A simple model for the evolution of the rate of molecular evolution is presented. With a Bayesian approach, this model can serve as the basis for estimating dates of important evolutionary events even in the absence of the assumption of constant rates among evolutionary lineages. The method can be used in conjunction with any of the widely used models for nucleotide substitution or amino acid replacement. It is illustrated by analyzing a data set of rbcL protein sequences.

Genome-wide scans of nucleotide variation in human subjects are providing an increasing number of replicated associations with complex disease traits. Most of the variants detected have small effects and, collectively, they account for a small fraction of the total genetic variance. Very large sample sizes are required to identify and validate findings. In this situation, even small sources of systematic or random error can cause spurious results or obscure real effects. The need for careful attention to data quality has been appreciated for some time in this field, and a number of strategies for quality control and quality assurance (QC/QA) have been developed. Here we extend these methods and describe a system of QC/QA for genotypic data in genome-wide association studies. This system includes some new approaches that (1) combine analysis of allelic probe

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Background A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) Identify public health user needs and preferences for infectious disease information visualization tools; (2) Identify existing infectious disease information visualization tools and characterize their architecture and features; (3) Identify commonalities among approaches applied to different data types; and (4) Describe tool usability evaluation efforts and barriers to the adoption of such tools. Methods We identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review. Results A total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool use. Discussion and Conclusion As the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload.

GWASTools is an R/Bioconductor package for quality control and analysis of genome-wide association studies (GWAS). GWASTools brings the interactive capability and extensive statistical libraries of R to GWAS. Data are stored in NetCDF format to accommodate extremely large datasets that cannot fit within R's memory limits. The documentation includes instructions for converting data from multiple formats, including variants called from sequencing. GWASTools provides a convenient interface for linking genotypes and intensity data with sample and single nucleotide polymorphism annotation.

Background: The usefulness of syndromic surveillance for early outbreak detection depends in part on effective statistical aberration detection. However, few published studies have compared different detection algorithms on identical data. In the largest simulation study conducted to date, we compared the performance of six aberration detection algorithms on simulated outbreaks superimposed on authentic syndromic surveillance data.

BackgroundHealth care providers play a significant role in large scale health emergency planning, detection, response, recovery and communication with the public. The effectiveness of health care providers in emergency preparedness and response roles depends, in part, on public health agencies communicating information in a way that maximizes the likelihood that the message is delivered, received, deemed credible and, when appropriate, acted on. However, during an emergency, health care providers can become inundated with alerts and advisories through numerous national, state, local and professional communication channels. We conducted an alert fatigue study as a sub-study of a larger randomized controlled trial which aimed to identify the most effective methods of communicating public health messages between public health agencies and providers. We report an analysis of the effects of public health message volume/frequency on recall of specific message content and effect of rate of message communications on health care provider alert fatigue.MethodsHealth care providers enrolled in the larger study (n=528) were randomized to receive public health messages via email, fax, short message service (SMS or cell phone text messaging) or to a control group that did not receive messages. For 12 months, study messages based on real events of public health significance were sent quarterly with follow-up telephone interviews regarding message receipt and topic recall conducted 5–10 days after the message delivery date. During a pandemic when numerous messages are sent, alert fatigue may impact ability to recall whether a specific message has been received due to the “noise” created by the higher number of messages. To determine the impact of “noise” when study messages were sent, we compared health care provider recall of the study message topic to the number of local public health messages sent to health care providers.ResultsWe calculated the mean number of messages that each provider received from local public health during the time period around each study message and provider recall of study message content. We found that recall rates were inversely proportional to the mean number of messages received per week: Every increase of one local public health message per week resulted in a statistically significant 41.2% decrease (p < 0.01), 95% CI [0.39, .87] in the odds of recalling the content of the study message.ConclusionsTo our knowledge, this is the first study to document the effects of alert fatigue on health care providers’ recall of information. Our results suggest that information delivered too frequently and/or repetitively through numerous communication channels may have a negative effect on the ability of health care providers to effectively recall emergency information. Keeping health care providers and other first-line responders informed during an emergency is critical. Better coordination between organizations disseminating alerts, advisories and other messages may improve the ability of health care provid...

Study Design. The enhanced perioperative care (EPOC) program is an institutional quality improvement initiative. We used a historically controlled study design to evaluate patients who underwent major spine surgery before and after the implementation of the EPOC program. Objective. To determine whether multidisciplinary EPOC program was associated with an improvement in clinical and financial outcomes for elective adult major spine surgery patients. Summary of Background Data. The enhanced recovery after surgery (ERAS) programs successfully implemented in hip and knee replacement surgeries, and improved clinical outcomes and patient satisfaction. Methods. We compared 183 subjects in traditional care (TRDC) group to 267 intervention period (EPOC) in a single academic quaternary spine surgery referral center. One hundred eight subjects in no pathway (NOPW) care group was also examined to exclude if the observed changes between the EPOC and TRDC groups might be due to concurrent changes in practice or population over the same time period. Our primary outcome variables were hospital and intensive care unit lengths of stay and the secondary outcomes were postoperative complications, 30-day hospital readmission and cost. Results. In this highly complex patient population, we observed a reduction in mean hospital length of stay (HLOS) between TRDC versus EPOC groups (8.2 vs. 6.1 d, standard deviation [SD] = 6.3 vs. 3.6, P < 0.001) and intensive care unit length of stay (ILOS) (3.1 vs. 1.9 d, SD = 4.7 vs. 1.4, P = 0.01). The number (rate) of postoperative intensive care unit (ICU) admissions was higher for the TRDC n = 109 (60%) than the EPOC n = 129 (48%) (P = 0.02). There was no difference in postoperative complications and 30-day hospital readmissions. The EPOC spine program was associated with significant average cost reduction—$62,429 to $53,355 (P < 0.00). Conclusion. The EPOC program has made a clinically relevant contribution to institutional efforts to improve patient outcomes and value. We observed a reduction in HLOS, ILOS, costs, and variability. Level of Evidence: 3