Globally, over 30 million doses of the COVID-19 vaccination have been dispensed throughout 43 countries. In the U.S., over nine million people have had at least one COVID-19 vaccination as of January 12, 2021, with 541,000 people completely vaccinated.
As the global COVID-19 rollout continues to unfold, the challenge of vaccine administration has become a large-scale humanitarian effort, merging private and public sectors. Protecting vulnerable communities is a critical factor in the fight to immunize the world’s population against COVID-19 and help curb the pandemic.
New solutions are arising that leverage data science, analytics, and other emerging technologies to identify and prioritize populations who need the vaccine based on specific criteria, like risk exposure. They can also combat the pervasive data, IT, and infrastructure challenges that can inevitably lead to distribution and allocation issues like shortages and equitable vaccine administration.
The Vaccine Administration Challenge
Critical populations, such as front-line healthcare workers, nursing home residents, and other high-risk demographics are being immunized before others who will become eligible for vaccination in the coming months.
In fact, a partnership has emerged between the World Economic Forum Supply Chain and Transport Industry Team and McKinsey & Co. to identify priority populations and the important elements that will contribute to a more seamless vaccination administration process.
But data and IT challenges present obstacles to successful vaccine administration rollouts. Reaching herd immunity in the U.S. (60 percent to 70 percent of the population vaccinated), depends on identifying, prioritizing, and monitoring the distribution.
The challenges of managing patient and consumer data to order, ship, and track medical supplies are even more complex due to the relative lack of integration across local, state, and federal government entities — and vaccine providers.
Covid-19 vaccine registries and other databases must maintain accurate, current information to prevent data challenges surrounding:
- Monitoring vaccinated individuals and what vaccine they received
- Ensuring first and second vaccine doses are from the same company
- Notifying individuals when they’re due for a second dose
- Monitoring vaccination efficacy and side effects
Compliance, Regulations, and Security
Other formidable risks and data challenges to contend with, like the potential for counterfeits and deviations, will require strong analytics-based solutions such as predictive modeling and blockchain technology.
Fines and regulatory mandates are another concern. The NY Department of Health, for example, is enforcing “Use it or Lose It” regulations that revoke hospital access to additional vaccine doses if they fail to administer their existing supply within seven days to priority populations, in addition to facing a potential $100,000 fine.
Other potential issues are medical identity theft, such as the possible risk that fake or stolen identities may be utilized so that people can attempt to get a vaccination earlier than they are otherwise eligible to receive. Conversely, false vaccination records are another potential risk factor to contend with for those people who are disinclined or unwilling to be vaccinated.
These possible risks underline the value of data and analytics in accounting for and addressing security concerns as national and global rollouts continue. Ironclad security protocols are necessary to mitigate information theft, to help maintain federal and state regulatory compliance, and clearly outline how personal data is managed.
New Solutions Emerge
A number of U.S. hospitals and health systems are using analytics and artificial intelligence (AI) algorithms to help determine who should receive initial COVID-19 vaccinations according to factors like exposure risk, age, existing medical conditions, and job role.
Other analytics-driven solutions are continuously emerging for a variety of vaccine administration concerns:
- Identifying Vaccine Safety Concerns: A new machine learning software screens doctor and patient reports, automatically finding patterns that may indicate safety problems and flagging it for further exploration.
- Patient Population Impact: MIT research used ML and AI tools to examine the effectiveness of a vaccine similar to the COVID-19 vaccine in different populations, with findings indicating potential ineffectiveness in certain racial minorities.
- Accelerating Vaccination Rates: Cloud-based mixed integer linear programming optimization solutions aim to increase vaccination rates, simulate demand/supply fluctuations, and help support decision making about site locations for vaccination administration.
- Identifying High Risk Patients: A predictive analytics based model helps identify people with particular vulnerability to COVID-19 complications in order to aid in care management, outreach, and prioritization.
Paving the Way for Innovation and New Solutions
Vaccine administration must be safe, accountable, ethical, and effective. Data science and analytics are particularly well suited for this challenge, playing a vital role as innovative frameworks and solutions materialize to ensure the well-being of communities and critical populations.
Check out Part 1 of this series here, where we explore supply chain and logistic challenges in vaccine distribution and the role of data science. Be sure to visit Simplilearn to discover educational and career path resources in data science and advanced analytics.