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Prevalence and Indicators of Viral Suppression Among Personswith Diagnosed HIV Infection Retained in Care - Georgia,2010 |
Laura Edison, DVM1,2, Denise Hughes2, Cherie Drenzek, DVM2, Jane Kelly, MD2,3 (Author affiliations at end of text). |
| viral loads | 0.460896 |
| new guidelines | 0.447237 |
| lower viral suppression | 0.500323 |
| ART | 0.450313 |
| new HIV infections | 0.447789 |
| injection drug | 0.448166 |
| prevalence ratio | 0.44632 |
| male-to-male sexual contact | 0.493345 |
| HIV patients | 0.449663 |
| health-care providers | 0.449207 |
| CD4+ percentage | 0.46394 |
| new treatment guidelines | 0.450191 |
| transmission category | 0.474358 |
| prevalence | 0.450315 |
| HIV infections | 0.451192 |
| viral load | 0.539366 |
| cells/ ТЕL | 0.471366 |
| CD4+ count | 0.458066 |
| HIV disease | 0.447434 |
| viral suppression | 0.928945 |
| HIV care continuum | 0.450729 |
| HIV diagnosis | 0.441387 |
| newly diagnosed HIV | 0.47242 |
| HIV transmission | 0.462975 |
|
| public health | 0.446683 |
| poor suppression | 0.461238 |
| unknown disease stage | 0.450668 |
| total lymphocytes | 0.496277 |
| patients | 0.495475 |
| diagnosis | 0.568708 |
| laboratory tests | 0.456228 |
| Viral Hepatitis | 0.453605 |
| HIV treatment centers | 0.450293 |
| CD4+ cell count | 0.450815 |
| persons | 0.589853 |
| national HIV treatment | 0.478823 |
| new HIV treatment | 0.446912 |
| HIV | 0.570128 |
| HIV treatment guidelines | 0.502345 |
| earlier disease stage | 0.496376 |
| viral nucleotide sequence | 0.475072 |
| human immunodeficiency virus | 0.462167 |
| heterosexual contact | 0.452176 |
| Georgia | 0.457948 |
| disease stages | 0.524289 |
| Program Core HIV | 0.444556 |
| HIV infection | 0.503573 |
|
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Progress Along the Continuum of HIV Care Among Blacks withDiagnosed HIV- United States, 2010 |
Y. Omar Whiteside, PhD1, Stacy M. Cohen, MPH1, Heather Bradley, PhD1, Jacek Skarbinski, MD1, H. |
| National HIV/AIDS Strategy | 0.326556 |
| data | 0.293479 |
| Los Angeles County | 0.27161 |
| HIV programs | 0.226883 |
| Human Services | 0.21878 |
| particularly black males | 0.232224 |
| diagnosed HIV infection | 0.322839 |
| blacks | 0.487369 |
| U.S. Department | 0.219325 |
| current HIV prevention | 0.250321 |
| transmission category | 0.209874 |
| health outcomes | 0.28716 |
| new HIV | 0.244844 |
| viral suppression | 0.983258 |
| Clin Infect Dis | 0.213166 |
| viral suppression §§ | 0.216822 |
| VL test results | 0.282998 |
| black males | 0.267255 |
| HIV medical care | 0.316177 |
| lowest percentage | 0.217935 |
| ART prescription | 0.42535 |
| persons | 0.329054 |
| HIV transmission categories | 0.25957 |
| human immunodeficiency virus | 0.281151 |
|
| heterosexual contact | 0.342145 |
| recent HIV VL | 0.253704 |
| viral load test | 0.222566 |
| Medical Monitoring Project | 0.316471 |
| Puerto Rico | 0.362295 |
| United States | 0.878246 |
| age group | 0.25359 |
| linkage | 0.214652 |
| hiv care continuum | 0.473393 |
| National HIV Surveillance | 0.457373 |
| Care Continuum Initiative | 0.248619 |
| HIV continuum | 0.233309 |
| HIV diagnoses | 0.226899 |
| HIV disease | 0.223641 |
| HIV diagnosis | 0.332915 |
| HIV testing projects | 0.249915 |
| HIV incidence | 0.223071 |
| risk factor | 0.214816 |
| HIV | 0.826007 |
| standard HIV core | 0.248977 |
| HIV viral load | 0.258922 |
| HIV testing | 0.266158 |
| data collection cycle | 0.203491 |
| HIV infection | 0.672107 |
|
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Q&A about CDC's Guidance for Emergency Shelters during the 2009-2010 Flu Season |
null |
| H1N1 flu vaccine | 0.572832 |
| current flu conditions | 0.654054 |
| sick household members | 0.493667 |
| shelter managers | 0.490563 |
| emergency warning signs | 0.528962 |
| Routine cleaning | 0.505344 |
| alcohol-based hand rubs | 0.548585 |
| pregnant women | 0.571377 |
| separate areas | 0.474969 |
| fever-reducing medicines | 0.553512 |
| degrees Fahrenheit | 0.548264 |
| individual rooms | 0.481984 |
| Flu viruses | 0.545005 |
| close quarters | 0.478869 |
| personal protective equipment | 0.475591 |
| sick people | 0.541136 |
| health care provider | 0.58693 |
| additional healthcare workers | 0.47818 |
| high risk | 0.481193 |
| respiratory etiquette | 0.477148 |
| seasonal flu | 0.69983 |
| urgent medical attention | 0.53015 |
| high-risk health conditions | 0.481741 |
| Flexible leave policies | 0.528266 |
| degrees Celsius | 0.553466 |
|
| antiviral flu medicines | 0.578119 |
| flu-like illness. Assign | 0.521612 |
| flu screening | 0.555659 |
| mental health personnel | 0.481079 |
| flu virus | 0.578803 |
| flu plan | 0.561577 |
| medical care provider | 0.476025 |
| Review sick-leave policies | 0.476574 |
| flu moves | 0.570706 |
| H1N1 flu | 0.727138 |
| higher risk | 0.528887 |
| child care programs | 0.480382 |
| flu-like symptoms | 0.851466 |
| flushed appearance | 0.557945 |
| emergency shelters | 0.647267 |
| H1N1 flu virus | 0.577075 |
| staff | 0.482273 |
| people | 0.641336 |
| flu | 0.941631 |
| local health department | 0.481164 |
| hand hygiene | 0.477668 |
| Seasonal flu vaccine | 0.569291 |
| group sick clients | 0.497579 |
| flu season | 0.679955 |
|
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CDC Meets With 23 African Countries to Discuss Influenza Surveillance |
CDC Meets With African Countries to Discuss Influenza Surveillance |
| influenza reporting routine | 0.464903 |
| influenza activities | 0.398079 |
| Global Disease Detection | 0.222281 |
| influenza laboratory methods | 0.416488 |
| African influenza surveillance | 0.501245 |
| Ghana Health Services | 0.23904 |
| CDC’s Influenza | 0.516793 |
| African countries | 0.444854 |
| influenza surveillance sites | 0.556136 |
| influenza training | 0.358674 |
| technical assistance | 0.243787 |
| CDC Influenza Division | 0.480356 |
| Research Unit No. | 0.243031 |
| influenza surveillance activities | 0.466124 |
| ANISE listserv | 0.254725 |
|
| Noguchi Memorial Institute | 0.242307 |
| World Health Organization | 0.236578 |
| field staff offer | 0.241245 |
| influenza sentinel site | 0.415 |
| ANISE group | 0.264843 |
| Medical Research | 0.226717 |
| cooperative agreements | 0.312061 |
| pandemic rapid response | 0.224087 |
| Influenza Division | 0.563155 |
| influenza surveillance | 0.91963 |
| influenza research studies | 0.4488 |
| outbreak response capabilities | 0.242191 |
| influenza surveillance methods | 0.487478 |
| annual ANISE meeting | 0.31735 |
| laboratory diagnostic capacity | 0.242444 |
|
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Survival Down Syndrome - NCBDDD |
null |
| baby’s body | 0.377068 |
| United States. | 0.386123 |
| regional resources | 0.368759 |
| Non-Hispanic black children | 0.440376 |
| largest population-based study | 0.437637 |
| Anomaly Multistate Prevalence | 0.42694 |
| greatest improvement | 0.376314 |
| visit https://www.cdc.gov/ncbddd/birthdefects/DownSyndrome.html | 0.366884 |
| Kucik JE | 0.369628 |
| major heart defect | 0.913706 |
| survival exist | 0.429614 |
| health care providers | 0.422473 |
| United States1 | 0.377451 |
| journal Pediatrics | 0.382534 |
| National Center | 0.367615 |
| racial/ethnic groups | 0.372784 |
| new study | 0.38797 |
| death changes | 0.370173 |
| survival | 0.62537 |
| syndrome growth charts | 0.450948 |
| racial/ethnic disparities | 0.366415 |
| brain’s development | 0.376465 |
| Overall survival | 0.426754 |
| disease tracking | 0.36655 |
| United States | 0.605993 |
|
| extra copy changes | 0.430959 |
| study area | 0.373035 |
| physical problems | 0.374474 |
| babies | 0.418224 |
| body forms | 0.376712 |
| extra chromosome | 0.375755 |
| general population | 0.370828 |
| Survival Collaborative | 0.419337 |
| small racial/ethnic differences | 0.447826 |
| syndrome impacts | 0.396794 |
| survival persist | 0.44857 |
| syndrome | 0.885779 |
| medical needs | 0.366184 |
| complete picture | 0.369772 |
| Population-based means | 0.373387 |
| people | 0.458335 |
| birth defects | 0.43347 |
| U.S. population | 0.365726 |
| younger age | 0.442213 |
| common chromosomal condition | 0.435953 |
| normal birth weight | 0.430956 |
| lower survival | 0.424149 |
| Non-Hispanic white children | 0.440078 |
| low birth weight | 0.693745 |
|
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PanFlu Storybook - An Immigrant's Tale, Antonio Grillo |
An Immigrant’s Tale, Many people fled war-ravaged Europe during WWI and several came to America. In addition to adjusting to a new culture and learning a new language, recent immigrants also had to cope with a deadly flu pandemic. Even for those who had settled in the United States before the Great War, the flu pandemic made a difficult existence almost unbearable. |
| guns | 0.244132 |
| pile | 0.24415 |
| bombs | 0.251108 |
| American man | 0.431871 |
| family farm | 0.45695 |
| Palermo | 0.257277 |
| thanks | 0.24889 |
| Grillo Family | 0.503566 |
| children | 0.29363 |
| neighbors | 0.323192 |
| intersection | 0.249248 |
| spoon | 0.248046 |
| grandfather | 0.333319 |
| Joseph M. Chiofolo | 0.714019 |
| kindness | 0.305298 |
| Mays Landing Highway | 0.677292 |
| vomiting | 0.252015 |
| family′s farm | 0.452882 |
| entire family | 0.655817 |
| Europe | 0.247249 |
| outhouse | 0.261899 |
| water | 0.438118 |
| diarrhea | 0.251433 |
| man′s house | 0.422703 |
|
| chickens | 0.246487 |
| flu pandemic | 0.468994 |
| younger brothers | 0.455749 |
| grandparents | 0.411095 |
| dirty sheets | 0.429095 |
| soldiers | 0.443083 |
| boy | 0.248571 |
| parents′ bed | 0.437367 |
| chicken soup | 0.636965 |
| hand pump | 0.454989 |
| Storyteller | 0.253472 |
| chicken coup | 0.463463 |
| World War | 0.453692 |
| stories | 0.252037 |
| East Vineland | 0.477239 |
| Antonio Grillo | 0.555897 |
| New Jersey | 0.924449 |
| English | 0.296555 |
| Sicily | 0.252005 |
| bed sheets | 0.420051 |
| high fever | 0.44731 |
| mother Frances M. | 0.776799 |
| time | 0.247778 |
| American couple | 0.430865 |
|
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Healthy Brain Initiative Logic Model |
null |
| outputs | 0.262449 |
| easily referenced tool | 0.625442 |
| Centers | 0.257778 |
| CDC activities | 0.430277 |
| list Skip | 0.695814 |
| Chicago | 0.231066 |
| page options Skip | 0.883771 |
| Public Health Road | 0.551725 |
| Healthy Brain Initiative | 0.970938 |
|
| navigation Skip | 0.703312 |
| Alzheimer’s Association | 0.436982 |
| Prevention | 0.257432 |
| Disease Control | 0.558261 |
| outcomes | 0.254694 |
| National Partnerships | 0.403821 |
| model | 0.262356 |
| Brain Initiative Logic | 0.616443 |
|
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Influenza Vaccination Coverage Among Health Care Personnel -United States, 2013-14 Influenza Season |
Carla L. Black, PhD1, Xin Yue, MPS, MS1, Sarah W. Ball, ScD2, Sara M. |
| influenza vaccination coverage | 0.853794 |
| general HCP personnel | 0.497781 |
| clinical HCP | 0.552274 |
| volunteer HCP members | 0.491506 |
| employer vaccination policies | 0.439416 |
| vaccination coverage | 0.868234 |
| Internet panel survey | 0.631414 |
| influenza vaccination levels | 0.428981 |
| nonclinical HCP | 0.512474 |
| vaccination status | 0.403458 |
| population Internet panels | 0.30528 |
| opt-in Internet panels | 0.381278 |
| Comprehensive vaccination strategies | 0.433792 |
| HCP vaccination coverage | 0.730905 |
| nurse practitioners/physician assistants | 0.305596 |
| facilities offering vaccination | 0.397908 |
| HCP population | 0.466074 |
| employer vaccination requirements | 0.423527 |
| HCP | 0.996707 |
| health care settings | 0.423264 |
| vaccination promotion | 0.424486 |
| free on-site vaccination | 0.449044 |
| unvaccinated HCP | 0.482865 |
| Internet panels | 0.387222 |
| HCP working | 0.510548 |
|
| vaccination availability | 0.401165 |
| vaccination | 0.895765 |
| higher HCP vaccination | 0.633843 |
| overall HCP influenza | 0.536686 |
| vaccination requirements | 0.472472 |
| higher vaccination coverage | 0.474228 |
| ascertain vaccination promotion | 0.405676 |
| food service workers | 0.316509 |
| on-site vaccination | 0.449209 |
| self-reported influenza vaccination | 0.464187 |
| HCP influenza vaccination | 0.751892 |
| Nonclinical personnel††| 0.308731 |
| work settings | 0.347349 |
| clerical support workers | 0.316708 |
| seasonal vaccination coverage | 0.429918 |
| general population Internet | 0.308658 |
| vaccination promotion trend | 0.404484 |
| occupation type | 0.344463 |
| Carla L. Black | 0.310489 |
| Professional clinical HCP | 0.535935 |
| Internet panel sources | 0.312919 |
| influenza vaccination | 0.868462 |
| clinical personnel | 0.312014 |
| LTC settings | 0.543738 |
|
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Cigarette, Cigar, and Marijuana Use Among High SchoolStudents - United States, 1997-2013 |
Italia V. Rolle, PhD1; Sara M. Kennedy, MPH1; Israel Agaku, DMD1; Sherry Everett Jones, PhD, JD2; Rebecca Bunnell, ScD1; Ralph Caraballo, PhD1; Xin Xu, PhD1; Gillian Schauer, MPH1; Tim McAfee, MD1. |
| Sherry Everett Jones | 0.297248 |
| racial/ethnic subgroups | 0.388897 |
| white students | 0.297708 |
| analytic sample | 0.295705 |
| current marijuana | 0.545415 |
| medical marijuana | 0.409789 |
| marijuana | 0.918197 |
| overall increase | 0.298521 |
| significant linear trend | 0.360773 |
| cigarette smoking.** Increases | 0.350851 |
| cigar | 0.669043 |
| recreational marijuana | 0.409333 |
| Youth Risk Behavior | 0.297962 |
| black students | 0.342018 |
| tobacco | 0.335532 |
| lower cigarette | 0.305278 |
| current users | 0.301393 |
| biennial cross-sectional survey | 0.29074 |
| racial /ethnic subgroups | 0.291839 |
| survey.§ Exclusive cigarette | 0.380585 |
| final analytic sample | 0.28636 |
| exclusive cigarette | 0.507563 |
| tobacco product prices | 0.288385 |
| cigar users | 0.583247 |
| study period | 0.40737 |
|
| current cigarette | 0.34514 |
| 12th grade students | 0.321139 |
| cigarettes | 0.313119 |
| significant quadratic trend | 0.351427 |
| quadratic trends | 0.326916 |
| private school students | 0.312629 |
| lower academic achievement | 0.293279 |
| logistic regression analyses | 0.36759 |
| exclusive marijuana | 0.877903 |
| Public health concerns | 0.281805 |
| linear increases | 0.289146 |
| current marijuana users | 0.486935 |
| Hispanic students | 0.743866 |
| public health advances | 0.283234 |
| public health professionals | 0.295624 |
| exclusive marijuana users | 0.474011 |
| detrimental health effects | 0.284119 |
| public health | 0.352958 |
| Logistic regression models | 0.282317 |
| cigarette | 0.663976 |
| cigars | 0.303111 |
| concomitant public health | 0.284835 |
| sex | 0.307528 |
| overall percentage decrease | 0.300395 |
|
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WHO South-East Asia Region (SEAR) 2014-2015 |
Overview of the CDC Influenza Division International Program WHO South-East Asia Region (SEAR), its objectives and goals, and contains downloadable annual reports on supported countries. |
| avian influenza | 0.644189 |
| Email | 0.488796 |
| epidemiologic influenza surveillance | 0.652315 |
| Global Influenza Surveillance | 0.654173 |
| seasonal influenza vaccination | 0.604334 |
| influenza virologic | 0.605186 |
| Bi-Regional Influenza Surveillance | 0.623533 |
| Disease Control | 0.515651 |
| novel influenza viruses | 0.610332 |
| novel respiratory viruses | 0.591911 |
| pandemic influenza preparedness | 0.707663 |
| standard operating procedures | 0.497701 |
| cooperative agreement | 0.61455 |
| influenza RT-PCR quality | 0.602017 |
| laboratory capacity | 0.491188 |
| pandemic influenza vaccine | 0.631206 |
| influenza laboratory staff | 0.613747 |
| India | 0.534819 |
| cooperative agreements | 0.513757 |
| New Delhi | 0.843893 |
| Influenza Division | 0.753727 |
| influenza surveillance | 0.717545 |
| Regional Office | 0.501593 |
| public health laboratories | 0.612282 |
|
| International Health Regulations | 0.513457 |
| acute respiratory infections | 0.519015 |
| influenza | 0.920861 |
| influenza laboratories | 0.573882 |
| U.S. Centers | 0.513757 |
| south-east asia region | 0.57054 |
| influenza vaccine manufacturing | 0.629439 |
| National Influenza Centers | 0.688122 |
| CDC Influenza Program | 0.724115 |
| pandemic influenza | 0.746508 |
| influenza diagnostics | 0.574859 |
| pandemic vaccine deployment | 0.522164 |
| influenza disease | 0.588402 |
| member countries | 0.557244 |
| CDC’s Influenza | 0.591406 |
| influenza pandemic preparedness | 0.624546 |
| influenza vaccine manufacturers | 0.600543 |
| regional laboratory workshop | 0.552944 |
| influenza vaccines | 0.606617 |
| Sri Lanka | 0.549297 |
| influenza surveillance data | 0.616007 |
| influenza RT-PCR procedures | 0.602179 |
| South-East Asia | 0.595001 |
| Influenza Program Director | 0.717711 |
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