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Centers for Disease Control and Prevention |
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Vaccine Acronyms and Abbreviations LP |
*Abbreviations used on U.S. immunization records. |
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| 986 |
Centers for Disease Control and Prevention |
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Measles Outbreak: Protect Your Child with MMR Vaccine | CDC Features |
Measles is a highly contagious disease. It can be serious for young children. Protect child by making sure he or she is up to date on vaccinations, including before traveling abroad. |
| red spots | 0.482578 |
| vaccinations | 0.439925 |
| runny nose | 0.488728 |
| Infants | 0.428411 |
| body | 0.416447 |
| 6-year-old children | 0.477755 |
| children | 0.592357 |
| young children | 0.564969 |
| measles quiz | 0.644573 |
| varicella vaccine | 0.527693 |
| vaccination record | 0.477528 |
| red eyes | 0.479627 |
| dose | 0.519842 |
| rubella vaccines | 0.501236 |
| mumps | 0.455954 |
| child | 0.591171 |
| Measles Vaccination | 0.645568 |
| doses | 0.462924 |
| death | 0.416319 |
| United States | 0.618912 |
| vaccines | 0.501916 |
| fever | 0.416472 |
| air | 0.415762 |
| head | 0.416466 |
| MMRV vaccine | 0.570805 |
|
| infected person coughs | 0.552859 |
| pneumonia | 0.417309 |
| measles vaccine | 0.78323 |
| combination vaccine | 0.525562 |
| eligible children | 0.471499 |
| mobile app | 0.478257 |
| health insurance plans | 0.52621 |
| unvaccinated people | 0.478932 |
| brain | 0.416326 |
| highly contagious disease | 0.566523 |
| people | 0.526008 |
| sneezes | 0.415746 |
| doctor | 0.484609 |
| rash | 0.418038 |
| health insurance provider | 0.522617 |
| healthcare provider | 0.473709 |
| chickenpox | 0.415948 |
| state VFC coordinator | 0.52577 |
| immunization scheduler | 0.474507 |
| Children Program | 0.469223 |
| Measles spreads | 0.670841 |
| measles | 0.97787 |
| MMR vaccine | 0.605942 |
| age | 0.519202 |
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| 7641 |
Centers for Disease Control and Prevention |
Html |
en |
Preventing Chronic Disease | State Quitlines and Cessation Patterns Among Adults With Selected Chronic Diseases in 15 States, 2005"2008 - CDC |
The death rate of people who have a chronic disease is lower among former smokers than current smokers. State tobacco cessation quitlines are available for free in every state. The objective of our study was to compare demographic characteristics, use of quitline services, and quit rates among a sample of quitline callers. |
| coronary artery disease | 0.585324 |
| state tobacco quitlines | 0.570166 |
| 7-month follow-up survey | 0.580801 |
| smoking-related chronic disease | 0.629073 |
| current tobacco user | 0.556474 |
| intent-to-treat quit rates | 0.554424 |
| NRT | 0.577918 |
| tobacco control programs | 0.581081 |
| Disease Control | 0.57695 |
| tobacco cessation quitlines | 0.600051 |
| lower quit rates | 0.577329 |
| tobacco users | 0.739006 |
| logistic regression | 0.56335 |
| State tobacco cessation | 0.582806 |
| American Quitline Consortium | 0.571197 |
| clinical practice guideline | 0.585511 |
| single disease groups | 0.5535 |
| asthma | 0.587648 |
| disease groups | 0.561788 |
| survey response rates | 0.55425 |
| smoking cessation | 0.55502 |
| chronic disease | 0.967905 |
| North American Quitline | 0.571595 |
| state tobacco quitline | 0.56661 |
| obstructive pulmonary disease | 0.58361 |
|
| chronic disease staff | 0.591651 |
| study | 0.587775 |
| chronic disease vs | 0.601303 |
| African American callers | 0.597712 |
| quitline callers | 0.646449 |
| multicall program | 0.604331 |
| cessation treatment | 0.554603 |
| quitline services | 0.594618 |
| uninsured callers | 0.589021 |
| heart disease | 0.558389 |
| chronic diseases | 0.786927 |
| chronic disease programs | 0.604295 |
| counseling calls | 0.559553 |
| following chronic diseases | 0.596069 |
| quit rates | 0.64381 |
| Chronic Disease Prevention | 0.59331 |
| 30-day quit rates | 0.598114 |
| 7-day quit rates | 0.556826 |
| chronic disease status | 0.652695 |
| Public Health Service | 0.582769 |
| higher quit rates | 0.554747 |
| callers | 0.791207 |
| randomly selected callers | 0.603405 |
| state quitlines | 0.66584 |
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| 10307 |
Centers for Disease Control and Prevention |
Html |
en |
HAN Archive - 00336 - Health Concerns about Misuse of Pesticides for Bed Bug Control |
Health Alert Network (HAN). Provided by the Centers for Disease Control and Prevention (CDC). |
| indoor pesticides | 0.308381 |
| recent pesticide treatment | 0.36373 |
| Animal Poison Control | 0.245665 |
| Disease Control | 0.262659 |
| pest control application | 0.332564 |
| muscle tremors | 0.240546 |
| Adult bed bugs | 0.34539 |
| pest control | 0.794698 |
| bed bugs | 0.901128 |
| family members | 0.247042 |
| IPM pest control | 0.313242 |
| pesticide control applicator | 0.385986 |
| state pesticide agency | 0.349082 |
| possible pesticide misuse | 0.331161 |
| multiple pesticides | 0.303699 |
| Pesticide Information Center | 0.600574 |
| pest management | 0.393868 |
| label directions | 0.241689 |
| product label | 0.31833 |
| pesticide exposure | 0.474816 |
| poison control center | 0.426666 |
| pesticide applicators | 0.330272 |
| experienced pest management | 0.292794 |
| bed bug-related inquiries | 0.286232 |
| health effects | 0.395186 |
|
| CDC Health Alert | 0.26507 |
| comprehensive pest control | 0.312612 |
| pest control applicator | 0.639012 |
| specific contact information | 0.243082 |
| right pest | 0.243545 |
| bed bug infestation | 0.283571 |
| National Pesticide Information | 0.601264 |
| pesticides indoors | 0.513184 |
| poultry bugs | 0.2468 |
| pesticides | 0.637505 |
| bed bug infestations | 0.259714 |
| pest control individual | 0.310449 |
| bed bug | 0.391602 |
| outdoor pesticides indoors | 0.508339 |
| pesticide residues | 0.303655 |
| pest control expert | 0.323831 |
| pesticide dusts | 0.306264 |
| pesticide poisoning | 0.370366 |
| local poison control | 0.251068 |
| pesticide regulatory agency | 0.334232 |
| home | 0.244548 |
| bed bug control | 0.309245 |
| bat bugs | 0.247288 |
| pest control applicators | 0.347717 |
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Centers for Disease Control and Prevention |
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NCIRD | DBD Bulletin Fall 2013 | ANISA Stats, Plikaytis Retires |
Division of Bacterial Diseases Bulletin Fall |
| Meningitis Vaccine Project | 0.783036 |
| neonatal survival | 0.752586 |
| community-acquired newborn infections | 0.794339 |
| public health interventions | 0.777411 |
| new statistical tools | 0.776497 |
| DBD scientist Stephanie | 0.779481 |
| standardized statistical tools | 0.775274 |
| future project design | 0.765435 |
| neonatal infection | 0.763952 |
| ANISA team | 0.786366 |
| ANISA Investigator Conference | 0.856001 |
| Melinda Gates Foundation | 0.768675 |
| individual pathogens | 0.710714 |
| South Asian countries | 0.791945 |
| Newborn deaths | 0.729329 |
| extensive lab efforts | 0.765675 |
| local health workers—seeing | 0.781577 |
| historical reasons | 0.697662 |
| pathogen pie | 0.699694 |
| fungal infectious diseases | 0.753139 |
| laboratory testing methods | 0.776992 |
| Neonatal Infections | 0.763637 |
| advanced statistical analyses | 0.768314 |
| analysis plan | 0.826505 |
| pathogen distribution | 0.700433 |
|
| key laboratory staff | 0.787593 |
| study facilities | 0.702258 |
| newborn babies | 0.696611 |
| Different statistical approaches | 0.773084 |
| public health impact. | 0.76477 |
| largest etiology studies | 0.769718 |
| statistician Nong Shang | 0.799506 |
| integrated statistical model | 0.773609 |
| basic prenatal care | 0.766844 |
| certain pathogens | 0.704182 |
| analysis finalization | 0.702626 |
| meningococcal conjugate vaccine | 0.763979 |
| neonatal deaths | 0.93653 |
| devastating meningitis epidemics | 0.768694 |
| public health | 0.832992 |
| laboratory techniques | 0.696957 |
| Brian Plikaytis | 0.70113 |
| statistical consultant | 0.698653 |
| public health importance | 0.763974 |
| bacterial pathogens | 0.721612 |
| potential challenges | 0.700539 |
| Stephanie Schrag | 0.772327 |
| neonatal sepsis | 0.769161 |
| methodological challenges | 0.696892 |
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Centers for Disease Control and Prevention |
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Knowledge and Attitudes Regarding Antibiotic Use Among AdultConsumers, Adult Hispanic Consumers, and Health Care Providers -United States, 2012-2013 |
Louise K. Francois Watkins, MD1,2; Guillermo V. Sanchez, MPH2; Alison P. |
| Antibiotics Work | 0.491434 |
| Guillermo V. Sanchez | 0.470324 |
| Estilos survey participants | 0.492019 |
| antibiotic prescription | 0.52828 |
| adult consumers | 0.567251 |
| health care provider | 0.540936 |
| family member | 0.471529 |
| potential participants | 0.474333 |
| Louise K. Francois | 0.527623 |
| Estilos survey questions | 0.478422 |
| national internet survey | 0.483268 |
| non-Hispanic consumers | 0.545549 |
| health care providers | 0.666114 |
| antibiotic self-administration | 0.504469 |
| response rate | 0.502844 |
| primary care physicians | 0.473082 |
| judicious antibiotic prescribing | 0.530062 |
| Community Survey data | 0.475484 |
| adverse drug events | 0.515289 |
| Hispanic communities | 0.495293 |
| patient expectations | 0.499002 |
| acculturation status | 0.471395 |
| K. Francois Watkins | 0.52857 |
| antibiotics | 0.618656 |
| Lauri A. Hicks | 0.470574 |
|
| antibiotic side effect | 0.51328 |
| Estilos survey | 0.497111 |
| United States | 0.631401 |
| HealthStyles survey participants | 0.493564 |
| low survey response | 0.468388 |
| neighborhood grocery store | 0.528046 |
| Hispanic consumers | 0.920102 |
| Hispanic respondents | 0.500117 |
| public health initiatives | 0.525645 |
| Alison P. Albert | 0.468085 |
| antibiotic resistance | 0.638327 |
| health care | 0.735457 |
| health care visit | 0.479052 |
| survey data | 0.498844 |
| U.S. consumers | 0.535915 |
| DocStyles survey participants | 0.486837 |
| over-the-counter antibiotic availability | 0.533916 |
| Hispanic subgroups | 0.492286 |
| Epocrates Allied Health | 0.479006 |
| Population Survey data | 0.473595 |
| national Hispanic population | 0.519231 |
| Hispanic consumer respondents | 0.529053 |
| leftover antibiotics | 0.497588 |
| adult Hispanic consumers | 0.648253 |
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Centers for Disease Control and Prevention |
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Calendar | Meaningful Use | CDC |
null |
| FACA Committees | 0.286153 |
| Collaboration Initiative Monthly | 0.362374 |
| CDC | 0.255742 |
| recommendations | 0.240765 |
| subcommittees | 0.246103 |
| –Electronic Health Records | 0.363851 |
| Joint Public Health | 0.359598 |
| Public Health Agencies | 0.358252 |
| potential barriers | 0.295058 |
| Disease Control | 0.438369 |
| Nationwide Monthly Webinar | 0.37524 |
| average attendance | 0.306486 |
| Federal Advisory Committee | 0.450941 |
| HIT Standards Committee | 0.350566 |
| Monthly Webinar Series | 0.587075 |
| Health Records | 0.375092 |
| Public Health Forum | 0.352737 |
| workgroups | 0.273973 |
| Vendors Collaboration Initiative | 0.541488 |
| public health objectives | 0.344974 |
| Reinvestment Act | 0.262571 |
| open forum | 0.293694 |
| Advisory Committee Act | 0.300364 |
| national coordinator | 0.529376 |
| Electronic Health Records | 0.35949 |
|
| Office | 0.260544 |
| Initiative Monthly Webinar | 0.368887 |
| health information infrastructure | 0.266319 |
| ONC | 0.270606 |
| Public Health associations | 0.358196 |
| meaningful use objectives | 0.297342 |
| Scheduled | 0.262504 |
| Prevention | 0.260504 |
| respective parent FACA | 0.358744 |
| HIT Policy Committee | 0.395116 |
| Health Information Exchanges | 0.363024 |
| parent FACA committee | 0.345058 |
| State Health Information | 0.363322 |
| public health | 0.916105 |
| ehr vendors | 0.478035 |
| initial focus | 0.300474 |
| implementation | 0.251797 |
| American Recovery | 0.265164 |
| Public Health Practitioners | 0.349741 |
| monthly webinars | 0.297355 |
| meeting schedule | 0.292257 |
| eligible healthcare professionals | 0.386192 |
| Regional Extension Centers | 0.376055 |
| PH | 0.377504 |
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Centers for Disease Control and Prevention |
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HAN Archive - 00387|Health Alert Network (HAN) |
Health Alert Network (HAN). Provided by the Centers for Disease Control and Prevention (CDC). |
| influenza | 0.908849 |
| influenza diagnostic test | 0.635436 |
| CDC Health Alert | 0.436624 |
| recent influenza season—the | 0.573045 |
| epidemiologic field studies | 0.389096 |
| United States | 0.396049 |
| false negative results | 0.398109 |
| symptom onset | 0.4233 |
| H1N1pdm09 virus infection | 0.407415 |
| 2015-2016 influenza vaccines | 0.576338 |
| empiric antiviral therapy | 0.483304 |
| sickle cell disease | 0.392866 |
| influenza vaccine formulation | 0.61257 |
| influenza antiviral medications | 0.687362 |
| influenza virus infection | 0.581869 |
| influenza B viruses | 0.578924 |
| Seasonal influenza | 0.531363 |
| middle-aged adults | 0.400965 |
| prompt antiviral treatment | 0.483448 |
| intensive care unit | 0.398314 |
| influenza-associated medical visits | 0.385099 |
| influenza vaccine options | 0.615573 |
| severe influenza illness | 0.667253 |
| spinal cord injury | 0.387264 |
|
| influenza morbidity | 0.572245 |
| antiviral treatment decisions | 0.484174 |
| influenza activity | 0.614566 |
| patients | 0.414371 |
| national surveillance systems | 0.388222 |
| antigen detection tests | 0.396443 |
| influenza vaccination | 0.552413 |
| 2015-2016 influenza season | 0.612394 |
| influenza complications | 0.555159 |
| influenza seasons | 0.57597 |
| vaccine effectiveness | 0.390186 |
| antiviral treatment | 0.848138 |
| influenza viruses | 0.608005 |
| negative RIDT results | 0.401459 |
| severe respiratory illness | 0.426899 |
| Early antiviral treatment | 0.566999 |
| high risk | 0.399973 |
| influenza virus | 0.58519 |
| long-term aspirin therapy | 0.388731 |
| clinical judgment | 0.386517 |
| illness onset | 0.456424 |
| RT-PCR testing results | 0.409681 |
| influenza diagnosis | 0.56594 |
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Centers for Disease Control and Prevention |
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Rural Adults' Perspectives on School Food in a North Carolina County |
Preventing Chronic Disease (PCD) is a peer-reviewed electronic journal established by the National Center for Chronic Disease Prevention and Health Promotion. PCD provides an open exchange of information and knowledge among researchers, practitioners, policy makers, and others who strive to improve the health of the public through chronic disease prevention. |
| North Carolina | 0.438276 |
| school meal guidelines | 0.214803 |
| key informant interviews | 0.397561 |
| portion sizes | 0.223961 |
| appealing school food | 0.228128 |
| fruit | 0.227906 |
| vegetable consumption | 0.800603 |
| school meals | 0.259499 |
| vegetables | 0.35564 |
| rural North Carolina | 0.227361 |
| school food | 0.99393 |
|
| Chapel Hill | 0.210691 |
| school cafeteria staff | 0.271144 |
| fruits | 0.366214 |
| children | 0.311953 |
| federal school meal | 0.216707 |
| elementary school food | 0.27315 |
| school lunch | 0.391972 |
| cafeteria staff member | 0.202028 |
| cafeteria staff | 0.61355 |
| current school food | 0.323594 |
| elementary school children | 0.229967 |
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Centers for Disease Control and Prevention |
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Differences in Food and Beverage Marketing Policies andPractices in US School Districts, by Demographic Characteristics ofSchool Districts, 2012 |
Preventing Chronic Disease (PCD) is a peer-reviewed electronic journal established by the National Center for Chronic Disease Prevention and Health Promotion. PCD provides an open exchange of information and knowledge among researchers, practitioners, policy makers, and others who strive to improve the health of the public through chronic disease prevention. |
| district size | 0.462571 |
| school wellness policies | 0.487794 |
| beverage marketing | 0.705757 |
| Practices Study | 0.314804 |
| large school districts | 0.545695 |
| school buildings | 0.459304 |
| Disease Control | 0.396396 |
| school | 0.976223 |
| healthful options | 0.465568 |
| school districts | 0.769576 |
| higher percentage | 0.628372 |
| marketing practices | 0.338743 |
| school nutrition environment | 0.328147 |
| metropolitan status | 0.489085 |
| rural districts | 0.440471 |
| school health policies | 0.557394 |
| school nutrition services | 0.507526 |
| urban districts | 0.440206 |
| schools | 0.535914 |
| nutrition services staff | 0.335568 |
| non-Hispanic white students | 0.480155 |
| fast food restaurants | 0.396711 |
| large districts | 0.528018 |
| school health council | 0.457878 |
| promotion policies | 0.351173 |
|
| public school districts | 0.42124 |
| General School Environment | 0.314448 |
| larger school districts | 0.392887 |
| districts | 0.915401 |
| school nutrition | 0.635879 |
| students | 0.566388 |
| total annual expenditures | 0.49172 |
| soft drinks | 0.504888 |
| healthful school nutrition | 0.370495 |
| technical assistance | 0.334291 |
| schools districts | 0.310675 |
| school grounds | 0.455842 |
| soft drink companies | 0.532946 |
| unhealthful foods | 0.744102 |
| small districts | 0.355251 |
| food marketing policies | 0.351428 |
| local school wellness | 0.58798 |
| district characteristics | 0.475325 |
| school health coordinator | 0.374676 |
| non-Hispanic white student | 0.454201 |
| practices | 0.640484 |
| school wellness policy | 0.3123 |
| medium-sized districts | 0.393185 |
| healthful foods | 0.320566 |
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