Data-Driven Goals for Curbing the U.S. HIV Epidemic by 2030

Disinformation campaigns on online social networks (OSNs) in recent years have underscored democracy’s vulnerability to such operations and the importance of identifying such operations and dissecting their methods, intents, and source. This paper is another milestone in a line of research on political disinformation, propaganda, and extremism on OSNs. A total of 40,000 original Tweets (not re-Tweets or Replies) related to the U.S. 2020 presidential election are collected. The intent, focus, and political affiliation of these political Tweets are determined through multiple discussions and revisions. There are three political affiliations: rightist, leftist, and neutral. A total of 171 different classes of intent or focus are defined for Tweets. A total of 25% of Tweets were left out while defining these classes of intent. The purpose is to assure that the defined classes would be able to cover the intent and focus of unseen Tweets (Tweets that were not used to determine and define these classes) and no new classes would be required. This paper provides these classes, their definition and size, and example Tweets from them. If any information is included in a Tweet, its factuality is verified through valid news sources and articles. If any opinion is included in a Tweet, it is determined that whether or not it is extreme, through multiple discussions and revisions. This paper provides analytics with regard to the political affiliation and intent of Tweets. The results show that disinformation and extreme opinions are more common among rightists Tweets than leftist Tweets. Additionally, Coronavirus pandemic is the topic of almost half of the Tweets, where 25.43% of Tweets express their unhappiness with how Republicans have handled this pandemic.

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AHEAD: a data resource to support the Ending the HIV Epidemic in the US Initiative (Preprint)

10.2196/preprints.33522 ◽

2021 ◽

Author(s):

Patrick Sullivan ◽

Cory R Woodyatt ◽

Oskian Kouzouian ◽

Kristen Parrish ◽

Jennifer Taussig ◽

...

Keyword(s):

Public Health ◽

Data Visualization ◽

Census Data ◽

Quality Data ◽

Surveillance Systems ◽

Data Systems ◽

Data Resource ◽

Hiv Epidemic ◽

Indicator Data ◽

The U.S

UNSTRUCTURED Objectives: America’s HIV Epidemic Analysis Dashboard (AHEAD) is a data visualization tool that displays relevant data on the 6 HIV indicators provided by CDC that can be used to monitor progress towards ending the HIV epidemic in local communities across the U.S. The objective of AHEAD is to make data available to stakeholders that can be used to measure national and local progress towards 2025 and 2030 Ending the HIV Epidemic in the U.S. (EHE) goals and to help jurisdictions make local decisions that are grounded in high-quality data. Methods: AHEAD displays data from public health data systems (e.g., surveillance systems, Census data), organized around the six EHE indicators (incidence, knowledge of status, diagnoses, linkage to HIV medical care, viral suppression, and PrEP coverage). Data are displayed for each of the EHE priority areas (48 counties Washington, D.C. and San Juan, PR) which accounted for more than 50% of all U.S. HIV diagnoses in 2016 and 2017 and seven primarily Southern states with high rates of HIV in rural communities. AHEAD also displays data for the 43 remaining states for which data are available. Data features prioritize interactive data-visualization tools that allow users to compare indicator data stratified by sex at birth, race, age, and transmission category within a jurisdiction (when available) or compare data on EHE indicators between jurisdictions. Results: AHEAD was launched on August 14, 2020. In the 11 months since its launch, the Dashboard has been visited 26,591 times by 17,600 unique users. About a third of all users returned to the Dashboard at least once. On average, users engaged with 2.4 pages during their visit to the Dashboard, indicating that the average user goes beyond the informational landing page to engage with one or more pages of data and content. The most frequently visited content pages are the Jurisdictions webpages. Conclusions: The Ending the HIV Epidemic plan is described as a “whole of society” effort. Societal public health initiatives require objective indicators and require that all societal stakeholders have transparent access to indicator data at the level of the health jurisdictions responsible for meeting the goals of the plan. Data transparency empowers local stakeholders to track movement towards EHE goals, identify areas with needs for improvement, make data-informed adjustments to deploy the expertise and resources required to locally tailor and implement strategies to end the HIV epidemic in their jurisdiction.

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The Rapid Adoption of Data-Driven Decision-Making

The American Economic Review ◽

10.1257/aer.p20161016 ◽

2016 ◽

Vol 106 (5) ◽

pp. 133-139 ◽

Cited By ~ 52

Author(s):

Erik Brynjolfsson ◽

Kristina McElheran

Keyword(s):

Decision Making ◽

Companion Paper ◽

Census Bureau ◽

Data Driven ◽

Data Driven Decision Making ◽

Manufacturing Plants ◽

Using Data ◽

Large Representative ◽

The U.S ◽

Case Based

We provide a systematic empirical study of the diffusion and adoption patterns of data-driven decision making (DDD) in the U.S. Using data collected by the Census Bureau for a large representative sample of manufacturing plants, we find that DDD rates nearly tripled (11%-30%) between 2005 and 2010. This rapid diffusion, along with results from a companion paper, are consistent with case-based evidence that DDD tends to be productivity-enhancing. Yet certain plants are significantly more likely to adopt than others. Key correlates of adoption are size, presence of potential complements such as information technology and educated workers, and firm learning.

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Men Who Have Sex With Men and Women: Pieces of the U.S. HIV Epidemic Puzzle

Sexually Transmitted Diseases ◽

10.1097/01.olq.0000233666.67788.fc ◽

2006 ◽

Vol 33 (10) ◽

pp. 596-598 ◽

Cited By ~ 15

Author(s):

Adaora A. Adimora ◽

Robert E. Fullilove

Keyword(s):

Men And Women ◽

Hiv Epidemic ◽

Sex With Men ◽

The U.S

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U.S. AI Workforce: Policy Recommendations

10.51593/20200087 ◽

2021 ◽

Author(s):

Diana Gehlhaus ◽

◽

Luke Koslosky ◽

Kayla Goode ◽

Claire Perkins

Keyword(s):

Training System ◽

Data Driven ◽

Policy Recommendations ◽

Policy Goals ◽

Workforce Policy ◽

Equity In Access ◽

Intelligence Education ◽

Definition Of ◽

And Training ◽

The U.S

This policy brief addresses the need for a clearly defined artificial intelligence education and workforce policy by providing recommendations designed to grow, sustain, and diversify the U.S. AI workforce. The authors employ a comprehensive definition of the AI workforce—technical and nontechnical occupations—and provide data-driven policy goals. Their recommendations are designed to leverage opportunities within the U.S. education and training system while mitigating its challenges, and prioritize equity in access and opportunity to AI education and AI careers.

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Multi-Attribute Ecological and Socioeconomic Geodatabase for the Gulf of Mexico Coastal Region of the United States

Data ◽

10.3390/data5010003 ◽

2019 ◽

Vol 5 (1) ◽

pp. 3

Author(s):

Andrew Shamaskin ◽

Sathishkumar Samiappan ◽

Jiangdong Liu ◽

Jennifer Roberts ◽

Anna Linhoss ◽

...

Keyword(s):

Gulf Of Mexico ◽

Gulf Coast ◽

Coastal Region ◽

The United States ◽

Geospatial Data ◽

Data Driven ◽

Ecosystem Functions ◽

Funding Agency ◽

Non Profit ◽

The U.S

Strategic, data driven conservation approaches are increasing in popularity as conservation communities gain access to better science, more computing power, and more data. High resolution geospatial data, indicating ecosystem functions and economic activity, can be very useful for any conservation expert or funding agency. A framework was developed for a data driven conservation prioritization tool and a data visualization tool. The developed tools were then implemented and tested for the U.S. Gulf of Mexico coastal region defined by the Gulf Coast Ecosystem Restoration Council. As a part of this tool development, priority attributes and data measures were developed for the region through 13 stakeholder charrettes with local, state, federal, and other non-profit organizations involved in land conservation. This paper presents the measures that were developed to reflect stakeholder priorities. These measures were derived from openly available geospatial and non-geospatial data sources. This database contained 19 measures, aggregated into a one km2 hexagonal grid and grouped by the overarching goals of habitat, water quality and quantity, living coastal and marine resources, community resilience, and economy. The developed measures provided useful data for a conservation planning framework in the U.S. Gulf of Mexico coastal region.

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A data-driven graphical approach to quantify learning capability for systems resilience: A case study on the U.S. electric power grid

Safety and Reliability – Theory and Applications ◽

10.1201/9781315210469-131 ◽

2017 ◽

Author(s):

B Cassottana ◽

L Shen ◽

L Tang

Keyword(s):

Electric Power ◽

Power Grid ◽

Data Driven ◽

Learning Capability ◽

Graphical Approach ◽

Electric Power Grid ◽

The U.S

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A National Hiv Clinical Mentorship Program: Enabling Zambia to Accelerate Towards the Controlling the Hiv Epidemic

10.21203/rs.3.rs-151655/v1 ◽

2021 ◽

Author(s):

Mary Adetinuke Boyd ◽

Sombo Fwoloshi ◽

Peter A. Minchella ◽

James Simpungwe ◽

Terence Siansalama ◽

...

Keyword(s):

People Living With Hiv ◽

Viral Load Suppression ◽

Mentorship Program ◽

Hiv Epidemic ◽

Level Data ◽

Control And Prevention ◽

Living With Hiv ◽

Clinical Mentorship ◽

Regular Site ◽

The U.S

Abstract Background Although Zambia has increased the proportion of people living with HIV (PLHIV) who are on antiretroviral therapy (ART) in recent years, progress toward HIV epidemic control remains inconsistent. Some districts are still failing to meet the UNAIDS 90/90/90 targets where 90% of PLHIV should know their status, 90% of those who know their status should be receiving sustained ART, and 90% of those on ART should have documented viral load suppression (VLS) by 2020. Providing consistently excellent HIV services at all ART health facilities is critical for achieving the UNAIDS 90/90/90 targets and controlling the HIV epidemic in Zambia. Zambia Ministry of Health (MoH), in collaboration with the U.S. Centers for Disease Control and Prevention (CDC), aimed to achieve these targets through establishing a national HIV clinical mentorship program in which government-employed mentors were assigned to specific facilities with a mandate to identify and ameliorate programmatic challenges. Methods Mentors were hired, trained and deployed to individual facilities in four provinces to mentor staff on quality HIV clinical and program management. The pre-mentorship period was July 2018–September 2018 and the post-mentorship period was July 2019–September 2019. Results Review of key programmatic indicators from the pre and post-deployment periods revealed HIV testing yield improved from 4.2–6.8% (P < 0.001) as fewer HIV tests were needed despite the number of PLHIV being identified and placed on ART increasing from 492,613 to 521,775, and VLS increased from 84.8–90.1% (p < 0.001). Conclusions Key considerations in the establishment of an HIV clinical mentorship program include having a government-led process of regular site level data review and continuous clinical mentorship underpinned by quality improvement methodology.

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