A data-driven approach to managing COVID-19By Staff Writer 24 June 2021 | Categories: feature articles
Reports have confirmed that South Africa is officially in an upthrust of the third wave of COVID-19, where infections in Gauteng recently saw a daily record of 10 806 new cases being recorded. And with predictions that the peak could possibly be reached within the fortnight, attention has turned to the efficacy of the vaccination programme. But keeping track of this process is not without its challenges.
“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,” says Greg Horne, Global Principal, Health Care, SAS.
Horne says agile, data-driven strategies are critical to optimise the available supplies and identify the location and concentration of priority populations. But beyond this, the need to reduce and potentially eliminate waste of vaccines require close monitoring of the expiry data along with predicting demand spikes. This is vital to ensure the transportation of the most at-risk supplies are done to those communities where the demand is highest.
An analytical strategy must therefore be able to monitor the spread of the infection; model future outbreaks; uncover relevant scientific literature; share real-time health insights; and optimise supply chains and medical resources.
“Globally, healthcare researchers and regulatory agencies need a more comprehensive view of patients to make confident decisions about healthcare, drug approvals, and policy. But clinical trial data, electronic health records, claims data, and adverse event reports are only snapshots of patients at random points in time. To provide real value, a holistic patient profile built with real world data – or observational data collected beyond controlled clinical trials – is needed to achieve the greatest effect on health and wellness and to assess the safety and efficacy of new drugs and medical devices,” believes Horne.
In order 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.
South African requirements
“The importance of such a global response cannot be underestimated. However, when it comes to country-specific interventions, South Africa can learn from best practice to refine its own strategy. For one, a rapid response to not only this pandemic but other, future emerging public health threats requires a comprehensive approach to detecting and assessing outbreaks, identifying characteristics of the threat, and determining optimal intervention strategies,” says Horne.
This requires modelling the spread of infections based on up-to-date health surveillance data to help the South African government mobilise critical health care resources at all levels and understand the effectiveness of mitigation and containment efforts.
“Critically, COVID-19 has exposed gaps in the public health data systems of not only South Africa, but most other countries around the world. Unfortunately, poor data management and reporting capabilities, coupled with the inability to work between systems, have contributed to how quickly the virus has been able to spread. South Africa must now look towards upgrading infectious disease surveillance systems to an integrated platform that can deliver analytical insights for case management and quick outbreak detection.”
Much of this comes down to having a trusted data foundation in place. In the past, the information needed to rapidly identify and respond to public health events has often been siloed or inaccessible. One of the lessons of COVID-19 is the importance of integrating data from laboratories, health information exchanges and patients, along with public health registries and other sources, to facilitate rapid case detection and investigation.
“Data on its own means little if advanced analytics are not in place for forecasting and modelling. Systems capable of anticipating trends and societal impacts are essential to effective public health responses and may prevent future public health crises,” concludes Horne.
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