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How analytics can improve vaccine distribution and administration

March 2, 2021

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The management of the COVID-19 vaccination program is one of the most complex tasks in modern history.  Even without the added complications of administering the vaccine during a pandemic, the race to vaccinate the populations who need it most all while maintaining the necessary cold-storage protocols, meeting double dose requirements, and still convincing populations of the vaccine safety, is daunting.

The vaccines available today are unlikely to be available in sufficient quantities to vaccinate the entire population in the near term, which creates the need for nimble, data-driven strategies to optimize limited supplies.

Analytics can be used to:

Identify the location and concentration of priority populations.

Monitor the relative adequacy of providers capable of vaccinating critical populations.

Measure changes in need and demand patterns to optimize supply-chain strategies.

Track community-based transmission and efficacy.

The storage and transportation of the vaccine is a complex logistical exercise, requiring coordination among governments and providers and the safe transport and storage of vaccines from manufacturers to vaccination sites.

Develop immediate and long-term vaccination strategies

Governments have struggled to balance the need to create an orderly, risk-driven prioritization strategy while quickly administering all of the doses they have been allocated. Integrating data to calculate the size of prioritized populations in given geographic areas enables a data-driven vaccine allocation strategy that maximizes throughput and minimizes wasted dosages. Locating and estimating the size of these populations will be critical to developing an effective allocation strategy. This complex task can be fraught with technical challenges; for instance, creating an analytically valid estimation that identifies targeted populations across data sources.

To succeed, governments and health agencies will need to integrate data to identify critical populations, enable populations to be further subset to accommodate unknowns in vaccine supply, and model vaccination impact on priority outcomes. Given the variety of public and private organizations collaborating on this response, the best solution will drive open, transparent communication across diverse agencies.

Visual analytics is paramount because showing priority population data on maps can also speed strategy development. Using proximity clustering and hot-spotting technology, leaders can identify population densities to ensure adequate vaccine supply. Epidemiological models can help ensure continued situational awareness, so that prioritization and allocation approaches don’t become reliant on point-in-time data, but are instead part of a continuous-learning system that is responsive to on-the-ground changes in the pandemic.

Optimize supply chain strategies

Health and human service agencies are being asked to allocate vaccine supply based on a range of complex, interrelated factors that include populations served and providers’ capability for storing and refrigeration. Optimizing these distribution strategies while facing fluctuating supplies, evolving need and changing provider enrollments will require a strong data and analytic approach.

By capturing inventory, demand, capacity and other related data across the distribution chain, one can create models that determine how agencies can optimize allocation strategies while accounting for the dynamic nature of pandemic outbreaks. The outcome is a set of flexible, adaptable plans for vaccination processing, inventory monitoring and distribution.

Dose administration analytics

Vaccination administrators must report certain data elements in near-real time (through electronic health records or directly via state immunization information systems). This information is a critical tool in creating rapid-response analytics that can guide decision making and future planning. Unfortunately, long-term underinvestment in public health IT infrastructure has led to significant data quality challenges and weak reporting capabilities, which collectively prevent a data-driven vaccination strategy.

Managing a cold chain for biologics

In the US, the CDC has updated the Vaccine Storage and Handling Toolkit to outline the proper conditions for maintaining an effective COVID-19 vaccine under cold-chain processes. Cold chain is a logistics management process for products that require specific refrigerated temperatures from the point of manufacturing through distribution and storage until the vaccine is administered. But how do you collect data along the chain to ensure product safety? New internet-connected sensors now travel along with the vaccines. Collecting and analyzing that data allows administrators to monitor, track and optimize distribution strategies in this multi-layered and complex vaccine rollout.

Source: SAS

 


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