Detection of Semantic Duplicates in Temporal Domains Using Directed Acyclic Graphs

We demonstrate the feasibility of a generalized technique for semantic deduplication in temporal data domains using graph-based representations of data records. Structured data records with multiple timestamp attributes per record may be represented as a directed graph where the nodes represent the events and the edges represent event sequences. Edge weights are based on elapsed time between connecting nodes. In comparing two records, we may merge these directed graphs and determine a representative directed acyclic graph (DAG) inclusive of a subset of nodes and edges that maintain the transitive weights of the original graphs. This DAG may then be evaluated by weighting elapsed time equivalences between records at each node and measuring the fraction of nodes represented in the DAG versus the union of nodes between the records being compared. With this information, we establish a duplication score and use a specified threshold requirement to assert duplication. This method is referred to as Temporal Deduplication using Directed Acyclic Graphs (TD:DAG). TD:DAG significantly outperformed established ASNM and ASNM+LCS methods for datasets rep-resenting two disparate domains, COVID-19 government policy data and PlayStation Network (PSN) trophy data. TD:DAG produced highly effective and comparable F1 scores of 0.960 and 0.972 for the two datasets, respectively, versus 0.864/0.938 for ASNM+LCS and 0.817/0.708 for ASNM. © 2023 IEEE.

Economic Recovery Strategy of Sectoral Industries Post-COVID-19: Input-Output Model Simulations

The global COVID-19 pandemic has suppressed the economy and people's welfare, including in Indonesia and Central Java Province, as indicated by the weakening of the national economy by -2.06 percent and locally by -2.65 percent in 2020. Although the economy grew by 3.32 percent in 2021, societal welfare remains lower than in 2019, marked by an increase in unemployment and poverty throughout 2019-2021. Furthermore, the threat of COVID-19 including new variants of the virus continues to weigh on the economy, in 2022 and beyond. This study considered an industrial approach to production, based on inter-industrial linkages and policy simulations with input-output analysis. The objectives of this research are to analyze the impact of the COVID-19 pandemic on the economy of Central Java and to formulate an effective economic recovery policy for industry. The results show that the industries affected by the COVID-19 pandemic in Central Java can promote recovery of overall income in economic industry better than the leading industry and the industries with the highest output multipliers, expressed as a proportional increase in final demand for each industry. Meanwhile, the economic recovery strategy of increasing final demand in industries with high output multipliers results in a faster increase in economic output compared with increasing final demand in the affected industries or leading industries.

Secondary distribution of HIV self-test kits by HIV index and antenatal care clients: implementation and costing results from the STAR Initiative in South Africa.

BACKGROUND: Partner-delivered HIV self-testing kits has previously been highlighted as a safe, acceptable and effective approach to reach men. However, less is known about its real-world implementation in reaching partners of people living with HIV. We evaluated programmatic implementation of partner-delivered self-testing through antenatal care (ANC) attendees and people newly diagnosed with HIV by assessing use, positivity, linkage and cost per kit distributed. METHODS: Between April 2018 and December 2019, antenatal care (ANC) clinic attendees and people or those newly diagnosed with HIV clients across twelve clinics in three cities in South Africa were given HIVST kits (OraQuick Rapid HIV-1/2 Antibody Test, OraSure Technologies) to distribute to their sexual partners. A follow-up telephonic survey was administered to all prior consenting clients who were successfully reached by telephone to assess primary outcomes. Incremental economic costs of the implementation were estimated from the provider's perspective. RESULTS: Fourteen thousand four hundred seventy-three HIVST kits were distributed - 10,319 (71%) to ANC clients for their male partner and 29% to people newly diagnosed with HIV for their partners. Of the 4,235 ANC clients successfully followed-up, 82.1% (3,475) reportedly offered HIVST kits to their male partner with 98.1% (3,409) accepting and 97.6% (3,328) using the kit. Among ANC partners self-testing, 159 (4.8%) reported reactive HIVST results, of which 127 (79.9%) received further testing; 116 (91.3%) were diagnosed with HIV and 114 (98.3%) initiated antiretroviral therapy (ART). Of the 1,649 people newly diagnosed with HIV successfully followed-up; 1,312 (79.6%) reportedly offered HIVST kits to their partners with 95.8% (1,257) of the partners accepting and 95.9% (1,206) reported that their partners used the kit. Among these index partners, 297 (24.6%) reported reactive HIVST results of which 261 (87.9%) received further testing; 260 (99.6%) were diagnosed with HIV and 258 (99.2%) initiated ART. The average cost per HIVST distributed in the three cities was US$7.90, US$11.98, and US$14.81, respectively. CONCLUSIONS: Partner-delivered HIVST in real world implementation was able to affordably reach many male partners of ANC attendees and index partners of people newly diagnosed with HIV in South Africa. Given recent COVID-19 related restrictions, partner-delivered HIVST provides an important strategy to maintain essential testing services.

Record linkage studies of drug-related deaths among adults who were released from prison to the community: a scoping review.

BACKGROUND: There are public health concerns about an increased risk of mortality after release from prison. The objectives of this scoping review were to investigate, map and summarise evidence from record linkage studies about drug-related deaths among former adult prisoners. METHODS: MEDLINE, EMBASE, PsychINFO and Web of Science were searched for studies (January 2011- September 2021) using keywords/index headings. Two authors independently screened all titles and abstracts using inclusion and exclusion criteria and subsequently screened full publications. Discrepancies were discussed with a third author. One author extracted data from all included publications using a data charting form. A second author independently extracted data from approximately one-third of the publications. Data were entered into Microsoft Excel sheets and cleaned for analysis. Standardised mortality ratios (SMRs) were pooled (where possible) using a random-effects DerSimonian-Laird model in STATA. RESULTS: A total of 3680 publications were screened by title and abstract, and 109 publications were fully screened; 45 publications were included. The pooled drug-related SMR was 27.07 (95%CI 13.32- 55.02; I 2 = 93.99%) for the first two weeks (4 studies), 10.17 (95%CI 3.74-27.66; I 2 = 83.83%) for the first 3-4 weeks (3 studies) and 15.58 (95%CI 7.05-34.40; I 2 = 97.99%) for the first 1 year after release (3 studies) and 6.99 (95%CI 4.13-11.83; I 2 = 99.14%) for any time after release (5 studies). However, the estimates varied markedly between studies. There was considerable heterogeneity in terms of study design, study size, location, methodology and findings. Only four studies reported the use of a quality assessment checklist/technique. CONCLUSIONS: This scoping review found an increased risk of drug-related death after release from prison, particularly during the first two weeks after release, though drug-related mortality risk remained elevated for the first year among former prisoners. Evidence synthesis was limited as only a small number of studies were suitable for pooled analyses for SMRs due to inconsistencies in study design and methodology.

TemporalDedup: Domain-Independent Deduplication of Redundant and Errant Temporal Data

Deduplication is a key component of the data preparation process, a bottleneck in the machine learning (ML) and data mining pipeline that is very time-consuming and often relies on domain expertise and manual involvement. Further, temporal data is increasingly prevalent and is not well suited to traditional similarity and distance-based deduplication techniques. We establish a fully automated, domain-independent deduplication model for temporal data domains, known as TemporalDedup, that infers the key attribute(s), applies a base set of deduplication techniques focused on value matches for key, non-key, and elapsed time, and further detects duplicates through inference of temporal ordering requirements using Longest Common Subsequence (LCS) for records of a shared type. Using LCS, we split each record's temporal sequence into constrained and unconstrained sequences. We flag suspicious (errant) records that are non-adherent to the inferred constrained order and we flag a record as a duplicate if its unconstrained order, of sufficient length, matches that of another record. TemporalDedup was compared against a similarity-based Adaptive Sorted Neighborhood Method (ASNM) in evaluating duplicates for two disparate datasets: (1) 22,794 records from Sony's PlayStation Network (PSN) trophy data, where duplication may be indicative of cheating, and (2) emergency declarations and government responses related to COVID-19 for all U.S. states and territories. TemporalDedup (F1-scores of 0.971 and 0.954) exhibited combined sensitivities above 0.9 for all duplicate classes whereas ASNM (0.705 and 0.732) exhibited combined sensitivities below 0.2 for all time and order duplicate classes. © 2023 World Scientific Publishing Company.

Consultation Rate and Mode by Deprivation in English General Practice From 2018 to 2022: Population-Based Study.

BACKGROUND: The COVID-19 pandemic has had a significant impact on primary care service delivery with an increased use of remote consultations. With general practice delivering record numbers of appointments and rising concerns around access, funding, and staffing in the UK National Health Service, we assessed contemporary trends in consultation rate and modes (ie, face-to-face versus remote). OBJECTIVE: This paper describes trends in consultation rates in general practice in England for key demographics before and during the COVID-19 pandemic. We explore the use of remote and face-to-face consultations with regard to socioeconomic deprivation to understand the possible effect of changes in consultation modes on health inequalities. METHODS: We did a retrospective analysis of 9,429,919 consultations by general practitioners, nurses, or other health care professionals between March 2018 and February 2022 for patients registered at 397 general practices in England. We used routine electronic health records from Clinical Practice Research Datalink Aurum with linkage to national data sets. Negative binomial models were used to predict consultation rates and modes (ie, remote versus face-to-face) by age, sex, and socioeconomic deprivation over time. RESULTS: Overall consultation rates increased by 15% from 4.92 in 2018-2019 to 5.66 in 2021-2022 with some fluctuation during the start of the COVID-19 pandemic. The breakdown into face-to-face and remote consultations shows that the pandemic precipitated a rapid increase in remote consultations across all groups, but the extent varies by age. Consultation rates increased with increasing levels of deprivation. Socioeconomic differences in consultation rates, adjusted for sex and age, halved during the pandemic (from 0.36 to 0.18, indicating more consultations in the most deprived), effectively narrowing relative differences between deprivation quintiles. This trend remains when stratified by sex, but the difference across deprivation quintiles is smaller for men. The most deprived saw a relatively larger increase in remote and decrease in face-to-face consultation rates compared to the least deprived. CONCLUSIONS: The substantial increases in consultation rates observed in this study imply an increased pressure on general practice. The narrowing of consultation rates between deprivation quintiles is cause for concern, given ample evidence that health needs are greater in more deprived areas.

Stakeholder Perspectives on the Impact of COVID-19 on the Implementation of a Community-Clinic Linkage Model in New York City.

Community-clinical linkage models (CCLM) have the potential to reduce health disparities, especially in underserved communities; however, the COVID-19 pandemic drastically impacted their implementation. This paper explores the impact of the pandemic on the implementation of CCLM intervention led by community health workers (CHWs) to address diabetes disparities among South Asian patients in New York City. Guided by the Consolidated Framework for Implementation Research (CFIR), 22 stakeholders were interviewed: 7 primary care providers, 7 CHWs, 5 community-based organization (CBO) representatives, and 3 research staff. Semi-structured interviews were conducted; interviews were audio-recorded and transcribed. CFIR constructs guided the identification of barriers and adaptations made across several dimensions of the study's implementation context. We also explored stakeholder-identified adaptations used to mitigate the challenges in the intervention delivery using the Model for Adaptation Design and Impact (MADI) framework. (1) Communication and engagement refers to how stakeholders communicated with participants during the intervention period, including difficulties experienced staying connected with intervention activities during the lockdown. The study team and CHWs developed simple, plain-language guides designed to enhance digital literacy. (2) Intervention/research process describes intervention characteristics and challenges stakeholders faced in implementing components of the intervention during the lockdown. CHWs modified the health curriculum materials delivered remotely to support engagement in the intervention and health promotion. (3) community and implementation context pertains to the social and economic consequences of the lockdown and their effect on intervention implementation. CHWs and CBOs enhanced efforts to provide emotional/mental health support and connected community members to resources to address social needs. Study findings articulate a repository of recommendations for the adaptation of community-delivered programs in under-served communities during a time of public health crises.

National data linkage assessment of live births and deaths in Mexico: Estimating under-five mortality rate ratios for vulnerable newborns and trends from 2008 to 2019.

BACKGROUND: Linked datasets that enable longitudinal assessments are scarce in low and middle-income countries. OBJECTIVES: We aimed to assess the linkage of administrative databases of live births and under-five child deaths to explore mortality and trends for preterm, small (SGA) and large for gestational age (LGA) in Mexico. METHODS: We linked individual-level datasets collected by National statistics from 2008 to 2019. Linkage was performed based on agreement on birthday, sex, residential address. We used the Centre for Data and Knowledge Integration for Health software to identify the best candidate pairs based on similarity. Accuracy was assessed by calculating the area under the receiver operating characteristic curve. We evaluated completeness by comparing the number of linked records with reported deaths. We described the percentage of linked records by baseline characteristics to identify potential bias. Using the linked dataset, we calculated mortality rate ratios (RR) in neonatal, infants, and children under-five according to gestational age, birthweight, and size. RESULTS: For the period 2008-2019, a total of 24,955,172 live births and 321,165 under-five deaths were available for linkage. We excluded 1,539,046 records (6.2%) with missing or implausible values. We succesfully linked 231,765 deaths (72.2%: range 57.1% in 2009 and 84.3% in 2011). The rate of neonatal mortality was higher for preterm compared with term (RR 3.83, 95% confidence interval, [CI] 3.78, 3.88) and for SGA compared with appropriate for gestational age (AGA) (RR 1.22 95% CI, 1.19, 1.24). Births at <28 weeks had the highest mortality (RR 35.92, 95% CI, 34.97, 36.88). LGA had no additional risk vs AGA among children under five (RR 0.92, 95% CI, 0.90, 0.93). CONCLUSIONS: We demonstrated the utility of linked data to understand neonatal vulnerability and child mortality. We created a linked dataset that would be a valuable resource for future population-based research.

The Impact of Industrial Linkage Structures on Urban Economic Resilience in China in the Context of the COVID-19 Shock

The structures of industrial linkages form an essential basis for the economy and have an important impact on urban economic resilience. By analyzing the impact of COVID-19 on China's urban economy in 2020, this study uses China's national input-output table to measure the centrality and diversity of industrial linkage structures. Extracted data from 298 cities in China are used to explore the impact of centrality and diversity on urban economic resilience. The results show that the cities in East China, Central China, and the Chengdu-Chongqing area in western China have a high centrality with respect to industrial linkage structures. Cities in the Yangtze River Delta, Pearl River Delta, the middle reaches of the Yangtze River city cluster, and the Chengdu-Chongqing city cluster have a high diversity of industrial linkages structures. During the shock of the COVID-19 pandemic, most cities in China have shown high economic resilience. For cities across the country, diversity shows a significant and positive correlation with economic resilience, and centrality shows a significant and positive correlation with economic resilience. The latter displays an inverted U-shaped relationship between centrality and economic resilience. For cities with different population sizes, there are differences in the impacts of centrality and diversity on urban economic resilience. Different industrial policies can be developed to adjust the centrality and diversity of the cities to enhance urban economic resilience.

Derivatization of sialylated glycopeptides plus based sialoglycopeptides enrichment using cation exchange media.

Glycosylation is one of the most important post-translational modifications. However, the characterizations of glycopeptides, especially the negatively charged sialoglycopeptides that are associated with various diseases, remain challenging, due to the co-existence with high abundant peptides and the low ionization efficiency of sialoglycopeptides resulting from the carboxyl groups. Therefore, it is essential to develop an efficient enrichment method for sialoglycopeptides. Here, we present a novel derivatization-based enrichment method that can (i) identify linkage isomers of sialic acids by generating mass difference, (ii) unify the net charge of peptides into zero, and (iii) introduce positive charges to sialoglycopeptides by conjugating quaternary ammonium with sialic acid. The derivatization, termed derivatization of sialylated glycopeptides plus (DOSG+), enables efficient enrichment through electrostatic interaction using weak cation exchange (WCX) media. DOSG+ -based WCX enrichment was validated and optimized with samples derived from bovine fetuin. Peptides were removed efficiently (recovery rate <1%). The signal intensity of a selected model sialoglycopeptide was increased by ∼30% (suggesting recovery rate >100%). The method was employed on human alpha-1 acid glycoprotein (AGP), and recombinant human erythropoietin (EPO), demonstrating the application of DOSG+ -based WCX enrichment on complexed N-linked and O-linked sialoglycopeptides. The method is simple, efficient, and targets small-scale sialoglycopeptide enrichment.

Transcriptome Profiling in Autoimmune Diseases

Autoimmune diseases are a group of different inflammatory disorders characterized by systemic or localized inflammation, affecting approximately 0.1–1% of the general population. Several studies suggest that genetic risk loci are shared between different autoimmune diseases and pathogenic mechanisms may also be shared. The strategy of performing differential gene expression profiles in autoimmune disorders has unveiled new transcripts that may be shared among these disorders. Microarray technology and bioinformatics offer the most comprehensive molecular evaluations and it is widely used to understand the changes in gene expression in specific organs or in peripheral blood cells. The major goal of transcriptome studies is the identification of specific biomarkers for different diseases. It is believed that such knowledge will contribute to the development of new drugs, new strategies for early diagnosis, avoiding tissue autoimmune destruction, or even preventing the development of autoimmune disease. In this review, we primarily focused on the transcription profiles of three typical autoimmune disorders, including type 1 diabetes mellitus (destruction of pancreatic islet beta cells), systemic lupus erythematosus (immune complex systemic disorder affecting several organs and tissues), and multiple sclerosis (inflammatory and demyelinating disease of the nervous system). © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2014, 2022.

Research on the time-varying effects among green finance markets in China: A fresh evidence from multi-frequency scale perspective

Green finance is an essential instrument for achieving sustainable development. Objectively addressing correlations among different green finance markets is conducive to the risk management of investors and regulators. This paper presents evidence on the time-varying correlation effects and causality among the green bond market, green stock market, carbon market, and clean energy market in China at multi-frequency scales by combining the methods of Ensemble Empirical Mode Decomposition Method (EEMD), Dynamic Conditional Correlation (DCC) GARCH model, Time-Varying Parameter Vector Autoregression with Stochastic Volatility Model (TVP-VAR-SV), and Time-varying Causality Test. In general, the significant negative time-varying correlations among most green finance markets indicate a prominent benefit of risk hedging and portfolio diversification among green financial assets. In specific, for different time points and lag periods, the green finance market shock has obvious time-varying, positive and negative alternating effects in the short-term scales, while its time delay and persistence are more pronounced in the medium-term and long-term scales. Interestingly, a positive event shock will generate positive connectivity among most green finance markets, whereas a negative event including the China/U.S. trade friction and the COVID-19 pandemic may exacerbate the reverse linkage among green finance markets. Furthermore, the unidirectional causality of "green bond market - carbon market - green stock and clean energy markets” was established during 2018–2019. © 2023

COVID-19 vaccination uptake in people with epilepsy in wales.

PURPOSE: People with epilepsy (PWE) are at increased risk of severe COVID-19. Assessing COVID-19 vaccine uptake is therefore important. We compared COVID-19 vaccination uptake for PWE in Wales with a matched control cohort. METHODS: We performed a retrospective, population, cohort study using linked, anonymised, Welsh electronic health records within the Secure Anonymised Information Linkage (SAIL) Databank (Welsh population=3.1 million).We identified PWE in Wales between 1st March 2020 and 31st December 2021 and created a control cohort using exact 5:1 matching (sex, age and socioeconomic status). We recorded 1st, 2nd and booster COVID-19 vaccinations. RESULTS: There were 25,404 adults with epilepsy (127,020 controls). 23,454 (92.3%) had a first vaccination, 22,826 (89.9%) a second, and 17,797 (70.1%) a booster. Comparative figures for controls were: 112,334 (87.8%), 109,057 (85.2%) and 79,980 (62.4%).PWE had higher vaccination rates in all age, sex and socioeconomic subgroups apart from booster uptake in older subgroups. Vaccination rates were higher in older subgroups, women and less deprived areas for both cohorts. People with intellectual disability and epilepsy had higher vaccination rates when compared with controls with intellectual disability. CONCLUSIONS: COVID-19 vaccination uptake for PWE in Wales was higher than that for a matched control group.

Linkage role of ICT and Big Data in COVID-19: a case of Korea's digital and social communication practices

Purpose: This paper aims to discuss characteristics of Korea's system responses with a research framework of the structure, conduct and performance theory and explain the role of information, communication technologies (ICT) and Big Data from a technology-mediated control (TMC) perspective. Design/methodology/approach: This study examines the contextual nature of Korea's diagnostic, preventive and treatment efforts. Particular attention is paid to issues related to the effective use of Big Data analytics and its applications, reporting mechanisms and public safety measures. The research model defines key factors in assessing the effectiveness of Korea's responses. Findings: Findings of this research suggest: effective strategic planning and operational execution use well-tested and designed crisis-responsive manuals;linkage role of ICT/Big Data is prominent in trace, test and treat and participation (3T + P);and aggressive epidemic investigations require synergistic efforts of national and local government units, broad societal support and participation and contribution of global firms offering their domestic and global supply chain network capabilities. Research limitations/implications: The Korean Government's effective response experiences suggest the synergy of political, social, cultural and technological factors. Future studies may explore how personal privacy and public safety are both achieved in different social–cultural–political contexts (Ahn et al., 2020;Delgado et al., 2020;Sharma and Bashir, 2020). Other emerging organizational issues and international comparative studies are worth further investigation in future studies. Practical implications: This case study suggests how to apply ICT capabilities for organizing a national response to the coronavirus pandemic (COVID-19) pandemic. Public and private partnership in the framework of sociotechnological synergy (i.e. integration of ICT and social orchestration) is essential for the 3T process. In support of public policy initiatives, global firms share their IT infrastructure and supply chain integration experiences to accommodate global-level crises like the COVID-19 pandemic. Social implications: This study extends the TMC framework to a national level. In the adapted TMC framework, the control source, control target and linkage mechanism are specified. Using TMC, this shows the dynamic roles of ICT/Big Data in Korea's COVID-19 response experiences. Originality/value: The impacts of the COVID-19 are rapid and enormous. Despite the controversial early policy decisions and the rapid rise of confirmed patients, the world has recognized Korea's effective responses to the COVID-19 pandemic. © 2023, Emerald Publishing Limited.

COVID-19 Vaccine Uptake by Infection Status in New South Wales, Australia.

Using linked public health data from Australia to measure uptake of COVID-19 vaccination by infection status, we found coverage considerably lower among infected than uninfected persons for all ages. Increasing uptake of scheduled doses, including among previously infected persons after the recommended postinfection delay, is needed to reduce COVID-19 illness rates.

Telemonitoring of the Continuum of Care of Hepatitis C During the COVID-19 Pandemic in Brazil.

Introduction: To accomplish elimination of hepatitis C virus (HCV) by 2030, as proposed by the World Health Organization, the Brazilian Ministry of Health outlined the Hepatitis C Elimination Plan, which provides coverage of all critical steps in the continuum of care (CoC) of hepatitis C. As expected, the advent of COVID-19 pandemic has disrupted the CoC of hepatitis C worldwide. The Brazilian Liver Institute launched a remote patient monitoring (RPM) program to assist the general population at risk in HCV testing and to provide linkage and retention to care for HCV-positive subjects. The RPM program was also designed to relink HCV-positive patients lost to follow-up during the COVID-19 pandemic due to their limited access to the health care system. Methods: The HCV telemonitoring number was highly advertised in Brazilian media. The RPM program was conducted by dedicated health care personnel trained to follow a predefined script designed to provide awareness, ensure consistent information for educational purposes, and recruit eligible participants to be tested for HCV. Results: From August 2020 to December 2021, 3,738 subjects entered in contact with RPM. There were 26,884 interactions (mean 7.2 interactions per participant), mostly by WhatsApp (78%). Twenty out of those 221 subjects (9%) who tested were HCV positive. Those subjects altogether with 128 other patients with HCV, tested elsewhere, were followed in the HCV CoC. Up to now, 94% of them were linked to care, 24% are undergoing treatment and 8% achieved sustained virological response (SVR). Conclusions: Our preliminary results showed that HCV CoC telemonitoring was a feasible and useful strategy to follow HCV at-risk subjects through all cascade of care until SVR during the COVID-19 health care disruption. It could be used beyond the defervescence of SARS-CoV-2 pandemic to ensure linkage to care of those HCV-positive patients.

Utilizing Policy and Electronic Health Record (EHR) System Modifications to Implement and Sustain Routine Opt-Out HIV Screening and Linkage to Care During the COVID-19 Pandemic.

The burden of HIV infection disproportionately impacts Black people across the United States. New York City (NYC) has taken substantial steps to End the HIV Epidemic, boasting reductions in new HIV infections by 40% since 2015; however, racial inequities persist. In 2019, Black people living in NYC accounted for 24% of the population, yet represented 46.1% of new HIV diagnoses and 48.7% of HIV deaths. To address the high incidence of HIV in a predominately Black community in Central Brooklyn, Brookdale Hospital Medical Center (BHMC) developed a multi-faceted approach to increase routine opt-out HIV screening and linkage. In order to integrate HIV testing into routine clinical care, BHMC leadership updated screening policies; developed an Electronic Health Record (EHR) algorithm to trigger HIV screening in five BHMC ambulatory clinics; and modified the EHR to transmit positive HIV screening results to patient navigators dedicated to linking patients to HIV care. During the height of the COVID-19 pandemic, between March and April 2020, HIV screening across all five ambulatory sites decreased by 87.3%. After activation of the EHR algorithm in three ambulatory sites in June 2020, HIV screening increased 216.3% from the prior month. By the time the final EHR algorithm launched in August 2020, HIV testing had fully rebounded to pre-pandemic levels. Policies supporting routine opt-out HIV screening coupled with EHR-prompted screening can improve and sustain HIV testing in a Black community with a high incidence and prevalence of HIV.

Linkage Disequilibrium in Targeted Sequencing

We propose an approach for optimizing the development of gene diagnostic panels, which is based on the construction of non-equilibrium linkage maps. In the process of gene selection we essentially use genome-wide association analysis (GWAS). Whole-genome analysis of associations makes it possible to reveal the relationship of genomic variants with the studied phenotype. However, the nucleotide variants that showed the highest degree of association can only be statistically associated with the phenotype, not being the true cause of the phenotype. In this case, they may be in the block of linked inheritance with nucleotide variants that really affect the manifestation of the phenotype. The construction of maps of non-equilibrium linkage of nucleotides makes it possible to optimally determine the boundaries of linkage blocks, in which the desired variants fall. The aim of this study was to optimize the demarcation of genomic loci to create targeted panels aimed at predicting susceptibility to SARS-CoV-2 and the severity of COVID-19. The proposed method for selecting loci for a target panel, taking into account nonequilibrium linkage, makes it possible to use the phenomenon of nonequilibrium linkage in order to maximally cover the regions involved in the development of the phenotype, while simultaneously minimizing the length of these regions, and, at the same time, the cost of sequencing © 2022, Mathematical Biology and Bioinformatics.All Rights Reserved.

Linkage Disequilibrium in Targeted Sequencing

We propose an approach for optimizing the development of gene diagnostic panels, which is based on the construction of non-equilibrium linkage maps. In the process of gene selection we essentially use genome-wide association analysis (GWAS). Whole-genome analysis of associations makes it possible to reveal the relationship of genomic variants with the studied phenotype. However, the nucleotide variants that showed the highest degree of association can only be statistically associated with the phenotype, not being the true cause of the phenotype. In this case, they may be in the block of linked inheritance with nucleotide variants that really affect the manifestation of the phenotype. The construction of maps of non-equilibrium linkage of nucleotides makes it possible to optimally determine the boundaries of linkage blocks, in which the desired variants fall. The aim of this study was to optimize the demarcation of genomic loci to create targeted panels aimed at predicting susceptibility to SARS-CoV-2 and the severity of COVID-19. The proposed method for selecting loci for a target panel, taking into account nonequilibrium linkage, makes it possible to use the phenomenon of nonequilibrium linkage in order to maximally cover the regions involved in the development of the phenotype, while simultaneously minimizing the length of these regions, and, at the same time, the cost of sequencing © 2022, Mathematical Biology and Bioinformatics.All Rights Reserved.

Identifying Variability in U.S. COVID-19 Response Through Temporal Partial Ordering Detection

We gain insight to the COVID-19 pandemic response by the various U.S. states through analysis of open source emergency declaration, mitigation, and response policy data. We propose ASNM + POD, a Partial Ordering Detection extension to the Adaptive Sorted Neighborhood Method to identify redundancies and implied temporal ordering requirements to understand how various U.S. states respond to COVID-19. We further strengthen the well-established ASNM entity matching method and address key limitations of its Longest Common Subsequence extension (ASNM + LCS) through detection of all temporal order requirements. Partial order requirements are determined probabilistically through empirical review of all records' time-ordered event sequences. We demonstrate effectiveness against a COVID-19 U.S. state policy dataset comprised of daily time-series data pulled from February and October 2022, where attributes are partially and variably populated. ASNM + POD yielded an F1 of 0.995 and an MCC of 0.985, significantly outperforming both ASNM and ASNM + LCS with F1/MCC improvements of 22%/50% and 15%/37%, respectively. Finally, we highlight the limited consensus on policies enacted, the variability in timelines of policy activations/deactivations, and activity at and after the two-year mark. © 2022 IEEE.