Impact of Big Data fighting against COVID-19 in Bangladesh

Abstract: Big data is the greatest tool in this digital era. In the Global epidemic COVID-19, big data has advanced to a place where it can provide emergency response teams with real-time tools and technology that have the potential to monitor, contain and even stop the spread of disease. In this article, we demonstrate the implication of big data in the COVID-19 battle plan. The study shows some perceptions of the big data execution in the healthcare system of Bangladesh.

 

 

Coronavirus(COVID-19)  is spreading rapidly all over the world. The world is facing the greatest trial decade. In Bangladesh, the situation is getting scary day by day. The advantage of this 2020 decade we have some high-level digital tools like big data, machine learning to fight against COVID-19. The lessons learned from the other countries of the world using digital technology to develop real-time forecasts and arm healthcare professionals and government decision-makers with the intel they can use to predict the impact of the coronavirus. In this article, we will discuss how big data is helping to fight against COVID-19 in Bangladesh.

Firstly we will know how Bangladesh is applying digital tools in this pandemic. It’s great news that our government initiated a process to draw a digital map to track coronavirus cases and find out areas susceptible to contamination by using mobile users’ information. This move may help portray the real picture of a possible outbreak.

This method is mainly a self-reporting method, mobile users will get a short message (SMS) from their operators and in reply, they will share some of their health information. Approximately 16.62 crore mobile phone users in the country will start getting SMS from this morning and they will be asked to make a call to *3332# free of charge. There is another method: a self-reporting system. Under this system, callers’ information will also be collected through the government’s “333 call center”, which receives more than one lakh calls daily. Some other agencies also handle thousands of calls every day and all the information will be used for analysis that will help the government prepare a roadmap on how to fight the pandemic. Some mobile operators have taken some steps to make a roadmap by using a customer’s mobile number, location, or his/her handset’s international mobile equipment identity (IMEI) number. All the data is customized that’s why there will be no probability of overlapping data. By this data, they can track the higher risk zone and share the information of the individuals of risk zones.

The Healthcare system in Bangladesh is incapacitated to apply digital tools to fight any pandemic. If we have a look at other countries we will see renowned healthcare centers using these big data tools effectively. Here we are discussing some research work executing big data analysis to avert coronavirus.

At RPI(Rensselaer Polytechnic Institute), researchers are using big data and analytics to better comprehend coronavirus from several different angles. The institute recently announced that it would offer government entities, research organizations, and industry access to innovative AI tools, as well as experts in data and public health to help combat COVID-19.

James Hendler, the Tetherless World Professor of Computer, Web, and Cognitive Science at Rensselaer Polytechnic Institute (RPI) and director of the Rensselaer Institute for Data Exploration and Applications (IDEA), told HealthITAnalytics he had given an insight how big data  “We’re working with several organizations on modeling and dealing with the virus directly using a supercomputer, and we’ve been creating some websites where we track all the open data and documents we can find to help our researchers find what they’re looking for,”.

“We also have some work we’ve been doing in understanding social media responses to the pandemic. One project, in particular, has focused on tracking data from Chinese social media as coronavirus spread there in mid-January, and then comparing it to American data”, he said.

Between recognizing signs and symptoms, tracking the virus, and monitoring the availability of hospital resources, researchers are dealing with enormous amounts of information – too much for humans to comprehend and analyze on their own. It’s a situation that is seemingly tailor-made for advanced analytics technologies, Hendler noted.

Here are some other applications using AI, Machine learning, and big data analysis to mitigate COVID-19.

 

Real-time data dashboard to track CoronaVirus

The Center for Systems Science and Engineering (CSSE) at Johns Hopkins University has developed an interactive, web-based dashboard that tracks real-time data on confirmed coronavirus cases, deaths, and recoveries for all affected countries. Researchers noted the primary data source for the visual dashboard is DXY, an online platform run by members of the Chinese medical community. DXY collects local media and government reports to provide COVID-19 cumulative case totals in near real-time at the province level in China and the country level otherwise.

Every 15 minutes, DXY updates the cumulative case counts for all provinces in China as well as other affected countries and regions. For regions and countries outside mainland China, such as Hong Kong, Taiwan, and Macau, CSSE manually updates case numbers throughout the day when new cases are identified.

 

 

Data platform to track hospital bed capacity

Definitive Healthcare has partnered with Esri to launch an interactive data platform that allows people to analyze and monitor US hospital bed capacity, as well as potential geographic areas of risk, during the COVID-19 outbreak. They used  Data visualization tools that have emerged as a viable way to track and monitor COVID-19 and its impact around the world.

Improved visual analytics capabilities and better big data dashboards can be an invaluable addition to both the executive toolkit and the clinical arsenal. Visualizations can make complex datasets clear in an instant by presenting information in intuitive and user-friendly ways, opening up the chance to dive deeply into existing data assets and unveil novel insights into opportunities for improvement.

In the early days of the coronavirus outbreak, Chinese data scientists built a graph database tool called Epidemic Spread. It allowed people to type in identifying information associated with the journeys they took, such as a flight number or even a car’s license plate. The database would then tell those users whether anyone with a confirmed coronavirus case took those same trips and may have spread it to fellow passengers.

 

 

Challenges of Big Data execution in Bangladeshi Healthcare:

Big data analytics in Bangladeshi healthcare could spare a great number of lives from coronavirus and enhance patient services. Big data analytics and applications in Bangladeshi healthcare are at an early phase of improvement, however quick advances in platforms and tools can quicken their developing process.

But there are some challenges of big data execution in the Bangladeshi healthcare sector. Some of the challenges discussed below.

Huge Data frameworks require data analysts, data scientists with particular experience to design, analyze, execute, and proceed with utilizing. The McKinsey Global Institute gauges that there will be a more than 100,000-man shortage through 2021. It implies that mean 50– 60% of a data analyst, data scientist positions may go empty. Information researchers require profoundly specialized ranges of abilities. They should have delicate technical skill sets, for example, correspondence, team effort, authority, imagination, and more (Rezaee& Wang, 2017).

One of the significant difficulties in utilizing health care’s huge information to its full degree is policies that protect the privacy of patient’s information in Bangladesh which is yet not strict to date. Numerous laws ensure the patient’s data and not uncover the patient’s identity that makes the big data analytics troublesome. Now and then healthcare providers are reluctant to share patient’s data because of huge competition in Bangladesh. A doctor may not want their competitors to know precisely what number and which sorts of techniques they performed and where. Additionally, the demographics of hospitals give one financial standpoint over another. A portion of datasets is openly accessible however these data sources are normally historical data or restricted to government payers (White, 2014).

To have an advantage through Big Data analytics, it is necessary for an organization level administration and analysis and also huge-scale speculation. In the healthcare area, the data is in unstructured shape. These unstructured data are as pictures, charts, notes, graphs of specialists, doctors, and so forth. Aside from this, the nature of structured data is for the most part heterogeneous. These may lead to an enormous issue at the season of accumulation of these data. Normal language processing and free-text software could take care of this issue to some degree yet it is in its underlying stage.

 

 

Conclusion:

COVID-19 is not the last pandemic virus. We could be attacked by the next one followed by. Big data analytics using live mobile phone connections must not be a one-off affair in Bangladesh. It should be captured in our national security policy with paramount importance. For this reason, mobile big data should be processed only by the individuals having required security clearance. Our government also needs to take more necessary steps to engage competent data scientists in the healthcare sector so that we win the battle of a pandemic using Big data analysis and other digital tools.

 

Farhana Afrin
Electrical Engineer, Writer
Email: farhanaafrineirin@gmail.com

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