Monkey Pox: What We Know So Far and Ways to Prevent Transmission

In the recent news, there have been talks about the monkeypox cases in Europe and now the United States. President Biden called it something “to be concerned about” and is being very closely monitored here and internationally. Monkeypox was first identified in 1970 in the Democratic Republic of the Congo and has since expanded over the last 10 years to many other African nations. Despite the name, monkeys, like humans, are accidental hosts. The wild animal reservoir remains unknown.

Here is some current information on the situation and monkeypox in general.

From the CDC About Monkeypox | Monkeypox | Poxvirus | CDC as of today:

  • A patient was confirmed in Massachusetts to be infected with a West African strain after returning to the US from Canada, they are currently being isolated and poses no risk to the public. See 2022 United States Monkeypox Case | Monkeypox | Poxvirus | CDC for more information.
  • Monkeypox is a rare viral disease. The virus belongs to the same family and genus as variola virus (causing smallpox), vaccinia virus (used in the smallpox vaccine), and cowpox. The rash is indistinguishable from smallpox.
  • CDC is also tracking multiple clusters of monkeypox cases reported in several countries that don’t normally report monkeypox, including in Europe and North America.
  • The rash associated with monkeypox involves vesicles or pustules that are deep-seated, firm or hard, well-circumscribed, and grow synchronously (all lesions at the same stage as the disease progresses, as opposed to chickenpox); the lesions may umbilicate or become confluent and progress over time to scabs.
  • Presenting symptoms typically include fever, chills, a distinctive rash, or new lymphadenopathy (swollen lymph nodes).
  • The rash associated with monkeypox can be confused with other diseases that are encountered in clinical practice (e.g., secondary syphilis, herpes, chancroid, and varicella-zoster).
  • The illness typically lasts for 2−4 weeks. Although rare, in Africa, monkeypox has been shown to cause death in as many as 1 in 10 persons who contract the disease.
  • Based on the limited information available at this time, the risk to the public appears low.

Transmission

  • Transmission of monkeypox virus occurs when a person comes into contact with the virus from an animal, human, or materials contaminated with the virus. The virus enters the body through broken skin (even if not visible), respiratory tract, or mucous membranes (eyes, nose, or mouth).
  • Human-to-human transmission is thought to occur primarily through large respiratory droplets. Respiratory droplets generally cannot travel more than a few feet, so prolonged face-to-face contact is required.
  • Other human-to-human methods of transmission include direct contact with body fluids or lesion material, and indirect contact with lesion material, such as through contaminated clothing or linens.
  • The secondary attack rate is estimated 10% in contacts unvaccinated against smallpox.

Prevention

  • The vaccine JYNNEOSTM (also known as Imvamune or Imvanex) has been approved by the U.S. Food and Drug Administration for the prevention of monkeypox. The Advisory Committee on Immunization Practices (ACIP) is currently evaluating JYNNEOSTM for the protection of people at risk of occupational exposure to other orthopoxviruses such as smallpox and monkeypox in a pre-event setting.
  • Smallpox (vaccinia) and monkeypox vaccines are effective at protecting people against monkeypox when given before exposure to monkeypox. Experts also believe that vaccination after a monkeypox exposure may help prevent the disease or make it less severe. In addition to smallpox vaccine, vaccinia immune globulin and some limited use medications are available for monkeypox outbreak control.
  • Routine vaccination of the American public against smallpox stopped in 1972 after the disease was eradicated in the United States and is no longer available to the public. Those of us that are old enough have a faded but unique vaccination scar on their left upper arm.

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About the Author

Dr. Joe Mignogna is Acuity’s Chief Medical Officer.  Connect with him at jmignogna@acuityinternational.com

Dr. Joe Mignogna, MD, MPH, CIME, FACOEM, Chief Medical Officer

Wellness Programs: Using Healthcare Analytics to Support Employee Health

Most well-designed corporate wellness programs are successful, but we’ve all seen well-intended short-lived efforts come and go over the years. The challenge is defining “well-designed” and “successful.” This third edition will focus on practical considerations for using employee healthcare analytics in your business setting to support employee health and wellness. But first, a brief background on employer-based wellness programs.

A thriving “culture of health” at any organization relies on many factors, from leadership support at all levels to shared corporate values, to formal and informal systems reinforcing healthy behaviors, to accurate, reliable, and reproducible tools to measure all aspects of the culture of health.

It’s been well-documented that custom-designed wellness products can support corporate performance, both in dollars and human capital. Examples of highly developed wellness models include the ACOEM Corporate Health Achievement Award or CHAA, HERO Employee Health and Well-Being Best Practices Scorecard, Health Risk Assessments, The Health Project C. Everett Koop National Health Awards, and health & wellness “contracts” using The Transtheoretical Model (Stages of Change) model.

Studies have shown a link between stock market price growth, financial performance, and having a great employee health program (CHAA, Koop Award). Employers attesting to comprehensive wellness programs outperformed the S&P index at rates ranging from 7-16 percentage points per year, representing a nearly doubling or tripling of earnings.

  • Stock performance is tied to companies with high ratings for corporate social responsibility, employee job satisfaction, spending on human resources and acknowledged as a best place to work
  • Stock values for a portfolio of companies that received high corporate health & wellness scores appreciated by 235% compared to the S&P Index of 159% over a six-year period
  • Investing in funds to develop a great wellness program will not make stock prices go down
  • Great wellness programs may be reliable indicators of future stock performance
  • Investing in funds to create a great wellness program will not make stock prices go down
  • Great wellness programs may be reliable indicators of future stock performance
  • A 2018 UK study by Glassdoor of over 35,000 reviews across 164 employers found those with more satisfied employees returned ~16% more than those with less satisfied employees
  • Koop Award companies outperformed the S&P Index over a 14-year period (2000-2014)

It’s also important to understand the practical concepts regarding CDC: Clinical Prevention Models. Most corporate wellness programs focus on primary and secondary prevention.

  • Primary prevention aims to prevent disease or injury before it ever occurs.
  • Secondary prevention focuses on early diagnosis to prompt timely interventions to prevent or minimize morbidity, reduced productivity and additional costs.
  • Tertiary prevention addresses effective interventions and employee disposition once disease or impairment is evident.

Most cookie-cutter wellness programs, despite great intentions, are often doomed to failure. You can create customized, focused programs that “learn” as they grow using well-designed analytics tools to harness your unique populations’ health data. Tap into those databases we discussed in an earlier blog, such as indemnity and workers’ compensation claims, demographics, HRAs and employee surveys to customize your wellness programs for maximal impacts on your bottom line and employee health, well-being, retention and productivity.

Stay tuned for further predictive healthcare analytics blogs covering a variety of other common and important business topics.

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About the Author:

Dr. Joe Mignogna is Acuity’s Chief Medical Officer.  Connect with him at jmignogna@acuityinternational.com

Dr. Joe Mignogna, MD, MPH, CIME, FACOEM, Chief Medical Officer

Predictive Health Analytics in the Workplace

Knowledge is Power, Power provides Information; Information leads to Education, Education breeds Wisdom; Wisdom is Liberation.”Israelmore Ayivor

Tackling health analytics in the workplace can appear daunting and intimidating. It can be difficult to know where to start, what resources are needed, and what the time commitment will be – not to mention balancing the initiative with other business needs.

Most organizations have a vast number of health data sources coming from different directions and in a variety of formats. It’s important to take it one step at a time, following a step-by-step approach to identify, collect, and analyze data:

  1. Identify your data streams and ensure access
  2. Determine how you will collect and store the data
  3. Develop and implement processes and technologies to analyze the data

Remember, the goal is to provide a valid and “living” real-world picture of your Population at Risk (PAR) at any point in time and as it trends over time. Some of the data may seem obvious and intuitive, but additional context and data can reveal a more holistic profile of your PAR. Keep in mind the importance of privacy and confidentiality while handling employee personally identifiable information (PII) and protected health information (PHI), and consider anonymizing and/or aggregating data whenever practical.

Here are some data points and data sources to consider when collecting healthcare data analytics for your organization:

  1. Employee demographics
    1. Can include but are not limited to age, gender, ethnicity, home of record zip code, and education level.
  2. Employee attributes related to Business Continuity Planning (BCP) or Continuation of Operations:
    1. For example, dependents living at home, a working spouse or partner, access to transportation during inclement weather or natural disasters (some of these attributes also covered under #12 social determinants of health), home location (risk of bridge or highway closures, areas prone to flooding, reliable utilities, etc.), availability of a secure home workstation to work remotely, and access to a mobile phone.
  3. Employment
    1. Can include years of service to the company, job category, location or department, salary quartile, performance rating, as well as professional certifications, experience, and interests.
  4. Healthcare
    1. Personal healthcare indemnity claims, which provide an exemption from incurred penalties or liabilities, bundled into a limited number of manageable diagnostic codes or categories.
  5. Workers’ compensation
    1. Similar profile to personal indemnity claims; include time out of work, costs, healthcare provider attributes (name, access, responsiveness, patient satisfaction, quality of care (best practices and published guidelines), and location.
  6. Medical leave
    1. Frequency and duration of leave, restricted duty, and accommodations.
  7. Drug testing data
    1. If relevant, can include pre-employment, random, or other reasons to test.
  8. Healthcare benefits utilization beyond claims data
    1. Can include Employee Assistance Programs (EAPs), wellness and prevention programs (i.e. smoking cessation), fitness club membership, weight loss, or exercise groups.
  9. Health Risk Appraisals (HRA)
    1. Lifestyle factors such as tobacco use, exercise, alcohol intake, diet, seatbelts, and sleep hygiene. HRA data can also examine mental health, work-life balance, biometrics, and personal & family medical history.
  10. Employee and manager surveys
    1. Examples include job satisfaction, suggestions, challenges, or complaints.
  11. Human resources data
    1. Including but not limited to recruiting, retention, and turnover.
  12. Social Determinants of Health (SDOH)
    1. A relatively new area of research, SDOH focuses on conditions in which people are born, grow, live, play, and age – connecting which factors are shown to lead to health disparities and inequality, many impacting work productivity. Examples include economic stability, access to healthcare and transportation, community and environment, education, family dynamics, social networks, safe and affordable housing, and access to healthy food.

The data collection and analysis phases generally require some investment into applicable technologies and informatics expertise. Many of your data streams and databases will require “translators” and interfaces to facilitate transforming the data into a common operational format for ongoing collection and eventual analysis.

Once you’ve collected your data and identified similarities, differences, and patterns, you can query that data to create a valuable information resource for your organization. Stay tuned for a blog on best practices for making the most of your healthcare data analytics.


About the author:
Dr. Joe Mignogna is Acuity’s Chief Medical Officer.  Connect with him at jmignogna@acuityinternational.com

Dr. Joe Mignogna, MD, MPH, CIME, FACOEM, Chief Medical Officer

How Predictive Analytics is Reshaping Workplace Health, Wellness, and Safety Planning

Predictive analytics is the practice of extracting insights from data and using that information to predict trends, patterns, and inform future outcomes. As consumers, we encounter predictive analytics in many aspects of our lives. It influences from what we purchase on Amazon to what we watch on Netflix.

But predictive analytics can also enhance employee health and wellness, and support business continuity. With the right tools and data, forward-thinking employers can yield valuable insights about improving the work environment, controlling absenteeism and presenteeism, retaining valued employees, and reducing workforce-related costs and risks.

Indeed, turning data about populations at risk (PAR) into an action plan for the business is a strategic opportunity that organizations can’t ignore. After all, if you don’t know where you are going, you might wind up someplace else.

Yield insights into populations at risk

A growing use case for predictive analytics in the workplace is employee health and wellness. Frequent workplace injuries or health issues have direct financial costs, including lost time, insurance premium hikes, workers’ compensation payments, and even litigation. Absenteeism due to illness is also costly, and presenteeism (working while sick) impacts both productivity and safety. Studies show that out of every dollar spent on health care benefits, $0.61 is spent on illness and injury-related absences and reduced work output.

At Acuity, we help organizations overcome these challenges. Using predictive health analytics and anonymized data – including demographics, job titles, worksites, claims data (workers’ compensation and indemnity), employee surveys, and turnover – we provide employers with valuable real-world insights about their populations at risk, such as those with health conditions or propensity for injury, and help them find patterns in this data to inform decision making.

In one engagement, I worked with a client to identify the health issues that were costly to the organization and had the most impact on absenteeism. The client assumed that cancer and heart disease were the most detrimental to productivity and had prioritized awareness around these conditions. But when we studied the data, it transpired that absent employees were largely predisposed to OB/GYN and skin problems – prompting a data-driven shift in the client’s wellness strategy to include family planning and skin cancer screening.

Understanding social determinants of health and productivity

Employee productivity, absenteeism, and presenteeism are also subject to societal challenges. We can know an employee’s demographics, health status, and where they spend their healthcare dollars, but what about other factors? For example, Employee A may neglect his health because he is busy caring for his elderly parents. Employee B shares one car with his working spouse, requiring long commutes using limited public transportation. While Employee C is a single parent who skips work on occasion to be present for her children.

With secondary, anonymized societal data sets, employers can more accurately identify the driving factors of lost workplace productivity and get answers to critical questions such as:

  • What factors keep their employees out of work?
  • Which employees are at risk?
  • What programs can be implemented to produce the best outcomes (flexible work arrangements, childcare programs, access to healthcare, dependent care assistance programs, etc.)?

 

Eliminate the guesswork and better manage employee risk

Another beneficial outcome of predictive analytics is that it helps businesses prepare for unforeseen circumstances and disasters that may impact workplace productivity.

For example, organizations can predict whose commute may be impacted by extreme weather by analyzing employee attributes such as home address and vehicle type. If a snowstorm hits, employers can quickly determine who can make it to work safely based on their location and access to a four-wheel-drive vehicle and who will be absent that day. This is especially important to employers who must ensure business continuity, such as federal agencies, law enforcement, critical infrastructure providers, and transportation operators.

Leveraging prediction to ensure successful outcomes

Companies have spent years trying to implement programs to address workplace health and safety. Yet these interventions are often generic or broad and not aligned with employee needs.

But by analyzing historical and demographic data, employers in any workplace – from the typical office to field operations teams – can model their workforce at an incredibly granular level. As a result, they can identify the driving factors of workplace incidents and absenteeism, develop targeted prevention strategies, and make informed decisions about procedures and policies to promote business continuity.

While predictive analytics can be challenging (due to large volumes of data from diverse sources, much of which must be anonymized and handled in confidence), predictive analytics ensures workplace leaders can make the most of available data and continuously improve operations and their bottom line.


About the author:
Dr. Joe Mignogna is Acuity’s Chief Medical Officer.  Connect with him at jmignogna@acuityinternational.com

Dr. Joe Mignogna, MD, MPH, CIME, FACOEM, Chief Medical Officer

U.S. Department of Homeland Security appoints Acuity’s Chief Medical Officer to National Merchant Mariner Medical Advisory Committee

Acuity’s Chief Medical Officer, Dr. Joe Mignogna, was recently appointed to a three-year term on the National Merchant Mariner Medical Advisory Committee by the U.S. Department of Homeland Security’s Acting Secretary.

The National Merchant Mariner Medical Advisory Committee is comprised of nine healthcare professional members and five professional mariners. Together they advise the Secretary of Homeland Security on matters relating to medical certification determinations for the issuance of licenses, certification of registry, and merchant mariners’ documents such as medical standards and guidelines, medical examiner education, and medical research. Dr. Joe has served on the committee continuously since 2014, contributing to and leading several task statements, and authoring an article for the U.S. Coast Guard Proceedings magazine devoted to mariner health and wellness.

“It’s really been a pleasure and a professionally rewarding experience working with Coast Guard leadership and the committee’s team of dedicated maritime professionals representing Acuity,” Dr. Mignogna said.

Congratulations Dr. Mignogna on this important recognition.

“As we work toward growing into Acuity this fall, the company is planning further corporate social responsibility initiatives to make real differences globally,” Stalick said. “We welcome partnering with other companies that align with our values of service in the areas of global missions, advanced technology and advanced medical.”