Using machine learning to improve bovine tuberculosis control in herd level outbreaks.

Bovine tuberculosis (bTB), a chronic disease of cattle, is caused by the Mycobacterium bovis infection. Despite having a serious social and economic impact in the United Kingdom and Ireland, there is no antemortem gold standard diagnostic test. Tuberculin skin tests (CICT) are commonly used as a control measure with the interferon gamma (IFN-γ) assay being applied in certain circumstances. This paper utilizes data gathered describing tuberculin regression in reactors (test positive cattle) following the CICT at 72 ± 4 h post injection in herds with large bTB outbreaks. The work then applies machine learning techniques (Decision Trees, Bagging Trees and Random Forests, alongside several balancing approaches) to predict which cattle were likely to be truly infected with tuberculosis, enabling identification of atypical breakdowns that require extra investigation and providing a mechanism for quality assurance of the existing CICT bTB surveillance scheme. The analysis showed that Random Forests (RF) trained using SMOTE balancing had the joint best performance and accuracy (0.90). The importance of the two components of the interferon gamma assay within the RF model also indicated that varying the assay threshold for large outbreaks would be beneficial. Furthermore, the combined use of the RF and IFN- γ models could lead to the improved detection of infection within breakdown herds, reducing the scale and duration of outbreaks. An additional use of these models would be for quality assuring the current bTB surveillance based on CICT and post mortem inspection. Quality control is well recognized as an essential component of a disease surveillance/eradication programme.Clinical Relevance- Bovine tuberculosis remains a disease that is hard to control on a national level. The use of the machine learning model could lead to significant improved detection of infection within breakdown herds, reducing the scale and duration of outbreaks. Advanced modelling, such as this, has the potential to strengthen the efficacy of disease surveillance and the eradication strategy and can meaningfully contribute to animal disease national control plans.

Examining provincial PrEP coverage and characterizing PrEP awareness and use among gay, bisexual and other men who have sex with men in Vancouver, Toronto and Montreal, 2017-2020.

INTRODUCTION: Accessibility of pre-exposure prophylaxis (PrEP) in Canada remains complex as publicly funded coverage and delivery differs by province. In January 2018, PrEP became publicly funded and free of charge in British Columbia (BC), whereas PrEP coverage in Ontario and Montreal is more limited and may require out-of-pocket costs. We examined differences over time in PrEP uptake and assessed factors associated with PrEP awareness and use. METHODS: Gay, bisexual and other men who have sex with men (GBM) were recruited through respondent-driven sampling (RDS) in Toronto, Vancouver and Montreal, Canada, in a prospective biobehavioural cohort study. We applied generalized estimating equations with hierarchical data (RDS chain, participant, visit) to examine temporal trends of PrEP use and correlates of PrEP awareness and use from 2017 to 2020 among self-reported HIV-negative/unknown GBM. RESULTS: Of 2008 self-identified HIV-negative/unknown GBM at baseline, 5093 study visits were completed from February 2017 to March 2020. At baseline, overall PrEP awareness was 88% and overall PrEP use was 22.5%. During our study period, we found PrEP use increased in all cities (all p<0.001): Montreal 14.2% during the first time period to 39.3% during the last time period (p<0.001), Toronto 21.4-31.4% (p<0.001) and Vancouver 21.7-59.5% (p<0.001). Across the study period, more Vancouver GBM used PrEP than Montreal GBM (aOR = 2.05, 95% CI = 1.60-2.63), with no significant difference between Toronto and Montreal GBM (aOR = 0.90, 95% CI = 0.68-1.18). CONCLUSIONS: Full free-of-charge public funding for PrEP in BC likely contributed to differences in PrEP awareness and use. Increasing public funding for PrEP will improve accessibility and uptake among GBM most at risk of HIV.

The regression of the bovine tuberculin reaction: Results from the Reactor Quality Assurance study in Northern Ireland.

Tuberculin skin tests remain widely used in the control of bovine tuberculosis (bTB) in cattle. Little is known about the rate of regression of tuberculin reactions after the comparative intradermal cervical test (CICT) in cattle. This study aimed to collect data to describe tuberculin regression in reactors following the CICT at 72 ± 4 h post injection. Reactors were also tested using the interferon gamma (IFN-γ) assay to establish if any pattern existed between these results and the CICT reaction regression. The data were derived from 108 herds, 112 herd-level CICTs and 1008 animals. A multivariable linear mixed model was built to explore the regression of the bovine tuberculin reaction over time and the influence of potential predictors. The results confirmed a proportional decline in the bovine tuberculin reaction occurred over time. The predictors in the final model demonstrated that regression of the tuberculin reaction differed between reactors according to their IFN-γ test results and whether visible lesions were present at slaughter. Follow-up measurement of tuberculin reactions and the serial use of the IFN-γ assay in large breakdowns has the potential to provide both a mechanism for quality assurance of the current CICT bTB surveillance and the identification of atypical breakdowns or reactors requiring further investigation.

A Peer-Based Strategy to Overcome HPV Vaccination Inequities in Rural Communities: A Physical Distancing-Compliant Approach.

The human papilloma virus (HPV) vaccine is the world's first proven and effective vaccine to prevent cancers in males and females when administered pre-exposure. Like most of the US, barely half of Vermont teens are up-to-date with the vaccination, with comparable deficits in New Hampshire and Maine. The rates for HPV vaccine initiation and completion are as low as 33% in rural New England. Consequently, there is a compelling responsibility to communicate its importance to unvaccinated teenagers before their risk for infection increases. Messaging in rural areas promoting HPV vaccination is compromised by community-based characteristics that include access to appropriate medical care, poor media coverage, parental and peer influence, and skepticism of science and medicine. Current strategies are predominantly passive access to literature and Internet-based information. Evidence indicates that performance-based messaging can clarify the importance of HPV vaccination to teenagers and their parents in rural areas. Increased HPV vaccination will significantly contribute to the prevention of a broadening spectrum of cancers. Reducing rurality-based inequities is a public health priority. Development of a performance-based peer-communication intervention can capture a window of opportunity to provide increasingly effective and sustained HPV protection. An effective approach can be partnering rural schools and regional health teams with a program that is nimble and scalable to respond to public health policies and practices compliant with COVID-19 pandemic-related modifications on physical distancing and interacting in the foreseeable future.

Identification of BACH2 and RAD51B as rheumatoid arthritis susceptibility loci in a meta-analysis of genome-wide data.

OBJECTIVE: A recent high-density fine-mapping (ImmunoChip) study of genetic associations in rheumatoid arthritis (RA) identified 14 risk loci with validated genome-wide significance, as well as a number of loci showing associations suggestive of significance (P = 5 × 10(-5) < 5 × 10(-8)), but these have yet to be replicated. The aim of this study was to determine whether these potentially significant loci are involved in the pathogenesis of RA, and to explore whether any of the loci are associated with a specific RA serotype. METHODS: A total of 16 single-nucleotide polymorphisms (SNPs) were selected for genotyping and association analyses in 2 independent validation cohorts, comprising 6,106 RA cases and 4,290 controls. A meta-analysis of the data from the original ImmunoChip discovery cohort and from both validation cohorts was carried out, for a combined total of 17,581 RA cases and 20,160 controls. In addition, stratified analysis of patient subsets, defined according to their anti-cyclic citrullinated peptide (anti-CCP) antibody status, was performed. RESULTS: A significant association with RA risk (P < 0.05) was replicated for 6 of the SNPs assessed in the validation cohorts. All SNPs in the validation study had odds ratios (ORs) for RA susceptibility in the same direction as those in the ImmunoChip discovery study. One SNP, rs72928038, mapping to an intron of BACH2, achieved genome-wide significance in the meta-analysis (P = 1.2 × 10(-8), OR 1.12), and a second SNP, rs911263, mapping to an intron of RAD51B, was significantly associated in the anti-CCP-positive RA subgroup (P = 4 × 10(-8), OR 0.89), confirming that both are RA susceptibility loci. CONCLUSION: This study provides robust evidence for an association of RA susceptibility with genes involved in B cell differentiation (BACH2) and DNA repair (RAD51B). The finding that the RAD51B gene exhibited different associations based on serologic subtype adds to the expanding knowledge base in defining subgroups of RA.

High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis.

Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

Genetics of rheumatoid arthritis: GWAS and beyond.

The study of complex genetics in autoimmune diseases has progressed at a tremendous pace over the last 4 years, as a direct result of the enormous gains made by genome wide association studies (GWAS). Novel genetic findings are continuously being reported alongside the rapid development of genetic technologies, sophisticated statistical analysis, and larger sample collections. It is now becoming clear that multiple genes contribute to disease risk in many complex genetic disorders including rheumatoid arthritis (RA) and that there are common genetic risk factors that underlie a spectrum of autoimmune diseases. This review details the current genetic landscape of RA, and describes what GWAS has taught us in terms of missing heritability, subsets of disease, existence of genetic heterogeneity, and shared autoimmune risk loci. Finally, this review addresses the initial challenges faced in translating the wealth of genetic findings into determining the biological mechanisms that contribute to the relationship between genotype and phenotype. Unraveling the mechanism of how genes directly influence the cause of RA will lead to a better understanding of the disease and will ultimately have a direct clinical impact, informing the development of new therapies that can be utilized in the treatment of RA.

Evaluating the quality of research into a single prognostic biomarker: a systematic review and meta-analysis of 83 studies of C-reactive protein in stable coronary artery disease.

BACKGROUND: Systematic evaluations of the quality of research on a single prognostic biomarker are rare. We sought to evaluate the quality of prognostic research evidence for the association of C-reactive protein (CRP) with fatal and nonfatal events among patients with stable coronary disease. METHODS AND FINDINGS: We searched MEDLINE (1966 to 2009) and EMBASE (1980 to 2009) and selected prospective studies of patients with stable coronary disease, reporting a relative risk for the association of CRP with death and nonfatal cardiovascular events. We included 83 studies, reporting 61,684 patients and 6,485 outcome events. No study reported a prespecified statistical analysis protocol; only two studies reported the time elapsed (in months or years) between initial presentation of symptomatic coronary disease and inclusion in the study. Studies reported a median of seven items (of 17) from the REMARK reporting guidelines, with no evidence of change over time. The pooled relative risk for the top versus bottom third of CRP distribution was 1.97 (95% confidence interval [CI] 1.78-2.17), with substantial heterogeneity (I(2) = 79.5). Only 13 studies adjusted for conventional risk factors (age, sex, smoking, obesity, diabetes, and low-density lipoprotein [LDL] cholesterol) and these had a relative risk of 1.65 (95% CI 1.39-1.96), I(2) = 33.7. Studies reported ten different ways of comparing CRP values, with weaker relative risks for those based on continuous measures. Adjusting for publication bias (for which there was strong evidence, Egger's p<0.001) using a validated method reduced the relative risk to 1.19 (95% CI 1.13-1.25). Only two studies reported a measure of discrimination (c-statistic). In 20 studies the detection rate for subsequent events could be calculated and was 31% for a 10% false positive rate, and the calculated pooled c-statistic was 0.61 (0.57-0.66). CONCLUSION: Multiple types of reporting bias, and publication bias, make the magnitude of any independent association between CRP and prognosis among patients with stable coronary disease sufficiently uncertain that no clinical practice recommendations can be made. Publication of prespecified statistical analytic protocols and prospective registration of studies, among other measures, might help improve the quality of prognostic biomarker research.