| 5088 |
Centers for Disease Control and Prevention |
Html |
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Science Clips - Monday, April 12, 2010 |
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| Apr | 0.712236 |
| total blood volume | 0.67991 |
| Intermittent preventive treatment | 0.676296 |
| PLoS ONE. | 0.745366 |
| serum cotinine levels | 0.678989 |
| CDC Knowledge | 0.73233 |
| passive immune therapy | 0.6746 |
| Hunter New England | 0.683143 |
| Action Science Clips | 0.971953 |
| Community Dent Oral | 0.678945 |
| fulminant bacterial infections | 0.674061 |
| new weekly digest | 0.695343 |
| social marketing intervention | 0.679115 |
| State cigarette minimum | 0.674041 |
| Northern New South | 0.687862 |
| body mass index | 0.683795 |
| Chief Science Officer | 0.696806 |
| high body mass | 0.697647 |
| State cigarette excise | 0.676539 |
| VZV Nomenclature Meeting | 0.68083 |
| HIV type | 0.676484 |
| cancer news coverage | 0.760944 |
| Defects Prevention Study | 0.69289 |
| news coverage trends | 0.749588 |
| Clin Chim Acta. | 0.694785 |
|
| type 1-infected patients | 0.686327 |
| planned behavior perspective | 0.670303 |
| Stephen B. Thacker | 0.76838 |
| Plasmodium falciparum multidrug | 0.684739 |
| Yanovski JA | 0.673337 |
| Proc Natl Acad | 0.67902 |
| ter Kuile FO | 0.682318 |
| Lyme disease agent | 0.677967 |
| comprehensive content analyses | 0.751425 |
| Serotype specific antisera | 0.680224 |
| HIV Outpatient Study | 0.689503 |
| rural Western Kenya | 0.674489 |
| Patient Educ Couns. | 0.675236 |
| newly diagnosed HIV | 0.679352 |
| Multiple genetic backgrounds | 0.677348 |
| species varicella-zoster virus | 0.678581 |
| potential human health | 0.692755 |
| double-blind placebo-controlled trial | 0.681529 |
| public health literature | 0.693747 |
| B. Thacker CDC | 0.806041 |
| et al | 0.674303 |
| study National Birth | 0.693052 |
| national survey data | 0.691183 |
| Thacker CDC Library | 0.806025 |
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Centers for Disease Control and Prevention |
Html |
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Fenamiphos - NIOSH Pocket Guide to Chemical Hazards |
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| MPEG | 0.378858 |
| search | 0.263099 |
| PDF | 0.261307 |
| PPT | 0.446092 |
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| DOC | 0.368812 |
| information | 0.262482 |
| different file formats | 0.938484 |
| page | 0.276773 |
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| 8987 |
Centers for Disease Control and Prevention |
Video |
en |
CDC: Tips From Former Smokers - Tiffany: You Don't Quit Just for Yourself |
Tiffany talks about losing her mother, a smoker, to lung cancer when she was 16. Despite this, Tiffany smoked for years before realizing what she might miss in her own daughter's life. In this video from CDC's Tips From Former Smokers campaign, Tiffany's daughter's, Jaelin, says she cannot imagine living without her mother. Jaelin goes on to tell her mom how proud she is of her for quitting smoking for good.
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://streaming.cdc.gov/vod.php?id=ff67b50b6de6064f26c7bb347d2aa68f20130326152816255 |
| Tiffany | 0.974332 |
| Smokers | 0.996151 |
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| CDC | 0.979113 |
| YouTube | 0.926248 |
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Centers for Disease Control and Prevention |
Html |
en |
Roadmap for State Program Planning - Tools'State Resources'DHDSP'CDC |
null |
| track health objectives | 0.595512 |
| BRFSS core health | 0.619911 |
| tool create online | 0.549584 |
| health promotion projects | 0.582245 |
| stroke mortality rates | 0.769406 |
| high blood cholesterol | 0.545036 |
| social determinants | 0.532768 |
| health topics | 0.5317 |
| evaluation plan | 0.538399 |
| congestive heart failure | 0.579325 |
| best practice programs | 0.538676 |
| national monitoring data | 0.553167 |
| National Center | 0.542361 |
| Partnerships Analysis Tool | 0.62532 |
| Stroke Statistics | 0.571663 |
| data collection program | 0.567025 |
| heart disease statistics | 0.688845 |
| Stroke Treatment Program | 0.612033 |
| American Heart Association | 0.601472 |
| Health Maps | 0.542437 |
| Health Statistics | 0.589806 |
| Chronic Disease Cost | 0.590778 |
| health problems | 0.532857 |
| current county-level variables | 0.559807 |
| Stroke Prevention Management | 0.618575 |
|
| Behavioral Risk Factor | 0.53794 |
| heart disease death | 0.659176 |
| public domain software | 0.541368 |
| health promotion | 0.63641 |
| CDC HDSP Program | 0.552327 |
| Community Tool Box | 0.55862 |
| stroke prevention programs | 0.754572 |
| heart disease | 0.948698 |
| Survey Generation Tool | 0.549882 |
| county heart disease | 0.636685 |
| public health professionals | 0.597239 |
| Gantt chart-based project | 0.542994 |
| CDC Heart Disease | 0.646107 |
| Metropolitan/Micropolitan Area Risk | 0.548198 |
| ASTP guides hospitals | 0.542125 |
| Primary Stroke Center | 0.607947 |
| primary health care | 0.576283 |
| chronic disease programs | 0.580637 |
| in-hospital resuscitation teams | 0.53831 |
| prevention programs development | 0.57667 |
| high blood pressure | 0.535309 |
| Wizard (PEW) | 0.544843 |
| Community Preventive Services | 0.533652 |
| coronary heart disease | 0.62738 |
|
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| 11573 |
Centers for Disease Control and Prevention |
Html |
en |
NER - Peer-Reviewed Biomonitoring Articles | Environmental Phenols: Triclosan |
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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| 11745 |
Centers for Disease Control and Prevention |
Html |
en |
Norovirus | Reporting and Surveillance | CDC |
Reporting and surveillance of norovirus utilizing NORS and CalicNet |
| norovirus outbreaks | 0.953408 |
| Public health agencies | 0.352689 |
| United States | 0.342611 |
| national surveillance | 0.234475 |
| current norovirus outbreak | 0.465697 |
| CDC surveillance systems | 0.442383 |
| norovirus outbreak | 0.566914 |
| territorial health departments | 0.418576 |
| monitor norovirus strains | 0.480894 |
| norovirus outbreak surveillance | 0.537489 |
| norovirus illness | 0.686194 |
| territorial health department | 0.374856 |
| state health departments | 0.564169 |
| new strains | 0.268574 |
| health departments | 0.696515 |
|
| Health care providers | 0.367036 |
| acute gastroenteritis | 0.262205 |
| surveillance network | 0.445316 |
| assess strain-specific characteristics | 0.293939 |
| Vaccine Surveillance Network | 0.338513 |
| norovirus outbreak reporting | 0.472749 |
| doctor’s offices | 0.200872 |
| local public health | 0.339475 |
| National Outbreak Reporting | 0.463785 |
| Norovirus Sentinel Testing | 0.367545 |
| outbreak frequency | 0.266077 |
| public health laboratories | 0.598862 |
| laboratory data | 0.320977 |
| Active Surveillance Network | 0.339337 |
|
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| 12295 |
Centers for Disease Control and Prevention |
Html |
en |
Non-Polio Enterovirus | Transmission Non-Polio Enterovirus Infection | Picornavirus | CDC |
You can get infected with non-polio enteroviruses by having close contact with an infected person. Also spread by touching objects or surfaces that have the virus on them and then touching your mouth, nose, or eyes. |
| stool | 0.418736 |
| hands | 0.447013 |
| objects | 0.334489 |
| sputum | 0.335759 |
| babies | 0.335386 |
| eyes | 0.383484 |
| Mothers | 0.336983 |
| navigation Skip | 0.615467 |
| coughing | 0.344144 |
| sneezing | 0.350418 |
| diapers | 0.345993 |
| mouth secretions | 0.551455 |
| close contact | 0.491626 |
| Infected people | 0.593088 |
| nasal mucus | 0.535609 |
| nose | 0.464758 |
| delivery | 0.332956 |
|
| non-polio enteroviruses | 0.720976 |
| list Skip | 0.616861 |
| pass | 0.337555 |
| page options Skip | 0.781747 |
| blister fluid | 0.5119 |
| Non-Polio Enterovirus Infection | 0.684831 |
| water | 0.335221 |
| infected person | 0.912067 |
| saliva | 0.352754 |
| eye | 0.336001 |
| doctor | 0.33318 |
| Pregnancy | 0.332548 |
| Pregnant women | 0.48825 |
| respiratory tract | 0.479622 |
| non-polio enteroviruses infection | 0.680301 |
| information | 0.332592 |
| feces | 0.36251 |
|
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Centers for Disease Control and Prevention |
Html |
en |
Progress Toward Measles Elimination - South-East AsiaRegion, 2003-2013 |
Arun Thapa, MD1; Sudhir Khanal, MPH1; Umid Sharapov, MD2; Virginia Swezy, MPH1; Tika Sedai, MA1; Alya Dabbagh, PhD3; Paul Rota, PhD4; James L. Goodson, MPH2; Jeffrey McFarland, MD1 (Author affiliations at end of text). |
| measles elimination platform | 0.469388 |
| endemic measles virus | 0.440691 |
| measles elimination | 0.837069 |
| measles incidence | 0.584168 |
| measles laboratory network | 0.50276 |
| aggregate measles surveillance | 0.474146 |
| measles genotypes | 0.406827 |
| routine immunization | 0.340674 |
| measles outbreaks | 0.561745 |
| MCV1 coverage | 0.308762 |
| timely case-based measles | 0.498258 |
| routine immunization services | 0.30856 |
| measles control | 0.415283 |
| World Health Organization | 0.4085 |
| measles virus genotypes | 0.446291 |
| Rubella Laboratory Network | 0.318499 |
| countries | 0.372906 |
| measles elimination activities | 0.461883 |
| Rubella Strategic Plan | 0.303569 |
| laboratory-confirmed measles outbreaks | 0.543037 |
| measles epidemiology | 0.411126 |
| congenital rubella syndrome | 0.466683 |
| rubella syndrome control | 0.459724 |
| measles case-based surveillance | 0.507425 |
| MCV2 coverage | 0.335589 |
|
| laboratory-confirmed measles cases | 0.453367 |
| Global Measles | 0.463257 |
| south-east asia region | 0.771863 |
| regional measles mortality | 0.451228 |
| laboratory-confirmed rubella outbreaks | 0.325887 |
| South-East Asia Region* | 0.31777 |
| laboratory-confirmed mixed measles | 0.457113 |
| measles elimination goal | 0.576663 |
| measles cases | 0.461191 |
| Asia Regional Office | 0.347612 |
| measles SIAs | 0.457287 |
| Regional Committee | 0.324839 |
| rubella/congenital rubella syndrome | 0.303718 |
| coverage | 0.351446 |
| South-East Asia Regional | 0.361093 |
| measles surveillance data | 0.506908 |
| target population | 0.312665 |
| Sri Lanka | 0.324549 |
| annual measles incidence | 0.461823 |
| rubella outbreaks | 0.343385 |
| case-based measles surveillance | 0.574895 |
| periodic high-quality SIAs | 0.307003 |
| routine immunization program | 0.301291 |
| measles deaths | 0.482338 |
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Cancer Prevention Starts in Childhood |
You can lower your children's risk of getting cancer later in life by helping them adopt a healthy lifestyle and following these tips to help prevent specific kinds of cancer. |
| young women | 0.334666 |
| skin cancer | 0.3595 |
| people’s cigarettes | 0.319467 |
| Indoor tanning | 0.36414 |
| safe level | 0.333316 |
| specific kinds | 0.373879 |
| children’s risk | 0.368375 |
| oropharyngeal cancers | 0.376264 |
| best way | 0.336271 |
| HPV vaccine | 0.904669 |
| lung cancer | 0.328212 |
| healthy choices | 0.373579 |
| sun safety tips | 0.556121 |
| Human papillomavirus | 0.370935 |
| teens tan | 0.354641 |
| smoking | 0.251205 |
| secondhand smoke | 0.416016 |
|
| HPV vaccine series | 0.725466 |
| Teen girls | 0.33186 |
| visit www.cdc.gov/quit | 0.323091 |
| commonly cause cancer | 0.577469 |
| common virus | 0.34591 |
| start | 0.21213 |
| healthy weight | 0.37262 |
| young men | 0.333856 |
| free support | 0.328662 |
| high school students | 0.519479 |
| cervical cancer | 0.361665 |
| tobacco products | 0.328026 |
| regular physical activity | 0.608424 |
| current cigarette smoker | 0.530282 |
| teen boys | 0.331061 |
| main cause | 0.374642 |
|
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Vaccination Coverage Among Children in Kindergarten - UnitedStates, 2015-16 School Year | MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| complete vaccination | 0.250263 |
| nonmedical exemptions | 0.303544 |
| median MMR coverage | 0.239456 |
| data | 0.680109 |
| catch-up vaccination schedule | 0.2624 |
| exemption | 0.44916 |
| New York City | 0.289999 |
| vaccination coverage | 0.96494 |
| period/provisional enrollment data | 0.278972 |
| school | 0.616396 |
| medical exemptions | 0.337576 |
| children | 0.294751 |
| kindergartners | 0.385646 |
| median exemption rate | 0.296183 |
| vaccination assessments | 0.257926 |
| varicella vaccine | 0.444936 |
| school entry | 0.37222 |
| acellular pertussis vaccine | 0.306489 |
| median vaccination coverage | 0.320837 |
| vaccination coverage data | 0.314113 |
| private school data | 0.24665 |
| school vaccination coverage | 0.314544 |
| provisional enrollment | 0.690162 |
| kindergarten vaccination | 0.313815 |
| grace period | 0.661534 |
|
| schools | 0.297357 |
| Median vaccination coverage* | 0.261228 |
| state-level vaccination coverage | 0.259599 |
| rubella vaccines | 0.296301 |
| high vaccination coverage | 0.240174 |
| doses | 0.548004 |
| MMR coverage | 0.356631 |
| vaccination requirements | 0.250466 |
| public school data | 0.361154 |
| states | 0.813703 |
| percentage points | 0.315128 |
| kindergarten vaccination data | 0.300031 |
| immunization programs | 0.443042 |
| rubella vaccine | 0.295852 |
| exemptions | 0.529276 |
| grace period/provisional enrollment | 0.524925 |
| 50 states | 0.37992 |
| missing vaccine doses | 0.250586 |
| varicella vaccine coverage | 0.240056 |
| DTaP vaccine | 0.23939 |
| median kindergarten vaccination | 0.244831 |
| vaccine | 0.450889 |
| exemption data | 0.372796 |
| vaccine-preventable diseases | 0.262809 |
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