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Reallocating Influenza Vaccine |
FDA-related information for health care professionals and institutions considering flu vaccine reallocation - CDC |
| extent | 0.317129 |
| emergency medical reason | 0.45749 |
| reasonable basis | 0.485481 |
| United States | 0.38033 |
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| section | 0.331382 |
| FDA-related information | 0.396149 |
| Vaccines Licensed | 0.383824 |
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| following information | 0.376603 |
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| shortage | 0.510452 |
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| mind | 0.314563 |
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| purchase | 0.315787 |
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| Federal Food | 0.392301 |
| institutions | 0.317094 |
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| C.F.R. | 0.314422 |
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| doctors | 0.327296 |
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| time | 0.313949 |
| FD&C Act | 0.467009 |
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CDC Media Relations - EID News Synopsis: November 2011 |
EID News Synopsis: November 2011 |
| avian influenza | 0.709762 |
| bat exposure | 0.580183 |
| tire shipment | 0.567252 |
| York State Department | 0.754895 |
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| CDC study | 0.609457 |
| large increase | 0.569675 |
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| bird flu. | 0.566041 |
| densely populated places | 0.626285 |
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| Richard Fielding | 0.567424 |
| New York State | 0.753722 |
| tire yards | 0.566955 |
| bat bite | 0.580961 |
| wholesale markets | 0.566656 |
| bird flu | 0.685547 |
| New Haven | 0.569451 |
| year. Researchers | 0.566323 |
| high risk | 0.568002 |
| Infectious Diseases | 0.577118 |
| genetic markers | 0.567447 |
| rapidly spreading outbreak | 0.622592 |
| Public Health | 0.619787 |
| Hong Kong | 0.910005 |
|
| Contact Millicent Eidson | 0.638523 |
| dangerous mosquitoes | 0.616352 |
| Yale University | 0.565769 |
| Fung Kuk Lo | 0.623093 |
| fiona.lo@cuhk.edu.hk | 0.567494 |
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| public safety | 0.575077 |
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| yellow fever viruses | 0.622337 |
| national recommendations | 0.626906 |
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| Julia E. Brown | 0.623596 |
| people | 0.568017 |
| p.m. EDT | 0.587095 |
| unnecessary preventive treatment | 0.631293 |
| julia.brown@yale.edu | 0.576887 |
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| live poultry | 0.631254 |
| Hong Kong residents | 0.640344 |
| Health Press Office | 0.636064 |
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Effectiveness of the Pasos Adelante Chronic Disease Prevention and Control Program in a US-Mexico border community, 2005-2008 |
This study examined whether Pasos Adelante participants living in a US border community showed improvements in selected physiological measures after participating in the program and whether changes were maintained at 3-month follow-up. |
| self-reported physical activity | 0.490714 |
| mean baseline age | 0.464194 |
| Pasos Adelante | 0.932539 |
| 3-month follow-up assessments | 0.508607 |
| glucose levels | 0.467714 |
| systolic blood pressure | 0.570836 |
| lifestyle intervention program | 0.511578 |
| total cholesterol | 0.467177 |
| promotores-facilitated chronic disease | 0.483295 |
| Su Vida curriculum | 0.480705 |
| diastolic blood pressure | 0.457286 |
| demographic variables | 0.472475 |
| 12-week promotora-facilitated program | 0.467061 |
| 12-week Pasos Adelante | 0.542037 |
| blood pressure | 0.614877 |
| Mexican Americans | 0.481125 |
| risk factors | 0.480457 |
| secondary prevention | 0.466928 |
| objective measures | 0.477575 |
| body mass index | 0.485451 |
| baseline | 0.496925 |
| Introduction
Pasos Adelante | 0.54936 |
| US-Mexico border community | 0.490774 |
| select physiological measures | 0.480549 |
| community health workers | 0.539975 |
|
| anthropometric measures | 0.578375 |
| physiological measures | 0.563131 |
| hip circumference | 0.467388 |
| chronic disease prevention | 0.61378 |
| Public Health | 0.460451 |
| Pasos Adelante participants | 0.625867 |
| fasting blood draw | 0.476971 |
| Pasos Adelante program | 0.766346 |
| program conclusion | 0.494387 |
| conclusion | 0.52022 |
| control program | 0.461894 |
| Diabetes Prevention Program | 0.490388 |
| Research Centers Program | 0.462483 |
| blood measures | 0.463256 |
| non-Hispanic whites | 0.490049 |
| Su Corazón | 0.472575 |
| selected physiological measures | 0.487446 |
| Pasos Adelante curriculum | 0.52543 |
| 3-month follow-up | 0.61826 |
| Baseline measures | 0.479318 |
| physical activity | 0.630733 |
| blood pressure measures | 0.487017 |
| evidence-based program | 0.46773 |
| Pasos Adelante classes | 0.529965 |
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Top 10 Ebola Response Planning Tips: Ebola Readiness Self-Assessment for State and Local Public Health Officials |
Top 10 Ebola Response Planning Tips: Ebola Readiness Self-Assessment for State and Local Public Health Officials - CDC |
| ebola outbreaks | 0.687467 |
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| CDC guidance | 0.50395 |
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| Ebola symptoms | 0.619828 |
| public health authorities | 0.51615 |
| Healthcare System Preparedness | 0.516629 |
| local epidemiologic staff | 0.506086 |
| state | 0.524023 |
| public health systems | 0.534703 |
| following guidance documents | 0.502996 |
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| local response partners | 0.516357 |
| Ebola Outbreaks web | 0.650986 |
| public health partners | 0.521834 |
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| health emergency response | 0.527835 |
| public health officials | 0.529792 |
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| Ebola patients | 0.59014 |
| Ebola | 0.816615 |
|
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| CDC Health Alert | 0.539851 |
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| local planning | 0.506327 |
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| CDC Interim Guidance | 0.540371 |
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| Ebola response planning | 0.649104 |
| align preparedness | 0.497508 |
| Ebola planning | 0.59776 |
| CDC resources | 0.521193 |
| key public health | 0.527012 |
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| public health | 0.924392 |
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| local jurisdictions | 0.506499 |
| local public health | 0.842003 |
| Ebola response | 0.771644 |
| latest Ebola information | 0.629747 |
| healthcare preparedness capability | 0.555282 |
| CDC Ebola website | 0.659645 |
| health emergency preparedness | 0.565977 |
| public health preparedness | 0.712099 |
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Update: CDC Ebola Response and Interim Guidance |
CDC public health news, press releases, government public health news, medical and disease news, story ideas, photos. |
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Occupational Fatalities During the Oil and Gas Boom - UnitedStates, 2003-2013 |
Krystal L. Mason, ScM1; Kyla D. Retzer, MPH1; Ryan Hill, MPH1; Jennifer M. |
| extraction industry employees | 0.41302 |
| gas industry employers | 0.391531 |
| occupational fatality rate | 0.586488 |
| Shale Transportation Safety | 0.38705 |
| automated technologies | 0.401218 |
| Gas Extraction Sector | 0.400266 |
| well-servicing companies | 0.460653 |
| average annual decrease | 0.38587 |
| transportation events | 0.402675 |
| transportation event data | 0.382565 |
| annual occupational fatality | 0.457311 |
| occupational fatalities | 0.396471 |
| gas extraction industry | 0.96835 |
| transportation safety policies | 0.400998 |
| frequent fatal events | 0.533261 |
| gas extraction workers | 0.423629 |
| transportation fatalities | 0.397031 |
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| event type | 0.402819 |
| Fatal Occupational Injuries | 0.493328 |
| fatality rates | 0.447793 |
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| gas operators | 0.38287 |
| fatal events | 0.536103 |
| drilling rigs | 0.448273 |
|
| work-related fatalities | 0.387464 |
| gas workers | 0.383087 |
| Occupational Injuries Program | 0.388625 |
| fatal event numbers | 0.403041 |
| transportation incidents | 0.384307 |
| oil | 0.461213 |
| active drilling rigs | 0.423726 |
| occupational fatal injury | 0.43849 |
| workers | 0.47289 |
| land transportation safety | 0.446882 |
| National Occupational Research | 0.38842 |
| transportation-related fatality rate | 0.427591 |
| fatal work injuries | 0.48715 |
| incident rate ratio | 0.389137 |
| highest fatality rate | 0.493844 |
| 11-year period | 0.432848 |
| occupational safety | 0.449215 |
| worker fatalities | 0.410285 |
| fatality rate | 0.7786 |
| overall fatality rates | 0.420502 |
| fatal injuries | 0.44232 |
| American Industry Classification | 0.39275 |
| fatalities | 0.423024 |
| Occupational Injury | 0.389765 |
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Update on Vaccine-Derived Polioviruses - Worldwide, January2014-March 2015 |
Ousmane M. Diop, PhD1; Cara C. Burns, PhD2; Roland W. |
| VP1 nucleotide substitutions | 0.723628 |
| sewage samples | 0.726617 |
| OPV sequence divergence | 0.66063 |
| recent positive sample | 0.641112 |
| oral poliovirus vaccine | 0.616116 |
| independent cVDPV2 emergences | 0.660216 |
| independent cVDPV2 emergence | 0.626945 |
| Global AFP surveillance | 0.638731 |
| VP1 region | 0.659157 |
| sequence divergence | 0.674289 |
| Polio Laboratory Network | 0.803201 |
| Olen M. Kew | 0.659291 |
| type | 0.630009 |
| VP1 substitutions | 0.758973 |
| AFP patients | 0.758032 |
| parental OPV strain | 0.669936 |
| North Waziristan Agency | 0.639982 |
| cVDPV outbreaks | 0.640772 |
| divergent environmental VDPVs | 0.62288 |
| OPV | 0.751636 |
| reporting period | 0.7639 |
| VP1 nucleotide positions | 0.702415 |
| Global Polio Eradication | 0.618824 |
| sensitive AFP surveillance | 0.628457 |
|
| Wild poliovirus type | 0.628361 |
| iVDPV infections | 0.717869 |
| World Health Organization | 0.713329 |
| VDPVs | 0.644889 |
| South Sudan | 0.727515 |
| cVDPV2 outbreaks | 0.651518 |
| new cVDPV outbreaks | 0.630084 |
| United Kingdom | 0.630433 |
| OPV dose | 0.64062 |
| indigenous cVDPV2 outbreaks | 0.627938 |
| common variable immunodeficiency | 0.65718 |
| severe combined immunodeficiency | 0.744966 |
| new iVDPV infections | 0.671229 |
| VP1 divergence | 0.96049 |
| low OPV coverage | 0.627132 |
| chronic iVDPV infections | 0.637485 |
| AFP patient | 0.638048 |
| VP1 sequences | 0.682542 |
| Global Polio Laboratory | 0.799698 |
| Regional Office | 0.650006 |
| VP1 positions | 0.651031 |
| small number | 0.618579 |
| recent onset date | 0.642963 |
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Strategies to Support Tobacco Cessation and Tobacco-Free Environments in Mental Health and Substance Abuse Facilities |
Preventing Chronic Disease (PCD) is a peer-reviewed electronic journal established by the National Center for Chronic Disease Prevention and Health Promotion. PCD provides an open exchange of information and knowledge among researchers, practitioners, policy makers, and others who strive to improve the health of the public through chronic disease prevention. |
| mental health facility | 0.521516 |
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| smoking cessation | 0.53048 |
| substance addiction populations | 0.47856 |
| cessation treatments | 0.478637 |
| substance abuse treatment | 0.500319 |
|
| tobacco control efforts | 0.4999 |
| http://www.oregon.gov/oha/amh/Pages/tobacco.aspx) state tobacco | 0.49431 |
| Oregon’s Tobacco | 0.47416 |
| mental health facilities | 0.500115 |
| tobacco cessation efforts | 0.512569 |
| substance abuse problems | 0.550533 |
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| Tobacco Freedom | 0.49319 |
| branded initiative | 0.527658 |
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| substance abuse | 0.928798 |
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| substance abuse populations | 0.539481 |
| tobacco control policies | 0.49463 |
| Chronic Disease Prevention | 0.501725 |
| smoke-free environments | 0.536424 |
| substance abuse population | 0.492406 |
| TCPs | 0.512982 |
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| mental health component | 0.508939 |
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Food Safety Smarts |
Use these tools and tips to help prevent food poisoning. |
| foodborne diseases | 0.610637 |
| Separate raw meat | 0.631893 |
| hands | 0.526764 |
| people age | 0.583934 |
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| germs | 0.686589 |
| right internal temperature | 0.631526 |
| diarrhea | 0.537437 |
| nausea | 0.515995 |
| foodborne illness | 0.775129 |
| O157 infection | 0.589168 |
| utensils | 0.5145 |
| Listeria infection | 0.672297 |
| refrigerator | 0.532655 |
| Young children | 0.580101 |
| harmful germs | 0.630524 |
| upset stomach | 0.579757 |
|
| kidney failure | 0.579079 |
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| certain groups | 0.64722 |
| leftovers | 0.518406 |
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| ready-to-eat foods | 0.5757 |
| times | 0.546681 |
| high-risk groups | 0.576342 |
| variety | 0.51502 |
| strikes | 0.515262 |
| lab-confirmed foodborne illness | 0.667131 |
| E. coli | 0.664339 |
| food poisoning | 0.913948 |
| Campylobacter | 0.51705 |
| fight germs | 0.626177 |
| higher risk | 0.577782 |
| people | 0.728371 |
| Older adults | 0.577668 |
| Anybody | 0.518766 |
| higher chance | 0.581291 |
| doctor | 0.514405 |
| certain germs | 0.625737 |
| Nearly half | 0.57646 |
| Salmonella infection | 0.594667 |
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CDC Grand Rounds: Chronic Fatigue Syndrome - Advancing Research and Clinical Education | MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| CDC | 0.410885 |
| myalgic encephalomyelitis/chronic fatigue | 0.452662 |
| mental health assessment | 0.400904 |
| postexertional malaise | 0.387731 |
| term ME/CFS | 0.601222 |
| ME/CFS patients | 0.75506 |
| fatigue immune dysfunction | 0.41482 |
| ME/CFS | 0.909297 |
| psychological illness | 0.390903 |
| health care professionals | 0.462726 |
| flu-like illness | 0.433314 |
| direct medical costs | 0.452322 |
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| new case definition | 0.432179 |
| medical school faculty | 0.392328 |
| medical school | 0.403423 |
| primary care physicians | 0.389834 |
| epstein-barr virus | 0.4276 |
| symptoms | 0.385358 |
| characteristic persistent fatigue | 0.416261 |
| case definition | 0.444632 |
| American Medical Colleges | 0.387806 |
| 3Harvard Medical School | 0.390553 |
| subsequent illness | 0.396015 |
|
| research case definition | 0.403356 |
| medical school courses | 0.392845 |
| systemic exertion intolerance | 0.557192 |
| new clinical case | 0.392878 |
| ME/CFS program | 0.550703 |
| United States | 0.436067 |
| basic science research | 0.387701 |
| acute onset illness | 0.42538 |
| exertion intolerance disease | 0.47602 |
| IOM report | 0.391542 |
| appropriate health care | 0.408512 |
| Epstein-Barr virus syndrome | 0.407596 |
| medical professional organizations | 0.389976 |
| U.S. population-based studies | 0.398641 |
| health care | 0.493907 |
| direct medical expenses | 0.402607 |
| illness | 0.534769 |
| Epstein-Barr virus infection | 0.398073 |
| white blood cell | 0.387728 |
| encephalomyelitis/chronic fatigue syndrome | 0.455649 |
| complete blood count | 0.384688 |
| chronic fatiguing illnesses | 0.387908 |
| thorough medical history | 0.405097 |
| chronic fatigue syndrome | 0.594081 |
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