Using Open Technology To Build a Biodefense Against the Coronavirus

What must it have felt like to be a guard on the watchtower of a castle back in the Middle Ages knowing that a deadly enemy is about to appear in the distance and assault the castle at any moment? News of the devastation in neighboring kingdoms has already reached you, and your job is to know when to sound the alarm of an invasion. Every rustle in the trees caused by a flock of birds has you jumping to your feet, and you are always guessing if that stray dog barking in the distance senses something you don’t.

This scene is comparable to the challenges facing epidemiologists in the United States today. As the number of carriers of the 2019-nCoV Coronavirus entering the US increases and with human to human spread within US borders having just begun, epidemiologists are on the front line of detecting the virus and containing its spread. The 2019-20 flu season was a rough one even before the coronavirus hit, with both A and B strains striking. Many hundreds of thousands of people who had their flu shot for the A-strain are still to this day getting hit hard with the B-strain.

As the number of US cases of the coronavirus rises, how will healthcare professionals be able to tell the difference between which panicked patients with similar symptoms has what? Even if the patient hasn’t traveled to Wuhan or China recently, what if they sat at a Starbucks with someone who did? With the incubation time-lag before symptoms appear, who would even know?

Monitoring 330 Million People

The challenge of monitoring 330 million people for infectious disease outbreaks is daunting. Take the flu as an example. During the last flu season which, as already discussed, was not as complex as this year’s season, approximately 35.5 million Americans had flu symptoms, 16.5 million received medical care, 490,600 were hospitalized and 34,200 died.

These are definitely not small numbers and monitoring all this activity is difficult as the information systems of the major hospital groups are not interoperable with each other and are effectively siloed.

When it comes to detecting the 2019-nCoV virus, by the time a patient is confirmed to have the virus and test samples and results have gone back and forth between their hospital and the Centers for Disease Control and Prevention (CDC), a significant amount of time will have elapsed and they would have already come in contact with many people, whether family, coworkers, random people in public places, or hospital staff.

One of the ways epidemiologists can tackle this problem to some degree is using technologies that survey massive data sets to identify patterns and anomalies. While at this stage only the CDC test provides definitive results but takes time, predictive Artificial Intelligence (AI) algorithms scanning for clusters of symptoms can provide early warning signs and flag groups of patients who may need additional attention and investigation.

Wake Up Call for US National Biodefense

Only time will tell how effective the US healthcare system’s response will be to the coronavirus, but whatever happens, it has definitely provided yet another wake-up call for real implementation of legislation that has been meandering in slow stutter steps for two decades.

This illustration, created at the CDC, reveals ultrastructural morphology exhibited by the 2019 Novel Coronavirus (2019-nCoV). Note the spikes that adorn the outer surface of the virus, which impart the look of a corona surrounding the virion, when viewed electron microscopically. This virus was identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. | Photo from CDC/ Alissa Eckert, MS; Dan Higgins, MAM, Wikimedia Commons is in the Public Domain

Soon after the Sept 11, 2001 attacks, the need for a national biodefense system to protect against biological threats – whether from terrorists or natural causes – became top of mind. In 2006, the US Congress mandated the Department of Health and Human Services (HHS) to improve the nation’s awareness of threats related to public health emergencies with the Pandemic and All-Hazards Preparedness Act (PAHPA).

With minimal progress made over the next seven years, the PAHPA was reauthorized in 2013, this time with a stipulation that, in additional to developing a strategy, the Department would also have to develop an accompanying implementation plan and called for the Government Accountability Office (GAO) to report on future progress made. The GAO released a report in September 2017 which is summarized by its title: “HHS Has Made Little Progress toward Implementing Enhanced Situational Awareness Network Capabilities.” PAHPA was reauthorized again in 2019 following an extensive set of Congressional hearings and in-depth review. HHS came under severe criticism at several of the hearings due to their failure to develop a syndromic surveillance (biosurveillance) tool to monitor the outbreaks of infectious diseases and epidemics.

While the 2017 GAO report outlines many reasons for the sluggish progress, one obvious technical reason is the sheer scale of integrating electronic health data from across 3,000 county, city or tribal health departments and 180,000 public and private clinical laboratories, all with their own proprietary data systems and privacy protocols. To make matters worse, many electronic health record (EHR) vendors are actively engaged in what is described as “information blocking.”

Stepping outside of the healthcare system, major industries have demonstrated that technology does exist to manage data sharing and analysis on this scale. Companies such as Google and Facebook have demonstrated these capabilities in the commercial sector. And one example of how bio-surveillance could be implemented is provided by the system currently in use at the US Department of Veterans Affairs (VA).

National Biosurveillance at the VA

One hospital system where a nationwide biosurveillance system is already in place is the US Veterans Health Administration (VHA). The VHA operates the largest integrated health care system in the United States, providing care at 1,255 health care facilities, including 170 VA Medical Centers and 1,074 outpatient sites of care of varying complexity (VHA outpatient clinics) to over 9 million Veterans enrolled in the VA health care program.

Data from all patients and medical encounters at these medical facilities is uploaded several times a day into Bitscopic’s Praedico platform where Artificial Intelligence algorithms can quickly scan for patterns and anomalies that warrant further investigation. This system was instrumental in detecting the first US cases of the Zika virus in 2016 when veterans in Puerto Rico began exhibiting unusual symptoms that Praedico flagged as requiring more investigation.

A more detailed discussion of the biosurveillance system used at the VA is available in the article published in Open Health News entitled Accelerating Identification and Tracking of Pandemic Disease Outbreaks.

A Screenshot from the Praedico System showing overlay data from the Veterans Health Administration (VHA) and the Department of Defense (DoD). The data being displayed is the anonymized H1N1 outbreak numbers from the 2009 flu season. The map shows the geospatial relationship between VHA and DoD data, whereas the time series graph shows the total number of influenza-like-illness (ILI) cases as well as the proportion of ILI cases over the number of all cases.

The 2019 coronavirus is not the first, nor will it be the last, pandemic spreading rapidly around the world, and this question of integrated biodefense is one that the US and all countries should consider. With falling stock markets and disrupted economies, the old adage of an ounce of prevention being preferable to many pounds of cure is very applicable.

No Man (or Country) is an Island

While much of this discussion has been focused on the United States, another lesson that the coronavirus and other pandemics makes abundantly clear is that no country can win these battles alone. The World Health Organization (WHO) has praised the measures that China has taken under difficult circumstances, but should the coronavirus spread in a country with a much weaker healthcare infrastructure, it will only be a detriment to the whole world over time.

Low-cost and effective open source electronic health solutions do exist, and again one of them, the open source VistA (EHR) was developed by the VHA as far back as the 1970s. The modest investment in helping countries that need assistance to get their hospitals up and running with such low-cost open source solutions is minuscule compared to the costs of dealing with a full-blown global pandemic.

The phrase in Chinese “Wei Ji” is described as meaning both “crisis” or “opportunity”. While translators disagree on the “opportunity” part, they do agree it also means “critical juncture”. We are definitely facing a “Wei Ji” moment now, and it is as good a time as any to really get serious about implementing the mandates from the Pandemic and All-Hazards Preparedness Act.

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