Coronavirus (COVID-19) has arrived in all its glory with consequences that are both unsettling and grave for the entire world. There are daily reports showcasing the scope of the outbreak and the fatality curves on a worldwide city/country basis. At the heart of it all lies Big Data, as it tries to make sense of all the efforts to forecast and comprehend the impact that coronavirus is going to have on the world.
To understand how Big Data is being deployed to forecast and understand the impact and reach of the coronavirus, we spoke with the leading experts to understand the impact of Big Data and how it can help us make sense of COVID-19.
How Big Data Is Enabling Everyone to Fight Coronavirus
The near real-time trackers of COVID-19 are continuously pulling data from sources all over the world and are helping scientists, policymakers, epidemiologists, and healthcare workers synthesize and aggregate incident data on a global basis. An interesting amount of data has resulted from GPS analysis of population movement by region and city.
That has ultimately helped provide a view of the compliance of the population, or lack of compliance with mandates for social distancing. Apart from that, a digital thermometer technology has been tracking recorded temperatures by their devices and has shown that average temperatures have declined in most locations after the enactment of social distancing guidelines.
How Advances in Big Data Management Have Made it Possible to Synthesize and Aggregate Incident Data Globally
There are a lot of opportunities to use Big Data in impactful situations like the current ones as an industry and as a society. However, people have still not managed to effectively leverage the power of Big Data in search of a cure. Ideas like creating large scale COVID-19 Real World Evidence (RWE) studies that have pulled data from various real-world sources, like how patients can be treated in a hospital setting, can help accelerate the development of treatments in a more patient-friendly and patient-centric manner.
We have only started seeing movement in advanced data aggregation services and virtual studies platforms when it comes to serving the life sciences sector. The aim here is to connect the results to the clinical status in real-time. If the curation timelines can be overcome meaningfully, these solutions can easily help create patient data sets that can be analyzed and interrogated with both AI-based pattern detection and traditional approaches to better understand the disease.
Views of population-level can help epidemiologists, clinicians, and biostatisticians to explore the relative effectiveness of variations in the protocols for local treatment. The COVID-19 pandemic can also be seen as a wake-up call to determine access to data can be improved.
How Big Data Is Helping Fight This Global Pandemic
While there are greater advancements being seen with Big Data today, both as an industry and as a society, we still have to take steps to effectively leverage the power of Big Data to search for a cure of COVID-19. Signal detection and advanced analytics within the healthcare system are two of several large automation improvements that are going to surface.
Models from big data support the prediction of a pandemic. Our ability to contain and respond with treatment depends on early detection and how we can leverage data aggregated on infected people. That helps us understand differences in presentation, response to different treatment modalities, and codification of the treatments that have a better impact.
How Big Data Is Contributing to the Effectiveness and Efficiency of Clinical Trials
Clinical trial operations benefit the most from the ability of data to connect us readily with patients during this time. As a result, we get faster, more targeted patient and site recruitment while ensuring patient access to these studies. The main benefit is the opportunity for faster and near real-time evaluation of decision-making based on this data set. That is going to save lives and will result in identifying effective therapies a lot faster.
Another great idea is to identify potential patients at the point of testing and then rapidly populating patient histories and tracking progress by linking to different world sources through tokenization, without any burden on the patient and the site. When healthcare data can be used directly to build the clinical data set for safety and efficacy analysis, there are going to be fewer patients that will need to be enrolled and randomized, which will reduce the duration of the study, and the logistical burden on patients as a result.
What Lessons Can Be Learned by Sourcing and Organizing Big Data Sets on a Global Basis?
There are massive efforts being deployed to leverage machine learning and AI on the datasets that are currently available. We anticipate that the value of the currently available datasets is going to increase significantly as testing for COVID-19 becomes more readily available. The key will be to progress ‘Clinical Research as Care’ from theory to practice.
We are getting better data more accurately and faster than ever before. There are various data sets in aggregation that provide us both broader and deeper views of our population health, our mobility, healthcare utilization, and lifestyle patterns. That information is critical as we assess the potential incidence and behavior of conditions.
by Bobby J Davidson
We love our company and we love what we do. Check out the ‘Why Percento‘ page to learn more: Love of Technology and Business! As the President of Percento Technologies International, I provide day-to-day leadership to the company’s senior management and I am personally involved in the strategy, business development and sales activities of the firm.
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