Agile In-Memory Software Can Track the Dynamic Rollout of Vaccine Distribution and Delivery to Quickly Spot Problems

Getting the COVID-19 crisis under control requires that we put in place an effective process for vaccine distribution so that the country can get to herd immunity as fast as possible. We are faced with quickly building a nationwide logistics network and standing up well more than 50,000 vaccination centers. Making all this work smoothly means that managers need accurate, up-to-the-minute information about all aspects of this operation, including:

• Where are all the vaccine shipments right now?
• What is the shortfall in vaccines at each center?
• How many people are waiting for vaccines at each center?
• How many qualified personnel are available at each center?
• Which centers have the most urgent needs and need immediate attention?
• Is vaccine distribution underserving certain regions or population groups?

Given the unique and highly dynamic nature of this challenge, we need software solutions that are agile enough to adapt to evolving needs and scalable enough to quickly handle a daunting amount of fast-changing data. Conventional, enterprise data architectures take months to develop and are complex to change. Is there a simpler, faster way to wrangle this data for crisis managers?

In-Memory Computing with Real Time Digital Twins: Fast and Agile

A software technology called in-memory computing has evolved over the last twenty years to grapple with the challenge of tracking and analyzing fast-changing data. Its two core competencies are speed and scalability. Widely used to track ecommerce shopping carts, financial transactions, airline flights and much more, in-memory computing can quickly store, retrieve, and analyze large volumes of live data. This powerful technology may also be just what we need to help tackle the challenge of vaccine distribution.

In the last two years, the concept of real-time digital twins has emerged to let in-memory computing track incoming data streams from hundreds of thousands of data sources, maintain pertinent information about each data source, and immediately alert when unusual conditions are detected. The power of this approach lies in its ability to simplify the problem for application developers. It encapsulates code that just focuses on analyzing messages from a single data source as they flow in, and it maintains an up-to-the second assessment of the data source’s status. Real-time digital twins are both easy to develop and easy to change as needs evolve. The in-memory computing system which hosts them typically runs as a cloud service (such as the ScaleOut Digital Twin Streaming Service) that transparently scales to handle as many data sources as needed.

Real-Time Digital Twins Can Help Expedite Vaccine Distribution

To track the distribution and delivery of COVID-19 vaccines, a real-time digital twin can be deployed for each shipment in transit and for each vaccination center. For shipments, the digital twins can track location, destination, and current condition on a second-by-second basis, allowing managers to instantly know where a shipment is and whether its viability is at risk, for example, due to a temperature change. For vaccination centers, real-time digital twins can track location, the supply of vaccines, current demand (number of recipients), availability of trained personnel to perform injections, and other parameters. Code in the digital twin continuously analyzes incoming messages to determine whether a problem exists or is likely to occur, and it alerts managers to urgent issues within a few milliseconds. This allows managers to keep track of which of the 50,000 centers need immediate assistance.

The following diagram illustrates the use of real-time digital twins to track thousands of vaccine shipments and vaccination centers. The red dotted lines depict message streams flowing from data sources located throughout the country over the Internet to their corresponding real-time digital twins hosted in the cloud service.

Let’s take a closer look at the real-time digital twin for a vaccination center. Using a simple web app, personnel at the vaccination center send periodic messages updating information about supplies, personnel, recipients, and wait times. The real time digital twin for this center records this data and then analyzes it for issues, such as a shortfall in supplies, lack of available personnel, or a surge in incoming recipients. It can then compute an assessment of the urgency for assistance (call it an alert level) which can be compared to other centers to identify which ones have the most urgent issues. If the alert level becomes sufficiently high, the analysis code can immediately notify managers. By analyzing incoming messages, real-time digital twins keep track of the latest status for all vaccination centers.

Here’s an illustration of a vaccination center sending messages to its real-time digital twin running in the cloud. It shows some of the state information that the twin maintains and the code which analyzes incoming messages as they arrive:

Aggregate Analytics Boost Situational Awareness

When dealing with thousands of dynamic data sources, managers can use real-time digital twins to serve as highly responsive watchdogs that continuously evaluate incoming information for changes that may need attention. This helps managers easily track thousands of data sources and focus on the most pressing concerns.

To further boost situational awareness, the in-memory computing platform can group and aggregate data held in the real-time digital twins every few seconds to help surface widespread changes that need strategic responses. For example, the average shortfall in vaccine doses for all centers in each region of the country can be aggregated to track where shortfalls may be occurring. This information can be visualized as shown in the chart below, which is updated every few seconds to provide managers with the most current view of the situation:

Likewise, this technique can be used to aggregate the average wait times for all vaccination centers by county. This can help determine where bottlenecks in vaccine delivery are occurring and enable mangers to render assistance by relocating personnel from less busy centers to overwhelmed ones.

Aggregate analytics of data maintained by real-time digital twins can also be used to track and validate the equitable distribution of vaccines. For example, it can aggregate information collected from each center about the demographics of vaccine recipients, such as age and ethnicity, and characteristics of the centers themselves, such as hospitals vs pharmacies and urban vs rural. This allows key real-time statistics to be tracked, such whether certain groups or regions are being underserved and whether hospitals have shorter wait times than pharmacies.

Summing Up

Without a doubt, distributing and delivering COVID-19 vaccines quickly and effectively over the next few months presents formidable challenges, namely:

• Ensuring that logistics managers get the critical information they need in a timely manner
• Avoiding the complexity and delay required to build custom information management systems that can provide this information

Because it is fast, scalable, and agile, in-memory computing technology with real-time digital twins can serve as a valuable tool for tracking the status of many thousands of vaccination centers and shipments. This innovative software infrastructure can quickly be programmed to analyze vital parameters and statistics in milliseconds and aggregate key data every few seconds. It offers managers a powerful and flexible means for helping ensure fast, efficient vaccine distribution and delivery.

The post Real-Time Digital Twins Can Help Expedite Vaccine Distribution appeared first on ScaleOut Software.