Select your language: EN JP

3 Ways COVID-19 Will Not Be The Next Great Influenza

Danielle Bradnan, Research Associate
February 3, 2020

As typically happens in the face of a global pandemic, COVID-19 is drawing comparisons to the Great Influenza of 1918. However, for the first time in human history, there are digital tools sufficiently advanced enough to support healthcare infrastructure in the face of pandemic disease.

Infrastructure is a critical yet often undervalued complement to the efforts made to develop successful treatments and vaccination protocols for an outbreak. In sharp contrast to the Great Influenza, now there are specific digital tools to both manage outbreaks and get ahead of them.

Great Inluenza 1918
Emergency Hospital During the Great Influenza of 1918

Three key issues contributed to making the influenza epidemic of 1918 so lethal:

1) Lack of knowledge of the disease's underlying cause
2) Inability to provide adequate resources to regions in need
3) Inability to maintain caregivers' capacity for work

While the epidemic of 1918 feels distant, the SARS epidemic faced many of the same problems, and even 10 years ago, the digital tools to combat these challenges were unavailable. Below, we highlight how the digital tools available today are tackling those same pandemic challenges for COVID-19.

Lack of knowledge of the disease's underlying cause and transmission

Great Influenza

In 1918, medical personnel did not know what caused or how to treat the disease. Even at the end of the pandemic, scientists continued to debate the causative agent. Research was frenetic but siloed, and while attempts were made to share data, it was more challenging due to the communications technologies at the time. 


Today we have apps like CURE ID as a way to identify new treatments for stubborn conditions, and they are currently being used to identify symptoms and new treatments for the Wuhan coronavirus. Even Twitter has specialized hashtags to help doctors crowdsource information from their colleagues in an easily accessible way. Less than a month after initial reports of the disease, researchers have developed a rapid diagnostic for determining the presence of the virus, which is critical for managing transmission. With a rapid diagnostic, epidemiologists are able to trace who may have come in contact with infected patients much faster, preventing or slowing further spread. Disease communications tools are excellent investment opportunities for companies who work with government agencies and who already have existing partnerships with research institutions in order to best make use of the information.

Inability to provide adequate resources to regions in need

Great Influenza

Despite clear supply lines as a result of the war effort, getting the necessary resources to patients became impossible. There was no way to predict where the next outbreaks would occur, and by the time supplies reached desperate regions, it was usually too little too late. 


Automated disease surveillance systems use web scraping tools to pool data to collate seemingly disparate data streams from social media activity, plane ticket purchases, and hospital admissions to draw insights and make predictions about pathogen spread. Critically, these predictions generated by AI can accurately be made days before the disease pops up in a new region, allowing for the administration of support in the form of medical personnel and supplies. Companies that have healthcare product offerings should partner with companies like BlueDot and Metabiota to inform their own supply and distribution systems.

Maintain caregiver capacity

Great Influenza

It was unclear how medical personnel could keep themselves safe. At the peak of the pandemic, fear kept potential caretakers from caring for friends, relatives, and neighbors. Caregivers that did provide basic care like feeding and changing bedding became ill, adding to the burden of already-crashing communities.


There has been significant hype surrounding the use of robots in the U.S. to treat coronavirus patients. The robot in question was designed to minimize exposure to individuals infected with Ebola by automating routine tasks like taking blood pressure and performing visual exams. In this case, it was deployed before scientists were sure of the mode of transmission in order to minimize risk for physicians. Remote continuous temperature monitoring is being deployed in Shanghai to monitor patients without the need for a nurse to interact with them. This kind of tool translates to minimal exposure for medical personnel, helping keep as many capable staff members on hand as possible. Companies either looking to develop their own products or seeking meaningful partnerships should watch how this use case evolves through this coronavirus outbreak.

Coronavirus Wuhan 2020
 Beds are seen in a temporary hospital set up in the Hongshan Gymnasium in Wuhan in central China's Hubei Province. | Source: Xinhua News Agency


Epidemics of disease can be scary, and often, much of the focus is on the race for a cure – but the infrastructural elements that support the management of the epidemic and the treatment have greater potential to stop the spread of the illness in the first place. Companies should not expect new opportunities to emerge immediately from attempts to develop a cure but rather look to digital tools for ways to slow the spread and reduce the eventual scope of the illness.




- Blog: Can Innovation Stop a Global Pandemic?

- Executive Summary: The Digital Transformation of Healthcare

- Blog: The 4 Major Challenges That Digital Therapeutics Face

Access Digital Research    Schedule Demo