| 4533 |
Centers for Disease Control and Prevention |
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en |
Good Health Habits for Preventing Seasonal Flu |
Good Health Habits for Preventing Seasonal Flu - CDC |
| better health habits | 0.992609 |
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| 5011 |
Centers for Disease Control and Prevention |
Video |
en |
Your Wake-Up Call |
In this 60 second public service announcement, Golden Globe and Academy Award-nominated actor and musician Terrance Howard urges Americans to be screened for colorectal cancer. Mr. Howard has a personal connection to the disease. He talks movingly about losing his mother to colon cancer, saying, "Let my heartbreak be your wake-up-call."
Comments on this video are allowed in accordance with our comment policy: http://www.cdc.gov/SocialMedia/Tools/CommentPolicy.html
This video can also be viewed at http://www.cdc.gov/CDCTV/YourWakeUpCall/index.html |
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| 11056 |
Centers for Disease Control and Prevention |
Html |
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Women's Safety and Health Issues at Work: Health Concerns: Cancer - NIOSH Workplace Safety and Health Topic |
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| glutathione S-transferase T1 | 0.739816 |
| possible link | 0.814084 |
| U.S. flight attendants | 0.758886 |
| proportionate lung cancer | 0.769409 |
| glioma risk | 0.649171 |
| cancer deaths | 0.684896 |
| non-white workers | 0.66586 |
| farm pesticide exposure | 0.85769 |
| American seafood workers | 0.813886 |
| case-control study | 0.684725 |
| shoe manufacturing facilities | 0.72394 |
| formaldehyde exposure | 0.873608 |
| mortality data | 0.695989 |
| M1 genotype | 0.634516 |
| fewer deaths | 0.664916 |
| noncancer mortality | 0.750723 |
| complete data | 0.632125 |
| earlier age | 0.968178 |
| tobacco smoke exposure | 0.838581 |
| sister chromatid exchanges | 0.724482 |
| dry-cleaning workers | 0.737585 |
| study | 0.845038 |
| capacitor manufacturing facilities | 0.73417 |
| female flight attendants | 0.757513 |
| previous study | 0.661522 |
|
| thyroid gland | 0.632763 |
| Hemoglobin adducts | 0.643975 |
| occupational exposure | 0.776573 |
| industry sector workers | 0.774179 |
| Cause-specific mortality | 0.72129 |
| Occupational lung cancer | 0.772213 |
| update study | 0.6726 |
| ethylene oxide | 0.768213 |
| heart disease | 0.635596 |
| hospital workers | 0.662455 |
| seafood processing plants | 0.769862 |
| cancer mortality risks | 0.869127 |
| particularly black women | 0.77182 |
| hazardous substances | 0.759838 |
| breast cancer risk | 0.783492 |
| study group | 0.68636 |
| cancer-causing agent | 0.631718 |
| breast cancer | 0.955793 |
| garment workers | 0.651751 |
| reduced blood supply | 0.746867 |
| lung cancer death | 0.894843 |
| EtO sterilizer | 0.693778 |
| Workplace exposures | 0.650009 |
| stomach cancer | 0.687439 |
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| 11462 |
Centers for Disease Control and Prevention |
Html |
en |
Birth Defects & Developmental Disabilities |
For the millions of Americans with birth defects, disabilities, and blood disorders, a happy, healthy life can be challenging to realize. |
| blood disorders | 0.715287 |
| CDC | 0.252991 |
| healthy life | 0.483173 |
| husband | 0.311029 |
| prevents | 0.257983 |
| program | 0.248757 |
| screening—pulse oximetry—that | 0.44158 |
| pregnant women | 0.488999 |
| medications | 0.249252 |
| Cora | 0.941699 |
| simple screening | 0.431571 |
| family members | 0.465042 |
| developmental disabilities | 0.453707 |
| pulse oximetry | 0.452629 |
| antibody | 0.251852 |
| lives | 0.252345 |
| genetic inhibitor | 0.46499 |
| Americans | 0.247305 |
| early identification | 0.458664 |
| congenital heart defect | 0.684702 |
| unborn babies | 0.495996 |
| undetected congenital heart | 0.989691 |
| gene mutations | 0.738154 |
| early morning | 0.442297 |
| millions | 0.255363 |
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| programs | 0.252436 |
| support | 0.248565 |
| congenital heart defects | 0.658523 |
| coroner | 0.323134 |
| treatment | 0.247646 |
| new law | 0.42649 |
| hemophilia worldwide | 0.483944 |
| prevention efforts | 0.483928 |
| health services | 0.469605 |
| normal pregnancy | 0.459295 |
| congenital heart disease | 0.660271 |
| researches autism | 0.481833 |
| hospital | 0.300353 |
| complications | 0.250213 |
| Kristine | 0.252291 |
| families | 0.248618 |
| heart defect | 0.828761 |
| birth defects | 0.486588 |
| people | 0.252401 |
| home | 0.24847 |
| Signs | 0.251635 |
| genetic testing | 0.455671 |
| risk | 0.251905 |
| Learn | 0.251658 |
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| 11624 |
Centers for Disease Control and Prevention |
Html |
en |
Fact Sheet: New Modeling Tool for Response to Ebola Virus Disease | Media Statement - Fact Sheet | CDC Online Newsroom | CDC |
CDC public health news, press releases, government public health news, medical and disease news, story ideas, photos. |
| humanitarian aid efforts | 0.312478 |
| multiple family members | 0.324924 |
| multiple U.S. departments | 0.316527 |
| affected countries | 0.321685 |
| case projections | 0.268227 |
| partner countries | 0.264122 |
| treatment beds | 0.265718 |
| Great Britain | 0.265028 |
| non-isolated individuals | 0.27142 |
| response modeling tool | 0.556022 |
| Ebola transmission | 0.441443 |
| federal government | 0.266011 |
| U.S. government Ebola | 0.493456 |
| ebola epidemic | 0.562078 |
| international responders | 0.270052 |
| tool illustrates | 0.275446 |
| local governments | 0.268111 |
| sick individuals | 0.270061 |
| burial practices | 0.455156 |
| prevention interventions | 0.274874 |
| short-term estimates | 0.271779 |
| World Health Organization | 0.319876 |
| safe burial practices | 0.435122 |
| emergency response resources | 0.350903 |
| key elements | 0.26858 |
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| treatment facilities | 0.266672 |
| State Department | 0.266264 |
| additional resources | 0.266661 |
| ebola treatment units | 0.618468 |
| isolation settings | 0.265821 |
| isolation capacity | 0.270554 |
| Microsoft Excel spreadsheet | 0.3244 |
| healthy individuals | 0.323174 |
| Ebola situations | 0.47198 |
| traditional burial practices | 0.433635 |
| health workers | 0.26656 |
| Sierra Leone | 0.339591 |
| robust response | 0.277896 |
| current situation | 0.268216 |
| deceased body | 0.269316 |
| new Ebola cases | 0.528368 |
| tipping point | 0.37752 |
| bodily fluids | 0.334829 |
| dynamic modeling tool | 0.359688 |
| public health actions | 0.314956 |
| ebola response modeling | 0.803393 |
| Gaining Control | 0.269961 |
| Key Variables | 0.269564 |
| home care | 0.265495 |
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Centers for Disease Control and Prevention |
Html |
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Notes from the Field: Prevalence of Risk Factors for SuicideAmong Veterinarians - United States, 2014 |
Please note: An erratum has been published for this article. To view the erratum, please click here. |
| veterinary medical associations | 0.576926 |
| mental health | 0.606677 |
| depressive episodes | 0.559508 |
| Human Services | 0.547349 |
| VIN News Service | 0.607502 |
| Tracy K. Witte | 0.59031 |
| psychological distress | 0.762075 |
| female respondents | 0.627566 |
| livestock department | 0.517904 |
| Suicide Among Veterinarians | 0.709267 |
| risk factors | 0.74992 |
| Local Readiness | 0.556183 |
| Paul D. Pion | 0.55791 |
| commonly reported age | 0.576851 |
| suicidal ideation | 0.698979 |
| underlying risk factors | 0.57302 |
| suicidal behavior | 0.718811 |
| Randall J. Nett | 0.756047 |
| small animal medicine | 0.696829 |
| Renee H. Funk | 0.583401 |
| Daniel R. O'Leary | 0.594697 |
| lower lifetime prevalence | 0.58784 |
| Kris K. Carter | 0.583598 |
| effective prevention methods | 0.558266 |
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| Katie M. Kurkjian | 0.5877 |
| Karl J. Musgrave | 0.590814 |
| State health departments | 0.613178 |
| prevalence estimates | 0.525443 |
| Kessler-6 psychological distress | 0.751624 |
| Brigid L. Elchos | 0.590562 |
| Kerry R. Pride | 0.58468 |
| Enzo R. Campagnolo | 0.598781 |
| social desirability bias | 0.567755 |
| U.S. veterinarians | 0.971581 |
| Veterinary Information Network | 0.730867 |
| Public Health Veterinarians | 0.748841 |
| Stacy M. Holzbauer | 0.597277 |
| Veterinary Medical Association | 0.57477 |
| Colorado State University | 0.580211 |
| Public Health Preparedness | 0.703706 |
| suicide risk factors | 0.621572 |
| Mental Health Investigation | 0.605564 |
| JAVMA News | 0.593635 |
| female U.S. adults | 0.729743 |
| psychological distress scale | 0.75158 |
| Animal Health | 0.532818 |
| veterinary medicine | 0.51696 |
| suicide attempts | 0.56542 |
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Centers for Disease Control and Prevention |
Html |
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Importation and Domestic Transmission of Shigella sonneiResistant to Ciprofloxacin - United States, May 2014-February2015 |
Anna Bowen, MD1, Jacqueline Hurd, MPH1, Cora Hoover, MD2, Yvette Khachadourian, MPH3, Elizabeth Traphagen, MPH4, Emily Harvey4, Tanya Libby, MPH5, Sara Ehlers, MPH2, Melissa Ongpin, MPH2, J. Corbin Norton1, Amelia Bicknese1, Akiko Kimura, MD6 (Author affiliations at end of text). |
| antimicrobial medications | 0.715624 |
| San Francisco Department | 0.559286 |
| Antimicrobial Resistance Monitoring | 0.767221 |
| intermediate susceptibility | 0.578329 |
| Anna Bowen | 0.549389 |
| PulseNet cluster | 0.545652 |
| Health care providers | 0.548336 |
| antimicrobial susceptibility data | 0.639422 |
| macrolide resistance genes | 0.549975 |
| National Center | 0.572231 |
| shigellosis | 0.67 |
| recent international travel | 0.634602 |
| oral antimicrobial medications | 0.642009 |
| antimicrobial susceptibility summary | 0.660435 |
| public health officials | 0.652363 |
| Francisco outbreak cases | 0.591135 |
| meticulous hygiene regimens | 0.546143 |
| Environmental Diseases | 0.572271 |
| National Antimicrobial Resistance | 0.765586 |
| Infectious Diseases | 0.568438 |
| J. Corbin Norton | 0.552908 |
| pulsed-field gel electrophoresis | 0.697465 |
| S. sonnei | 0.690217 |
| antimicrobial susceptibilities | 0.570818 |
| Puerto Rico | 0.552442 |
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| United States | 0.835663 |
| Shigella sonnei infections | 0.612785 |
| reserve antimicrobial medications | 0.612391 |
| azithromycin-nonsusceptible shigellosis | 0.545661 |
| antimicrobial therapy | 0.549135 |
| uncommon pulsed-field gel | 0.552427 |
| total isolates | 0.570745 |
| antimicrobial susceptibility information | 0.685194 |
| counsel shigellosis patients | 0.657983 |
| adult international travelers | 0.591357 |
| local health departments | 0.570567 |
| public health | 0.789648 |
| antimicrobial treatment | 0.553771 |
| cases | 0.654265 |
| international travel | 0.925055 |
| child care settings | 0.648817 |
| ciprofloxacin-resistant shigellosis | 0.640332 |
| antimicrobial susceptibility | 0.774439 |
| Public Health Division | 0.552468 |
| San Francisco | 0.78662 |
| ciprofloxacin-resistant S. sonnei | 0.652348 |
| national molecular subtyping | 0.567426 |
| Dominican Republic | 0.603611 |
| federal public health | 0.567466 |
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Centers for Disease Control and Prevention |
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Women's Stories |
Learn more about breast cancer in young women and understanding your risk for breast cancer by hearing from eight women whose lives have been deeply affected by breast cancer. |
| young women | 0.400132 |
| treatment | 0.340073 |
| Carletta | 0.338691 |
| genetic counselor | 0.488036 |
| biopsy results | 0.39255 |
| Ashkenazi Jewish heritage | 0.671211 |
| health care provider | 0.458206 |
| father | 0.340997 |
| maternal aunt | 0.390072 |
| mom | 0.344695 |
| triathlon | 0.319416 |
| BRCA2 gene mutation | 0.642837 |
| regular screening | 0.38862 |
| Jackie | 0.340795 |
| options | 0.340436 |
| Cassie | 0.407312 |
| surveillance | 0.342002 |
| lump | 0.345292 |
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| Marleah | 0.356554 |
| goal | 0.319867 |
| lives | 0.321948 |
| ovarian cancer | 0.38565 |
| gene mutation | 0.853887 |
| BRCA1 gene mutation | 0.806208 |
| colon cancer | 0.391632 |
| grandmother | 0.319943 |
| breast MRI | 0.443842 |
| breast cancer | 0.978773 |
| Meagan | 0.348983 |
| preventive surgeries | 0.394152 |
| Lisa’s family | 0.379194 |
| Amy | 0.343475 |
| relatives | 0.318998 |
| Cara | 0.410552 |
| aunts | 0.323805 |
| family history | 0.397883 |
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Centers for Disease Control and Prevention |
Html |
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National Homeless Person's Memorial Day | CDC Features |
This day serves to raise awareness of those who don't have a place to call home, and to remember those who have died as a result of being homeless. Since 1990, our country has observed National Homeless Persons' Memorial Day. |
| social service agencies | 0.598624 |
| country | 0.398567 |
| homeless people | 0.681429 |
| important HUD endeavor | 0.616952 |
| housing outcomes | 0.470106 |
| U.S. Department | 0.476061 |
| residential programs | 0.471256 |
| awareness | 0.364536 |
| unsheltered locations | 0.470984 |
| poverty | 0.362787 |
| health care providers | 0.617554 |
| Memorial | 0.364414 |
| biennial PIT count | 0.624506 |
| greater risk | 0.466424 |
| poor health outcomes | 0.657761 |
| stable shelter | 0.472924 |
| poor mental health | 0.624793 |
| integrated efforts | 0.457713 |
| public-private partnerships | 0.46602 |
| life expectancy | 0.48451 |
| local HUD | 0.477632 |
| homeless persons | 0.971712 |
| single individuals | 0.469909 |
| national effort | 0.45639 |
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| health protection agency | 0.614128 |
| unaffordable housing | 0.490575 |
| safe housing | 0.502187 |
| HPMD events | 0.475958 |
| unaccompanied youth | 0.478729 |
| Urban Development | 0.475887 |
| United States | 0.475539 |
| profound impact | 0.481173 |
| general population | 0.463407 |
| percent | 0.533517 |
| National Homeless Persons | 0.838793 |
| risk homelessness | 0.538098 |
| national concern | 0.462322 |
| accurate health information | 0.60887 |
| substance abuse | 0.464376 |
| federal agencies | 0.457456 |
| public health needs | 0.621057 |
| rapid re-housing | 0.456373 |
| cross-sector partnership discussions | 0.601999 |
| community organizations | 0.461859 |
| non-federal organizations | 0.469122 |
| Collective efforts | 0.451051 |
| mortality rate | 0.460979 |
| Housing First initiatives | 0.464434 |
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| 16003 |
Centers for Disease Control and Prevention |
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FIGURE 1. Influenza vaccine dosing algorithm for children aged 6 months through 8 years - Advisory Committee on Immunization Practices, United States, 2015-16 influenza season* |
Vaccinating Children Algorithm (Figure 1) - CDC |
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