Big Data Analytics Can Stop Coronavirus Infection Trends

Amidst the coronavirus crisis, government, data science professionals, health care leaders, and others join hands in curtailing the infection spread with big data.

Every corner of the globe is facing a crisis due to coronavirus pandemic. The coronavirus is spreading like a bush fire. Though the virus got first reported in Wuhan, China in last December 2019, it resulted in a global health emergency owing to its contagious nature. It is not clear how contagious this virus and how widely it has already spread. Tens of thousands of people are infected, thousands of people died, and the infection and deaths continue to rise every day.

Millions of leaders are spending their quality of time in bringing back life and shaping the universe. The health professionals are combating this situation day in and out with lots of pressure about the unknown situation. The leaders of the health sector are taking decisions in coordination with the government to allocate available limited resources to save lives.

The government through various sources is collecting data to understand the trends and there is a sudden surge of data. With huge data pouring in only tools like Big data and can assist in understanding the trends and help to prevent the alien. 🔗Data science professionals and scientists are developing models on Big data which is enabling the decision-makers to understand the spread of infection post reporting. The tech startups are getting connected with clinicians, academicians, and other conventional research entities to leverage every outlet as a means to fight coronavirus infection.

These big data tools with an added instinct of Artificial Intelligence understand the zones, regions which may have sudden growth of infection and gear up the authorities to prepare necessary hospital beds, doctors, nurses, and paramedical staff.

Besides, big data has capabilities to understand deep algorithms that can run on huge and live data to enable synchronization of the sequence of medical requirements, right from basic testing through labs, isolated cases until healthy discharged patients.

Bigdata has innate capabilities to connect with various national data sources which give feeds about the density of population information. Bigdata absorbs data and helps in predictive analysis of the data to envisage the possible infections in the future keeping the location, density of population, age, gender, and people with special requirements.

It would be difficult to monitor people’s movements during this crisis. At this juncture, technology aggressive information comes through telecom data, which monitors people’s movement and keeps the emergency alert team like Police & public health workers informed with the consolidated reports generated by big data.

Likewise, it is also very important to analyze more vulnerable communities who live cheek by jowl and notify through various media about the dos and don’ts. The aggregated information also gives the government to raise emergency funding and support the affected patients’ post-incident.

The algorithm models help all the health authorities to run their department with less probability of failure. The analytics reports are data deep driven, near-live which also aids to signal and send alerts to various departments simultaneously and keeping them well prepared.

Since big data connects to various sources and collects data for correlation it uses high-end computers and storage capabilities and usually implemented through state-wide sponsors. While most of the data is in rest the security is always questioned by few. Bigdata tools handle data security with combined responsibility along with a single sign-on and data encryption. Bigdata can be integrated with many authentication tools for better security.

Big data can be used to build many mobile apps and dashboards to push data depending on the location and geography to ensure contentions employing isolation and detection of early cases. The tool can also connect various self-help organizations, professionals involved in 🔗data science careers to join hands with government and other authorities to support the underprivileged through meeting their daily needs.