Revealed: How Data Scientists are Containing the Spread of COVID-19. The Do’s and Don’ts

Of many events happening recently, thousands of people have lost their lives to the pandemic crisis. The data science industry is contributing to fighting the cause of COVID-19.

The global COVID-19 infection reached over 13,486,823 with 5,028,743 active cases worldwide. So far, the death toll mounts up to 581,965 people till date, statistics taken from www.worldometers.info.

Scientists and medical researchers have been thoroughly studying about coronavirus ever since it struck the world.

The pandemic has caused humanity with problems like the common cold. Also, in the most recent news, several versions of this pandemic are known to have triggered other deadly illnesses. These versions are also known as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS).

However, their impact has been slightly milder if compared with COVID-19.

What do scientists know about COVID-19 so far?

SARS-CoV-2, the virus that caused Covid-19, and an organism unknown to humanity until five months ago has become the subject of study by all researchers.

The discovery of new vaccines, antiviral drug trials, and new diagnostic tests keeps appearing daily.

But, is it enough to halt the pandemic crisis?

On the other hand, many 🔗data science professionals are looking at the crisis from a different perspective.

“I worked in post-conflict development for the UN in West Africa before coming to Silicon Valley to complete a Ph.D. focused on adapting Machine Learning to low resource languages in health and disaster response contexts. I’ve helped respond to many disasters worldwide, including the recent Ebola outbreak in West Africa, the MERS-coronavirus outbreak 10 years ago” — Robert Munro, founder & CEO of Machine Learning Consulting and an expert at finding solutions for tracking global outbreaks.

With coronavirus having spread virulently, data scientists are onto something. They’re trying the best they can to help curb the disease that caused COVID-19.

The Five Do’s

👉Help interpret information to the people around

Many people do not share the same sense of grabbing information or perhaps they are not tuned to how true scientific reporting looks like since they are not experienced in the field. You may be surrounded by people who are less experienced to you. Thus, as a data scientist, this can be the perfect time to teach them how to interpret information from log scales on a graph and why extra attention is required if they see any graph without log scales.

Curbing the spread of misleading information on the internet is one of the most significant responsibilities you can do in the current times of uncertainty.

Also, you need to trust information coming from reliable sources or from someone you’ve known for ages. If you come across people sharing misleading information, you need to educate and warn them about the severity and damage it could cause at a larger scale.

👉Try to translate the information into more than one language

People often know more than one language. You can start sharing valuable information by translating into those languages. Or things could be worse if the spread of misleading information has already taken a toll. Data that is relevant and translated with the help of speech recognition models and machine learning can be useful. For instance, Munro led a project to create 10+ hours of the disaster and health-related recordings of informational messages from the Red Cross in Swahili, with transcriptions and English translations two years ago. Now, this data was made open source, thus helping speech recognition services and machine learning translation use the data to find how accurately and similar datasets can be used for COVID-19.

👉Prepare data that is directly related to the response

The majority of the epidemiologists are data science professionals who spend almost 90 percent of their time to prepare data. If you can take the data that directly responds and transform it into a format, then you might be the ideal individual to take up this responsibility.

👉Analyze data that is not related to the response

Else if you’re not an epidemiologist or a 🔗data scientist, then taking up this responsibility is only going to become a challenge. Most of the information you analyze might only hurt people rather than help them. However, you may still be able to analyze the data and find out the information does not have a direct relationship to the response. As a result, you can find a change in peoples’ behavior.

👉Do your research with the help of disaster response datasets

If your focus is solely on disaster response, then you might need to look through the relevant datasets and insights of the past dataset. Doing so can help develop new models for COVID-19 and other crises in the foreseeable future.

An example to be noted, one NLP dataset helped develop nearly 30,000 messages that were drawn during multiple events like the earthquake that shook Haiti in 2010, the earthquake in Chile in 2010, Superstorm Sandy in the US in 2012, and the floods in Pakistan in 2010.

The Four Don’ts

👉Avoid working with organizations that do not respond

Organizations reaching out to help data science professionals with 🔗COVID-19 are nor directly looking to help in response to the pandemic. If someone reaches out their hand for help, ensure they are big organizations like WHO or CDC. Although at times such as this, it might be difficult to assume such organizations would need help. However, such organizations might project you toward another local implementing partner that needs help.

Non-operation organizations will reach out to you just for funding and publicity.

👉Do not start a task you cannot support

Avoid recruiting people during a disaster you know you cannot support unless needed. Recruiting people who can help for a longer period amid pandemic can be a challenge. You cannot place yourself on such a critical path if you cannot project yourself to be resourceful as a worker. Therefore, you need to be dispassionate, effective disaster responder, and highly empathetic.

👉Avoid amplifying fake media

You will come across multiple fake news especially when a disaster like this happens. The targeted ones include the response organizations for not being able to do the right thing. It is the tendency of most media outlets to target organizations that couldn’t do their part toward the cause. No matter how small the situation or crisis may be, it is easy for the media flag news stating — it has endangered a million lives. Eventually, they’re the ones who create controversy even when it is not needed.

👉Make sure not to release personal information of people working for the cause

Every government will have one person or another who tends to invade or take away your civil rights. The same is for criminals, they tend to find happiness in exploiting the lives of others. Thus, it is very important to look out for your family, especially the elderly since they’re easy targets during disasters.

Simply said, there is no need to release any data to be public.

Closing remarks

If there’s nothing you can contribute to the cause right now, you can still make amends. You can start preparing yourself for disaster fatigue, disaster response research, or support people around you.