Big Data lies at the heart of efforts to comprehend and forecast the impact that Coronavirus will have on all of us.
To better understand how Big Data is being employed to forecast and understand the reach and impact of Coronavirus, I would like to highlight few sources and extractions of the Data:
Sources of Data
The researchers have very large data sets to work on and all the learnings thus far, the data science and new techniques should be available in the public domain, so it’s accessible for the world to use and be published. Currently, data sets that are aggregated comprises information from various sources such as: CDC, NIHS, World Health Organization, Kaiser, Johns Hopkins plus it’s epidemiological data, X- rays, CAT scans, patients’ history. This will support researchers at the first instance.
Part of a strategy is the integrated national health insurance database with which data from its immigration and customs database are pulled. By centralizing the data in this way, when faced with coronavirus, they are able to get real-time alerts regarding who might be infected based on symptoms and travel history. In addition to this, QR code scanning and online reporting of travel and health symptoms help classify travelers’ infection risks and a toll-free hotline for citizens to report suspicious symptoms. Officials did take immediate action from the minute WHO broadcast information about a pneumonia of unknown cause in China. This was the first reported case of coronavirus, and Taiwan’s quick response and use of technology are the likely reasons they have a lower rate of infection than others despite their proximity to China.
The near real-time COVID-19 trackers that continuously pull data from sources around the world are helping healthcare workers, scientists, epidemiologists and policymakers aggregate and synthesize incident data on a global basis.
There has been some interesting data resulting from GPS analyses of population movement by region, city, etc., which ultimately helps provide a view of the population’s compliance or lack of compliance with social-distancing mandates
There are many opportunities to make the use of Big Data more impactful in situations like these as a society and as an industry, though we have not yet been able to effectively leverage the power of Big Data in search of a cure.
Ideas such as creating large scale COVID-19 Real World Evidence (RWE) studies that pull data from a variety of real-world sources including patients now be treated in the hospital setting could help accelerate the development of treatments in a more patient-centric and patient-friendly way.
We are just starting to see movement among advanced data aggregation service companies and virtual studies platforms in serving the life sciences sector. The most common aim is to connect assay results to clinical status in near real time.
Ultimately, fully understanding and solving the coronavirus pandemic will be about the data. There’s no shortage of data sources that are growing hourly. Business and academic coalitions formed to bring coronavirus data sources together, and added incentives for researchers who can apply modern data analysis and artificial intelligence to it.
The data sets from the COVID-19 pandemic will likely form part of the evidence package that will be presented to regulatory authorities once a therapy or therapies have been identified that appear to be effective. This will potentially set a precedent for how data can be used in similar situations in the future.
What we learn from approaches like synthetic control in the absence of randomized control populations will be effective in mitigating challenges for future epidemiological outbreaks.
by: Dr. Jassim Haji