Using molecular dating tools and epidemiological simulations, researchers at the University of California San Diego School of Medicine, along with colleagues from the University of Arizona and Illumina, Inc. , estimate that the SARS-CoV-2 virus probably circulated undetected for up to two months. before the first human cases of COVID-19 were described in Wuhan, China at the end of December 2019.
Written in the March 18, 2021 online issue of Science, they also note that their simulations suggest that the mutant virus naturally goes out more than three-quarters of the time without causing an outbreak.
“Our study was designed to answer the question of how long could SARS-CoV-2 circulate in China before it was discovered,” said lead author Joel O. Wertheim, PhD, professor. associated with the Division of Infectious Diseases and Global Public Health. at UC San Diego School of Medicine.
“To answer this question, we have combined three important pieces of information: a detailed understanding of the spread of SARS-CoV-2 in Wuhan before the lockdown, the genetic diversity of the virus in China, and reports of the first cases of COVID-19 in China. By combining this disparate evidence, we were able to set an upper limit in mid-October 2019 for when SARS-CoV-2 started circulating in Hubei province. “
Cases of COVID-19 were first reported in late December 2019 in Wuhan, located in central China’s Hubei province. The virus quickly spread beyond Hubei. Chinese authorities have cordoned off the region and implemented mitigation measures across the country. As of April 2020, local transmission of the virus was under control but, at that time, COVID-19 was pandemic with more than 100 countries reporting cases.
SARS-CoV-2 is a zoonotic coronavirus, which is believed to have jumped from an animal host unknown to humans. There have been many efforts to identify when the virus began to spread in humans, based on investigations of early diagnosed cases of COVID-19. The first cluster of cases – and the first sequenced SARS-CoV-2 genomes – have been linked to the Huanan Seafood wholesale market, but the study’s authors say the market cluster likely did not mark the beginning. pandemic, because the first documented COVID -19 cases were unrelated to the market.
Regional newspaper articles suggest that diagnoses of COVID-19 in Hubei date back to at least November 17, 2019, suggesting that the virus was already actively circulating when Chinese authorities adopted public health measures.
In the new study, the researchers used analyzes of the evolution of the molecular clock to try to determine when the first case, or clue, of SARS-CoV-2 occurred. “Molecular clock” is a term for a technique that uses the rate of gene mutation to infer when two or more life forms have diverged – in this case, when the common ancestor of all SARS-CoV variants – 2 existed, estimated in this study until mid-November 2019.
Molecular dating of the most recent common ancestor is often considered synonymous with the index case of emerging disease. However, said co-author Michael Worobey, PhD, professor of ecology and evolutionary biology at the University of Arizona: “The index case can presumably predate the common ancestor – the first real case of this. epidemic may have occurred days, weeks, or even several months before the estimated common ancestor. Determining the length of this “phylogenetic fuse” was at the heart of our investigation. “
Based on this work, the researchers estimate that the median number of people infected with SARS-CoV-2 in China was less than one until November 4, 2019. Thirteen days later, it was four people, and only new on December 1, 2019. The first hospitalizations in Wuhan with a condition later identified as COVID-19 took place in mid-December.
The study authors used various analytical tools to model the behavior of the SARS-CoV-2 virus during the initial outbreak and the early days of the pandemic when it was a largely unknown entity and the scope of the threat to public health was not yet fully realized. .
These tools included epidemic simulations based on the known biology of the virus, such as its transmissibility and other factors. In only 29.7% of these simulations, the virus was able to create self-sustaining epidemics. In the remaining 70.3%, the virus infected relatively few people before becoming extinct. The average failed outbreak ended just eight days after the index case.
“Typically, scientists use viral genetic diversity to find out when a virus has started to spread,” Wertheim said. “Our study added a crucial layer to this approach by modeling how long the virus could have circulated before giving rise to the observed genetic diversity.
“Our approach has yielded surprising results. We have seen that over two-thirds of the epidemics we tried to simulate have disappeared. This means that if we could go back in time and repeat 2019 a hundred times, two out of three times, COVID-19 would have failed on its own without triggering a pandemic. This discovery confirms the idea that humans are constantly bombarded with zoonotic agents. “
Wertheim noted that although SARS-CoV-2 was circulating in China in the fall of 2019, the researchers’ model suggests that it was doing so at low levels until at least December of this year.
“Given this, it is difficult to reconcile these low levels of the virus in China with claims of infections in Europe and the United States at the same time,” Wertheim said. “I am quite skeptical of the COVID-19 allegations outside of China at this time.”
The original strain of SARS-CoV-2 became epidemic, the authors write, because it was widely dispersed, which promotes persistence, and because it thrived in urban areas where transmission was easier. In simulated epidemics involving less dense rural communities, the epidemics died out 94.5 to 99.6% of the time.
The virus has since mutated several times, with a number of variants becoming more transmissible.
“Pandemic surveillance was not prepared for a virus like SARS-CoV-2,” Wertheim said. “We were looking for the next SARS or MERS, something that has killed people at a high rate, but looking back we see how a highly transmissible virus with a modest death rate can also throw the world down.”
Co-authors include: Jonathan Pekar and Niema Moshiri, UC San Diego; and Konrad Scheffler, Illumina, Inc.
Funding for this research came in part from the National Institutes of Health (grants AI135992, AI136056, T15LM011271), the Google Cloud COVID-19 Research Credits Program, the David and Lucile Packard Foundation, the University of the Arizona and the National Science Foundation. (grant 2028040).