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Flu Prevention Partners Success Stories: Text4baby Service |
Partnership success stories, Text4baby - CDC |
| California San Diego | 0.598877 |
| date | 0.343364 |
| reminders | 0.334184 |
| free service | 0.514386 |
| CDC | 0.329428 |
| Washington University study | 0.607066 |
| collective efforts | 0.461634 |
| motherhood | 0.335112 |
| new partnership | 0.489097 |
| number | 0.327451 |
| fall publisher briefing | 0.617532 |
| flu vaccination | 0.760029 |
| Rite Aid | 0.886622 |
| safe sleep | 0.459282 |
| non-Text4baby participants | 0.497154 |
| Evaluation results | 0.461226 |
| appointments | 0.32664 |
| goal | 0.32753 |
| free text messages | 0.627613 |
| email Rachel Griffith | 0.601059 |
| celebration | 0.327168 |
| Pregnant women | 0.527169 |
| Healthy Babies Coalition | 0.681944 |
| California State University | 0.599553 |
| code | 0.328352 |
|
| Text4baby mothers | 0.549513 |
| free flu shots | 0.950974 |
| developmental milestones | 0.465483 |
| Text4baby moms | 0.552426 |
| health providers | 0.459835 |
| Prevention | 0.326712 |
| national retail partner | 0.656866 |
| medical warning signs | 0.592162 |
| new moms | 0.544825 |
| National Healthy Mothers | 0.692352 |
| BEBE | 0.341895 |
| Text4baby facilitates | 0.490603 |
| Families Fighting Flu | 0.856113 |
| Communications Manager | 0.461765 |
| flu blog Shot | 0.873706 |
| Text4baby participants | 0.52289 |
| San Marcos/University | 0.462263 |
| barriers | 0.330145 |
| baby’s birth | 0.470595 |
| flu season | 0.901202 |
| Dimes | 0.342609 |
| annual flu messaging | 0.879645 |
| local Rite Aid | 0.678633 |
| Pregnant Moms | 0.553921 |
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MMWR - Differences by Sex in Tobacco Use and Awareness of Tobacco Marketing - Smoking & Tobacco Use |
CDC's Office on Smoking and Health offers information related to smoking and tobacco use. |
| smoking cessation attempts | 0.574486 |
| excise tax rates | 0.56342 |
| Adult Tobacco Surveys | 0.682198 |
| current smokers | 0.625326 |
| GATS response rate | 0.613187 |
| Framework Convention | 0.482273 |
| cigarette excise taxes | 0.604298 |
| tobacco | 0.991589 |
| representative household survey | 0.573278 |
| large difference | 0.482674 |
| indirect advertising | 0.480725 |
| World Health Organization | 0.547236 |
| MPOWER package | 0.485173 |
| countries | 0.536278 |
| tobacco industry | 0.586599 |
| tobacco products | 0.586144 |
| cigarette marketing | 0.903036 |
| statistically significant difference | 0.557729 |
| women | 0.854053 |
| smoking prevalence | 0.484569 |
| current tobacco | 0.602973 |
| young adult women | 0.566545 |
| complex interaction | 0.488683 |
| U.S. government | 0.489046 |
| Thailand | 0.598729 |
|
| tobacco advertising | 0.580812 |
| South Carolina | 0.486014 |
| gender differences | 0.485098 |
| subnational estimates | 0.499644 |
| tobacco marketing | 0.745844 |
| men | 0.672114 |
| Adult Tobacco Survey | 0.707132 |
| gender-specific pattern | 0.491051 |
| sample respondent | 0.485995 |
| Rhode Island | 0.482822 |
| social factors | 0.488419 |
| Uruguay | 0.63873 |
| Tobacco use differences | 0.602307 |
| nationally representative data | 0.569154 |
| Global Adult Tobacco | 0.847456 |
| sample design | 0.49851 |
| Tobacco Control | 0.584817 |
| older women | 0.50916 |
| data collection | 0.498978 |
| management protocols | 0.498496 |
| smokeless tobacco | 0.937641 |
| Bangladesh | 0.65118 |
| continued implementation | 0.481519 |
| average excise tax | 0.560255 |
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National Capacity for Surveillance, Prevention, and Controlof West Nile Virus and Other Arbovirus Infections - United States,2004 and 2012 |
James L. Hadler, MD1, Dhara Patel, MPH2, Kristy Bradley, DVM3, James M. Hughes, MD4, Carina Blackmore, DVM5, Paul Etkind, DrPH6, Lilly Kan, MPH6, Jane Getchell, DrPH7, James Blumenstock, MA8, Jeffrey Engel, MD2 (Author affiliations at end of text). |
| environmental surveillance | 0.632701 |
| Los Angeles County | 0.517851 |
| mosquito-borne virus surveillance | 0.590502 |
| current CDC guidance | 0.51559 |
| cooperative agreement funding | 0.511231 |
| arbovirus surveillance functions | 0.575188 |
| assessment | 0.534415 |
| arbovirus surveillance | 0.637264 |
| current arboviral threats | 0.58941 |
| arboviruses | 0.653869 |
| virus surveillance capacity | 0.600096 |
| standard case report | 0.512811 |
| mosquito surveillance systems | 0.665005 |
| jurisdictions | 0.566772 |
| arboviral disease case | 0.594479 |
| laboratory capacity | 0.663129 |
| recent CSTE assessment | 0.52797 |
| WNV surveillance | 0.825623 |
| mosquito-borne arboviral disease | 0.602802 |
| Mosquito surveillance capacity | 0.78616 |
| adult mosquitoes | 0.566212 |
| national surveillance platform | 0.57469 |
| laboratory surveillance capacity | 0.685941 |
| public health laboratories | 0.549957 |
| national arboviral surveillance | 0.796318 |
|
| United States | 0.600691 |
| avian mortality surveillance | 0.700449 |
| mosquito/environmental surveillance | 0.524203 |
| local health department | 0.532756 |
| arboviral activity | 0.639942 |
| adult mosquito surveillance | 0.66282 |
| additional mosquito surveillance | 0.649866 |
| city/county health departments | 0.647254 |
| health departments | 0.739603 |
| surveillance | 0.967029 |
| local health departments | 0.61328 |
| WNV | 0.861473 |
| local arboviral surveillance | 0.668523 |
| mosquito surveillance | 0.842938 |
| New York | 0.583105 |
| arboviral surveillance infrastructure | 0.792997 |
| arboviral disease | 0.627725 |
| dead bird surveillance | 0.669687 |
| active human surveillance | 0.630529 |
| mosquito pools | 0.525001 |
| West Nile virus | 0.77847 |
| arboviral surveillance capacity | 0.68102 |
| ELC funding | 0.727907 |
| current surveillance systems | 0.79938 |
|
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Centers for Disease Control and Prevention |
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Mineral wool fiber - NIOSH Pocket Guide to Chemical Hazards |
null |
| MPEG | 0.378858 |
| search | 0.263099 |
| PDF | 0.261307 |
| PPT | 0.446092 |
|
| DOC | 0.368812 |
| information | 0.262482 |
| different file formats | 0.938484 |
| page | 0.276773 |
|
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| 6097 |
Centers for Disease Control and Prevention |
Html |
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Chlorine - NIOSH Pocket Guide to Chemical Hazards |
null |
| MPEG | 0.378858 |
| search | 0.263099 |
| PDF | 0.261307 |
| PPT | 0.446092 |
|
| DOC | 0.368812 |
| information | 0.262482 |
| different file formats | 0.938484 |
| page | 0.276773 |
|
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| 7199 |
Centers for Disease Control and Prevention |
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Unintentional Drowning: Get the Facts |
null |
| three-sided property-line fencing.12 | 0.605627 |
| Injury Prevention | 0.801581 |
| swimming ability | 0.778197 |
| Product Safety Commission | 0.66366 |
| United States | 0.72293 |
| natural water settings | 0.693957 |
| children 5-19 drown | 0.6841 |
| African Americans | 0.604755 |
| children ages | 0.607222 |
| home swimming | 0.658003 |
| seizure disorders | 0.644959 |
| self-reported swimming ability | 0.728577 |
| childhood drowning | 0.718997 |
| S. Consumer Product | 0.66385 |
| unintentional injuries | 0.663367 |
| nonfatal drowning injuries | 0.840657 |
| children | 0.794212 |
| case-control study | 0.604206 |
| unsupervised water access | 0.64254 |
| water-related recreational activities | 0.619452 |
| swimming pools.2 Drowning | 0.884974 |
| young children | 0.697305 |
| formal swimming lessons | 0.910125 |
| recreational water illnesses | 0.624686 |
|
| four-sided pool fence | 0.622526 |
| Web-based Injury Statistics | 0.612106 |
| Seizure Disorder Safety | 0.616071 |
| National Center | 0.60415 |
| basic swimming skills | 0.654217 |
| life jackets | 0.912487 |
| unintentional injury death | 0.78905 |
| Consumer Product Safety | 0.663669 |
| fatal unintentional drownings | 0.710344 |
| unintentional injury-related death | 0.685837 |
| nonfatal submersion injuries | 0.625559 |
| wear life jackets | 0.717882 |
| unintentional drowning rate | 0.890953 |
| pool area | 0.749145 |
| emergency department care | 0.620585 |
| highest drowning rates | 0.837338 |
| shallow water blackout | 0.621445 |
| fatal unintentional drowning | 0.967152 |
| U. S. Consumer | 0.663859 |
| severe brain damage | 0.607158 |
| pool fencing | 0.658925 |
| motor vehicle crashes | 0.611631 |
| permanent vegetative state | 0.614223 |
|
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| 8362 |
Centers for Disease Control and Prevention |
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Preventing Chronic Disease | Giant Inflatable Colon and Community Knowledge, Intention, and Social Support for Colorectal Cancer Screening - CDC |
Colorectal cancer (CRC) is the second-leading cause of deaths from cancer in the United States. Screening decreases CRC deaths through early cancer detection and through removal of precancerous lesions. |
| potential colon displays | 0.463116 |
| colon cancer screenings | 0.512132 |
| giant inflatable colon | 0.585964 |
| CRC stages | 0.468992 |
| alaska native people | 0.773316 |
| CRC knowledge | 0.551432 |
| giant colon exhibits | 0.4607 |
| Alaska community members | 0.463274 |
| Alaska Native | 0.835412 |
| screening method | 0.46911 |
| interactive colon exhibits | 0.484042 |
| Alaska Tribal Health | 0.515434 |
| colorectal cancer screening | 0.579663 |
| nylon colon model | 0.489328 |
| Cancer Super Colon | 0.51755 |
| social support | 0.609301 |
| colorectal cancer | 0.607456 |
| CRC screening | 0.959501 |
| community events | 0.464513 |
| Health Interview Survey | 0.462518 |
| Alaska Native community | 0.468626 |
| colon model | 0.794332 |
| specific screening method | 0.460382 |
| Cancer Control Program | 0.457245 |
|
| human colon | 0.513328 |
| adult community members | 0.49234 |
| statewide CRC Partnership | 0.478916 |
| CRC prevention tips | 0.520678 |
| community members | 0.782222 |
| cancer screening | 0.671574 |
| Alaska Comprehensive Cancer | 0.469554 |
| Alaska Native Tribal | 0.664603 |
| Native/American Indian/Aboriginal Canadian | 0.516088 |
| Alaska Native population | 0.473903 |
| comprehensive cancer control | 0.506345 |
| CRC screening knowledge | 0.677941 |
| available screening methods | 0.467479 |
| CRC prevention | 0.543565 |
| Colon Cancer Alliance | 0.500946 |
| interactive colon model | 0.545022 |
| CRC screening rates | 0.650429 |
| CRC knowledge questions | 0.504163 |
| cancer screening utilization | 0.48903 |
| Native Tribal Health | 0.656334 |
| Alaska Native/American Indian/Aboriginal | 0.542564 |
| age-adjusted CRC incidence | 0.499893 |
| decreases CRC deaths | 0.505516 |
| Tribal Health Consortium | 0.65147 |
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Norovirus | Symptoms |
Symptoms of norovirus include diarrhea, throwing up, nausea, stomach pain as well as fever, headache and body aches |
| alcohol | 0.457279 |
| minerals | 0.457361 |
| Sports drinks | 0.742887 |
| common symptoms— | 0.65129 |
| tears | 0.461506 |
| illnesses | 0.451931 |
| stomach | 0.469631 |
| plenty | 0.467322 |
| liquids | 0.468735 |
| counter | 0.457961 |
| people | 0.484985 |
|
| diarrhea many times | 0.679606 |
| doctor | 0.453331 |
| caffeine | 0.475306 |
| mild dehydration | 0.984615 |
| Oral rehydration fluids | 0.847047 |
| inflammation | 0.469608 |
| norovirus illness | 0.639684 |
| older adults | 0.638614 |
| young children | 0.622038 |
| acute gastroenteritis | 0.706118 |
| intestines | 0.48174 |
|
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Long-Term Care Toolkit: Importance of Influenza Vaccination for Healthcare Personnel in Long-term Care |
The Importance of Influenza Vaccination for Health Care Personnel in Long-term Care - CDC |
| long-term medical conditions | 0.407647 |
| lab-confirmed flu | 0.417406 |
| Influenza Outbreak Management | 0.471986 |
| Long-Term Care Medicine | 0.410166 |
| influenza-related complications | 0.383495 |
| high flu vaccination | 0.473148 |
| Different flu vaccines | 0.483178 |
| pregnant women | 0.347578 |
| standard flu shots. | 0.466196 |
| Fluzone® High-Dose | 0.348818 |
| health care personnel | 0.985559 |
| health professional organizations | 0.395577 |
| special emphasis | 0.352086 |
| influenza vaccine | 0.606132 |
| vaccine options | 0.408791 |
| chronic medical conditions | 0.380692 |
| MF59 adjuvant | 0.352188 |
| flu hospitalizations | 0.44615 |
| dose influenza vaccine | 0.557038 |
| flu illness | 0.468389 |
| long-term care facility | 0.416069 |
| infected residents | 0.347017 |
| standard dose vaccine | 0.45376 |
| vaccine effectiveness | 0.396306 |
| high risk | 0.474577 |
|
| influenza outbreak | 0.483668 |
| influenza prevention measures | 0.469261 |
| influenza | 0.657668 |
| CDC’s Interim | 0.346093 |
| United States | 0.352302 |
| chronic health conditions | 0.40231 |
| health threat | 0.370091 |
| flu vaccine | 0.584495 |
| Health Care Settings | 0.411144 |
| different people | 0.360347 |
| trivalent vaccine | 0.407273 |
| spray flu vaccine | 0.532242 |
| influenza season | 0.436316 |
| long-term care facilities | 0.542132 |
| recombinant influenza vaccine | 0.555455 |
| flu viruses | 0.426871 |
| Seasonal Influenza | 0.433698 |
| influenza vaccination | 0.491715 |
| people | 0.412161 |
| high dose | 0.384813 |
| mild flu symptoms | 0.456999 |
| influenza infections | 0.435566 |
| ACIP recommendations | 0.354545 |
| older adults | 0.396802 |
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Communication and Leadership Personal Protective Equipment(PPE) | Ebola Hemorrhagic Fever | CDC |
null |
| ease | 0.348097 |
| casual observer | 0.581097 |
| challenges | 0.341969 |
| example | 0.339273 |
| demands active communication | 0.753606 |
| safety | 0.387006 |
| patient | 0.337419 |
| leadership | 0.337945 |
| verbal explanations | 0.531088 |
| healthcare worker | 0.95933 |
| situations | 0.342228 |
| proper communication protocols | 0.674693 |
| mind | 0.3377 |
| process | 0.431134 |
|
| Trained Observer | 0.576817 |
| equipment | 0.337569 |
| role clarity | 0.569702 |
| ‘red flag | 0.505215 |
| priority | 0.351903 |
| donning | 0.397856 |
| steps | 0.342604 |
| command | 0.382996 |
| clear roles | 0.543811 |
| extra diligence | 0.532482 |
| methodical pace | 0.551792 |
| closed-loop communication | 0.525122 |
| misunderstandings | 0.36107 |
| job | 0.339031 |
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