Can Digital Healthcare Help Contain the COVID-19 Pandemic?

Digital Health and the Fight Against the COVID-19 Pandemic

The Wuhan virus, aptly named after where it was found first, Wuhan, Central China’s most populous city and the biggest one in Hubei province, pertains to the coronavirus family that is accountable for causing non-critical health conditions, such as the flu, to potentially life-threatening ones, for instance, the SARS or severe acute respiratory syndrome. 

The novel coronavirus strain reported in Wuhan the previous year and denoted as 2019-nCoV shares a considerable number of commonalities to those identified in bats

The lethal virus is likely to have propagated initially through the seafood wholesale market at Huanan, which is situated in the city’s downtown area and is about half a mile away from the railway station at the picturesque Hankou town.

Arguably known as Central China’s biggest wholesale seafood market, situated in the district of Jianghan, it used to sell game meat and poultry as well until the facility was closed on 1st January 2020.

The officials at the Chinese Center for Disease Control and Prevention (Chinese CDC) are known to have previously collected as many as a whopping 585 environmental samples from the Huanan seafood market and already achieved success in isolating the 2019-nCoV. The novel coronavirus nucleic acid was found in 33 of all the samples procured. 

A total of 80981 cases and 3173 mortalities were confirmed in China alone as of 12th March this year, a day after the World Health Organization (WHO) has declared the situation as a controllable pandemic. The death toll has now increased to a loss of 4613 lives on a global scale and there were 125048 confirmed cases reported across the world as of 12th March 2020. 


The US House of Representatives has passed an $8.3 billion emergency spending plan on the 14th March 2020 for controlling the deadly coronavirus outbreak. The multibillion-dollar supplemental funding bill is known as the Coronavirus Relief Bill and will include the following.

• Over $3 billion for researching and developing the vaccines, diagnostics, and therapeutics

• $2.2 billion for improving public health through ensuring deterrence, preparedness, and response measures; includes $950 million for aiding the local and state agencies

• About $1 billion to be spent towards healthcare preparedness, clinical supplies, medical surge capacity, and community health centers

• $1.25 billion for managing the overseas manifestations

Meanwhile, state-of-the-art healthcare technologies are being developed and deployed across the globe, some of which are to be briefly covered in today’s discussion.


Artificial intelligence at work for predicting an epidemic

When it comes to issuing advisories about the 2019-nCoV’s spread, an AI-driven IDS (infectious disease surveillance) solutions provider called BlueDot has outperformed both the US CDC and WHO. The Canadian startup has even accurately estimated the probable locus of the virus from Wuhan to the capital of Japan, Tokyo, since its maiden appearance. 

The proprietary SaaS (software as a service) platform can identify, trace, and make forecasts about the possibility of infectious disease spread. Its AI engine accumulates data on more than 150 diseases and their syndromes across the globe by continuously searching the World Wide Web round the clock. The system maintains an interval of 15 minutes between 2 consecutive web queries. In addition to gathering official data from global and/or national health bodies, such as the WHO and the Chinese CDC, the BlueDot engine relies on less structured information as well.

The predictive ability of BluDot is largely dependent on the data that it gathers alongside information taken from official healthcare organizations; such as the worldwide mobility of over 4 billion travelers on passenger flights per annum; population data of humans, insects, and animals; climate information transmitted by the satellites; and local data from the healthcare professionals and journalists, effectively measuring to a colossal number of 100000 articles online and in as many as 65 different languages.

The specialists at BlueDot grouped the information manually, designed an efficient taxonomy for scanning the relevant keywords with utmost precision, and implemented natural language processing and machine learning for training the system. Hence, only a few of the cases require involving a human expert for the analysis.

The company erstwhile known as BioDiaspora Inc. intimates governmental, healthcare, public health, and business clients on a periodic basis. Its alerts offer a summary of all the incongruous instances of disease outbreaks discovered by the BlueDot engine along with a general overview of the consequences they may pose.

In order to generate an early warning about COVID-19, the SaaS system marked out the Chinese articles that stated 27 pneumonia cases, all of which making reference to a market in Wuhan that sells live animals and seafood. Additionally, BlueDot accurately located the cities that turned out to be significantly connected to Wuhan through critically examining the information related to global flight ticketing to make predictions about the places where the infected individuals are most likely to travel. The names of global destinations with the highest number of travelers as per the estimates provided by the SaaS platform were comprised of Hong Kong, Bangkok, Taipei, Tokyo, Seoul, Phuket, and Singapore. Finally, 11 entries on the list that BlueDot came up with were the first cities to witness COVID-19 cases.

AI modeling is indeed becoming increasingly instrumental in disease outbreak predictions. By making the artificial intelligence thoroughly study the information available along with isolating irrelevant data to yield knowledge-based predictions, which are then cross-validated by the experts, concerned authorities will now be able to contain such epidemics even before they are to abandon their place of origin. 

Interactive maps for disease surveillance

Johns Hopkins University’s Center for Systems Science and Engineering (CSSE, JHU) designed an internet dashboard for visualizing and monitoring the reported cases every day. It represents fresh manifestations of the virus, registered mortalities, as well as cases of recuperation. One may also choose to download the entire data set in the Google Sheet format. 

The data it utilizes for generating a digital visualization like this is accumulated from several sources and is inclusive of the Chinese CDC (CCDC), WHO, US CDC, NHC (National Health Commission in China), and DXY, to name a few, the last being an online portal in China that collates near real-time regional CCDC and NHC situation reports, offering an increased number of local case estimates in comparison with what the national level reporting agencies are capable of, and this is how the web-based tool is engaged to plot all the cases reported in the entire mainland China.

The US instances data is derived from the CDC (Centers for Disease Control and Prevention) in Atlanta, Georgia, and case information of all other countries is obtained from the respective local health departments. The nifty dashboard is built with the objective of empowering the public with an overall perspective of the prevailing situations while it continues to unfold and the brains behind this useful utility did make a point to leverage transparent data sources for accomplishing the said purpose. 

Futuristic technology for real-time diagnosis

Technology continued to progress at a breathtaking speed since the historic SARS outbreak. The first patient was identified in no more than a week after the public announcement and was succeeded by the first 2019-nCoV diagnosis examination developed shortly thereafter. The genome sequences for pathogens that used to typically take days can now be executed within hours. Moreover, these days one need not culture the viruses in abundance prior to examining them as the viral DNA of minute quantity can be evaluated directly from a blood or saliva sample.

Veredus Laboratories, a private company in Singapore, has recently announced the revolutionary VereCoV™, a portable LoC or laboratory-on-chip diagnosis kit. With rapid and mobile detection tools, zeroing in on the infected persons and delivering them proper medical care is also expected to be faster and easier for the medical staff on the ground, particularly when the hospitals happen to be overcrowded.  

Genome sequencing for designing potential vaccines

After the first-ever case was found in China, its researchers did not even take a month for completing the 2019-nCoV genome sequence, and nearly 24 more were done since then. In comparison, the complete SARS genome was not made available until April of 2003, about five months after the virus surfaced first, and this considerable reduction in the sequencing execution window testifies the continuous strides in technology, particularly in the healthcare industry, signifying a worldwide consensus on inter-country collaborations. 

To put things into perspective, pharmaceutical corporations have received funds worth millions from the Coalition for Epidemic Preparedness Innovations (CEPI) so that a vaccine could be devised for human trials in as little as four months, something that is to usually take years if not decades. 

First proposed in 2015 and officially introduced in 2017 at the WEF, Davos, Graubünden canton, Switzerland, the CEPI is a Norwegian association that is engaged in research activities for preventing the emerging infectious diseases and developing appropriate EID vaccines. Headquartered in Oslo, Norway, with branches in London and Washington, it is jointly incorporated by the Indian and Norwegian governments, the World Economic Forum, the Wellcome Trust, and the Bill & Melinda Gates Foundation. 

It is evident that the genome sequences are to play a pivotal role in realizing such a determined and enterprising objective of CEPI. As the scientists can now afford to finish the genome sequencing procedures faster than ever with the assuring bliss of bleeding-edge technology, the chance of coming up with adequate therapies are also to improve and more lives can be saved in the years ahead.  

Rise of the machines

The likelihood of infections is comparatively more among medical professionals for the very reason that 2019-nCoV has the ability to spread through the human to human route. On the contrary, the clinical-grade robots are immune to cross-infections and they could genuinely prove to be key game changers in scenarios like these. 

A Snohomish County (Seattle-north) resident is known to have been already receiving such a course of treatment after he was diagnosed with the novel coronavirus. The physicians at the Providence Regional Medical Center (PRMC), Everett, Washington, have employed a robot that allows them to interact with the said patient through a screen and it is fitted with a stethoscope as well for monitoring the vitals while ensuring minimal exposure to all the members of his medical team. Agreed, it might not be a viable proposition for a crowded Chinese hospital in the immediate future, though over time, the robots are to evolve at a phenomenal pace and become the preferred alternative to better surveil the quarantined patients. 

The Bottom Line

There do exist a number of striking similarities between an outbreak like this and that of the SARS, such as the geolocation of the virus, the way it spreads, and its attributes. 

However, there has been enough progress made since the 17 years post the first-ever SARS pandemic that occurred in November of 2002. The healthcare industry gradually became more digitally dependent as the new technologies, all the stuff that happened to be undergoing development or probably never existed even in the wildest imaginations of evangelists and futurists during the early 21st century, are now more commonplace and affordable and could immensely aid in controlling and preventing such instances. 

Going further, medical drones could easily reach quarantined zones, such as Wuhan, and safely deliver the necessary medications and/or required supplies. If China has the capability of constructing a hospital in less than a week, then it is also expected to include digital healthcare services for facilitating diagnosis and treatment that are characteristically quicker and more connected. 

In any case, controlling and preventing such situations is to primarily depend on the experts and global collaborative efforts. With the comforting promise of next-generation healthcare technology, measures for containing and eventually addressing the outbreaks are only poised to run smoother. 

It is certain that patient care is to rely more on technology in the coming days and there are already quite a few startups in the global arena that are investing heavily in digital healthcare. For instance, PatientMD is a data-driven healthcare platform that not only uses a varying gamut of AI technologies (machine learning, natural language processing or NLP, and deep learning) but also other cutting-edge technologies, such as blockchain and big data, for significantly improving the quality and extent of patient-practitioner engagement. The registered users can book an in-clinic consult through the platform-integrated physician appointment scheduler, or may choose to try the next-generation, telemedicine delivery channel to remotely visit a practitioner in any of the sixteen specialties, including general medicine (Dr. Anandmoy Dutta, Dr. Ruhi Satija, Dr. Chirag Jain, and Dr. Koushik Samanta, to name a few).