Lumina’s AI-Driven Radiance Technology Provides Solution for Modernizing Security Clearance Process

Lumina’s AI-Driven Radiance Technology Provides Solution for Modernizing Security Clearance Process

~~Artificial Intelligence, machine learning, and data analysis can speed the investigatory process, allow for continuous evaluation and reduce existing backlog~~

Lumina’s AI-driven Radiance platform, which uses proprietary, deep-web listening algorithms to uncover risk, provides one solution for modernizing the security clearance process and reducing the existing backlog.  The company has configured Radiance’s exclusive Behavioral Risk Profiles (BRPs) against the 13 adjudicative guidelines criteria, allowing for earlier risk determination and prioritization of investigatory resources.

“As many security experts have pointed out, our current system is not only time consuming and slow, it is also out of sync with how people live in the 21st century.  To be sure, 50 years ago, interviews with neighbors, colleagues and other associates could help provide meaningful insights into our lives and habits,” said Allan Martin, CEO of Lumina. “Today, we share these very same insights willingly, publicly and knowingly across a variety of online platforms.  But, with more than 2.5 quintillion bytes of data created on the Internet every day, only a platform with Radiance’s capabilities can quickly and thoroughly find and prioritize relevant and actionable content.”

Radiance is designed to overcome the challenges of massive unstructured data ingestion, evaluation, and prioritization. This provides a rapidly deployable, scalable and user-friendly solution for the security clearance process.  The technology is comprised of three modules, for edge-to-edge risk detection.

Radiance Open Source Intelligence (OS-INT)

OS-INT is a deep-web listening tool that uses machine learning and artificial intelligence to assess and prioritize risk.  OS-INT scours publicly available data across the entire Internet, correlating names entered into the system with content related to its exclusive BRPs, and cross-referenced with more than one million queries into Lumina’s proprietary databases of risk.  Unlike social media monitoring, OS-INT is not reliant on a single platform or social media API, allowing for continuous ingestion of all open source data.

OS-INT’s security clearance bundle includes more than 16,220 terms related to the 13 adjudicative guidelines. OS-INT performs nearly 325,000 searches across the entire web, correlating names with associated risk behaviors. Similar results would take an individual running a manual web query more than 18 years to read and analyze.

OS-INT completes searches in an average of 4-5 minutes, providing prioritized, high resolution, and actionable results. The system allows for continuous monitoring and evaluation, mapping previous results against results from more recent queries.

The configuration of BRPs only collects publicly available information, within the scope of the investigation and does not use account creation or digital interaction with POIs. As a result, the collection of information adheres to Security Executive Agent Directive 5 guidelines.

Radiance Internet Intelligence’s (NET-INT) 

NET-INT’s proprietary algorithms continuously identify, monitor, capture, and prioritize IP addresses exhibiting anomalous behavior across multiple risk dimensions.  Its massive system of data ingestion has the capability to catalogue, index and redeploy Internet content related to risk dimensions associated with SEADs.

The system captures an IP addresses’ pattern of life data, prioritizing anomalous behavior. NET-INT also screens IP addresses associated with an entity or person of interest against all IP addresses displaying anomalous behavior collected over the system’s lifespan. 

NET-INT’s continuous monitoring of a POI’s Internet research behavior helps predict emergent behavior indicative of a violation of the guidelines.

Radiance Human Intelligence (HUM-INT) 

HUM-INT is powered by the S4 app, a crowd-sourced, mobile application that allows users to confidentially report concerns in real time. S4 app can be configured as a workplace tool, allowing employees to submit information related to potential risk behaviors exhibited by co-workers. A centralized management portal allows clients to access real-time threats to geo-fenced facility locations.

View Lumina’s blog and white paper on security clearance at www.luminaanalytics.com

About Lumina 
Lumina is a predictive analytics company founded on the idea that technology is a force for good.  The company’s optimized artificial intelligence capabilities help keep people and places safe and secure through active and early detection of high-risk behavior.  Lumina’s Radiance platform uses proprietary, deep web listening algorithms to uncover risk, provide timely, actionable information, and help prevent catastrophic loss.  Lumina is committed to protecting what matters most, and its Radiance platform is designed to help solve the world’s most challenging problems. 

For more information contact Jill Kermes at 202-957-0715 or jill.kermes@luminaanalytics.com

Modernizing the Security Clearance Process through Machine Learning and AI

Modernizing the Security Clearance Process through Machine Learning and AI

Late last month, President Donald Trump signed an Executive Order transferring responsibility for security clearance screening from the Office of Management and Budget to the Defense Department. 

The Administration had previously called the clearance process a target for government reform, noting in 2018 that “background investigations are critical to enabling national security missions and ensuring public trust in the workforce across the Government.”

The Administration’s efforts are part of an ongoing focus on reforming the clearance process, and reducing the existing backlog. 

That is because the current backlog peaked at 725,000 open investigations in 2018, with some Americans waiting more than 500 days just to start their first day at work.  As part of these efforts, the Federal Government hired 2,500 additional investigators in 2018 to address the backlog.


Re-thinking Security Clearance

In addition to the Executive Order, in February, Senator Mark Warner (D-VA), reintroduced The Modernizing the Trusted Workforce for the 21st Century Act (S.314).

The legislation calls for a major overhaul of the system.

It also sets targets to reduce the backlog to 200,000 by the end of 2020, and shorten the time required to issue a secret level clearance to 30 days or fewer and top secret level clearance to 90 days. 

The legislation also establishes the “clearance in person” or “one-clearance” concept. This would enable – within two weeks or fewer – clearances to follow employees who change agencies.

Similarly, the legislation calls for continuous evaluation. It would move from the existing periodic reviews, to dynamic and ongoing reviews in the future.

In many ways, these recommendations represent a complete re-thinking of the security clearance process.

As Senator Warner notes in his legislation, technologies will play a critical role in preventing, detecting and monitoring threats. He also notes the role data integration and analytics can play in expediting or focusing
re-investigations through delta reporting and continuous evaluation. 


An Antiquated System

As many security experts have pointed out, the current system is not only time consuming and slow, it is also out of sync with how people live today.  For example, as it currently works, a field investigator is assigned to confirm information from the applicant’s form, and to make sure that individual does not represent a threat to national security.

These determinations are based on the 13 adjudicative guideline criteria, which among others include, financial considerations, foreign preference and influence, alcohol consumption, and drug involvement.

To be sure, 50 years ago, interviews with neighbors, colleagues and other associates could help provide meaningful insights into our lives and habits.  But today, we share these very same insights publicly, willingly and knowingly across a variety of online platforms, making the Internet a useful, but largely untapped resource.


Challenges to Reform

In fact, according to Gary Reid, Director of Defense Intelligence patterns of life, including scans of public-facing social media could one day be considered.

A significant challenge is the volume of data on the web. 

With more than 2.5 quintillion bytes of data created on the Internet every day, searching for relevant content can be like looking for the proverbial needle in a haystack.


The role of AI and Machine Learning

One way to solve for this is through machine learning and AI capabilities – a super-charged web search, allowing for all that publicly available, open-source data to be searched for risk behaviors – in this case, associated with the 13 established adjudicative guidelines.

But rather than having to weed through thousands of pages of search results, these technologies can quickly synthesize the data and cull out high priority risks associated with guideline selectors. 

As a result, analysts receive the most critical data first, helping streamline their search process and gather the most relevant information.


Call it the Radiance Solution
              

Lumina’s AI-powered Radiance technology is specifically designed to overcome the challenges of massive unstructured data ingestion, evaluation, and prioritization. This provides a rapidly deployable, scalable and user-friendly solution for the security clearance process. 

The technology is comprised of three modules, for edge-to-edge risk detection.


Radiance Open Source Intelligence (OS-INT)

OS-INT is a deep-web listening tool that uses machine learning and artificial intelligence to assess and prioritize risk.  OS-INT scours publicly available data across the entire Internet, correlating names entered into the system with content related to its exclusive behavioral risk profiles (BRPS). It then cross-references that information with more than one million queries into Lumina’s proprietary databases of risk.  And, unlike social media monitoring, OS-INT is not reliant on a single platform or social media API, allowing for continuous ingestion of all open source data.

OS-INT’s security clearance bundle includes more than 16,220 terms related to the adjudicative guidelines. OS-INT performs nearly 325,000 searches across the entire web. It then correlates names with associated risk behaviors. Similar results would take an individual running a manual web query more than 18 years to read and analyze.

OS-INT completes searches in an average of 4-5 minutes, providing prioritized, high resolution, and actionable results. In addition, the system allows for continuous monitoring and evaluation, mapping previous results against results from more recent queries.

The configuration of BRPs only collects publicly available information, within the scope of the investigation. And, it does not use account creation or digital interaction with a person of interest. As a result, the collection of information adheres to Security Executive Agent Directive 5 guidelines.


Radiance Internet Intelligence (NET-INT)

NET-INT’s proprietary algorithms continuously identify, monitor, capture, and prioritize IP addresses exhibiting anomalous behavior across multiple risk dimensions.  In addition, its massive system of data ingestion has the capability to catalogue, index and redeploy Internet content related associated with the adjudicative guidelines.

The system captures an IP addresses’ pattern of life data, prioritizing anomalous behavior. NET-INT also screens IP addresses associated with an entity or person of interest against all IP addresses displaying anomalous behavior collected over the system’s lifespan. 

NET-INT’s continuous monitoring of a POI’s Internet research behavior then helps predict emergent behavior indicative of a violation of the guidelines.


Radiance Human Intelligence (HUM-INT)

HUM-INT is powered by the S4 app, a crowd-sourced, mobile application that allows users to confidentially report concerns in real time. The S4 app can be configured as a workplace tool, allowing employees to submit information related to potential risk behaviors exhibited by co-workers. A centralized management portal allows clients to access real-time threats to geo-fenced facility locations.


The Way Forward

As Washington continues its efforts to reduce the security backlog, and modernize the existing process, machine learning and artificial intelligence will play an important role.

Senator Warner recently said, “There is much more we can do to reform decades-old policies and processes to reflect today’s threat environment, adapt to the dynamic of a modern mobile workforce, and capitalize on opportunities offered by modern information technology.”

Lumina Expands its Predictive Analytics and Risk Sensing Capabilities with  Radiance Launch

Lumina Expands its Predictive Analytics and Risk Sensing Capabilities with Radiance Launch

~~AI-powered technology helps organizations anticipate, understand,
manage and mitigate risk~~

Lumina announced today the launch of its new Radiance platform, which uses proprietary, deep-web listening algorithms to uncover risk, provide timely and actionable information and help prevent catastrophic loss. The Radiance platform brings the power of Open-Source Intelligence (OS-INT), Internet Intelligence (NET-INT) and the See Something Say Something app (HUM-INT) for edge-to-edge risk detection.

“The power of Radiance is two-fold – its ability to ingest massive amounts of unstructured, open source data and its real-time ability to analyze that information to predict and prevent organizational risks and threats,” said Allan Martin, CEO of Lumina. “Radiance is designed to help keep people and places safe and secure, and this AI-driven solution will immediately transform how organizations think about risk management and risk mitigation.”

Radiance’s purpose-built, best-in-class algorithms overcome the challenges of massive unstructured data ingestion and prioritization.  Radiance scours the web, prioritizing current behaviors to predict future action. This is an advantage over other technologies, which focus only on historical behavior, which can lead to bias in the results. Additionally, clients can integrate their own structured and unstructured data into Radiance, allowing for correlation of internal databases against open source, publicly available data.

Radiance is a Software-as-a-Service (Saas) platform that includes managed service capabilities. It is rapidly deployable, scalable, highly configurable and user-friendly, and is comprised of the following components:

  • Radiance Open Source Intelligence (OS-INT) is a deep-web listening tool that uses machine learning and artificial intelligence to assess and prioritize risk. Names entered into OS-INT are correlated with content related to 20 different risk factors, known as Behavioral Risk Profiles (BRPs) and cross-referenced with more than 1 million queries into Lumina’s proprietary databases of risk, known as ecosystems. One search across all BRPs equates to more than 465,000 deep web searches.  OS-INT delivers prioritized results in about 5 minutes. A manual search of this magnitude would take a person more than 3 1/2 years to complete.
  • Radiance Internet Intelligence (NET-INT) detects means, motivation and target for attack planning. Its proprietary algorithms continuously identify, monitor, capture and prioritize IP addresses exhibiting anomalous behavior across multiple risk dimensions. The platform collects and stores more than 1 million interactions every day and since its inception has recorded more than 623,000 IP addresses engaged with threat-related risk topics.
  • Radiance Human Intelligence (HUM-INT) is powered by the S4 app, a crowd-sourced, mobile application that allows users to confidentially report concerns in real time. A centralized management portal allows clients to access real-time threats to geo-fenced locations.

“We constantly hear people say, ‘We have so much data, but what can we do with it?’  Radiance solves that problem by ingesting, integrating, correlating and analyzing disparate datasets.  It takes data never designed to identify risk, and prioritizes it – giving our clients an unbiased and fully auditable understanding of human behavior and associated threats,” said Dr. Morten Middelfart, Chief Data Scientist at Lumina.

He added that Radiance’s BRPs solve for the “data noise” obstacle associated with other OS-INT SaaS solutions.  In addition, Radiance drastically outperform existing Natural Language Processing (NLP) approaches to identify names of persons or entities in unstructured data. Radiance performed at a 93.1 percent accuracy level on unstructured, improperly cased documents such as HTML, JSON or computer code and other so-called messy documents compared to 0 percent for Stanford Named Entity Recognizer (NER) and other popular open-source NLP software. Additionally, the BRPs generated with Lumina’s machine learning are “human readable,” making them fully auditable as well.

About Lumina

Lumina is a predictive analytics company founded on the idea that technology is a force for good.  The company’s optimized artificial intelligence capabilities help keep people and places safe and secure through active and early detection of high-risk behavior.  Lumina’s Radiance platform uses proprietary, deep web listening algorithms to uncover risk, provide timely, actionable information, and help prevent catastrophic loss.  Lumina is committed to protecting what matters most, and its Radiance platform is designed to help solve the world’s most challenging problems.

For more information contact Jill Kermes at 202-957-0715 or jill.kermes@luminaanalytics.com

Technology’s Impact on National Security

Introduction

Homegrown radical terrorism and mass casualty events such as active shooter incidents in public spaces and schools remain real, prevalent threats to national security, to the security of private entities and their employees, to the economy, and to the values of a democratic society. There have been over 30 successful or attempted radical Islamist terror attacks on U.S. soil since 2009, in addition to multiple terrorist incidents stemming from other ideological motivations. There have also been dozens of mass shootings and school shootings during that same period. These types of incidents have cost hundreds of Americans their lives just in the past year.

Being able to respond to attacks is not enough. Instead, we can best protect ourselves by proactively detecting and preventing these threats from being realized, integrating cutting edge technology into our efforts. Individuals looking to commit terrorist attacks or other acts of violence do not operate in isolation – they leave indicators in their discussions, their behaviors, and their online activities. Using technology to identify these indicators and find these individuals before they can commit heinous acts is of the utmost importance for ensuring the security of our society and of private entities that may be at risk.

PART ONE: 
Detecting Online Radicalization

Since 9/11, America has experienced a shift in the type of threat posed by radical Islamist terrorism to the homeland. While the country’s major concern was once highly coordinated terrorist plots emanating from and directed by terrorist groups abroad, recent events, such as the Boston Marathon Bombing and the Orlando and San Bernardino shootings, have proven that homegrown terrorism and attacks carried out by single individuals or small groups are the more pressing concern. The Internet and social media have enabled terrorist groups like ISIS to reach and radicalize individuals and direct or inspire attacks around the globe, including in America. As a result, we need better methods to detect online radicalization of potential homegrown terrorists in order to prevent further attacks.

As of 2015, the FBI had 900 active investigations into homegrown violent extremists in all 50 states. Additionally, over 250 Americans have tried or succeeded at travelling to Syria to join the conflict there. 4 28 States and the District of Columbia have brought ISIS-related charges against individuals, and since the first arrests in 2014, 157 individuals have been charged in the U.S. for ISIS-related offenses. 5 Yet perhaps the most important statistic is that the majority of people charged in the U.S. for ISIS-related offenses are U.S. citizens or permanent residents.  These individuals were mainly radicalized in America through terrorist groups’ adept use of the Internet and social media. Terrorist groups create online communities and propaganda that exploit and legitimize the grievances of isolated or angry individuals with radical leanings and push them towards full-fledged radicalization. Many of these individuals are searching for a purpose or for a way to avenge what they see as discrimination against or attacks on their community, religion, or homeland.  Terrorist groups are therefore quick to offer belonging, purpose, status, recognition, and a chance for revenge to those who join their ranks. 9

The majority of people charged in the U.S. for ISIS-related offenses are U.S. citizens or permanent residents.

Before the Internet age, terrorist groups used recruiters who physically travelled to find individuals sympathetic to their cause. However, they are now able to recruit and radicalize online through widespread dissemination of their propaganda and through a plethora of online extremist discussion forums where they target vulnerable individuals in the West. These individuals are mainly first or second-generation Muslims living in non-Muslim majority countries who may feel disconnected from both their cultural and current homelands. 10 The terrorist recruiters push an “us” versus “them” ideology that further isolates these susceptible individuals from their communities, and both the recruiters and other participants in online extremist discussion forums rationalize the use of violence by capitalizing on the grievances these individuals feel against their Western home, often due to experienced discrimination or opposition to U.S. foreign policy in the Middle East. 11

In the past, after becoming radicalized, individuals plotting terror attacks often met in person to plan, which helped law enforcement track their communications and meetings. Some also traveled abroad to receive training in the Middle East, which allowed the intelligence community to follow their movements and connections with foreign terrorist groups. However, the advent of encrypted communication technology, such as Telegram, and prevalent use of social media has enabled terrorists to conduct their communication, planning, and attack training online in mediums largely untraceable by law enforcement. Due to the changes in the threat posed by radical Islamist terrorism and in the process of radicalization, the key venue for identifying radicalized individuals who are planning to strike the U.S. is now online. As the terrorists shift to this platform, so must efforts to prevent terrorist attacks.

PART TWO: 
Clues to Far-Right Extremist Behavior

In addition to radical Islamist terrorism, right-wing terrorism remains a prevalent security threat in the U.S. From 9/11 through 2014, far-right extremists killed over twice as many people in the U.S. as radical Islamist extremists. Right-wing extremism not only poses a threat to civilians, but also to law enforcement as at least 57 officers have been killed in right-wing attacks since 1990. 14 The number of terrorist attacks in the U.S. attributed to right-wing extremism rather than to other ideological motivations has increased from 6% of total attacks in 2010 to 35% in 2016. Incidents in recent years include the Emanuel African Methodist Episcopal Church shooting in Charleston, South Carolina that killed nine people, the Sikh temple attack in Wisconsin that killed six, and the killing of Heather Heyer during the Charlottesville rallies in Virginia. These attacks remind us that the threat of right-wing terrorism remains prevalent and must be taken as seriously as that of radical Islamist terrorism. And just like Islamist radicalization, right-wing radicalization has also moved to the Internet where individuals can become radicalized without attending group meetings or interacting in-person with other right-wing extremists in scenarios that are easier to monitor. Susceptible individuals can access discussion forums and a plethora of material about right-wing beliefs from their bedrooms.

The number of terrorist attacks in the U.S. attributed to right-wing extremism rather than to other ideological motivations has increased from 6% of total attacks in 2010 to 35% in 2016.

Both Keith Luke and Dylann Roof were radicalized online prior to their shooting sprees that targeted ethnic and religious minorities including African Americans and Jews. Widespread use of the Internet and social media means that this threat will persist. 17 One study on right-wing terrorism in America found that “right-wing terror incidents occur consistently because the movements from which they emanate are mature extremist movements with deep-seated roots. The Internet has made it easier for extremists to meet each other (and thus engage in plots), as well as to self-radicalize and become lone wolf offenders.”18 But like potential radical Islamist terrorists, potential right-wing terrorists leave clues about their radicalization and intentions in their online behaviors and discussions. The enhanced role of the Internet in radicalization and attack planning for both right-wing and radical Islamist terrorism emphasizes the necessity for technological innovation to combat these threats. Older methods of detecting and monitoring terrorist threats are no longer sufficient – the people looking to cause harm can be intelligent, cunning, and cautious. As the nature of these threat changes, so must our approach to fighting it. Only the use of threat-targeted technology will enable us to maintain public safety in this digital age.

PART THREE: 
Predicting Mass Casualty Events

In addition to terror attacks, the U.S. has witnessed a recent surge in mass casualty events such as mass shootings and school shootings. From 1966 to 2015, there were 146 mass shootings across 40 states and Washington D.C., resulting in 1,048 deaths. There have been 55 mass shootings since 2007 and 11 in 2017 alone. Statistical evidence shows that the frequency of mass shootings is increasing. Since 2011, the rate of mass shootings in the U.S. has tripled to an average of at least one event every 64 days. Yet, in many cases, the shooters have no connection to their victims or to their target locations that could provide a clue to their intentions. Over 71% of active shooter situations in the U.S. from 2000 to 2013 occurred in publicly accessible spaces including businesses, malls, schools, health care facilities, and houses of worship. 23

Furthermore, victims of U.S. mass shootings are of every age, gender, race, and religion with no clear patterns. 24

This lack of generalized predictive information regarding who may commit these violent acts, where they may do so, and who they may target means that we must find new ways to detect and prevent mass casualty planning behavior. Schools are implementing active shooter safety drills and commercial facilities and organizations have new security measures and training to prepare for these scenarios. However, many of these mass casualty events occur in less than five minutes, meaning that training may not be enough to avoid fatalities. 25 Stopping these attacks before they occur is key to averting mass casualties. Yet, mass shootings can be extremely difficult to predict or prevent due to the individualized nature of each attack, the relative ease of access to firearms in the U.S., and the minimal planning required.

Therefore, we need new technological capabilities that can identify specific indicators of these threats before they actualize. For example, it has come to light since the Parkland school shooting that the shooter had previously posted comments on social media about carrying out a school shooting and that his social media accounts contained pictures of guns, ammunition, and other violent or concerning content. We must deploy technology that senses the Internet for these types of threats and language as these may be readily available clues to a shooter’s intentions prior to an attack. Furthermore, school shooters often conduct extensive research into prior school shootings and often try to emulate components of previous attacks based on this research. Such topical investigations can and should be monitored and correlated with other online behavioral patterns to identify individuals who demonstrate attack-planning behavior and thus pose high-risk threats, distinguished from people conducting general research. This activity can also identify the particular web signatures of users engaging in attack-planning behavior. As a result, only users truly engaging in extreme, outlier behavior will be identified, making threat identification a fact-based process rather than one that could be biased on prior knowledge of a suspect individual. Similarly, this type of sensing can detect threats posed by individuals who may not be on law enforcement’s radar.

As new technologies and weapons are developed and more information becomes accessible online, the potential severity of threats to our country and its citizens increases. We must similarly change the way we approach detecting and preventing these violent threats in order to adequately address the enhanced capabilities and methods of those seeking to do us harm.

Many of these mass casualty events occur in less than five minutes, meaning that training may not be enough to avoid fatalities.

Summary

In today’s world, there are far too many Westminster and Nice vehicular attacks, Orlando shootings, Brussels airport bombings, Las Vegas massacres, Sandy Hook, and Parkland school shootings that occupy our news cycle and the front of our minds. The individuals who carry out these devastating and heinous acts seek to undermine our way of life, our sense of security, our freedoms, and our belief in our government. They also become increasingly hard to detect as they are radicalized through social media and carry out attack planning in online forums or encrypted apps where they are not easily identified or monitored. The UK Home Office found that in 2017, ISIS followers published propaganda on 400 different platforms, including 145 new ones between July and December alone. 27These terrorists and other violent actors must be met head on by the best possible tactics and tools to detect and prevent such threats before they are carried out. Indeed, both the public and private sectors are embracing the power of technology in this realm, particularly related to artificial intelligence and machine learning. At Lumina Analytics, we’re using these tools to understand threat-specific behavioral patterns and predicatively identify threats to society and national security, as well as to private corporations, venues, and events.

Mission LISA Announces Recommendations to Address Federal Funding Disparities in the Opioid Crisis


Analysis of Major Opioid Grants Shows More Populous States Get More Funding Per Victim, Leaving Smaller, More Impacted States Underfunded

TAMPA, Fla., April 30, 2019 /PRNewswire/ — State allocations of federal opioid grants are biased toward more populous states according to an analysis conducted by Mission LISA (Learning Indicators of Substance Addiction).  Disparities are based on current funding formulas which only address the absolute number of people affected.  To better fund the states most impacted by the crisis – regardless of size – Mission LISA recommends changing funding formulas to account for epidemic severity relative to state population.

“As a guidance to crisis mitigation efforts, Mission LISA recommends federal agencies optimize current opioid funding formulas by incorporating state prevalence as a significant factor,” said Vicky Liao, Director of Mission LISA.  “Smaller states are bearing the brunt of this crisis, and this updated formula would provide them the funds they need for prevention, treatment and intervention.”

She added that as a result of the analysis, Mission LISA developed an optimal formula for determining funding for states which incorporates both absolute numbers of victims as well as state prevalence.

Mission LISA reviewed major opioid grants, including grants from the Substance Abuse and Mental Health Services Administration (SAMHSA), the Health Resources and Services Administration, and the Department of Justice, comparing 2018 state-level funding distribution with the 2017 state ranking by prevalence of opioid misuse.  Results show some highly impacted states were underfunded and received funding that is disproportional to the epidemic prevalence in those states:

Delaware, Maine, New Hampshire, Maryland, and West Virginia.

Incorporating prevalence into the determination of funding for SAMHSA’s State Targeted Response grant would result in an addition of approximately $108 million to at least 37 states and the District of Columbia.  The top five jurisdictions to receive more funding are:

Maine, the District of Columbia, Delaware, New Hampshire, and West Virginia.

About Mission LISA: 
Mission LISA is a data aggregation initiative surrounding America’s national opioid crisis. Using deep web mining and machine learning technology, Lumina Analytics is collecting, synthesizing, and analyzing massive amounts of publicly available data to provide policymakers and healthcare service providers with timely and relevant intelligence surrounding the current state of the crisis and how best to combat nationwide overdose death and addiction. This data drives production of evidence-based policy recommendations and patient-centric treatment pathways, yielding highly targeted solutions for the epidemic.

Mission LISA was launched by Lumina Analytics in 2017 to address the need for more robust and timely data surrounding the opioid crisis in America. Visit www.LuminaAnalytics.com to learn more about Mission LISA technology and data analysis. Follow Mission LISA on LinkedIn and Twitter for relevant intelligence and policy updates.

About the Mission LISA Foundation:  
The Mission LISA Foundation conducts educational meetings, prepares and distributes educational materials, and considers public policy issues in an educational manner, presenting materials and information on a non-biased, non-partisan basis for wholly educational purposes regarding the nation’s opioid epidemic. LISA is an acronym for Learning Indicators of Substance Addiction. Mission LISA Foundation’s Advisory Board is comprised of expert physicians, researchers, academics, policy veterans, and industry professionals.