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Centers for Disease Control and Prevention |
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VFC Program | CDC Features |
The Vaccines for Children (VFC) Program offers vaccines at no cost for eligible children through doctors enrolled in the program. Find out if your child qualifies. Vaccinating on time means healthier children, families and communities. |
| healthcare providers | 0.352856 |
| Centers | 0.226435 |
| VFC Program Coordinator | 0.854144 |
| CDC | 0.251977 |
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| vaccines | 0.748766 |
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| RHC | 0.269006 |
| Medicaid Services | 0.35548 |
| local health department | 0.544887 |
| Rural Health Clinics | 0.590484 |
| Disease Control | 0.341879 |
| children | 0.652203 |
| territorial health department | 0.559091 |
|
| state health departments | 0.55046 |
| young children | 0.387671 |
| following requirements | 0.369898 |
| eligible children | 0.645927 |
| health care | 0.36802 |
| *Underinsured children | 0.379627 |
| Medicare | 0.202669 |
| VFC Program | 0.960377 |
| city’s VFC | 0.4932 |
| better chance | 0.377315 |
| medically underserved areas | 0.597482 |
| certain criteria | 0.358609 |
| Medicaid programs | 0.377378 |
| healthier children | 0.407541 |
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A framework for disseminating evidence-based health promotion practices |
Wider adoption of evidence-based, health promotion practices depends on developing and testing effective dissemination approaches. |
| ACS WPS | 0.545488 |
| dissemination efforts | 0.509306 |
| dissemination challenge | 0.496357 |
| dissemination approach | 0.634392 |
| Senior Services | 0.528888 |
| HPRC framework | 0.526298 |
| dissemination process | 0.552178 |
| American Cancer Society | 0.554168 |
| dissemination | 0.834214 |
| Health Promotion Research | 0.564636 |
| theory-based dissemination approaches | 0.523701 |
| ACS National Home | 0.493451 |
| active dissemination process | 0.531957 |
| ACS WPS practices | 0.49339 |
| researchers | 0.515738 |
| research dissemination | 0.514271 |
| workplace health promotion | 0.504209 |
| Washington Health Promotion | 0.493606 |
| Successful dissemination | 0.508276 |
| Dissemination results | 0.521869 |
| potential user organizations | 0.511767 |
| dissemination approaches | 0.750718 |
| user organizations | 0.946433 |
| larger dissemination approach | 0.533378 |
| health promotion | 0.655506 |
|
| user organization | 0.531043 |
| social marketing | 0.510771 |
| dissemination research | 0.562713 |
| dissemination effectiveness | 0.518886 |
| evidence-based practice | 0.503493 |
| effective dissemination approaches | 0.55196 |
| key dissemination resources | 0.51901 |
| dissemination framework | 0.547887 |
| public health | 0.589327 |
| evidence-based practices | 0.898909 |
| Figure. The dissemination | 0.512613 |
| evidence-based workplace health | 0.513164 |
| implementation | 0.494574 |
| Disseminating Evidence-Based Practices | 0.499145 |
| physical activity | 0.535429 |
| health promotion practices | 0.591229 |
| dissemination resources | 0.530776 |
| framework | 0.581425 |
| older adults | 0.511203 |
| evidence-based health promotion | 0.50636 |
| testing dissemination approaches | 0.525357 |
| outer context | 0.558422 |
| Promotion Research Center | 0.5543 |
| dissemination strategy | 0.498847 |
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Global Health - Thailand |
null |
| transient mobile populations | 0.535705 |
| new disease prevention | 0.585065 |
| CDC | 0.804812 |
| new HIV infections | 0.627939 |
| PMI regional strategy | 0.558329 |
| emergency outbreak response | 0.544185 |
| HIV programs | 0.542513 |
| infectious diseases | 0.728917 |
| Thailand MoPH | 0.607369 |
| Respiratory Syndrome Coronavirus | 0.535418 |
| South East Asia | 0.540674 |
| significant global impacts | 0.557205 |
| HIV research | 0.540629 |
| recent multi-country study | 0.540486 |
| extensive global health | 0.570306 |
| Thai MoPH | 0.91051 |
| World Health Organization | 0.577881 |
| national HIV response | 0.628506 |
| public health emergencies | 0.571133 |
| Thailand Behavioral Risk | 0.591374 |
| core capacity requirements | 0.539456 |
| maximal programmatic impact | 0.538878 |
| Thailand Ministry | 0.545538 |
| health care settings | 0.578696 |
|
| National Vaccination Program | 0.540169 |
| International Health Regulations | 0.5728 |
| Regional GDD Centers | 0.55006 |
| Current research activities | 0.553038 |
| HIV care quality | 0.630563 |
| mobile populations | 0.547444 |
| infectious disease threats. | 0.551167 |
| Global Health Security | 0.570964 |
| Epidemiology Training Program | 0.571359 |
| Asia Regional Office | 0.567973 |
| new diagnostic techniques | 0.540991 |
| Thailand’s response | 0.535216 |
| technical assistance | 0.545977 |
| Thai government partners | 0.574776 |
| surveillance | 0.574354 |
| seasonal influenza vaccine | 0.544823 |
| public health | 0.585263 |
| poor health care | 0.573727 |
| HIV incidence | 0.538495 |
| major health threats | 0.59991 |
| maximum health impact | 0.587833 |
| CDC Thailand | 0.667098 |
| drug resistance surveillance | 0.573406 |
| H1N1 influenza pandemic | 0.551405 |
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Centers for Disease Control and Prevention |
Html |
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Secondhand Smoke and Children - Health Communication |
Gateway to Health Communication and Social Marketing Practice - Secondhand Smoke and Children |
| Tobacco Smoke | 0.590892 |
| SIDS | 0.422448 |
| grandparents | 0.611448 |
| dad | 0.445031 |
| Health Consequences | 0.483491 |
| mom | 0.441979 |
| wheezing | 0.424464 |
| coffin nails | 0.496112 |
| Caitlin | 0.449095 |
| house | 0.418065 |
| Cigarette smokers | 0.499232 |
| times | 0.416481 |
| sudden infant death | 0.594083 |
| coats | 0.41709 |
| pneumonia | 0.422779 |
| cigar smoke | 0.616263 |
| children | 0.585974 |
| syndrome | 0.419544 |
| Surgeon General Excerpts | 0.555284 |
| trouble | 0.416788 |
| pipe | 0.418064 |
| Involuntary Exposure | 0.495509 |
| secondhand smoke | 0.956942 |
|
| chemicals | 0.419947 |
| Smoke-free homes | 0.50193 |
| health hazards | 0.491863 |
| lung diseases | 0.506427 |
| asthma attacks | 0.505644 |
| town | 0.417505 |
| bronchitis | 0.423339 |
| steps | 0.416431 |
| doctor | 0.449119 |
| health problems | 0.491159 |
| smoking cessation | 0.504016 |
| lung growth | 0.505161 |
| white sticks | 0.495103 |
| Pediatricians | 0.422034 |
| ages | 0.418852 |
| ear infections | 0.506271 |
| risk | 0.438154 |
| cancer | 0.419884 |
| cigarettes | 0.417696 |
| information | 0.416266 |
| visit Office | 0.487954 |
| time | 0.434382 |
| acute respiratory infections | 0.591834 |
|
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Centers for Disease Control and Prevention |
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Evaluation of Meningitis Surveillance Before Introduction ofSerogroup A Meningococcal Conjugate Vaccine - Burkina Faso andMali |
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. |
| Haemophilus influenzae type | 0.502007 |
| standardized surveillance database | 0.511766 |
| epidemic meningitis | 0.530792 |
| real-time PCR | 0.522483 |
| enhanced meningitis surveillance | 0.593801 |
| meningitis surveillance | 0.802864 |
| Mali | 0.597411 |
| causative pathogen confirmation | 0.49346 |
| national reference laboratory | 0.675487 |
| national surveillance office | 0.57276 |
| World Health Organization | 0.540729 |
| laboratory capacity | 0.509224 |
| Inter-Country Support Team | 0.500252 |
| high-quality surveillance data | 0.527202 |
| pneumoniae cause meningitis | 0.53147 |
| baseline surveillance evaluations | 0.505866 |
| field effectiveness trials | 0.495935 |
| CSF macroscopic examination | 0.511913 |
| CSF specimens | 0.529012 |
| laboratory confirmation | 0.565205 |
| African meningitis belt | 0.50695 |
| surveillance officers | 0.490616 |
| data management | 0.516331 |
| surveillance databases | 0.498686 |
| surveillance infrastructures | 0.504193 |
|
| meningitis epidemics | 0.503556 |
| data management tools | 0.49777 |
| meningitis disease | 0.492752 |
| case-based surveillance | 0.722886 |
| meningococcal conjugate vaccine | 0.632524 |
| line-listed cases | 0.545454 |
| bacterial meningitis mortality | 0.516908 |
| Strong meningitis surveillance | 0.607872 |
| bacterial meningitis | 0.655116 |
| Surveillance needs | 0.491077 |
| meningitis surveillance data | 0.634999 |
| preliminary surveillance data | 0.527189 |
| reference laboratories | 0.527266 |
| case-level data | 0.609743 |
| white blood cell | 0.499159 |
| Burkina Faso capital | 0.551053 |
| Strong case-based surveillance | 0.521557 |
| meningitis cases | 0.536545 |
| level surveillance epidemiologists | 0.513774 |
| conventional PCR | 0.500224 |
| Burkina Faso | 0.931922 |
| meningitis belt | 0.627632 |
| laboratory data | 0.503646 |
| Africa Inter-Country Support | 0.500458 |
|
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Paralytic Shellfish Poisoning — Southeast Alaska, May–June 2011 |
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. |
| shellfish consumption | 0.379356 |
| PSP cases | 0.681048 |
| Commercially harvested shellfish | 0.619224 |
| PSP toxin | 0.43576 |
| Public Health Center | 0.432041 |
| Health Center staff | 0.331157 |
| probable PSP cases | 0.616882 |
| public health recommendation | 0.349089 |
| SOE requests | 0.34969 |
| Annette Island Service | 0.429717 |
| Metlakatla | 0.494496 |
| noncommercially harvested shellfish | 0.865244 |
| active case finding | 0.553531 |
| Public health authorities | 0.340389 |
| Kimberly A. Porter | 0.394676 |
| Alaska Department | 0.383645 |
| intensive-care unit | 0.335616 |
| Metlakatla Dept | 0.334329 |
| PSP | 0.963226 |
| PSP develop | 0.427634 |
| Alaska Sea Grant | 0.342884 |
| additional case finding | 0.339447 |
| local health authorities | 0.330147 |
| PSP risks | 0.435155 |
|
| uneaten shellfish | 0.377762 |
| noncommercially harvested mussels | 0.447925 |
| community members | 0.332783 |
| important public health | 0.343624 |
| public health nurse | 0.361542 |
| paralytic shellfish poisoning | 0.568874 |
| affected area | 0.33142 |
| shellfish harvesting | 0.379401 |
| shellfish allergies | 0.392001 |
| Island Service Unit | 0.4298 |
| PSP saxitoxins | 0.468588 |
| Alaskan shellfish | 0.585518 |
| noncommercial shellfish | 0.381727 |
| untested Alaskan shellfish | 0.432713 |
| public health | 0.805298 |
| southeast Alaska | 0.523803 |
| Alaska Southeast | 0.347954 |
| community member | 0.329711 |
| Alaska Div | 0.349105 |
| additional probable cases | 0.377641 |
| PSP range | 0.468847 |
| Ketchikan Public Health | 0.471115 |
| public health responses | 0.340682 |
| PSP symptoms | 0.524229 |
|
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Centers for Disease Control and Prevention |
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Email Updates: December 30, 2013'Clinicians Outreach and Communication Activity (COCA) |
CDC Clinician Outreach and Communication Activity (COCA). Providing clinicians the most current and reliable information on emerging public health threats, such as pandemics, natural disasters, and bioterrorism. |
| FDA News Release | 0.704579 |
| CDC Health Alert | 0.876747 |
| CDC | 0.94921 |
| muscle growth product | 0.665823 |
| Health Professionals | 0.62753 |
| Public Health Matters | 0.738217 |
| Emergency Preparedness | 0.709351 |
| COCA Email Update | 0.742342 |
| FDA Safety Information | 0.723143 |
| preparedness planning | 0.669351 |
| public health community | 0.748666 |
| COCA Call/Webinar | 0.642394 |
| 2013-14 Influenza Season | 0.719768 |
| risk assessment tools | 0.7114 |
| – (CDC) | 0.772491 |
| new avian influenza | 0.736205 |
| CDC Science Clips | 0.88043 |
| Additional COCA Conference | 0.727368 |
| CDC Influenza Division | 0.883526 |
| new H7N9 virus | 0.707794 |
| important safety information | 0.682224 |
| Upper Midwest Preparedness | 0.734515 |
| health care providers | 0.80957 |
| Weekly Flu View | 0.691162 |
|
| Free CE credit/contact | 0.683984 |
| human medical products | 0.670567 |
| public health | 0.938801 |
| synthetic anabolic steroid | 0.665362 |
| community’s risk | 0.620454 |
| Specific Hazards preparedness | 0.736782 |
| Risk assessments | 0.613557 |
| Current Travel Warnings | 0.672761 |
| seasonal flu | 0.666951 |
| Community decisions | 0.614087 |
| in-person training centers | 0.683667 |
| FDA gateway | 0.628469 |
| key stakeholders | 0.60995 |
| baseline information | 0.620001 |
| FoodSafety.gov Reports FDA | 0.724837 |
| Event Reporting Program | 0.671456 |
| severe respiratory illness | 0.837906 |
| weekly influenza surveillance | 0.71106 |
| flu season | 0.611933 |
| public health agencies | 0.745055 |
| USDA Food Recalls | 0.674614 |
| Emergency Response Learning | 0.708027 |
| Response Training Resources | 0.697397 |
|
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Long-Haul Truck Drivers -Resources for Truck Drivers, Employers, and Educators - NIOSH WOrkplace Safety & Health Topics |
Division of Surveillance, Hazard Evaluations, and Field Studies |
| journal articles | 0.464926 |
| associations | 0.329624 |
| Fact sheet | 0.501463 |
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| perforated postcard paper | 0.674519 |
| searchable bibliographic database | 0.606455 |
| illnesses | 0.363681 |
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| Important | 0.373404 |
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| motor vehicle drivers | 0.648232 |
| Selective Literature Review | 0.632841 |
| safety effects | 0.509073 |
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| Plain Language | 0.489345 |
| NIOSH study | 0.504652 |
| grant reports | 0.458977 |
| Employers | 0.327592 |
| educational video | 0.464174 |
| truck drivers | 0.715022 |
|
| Quick Sleep Tips | 0.74892 |
| older drivers | 0.648605 |
| Wayne State University | 0.622368 |
| shiftwork | 0.400376 |
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| stress | 0.354094 |
| Recent Findings | 0.484203 |
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| card stock | 0.466134 |
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| Designing Safer Cabs | 0.640443 |
| Opportunities | 0.331958 |
| safety concerns | 0.525701 |
| truck cabs | 0.510601 |
| research reports | 0.485332 |
| Driver Occupational Safety | 0.679326 |
| Crash prevention factors | 0.661198 |
| work organization factors | 0.605426 |
| interventions | 0.329749 |
| performance | 0.329486 |
| Workers | 0.332408 |
| trucking industry | 0.464317 |
| special topics | 0.488564 |
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2009-10 Pregnant Women State Vaccination Report I |FluVaxView | Seasonal Influenza (Flu) | CDC |
FluVaxView 2009-10 Pregnant Women State Vaccination Report I - CDC |
| United States | 0.576578 |
| influenza vaccination coverage | 0.995096 |
| Click | 0.488433 |
| PRAMS states | 0.668439 |
| Coverage bar chart | 0.678047 |
| help | 0.42622 |
| Refer | 0.449689 |
| PRAMS state | 0.629793 |
| bar chart | 0.684267 |
|
| estimate | 0.450152 |
| report | 0.425953 |
| State Influenza Vaccination | 0.791096 |
| Map Selection button | 0.684099 |
| mouse pointer | 0.622255 |
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| small window | 0.573219 |
| time | 0.427244 |
|
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Coccidioidomycosis in a State Where It Is Not Known To BeEndemic - Missouri, 2004-2013 |
George Turabelidze, MD, PhD1; Ravi K. Aggu-Sher, MD1; Ehsan Jahanpour, MS1; C. Jon Hinkle1 (Author affiliations at end of text). |
| positive predictive value | 0.461735 |
| Ravi K. Aggu-Sher | 0.401357 |
| Poisson regression analysis | 0.387672 |
| Senior Services | 0.457142 |
| recent travel | 0.400727 |
| endemic area | 0.440758 |
| current diagnostic tests | 0.385862 |
| recent coccidioidomycosis | 0.536376 |
| positive coccidioidomycosis culture | 0.661896 |
| health care providers | 0.38336 |
| diagnostic tests | 0.487395 |
| coccidioidomycosis cases | 0.859562 |
| southwestern United States | 0.396762 |
| exact diagnostic tests | 0.381769 |
| commonly used drugs | 0.387992 |
| patients | 0.605819 |
| endemic disease | 0.58424 |
| Missouri Department | 0.402079 |
| health surveillance data | 0.382333 |
| enzyme immunoassay | 0.454382 |
| coccidioidomycosis diagnosis | 0.578407 |
| common diagnostic tests | 0.392759 |
| positive coccidioidomycosis cultures | 0.586058 |
| coccidioidomycosis | 0.978942 |
|
| truly endemic cases | 0.498407 |
| endemic areas | 0.460593 |
| Coccidioides spores | 0.395272 |
| George Turabelidze | 0.401788 |
| influenza-like illness | 0.403916 |
| used antifungal drug | 0.3931 |
| additional contributing factor | 0.380389 |
| Missouri | 0.424906 |
| serological tests | 0.4469 |
| acute coccidioidomycosis cases | 0.583013 |
| travel history | 0.476332 |
| polymerase chain reaction | 0.393047 |
| endemic coccidioidomycosis | 0.684724 |
| Notifiable Diseases Surveillance | 0.392818 |
| locally acquired cases | 0.394482 |
| coccidioidomycosis surveillance case | 0.573851 |
| positive culture | 0.391136 |
| coccidioidomycosis surveillance data | 0.714319 |
| complement fixation | 0.452023 |
| C. Jon Hinkle | 0.399968 |
| symptom onset date | 0.38781 |
| qualitative enzyme immunoassay | 0.386178 |
| travel | 0.542058 |
| incidence | 0.390399 |
|
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