Role of Data Science in combating covid-19.
The world is still grappling with the coronavirus pandemic, making people helpless and forcing them to change many aspects of their life. Since this is a new situation and has not been encountered before, it is becoming a task for the governments to defeat this unseen enemy. In the absence of any treatment to date, identifying the number of positive covid-19 cases, tracking them, isolating them has become the need of the hour.
Data science involves collecting, visualizing, evaluating, and interpreting relevant data using several statistical and mathematical models. Data scientists are facilitating the authorities in making predictions quickly in order to make needful decisions.
Since pandemic is not a situation where we can rely on intuition, Data science is becoming a guiding beacon to defeat this unseen enemy. You must be wondering what role do Data scientists have to play in combating Covid-19?
Let’s take a closer look at how Data science applications have helped us in fighting this enemy-
- The collection and interpretation of data-
Data collection in the case of coronavirus has been an arduous task because of fewer people reaching the medical facilities for testing and treatment. So, data science techniques such as Regression and GLM (Generalised linear models) facilitated in estimating the number of positive infected cases, number of deaths, and the number of recovered cases.
India’s Aarogya Setu App played a very important role in storing huge amounts of data as there was tremendous raw data that had to be evaluated which was very critical to help countries combat the Covid-19 pandemic. Vast data relating to the health conditions of people were collected using the App and was interpreted using data science techniques.
Data science also helped in analyzing the rate of deaths in comparison with the number of positive cases and made interpretations of whether there has been linear growth or exponential growth in the number of deaths.
2. Contact tracing-
The first step in fighting this disease was to identify whether you have come in contact with a positive covid-19 patient and take necessary precautions such as self-isolation and social distancing in order to stop the chain infection. Contact tracing played a very important role in combating covid-19.
Data science helped in the functioning of Contact tracing apps such as India’s Aarogya Setu app. This app involved an elaborate and comprehensive process and required sound data analysis to make conclusions. By using Bluetooth technology, it collected raw personal data, location data, and made use of data analytics applications to place the person in the High-Risk or Low-Risk category. With the help of location data, data analytics could also keep a record of places you visited and evaluate whether you are at risk or not.
Artificial intelligence has played a very important role in the technology behind the working of the Aarogya Setu App.
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3. Speeding up vaccine development-
Amidst this pandemic, a major concern by top Pharmaceutical companies was to develop and distribute a vaccine as quickly as possible. A vaccine usually goes through rigorous testing protocols and regulatory approvals and takes a lot of effort and time to manufacture.
Data analytics are helping in speeding up the vaccine development process in several laboratories by enabling more efficient Design of Experiments (DOE) facilitating rapid-scale production rollout processes. (DOE) is a systematic tool that helps in analyzing medical data easily with a systematic approach by reducing the number of experiments leading to the speedy development of drugs because tests are performed quickly.
Google’s DeepMind AI(Artificial Intelligence) system is being used for predicting the 3D structure of proteins based on their genetic sequence. These predictions of several proteins that were associated with SARS-CoV-2 helped the researchers in studying the virus that caused Covid-19. It further helped them to analyze this data and identify potentially important proteins that could become probable drug or vaccine targets using machine learning.
The Allen Institute for AI has collaborated with several other research organizations to produce Covid-19 Open research Dataset(CORD-19) a resource that includes 44000 scholarly articles relating to covid-19, SARS-CoV-2, and other related coronaviruses. This data set is machine-readable to help researchers create and apply natural-language processing algorithms, and accelerate vaccine discovery.
4. Developing comprehensive antibody testing-
Therapeutic antibodies are rapidly screened using Machine learning algorithms with a high probability of success. Generally conducting antibody tests takes years in the lab as experiments, but these algorithms can help identify antibodies that can fight against the virus in just a week.
Rensselaer Polytechnic Institute(RPI) in partnership with IBM is offering researchers access to a world-class computer “Artificial Intelligence Multiprocessing Optimized System (AiMOS)” with regard to data, networking, therapeutic interventions, materials, public health, and other areas that are being used to combat covid-19.
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5. Predicting and analyzing how to control this outbreak-
Several questions arose such as what will be the rate of spread of the virus? Whether a lockdown would help in controlling the virus? How effective will social distancing be? What time will the virus reach the peak? Whether we are heading for a community spread etc? Now predictions on questions like these couldn’t be based on intuitions. That’s where the data scientists stepped in and with the help of sophisticated data science models such as Rstudio software they helped in making long-term predictions of cumulative cases in India and helped the government frame specific public health policies.
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6. Data visualization and Communication-
Data scientists are creating continuously updated visual information about coronavirus to keep us updated about the latest numbers. Data visualizations and infographics are an efficient way to sort all the collected data and present it in a way that is visually appealing and easy for the layman to understand.
‘#Flatten the curve’ became the most defining graphic of coronavirus and has made 4.5 million impressions on Twitter and has been shared across all media platforms.
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7. Deep learning models were used to Evaluate lung infections due to covid-19 with the help of CT scans-
Deep learning models of data science were used by radiologists in evaluating lung infections in patients with pneumonia caused by Covid -19. Since CT scans are the preferred imaging method for assessing infection and determining treatment options in the case of pneumonia these models helped in reducing the radiologist’s read time by 65%. Thereby improving the efficiency and quick diagnosis in case of a large number of patients.
Conclusion- Artificial Intelligence is playing an important role in helping researchers to evaluate global data about the known viruses, visualizing the given data, and mapping it to make predictions where the next pandemic will arrive and the impacts it will have. Data collected from this pandemic will also facilitate the data scientists and authorities in analyzing and dealing with future outbreaks.
So, it can be rightly concluded that data scientists have played an important role along with medical staff and the government in fighting this unseen enemy and the pandemic undoubtedly projected Data science as an important discipline in understanding various critical aspects of covid -19.
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