| 579 |
Centers for Disease Control and Prevention |
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National Latino AIDS Awareness Day | CDC Features |
October 15 is National Latino AIDS Awareness Day, a day to raise awareness about HIV and AIDS prevention among Hispanics/Latinos living in the United States and its territories. |
| prevention options | 0.396544 |
| pre-exposure prophylaxis | 0.389864 |
| male condom | 0.387689 |
| health care provider | 0.445465 |
| lifesaving information | 0.385536 |
| right way | 0.521984 |
| HIV prevention | 0.616634 |
| gender-neutral alternative | 0.382286 |
| viral load | 0.374041 |
| undetectable levels | 0.376593 |
| post-exposure prophylaxis | 0.394999 |
| sexual assault | 0.379383 |
| effective prevention | 0.389011 |
| community-based organizations | 0.378512 |
| HIV Risk Reduction | 0.71297 |
| Latinx AIDS Awareness | 0.618245 |
| National Latinx AIDS | 0.618294 |
| Additional resources | 0.378556 |
| Defeat HIV | 0.688368 |
| term Latinx | 0.377521 |
| Health departments | 0.376513 |
| treatment strategies | 0.388969 |
| best ways | 0.375509 |
| Latino Commission | 0.395839 |
| Hispanic/Latino communities | 0.510641 |
|
| United States | 0.390078 |
| HIV Treatment Works | 0.684128 |
| prevention campaign | 0.386731 |
| sexual behaviors | 0.3868 |
| good news | 0.395595 |
| powerful treatment | 0.393013 |
| HIV diagnoses | 0.822308 |
| Hispanic women/Latinas | 0.39407 |
| CDC Act | 0.388873 |
| higher risk | 0.385027 |
| total population | 0.3865 |
| HIV-negative sexual partners | 0.446268 |
| sexual transmission | 0.375552 |
| testing site | 0.388406 |
| ZIP code | 0.381267 |
| sexual partners | 0.447247 |
| bisexual men | 0.392607 |
| female condom | 0.387631 |
| HIV | 0.964073 |
| AIDS Campaign | 0.382515 |
| testing services | 0.382797 |
| HIV infection | 0.618489 |
| HIV medication | 0.608629 |
| national HIV testing | 0.72587 |
|
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| 6222 |
Centers for Disease Control and Prevention |
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en |
National survey shows HPV vaccine rates trail other teen vaccines - Press Release: August 25, 2011 |
Latest State Data Show Rates of Obesity Remain High |
| vaccines —Tdap | 0.357095 |
| Mortality Weekly Report | 0.314699 |
| annual health checkup | 0.285964 |
| routine teen vaccines | 0.437375 |
| Tdap vaccine | 0.338276 |
| CDC’s National | 0.211813 |
| health care provider | 0.464367 |
| random telephone survey | 0.273223 |
| CDC NIS-Teen survey | 0.335515 |
| teens | 0.250914 |
| girls | 0.207539 |
| HPV vaccine | 0.99415 |
| adolescent vaccines | 0.291447 |
| HPV results | 0.432649 |
|
| U.S. teens | 0.201688 |
| vaccination rates | 0.329063 |
| health care providers | 0.277806 |
| National Immunization Survey-Teen | 0.586495 |
| preteens | 0.205206 |
| childhood vaccines | 0.288105 |
| cervical cancers | 0.20855 |
| cervical cancer | 0.692227 |
| HPV infection | 0.464009 |
| HPV series | 0.399408 |
| HPV vaccines | 0.573777 |
| local health care | 0.269539 |
| CDC’s Morbidity | 0.221072 |
|
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| 7259 |
Centers for Disease Control and Prevention |
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The Role of Public Health Informatics in Enhancing PublicHealth Surveillance |
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. |
| data | 0.532097 |
| public health interventions | 0.484025 |
| syndromic surveillance systems | 0.460832 |
| Public Health Data | 0.493869 |
| public health problems | 0.494821 |
| Joint Public Health | 0.474809 |
| public health surveillance | 0.780127 |
| public health systems | 0.504043 |
| public health decisions | 0.490826 |
| century public health | 0.502579 |
| health surveillance challenges | 0.48216 |
| health information exchange | 0.472176 |
| public health practice | 0.493033 |
| Health Informatics Institute | 0.468491 |
| health surveillance systems | 0.518439 |
| Public Health Information | 0.490679 |
| clinical information systems | 0.457996 |
| public health agencies | 0.567735 |
| health informatics expertise. | 0.473053 |
| electronic health record | 0.490548 |
| public health surveillance. | 0.498203 |
| health surveillance information | 0.498031 |
| health surveillance tools | 0.484178 |
| health information technology | 0.529241 |
| public health life | 0.475 |
|
| health informatics designs | 0.476839 |
| public health community | 0.532593 |
| public health informatics | 0.702993 |
| public health associations | 0.475062 |
| 21st century | 0.455688 |
| health record technology | 0.461788 |
| public health outcomes | 0.475307 |
| syndromic surveillance data | 0.485642 |
| public health professionals | 0.475259 |
| information systems | 0.502067 |
| different information systems | 0.457372 |
| surveillance informatics | 0.457636 |
| public health | 0.937449 |
| health care | 0.460852 |
| public health perspective | 0.476308 |
| public health goal | 0.492452 |
| Public health leaders | 0.480753 |
| public health nursing | 0.486526 |
| public health programs | 0.485098 |
| public health workers | 0.478024 |
| term health information | 0.48387 |
| data collection | 0.477456 |
| informatics-augmented public health | 0.479703 |
| public health requirements | 0.479867 |
|
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| 8612 |
Centers for Disease Control and Prevention |
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PanFlu Storybook - In Memorial, Marcella Bobzien |
In Memorial, To date, October 1918 remains the deadliest month in U.S. history when approximately 200,000 Americans died of the flu. Healthy, young adults (average age 35 years) began coughing in the morning and were dead by the evening. The family stories described in this section define true courage amid unbearable loss. |
| 1918 flu pandemic | 0.831942 |
| urban America | 0.420165 |
| brothers | 0.271262 |
| arrangement | 0.238189 |
| Carmen Garske Bobzien | 0.696732 |
| toddler | 0.244613 |
| community′s capacity | 0.403409 |
| Robert | 0.312156 |
| rural North Dakota | 0.960055 |
| sister′s children | 0.402576 |
| young children | 0.406766 |
| Leon | 0.238229 |
| Marilynn Sutherland | 0.479123 |
| saddened listening | 0.451394 |
| grandmother Carmen | 0.502497 |
| siblings Millie | 0.449186 |
| outskirts | 0.239438 |
| Marcella Bobzien | 0.512074 |
| adult | 0.236965 |
| Bismarck | 0.239291 |
| second-hand knowledge | 0.409664 |
| pandemic flu | 0.840436 |
| Stella Garske Bobzien | 0.604021 |
| Dolores | 0.248085 |
| close–knit farming community | 0.582038 |
|
| epidemic′s dependent survivors | 0.576819 |
| duration | 0.239408 |
| mother′s stories | 0.423821 |
| Storyteller | 0.244065 |
| orphanage | 0.23989 |
| Otto′s diary | 0.407305 |
| Jack | 0.237371 |
| Otto John Bobzien | 0.634523 |
| public health | 0.402595 |
| Bea | 0.247028 |
| sod farmhouse | 0.416584 |
| flu deaths | 0.542349 |
| maternal grandparents | 0.445172 |
| Carmen′s younger sister | 0.584438 |
| recollections | 0.243008 |
| Dick | 0.236716 |
| inevitable next flu | 0.545216 |
| Vernon | 0.34896 |
| Jim | 0.237393 |
| Ferd | 0.335858 |
| time | 0.237618 |
| family | 0.339136 |
| pandemics | 0.252807 |
| isolated farming families | 0.61478 |
|
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| 9164 |
Centers for Disease Control and Prevention |
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Firearm Homicides and Suicides in Major Metropolitan Areas -United States, 2006-2007 and 2009-2010 |
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. |
| firearm suicide rates | 0.783148 |
| firearm-related violence | 0.319526 |
| metropolitan statistical areas | 0.305441 |
| national unemployment rates | 0.27274 |
| national trend | 0.262976 |
| all-ages rate | 0.290118 |
| firearm homicide statistics | 0.403318 |
| firearm homicide | 0.914536 |
| NVSS mortality data | 0.25959 |
| National Center | 0.258062 |
| firearm injury | 0.340963 |
| major metropolitan areas | 0.26455 |
| mortality data | 0.261219 |
| firearm suicide rate | 0.425339 |
| reporting periods | 0.270467 |
| National Vital Statistics | 0.268818 |
| large MSAs | 0.422091 |
| persons | 0.368971 |
| firearm homicide rate | 0.602707 |
| large metropolitan areas | 0.334911 |
| firearm suicides | 0.513516 |
| national rate | 0.38209 |
| United States | 0.377628 |
| Scott R. Kegler | 0.310643 |
| age group | 0.327346 |
|
| firearm homicide rates | 0.668309 |
| MSA rate | 0.34107 |
| firearm homicide victims | 0.446547 |
| largest MSAs | 0.337791 |
| U.S. Census Bureau | 0.312724 |
| all-ages rates | 0.323892 |
| early prevention efforts | 0.257369 |
| public health concern | 0.261 |
| MSAs | 0.497823 |
| national firearm homicide | 0.400667 |
| U.S. residents | 0.260707 |
| firearm homicides | 0.401834 |
| national decrease | 0.264345 |
| population estimates | 0.256821 |
| firearm fatality statistics | 0.348747 |
| cause codes | 0.255687 |
| Practice Integration | 0.257775 |
| All-ages firearm suicide | 0.38803 |
| higher firearm homicide | 0.388813 |
| higher firearm suicide | 0.366639 |
| firearm assault | 0.324733 |
| suicide counts | 0.26841 |
| annual firearm homicide | 0.406448 |
| earlier reporting period | 0.260038 |
|
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| 10602 |
Centers for Disease Control and Prevention |
Html |
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Preventing Chronic Disease | Using a Health Informatics System to Assess Effect of a Federal Cigarette Tax Increase on Readiness to Quit Among Low-Income Smokers, Louisiana, 2009 - CDC |
Health informatics systems are a proven tool for tobacco control interventions. To address the needs of low-income groups, the Tobacco Control Initiative was established in partnership with the Louisiana State University Health Care Services Division to provide cost-effective tobacco use cessation services through the health informatics system in the state public hospital system. |
| tobacco use cessation | 0.50604 |
| substantial tax increase | 0.48257 |
| cigarette tax price | 0.492422 |
| tobacco tax increase | 0.55834 |
| State University Health | 0.53218 |
| tax increases | 0.491876 |
| public hospital | 0.55096 |
| Tobacco control state | 0.49181 |
| control policy change | 0.480489 |
| health care delivery | 0.486003 |
| federal tobacco control | 0.528044 |
| state public hospital | 0.492302 |
| tobacco excise tax | 0.498137 |
| tobacco | 0.678963 |
| health informatics | 0.543419 |
| tax affects smokers | 0.512318 |
| African American smokers | 0.516499 |
| clinical practice guideline | 0.507146 |
| University Health Care | 0.501708 |
| cessation services | 0.555309 |
| tobacco products | 0.504795 |
| cigarette tax increase | 0.751199 |
| federal tax increase | 0.553007 |
| low-income tobacco users | 0.533959 |
| smoking cessation | 0.503913 |
|
| effect | 0.496242 |
| tobacco products rises | 0.490774 |
| statewide tobacco control | 0.489325 |
| Health Care Services | 0.505239 |
| readiness | 0.641074 |
| tax increase | 0.91033 |
| smokers | 0.60046 |
| LSU HCSD | 0.493493 |
| Louisiana State University | 0.525248 |
| tobacco control policy | 0.525288 |
| Care Services Division | 0.490349 |
| Louisiana smokers | 0.49512 |
| health care | 0.595402 |
| public health | 0.487152 |
| Health informatics systems | 0.496572 |
| adult smokers | 0.483164 |
| federal cigarette tax | 0.564771 |
| tobacco control program | 0.506577 |
| tobacco control policies | 0.485025 |
| increased tobacco taxes | 0.480634 |
| tobacco control interventions | 0.539792 |
| clinic visit | 0.480288 |
| commercial insurance | 0.505291 |
| Tobacco Control Initiative | 0.537147 |
|
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| 10937 |
Centers for Disease Control and Prevention |
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en |
Increased Risk of Rare Cancer as DES Daughters Age |
This study compared the risk of getting clear cell adenocarcinoma of the cervix and vagina between women who were born between 1947 and 1971 to women who were born before 1947 or after 1971. |
| young women | 0.653543 |
| White MC | 0.639551 |
| Higher incidence | 0.644296 |
| rare cancer | 0.639231 |
| data | 0.551319 |
| United States | 0.785604 |
| premature births | 0.68236 |
| link | 0.526746 |
| Drug Administration | 0.662171 |
| babies | 0.528005 |
| entire country | 0.643489 |
| Epidemiology | 0.527237 |
| Thompson TD | 0.643191 |
| Control | 0.524528 |
| pregnant women | 0.675285 |
| miscarriages | 0.548265 |
| clear cell adenocarcinoma | 0.980628 |
| mothers | 0.529012 |
| NPCR | 0.524903 |
| Pap tests | 0.647255 |
|
| rare type | 0.661337 |
| DES Daughters. | 0.750064 |
| cell samples | 0.633866 |
| Food | 0.529326 |
| CCA | 0.689935 |
| cervix | 0.592456 |
| EK | 0.534673 |
| patterns | 0.525379 |
| National Program | 0.638193 |
| cervical cancer | 0.643666 |
| upper vagina | 0.68367 |
| DES | 0.865499 |
| Cancer Registries | 0.64809 |
| doctors | 0.527552 |
| Diethylstibestrol | 0.529877 |
| risk | 0.526028 |
| programs | 0.525001 |
| federal cancer registry | 0.760706 |
| women | 0.69539 |
| Weir HK | 0.646738 |
|
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| 12248 |
Centers for Disease Control and Prevention |
Video |
en |
Public Health Grand Rounds on Excessive Alcohol Use |
Excessive alcohol use, including underage drinking and binge drinking (drinking 5 or more drinks during a single occasion for men or 4 or more drinks during a single occasion for women), is responsible for 80,000 deaths and 2.3 million years of potential life lost in the U.S. each year, and cost the United States $223.5 billion in 2006 or about $1.90 per drink.
This powerful session of Public Health Grand Rounds explored the public health impact of excessive alcohol use and evidence-based strategies to prevent it, with specific attention to the role that state and local public health agencies play in addressing this important public health problem.
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://www.cdc.gov/about/grand-rounds/archives/2012/March2012.htm |
| Excessive Alcohol | 0.989005 |
|
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CLICK HERE |
| 14490 |
Centers for Disease Control and Prevention |
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Who Would Pay for State Alcohol Tax Increases in the UnitedStates? |
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. |
| capita alcohol consumption | 0.30075 |
| alcohol tax increase | 0.296011 |
| binge drinkers | 0.229577 |
| net cost | 0.29351 |
| binge drinking | 0.365435 |
| hypothetical tax increases | 0.333861 |
| tax increases | 0.788391 |
| alcohol prices | 0.237541 |
| hypothetical tax increase | 0.31302 |
| Alcohol Abuse | 0.225825 |
| higher alcohol taxes | 0.283553 |
| alcohol taxes | 0.45171 |
| alcohol | 0.791816 |
| aggregate costs | 0.290183 |
| adult excessive drinkers | 0.290387 |
| state alcohol tax | 0.464782 |
| BRFSS core alcohol | 0.230523 |
| heavy drinker | 0.254124 |
| daily average | 0.255015 |
| alcohol tax increases | 0.746898 |
| state alcohol taxes | 0.34449 |
| sociodemographic characteristics | 0.234235 |
| alcohol policy interventions | 0.233863 |
| capita costs | 0.345711 |
|
| State-specific tax increases | 0.249169 |
| United States | 0.387976 |
| drinks | 0.467223 |
| current alcohol taxes | 0.253209 |
| average annual increase | 0.230942 |
| non-Hispanic white drinkers | 0.274355 |
| alcohol consumption | 0.607549 |
| Average daily alcohol | 0.264005 |
| Alcohol Epidemiologic Data | 0.232708 |
| excessive drinkers | 0.841684 |
| Excessive alcohol consumption | 0.347454 |
| excessive drinking | 0.243269 |
| hypothetical state alcohol | 0.373777 |
| non-Hispanic whites | 0.284088 |
| public health | 0.250963 |
| nonexcessive drinkers | 0.909314 |
| costs | 0.35543 |
| Alcohol Policy Information | 0.282279 |
| value-based alcohol taxes | 0.253549 |
| annual alcohol consumption | 0.244944 |
| hypothetical alcohol tax | 0.299364 |
| evidence-based public health | 0.239268 |
| alcohol spectrum disorders | 0.239775 |
| current drinkers | 0.239986 |
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| 14593 |
Centers for Disease Control and Prevention |
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Fentanyl Overdose Data |
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| synthetic opioid overdose | 0.647614 |
| regions | 0.2297 |
| United States | 0.346501 |
| illicitly-manufactured fentanyl.2,3 | 0.36102 |
| cause-of-death codes | 0.347373 |
| increases | 0.324685 |
| direct method | 0.348494 |
| number | 0.229663 |
| total | 0.227028 |
| synthetic opioids | 0.806785 |
| Drug overdose deaths | 0.785786 |
| law enforcement | 0.365654 |
| methadone | 0.309075 |
| numerous states | 0.371619 |
| drugs | 0.230806 |
| tramadol | 0.31933 |
|
| South | 0.227433 |
| West.1 | 0.227347 |
| census region | 0.359103 |
| Diseases | 0.226857 |
| Synthetic opioid death | 0.642758 |
| drug products | 0.358438 |
| International Classification | 0.350574 |
| Midwest | 0.227507 |
| standard population | 0.346296 |
| Revision | 0.229431 |
| synthetic opioid-involved deaths | 0.930231 |
| Recent state reports | 0.498151 |
| fentanyl-involved overdose deaths | 0.67769 |
| fentanyl prescribing rates | 0.586152 |
| Age-adjusted death rates | 0.693768 |
| demographics | 0.236378 |
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