COVID-19 or Coronavirus, as labeled by media houses, is an infectious disease caused by a strain of Coronavirus. The first case was discovered in Wuhan, capital of Hubei province, China, during December 2019. Since its discovery, the virus has spread across multiple nations, with a number of infected people reaching 134,804, and the number of deaths reaching 4,894.

World Health Organization (WHO) declared Coronavirus as a pandemic. Pandemic is nothing do with a change in the virus characteristics, it is declared when a disease spreads across the world, and we don’t have an antidote for it. The effect of the virus has been felt across various social gatherings around the globe, from international sporting events to business conferences. Everything involving crowd gathering has been canceled.  

Technology businesses are moving toward providing remote working tips or using AI and machine learning to track and predict how the Coronavirus will spread, and its impact on the population.

1. 3D mapping to track cases

The spread can be followed on a 3D map that will be illustrating the global path of the virus. The United Nations aviation agency built a 3DFX dispersion map that shows the movement of the Coronavirus around the world via air traffic routes from its origin center, Wuhan, China. The Geographic Information System (GIS) map displays multiple layers of data, including deaths, confirmed cases, and cases based on the geographic region.

The 3D map provides information on first out cases of patients with the Turquoise axis starting in Central America, Australia, and Asia and moving around the world to end at Wuhan. These are illustrated as the first wave of cases inside China, while the other layer of the map shows the second wave of the cases.

2. Use of social media and technology

Coronavirus illness is now a public health emergency, even bigger than the SARS outbreak of 2003. However, scientists are better prepared to tackle such an outbreak with better genome sequencing, machine learning, and predictive analysis tools to better understand and monitor the outbreak.   

During the SARS outbreak, the scientists took around five months to sequence the virus genome, while in the case of Coronavirus, the scientists were able to do that just after a month.

Este Geraghty, MD, MS, MPH, GISP, and Chief Medical Officer and Health Director at Esri said in a statement that after the SARS outbreak in 2003, there had been a revolution in applied geography through the web-based tools. With the deployment of new tools, the medical teams are prepared to protect human lives by ingesting real-time data and display results on the interactive dashboards built by Johns Hopkins University using ArcGIS.

The outbreak even provides them with data set that wasn’t available before; scientists now have social media. In 2014, Chicago’s Department of Innovation and Technology built an algorithm that used social media data mining and illness prediction technology to target restaurant violations. The algorithm found the violations of about 7.5 days before any regular inspection routine.  

Though the above-listed applications of technology are to curb the spread of Coronavirus that will help after the outbreak, but the question is, what can be done in advance to prevent such outbreaks from happening or spreading across the world and become an epidemic.

Here is the four-step process every government must follow with any new epidemic outbreak.

1. Prediction

With the rapid growth of the human population around the world, humans and animals are interacting under various circumstances. The interaction is leading to virus jumping from animals to humans leading to spread. In recent years, the outbreak of SARS and MERS viruses to new forms of flu and Ebola outbreak in 2018 in West Africa happened during a particular stage when a human interacted with an animal. The Ebola outbreak resulted from the toddlers interacting with bats from the stump.   

The CDC estimates that out of every four new diseases, three are transmitted from animals. Scientists believe that there are approximately 800,000 unknown animal viruses that could infect humans. Researchers are turning to Artificial Intelligence to predict the hotspots where the new disease could emerge; the technology provides a model by integrating data from unknown viruses, animal populations, human demographics, and cultural/social practices around the world to predict outbreaks.

2. Detection

When a virus from the animal kingdom jumps to humans, time is the most important resource. Quicker the response to the disease outbreak, the sooner actions can be taken to stop the spread and effectively treat the infected population.

The National Biosurveillance Integration Center (NBIC) in the Department of Homeland Security developed a pilot approach using Machine Learning to mine social data for the indicators of unusual flu symptoms. The developed ML was able to examine near-real-time emergency medical services and ambulance data using the ML to look for anomalies in the medical notes as patients were admitted to hospitals. AI provided better detection for any abnormal disease event at a much faster rate.

3. Response

After the diseases have been identified, it’s important to make informed decisions in a timely manner to limit the impact. AI can integrate travel, population, and disease data to predict where and how quickly the diseases might spread. With more data on the outbreak of the new cases of flu, we can leverage travel, flight, and population data around the world.

After the Ebola outbreak, scientists in the Department of Agriculture created a travel-census model that predicted the exact county in Texas and even the likely hospital wherein the Ebola case was to be found; the model was spot-on.

Machine learning systems can even better respond to all types of outbreaks as they can learn from large data sets to make better treatment decisions based on medical imaging.  

For example, data from the chest x-rays of coronavirus patients can serve as an input for AI models; therefore, the physician can make a faster diagnosis. Developing new treatments and the creation of new vaccines is a difficult and time-consuming process, and using AI can examine the data from similar vital diseases and then predict the vaccines and medicines likely to be effective.

4. Recovery

Once the governments and global health organizations have contained the outbreak, the next challenge would be how to prevent such an outbreak in the future. ML can be a beneficial tool in limiting or preventing such an outbreak. It can be easily done with the prediction of various sensitive areas that need to be watched, and the various medical staff conduct routine health initiatives to prevent such attacks.  


Containing diseases outbreak can be a challenge with ease in global transportation across the world; however, by using technology, health authorities can identify various sensitive areas which need to be watched regularly. Technology gives us the best tools; it’s now up to us whether we are able to utilize them efficiently. To know more about technology, you can download our latest whitepapers on Technology.