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Data, Analytics and AI Power Public Health in the U.S.

The COVID-19 pandemic revealed how big data and analytics technologies are being used in the public health sector. For example, governments and organisations developed contact tracing, where phone numbers and location data from mobile devices were combined with lab results in public health systems to issue alerts when an individual came in contact with a confirmed COVID patient. This information empowered people to preemptively self-isolate and/or head for rapid testing.

Public health agencies must understand how to use data effectively as the use of big data during the pandemic is essential. They should start working on plans to protect the privacy of the end-user and comply with the evolving laws around personal data privacy.

Additionally, organisations should determine what they will do with the data they are gathering. Data is only worthwhile if the organisations use the right tools to read and interpret it. Artificial Intelligence (AI) is vital for processing the vast amounts of data collected by today’s technology.

AI has powered everything from tracking the initial spread of the outbreak to helping researchers quickly analyse and interpret huge amounts of data to come up with a vaccine. Going forward, AI and big data will be vital to analysing vaccine efficacy, identifying breakthrough case trends and more.

Targeted outreach and prevention 

Big data and AI have been foundational technologies for other programs. During the pandemic, data was used for targeted outreach and prevention efforts, especially during the vaccine rollout. The ability to recognise trends in a cohort or region allowed for more effective risk mitigation.

For immunisation information systems (IIS), this meant parsing data to identify and prioritise groups that are most at risk from a lack of vaccination. Identifying at-risk groups is just one part of the pandemic response process. From there, it involves what are essentially next-generation logistics efforts: monitoring vaccine distribution, managing vaccine appointments and tracking the growing numbers of vaccinated individuals.

These efforts feature an incredible number of moving parts: government and public health offices, vaccine providers, health care workers and more. Marketing and education components will also see data analytics play an important role in their efforts.

All of which places a high data load on systems — a load that requires modern architectures and flexibility to manage. Unfortunately, most public health offices today are using outdated systems that were designed for managing a load about 10 times smaller than what they’re forced to deal with now.

Cloud computing can help public health agencies scale up to accommodate the new data load, with architectures that auto-scale and adapt to changing flows. But the systems themselves must also be architected to support the horizontal scaling enabled by cloud computing.

Stateless Architectures

Newer architectures are designed for this sort of flexibility. Called “stateless applications,” these architectures don’t store their state on the server and don’t need to know the history of what was happening on the system, allowing organisations to add more servers to scale up and meet demand.

The pandemic served as a powerful reminder of just how fast things can change. Stateless applications are the ideal way to keep up with evolving requirements and mandates, allowing agencies to implement new functional changes quickly and easily.

Sharing data among multiple entities

Science depends on reliable data, but it has traditionally been a rare occurrence for health care data to be shared among multiple entities. Data privacy concerns are one of the main reasons for this siloed approach. However, those silos started coming down as health care researchers and public health agencies around the world started collaborating during the pandemic.

Sharing health care data is a new trend. As AI makes it easier to provide meaningful data ownership and protect personal data privacy, it facilitates collaboration by multiple entities on shared data. This in turn spurs innovation, allowing the best minds in science to work together toward a better future. Big data, analytics and AI allow public health organisations to respond rapidly to public health emergencies, which potentially translates into lives saved.

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