Last data update: May 13, 2024. (Total: 46773 publications since 2009)
Records 1-4 (of 4 Records) |
Query Trace: Trapp J[original query] |
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Initial public health response and interim clinical guidance for the 2019 novel coronavirus outbreak - United States, December 31, 2019-February 4, 2020.
Patel A , Jernigan DB , 2019-nCOV CDC Response Team , Abdirizak Fatuma , Abedi Glen , Aggarwal Sharad , Albina Denise , Allen Elizabeth , Andersen Lauren , Anderson Jade , Anderson Megan , Anderson Tara , Anderson Kayla , Bardossy Ana Cecilia , Barry Vaughn , Beer Karlyn , Bell Michael , Berger Sherri , Bertulfo Joseph , Biggs Holly , Bornemann Jennifer , Bornstein Josh , Bower Willie , Bresee Joseph , Brown Clive , Budd Alicia , Buigut Jennifer , Burke Stephen , Burke Rachel , Burns Erin , Butler Jay , Cantrell Russell , Cardemil Cristina , Cates Jordan , Cetron Marty , Chatham-Stephens Kevin , Chatham-Stevens Kevin , Chea Nora , Christensen Bryan , Chu Victoria , Clarke Kevin , Cleveland Angela , Cohen Nicole , Cohen Max , Cohn Amanda , Collins Jennifer , Conners Erin , Curns Aaron , Dahl Rebecca , Daley Walter , Dasari Vishal , Davlantes Elizabeth , Dawson Patrick , Delaney Lisa , Donahue Matthew , Dowell Chad , Dyal Jonathan , Edens William , Eidex Rachel , Epstein Lauren , Evans Mary , Fagan Ryan , Farris Kevin , Feldstein Leora , Fox LeAnne , Frank Mark , Freeman Brandi , Fry Alicia , Fuller James , Galang Romeo , Gerber Sue , Gokhale Runa , Goldstein Sue , Gorman Sue , Gregg William , Greim William , Grube Steven , Hall Aron , Haynes Amber , Hill Sherrasa , Hornsby-Myers Jennifer , Hunter Jennifer , Ionta Christopher , Isenhour Cheryl , Jacobs Max , Jacobs Slifka Kara , Jernigan Daniel , Jhung Michael , Jones-Wormley Jamie , Kambhampati Anita , Kamili Shifaq , Kennedy Pamela , Kent Charlotte , Killerby Marie , Kim Lindsay , Kirking Hannah , Koonin Lisa , Koppaka Ram , Kosmos Christine , Kuhar David , Kuhnert-Tallman Wendi , Kujawski Stephanie , Kumar Archana , Landon Alexander , Lee Leslie , Leung Jessica , Lindstrom Stephen , Link-Gelles Ruth , Lively Joana , Lu Xiaoyan , Lynch Brian , Malapati Lakshmi , Mandel Samantha , Manns Brian , Marano Nina , Marlow Mariel , Marston Barbara , McClung Nancy , McClure Liz , McDonald Emily , McGovern Oliva , Messonnier Nancy , Midgley Claire , Moulia Danielle , Murray Janna , Noelte Kate , Noonan-Smith Michelle , Nordlund Kristen , Norton Emily , Oliver Sara , Pallansch Mark , Parashar Umesh , Patel Anita , Patel Manisha , Pettrone Kristen , Pierce Taran , Pietz Harald , Pillai Satish , Radonovich Lewis , Reagan-Steiner Sarah , Reel Amy , Reese Heather , Rha Brian , Ricks Philip , Rolfes Melissa , Roohi Shahrokh , Roper Lauren , Rotz Lisa , Routh Janell , Sakthivel Senthil Kumar Sarmiento Luisa , Schindelar Jessica , Schneider Eileen , Schuchat Anne , Scott Sarah , Shetty Varun , Shockey Caitlin , Shugart Jill , Stenger Mark , Stuckey Matthew , Sunshine Brittany , Sykes Tamara , Trapp Jonathan , Uyeki Timothy , Vahey Grace , Valderrama Amy , Villanueva Julie , Walker Tunicia , Wallace Megan , Wang Lijuan , Watson John , Weber Angie , Weinbaum Cindy , Weldon William , Westnedge Caroline , Whitaker Brett , Whitaker Michael , Williams Alcia , Williams Holly , Willams Ian , Wong Karen , Xie Amy , Yousef Anna . Am J Transplant 2020 20 (3) 889-895 This article summarizes what is currently known about the 2019 novel coronavirus and offers interim guidance. |
Demographic trends of sick leave absenteeism among civil service employees at a federal agency from 2004 to 2012
Gajewski K , Burris D , Spears DR , Sullivan K , Oyinloye O , McNeil C , Meechan P , Warnock E , Trapp J , Decker KC , Chapman S . J Occup Environ Med 2015 57 (3) 277-83 OBJECTIVE: To investigate the associations between demographic variables and sick leave use. METHODS: We analyzed sick leave use among civil servants at a federal agency (FA) from 2004 to 2012 by demographic and FA-specific variables. We used a mixed methods approach and type III analysis to build a descriptive model of sick leave proportions and demographic variables. RESULTS: Sick absenteeism usage varied significantly (variation of greater than one sick day per year) by sex, Emergency Operations Center response tier, length of service at the FA, age, and general schedule pay grade level. Our final descriptive model contained age, sex, response tier and an interaction term between age and sex. CONCLUSIONS: Future studies should examine these associations on smaller time scales, perhaps breaking the data down by month or day of the week. |
Predicting temporal trends in total absenteeism rates for civil service employees of a federal public health agency
Spears DR , McNeil C , Warnock E , Trapp J , Oyinloye O , Whitehurst V , Decker KC , Chapman S , Campbell M , Meechan P . J Occup Environ Med 2014 56 (6) 632-8 OBJECTIVE: This study evaluates the predictability in temporal absences trends due to all causes (total absenteeism) among employees at a federal agency. The objective is to determine how leave trends vary within the year, and determine whether trends are predictable. METHODS: Ten years of absenteeism data from an attendance system were analyzed for rates of total absence. RESULTS: Trends over a 10-year period followed predictable and regular patterns during a given year that correspond to major holiday periods. Temporal trends in leave among small, medium, and large facilities compared favorably with the agency as a whole. CONCLUSIONS: Temporal trends in total absenteeism rates for an organization can be determined using its attendance system. The ability to predict employee absenteeism rates can be extremely helpful for management in optimizing business performance and ensuring that an organization meets its mission. |
Predicting temporal trends in sickness absence rates for civil service employees of a federal public health agency
Spears DR , McNeil C , Warnock E , Trapp J , Oyinloye O , Whitehurst V , Decker KC , Chapman S , Campbell M , Meechan P . J Occup Environ Med 2012 55 (2) 179-90 OBJECTIVE: To determine whether trends of sickness in employees at a federal agency are predictable, and whether the variance was minimal enough to detect unusual levels of employee illness for further investigation. METHODS: Ten years of absenteeism data from an attendance system were analyzed for rates of sickness absence. Specifically, week of year and day of week were used to describe temporal trends. RESULTS: This study evaluates the predictability in temporal absence trends due to sickness among employees at a federal agency. Trends follow regular patterns during a given year that correspond to seasonal illnesses. Temporal trends in sick leave have been proven to be very predictable. CONCLUSION: The minimal variance allows the detection of sick leave anomalies that may be ascribable to specific causes, allowing the business or agency to follow-up and develop interventions. |
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