Last data update: Apr 22, 2024. (Total: 46599 publications since 2009)
Records 1-5 (of 5 Records) |
Query Trace: Barry Vaughn[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. |
Patterns in COVID-19 Vaccination Coverage, by Social Vulnerability and Urbanicity - United States, December 14, 2020-May 1, 2021.
Barry V , Dasgupta S , Weller DL , Kriss JL , Cadwell BL , Rose C , Pingali C , Musial T , Sharpe JD , Flores SA , Greenlund KJ , Patel A , Stewart A , Qualters JR , Harris L , Barbour KE , Black CL . MMWR Morb Mortal Wkly Rep 2021 70 (22) 818-824 Disparities in vaccination coverage by social vulnerability, defined as social and structural factors associated with adverse health outcomes, were noted during the first 2.5 months of the U.S. COVID-19 vaccination campaign, which began during mid-December 2020 (1). As vaccine eligibility and availability continue to expand, assuring equitable coverage for disproportionately affected communities remains a priority. CDC examined COVID-19 vaccine administration and 2018 CDC social vulnerability index (SVI) data to ascertain whether inequities in COVID-19 vaccination coverage with respect to county-level SVI have persisted, overall and by urbanicity. Vaccination coverage was defined as the number of persons aged ≥18 years (adults) who had received ≥1 dose of any Food and Drug Administration (FDA)-authorized COVID-19 vaccine divided by the total adult population in a specified SVI category.(†) SVI was examined overall and by its four themes (socioeconomic status, household composition and disability, racial/ethnic minority status and language, and housing type and transportation). Counties were categorized into SVI quartiles, in which quartile 1 (Q1) represented the lowest level of vulnerability and quartile 4 (Q4), the highest. Trends in vaccination coverage were assessed by SVI quartile and urbanicity, which was categorized as large central metropolitan, large fringe metropolitan (areas surrounding large cities, e.g., suburban), medium and small metropolitan, and nonmetropolitan counties.(§) During December 14, 2020-May 1, 2021, disparities in vaccination coverage by SVI increased, especially in large fringe metropolitan (e.g., suburban) and nonmetropolitan counties. By May 1, 2021, vaccination coverage was lower among adults living in counties with the highest overall SVI; differences were most pronounced in large fringe metropolitan (Q4 coverage = 45.0% versus Q1 coverage = 61.7%) and nonmetropolitan (Q4 = 40.6% versus Q1 = 52.9%) counties. Vaccination coverage disparities were largest for two SVI themes: socioeconomic status (Q4 = 44.3% versus Q1 = 61.0%) and household composition and disability (Q4 = 42.0% versus Q1 = 60.1%). Outreach efforts, including expanding public health messaging tailored to local populations and increasing vaccination access, could help increase vaccination coverage in high-SVI counties. |
Opening of Large Institutions of Higher Education and County-Level COVID-19 Incidence - United States, July 6-September 17, 2020.
Leidner AJ , Barry V , Bowen VB , Silver R , Musial T , Kang GJ , Ritchey MD , Fletcher K , Barrios L , Pevzner E . MMWR Morb Mortal Wkly Rep 2021 70 (1) 14-19 During early August 2020, county-level incidence of coronavirus disease 2019 (COVID-19) generally decreased across the United States, compared with incidence earlier in the summer (1); however, among young adults aged 18-22 years, incidence increased (2). Increases in incidence among adults aged ≥60 years, who might be more susceptible to severe COVID-19-related illness, have followed increases in younger adults (aged 20-39 years) by an average of 8.7 days (3). Institutions of higher education (colleges and universities) have been identified as settings where incidence among young adults increased during August (4,5). Understanding the extent to which these settings have affected county-level COVID-19 incidence can inform ongoing college and university operations and future planning. To evaluate the effect of large colleges or universities and school instructional format* (remote or in-person) on COVID-19 incidence, start dates and instructional formats for the fall 2020 semester were identified for all not-for-profit large U.S. colleges and universities (≥20,000 total enrolled students). Among counties with large colleges and universities (university counties) included in the analysis, remote-instruction university counties (22) experienced a 17.9% decline in mean COVID-19 incidence during the 21 days before through 21 days after the start of classes (from 17.9 to 14.7 cases per 100,000), and in-person instruction university counties (79) experienced a 56.2% increase in COVID-19 incidence, from 15.3 to 23.9 cases per 100,000. Counties without large colleges and universities (nonuniversity counties) (3,009) experienced a 5.9% decline in COVID-19 incidence, from 15.3 to 14.4 cases per 100,000. Similar findings were observed for percentage of positive test results and hotspot status (i.e., increasing among in-person-instruction university counties). In-person instruction at colleges and universities was associated with increased county-level COVID-19 incidence and percentage test positivity. Implementation of increased mitigation efforts at colleges and universities could minimize on-campus COVID-19 transmission. |
Enhanced contact investigations for nine early travel-related cases of SARS-CoV-2 in the United States.
Burke RM , Balter S , Barnes E , Barry V , Bartlett K , Beer KD , Benowitz I , Biggs HM , Bruce H , Bryant-Genevier J , Cates J , Chatham-Stephens K , Chea N , Chiou H , Christiansen D , Chu VT , Clark S , Cody SH , Cohen M , Conners EE , Dasari V , Dawson P , DeSalvo T , Donahue M , Dratch A , Duca L , Duchin J , Dyal JW , Feldstein LR , Fenstersheib M , Fischer M , Fisher R , Foo C , Freeman-Ponder B , Fry AM , Gant J , Gautom R , Ghinai I , Gounder P , Grigg CT , Gunzenhauser J , Hall AJ , Han GS , Haupt T , Holshue M , Hunter J , Ibrahim MB , Jacobs MW , Jarashow MC , Joshi K , Kamali T , Kawakami V , Kim M , Kirking HL , Kita-Yarbro A , Klos R , Kobayashi M , Kocharian A , Lang M , Layden J , Leidman E , Lindquist S , Lindstrom S , Link-Gelles R , Marlow M , Mattison CP , McClung N , McPherson TD , Mello L , Midgley CM , Novosad S , Patel MT , Pettrone K , Pillai SK , Pray IW , Reese HE , Rhodes H , Robinson S , Rolfes M , Routh J , Rubin R , Rudman SL , Russell D , Scott S , Shetty V , Smith-Jeffcoat SE , Soda EA , Spitters C , Stierman B , Sunenshine R , Terashita D , Traub E , Vahey GM , Verani JR , Wallace M , Westercamp M , Wortham J , Xie A , Yousaf A , Zahn M . PLoS One 2020 15 (9) e0238342 Coronavirus disease 2019 (COVID-19), the respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first identified in Wuhan, China and has since become pandemic. In response to the first cases identified in the United States, close contacts of confirmed COVID-19 cases were investigated to enable early identification and isolation of additional cases and to learn more about risk factors for transmission. Close contacts of nine early travel-related cases in the United States were identified and monitored daily for development of symptoms (active monitoring). Selected close contacts (including those with exposures categorized as higher risk) were targeted for collection of additional exposure information and respiratory samples. Respiratory samples were tested for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction at the Centers for Disease Control and Prevention. Four hundred four close contacts were actively monitored in the jurisdictions that managed the travel-related cases. Three hundred thirty-eight of the 404 close contacts provided at least basic exposure information, of whom 159 close contacts had ≥1 set of respiratory samples collected and tested. Across all actively monitored close contacts, two additional symptomatic COVID-19 cases (i.e., secondary cases) were identified; both secondary cases were in spouses of travel-associated case patients. When considering only household members, all of whom had ≥1 respiratory sample tested for SARS-CoV-2, the secondary attack rate (i.e., the number of secondary cases as a proportion of total close contacts) was 13% (95% CI: 4-38%). The results from these contact tracing investigations suggest that household members, especially significant others, of COVID-19 cases are at highest risk of becoming infected. The importance of personal protective equipment for healthcare workers is also underlined. Isolation of persons with COVID-19, in combination with quarantine of exposed close contacts and practice of everyday preventive behaviors, is important to mitigate spread of COVID-19. |
Genotypic distribution of hepatitis B virus (HBV) among acute cases of HBV infection, selected United States counties, 1999-2005.
Teshale EH , Ramachandran S , Xia GL , Roberts H , Groeger J , Barry V , Hu DJ , Holmberg SD , Holtzman D , Ward JW , Teo CG , Khudyakov Y . Clin Infect Dis 2011 53 (8) 751-6 BACKGROUND: Knowledge of the genotypic distribution of hepatitis B virus (HBV) facilitates epidemiologic tracking and surveillance of HBV infection as well as prediction of its disease burden. In the United States, HBV genotyping studies have been conducted for chronic but not acute hepatitis B. METHODS: Serum samples were collected from patients with acute hepatitis B cases reported from the 6 counties that participated in the Sentinel Counties Study of Acute Viral Hepatitis from 1999 through 2005. Polymerase chain reaction followed by nucleotide sequencing of a 435-base pair segment of the HBV S gene was performed, and the sequences were phylogenetically analyzed. RESULTS: Of 614 patients identified with available serum samples, 75% were infected with genotype A HBV and 18% were infected with genotype D HBV. Thirty-two percent of genotype A sequences constituted a single subgenotype A2 cluster. The odds of infection with genotype A (vs with genotype D) were 5 times greater among black individuals than among Hispanic individuals (odds ratio [OR], 5; 95% confidence interval [CI], 2.3-10.7). The odds of infection with genotype A were 49, 8, and 4 times greater among patients from Jefferson County (Alabama), Pinellas County (Florida), and San Francisco (California), respectively, than among those living in Denver County (Colorado). Genotype A was less common among recent injection drug users than it was among non-injection drug users (OR, 0.2; 95% CI, 0.1-0.4). CONCLUSIONS: HBV genotype distribution was significantly associated with ethnicity, place of residence, and risk behavior. |
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