How We Can Prevent Crisis with Data

Natural disasters and epidemics have been around since the beginning of time. They have caused many deaths and injuries and devastation to so many people and up until recently have been completely unpredictable. Luckily in today’s age, we have the advantage to help predict these things and try to prevent them, or at least prevent as much damage and death as possible- and that is big data. 

The use of data collection and digital technology helps to lessen the impact of these terrible occurrences. There are some great ways that data is currently being used to keep track of natural disasters such as earthquakes, hurricanes, flooding, landslides, and droughts that often lead to wildfires. The most relevant of course is the use of data to fight the spread of COVID-19 at this time. There are some great benefits to the use of big data, but also some controversy surrounding how it is used and if it crosses a line into invasion of privacy.

The effects of natural disasters are catastrophic and it can take years to rebuild- sometimes decades. There are parts of New Orleans that are still in the process of rebuilding after Hurricane Katrina in 2005, nearly 15 years ago. According to the World Health Organization, natural disasters kill around 90,000 people and harm 160 million people worldwide each year. 

By using the data collected from surveillance and satellite imagery from previous natural disaster areas, it helps determine flood-prone zones and areas that are more likely to be affected and the reason why it was most affected- which can put plans in place to prevent that or evacuate that part of the area first in another occurrence in places that are prone to natural disasters. 

Data scientists are measuring everything from everywhere. On land, they are using seismic sensors to track movements caused by earthquakes and volcanic activity. The sensors detect the primary seismic sound waves and turn those into plotted graphical images that are analyzed to predict the likelihood of an earthquake or eruption. On the water, they use Marine sensors, data scientists can analyze changes in ocean currents, waves, and water levels to predict Tsunamis. Unmanned aircraft systems or (UAS) can give visuals of areas that are difficult to access for whatever reason and can help with the analysis of different rescue strategies for those cases. Some places we are aware of that get more difficult to access after flooding and this can help with those situations. All of this not only allows for people to evacuate sooner but also we can identify the safest shelter location- overall while we, at least as of now, can't prevent natural disasters from occurring it helps save as many lives as possible. 

One of the greatest data collection techniques comes from social media. Facebook started to have people “mark as safe” during disasters and you can also request help and tag your location. Google Person Finder can help people find their missing loved ones and post updates. All of this is not only helpful to the community at the time, but the data collected to be analyzed later is essential for future disasters in many ways. 

Similar to natural disaster tracking, Pandemic tracking has a lot of data that is already collected. There are teams that work to try and prevent Zoonotic disease by testing bats in different parts of the world for current and new diseases to try and prevent pandemics. Unfortunately, we are a little too deep into that now so the data we are collecting and using is to try and prevent more deaths and further spread aka “flatten the curve.” 

The data collected that tracks the number of contracted individuals, deaths, and predictive analysis of where it may spread based on population densities and air traffic is called Outbreak Analytics. It is the best data that we have to predict when and where the virus may peak and what precautions to take and healthcare systems can prepare for surges in different areas.

Currently, there are data visualization dashboards that are available online like the CDC and WHO dashboards that pull data from around the world and show confirmed cases, recovered, and death from COVID-19 where anyone can see what is happening in real-time. They are using many sources to determine this information such as healthcare reports and laboratory testing results- however, there are some ways data was collected in China that many believe violate privacy rights.

China has already been under fire about its questionable surveillance culture of watching for criminal activity and now they are utilizing that system to track those exposed to Coronavirus. They did this by using thermal scanners installed in the train station to detect elevated body temperatures. If there was a high temperature detected, health officials would detain the person and test them for COVID-19. If they tested positive, authorities then alerted any passenger who may have been exposed and required them to quarantine as China tracks transporters by their government IDs anytime they travel. Not only that but they track by AI recognition and were arresting those who were supposed to be quarantined but were caught in public on camera and were tracking their mobile data to see if they left their house.

The Chinese government also created a “close contact detector” app that alerted users if they were in contact with someone who had the virus. This is less controversial as it at least protects the privacy of that person and other countries are working on doing the same. In the US, the government is working with Facebook and Google and other tech giants to determine what is possible for tech to track and prevent the spread of disease while also being ethical in terms of data and tracking smartphone movement. There would be a lot that would need to go into doing that and policies that would need to be put in place- but the idea is that someone diagnosed with COVID would be able to anonymously message anyone they had a contact within the weeks prior to being diagnosed through the app so those that came in contact would be aware they may have been exposed but not be aware of by who.    

On a lighter note, data helped a grocery store in Utah predict sales of certain items and stock up for the pandemic buying that happened very quickly after it became clear we were going to need to quarantine. They use a data visualization platform that I am a big fan of called DOMO. The store in Utah, Harmons, saw a spike in sales when Utah Jazz basketball player Rudy Gobert tested positive for COVID-19 on March 11. The platform detected an immediate spike in sales of SPAM and other items that do not usually show up on Harmons’ daily inventory reports on what needs to be reordered. By using data they were able to analyze the top 4,000 most important items to keep in stock- hoping one of those was toilet paper. As much as I laugh that data helped SPAM sales it does show just how much data can help all around when a crisis hits. They were able to stock up before the panic buying hit and so many businesses can benefit from having a good data collection system and team. 

Overall, big data provides a deeper understanding of how everything is interconnected and allows for predictability and prevention. While it won’t solve all the world’s problems- it definitely helps us take measures to learn from them and be better.

**This is an article based on show notes from my podcast, Talk Digital To Me. Episode 13. Listen to the full episode here: https://www.spreaker.com/user/nrdigitalconsulting/episode13