How analytics can improve COVID-19 vaccine distribution and administration
Governments can use analytics to identify the location and concentration of priority populations, optimise supply chain strategies and track transmission, among many other things
The management of the COVID-19 vaccination programme is one of the most complex tasks in modern history. Alongside the 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 convincing populations of the vaccine safety – is daunting.
The vaccines available today are unlikely to be accessible in sufficient quantities to vaccinate the entire population in the near term, which creates the need for nimble, data-driven strategies to optimise 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 optimise supply-chain strategies.
- Track community-based transmission and efficacy.
The storage and transportation of the vaccine is a complex logistical exercise too, requiring coordination among governments and providers and the safe transport and storage of vaccines from manufacturers to vaccination sites.
Using analytics to shape strategy and execution
Since the beginning of the pandemic, SAS has used analytics to:
- Monitor the spread of infection.
- Model future outbreaks.
- Uncover relevant scientific literature.
- Share real-time health insights.
- Optimise supply chains and medical resources.
These strategies can be used for vaccination programmes because analytics, based on trusted data, drives the best decisions. Here are some examples of how this can work in practice:
Develop immediate and long-term vaccination strategies
A data-driven strategy can help you to identify and estimate critical populations so that the vaccination programme will benefit the most people. Governments have struggled to balance the need to create an orderly, risk-driven prioritisation strategy while quickly administering the doses they have been allocated.
Integrating data to calculate the size of prioritised populations in given geographic areas enables a data-driven vaccine allocation strategy that maximises throughput and minimises 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 organisations 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 also help to ensure continued situational awareness, so that prioritisation 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.
Optimise 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. Optimising these distribution strategies – while facing fluctuating supplies, evolving need and changing provider enrollments – will require a strong data and analytic approach.
End-to-end supply chain analysis can help agencies develop an efficient, coordinated vaccine distribution response. By capturing inventory, demand, capacity and other related data across the distribution chain, you can create models that determine how agencies can optimise 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.
Monitor vaccination capacity and adverse events
Identifying and recruiting enough providers to ensure sufficient access to COVID-19 vaccines (especially once supplies increase) will be crucial. By working with government health agencies, we can monitor the adequacy of healthcare provider networks, using both human skills and technology to give agencies an evidence-driven view of vaccine administration capacity and vaccination goals.
We also work with commercial partners worldwide to augment the public health workforce to meet rising demand for vaccines. Related data, such as storage capacity and throughput, can be included for a fuller understanding of network adequacy.
As more data is collected regarding adverse events, SAS continues to help with health surveillance and research for many national health regulatory agencies. For more insights, watch this on-demand webinar: AI for Supporting Vaccine Adverse Event Reporting, part of the ongoing State of Analytics series.
Dose administration analytics
Vaccination administrators must report certain data elements in near-real time (through electronic health records or directly via state immunisation 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 our public health IT infrastructure has led to significant data quality challenges and weak reporting capabilities, which collectively prevent a data-driven vaccination strategy.
Our data management solutions can help departments build a trusted, consolidated vaccination record. This includes automating tedious and manual processes such as data preparation, data integration and entity resolution to provide analysts more time for treatment and vaccination efforts. With this reconciled vaccination data, analytics can then help agencies to:
- Predict evolving resource needs across jurisdictions such as states, regions and countries to optimise allocation strategies.
- Monitor uptake to help ensure alignment with anticipated need, provider requests and vaccine distributions.
- Analyse unexpected gaps in vaccination administration to guide outreach and engagement efforts.
- Anticipate barriers to delivering second doses.
- Gain insights on changes in susceptibility, rate of transmission, status population immunity, etc.
Managing a cold chain for biologics
In the US, the Centers for Disease Control and Prevention (CDC) have 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 analysing that data allows administrators to monitor, track and optimise distribution strategies in this multi-layered and complex vaccine rollout.
The path forward
As you read this, shipping and logistics companies are recording data on vaccine temperature and location. Governments are rapidly transforming into organisations capable of allocating, distributing and administering vaccines and their necessary components at massive scale. Retailers (pharmacies) are implementing customer contact programmes to help track, administer and verify vaccinations.
The coordination across these various public and private companies is critical for a successful vaccination programme. Even though the scale of this operation is historic, the sub-components of the process can be likened to other large, data-driven strategies.
For additional information on how SAS helps governments with complex data analysis, read how:
North Carolina modernized their Health Information Exchange with SAS.
About the author
Steve Kearney is the Medical Director at SAS where he helps lead the organisation’s focus on the future of digital health across health care, life sciences, government research and development divisions. An innovator in health outcomes and digital medicine, Dr. Kearney co-developed and implemented one of the first electronic disease registries at Duke Health while also offering the first web-based ambulatory medicine elective at UNC. Dr. Kearney then joined the medical outcomes group at Pfizer where he continued his practical, actionable approach to data and the patient journey. He focused on health outcome insights from electronic medical record migrations, early personal digital assistants, novel health software programs and the first large patient claims databases. Throughout his career, Dr. Kearney has been a trusted advisor on health policy for state and federal agencies.
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