Judy Henry, P. Murphy, Janet Pichette, David Anderson, Heather Cooks-Sinclair
{"title":"Natural disasters and use of syndromic surveillance: Austin, Texas Metro Area 2011","authors":"Judy Henry, P. Murphy, Janet Pichette, David Anderson, Heather Cooks-Sinclair","doi":"10.3402/EHTJ.V4I0.11194","DOIUrl":"https://doi.org/10.3402/EHTJ.V4I0.11194","url":null,"abstract":"","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"85 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78159598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Confusing standards: common misconceptions about disease surveillance standards","authors":"Wayne Loschen","doi":"10.3402/EHTJ.V4I0.11180","DOIUrl":"https://doi.org/10.3402/EHTJ.V4I0.11180","url":null,"abstract":"","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"324 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73143921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Yard, J. Gilchrist, D. Comstock, T. Haileyesus, M. Murphy
{"title":"Using injury surveillance to assess sport- and recreation-related heat illness","authors":"E. Yard, J. Gilchrist, D. Comstock, T. Haileyesus, M. Murphy","doi":"10.3402/ehtj.v4i0.11043","DOIUrl":"https://doi.org/10.3402/ehtj.v4i0.11043","url":null,"abstract":"","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"92 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87496408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Cheek, Aneel A. Advani, B. Reilley, F. Hack, Amy V. Groom, J. Hayslett, J. Redd, J. Keck, T. Cullen
{"title":"Use of an electronic health record system for public health surveillance","authors":"J. Cheek, Aneel A. Advani, B. Reilley, F. Hack, Amy V. Groom, J. Hayslett, J. Redd, J. Keck, T. Cullen","doi":"10.3402/ehtj.v4i0.11115","DOIUrl":"https://doi.org/10.3402/ehtj.v4i0.11115","url":null,"abstract":"","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86540237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Painter, J. Eaton, D. Olson, William Lober, D. Revere
{"title":"Visualizing data quality: tools and views","authors":"I. Painter, J. Eaton, D. Olson, William Lober, D. Revere","doi":"10.3402/EHTJ.V4I0.11144","DOIUrl":"https://doi.org/10.3402/EHTJ.V4I0.11144","url":null,"abstract":"","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83024357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluating the relationship between heat-related ED visits and weather variables","authors":"B. Storm, B. Fowler","doi":"10.3402/EHTJ.V4I0.11080","DOIUrl":"https://doi.org/10.3402/EHTJ.V4I0.11080","url":null,"abstract":"","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89845165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Spatial and Temporal Anatomy of Seasonal Influenza in the United States, 1968-2008 Bianca Malcolm Seasonality has a major effect on the spatiotemporal dynamics of natural systems and their populations and is a driving force behind the transmission of influenza in temperate regions. Although the seasonality of influenza in temperate countries is widely recognized, inter-state spread of influenza in the United States has not been well characterized. This dissertation characterized the seasonality of influenza throughout the United States by using monthly pneumonia and influenza (P&I) mortality to model inter-state movement of seasonal influenza in the continental United States between 1968 and 2008. The first chapter summarizes the current knowledge of the burden, morphology, and geography of influenza as well as limitations of prior studies. In the second chapter, weekly data on laboratory-confirmed influenza isolates from a national viral surveillance system (considered the “gold standard”) is compared with weekly pneumonia and influenza (P&I) mortality data from a national mortality surveillance system in order to determine if the timing of mortality data correlated well with the timing of viral surveillance data and was, therefore, a good measurement for determining the timing of annual influenza epidemics. Sufficient viral surveillance data for influenza is not available for the majority of the study period and its quality most likely varies geographically. This made it necessary for this study to use mortality data as a substitute. It was, therefore, critical for this dissertation to assess the reliability of mortality data as a measurement to determine the timing of annual influenza waves. In the third chapter, an analysis of monthly P&I mortality data was conducted to identify an average underlying wave of seasonal influenza spread in the United States, the spatial and temporal patterns of seasonal influenza in the U.S. from 1968 to 2008, and the dependence of the timing and spread of influenza on the dominant circulating influenza type or subtype in a given influenza season. Source locations of influenza transmission in the U.S. were also identified. The dependence of the spread process of seasonal influenza in the U.S. on distance and/or population was assessed in chapter four. Additionally, spatial clusters of P&I mortality rates at different phases of an average influenza wave were identified. An assessment of the effect of the introduction or reintroduction of a novel influenza virus subtype on the spatio-temporal dynamics of influenza spread in the U.S. was performed in the fifth chapter. In the sixth and final chapter, I conclude by summarizing the findings of these four studies. This research found that P&I mortality was a valid measure used to assess the timing of influenza epidemics. Additionally, seasonal influenza in the U.S. typically began in November, peaked in February, and ceased in May. Annual influenza epidemics laste
{"title":"The spatial and temporal anatomy of seasonal influenza in the United States, 1972–2007","authors":"Bianca Malcolm, S. Morse","doi":"10.3402/EHTJ.V4I0.11013","DOIUrl":"https://doi.org/10.3402/EHTJ.V4I0.11013","url":null,"abstract":"The Spatial and Temporal Anatomy of Seasonal Influenza in the United States, 1968-2008 Bianca Malcolm Seasonality has a major effect on the spatiotemporal dynamics of natural systems and their populations and is a driving force behind the transmission of influenza in temperate regions. Although the seasonality of influenza in temperate countries is widely recognized, inter-state spread of influenza in the United States has not been well characterized. This dissertation characterized the seasonality of influenza throughout the United States by using monthly pneumonia and influenza (P&I) mortality to model inter-state movement of seasonal influenza in the continental United States between 1968 and 2008. The first chapter summarizes the current knowledge of the burden, morphology, and geography of influenza as well as limitations of prior studies. In the second chapter, weekly data on laboratory-confirmed influenza isolates from a national viral surveillance system (considered the “gold standard”) is compared with weekly pneumonia and influenza (P&I) mortality data from a national mortality surveillance system in order to determine if the timing of mortality data correlated well with the timing of viral surveillance data and was, therefore, a good measurement for determining the timing of annual influenza epidemics. Sufficient viral surveillance data for influenza is not available for the majority of the study period and its quality most likely varies geographically. This made it necessary for this study to use mortality data as a substitute. It was, therefore, critical for this dissertation to assess the reliability of mortality data as a measurement to determine the timing of annual influenza waves. In the third chapter, an analysis of monthly P&I mortality data was conducted to identify an average underlying wave of seasonal influenza spread in the United States, the spatial and temporal patterns of seasonal influenza in the U.S. from 1968 to 2008, and the dependence of the timing and spread of influenza on the dominant circulating influenza type or subtype in a given influenza season. Source locations of influenza transmission in the U.S. were also identified. The dependence of the spread process of seasonal influenza in the U.S. on distance and/or population was assessed in chapter four. Additionally, spatial clusters of P&I mortality rates at different phases of an average influenza wave were identified. An assessment of the effect of the introduction or reintroduction of a novel influenza virus subtype on the spatio-temporal dynamics of influenza spread in the U.S. was performed in the fifth chapter. In the sixth and final chapter, I conclude by summarizing the findings of these four studies. This research found that P&I mortality was a valid measure used to assess the timing of influenza epidemics. Additionally, seasonal influenza in the U.S. typically began in November, peaked in February, and ceased in May. Annual influenza epidemics laste","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90371528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. M. Velasco, V. Roque, J. Coberly, R. Wojcik, Charles J. Hodanics, June Corpuz, Sheri H. Lewis, I. Yoon
{"title":"Applications of the ESSENCE Desktop Edition for outbreak detection in a resource-limited setting","authors":"J. M. Velasco, V. Roque, J. Coberly, R. Wojcik, Charles J. Hodanics, June Corpuz, Sheri H. Lewis, I. Yoon","doi":"10.3402/EHTJ.V4I0.11101","DOIUrl":"https://doi.org/10.3402/EHTJ.V4I0.11101","url":null,"abstract":"","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"193 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77028082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction The Public Health*Seattle & King County (PHSKC) syndromic surveillance system has been collecting emergency department (ED) data since 1999. These data include hospital name, age, sex, zip code, chief complaint, diagnoses (when available), disposition and a patient and visit key. Data are collected for 19 of 20 King County EDs, for visits that occurred the previous day. Over time, various problems with data quality have been encountered, including data drop-offs, missing data elements, incorrect values of fields, duplication of data, data delays and unexpected changes in files received from hospitals. In spite of close monitoring of the data as part of our routine syndromic surveillance activities, there have occasionally been delays in identifying these problems. Since the validity of syndromic surveillance is dependent on data quality, we sought to develop a visualization to help monitor data quality over time, in order to improve the timeliness of addressing data quality problems.
{"title":"An information visualization approach to improving data quality","authors":"A. Baer","doi":"10.3402/EHTJ.V4I0.11014","DOIUrl":"https://doi.org/10.3402/EHTJ.V4I0.11014","url":null,"abstract":"Introduction The Public Health*Seattle & King County (PHSKC) syndromic surveillance system has been collecting emergency department (ED) data since 1999. These data include hospital name, age, sex, zip code, chief complaint, diagnoses (when available), disposition and a patient and visit key. Data are collected for 19 of 20 King County EDs, for visits that occurred the previous day. Over time, various problems with data quality have been encountered, including data drop-offs, missing data elements, incorrect values of fields, duplication of data, data delays and unexpected changes in files received from hospitals. In spite of close monitoring of the data as part of our routine syndromic surveillance activities, there have occasionally been delays in identifying these problems. Since the validity of syndromic surveillance is dependent on data quality, we sought to develop a visualization to help monitor data quality over time, in order to improve the timeliness of addressing data quality problems.","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78354749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Pandemic H1N1-related ICU rates according to race/ethnic groups in Massachusetts","authors":"H. Placzek, L. Madoff","doi":"10.3402/EHTJ.V4I0.11058","DOIUrl":"https://doi.org/10.3402/EHTJ.V4I0.11058","url":null,"abstract":"","PeriodicalId":72898,"journal":{"name":"Emerging health threats journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74475544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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