U.S. medical resident familiarity with national tuberculosis guidelines

<p>Abstract</p> <p>Background</p> <p>The ability of medical residents training at U.S. urban medical centers to diagnose and manage tuberculosis cases has important public health implications. We assessed medical resident knowledge about tuberculosis diagnosis and early management based on American Thoracic Society guidelines.</p> <p>Methods</p> <p>A 20-question tuberculosis knowledge survey was administered to 131 medical residents during a single routinely scheduled teaching conference at four different urban medical centers in Baltimore and Philadelphia. Survey questions were divided into 5 different subject categories. Data was collected pertaining to institution, year of residency training, and self-reported number of patients managed for tuberculosis within the previous year. The Kruskal-Wallis test was used to detect differences in median percent of questions answered correctly based on these variables.</p> <p>Results</p> <p>The median percent of survey questions answered correctly for all participating residents was 55%. Medical resident knowledge about tuberculosis did not improve with increasing post-graduate year of training or greater number of patients managed for tuberculosis within the previous year. Common areas of knowledge deficiency included the diagnosis and management of latent tuberculosis infection (median percent correct, 40.7%), as well as the interpretation of negative acid-fast sputum smear samples.</p> <p>Conclusion</p> <p>Many medical residents lack adequate knowledge of recommended guidelines for the management of tuberculosis. Since experience during training influences future practice pattterns, education of medical residents on guidelines for detection and early management of tuberculosis may be important for future improvements in national tuberculosis control strategies.</p

Using combined diagnostic test results to hindcast trends of infection from cross-sectional data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time