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Graphs of the Year: Nightmare bacteria spread and 100,000 smokers likely quit with Tips | CDC Newsroom | CDC |
CDC’s Graphs of the Year: Nightmare bacteria spread and 100,000 smokers likely quit with Tips |
| CDC recommendations | 0.528949 |
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| Nation’s Health | 0.389265 |
| 50th anniversary | 0.385005 |
| nightmare bacteria | 0.426275 |
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| Disease Control | 0.387203 |
| secondhand smoke | 0.370092 |
| medical facility | 0.409423 |
| non-smokers | 0.241128 |
| Smokers campaign | 0.632058 |
| additional calls | 0.377662 |
| Americans | 0.349948 |
| health challenges | 0.380307 |
| strongest antibiotics | 0.417183 |
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| daily smokers | 0.488711 |
| painful effects | 0.377818 |
| CRE | 0.390189 |
| HUMAN SERVICES | 0.374105 |
| nightmare bacteria. | 0.426059 |
| Director Tom Frieden | 0.902574 |
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| health worries | 0.394937 |
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| Tips campaign | 0.383457 |
| cigarette smoking | 0.423488 |
| U.S. DEPARTMENT | 0.374338 |
| preventable death | 0.389763 |
| M.P.H | 0.245906 |
| health care expenses | 0.535844 |
| public health | 0.405225 |
| taxpayer-supported payments | 0.37595 |
| n’t work | 0.395059 |
| likely quit smoking | 0.591969 |
| plasmids | 0.247922 |
| CDC Director Tom | 0.980445 |
| Smoking-related diseases | 0.408935 |
| Healthcare facilities | 0.38888 |
| people | 0.26395 |
| Surgeon General | 0.380583 |
| carbapenem-resistant Enterobacteriaceae | 0.413458 |
| microbes | 0.283083 |
| potentially untreatable infections | 0.599243 |
| report | 0.263873 |
| antibiotic resistance threat | 0.557988 |
| medical facilities | 0.407448 |
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Science Clips - Monday, January 24, 2011 |
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| adult community-acquired pneumonia | 0.772959 |
| Med Inform Assoc. | 0.773742 |
| rotavirus hospitalization disease | 0.784335 |
| Marston BJ | 0.781348 |
| suboptimal glycemic control | 0.76609 |
| CDC Science Clips | 0.893327 |
| Appl Environ Microbiol. | 0.77597 |
| rotavirus vaccine program | 0.782804 |
| real-time reverse-transcriptase polymerase | 0.764209 |
| Arch Dis Child. | 0.7611 |
| Chief Science Officer | 0.783343 |
| postnatally HIV-infected children | 0.77566 |
| Bartonella vinsonii subsp. | 0.772965 |
| trivalent polio vaccine | 0.766185 |
| rural western Kenya | 0.770165 |
| clinician-ordered rapid antigen | 0.763937 |
| Parashar UD | 0.774736 |
| influenza vaccine effectiveness | 0.768297 |
| Stephen B. Thacker | 0.845308 |
| Self-reported influenza-like illness | 0.75997 |
| New gene variants | 0.761405 |
| national worklife priorities | 0.762881 |
| High Alt Med | 0.774637 |
| United States | 0.817592 |
| specific airway resistance | 0.762021 |
|
| artificial human lung | 0.761478 |
| virus polyprotein sites | 0.761712 |
| Bresee JS | 0.783693 |
| proportional hazards model | 0.760473 |
| CDC’s Community | 0.791959 |
| United States Whites | 0.772657 |
| Patient Educ Couns. | 0.76938 |
| Acquir Immune Defic | 0.769582 |
| urine antigen detection | 0.778415 |
| Database Syst Rev. | 0.770896 |
| public health | 0.776577 |
| Jackson Heart Study | 0.782206 |
| treatment decision-making process | 0.774089 |
| public health literature | 0.775793 |
| breast cancer | 0.771665 |
| oxide particle/fiber mixtures | 0.762392 |
| B. Thacker CDC | 0.882651 |
| Ind Med. | 0.81642 |
| systematic review | 0.769922 |
| modeling HIV susceptibility | 0.763709 |
| Health Belief Model | 0.772275 |
| Jan | 0.998928 |
| Crit Care Med. | 0.785678 |
| latent tuberculosis infection | 0.770291 |
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Science Clips - Monday, April 05, 2010 |
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| endorsement | 0.374074 |
| Prevalence | 0.320102 |
| Issue | 0.320056 |
| current awareness | 0.397539 |
| findings | 0.332494 |
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| Disease Control | 0.394967 |
| CDC Knowledge | 0.622003 |
| Action Science Clips | 0.952119 |
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| new weekly digest | 0.510057 |
| Chief Science Officer | 0.498203 |
| conclusions | 0.318931 |
| patients | 0.316629 |
| human pulmonary sources | 0.485696 |
| article | 0.327462 |
| DHHS | 0.420349 |
| DISCLAIMER | 0.323153 |
| public domain | 0.404358 |
| Stephen B. Thacker | 0.687446 |
| Emergency department visits | 0.485898 |
| dementia | 0.317908 |
| Rubella virus genotypes | 0.514346 |
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| items | 0.338856 |
| components | 0.318669 |
| Nocardia niwae sp. | 0.482362 |
| United States | 0.400098 |
| inclusion | 0.317082 |
| China | 0.316857 |
| omission | 0.324041 |
| views | 0.328158 |
| informational purposes | 0.389958 |
| People | 0.316879 |
| public health literature | 0.47767 |
| descriptive study | 0.401709 |
| permission | 0.319586 |
| B. Thacker CDC | 0.822501 |
| original authors | 0.395813 |
| endemic viruses | 0.405101 |
| opinion | 0.328796 |
| non-CDC Websites | 0.394879 |
| original sources | 0.405787 |
| Vol. | 0.320076 |
| service | 0.317553 |
| news sources | 0.397326 |
| report | 0.318694 |
| Thacker CDC Library | 0.822326 |
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Centers for Disease Control and Prevention |
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Preventing Chronic Disease | Expansion of Electronic HealthRecord-Based Screening, Prevention, and Management of Diabetes inNew York City - CDC |
To address the increasing burden of diabetes in New York City, we designed 2 electronic health records (EHRs)-facilitated diabetes management systems to be implemented in 6 primary care practices on the West Side of Manhattan, a standard system and an enhanced system. The standard system includes screening for diabetes. |
| diabetes prevention | 0.654428 |
| standard diabetes management | 0.62832 |
| Diabetes Educ | 0.534914 |
| IT-based diabetes management | 0.534008 |
| primary care physician | 0.486341 |
| HbA1c measurement | 0.46943 |
| New York City | 0.542709 |
| Vermont Diabetes Information | 0.510165 |
| final hba1c | 0.504446 |
| primary care practices | 0.554767 |
| primary care practice | 0.548624 |
| newly diagnosed diabetes | 0.720095 |
| participant HbA1c levels | 0.500942 |
| evidence-based diabetes management | 0.577525 |
| HbA1c tests | 0.565697 |
| patients | 0.502541 |
| baseline HbA1c | 0.524879 |
| HbA1c values | 0.482436 |
| enhanced diabetes management | 0.640965 |
| HbA1c measures | 0.47416 |
| established diabetes prevention | 0.547318 |
| chronic care model | 0.525809 |
| log-transformed HbA1c measure | 0.487378 |
| new-onset diabetes | 0.501683 |
|
| primary care clinics | 0.48976 |
| diabetes care | 0.708109 |
| diabetes screening | 0.5086 |
| HbA1c test | 0.47077 |
| HbA1c levels | 0.660464 |
| HbA1c measurements | 0.502134 |
| health care | 0.631659 |
| health care systems | 0.472761 |
| New York | 0.675889 |
| Diabetes Cost-Effectiveness Study | 0.532528 |
| electronic health records | 0.50425 |
| previously undiagnosed diabetes | 0.542974 |
| diabetes management systems | 0.625326 |
| routine diabetes care | 0.608804 |
| diabetes prevention behaviour | 0.531707 |
| diabetes management | 0.823149 |
| Diabetes Prevention Program | 0.559978 |
| et al | 0.554064 |
| patient-centered medical home | 0.490998 |
| primary care | 0.711042 |
| American Diabetes Association | 0.594074 |
| HbA1c improvements | 0.484266 |
| HbA1c outcomes | 0.471203 |
| diabetes | 0.921546 |
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Climate Change and Health - Health Communication |
Climate Change and Health - Gateway to Health Communication - CDC |
| extent | 0.528952 |
| greenhouse gases | 0.57591 |
| faster increase | 0.574848 |
| GHGs | 0.5515 |
| basic requirements | 0.63385 |
| number | 0.512174 |
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| homes | 0.513271 |
| clean air | 0.568717 |
| heat stroke | 0.56507 |
| climate change | 0.904066 |
| energy | 0.525182 |
| drastic warming | 0.583513 |
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| Daniel | 0.554377 |
| average global temperature | 0.633221 |
| quality | 0.513247 |
| secure shelter | 0.570777 |
| current rate | 0.566656 |
| light | 0.513282 |
| coal | 0.512191 |
| heat waves | 0.565416 |
| health effects | 0.685639 |
| specific health risks | 0.62413 |
|
| mid-July heat wave | 0.622812 |
| improved health | 0.568046 |
| teammate notices | 0.565302 |
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| GHG emissions | 0.639404 |
| hot skin | 0.562431 |
| recent decades | 0.577251 |
| life | 0.513241 |
| result | 0.52627 |
| ways | 0.524273 |
| oil | 0.513309 |
| common Heat Related | 0.619608 |
| global climate change | 0.779692 |
| football player | 0.564102 |
| 17-year-old high school | 0.620721 |
| rainfall | 0.515221 |
| human activities | 0.635827 |
| burning fossil fuels | 0.637491 |
| interventions | 0.512418 |
| future climate change | 0.678875 |
| wind patterns | 0.578126 |
| earth | 0.557107 |
| sufficient food | 0.572757 |
| excess deaths | 0.575466 |
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Vital Signs: Overdoses of Prescription Opioid Pain Relieversand Other Drugs Among Women - United States, 1999-2010 |
Persons using assistive technology might not be able to fully access information in this file. For assistance, please send e-mail to: mmwrq@cdc.gov. |
| highest ED visit | 0.41494 |
| OPR | 0.731784 |
| long-term OPR | 0.461925 |
| Cocaine deaths | 0.421751 |
| prescription drugs | 0.399692 |
| OPR overdose death | 0.553641 |
| OPR overdose deaths | 0.720211 |
| suicide drug overdose | 0.442813 |
| Drug Abuse Warning | 0.437945 |
| drug monitoring program | 0.388294 |
| opioid pain relievers | 0.425961 |
| bridged-race population estimates | 0.386441 |
| National Vital Statistics | 0.395136 |
| OPR abuse | 0.477697 |
| Abuse Warning Network | 0.409921 |
| injury deaths | 0.403036 |
| abuse-related ED visits | 0.559327 |
| prescription drug monitoring | 0.430819 |
| ED visit rates | 0.525261 |
| OPR deaths | 0.636882 |
| drug-related deaths | 0.412691 |
| Drug poisoning deaths | 0.455089 |
| women | 0.604918 |
| OPR overdoses | 0.469726 |
| United States | 0.448695 |
|
| drug overdoses | 0.435783 |
| ED visits | 0.868651 |
| health-care providers | 0.435684 |
| OPR misuse | 0.481382 |
| overdose death rates | 0.509503 |
| overdose–related suicide deaths | 0.417329 |
| drug-specified deaths | 0.399076 |
| OPR death rates | 0.500521 |
| prescription drug overdose | 0.490215 |
| unintentional pharmaceutical overdose | 0.405107 |
| Age-adjusted drug overdose | 0.47325 |
| OPR rate | 0.470664 |
| substance abuse | 0.410037 |
| heroin deaths | 0.400617 |
| overdose death rate | 0.439839 |
| public health | 0.398002 |
| fatal drug overdoses | 0.391209 |
| drug overdose deaths | 0.907127 |
| hospital ED visits | 0.397489 |
| drug overdose death | 0.603426 |
| prescription OPR | 0.475307 |
| highest drug overdose | 0.443439 |
| chronic opioid therapy | 0.393685 |
| et al | 0.427215 |
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Centers for Disease Control and Prevention |
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Prepare su casa|Temporada invernal |
Tomar medidas preventivas es su mejor protección contra las temperaturas frías extremas. Usted puede reducir el riesgo de sufrir afecciones atribuidas a las condiciones climáticas si prepara su casa y auto con antelación para las emergencias de invierno y si toma precauciones de seguridad durante las temperaturas extremadamente frías. |
| Archivo Apple Quicktime | 0.608606 |
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| Archivo Zip Comprimido | 0.603548 |
| Archivo Microsoft PowerPoint | 0.625342 |
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| Archivo Adobe PDF | 0.604772 |
| Archivo Microsoft Excel | 0.59788 |
| Coloque masilla | 0.523119 |
| Archivo Microsoft | 0.915959 |
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Roadmap for State Program Planning - Collect Resources and Data Establish Partnerships'State Resources'DHDSP'CDC |
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| current policies | 0.442928 |
| complementary resources | 0.452914 |
| potential partner organizations | 0.682049 |
| business groups | 0.439004 |
| high blood cholesterol | 0.57831 |
| San Diego | 0.445406 |
| bigger impact | 0.458721 |
| common ground | 0.442158 |
| American Stroke Association | 0.575295 |
| quick reference | 0.43586 |
| HDSP program | 0.471027 |
| Partnerships Analysis Tool | 0.6977 |
| important vehicle | 0.461997 |
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| quality assurance | 0.446284 |
| Educate potential partners | 0.610266 |
| heart health | 0.473467 |
| business cards | 0.446513 |
| share responsibility | 0.449443 |
| Campaign Consultation | 0.445781 |
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| effective health promotion | 0.613909 |
| joint advocacy | 0.457444 |
| cardiovascular health | 0.603314 |
| emergency medical services | 0.577007 |
| potential partners | 0.93455 |
| burden data | 0.564552 |
| disease prevention | 0.460436 |
| state health department | 0.611763 |
| heart disease | 0.600232 |
| private sectors | 0.44926 |
| diverse partners | 0.481571 |
| health care | 0.47075 |
| Internal partnerships | 0.559943 |
| Stroke Prevention | 0.47906 |
| HDS burden | 0.475084 |
| press releases | 0.443638 |
| potential partner | 0.830894 |
| following types | 0.444303 |
| successful partnerships | 0.623751 |
| HDS-related risk factors | 0.572834 |
| vital statistics | 0.44436 |
| high blood pressure | 0.57755 |
| Sustain Institute | 0.446782 |
| business card | 0.438179 |
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CDC - Skin Cancer Prevention Fact Sheets |
These fact sheets list skin cancer prevention strategies for parents, teachers, employers, and parks and recreation staff. |
| proven education programs | 0.621633 |
| skin cancer | 0.895654 |
| sunbathing | 0.345063 |
| UV rays | 0.443541 |
| sun-safe behaviors | 0.427367 |
| skin cancers | 0.487604 |
| parks | 0.282965 |
| su familia | 0.466486 |
| school | 0.239762 |
| long-sleeved shirt | 0.452575 |
| sun protection items | 0.605961 |
| fact sheets list | 0.660699 |
| safe workplace | 0.418285 |
| sunglasses | 0.246046 |
| recreation staff | 0.641203 |
| midday | 0.441532 |
| wide-brimmed hat | 0.439131 |
| shade | 0.359988 |
| Visitors | 0.267456 |
| discourage children | 0.495143 |
| sun protection | 0.781218 |
| Proteja | 0.278879 |
| Fellow Staff Members | 0.614851 |
| umbrellas | 0.243072 |
|
| Recess | 0.257405 |
| parents | 0.242324 |
| United States | 0.472418 |
| broad-spectrum sunscreen | 0.776448 |
| wide-brimmed hats | 0.415816 |
| layer | 0.242025 |
| high-use areas | 0.417139 |
| sus | 0.256594 |
| Stay sun-safe outdoors | 0.64538 |
| productivity | 0.278199 |
| teachers | 0.242292 |
| sun protection gear | 0.650083 |
| cáncer | 0.278727 |
| outdoor workers | 0.415293 |
| strategies | 0.242355 |
| outdoor activities | 0.428815 |
| protective clothing | 0.417559 |
| Skin Cancer. | 0.985322 |
| indoor tanning | 0.665859 |
| people | 0.246085 |
| outdoor recreational areas | 0.604227 |
| money | 0.239066 |
| sun exposure | 0.42678 |
| Family | 0.241838 |
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School District Crisis Preparedness, Response, and RecoveryPlans - United States, 2012 | MMWR |
The Morbidity and Mortality Weekly Report (MMWR) Series is prepared by the Centers for Disease Control and Prevention (CDC). |
| disaster preparedness planning | 0.572537 |
| school district level | 0.402299 |
| nonurban districts | 0.546919 |
| all-hazards response plans | 0.386748 |
| U.S. Department | 0.450355 |
| community preparedness | 0.379865 |
| health preparedness plans | 0.529726 |
| school districts | 0.69797 |
| school district preparedness | 0.524297 |
| infectious disease outbreaks | 0.749757 |
| mental health services | 0.685332 |
| crisis preparedness plans | 0.741056 |
| Services Emergency Preparedness | 0.432195 |
| school health policies | 0.590865 |
| disaster planning | 0.431639 |
| public health practice | 0.468586 |
| urban districts | 0.54717 |
| school preparedness plans | 0.541061 |
| schools | 0.4631 |
| school crisis preparedness | 0.487852 |
| child care facilities | 0.410765 |
| crisis preparedness | 0.795295 |
| community-based preparedness planning | 0.444437 |
| public school districts | 0.485882 |
| vulnerable population | 0.400192 |
|
| districts | 0.74975 |
| Southern districts | 0.37385 |
| family reunification procedures | 0.604828 |
| preparedness planning | 0.652021 |
| school disaster planning | 0.383747 |
| pandemic influenza | 0.510795 |
| school district–level data | 0.388573 |
| census regions | 0.394579 |
| Healthy People | 0.39165 |
| special needs | 0.645482 |
| school staff members | 0.38452 |
| community partners | 0.411147 |
| staff members | 0.946565 |
| law enforcement agencies | 0.458124 |
| local mental health | 0.370412 |
| safe school environment | 0.485098 |
| school environment questionnaire | 0.477708 |
| district–based disaster preparedness | 0.467652 |
| specific topics | 0.629963 |
| local law enforcement | 0.458781 |
| unique vulnerabilities | 0.408273 |
| preparedness objectives | 0.394811 |
| school-based preparedness | 0.458887 |
| National Report Card | 0.437312 |
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