As more and more people around the world are vaccinated, you can almost feel the collective sigh of relief. But the upcoming pandemic threat is probably already making its way through the population right now.
My research as infectious disease The epidemiologist has found that there is a simple strategy to mitigate emerging outbreaks: proactive, real-time surveillance in environments where disease overflow between humans is more likely to occur.
In other words, don’t expect sick people to show up at a hospital. Instead, control the populations where the disease actually spills.
The current pandemic prevention strategy
World health professionals have long known that pandemics feed off spill of zoonotic disease, or the transmission of diseases between animals and humans, were a problem. In 1947, the World Health Organization established a worldwide network of hospitals in detect pandemic threats through a process called syndromic surveillance. The process is based on standardized symptom checklists to look for signs of emerging or re-emerging diseases of pandemic potential among patient populations with symptoms that cannot be easily diagnosed.
There is only one problem: when someone sick shows up at a hospital, an outbreak has already occurred. In the event that SARS-CoV-2, the virus that causes COVID-19, probably spread long before it was detected. This time, we have only failed the clinical strategy.
The overflow of zoonotic disease is not a fact
One more proactive approach it is currently gaining prominence in the world of pandemic prevention: viral evolutionary theory. This theory suggests that animal viruses become dangerous human viruses incrementally over time through frequent zoonotic spillage.
This is not a single agreement: it may be necessary for an “intermediate” animal such as a civet cat, a pangolin, or a pig to mutate the virus so that it can make initial jumps in people. But the final host that allows a variant to fully adapt to humans may be themselves.
Viral evolutionary theory is developed in real time with the rapid development of COVID-19 variants. In fact, an international team of scientists has proposed that undetected transmission from one man to another after a jump from one animal to another is likely. origin of SARS-CoV-2.
When new outbreaks of zoonotic viral diseases such as Ebola first came to global attention in the 1970s, research on the extent of disease transmission was based on antibody assays, blood tests to identify people who have already been infected. Antibody surveillance, also called serious survey, test blood samples from target populations to identify how many people have become infected. Serous surveys help determine if diseases like Ebola are circulating undetected.
It turns out that they were: antibodies against Ebola were found in more than 5% of people tested in Liberia in 1982, decades before the West African epidemic in 2014. These results support viral evolutionary theory: it takes time (sometimes a long time) to make an animal virus dangerous and transmissible among humans.
This also means that scientists have the opportunity to intervene.
Measurement of zoonotic disease overflow
One way to take advantage of delivery time for animal viruses to fully adapt to humans is long-term repeated surveillance. Setting one pandemic threat alert system with this strategy in mind it could help you detect pre-pandemic viruses before they are harmful to humans. And the best place to start is straight to the source.
My team worked virologist Shi Zhengli of the Wuhan Institute of Virology to develop a human antibody assay to test a very distant cousin of SARS-CoV-2 found in bats. We established zoonotic spill tests in a small 2015 serum survey in Yunnan, China: 3% of study participants living near bats carrying this SARS-like coronavirus tested the antibody positive. But there was an unexpected result: none of the previously infected study participants reported harmful health effects. The first outbreaks 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 didn’t do such a thing.
The researchers conducted a larger study in southern China between 2015 and 2017. It is a region where there are bats known to carry SARS-like coronaviruses, including the one that caused the original SARS pandemic of 2003 and the one more related to SARS-CoV-2.
Less than 1% of participants in this study tested positive for antibodies, that is, they had previously been infected with the SARS-like coronavirus. Again, none of them reported negative health effects. But syndromic surveillance — the same strategy used by sentinel hospitals — revealed something even more unexpected: an additional 5% of community participants reported symptoms consistent with SARS over the past year.
This study provided more than just the biological evidence needed to establish a proof of concept to measure zoonotic spillage. The pandemic threat alert system also picked up a signal for a SARS-like infection that could not yet be detected by blood tests. He may even have detected the first variants of SARS-CoV-2.
If surveillance protocols had been established, these results would have triggered a search for community members who may have been part of an undetected outbreak. But without an established plan, the signal was lost.
From prediction to surveillance to genetic sequencing
Most of the funding and pandemic prevention effort in the last two decades has focused on the discovery of wildlife pathogens and the prediction of pandemics before animal viruses can infect humans. But this approach has not predicted any major outbreak of zoonotic diseases, including the H1N1 flu in 2009, the MERS in 2012, the Ebola epidemic in West Africa in 2014, or the current COVID-19 pandemic.
However, predictive modeling has provided robust heat maps of the global “hot spots” where a zoonotic spill is more likely to occur.
Regular, long-term monitoring of these “hot spots” could detect signs of spillage, as well as any changes that occur over time. These could include an increase in people with positive antibodies, an increase in disease levels, and demographic changes among infected people. As with any proactive surveillance of the disease, if a signal is detected, an investigation of the outbreak would be followed. People identified with symptoms that cannot be easily diagnosed it can be examined by genetic sequencing to characterize and identify new viruses.
This is exactly what Greg Gray and his Duke University team did in their research undetected coronavirus in rural Sarawak, Malaysia, a well-known “hot spot” for zoonotic spills. Eight of the 301 specimens collected from patients with pneumonia hospitalized in 2017-2018 were found to have canine coronavirus never seen in humans. Complete sequencing of the viral genome not only suggested that it had recently jumped from an animal host, but also harbored the same mutation that made both SARS and SARS-CoV-2 so deadly.
We don’t miss the next pandemic warning sign
The good news is that there is already a surveillance infrastructure in the world’s “hot spots”. He Liaison organizations for regional disease surveillance the program links six regional disease surveillance networks to 28 countries. They pioneered “participant surveillance,” in collaboration with communities at high risk of both initial zoonotic spillage and severe health outcomes to contribute to prevention efforts.
For example, Cambodia, a country at risk of a bird flu pandemic spill, established a free national hotline for community members to report animal diseases directly to the Ministry of Health in real time. Field approaches such as these are key to a timely and coordinated public health response to stop outbreaks before they become pandemics.
It is easy to lose warning signs when global and local priorities are tentative. The same mistake does not have to happen again.
Citation: Targeted disease surveillance can help prevent the next pandemic (2021, June 2) recovered on June 2, 2021 at https://medicalxpress.com/news/2021-06-disease-surveillance-pandemic.html
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