached in 72% of cases after inspecting only 10 plants, while only 6% of the cases required examining more than 25 plants. Comparisons with fixed-sample sizes ranging from 23 to 68 plants revealed a 96% agreement in decision-making and a 78% reduction in sampling effort when using the sequential sampling plans.

The MoodWheel app: validation and factor structure of a new tool for the assessment of mood based on the experience sampling method.

BACKGROUND: The MoodWheel app is a newly developed tool that uses experience sampling method (ESM) for assessing negative and positive emotions, based on the circumplex model of emotions and the binary model of distress, and including behavioral and heart rate (HR) measurement via photoplethysmography and the possibility to personalize the application with additional measures. Aims: This study was designed to assess the factorial structure, reliability and validity of the MoodWheel (MW) application for evaluating emotions in children, adolescents. METHODS: A sample of 490 children and adolescents were recruited from the schools. Internal consistency was assessed via Cronbach's alpha test. Concurrent validity was assessed by evaluating the correlations between MW and Profile of Emotional Distress scale (PED) scores, in terms of functional/dysfunctional negative and positive emotions. RESULTS: Results obtained show that MW has good to excellent internal consistency and test-retest reliability, while the convergent validity was also adequate. Moreover, we found support for the organization of the MW based on the binary model of distress, given the predictive value found for the irrational and rational beliefs. CONCLUSIONS: The MW application is a useful and easy to use tool that can be used for the accurate measurement of emotions, which will be complimented in future with additional behavioral parameters to provide a comprehensive and dynamic assessment.

Hidden Structural States of Proteins Revealed by Conformer Selection with AlphaFold-NMR.

Recent advances in molecular modeling using deep learning can revolutionize our understanding of dynamic protein structures. NMR is particularly well-suited for determining dynamic features of biomolecular structures. The conventional process for determining biomolecular structures from experimental NMR data involves its representation as conformation-dependent restraints, followed by generation of structural models guided by these spatial restraints. Here we describe an alternative approach: generating a distribution of realistic protein conformational models using artificial intelligence-(AI-) based methods and then selecting the sets of conformers that best explain the experimental data. We applied this conformational selection approach to redetermine the solution NMR structure of the enzyme Gaussia luciferase. First, we generated a diverse set of conformer models using AlphaFold2 (AF2) with an enhanced sampling protocol. The models that best-fit NOESY and chemical shift data were then selected with a Bayesian scoring metric. The resulting models include features of both the published NMR structure and the standard AF2 model generated without enhanced sampling. This "AlphaFold-NMR" protocol also generated an alternative "open" conformational state that fits nearly as well to the overall NMR data but accounts for some NOESY data that is not consistent with first "closed" conformational state; while other NOESY data consistent with this second state are not consistent with the first conformational state. The structure of this "open" structural state differs from that of the "closed" state primarily by the position of a thumb-shaped loop between α-helices H5 and H6, revealing a cryptic surface pocket. These alternative conformational states of Gluc are supported by "double recall" analysis of NOESY data and AF2 models. Additional structural states are also indicated by backbone chemical shift data indicating partially-disordered conformations for the C-terminal segment. Considered as a multistate ensemble, these multiple states of Gluc together fit the NOESY and chemical shift data better than the "restraint-based" NMR structure and provide novel insights into its structure-dynamic-function relationships. This study demonstrates the potential of AI-based modeling with enhanced sampling to generate conformational ensembles followed by conformer selection with experimental data as an alternative to conventional restraint satisfaction protocols for protein NMR structure determination.

Pressure to not feel bad among (different-sex) romantic partners: prevalence, and correlates.

Western society generally highly values happiness. As a result, people sometimes experience pressure not to feel negative emotions. In this study, we comprehensively investigated this pressure, and how it manifests itself, in adult romantic relationships. Specifically, we first examined when, how often and how intensely people experience pressure not to feel bad from their romantic partners (94 different-sex couples). Additionally, we investigated (both between- and within-person) how this pressure is related to context (presence of, contact and or conflict with a partner), emotional processes (i.e. experienced sadness and anxiety, emotion suppression, and how their partner perceived their affect), and relationship well-being. Using experience sampling methodology data (6/14 reports per day over one week) we found that although participants generally did not experience strong pressure from their partner, they experienced some feelings of pressure about 50% of the time. Furthermore, within-person predictors associated with negative processes/emotions (i.e. negative emotions, conflict, emotion suppression) were related to the momentary frequency (odds) and/or intensity of perceived pressure not to feel bad. At the between-person level, individuals who experience more sadness, anxiety and reported suppressing their emotions more often tended to experience more and/or stronger pressure. Only weak associations with relationship well-being were found.

From anticipation to action: A RCT on mental imagery exercises in daily life as a motivational amplifier for individuals with depressive symptoms.

Encouraging engagement in rewarding or pleasant activities is one of the most important treatment goals for depression. Mental imagery exercises have been shown to increase the motivation for planned behaviour in the lab but it is unclear whether this is also the case in daily life. Therefore, we aimed to investigate the effect of mental imagery exercises on motivation and behaviour in daily life. Participants with depressive symptoms (N = 59) were randomly assigned to a group receiving mental imagery (MI) exercises or a control group receiving relaxation (RE) exercises via study phones. We employed an experience sampling design with 10 assessments per day for 10 days (three days baseline, four days with two exercises per day and three days post-intervention). Data was analysed using t-tests and multilevel linear regression analyses. As predicted, MI exercises enhanced motivation and reward anticipation during the intervention phase compared to RE. However, MI did not enhance active behaviour or strengthen the temporal association from reward anticipation (t-1) to active behaviour (t). Mental imagery exercises can act as a motivational amplifier but its effects on behaviour and real-life reward processes remain to be elucidated.

Estimating Haplotype Structure and Frequencies: A Bayesian Approach to Unknown Design in Pooled Genomic Data.

The estimation of haplotype structure and frequencies provides crucial information about the composition of genomes. Techniques, such as single-individual haplotyping, aim to reconstruct individual haplotypes from diploid genome sequencing data. However, our focus is distinct. We address the challenge of reconstructing haplotype structure and frequencies from pooled sequencing samples where multiple individuals are sequenced simultaneously. A frequentist method to address this issue has recently been proposed. In contrast to this and other methods that compute point estimates, our proposed Bayesian hierarchical model delivers a posterior that permits us to also quantify uncertainty. Since matching permutations in both haplotype structure and corresponding frequency matrix lead to the same reconstruction of their product, we introduce an order-preserving shrinkage prior that ensures identifiability with respect to permutations. For inference, we introduce a blocked Gibbs sampler that enforces the required constraints. In a simulation study, we assessed the performance of our method. Furthermore, by using our approach on two distinct sets of real data, we demonstrate that our Bayesian approach can reconstruct the dominant haplotypes in a challenging, high-dimensional set-up.

Inferring Population HIV Viral Load From a Single HIV Clinic's Electronic Health Record: Simulation Study With a Real-World Example.

BACKGROUND: Population viral load (VL), the most comprehensive measure of the HIV transmission potential, cannot be directly measured due to lack of complete sampling of all people with HIV. OBJECTIVE: A given HIV clinic's electronic health record (EHR), a biased sample of this population, may be used to attempt to impute this measure. METHODS: We simulated a population of 10,000 individuals with VL calibrated to surveillance data with a geometric mean of 4449 copies/mL. We sampled 3 hypothetical EHRs from (A) the source population, (B) those diagnosed, and (C) those retained in care. Our analysis imputed population VL from each EHR using sampling weights followed by Bayesian adjustment. These methods were then tested using EHR data from an HIV clinic in Delaware. RESULTS: Following weighting, the estimates moved in the direction of the population value with correspondingly wider 95% intervals as follows: clinic A: 4364 (95% interval 1963-11,132) copies/mL; clinic B: 4420 (95% interval 1913-10,199) copies/mL; and clinic C: 242 (95% interval 113-563) copies/mL. Bayesian-adjusted weighting further improved the estimate. CONCLUSIONS: These findings suggest that methodological adjustments are ineffective for estimating population VL from a single clinic's EHR without the resource-intensive elucidation of an informative prior.