Time series modeling for syndromic surveillance

BACKGROUND: Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED) visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. METHODS: Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA) residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. RESULTS: Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. CONCLUSIONS: Time series methods applied to historical ED utilization data are an important tool for syndromic surveillance. Accurate forecasting of emergency department total utilization as well as the rates of particular syndromes is possible. The multiple models in the system account for both long-term and recent trends, and an integrated alarms strategy combining these two perspectives may provide a more complete picture to public health authorities. The systematic methodology described here can be generalized to other healthcare settings to develop automated surveillance systems capable of detecting anomalies in disease patterns and healthcare utilization

Global genome expression analysis of rice in response to drought and high-salinity stresses in shoot, flag leaf, and panicle

To elucidate genome-level responses to drought and high-salinity stress in rice, a 70mer oligomer microarray covering 36,926 unique genes or gene models was used to profile genome expression changes in rice shoot, flag leaf and panicle under drought or high-salinity conditions. While patterns of gene expression in response to drought or high-salinity stress within a particular organ type showed significant overlap, comparison of expression profiles among different organs showed largely organ-specific patterns of regulation. Moreover, both stresses appear to alter the expression patterns of a significant number of genes involved in transcription and cell signaling in a largely organ-specific manner. The promoter regions of genes induced by both stresses or induced by one stress in more than one organ types possess relative enrichment of two cis-elements (ABRE core and DRE core) known to be associated with water stress. An initial computational analysis indicated that novel promoter motifs are present in the promoters of genes involved in rehydration after drought. This analysis suggested that rice might possess a mechanism that actively detects rehydration and facilitates rapid recovery. Overall, our data supports a notion that organ-specific gene regulation in response to the two abiotic stresses may primarily be mediated by organ-specific transcription responses. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11103-006-9111-1) contains supplementary material, which is available to authorized users

Cognitive and Psychological Reactions of the General Population Three Months After the 2011 Tohoku Earthquake and Tsunami

BACKGROUND: The largest earthquake on record in Japan (magnitude 9.0) occurred on March 11, 2011, and the subsequent tsunami devastated the Pacific coast of Northern Japan. These further triggered the Fukushima I nuclear power plant accidents. Such a hugely complex disaster inevitably has negative psychological effects on general populations as well as on the direct victims. While previous disaster studies enrolled descriptive approaches focusing on direct victims, the structure of the psychological adjustment process of people from the general population has remained uncertain. The current study attempted to establish a path model that sufficiently reflects the early psychological adaptation process of the general population to large-scale natural disasters. METHODS AND FINDINGS: Participants from the primary disaster area (n = 1083) and other areas (n = 2372) voluntarily participated in an online questionnaire study. By constructing path models using a structural equation model procedure (SEM), we examined the structural relationship among psychological constructs known related to disasters. As post-traumatic stress symptoms (PTS) were significantly more present in people in the primarily affected area than in those in secondary- or non-affected areas, the path models were constructed for the primary victims. The parsimoniously depicted model with the best fit was achieved for the psychological-adjustment centered model with quality of life (QoL) as a final outcome. CONCLUSION: The paths to QoL via negative routes (from negative cognitive appraisal, PTS, and general stress) were dominant, suggesting the importance of clinical intervention for reducing negative cognitive appraisal, and for caring for general stress and PTS to maintain QoL at an early stage of psychological adaptation to a disaster. The model also depicted the presence of a positive route where positive cognitive appraisal facilitates post-traumatic growth (PTG) to achieve a higher QoL, suggesting the potential importance of positive psychological preventive care for unexpected natural disasters

Photometric and radial-velocity time-series of RR Lyrae stars in M3: analysis of single-mode variables (vol 468, pg 1317, 2017)

status: publishe