Sherry L. Burrer
Centers for Disease Control and Prevention
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Clinical Infectious Diseases | 2010
Hannah L. Kirking; Jennifer E. Cortes; Sherry L. Burrer; Aron J. Hall; Nicole J. Cohen; Harvey B. Lipman; Curi Kim; Elizabeth R. Daly; Daniel B. Fishbein
BACKGROUND On 8 October 2008, members of a tour group experienced diarrhea and vomiting throughout an airplane flight from Boston, Massachusetts, to Los Angeles, California, resulting in an emergency diversion 3 h after takeoff. An investigation was conducted to determine the cause of the outbreak, assess whether transmission occurred on the airplane, and describe risk factors for transmission. METHODS Passengers and crew were contacted to obtain information about demographics, symptoms, locations on the airplane, and possible risk factors for transmission. Case patients were defined as passengers with vomiting or diarrhea (> or =3 loose stools in 24 h) and were asked to submit stool samples for norovirus testing by real-time reverse-transcription polymerase chain reaction. RESULTS Thirty-six (88%) of 41 tour group members were interviewed, and 15 (41%) met the case definition (peak date of illness onset, 8 October 2008). Of 106 passengers who were not tour group members, 85 (80%) were interviewed, and 7 (8%) met the case definition after the flight (peak date of illness onset, 10 October 2008). Multivariate logistic regression analysis showed that sitting in an aisle seat (adjusted relative risk, 11.0; 95% confidence interval, 1.4-84.9) and sitting near any tour group member (adjusted relative risk, 7.5; 95% confidence interval, 1.7-33.6) were associated with the development of illness. Norovirus genotype II was detected by reverse-transcription polymerase chain reaction in stool samples from case patients in both groups. CONCLUSIONS Despite the short duration, transmission of norovirus likely occurred during the flight.
Journal of American College Health | 2012
Elizabeth A. Talbot; Dawn Harland; Wendy Wieland-Alter; Sherry L. Burrer; Lisa V. Adams
Abstract Objective: Interferon-γ release assays (IGRAs) are an important tool for detecting latent Mycobacterium tuberculosis infection (LTBI). Insufficient data exist about IGRA specificity in college health centers, most of which screen students for LTBI using the tuberculin skin test (TST). Participants: Students at a low–TB incidence college health center. Methods: TST and T-SPOT.TB were performed on prospectively recruited students. TB exposure risk was assessed using a questionnaire: Those at low risk were assumed to not have LTBI in order to calculate test specificity. Results: Of 184 students enrolled, 143 had results available for both TST and T-SPOT.TB. Agreement of the tests was 97% (kappa statistic 0.717; 95% confidence interval, 0.399–1.00). Among 124 low-risk students, specificity for TST and T-SPOT.TB were 98.4% and 100%, respectively. Conclusions: T-SPOT.TB specificity was high among low-risk students. Additional studies such as cost-effectiveness analyses using T-SPOT.TB as a single or confirmatory test to TST are needed to contribute to LTBI screening policy decisions.
Public Health Reports | 2017
Erica Thomasson; Elizabeth Scharman; Ethan Fechter-Leggett; Danae Bixler; Sheri’f Ibrahim; Mary Anne Duncan; Joy Hsu; Melissa Scott; Suzanne Wilson; Loretta Haddy; Anthony Pizon; Sherry L. Burrer; Amy Wolkin; Lauren Lewis
Objectives: On January 9, 2014, approximately 10 000 gallons of a mixture of 4-methylcyclohexanemethanol and propylene glycol phenyl ether spilled into West Virginia’s Elk River, contaminating the potable water supply of about 300 000 West Virginia residents. This study sought to describe acute health effects after the chemical spill. Methods: We conducted a descriptive analysis using 3 complementary data sources: (1) medical records of patients who visited an emergency department during January 9-23, 2014, with illness potentially related to the spill; (2) West Virginia Poison Center caller records coded as “contaminated water” during January 9-23, 2014; and (3) answers to household surveys about health effects from a Community Assessment for Public Health Emergency Response (CASPER) questionnaire administered 3 months after the spill. Results: In the 2 weeks after the spill, 2000 people called the poison center reporting exposure to contaminated water, and 369 people visited emergency departments in the affected area with reports of exposure and symptoms potentially related to the spill. According to CASPER weighted cluster analyses, an estimated 25 623 households (21.7%; 95% confidence interval [CI], 14.4%-28.9%) had ≥1 person with symptoms who felt that they were related to the spill in the 3 months after it. Reported health effects across all 3 data sources included mild skin, respiratory, and gastrointestinal symptoms that resolved with no or minimal treatment. Conclusions: Medical records, poison center data, and CASPER household surveys were inexact but useful data sources to describe overall community health effects after a large-scale chemical spill. Analyzing multiple data sources could inform epidemiologic investigations of similar events.
Public Health Reports | 2017
Sherry L. Burrer; Ethan Fechter-Leggett; Tesfaye Bayleyegn; Miguella Mark-Carew; Carrie A. Thomas; Danae Bixler; Rebecca S. Noe; Joy Hsu; Loretta Haddy; Amy Wolkin
Objectives: In January 2014, 4-methylcyclohexanemethanol spilled into the Elk River near Charleston, West Virginia, contaminating the water supply for about 120 000 households. The West Virginia American Water Company (WVAWC) issued a “do not use” water order for 9 counties. After the order was lifted (10 days after the spill), the communities’ use of public water systems, information sources, alternative sources of water, and perceived impact of the spill on households were unclear to public health officials. To assist in recovery efforts, the West Virginia Bureau for Public Health and the Centers for Disease Control and Prevention conducted a Community Assessment for Public Health Emergency Response (CASPER). Methods: We used the CASPER 2-stage cluster sampling design to select a representative sample of households to interview, and we conducted interviews in 171 households in April 2014. We used a weighted cluster analysis to generate population estimates in the sampling frame. Results: Before the spill, 74.4% of households did not have a 3-day alternative water supply for each household member and pet. Although 83.6% of households obtained an alternative water source within 1 day of the “do not use” order, 37.4% of households reportedly used WVAWC water for any purpose. Nearly 3 months after the spill, 36.1% of households believed that their WVAWC water was safe, and 33.5% reported using their household water for drinking. Conclusions: CASPER results identified the need to focus on basic public health messaging and household preparedness efforts. Recommendations included (1) encouraging households to maintain a 3-day emergency water supply, (2) identifying additional alternative sources of water for future emergencies, and (3) increasing community education to address ongoing concerns about water.
Online Journal of Public Health Informatics | 2015
Sanjaya Dhakal; Sherry L. Burrer; Carla A. Winston; Achintya Dey; Umed A. Ajani; Samuel L. Groseclose
Objective Electronic laboratory reporting has been promoted as a public health priority. The Office of the U.S. National Coordinator for Health Information Technology has endorsed two coding systems: Logical Observation Identifiers Names and Codes (LOINC) for laboratory test orders and Systemized Nomenclature of Medicine-Clinical Terms (SNOMED CT) for test results. Materials and Methods We examined LOINC and SNOMED CT code use in electronic laboratory data reported in 2011 by 63 non-federal hospitals to BioSense electronic syndromic surveillance system. We analyzed the frequencies, characteristics, and code concepts of test orders and results. Results A total of 14,028,774 laboratory test orders or results were reported. No test orders used SNOMED CT codes. To describe test orders, 77% used a LOINC code, 17% had no value, and 6% had a non-informative value, “OTH”. Thirty-three percent (33%) of test results had missing or non-informative codes. For test results with at least one informative value, 91.8% had only LOINC codes, 0.7% had only SNOMED codes, and 7.4% had both. Of 108 SNOMED CT codes reported without LOINC codes, 45% could be matched to at least one LOINC code. Conclusion Missing or non-informative codes comprised almost a quarter of laboratory test orders and a third of test results reported to BioSense by non-federal hospitals. Use of LOINC codes for laboratory test results was more common than use of SNOMED CT. Complete and standardized coding could improve the usefulness of laboratory data for public health surveillance and response.
Journal of Homeland Security and Emergency Management | 2015
Amy Wolkin; Jennifer Rees Patterson; Shelly Harris; Elena Soler; Sherry L. Burrer; Michael A. McGeehin; Sandra Greene
Abstract All regions of the US experience disasters which result in a number of negative public health consequences. Some populations have higher levels of social vulnerability and, thus, are more likely to experience negative impacts of disasters including emotional distress, loss of property, illness, and death. To mitigate the impact of disasters on at-risk populations, emergency managers must be aware of the social vulnerabilities within their community. This paper describes a qualitative study which aimed to understand how emergency managers identify social vulnerabilities, also referred to as at-risk populations, in their populations and barriers and facilitators to current approaches. Findings suggest that although public health tools have been developed to aid emergency managers in identifying at-risk populations, they are not being used consistently. Emergency managers requested more information on the availability of tools as well as guidance on how to increase ability to identify at-risk populations.
Prehospital and Disaster Medicine | 2015
Tesfaye Bayleyegn; Amy H. Schnall; Shimere G. Ballou; David F. Zane; Sherry L. Burrer; Rebecca S. Noe; Amy Wolkin
Prehospital and Disaster Medicine | 2018
Gamola Z. Fortenberry; Patricia Reynolds; Sherry L. Burrer; Vicki Johnson-Lawrence; Alice Wang; Amy H. Schnall; Price Pullins; Stephanie Kieszak; Tesfaye Bayleyegn; Amy Wolkin
Online Journal of Public Health Informatics | 2013
Howard Burkom; Sherry L. Burrer; Laurie K. Barker; Valerie A. Robison; Peter Hicks; Amy Ising
Online Journal of Public Health Informatics | 2013
Sanjaya Dhakal; Sherry L. Burrer; Carla A. Winston; Mathew Miller; Samuel L. Groseclose