The international epidemiology of Hepatitis Delta Virus (HDV) is challenging to accurately estimate due to limited active surveillance for this rare infectious disease. Prior HDV epidemiological studies have relied on meta-analysis of aggregated and static datasets. These limitations restrict the capacity to actively detect low-level and/or geographically dispersed changes in the incidence of HDV diagnoses. This study was designed to provide a resource to track and analyze the international HDV epidemiology. Datasets analyzed collectively consisted of >700,000 HBV and >9,000 HDV reported cases ranging between 1999–2020. Datasets mined from government publications were identified for Argentina, Australia, Austria, Brazil, Bulgaria, Canada, Finland, Germany, Macao, Netherlands, New Zealand, Norway, Sweden, Taiwan, Thailand, United Kingdom, and United States. Time series analyses, including Mann-Kendall (MK) trend test, Bayesian Information Criterion (BIC), and hierarchal clustering, were performed to characterize trends in the HDV timelines. An aggregated prevalence of 2,560 HDV/HBV100,000 cases (95% CI 180–4940) or 2.56% HDV/HBV cases was identified, ranging from 0.26% in Canada to 20% in the United States. Structural breaks in the timeline of HDV incidence were identified in 2002, 2012, and 2017, with a significant increase occurring between 2013–2017. Significant increasing trends in reported HDV and HBV cases were observed in 47% and 24% of datasets, respectively. Analyses of the HDV incidence timeline identified four distinct temporal clusters, including Cluster I (Macao, Taiwan), Cluster II (Argentina, Brazil, Germany, Thailand), Cluster III (Bulgaria, Netherlands, New Zealand, United Kingdom, United States) and Cluster IV (Australia, Austria, Canada, Finland, Norway, Sweden). Tracking of HDV and HBV cases on an international scale is essential in defining the global impact of viral hepatitis. Significant disruptions of HDV and HBV epidemiology have been identified. Increased surveillance of HDV is warranted to further define the etiology of the recent breakpoints in the international HDV incidence.

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Background Dry mouth currently affects roughly 20% of the population and is a condition characterized by chronic hyposalivation and/or subjective reports of xerostomia. Low saliva flow can be indicative of other undiagnosed diseases, such as primary Sjogren’s syndrome, and may contribute to difficulty chewing, increased caries susceptibility and infection. The passive drool test (PDT) is the primary method used to evaluate patients for hyposalivation but it is time-consuming and inconvenient. New methodology is needed to facilitate increased testing for hyposalivation in the dental clinic. The aim of this study was to evaluate an alternative method to measure salivary flow in dental offices. Methods In this study, we tested a new biomedical device, the BokaFlo™, to measure salivary flow in subjects in comparison to the current PDT standard. Participants completed an oral health questionnaire and saliva flow was evaluated by the PDT and the BokaFlo™ system. Results Saliva flow as measured by the BokaFlo™ positively correlated with the saliva flow measured by the PDT methodology (r = 0.22, p < 0.05). The device predicted low saliva flow in subjects with a sensitivity of 0.76 and specificity of 0.84 for subjects with hyposalivation, defined as a saliva flow rate of ≤ 0.1 ml/min. A significant negative correlation between the total oral health questionnaire score and the likelihood of participant exhibiting low salivary flow was observed (r = − 0.31, p < 0.006). Conclusion The BokaFlo™ was effectively able to measure low saliva flow correlating with the PDT methodology and may provide more efficient testing of saliva flow in the dental office.

BackgroundA significant increase in the yearly incidence of hepatitis delta virus (HDV) diagnosis in hepatitis B virus (HBV) patient populations has been identified through analysis of global infectious disease datasets. Currently, HDV is classified as a non-notifiable infectious disease in many countries around the world. Kuschner et al. reported over 90% of HBV-positive patients are not being tested for HDV (2015). Together, the non-notifiable status of HDV and the noncompliance in testing potential HDV carriers presents a significant barrier in active surveillance of changes in the incidence of HDV. Therefore, a study was designed to evaluate the global incidence of HDV using datamining approaches.MethodsDatasets containing yearly HDV and HBV incidence were utilized in this study including the National Health and Nutritional Examination Survey (NHANES) datasets and 14 additional datasets obtained through data-mining of global infectious disease datasets. These global datasets of reported yearly HDV and HBV diagnoses and demographic data ranging between 1999 and 2016 were analyzed.ResultsEpidemiological analysis of infectious disease datasets from 15 countries identified a significant increase in the incidence of HDV relative to HBV-positive patients starting in 2011. Within the United States, analysis of NHANES datasets identified an increase in the incidence of HDV diagnosis among HBV-positive individuals from 5% in 1999–2010 to 58% in 2016. Comparative analysis of the yearly reported incidence of HDV and HBV in 14 additional countries identified a significant increase in the incidence of HDV in the same time period. Modeling of the collective spatiotemporal profile of the increase in HDV incidence is suggestive of a shared common intermittent exposure pattern of infection. The fastest growing demographic in the HDV-positive populations is in patients greater than 65 years of age.ConclusionOur analysis identified a significant increase in the incidence of HDV diagnoses spanning three continents starting in 2011 and may be suggestive of an alteration in HDV transmission pattern. Active surveillance of HDV in the United States and worldwide is warranted to further define these observed changes in HDV incidence.Disclosures All authors: No reported disclosures.

The On Time education program is an innovative, online point-of-care tool designed to uncover and address barriers to insulin initiation, and to facilitate timely insulin initiation, when appropriate, in insulin-naïve individuals with type 2 diabetes (T2D). A total of 195 health care professionals (HCPs) completed online profiles of 1025 insulin-naïve individuals with T2D currently treated with non-insulin antihyperglycemic agents (NIAHAs) and with a glycated hemoglobin (A1C) above the Diabetes Canada target (for most individuals ≤7%). After having completed the discussion tool and questionnaires, participating HCPs were asked to evaluate the program, tool, and questionnaires. Mean age of participants was 61.2 years; 55% were male; mean duration of diabetes was 10.5 years. For the majority of participants (70%) the recommended A1C target was ≤7.0%. On average, participants were prescribed 2.6 NIAHAs, mainly metformin and dipeptidyl peptidase-4 inhibitors. Prior to using the On Time discussion tool, only 23% of individuals with diabetes were judged as likely (16%) or extremely likely (7%) willing to initiate insulin. The leading barriers to initiating insulin were apprehension toward needles/injections (59%), belief that insulin was complicated (56%), and psychological insulin resistance (45%). After using the On Time discussion tool, participants’ perceived willingness to initiate insulin increased (likely: 34%, extremely likely: 28%). Initiation of insulin was planned in 77% of participating individuals. The evaluation questionnaire was completed by 149 HCPs (76.4%), and showed that the discussion tool was perceived to help HCPs address insulin-related barriers (82%), positively impacted their practice (79%), and improved their approach when discussing insulin initiation with individuals with diabetes (76%). Identifying the barriers to initiating insulin and providing educational interventions to address them may help to improve insulin acceptance. Disclosure J. Gilbert: Other Relationship; Self; AstraZeneca, Boehringer Ingelheim GmbH, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Janssen Pharmaceuticals, Inc., Sanofi. G. MacNeill: Consultant; Self; Becton, Dickinson and Company. Advisory Panel; Self; Janssen Pharmaceuticals, Inc., Eli Lilly and Company, Novo Nordisk Inc.. Consultant; Self; Sanofi. E.M. Cooke: Other Relationship; Self; Abbott. Speaker's Bureau; Self; Becton, Dickinson and Company, LifeScan Canada. Other Relationship; Self; LifeScan Canada. Speaker's Bureau; Self; Merck & Co., Inc.. Advisory Panel; Self; Sanofi. Speaker's Bureau; Self; Sanofi. Other Relationship; Self; Sanofi, mdBriefCase Group.P. Filteau: None. M. Vallis: Speaker's Bureau; Self; Novo Nordisk A/S. Advisory Panel; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; AbbVie Inc.. Advisory Panel; Self; Valeant Pharmaceuticals International, Inc.. Speaker's Bureau; Self; Merck & Co., Inc.. Advisory Panel; Self; Sanofi. Speaker's Bureau; Self; Sanofi. M. Groleau: Employee; Self; Sanofi. P. Javadi: Employee; Self; Sanofi. C. Lebovics: Employee; Self; Sanofi.