by Chandana Balasubramanian
In 2019, a crew of nine pilots and astronauts broke a world record. They flew around the Earth in just 46 hours. More incredible is that they did not fly in a never-before-seen, advanced aircraft prototype. They flew a commercially available jet plane.
The future is already here.
Based on the new world record, it could take less than a weekend for an emerging infectious disease to spread all over the globe. And chances are, it may take a week or more before it gets detected based on the incubation period.
Unfortunately, healthcare providers at the frontlines of infectious disease management face a significantly higher risk of infection. The risk extends beyond healthcare workers to their families and communities.
As the world grapples with the impact of COVID-19 and its mutations, it’s a good time to ask: What can health systems worldwide do to detect emerging infectious diseases imported from other countries early?
Recent research empirically demonstrated that local outbreaks of various Infectious Diseases could “quickly spread to other countries through the international movement of people and goods, with potentially disastrous health consequences .”
While this fact may not be news to clinicians and Infectious Disease specialists, the study also shows a close spatial dependence between the health conditions in one country and another – a spillover effect. The study used GIDEON (Global Infectious Disease and Epidemiology Online Network), a database covering all Infectious Disease outbreaks.
An epidemic in one country can become a pandemic in others – irrespective of travel and other physical barriers to entry. Studies of previous epidemics show that even a 90% travel restriction between countries merely delays the arrival of an emerging infection by a few weeks. Another study by Quilty et al. reported that airport-based screening measures to detect COVID-19 missed 46% of cases because of the incubation period .
So, while a travel ban and thermal screening can help a country buy some time to prepare for an outbreak, epidemic, or pandemic, they cannot stop or prevent a new infection from spreading to foreign shores.
Travel has always been one of the fastest ways to introduce a pathogen to a new environment. And as two clinicians, Trish Perl and Connie Savor Price, argue in a recent ‘Annals of Internal Medicine’ article, travel history must be treated as the fifth vital sign in emergency rooms and all physician evaluations .
The doctors make a strong case that including a patient’s travel history as part of a vital signs check can “help put symptoms of infection in context and trigger us to take a more detailed history, do appropriate testing, and rapidly implement protective measures.”
Monkeypox in the UK, 2021
For example, in May 2021, the World Health Organization received notification from the United Kingdom of a confirmed case of monkeypox in an individual who had just traveled from Nigeria. Monkeypox has an incubation period of six to thirteen days, but according to WHO, it can range anywhere from five to twenty-one days. Eventually, the infection spread to another family member, and they were isolated. Differential diagnosis considerations for monkeypox include chickenpox, measles, bacterial infections, scabies, syphilis, and medication-associated allergies. In such a case, taking the patient’s travel history can help healthcare workers take the necessary precautions even before the PCR results.
COVID-19 in the United States, 2019
The first case of COVID-19 in the US was reported in Washington when the patient returned from Wuhan, China. Based on the patient’s travel history and symptoms, healthcare professionals could isolate and send clinical specimens to be tested by the CDC overnight. Hospitals in the United States were already on alert for patients from Wuhan presenting with symptoms, and testing could be prioritized accordingly.
Ebola in the United States, 2014
Let’s look at an example where a patient’s travel history would have helped protect healthcare professionals. In 2014, a man traveled from West Africa and admitted himself into a hospital in Dallas with fever, abdominal pain, dizziness, headache, and nausea. Without an integral piece of the puzzle – his travel history – he was treated for sinusitis and sent home. The hospital suspected Ebola only when he returned three days later with persistent fever, abdominal pain, and diarrhea. Unfortunately, within this time, this patient had infected healthcare professionals, ambulance transport personnel, and the patient’s caregivers.
Monkeypox and Ebola are not as contagious as COVID-19 and its variants, and Ebola is not contagious until symptoms appear, making containment easier. But emerging infectious diseases and their variants might be.
Infectious Disease specialists, clinicians, researchers, and medical librarians will need to be vigilant against the next outbreak. Epidemiological data plays an integral role in facilitating improved clinical decisions and saved lives.
In a GIDEON survey of 363 clinicians in the US, UK, and Canada, 35% stated that they would consult a colleague for a second opinion before making clinical decisions. As a close second, 30% indicated that they trust their judgment. This means that 65% of the survey respondents trusted human judgment over Point-of-Care tools.
But the stakes are higher when dealing with highly transmissible emerging infections. The importance of first-time diagnosis accuracy is compounded due to the rising urgency to prevent the next epidemic or pandemic.
Consider the dramatic difference in transmission rates between SARS-CoV-2 and its variants:
Here are some comparisons of how newer, emerging pathogens and their variants compare to older, Infectious Diseases.
|Pathogen||Transmissibility Rate (R0)|
|B.1.617.2, SARS-CoV-2 Delta variant||5-8|
|B .1. 1. 7, SARS-CoV-2 Alpha Variant||4-5|
In other words, an outbreak may already be well underway before an Infectious Disease specialist is consulted for assistance on differential diagnosis or a medical librarian is requested for location-specific disease symptoms.
As pathogens mutate, traditional methods of differential diagnosis need an upgrade. Clinicians, Infectious Disease specialists, and researchers need data from local outbreaks anywhere in the world at their fingertips to help drive decision-making and advance the global effort against Infectious Disease.
Drs Perl and Price champion the need for greater access to digital resources that integrate electronic health records with patient travel histories and can “suggest specific diagnoses in febrile returning travelers.”
One of the more well-known DDx tools is GIDEON with its First Case Scenario feature, created in partnership with the World Health Organization (WHO) after the West Nile Fever outbreak in the United States.
Using a DDx platform such as GIDEON helps:
Why is this important? Because, for example, in respiratory viral illnesses, early detection is the critical step to mitigate disease transmission but is often delayed . Depending on the type of pathogen, this could lead to a greater number of hospitalizations, more morbidity, a burden on healthcare systems, and have significant ramifications on a country, its people, and the economy.
Having a differential diagnosis platform that incorporates a patient’s travel history can make a huge difference in how the world manages emerging infectious diseases.
Here’s an example. Suppose a patient presents with elevated body temperature, severe headache, chills, myalgia, diarrhea, and malaise.
These are nonspecific presentations and could be representative of a variety of diseases. With international transmission now the norm, no clinician can be expected to keep track of every single emerging disease and its symptoms.
Step 1: Focusing on most likely diseases based on symptoms and travel information
Entering a patient’s symptoms and the locations and dates of travel in a tool like GIDEON’s Bayesian analysis-driven Probability engine can help identify what diseases are most likely to correspond to the data entered. The illustration below shows Ebola as a high probability based on the patient’s symptoms and travel location.
Step 2: Conduct a differential diagnosis
The screenshot of the First Case Scenario feature below shows a 95% probability that the patient has Ebola. What if there were fewer symptoms at presentation, the likelihood of Ebola was 65%, and another disease was 25% probable? You could conduct a differential analysis by comparing the two disease symptoms on the platform, download the comparison, and order the requisite laboratory tests to confirm.
Step 3: First Case Scenario
Imagine it is 2014, and you haven’t heard of Ebola. A patient walks in with the symptoms listed above. You enter the symptoms and the patient’s travel history. Using GIDEON’s First Case Scenario, you can determine how likely it is that your patient is the first in the country to present with Ebola.
Based on a GIDEON survey of 230 clinicians in the US, UK, and Canada, while clinicians were open to using a DDx tool to help diagnose Infectious Diseases, a lack of budget was the primary reason they did not.
One physician even stated, “I would use them every day if my institution would offer.”
But an interactive platform with a robust database of Infectious Disease symptoms that incorporates patient locations, exposure to disease-causing elements, and comparisons between two or more similar diseases can offer benefits beyond what a seasoned clinician can accomplish.
It can train the next generation of Infectious Disease-fighting doctors and healthcare professionals. For example, take GIDEON’s step-by-step Bayesian analysis toolkit. Teaching institutions, medical librarians, medical students, residents, researchers, and more can use DDx tools to help hone their diagnoses of emerging as well as well-known infectious diseases.
The tool helps you list symptoms, patient travel information (if any), and any exposure to disease-causing elements (if known). For example, the patient ate chicken in a region that recently had a Salmonella outbreak.
The tool offers a list of probable diseases in descending order of probability. It helps that the tool is dynamic because what if the patient forgot a symptom and told you about it later? A new list of probable diseases is re-calculated automatically. An added benefit is that the DDx tool is integrated with the First Case Scenario to determine if a patient’s symptoms are the first in a specific location.
Health systems and medical colleges and universities may benefit greatly from such a diagnostic solution.
War often provides an opportunity for innovation. After all, the internet was invented because computers at the time were enormous, and it was incredibly difficult to physically transport military intel from the United States to soldiers deployed around the world . And clinicians are actively in a battle against the spread of infectious pathogens.
A global platform that offers timely location-specific intelligence about emerging infectious diseases and helps speed up clinical decisions is invaluable to future-proof the world against outbreaks, epidemics, and pandemics and save thousands of lives.
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 R. Desbordes, “Spatial dynamics of major Infectious Diseases outbreaks: A global empirical assessment,” J. Math. Econ., vol. 93, no. 102493, p. 102493, 2021.
 B. J. Quilty, S. Clifford, S. Flasche, R. M. Eggo, and CMMID nCoV working group, “Effectiveness of airport screening at detecting travellers infected with novel coronavirus (2019-nCoV),” Euro Surveill., vol. 25, no. 5, 2020.
 T. M. Perl and C. S. Price, “Managing emerging Infectious Diseases: Should travel be the fifth vital sign?” Ann. Intern. Med., vol. 172, no. 8, pp. 560–561, 2020.
 N. G. Davies et al., “Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England,” Science, vol. 372, no. 6538, p. eabg3055, 2021.
 Scientific Advisory Group for Emergencies, “Imperial College London: Evaluating the roadmap out of lockdown – modelling Step 4 of the roadmap in the context of B.1.617.2 (Delta), 9 June 2021,” Gov.uk, 14-Jun-2021. [Online]. Available: https://www.gov.uk/government/publications/imperial-college-london-evaluating-the-roadmap-out-of-lockdown-modelling-step-4-of-the-roadmap-in-the-context-of-b16172-delta-9-june-2021. [Accessed: 15-Jun-2021].
 B. Tarnoff, “How the internet was invented,” The Guardian, 15-Jul-2016.