As more and more people around the world are vaccinated, one can almost hear the sigh of collective relief. But the next pandemic threat is probably already making its way through the population right now.
My research as an epidemiologist from infectious diseases has found that there is a simple strategy to reduce new outbreaks: proactive monitoring in real time in environments where infection from animals to humans is most likely to occur.
In other words, do not wait for sick people to show up at a hospital. Instead, you need to monitor populations where disease outbreaks actually occur.
The current pandemic prevention strategy
Global healthcare professionals have long known that pandemics driven by the release of zoonotic disease, or the transmission of animals to humans, were a problem. In 1947, the World Health Organization set up a global network of hospitals to detect pandemic threats through a process called syndromic surveillance. The process relies on standardized symptom checklists to look for signals of new or re-emergence diseases of pandemic potential among patient populations with symptoms that cannot be easily diagnosed.
This clinical strategy depends on infected people coming to sentinel hospitals and medical authorities who are influential and persistent enough to sound the alarm.
There is only one problem: When a sick person shows up at a hospital, an outbreak has already occurred. In the case of SARS-CoV-2, the virus that causes COVID-19, it was probably widespread long before it was discovered. This time, the clinical strategy alone failed us.
Zoonotic disease release is not one and is finished
A more proactive approach is currently playing a prominent role in the world of pandemic prevention: viral theory of evolution. This theory suggests that animal viruses become dangerous human viruses gradually over time through frequent zoonotic releases.
It is not a one-time deal: An “intermediary” such as a civet cat, pangolin or pig may be required to mutate the virus so that it can make the first jump to humans. But the last host who allows a variant to be fully adapted to humans, may be humans themselves.
Viral evolution theory plays in real time with the rapid development of COVID-19 variants. In fact, an international team of researchers has suggested that undetected human-to-human transmission after an animal-to-human jump is the likely origin of SARS-CoV-2.
When new zoonotic viral outbreaks such as Ebola first became the world’s attention in the 1970s, research on the extent of disease transmission depended on antibody analyzes, blood tests to identify people who have already been infected. Antibody monitoring, also called serosurveys, tests blood samples from target populations to identify how many people have been infected. Serosurveys help determine if diseases such as Ebola are circulating undetected.
It turns out they were: Ebola antibodies were found in more than 5% of those tested in Liberia in 1982, decades before the West African epidemic in 2014. These results support viral evolutionary theory: It takes time – sometimes a lot of time – to make an animal virus dangerous and transmissible between humans.
What this also means is that researchers have a chance to intervene.
Measurement of emissions of zoonotic disease
One way to take advantage of the lead time for animal viruses to fully adapt to humans is long-term, repeated monitoring. Setting up a pandemic threat alert system with this strategy in mind can help detect pre-pandemic viruses before they become harmful to humans. And the best place to start is directly at the source.
My team worked with virologist Shi Zhengli of the Wuhan Institute of Virology to develop a human antibody assay to test for a very distant cousin of SARS-CoV-2 that was found in bats. We established evidence of zoonotic overflow in a small serosurvey from 2015 in Yunnan, China: 3% of study participants living near bats carrying this SARS-like coronavirus tested antibody positive. But there was one unexpected result: None of the previously infected participants reported any adverse health effects. Previous releases of SARS coronavirus – such as the first SARS epidemic in 2003 and the Middle East Respiratory Syndrome (MERS) in 2012 – had caused high levels of disease and death. This one did not do such a thing.
Researchers conducted a major study in southern China between 2015 and 2017. It is a region home to bats that is known to have SARS-like coronavirus, including the one that caused the original SARS pandemic in 2003 and the one most closely linked to SARS-CoV-2.
Less than 1% of the participants in this study tested antibody-positive, which means that they were previously infected with the SARS-like coronavirus. Again, none of them reported adverse health effects. But syndrome monitoring – the same strategy used by sentinel hospitals – revealed something even more unexpected: Another 5% of community participants reported symptoms consistent with SARS in the past year.
This study provided more than just the biological evidence needed to establish evidence for the concept of measuring zoonotic spillage. The pandemic threat warning system also picked up a signal for a SARS-like infection that could not yet be detected through blood tests. Early variants of SARS-CoV-2 may even have been detected.
Had surveillance protocols been in place, these results would have triggered a search for members of society that may have been part of an undetected outbreak. But without an established plan, the signal was missed.
From prediction to monitoring to genetic sequencing
The bulk of funding and efforts for pandemic prevention over the past two decades have focused on detecting pathogens from wildlife, and predicting pandemics before animal viruses can infect humans. But this approach has not predicted any major zoonotic outbreaks – including H1N1 flu in 2009, MERS in 2012, the West African Ebola epidemic in 2014 or the current COVID-19 pandemic.
Predictive modeling, however, has provided robust heat maps of the global “hot spots” where zoonotic spillover is most likely to occur.
Prolonged, regular monitoring of these “hot spots” can detect overflow signals, as well as any changes that occur over time. These may include an increase in antibody-positive individuals, increased levels of disease and demographic changes among infected people. As with any proactive disease surveillance, if a signal is detected, an outbreak examination will follow. Individuals identified with symptoms that are not easily diagnosed can then be screened using genetic sequencing to characterize and identify new viruses.
This is exactly what Greg Gray and his team from Duke University did in their search for undetected coronavirus in rural Sarawak, Malaysia, a famous “hot spot” for zoonotic emissions. Eight of 301 specimens collected from pneumonia patients hospitalized in 2017-2018 were found to have a coronavirus from the dog that has never been seen in humans before. Complete virus sequencing not only indicated that it had recently jumped from an animal host – it also had the same mutation that made both SARS and SARS-CoV-2 so deadly.[[[[The conversation’s most important coronavirus headlines, weekly in a scientific newsletter]
Let’s not miss the next pandemic warning signal
The good news is that surveillance infrastructure in global “hot spots” already exists. The Connecting Organizations for Regional Disease Surveillance program connects six regional disease surveillance networks in 28 countries. They were groundbreaking for “participant monitoring”, and collaborated with communities at high risk for both initial zoonotic discharges and the most serious health outcomes to contribute to prevention efforts.
For example, Cambodia, a country at risk of avian influenza pandemic, established a free national hotline for community members to report animal diseases directly to the Ministry of Health in real time. Boots-on-the-ground approaches such as these are the key to timely and coordinated public health preparedness to stop outbreaks before they become pandemics.
It is easy to miss warning signs when global and local priorities are preliminary. The same mistake does not have to happen again.
This article is republished from The Conversation, an ideal news site dedicated to sharing ideas from academic experts. It was written by: Maureen Miller, Columbia University.
Maureen Miller received funding from USAID which was used to develop the pandemic threat alert system discussed in this article.