While most of us are locked inside our homes due to the outbreak of Coronavirus, healthcare professionals and scientists are doing their best to find a way to end this pandemic. One of their key weapons against this virus is technology, and specifically data science. Data is proving to be the most powerful resource for medical research. It is allowing researchers and scientists to understand the virus better and develop new preventive measures.
So how is data fighting this battle? Let us find out.
Data against the pandemic – Research and contact tracing
As thousands of patients are getting admitted, their patient records, along with earlier patient records are being stocked in the hospitals and medical research centers. Data scientists are understanding and analyzing this data to identify a solution. Using data analytics tools, they are able to find hidden patterns in these huge medical datasets.
These patterns are allowing them to draw conclusions about transmission rates, symptoms, drugs, and treatment methods. Data tools can be used to enhance existing treatment methods. For example, countries such as Taiwan and Singapore are using location data from people’s mobile phones to trace if they had been close to a person tested positive for COVID-19. This data helps in contact tracing – how far the infection may have reached.
Based on location statistics, scientists can isolate localities and analyze whether these areas are COVID-19 hotspots or not. Singapore government’s TraceTogether application allows individuals to share data with the government about who they have been in close contact with. In South Korea, websites are being developed for notifying people about the recent COVID-19 cases.
All government personnel can contribute to building a huge and extensive data set for research. The more data is available, the better will be the research. As a result, discovering solutions will be easier.
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Tracking the movement data of the public without breaching data privacy is tough, but possible. It is important for tracing the spread of the virus. Tracking movement data also helps in analyzing the effectiveness of quarantine measures.
In the COVID-19 Mobility Monitoring project of Italy, anonymous users have volunteered to provide their location data to the government. The data is gathered from various sensors from smartphones, WiFi networks, beacons, and GPS.
Similarly, Google is also releasing mobility data of people across the world anonymously using Google Maps.
Data against the pandemic – Spreading awareness
Organizations are collecting pandemic data from various sources to create dashboards. These dashboards depict COVID-19 information such as confirmed cases, deaths, transmission rates, infection hotspots, people who have recovered – all in real-time. Several websites are also using these dashboards to spread awareness among people.
These dashboards have helped governments gain public support while implementing preventive measures such as social distancing and home quarantine. Moreover, these dashboards have helped hospitals to analyze the real-time impact on medical resources and facilities. They have been able to manage, allocate, and properly utilize their resources.
Data against the pandemic – Assessing the survival chances of patients
Examining several medical records and patient data helps the doctors to predict the survival chances of their patients. The medical data is fed to the data science programs that analyze the health conditions of the patients. The results obtained from these data tools help in prescribing medications, modifying treatment plans, and also predicting infections.
This has vastly helped drug research and development.
Organizations and government agencies are continuously looking to figure out better ways to use data against the pandemic, COVID-19. Without a vaccine, the world is currently dependent on data science and technology to control virus transmission. As the saying goes, “Tough times never last, tough people do”, the combined efforts of our heroes – medical professionals and scientists – will surely rescue us from this pandemic, sooner or later.
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How can social distancing be maintained with the help of data science?
To reduce the spread of the virus, social distancing strategies can be used. Governments can use dashboards to see where measures are or aren't working, as well as include critical POIs (hospitals, supermarkets, and clinics) to understand patterns using spatial data on human mobility. The police can use these insights for law enforcement purposes as well. We can calculate infection prevalence, daily growth, and transmission rates with reliable tracking and benchmarking, which is critical for determining whether policies are working. Social distancing can be strictly enforced in this way.
Can data science be of any help in the vaccination process?
Vaccine distribution is subject to a number of criteria, including the allocation of storage facilities, as the vaccine must be stored at low temperatures to maintain its efficacy. The electronic Vaccine Intelligence Network, or eVIN, has been tasked with vaccine management. But managing this is not an easy task. However, AI can assist in optimizing delivery, and IoT can alert authorities if the vaccine's storage temperatures fluctuate. AI can also keep track of how many people have been vaccinated in a given area.
How can data science redefine the process of clinical tests?
When it comes to evaluating potential new medicines, randomized clinical trials (RCTs) are currently the method of choice for pharma. They have, however, become more expensive and complex over time, according to publicly available data. Data science advances can assist us in rethinking clinical trials, improving current practice, and discovering new ways to discover and develop potential new medicines. The rapid adoption of high-quality Electronic Health Records (EHRs), for example, represents a vast, rich, and highly relevant data source with enormous potential for improving clinical trial implementation. Federated EHR technology is enabling new ways to improve clinical research and change how clinical trials are conducted. Many clinical trial processes, such as patient identification, selection, trial conduct, and data collection, could be improved or replaced by the technology.