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Global Health - South Africa - CDC's HIV/AIDS Care and Treatment Programs: TB and HIV |
CDC partners in South Africa with government and parastatal agencies, private institutions, universities and non-governmental organizations to improve the country’s public health foundation, to prevent transmission of HIV, to provide care and treatment for those who are already infected with HIV, and to strengthen laboratory capacity.
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| southern Africa sub | 0.378146 |
| test kits | 0.27099 |
| Laboratory investments | 0.268604 |
| number | 0.226758 |
| pregnant women | 0.271762 |
| Disease Control | 0.273419 |
| special populations | 0.270508 |
| integrated response | 0.278505 |
| TB/HIV clinical services | 0.433796 |
| TB screening | 0.539373 |
| miners | 0.22894 |
| TB patients | 0.531144 |
| biosafety cabinets | 0.271045 |
| TB incidence | 0.593332 |
| peri-mining communities | 0.271833 |
| HIV+ populations | 0.275581 |
| South Africa | 0.871379 |
| HIV systems integration | 0.403273 |
| Dr. Hloniphile Mabuza | 0.35736 |
| Human resources | 0.268815 |
| Dr Hloniphile Mabuza | 0.3422 |
| age group | 0.284986 |
| prisoners | 0.227811 |
| targets | 0.224212 |
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| TB/HIV co-infection rate | 0.466367 |
| TB epidemic | 0.695044 |
| TB high burden | 0.630341 |
| Hloniphile Mabuza | 0.360779 |
| collaborative TB/HIV activities | 0.426624 |
| dual epidemics | 0.280918 |
| TB/HIV response | 0.376628 |
| sub district | 0.280202 |
| TB diagnostics | 0.533101 |
| drug resistant strains | 0.338003 |
| TB infection prevention | 0.593079 |
| per-mining communities | 0.274831 |
| TB/HIV Lead | 0.389604 |
| implementation | 0.223403 |
| Global AIDS Program | 0.336367 |
| AFB smear | 0.275322 |
| greatest brunt | 0.289069 |
| TB | 0.949547 |
| Global TB report | 0.631171 |
| limited GeneXpert equipment | 0.330516 |
| site-level integration | 0.269389 |
| PLHIV | 0.223412 |
| congregate settings | 0.271696 |
| HIV epidemic. South | 0.46238 |
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CDC Telebriefing: Influenza A (H3N2) Variant Virus - Friday, August 3, 2012 |
CDC Weight of the Nation Press Briefing
November 10, 2011, Noon E.T. |
| pandemic H1N1 virus | 0.497181 |
| swine virus | 0.572893 |
| numbers. Dr. Bresee | 0.490483 |
| H1N1 pandemic virus | 0.492983 |
| pigs | 0.511395 |
| novel influenza viruses | 0.505433 |
| CNN Medical News | 0.477202 |
| H3N2v virus | 0.502639 |
| joe bresee | 0.938128 |
| close contact | 0.501015 |
| influenza A virus | 0.514282 |
| seasonal influenza virus | 0.536778 |
| LISA FERGUSON | 0.610433 |
| H3N2 variant viruses | 0.486865 |
| mike stobbe | 0.49912 |
| seasonal flu | 0.483026 |
| early pandemic virus | 0.501625 |
| variant virus infections | 0.51805 |
| variant virus vaccine | 0.522627 |
| good question. | 0.505707 |
| influenza viruses | 0.645907 |
| b-r-e-s-e-e. Dr. Bresee | 0.499999 |
| human influenza viruses | 0.509845 |
| TOM SKINNER | 0.822115 |
| rob stein | 0.487472 |
|
| H3N2 variant virus | 0.62666 |
| variant virus infection | 0.537254 |
| virus | 0.850889 |
| Dr. Bresee | 0.703581 |
| variant influenza viruses | 0.512678 |
| pandemic H1 virus | 0.501387 |
| Seasonal influenza viruses | 0.497291 |
| variant viruses | 0.495519 |
| public health | 0.478186 |
| purposes animal viruses | 0.47507 |
| virus vaccine candidate | 0.503008 |
| cases | 0.670753 |
| question | 0.616385 |
| miriam falco | 0.563427 |
| flu viruses | 0.482521 |
| timothy martin | 0.520317 |
| human virus | 0.506645 |
| people | 0.4879 |
| Ohio. The virus | 0.492578 |
| Dr. Joseph Bresee | 0.500028 |
| previous swine viruses | 0.508338 |
| H3N2 virus infections | 0.519226 |
| seasonal virus | 0.510095 |
| humans | 0.543112 |
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Fewer Americans having problems paying medical bills | CDC Online Newsroom | Press Release |
Fewer Americans having problems paying medical bills |
| CDC’s National | 0.515445 |
| private coverage | 0.562931 |
| adults | 0.447837 |
| findings | 0.422596 |
| medical bills | 0.953645 |
| percent | 0.689147 |
| 2011-June | 0.44653 |
| children | 0.448216 |
| percentage | 0.529229 |
| U.S. DEPARTMENT | 0.500413 |
| Early Release | 0.513522 |
| Center | 0.425045 |
| period | 0.423248 |
| bills. Medical bills | 0.644639 |
| dentists | 0.424317 |
|
| nursing home | 0.50457 |
| equipment | 0.422899 |
| medication | 0.423018 |
| therapists | 0.422747 |
| families | 0.556389 |
| age groups | 0.49921 |
| people | 0.448678 |
| Estimates | 0.424406 |
| Health Statistics | 0.511625 |
| home care | 0.504467 |
| doctors | 0.421846 |
| Health Interview Survey | 0.594119 |
| report | 0.479131 |
| HUMAN SERVICES | 0.500235 |
| problems | 0.622035 |
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Preventing Chronic Disease | The Impact of New York City™s Health Bucks Program on Electronic Benefit Transfer Spending at Farmers Markets, 2006"2009 - CDC |
Increasing the accessibility and affordability of fresh produce is an important strategy for municipalities combatting obesity and related health conditions. |
| EBT data | 0.399407 |
| Supplemental Nutrition | 0.321878 |
| neighborhood poverty level | 0.304303 |
| daily EBT revenues | 0.380487 |
| Health Bucks markets | 0.354253 |
| low-income neighborhoods | 0.320155 |
| York City farmers | 0.339312 |
| financial incentives | 0.312277 |
| New York City | 0.782848 |
| EBT spending | 0.454294 |
| daily mean EBT | 0.356554 |
| electronic benefit transfer | 0.368906 |
| Bucks EBT incentive | 0.459543 |
| records EBT sales | 0.385378 |
| related EBT sales | 0.38071 |
| NYC farmers markets | 0.309787 |
| Human Resources Administration | 0.299893 |
| EBT sales | 0.826206 |
| study period | 0.297857 |
| EBT credits | 0.347406 |
| Two-dollar Health Bucks | 0.338277 |
| health bucks program | 0.553633 |
| Health Bucks coupons | 0.612701 |
| daily EBT revenue | 0.368331 |
|
| mean EBT market | 0.378215 |
| Health Bucks EBT | 0.478818 |
| farmers markets | 0.674985 |
| City farmers markets | 0.364892 |
| Public Health Nutr | 0.319386 |
| mean daily EBT | 0.388721 |
| Bucks coupons introduction | 0.303516 |
| average daily ebt | 0.58814 |
| Health Bucks incentives | 0.32038 |
| EBT terminals | 0.36256 |
| Health Bucks incentive | 0.414807 |
| daily EBT sales | 0.741479 |
| mean EBT sales | 0.430219 |
| per-market EBT sales | 0.379711 |
| EBT wireless terminals | 0.362849 |
| fresh produce | 0.382889 |
| higher daily EBT | 0.38405 |
| York City Department | 0.389447 |
| SNAP recipients | 0.38487 |
| Health Bucks | 0.940348 |
| required EBT terminals | 0.350032 |
| SNAP benefits | 0.368057 |
| EBT sales data | 0.484403 |
| ongoing farmers markets | 0.309461 |
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Enterovirus D68 (EV-D68) |
Enterovirus D68 (EV-D68) is one of many non-polio enteroviruses. |
| Enterovirus D68 | 0.736639 |
| common type | 0.524062 |
| CDC | 0.570702 |
| body aches | 0.468189 |
| runny nose | 0.465225 |
| specific lab tests | 0.508131 |
| Health Care Professionals | 0.506626 |
| respiratory secretions | 0.501178 |
| state health departments | 0.503226 |
| Small numbers | 0.47106 |
| nasal mucus | 0.464171 |
| EV-D68 likely spreads | 0.546488 |
| enterovirus typing | 0.544698 |
| enterovirus season | 0.538839 |
| especially long-term control | 0.497715 |
| CDC’s guidance | 0.48332 |
| enterovirus testing | 0.561772 |
| symptoms | 0.531301 |
| different types | 0.528074 |
| asthma medications | 0.469871 |
| state public health | 0.518028 |
| primary care provider | 0.500973 |
| difficulty breathing | 0.509492 |
| CDC medical epidemiologist | 0.533894 |
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| EV-D68 testing | 0.48777 |
| medical treatment | 0.461995 |
| United States | 0.513991 |
| mild symptoms | 0.522906 |
| likely many thousands | 0.46941 |
| enterovirus infection | 0.546657 |
| infected person coughs | 0.539177 |
| severe symptoms | 0.524016 |
| muscle aches | 0.466216 |
| mild EV-D68 infections | 0.551232 |
| polymerase chain reaction | 0.507691 |
| higher risk | 0.510875 |
| future seasons | 0.529265 |
| non-polio enteroviruses | 0.559256 |
| EV-D68 | 0.630158 |
| EV-D68 cases | 0.499425 |
| asthma action plan | 0.595303 |
| people | 0.490265 |
| respiratory illnesses | 0.488985 |
| enteroviruses | 0.653222 |
| intensive supportive therapy | 0.502573 |
| confirmed EV-D68 infection | 0.562029 |
| nationwide outbreak | 0.53129 |
| severe respiratory illness | 0.933572 |
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CDC Web-based PPE Training |
Description |
| Ebola Preparedness | 0.956629 |
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| PPE Guidelines Introduction | 0.915042 |
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Announcements: Global Road Safety Week - May 4-10,2015 |
The United Nations Road Safety Collaboration has declared May 4–10, 2015, as the third United Nations Global Road Safety Week (GRSW). With the theme #SaveKidsLives, this year's GRSW is dedicated to children, focusing on their safety on the world's roads, actions that better ensure this, and the promotion for inclusion of safe and sustainable transport in the U.N. |
| CDC | 0.479254 |
| promotion efforts | 0.466763 |
| Road Safety Collaboration | 0.692297 |
| global development agenda | 0.535979 |
| United Nations Decade | 0.532899 |
| Human Services | 0.512785 |
| MMWR HTML versions | 0.517582 |
| U.S. Department | 0.510691 |
| electronic PDF version | 0.512678 |
| Child Declaration | 0.473117 |
| regional congress | 0.466757 |
| government agencies | 0.468782 |
| World Health Organization | 0.525784 |
| Injury Center | 0.467426 |
| Additional information | 0.466177 |
| Contact GPO | 0.474647 |
| commercial sources | 0.464534 |
| SaveKidsLives campaign | 0.478261 |
| GRSW | 0.475632 |
| private sector | 0.465174 |
| original paper copy | 0.515105 |
| safety tips | 0.495238 |
| Global Road Safety | 0.682275 |
| Children Safe | 0.475201 |
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| share best practices | 0.526381 |
| United Nations Road | 0.676224 |
| United States | 0.472247 |
| U.S. Government Printing | 0.520602 |
| original MMWR paper | 0.515675 |
| key leaders | 0.468819 |
| development agenda | 0.546407 |
| child road safety | 0.585205 |
| road safety | 0.946639 |
| MMWR readers | 0.467122 |
| Costa Rica | 0.464045 |
| U.S. efforts | 0.465918 |
| road safety experts | 0.591653 |
| non-governmental organizations | 0.468153 |
| sustainable transport | 0.476622 |
| world leaders | 0.475081 |
| Safe Kids Coalition | 0.521201 |
| larger Decade | 0.468362 |
| typeset documents | 0.464483 |
| trade names | 0.46457 |
| post-2015 development agenda | 0.541748 |
| non-CDC sites | 0.463857 |
| Nations Road Safety | 0.69144 |
| consensus document | 0.467747 |
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US Food and Drug Administration, socioeconomic factors, smoking, commerce, policy |
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 | 0.517418 |
| black residents | 0.461218 |
| Tobacco Control Act | 0.549533 |
| labeling violations | 0.450802 |
| tobacco retailer compliance | 0.453327 |
| FDA inspections data | 0.457681 |
| self-service display violation | 0.471446 |
| regulated tobacco products | 0.500255 |
| tobacco | 0.69624 |
| recent FDA regulations | 0.445632 |
| neighborhood health disparities | 0.491094 |
| FDA retailer advertising | 0.462116 |
| neighborhoods | 0.497921 |
| mislabeled products | 0.45222 |
| labeling regulations | 0.463557 |
| labeling retailer violations | 0.47207 |
| labeling inspections | 0.568947 |
| violations | 0.536098 |
| particular neighborhood characteristics | 0.443254 |
| neighborhood disparities | 0.569803 |
| poverty line | 0.564623 |
| free samples | 0.487613 |
| tobacco products | 0.612704 |
| Nicotine Tob Res | 0.499458 |
| tobacco retailer regulations | 0.492108 |
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| Latino residents | 0.51205 |
| single-cigarette sales | 0.443168 |
| tobacco sales violation | 0.453899 |
| specific FDA advertising | 0.453595 |
| Family Smoking Prevention | 0.490054 |
| new FDA advertising | 0.443496 |
| point-of-sale tobacco advertising | 0.449011 |
| FDA | 0.527865 |
| United States | 0.472677 |
| retailer compliance | 0.457166 |
| single cigarettes | 0.915179 |
| FDA regulations | 0.454776 |
| neighborhood characteristics | 0.889177 |
| FDA retailer inspections | 0.480264 |
| FDA advertising | 0.501029 |
| self-service displays | 0.655414 |
| Latino residents increases | 0.468935 |
| tobacco retailers | 0.506002 |
| Federal Poverty Line | 0.4938 |
| Tob Control | 0.520468 |
| Tobacco retailer violations | 0.496302 |
| et al | 0.456153 |
| FDA inspections | 0.487577 |
| tobacco industry products | 0.463844 |
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CDC Challenge Winners! | CDC Features |
On March 29, 2016 the Centers for Disease Control and Prevention (CDC) recognized 8 public and private healthcare practices and systems across the country as the 2015 HA-VTE Prevention Challenge Champions for their success in helping patients prevent healthcare-associated blood clots. |
| innovative HA-VTE prevention | 0.536348 |
| unique ambulation program | 0.509332 |
| risk assessment | 0.5122 |
| honorable mentions | 0.521888 |
| prevention activities | 0.484087 |
| U.S. federal entities | 0.49982 |
| recent hospitalization | 0.470932 |
| Sheppard Pratt Hospital | 0.508074 |
| Cincinnati Medical Center | 0.501744 |
| exceptional VTE prevention | 0.531209 |
| Rotunda Hospital | 0.467097 |
| care organizations | 0.513276 |
| Healthcare Network | 0.509787 |
| Disease Control | 0.467464 |
| visit HA-VTE Prevention | 0.531059 |
| health care professionals | 0.515109 |
| Challenge Champions range | 0.542054 |
| Medium Reach | 0.509725 |
| patients | 0.475979 |
| innovative prophylaxis-dosing protocol | 0.511554 |
| post-discharge monitoring program | 0.505171 |
| VTE prevention initiatives | 0.536881 |
| hospital networks | 0.518547 |
| Large Single Hospital | 0.516203 |
| public health issue | 0.527039 |
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| Prevention Challenge Champions | 0.745153 |
| Regional Medical Center | 0.504204 |
| United States | 0.460756 |
| appropriate prevention measures | 0.527346 |
| healthcare-associated blood clots | 0.652575 |
| private healthcare practices | 0.533551 |
| major decreases | 0.463881 |
| healthcare treatment | 0.476241 |
| Medical Center | 0.546317 |
| HA-VTE Prevention Challenge | 0.956097 |
| large healthcare systems | 0.52378 |
| Healthcare Research | 0.465094 |
| Large Reach | 0.508709 |
| Michigan Hospital Medicine | 0.510228 |
| VTE prevention strategies | 0.545214 |
| obstetric patients | 0.465667 |
| innovative strategies | 0.465688 |
| hospital trauma units | 0.514983 |
| healthcare organization | 0.460653 |
| Harborview Medical Center | 0.506534 |
| multi-hospital systems | 0.482988 |
| electronic risk assessment | 0.510642 |
| non-cash award recognition | 0.500622 |
| healthcare-associated venous thromboembolism | 0.527824 |
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TB Guidelines by Topic |
Centers for Disease Control and Prevention, Division of Tuberculosis Elimination |
| (TB) | 0.638881 |
| Basic TB Facts | 0.573107 |
| National TB Program | 0.510618 |
| United States | 0.20697 |
| TB Risk Factors | 0.56831 |
| TB Cohort Review | 0.531596 |
| Infection Control | 0.236657 |
| latent tb infection | 0.74251 |
| Stop TB | 0.577465 |
| TB Genotyping | 0.503887 |
| Search Form Controls | 0.224129 |
| Tuberculosis Laboratory Aggregate | 0.219952 |
| Community Stop TB | 0.556101 |
| Latent Tuberculosis Infection | 0.303427 |
| Molecular DR Testing | 0.209848 |
| Effective TB Interviewing | 0.531182 |
| TB Terms | 0.558212 |
| Webinars TB | 0.490837 |
| World TB | 0.556117 |
| TB Contact Investigation | 0.535221 |
| Toolkits TB eDOT | 0.532965 |
| U.S. TB Champions | 0.509169 |
| TB | TB | 0.932895 |
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| TB Prevention | 0.564815 |
| Detect Drug-Resistant TB | 0.564712 |
| Specific Populations | 0.218736 |
| TB Incidence | 0.518272 |
| XDR Mycobacterium tuberculosis | 0.223379 |
| Drug-Resistant TB | 0.746806 |
| Health Care Workers | 0.207274 |
| Research TB Epidemiologic | 0.565476 |
| Infectious TB | 0.490688 |
| TB Trials Consortium | 0.556929 |
| Tuberculosis Testing | 0.210639 |
| tb disease | 0.616236 |
| Latent TB Infection-Patient | 0.542123 |
| TB Day Resources | 0.49207 |
| TB Notes | 0.576786 |
| TB Programs | 0.522175 |
| Care Workers TB | 0.51707 |
| Treat Latent TB | 0.582627 |
| TB Treatment | 0.564937 |
| TB Control Programs | 0.52074 |
| Federal TB Task | 0.505824 |
| TB Background | 0.532655 |
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