Global surveillance networks
Expanding networks & sequencing
Dedicated global surveillance of high-risk pathogens can speed identification of Disease X, which will be crucial to achieving the 100 days mission.
At one minute to midnight on 30th December 2019, the global disease tracking site ProMED published a worrying post. It highlighted an urgent notice issued earlier that day by the Wuhan Municipal Health Committee, warning of patients arriving at local medical facilities with pneumonia of an unknown cause.
Over the next couple of months, infections—quickly sequenced and shown to be caused by a novel coronavirus, later named SARS-CoV-2—were reported in other cities across China, as well as Japan, Singapore, Korea, Italy, and other regions, before encroaching on all corners of the Earth. By late March 2020, it was estimated that around one in five people around the world were in lockdown, ordered to stay at home in an attempt to halt the viral spread.
Despite these warnings proving key to tracking and alerting the world to the looming crisis, the world didn’t respond quickly enough. Scientists now believe that, as a result of the deadly virus being allowed to spread among populations unchecked, it is unlikely we will ever be able to truly eradicate COVID-19.
We cannot be caught unawares by another deadly pathogen with epidemic or even pandemic potential. Vigilance, in the form of greater and faster disease surveillance, is key to move from a recurring cycle of ‘panic and neglect’ to a world that is properly prepared.
“We need a global early warning system to respond to the next pandemic threat” explains Gabrielle Breugelmans, Head of Epidemiology at CEPI. “This is especially important as, with climate change and rapidly changing ecology, deforestation, urbanization, and travel habits, outbreaks are likely to become more frequent. They could also be far worse than COVID-19’s impact today.”
“Such a system would allow CEPI, and the world, to push forward the ambition to quickly identify and track novel pathogens so that it can sequence them and build lifesaving vaccines within a 100-days timeline.”
Using John Snow’s approach in the 21st century
Previous outbreaks have typically been detected through healthcare workers and other experts reporting unusual clusters of patients with serious symptoms and potentially excess deaths.
This tried-and-tested strategy was used as part of Dr John’s Snow’s famous investigations into the cause of 19th century cholera epidemics in Soho, London. More recently, it was used during the recent West African Ebola epidemic in 2014-2016 and the Zika outbreak in Brazil in 2015.
We have also seen the same epidemiological tracking approach play out today, with many of those infected with SARS-CoV-2 (the virus that causes COVID-19) displaying a variety of symptoms, with those most sick filling up hospital beds within ICUs.
“Unlike other global disasters, COVID-19 and future outbreaks present a unique challenge – where populations are having to grapple with and respond to an unseen being” says Breugelmans. “But, while SARS-CoV-2 may be invisible, its devastating health impact is evident worldwide and this detection of illness is what enables us to start our response.”
Getting ahead of the game
While advantageous, this method of disease surveillance is, primarily, a reactive and passive measure. By the time a cluster of patients gets sick enough for the virus to be detected and an alert is raised, a virus may, to an extent, already spread.
In recent decades, scientists have therefore taken efforts one step further – hunting for viruses before they even infect humans.
Reports suggest that 75 percent of emerging infectious diseases in humans originate from animals and it is estimated that there are more than a million undiscovered viruses lurking in wildlife potentially capable of infecting people.
Surveillance of wildlife for novel pathogens has consequently become part of global disease detection strategies, as this could allow for the discovery of pre-pandemic viruses before they make their harmful leap into humans.
For example, from 2009-2019, the USAID-funded PREDICT programme collected over 140,000 biological samples from various animals in potential disease hotspots. Their work identified over 1200 viruses with the potential to cause human disease and pandemics, including over 160 novel coronaviruses. DEEP VZN has now been created by USAID as a follow-up to better understand and address the risks posed by zoonotic diseases and the Global Virome Project is another initiative set up to strengthen local abilities to monitor viral spillover.
The role of Artificial Intelligence
Computer scientists too have joined the pandemic hunt. Researchers now employ cutting edge techniques, like machine learning, to predict the likelihood of spillover events and to inform both field and laboratory research. Other methods utilise artificial intelligence to flag when multiple news reports start to hint at any new or unusual symptoms emerging in a cluster of patients.
These innovative algorithms and Big Data approaches to disease surveillance have even been applied from outer space. In recent years, orbiting NASA satellites have monitored daily changes in the Earth’s environment (eg, climate, rainfall, vegetation coverage in an area) and used these data to identify areas at risk of malaria and Rift Valley fever outbreaks, giving authorities time to plan ahead.
Bringing it all together
Taken together, the use of traditional epidemiological disease surveillance tools, viral monitoring in animals, genomic sequencing, and artificial intelligence are the vital ingredients for creating a groundbreaking global disease warning system—a system capable of speeding up the identification of the next Disease X, quickly alerting scientists and developers to trigger vaccine R&D, and enabling development of safe and effective vaccines in 100 days.
Such a global warning system—which could span wildlife, livestock, and human populations—can build on a wealth of existing surveillance systems set up to monitor and track single diseases, like HIV, TB, and malaria, to conduct viral surveillance for the early detection of disease spillover into human populations in real-time, while also identifying and tracking ‘hot spots’ of human disease in parallel. If the system found a new animal virus or pockets of new infections, we could rapidly alert health authorities to pre-emptively contain transmission at a local scale before it becomes a larger crisis.
Crucially, this global network must cover both pandemic and non-pandemic periods across all areas, including low- and middle-income countries where, despite having some of the world’s greatest disease burden, current disease monitoring structures and epidemiological capacity remain scarce and sub-optimal.
The local ‘lookouts’ would also need to be linked to a network of international hubs which, when alerted, could begin swift genetic sequencing to provide insight into the pathogen and guide the rapid development of safe and effective countermeasures, supported by CEPI and others.
As demonstrated by the work of the GISAID initiative, where over 5 million SARS-CoV-2 have been made available on a publicly accessible platform, the quick global sourcing and sharing of data, alongside considerations around governance, will be crucial to enabling such a system to work. Harnessing the work of new initiatives like the world-first WHO Pandemic Intelligence Hub in Berlin will help achieve this vision.
No stone unturned
With such a system in place, the world can be better prepared for the next epidemic or pandemic threat – wherever or whenever it may appear.
On the vaccine front, the quick tracking and alerting of potential viral spillovers or clusters of new symptoms would enable CEPI’s enabling sciences, vaccine R&D, and manufacturing partnerships to spring into action, and work to create vaccines within 100 days.
“To avoid the next pandemic, we’ve got to move fast, and we must always be on the lookout” says Breugelmans. “We must leave no stone unturned.”
Find out more about the 100 days mission here.