vaccination Depositphotos 6866297 s 2019 e1621964872628

As we continue the COVID-19 vaccination effort across the globe and plan for future pandemics, we need to ensure that advanced technologies for streaming analytics are incorporated into the management of the distribution network.

The United Kingdom, Bahrain, Canada, Mexico, and the United States became some of the first countries to approve the authorization and distribution of vaccinations to combat the COVID-19 pandemic in December of 2020. Soon after, leaders were tasked with the immense challenge of quickly building a global and nationwide logistics network and standing up millions of vaccination locations. The use of in-memory computing with real-time digital twins brought some needed help.

Vaccination rollout operations did not go without missteps that slowed down the life-saving effort. For example, in the U.S., there were 20 million missing COVID-19 vaccine doses, reports of thousands of unused doses, canceled vaccinations due to shortages, and a series of other issues. Additionally, while the U.K. was the first in the world to approve a vaccine for distribution, its efforts were stalled in March of 2021 due to major shortages in supply.

Tracking’s role is critical

Now it’s
clear that global governments and leaders need more effective and timely tracking
of vaccine distribution and delivery to complete this effort, roll out COVID-19
variant boosters, and prepare for future pandemics. Ensuring that vaccine
distribution and delivery run smoothly requires analyzing large quantities of
real-time information about all aspects of the distribution network and then
quickly responding to emerging issues. This information is consumed by
governments, health organizations, and the private sector, all working together
to implement vaccine distribution. Here are some key questions that this
real-time information can answer:

  • Where
    are all the vaccine shipments right now in North America?
  • Where
    is the largest shortfall of vaccines, and which specific vaccination centers
    have the most pressing needs?
  • How
    many qualified medical personnel are available at each center, and which
    centers need additional personnel to handle current workloads?
  • Which
    centers have the highest wait times and have neighboring centers with extra
    capacity to which people could be redirected?
  • Is
    vaccine distribution underserving certain population groups and in need of

the unique and highly dynamic nature of this challenge, vaccine distribution
teams need real-time information processing technologies that can continuously digest
incoming messages from millions of data sources: vaccination centers,
warehouses, fleet vehicles, and other locations in the distribution network. These
technologies need to be able to create a dynamic, comprehensive picture of the
distribution system and continuously highlight the highest priority issues so
that management personnel can maintain situational awareness and respond to
critical challenges.

The role of a real-time digital twin

it can track, analyze, and aggregate large volumes of fast-changing data in
real-time, in-memory computing technology is well suited to meeting these
requirements. Its capabilities can give leaders a complete visual picture of
how a logistics network for vaccine distribution is performing. By creating a
software component called a “real-time digital twin” for each reporting source
within the distribution network, in-memory computing software can process
incoming messages within milliseconds and maintain key information about the
current state of each source. It can then aggregate this information and, within
seconds, visualize the results in charts, tables, and maps.

a real-time digital twin for a vaccination center, which holds dynamic
information about the status of the center that is updated as messages are
received from personnel. For example, it can track the real-time
supply of vaccines, current demand (number of waiting recipients), the number
of people vaccinated the availability of trained personnel to perform
injections, and much more. It also can hold relevant background information,
such as the center’s location, capacity, and nearby medical facilities. As it
receives periodic messages from personnel, the real-time digital twin immediately
updates the center’s status, analyzes evolving conditions, and looks for
problems (such as an impending shortfall in vaccines).

The in-memory computing system continuously aggregates status information and priorities for managers, enabling them to visualize in seconds where problems are emerging and where action needs to be taken. For example, using continuous queries of real-time digital twins, it can show on a map which vaccination centers have the largest predicted vaccine shortfalls in the next hour based on trends that have been developing throughout the day. Personnel can then direct supplies to these centers to avoid turning away recipients.

The power of real-time digital twins also lies in their ability to
simplify application development. By allowing application developers to focus
only on the algorithms and state information needed to process incoming
messages, code is both easy to write and easy to change as needs evolve. The
in-memory computing system handles the details of data orchestration, message
processing, aggregation of results, and visualization. It typically runs as a
cloud service that can transparently scale to handle millions of data sources.

As we continue the COVID-19 vaccination effort across the globe
and plan for future pandemics, we need to ensure that advanced technologies for
streaming analytics are incorporated into the management of the distribution
network. Inefficiencies in distribution can translate into thousands of lives
lost and a lengthy economic recovery. In-memory computing with real-time
digital twins offers an important new tool for tracking vaccine distribution
and quickly surfacing problems so that personnel can quickly address them. This
technology can play a key role both now and when the next pandemic inevitably

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