Using molecular dating tools and epidemiological simulations, researchers from the University of California School of Medicine in San Diego, with colleagues from the University of Arizona and Illumina, Inc., estimate that the SARS-CoV-2 virus was probably circulating undetected for a maximum of two months before the first human cases of COVID-19 were described in Wuhan, China, in late December 2019.
Written in the online March 18, 2021 edition of Science, they also note that their simulations suggest that the mutant virus dies naturally more than three-quarters of the time without causing an epidemic.
“Our study was designed to answer the question of how long SARS-CoV-2 may have been circulating in China before it was discovered,” said senior author Joel O. Wertheim, PhD, associate professor in the Infectious Diseases and Public Health Division. Global at UC San Diego School of Medicine.
“To answer this question, we combined three important pieces of information: a detailed understanding of how SARS-CoV-2 spread in Wuhan before the blockade, the genetic diversity of the virus in China and reports of the first cases of COVID-19 in China. By combining these disparate lines of evidence, we were able to establish a ceiling from mid-October 2019 to when SARS-CoV-2 started to circulate in Hubei province. “
COVID-19 cases were first reported in late December 2019 in Wuhan, located in central China’s Hubei province. The virus spread quickly beyond Hubei. Chinese authorities isolated the region and implemented mitigation measures across the country. In April 2020, local transmission of the virus was under control, but until then, COVID-19 was a pandemic with more than 100 countries reporting cases.
SARS-CoV-2 is a zoonotic coronavirus, believed to have jumped from an unknown host animal to humans. Numerous efforts have been made to identify when the virus began to spread among humans, based on investigations of early diagnosed cases of COVID-19. The first cluster of cases – and the first sequenced SARS-CoV-2 genomes – were associated with the Huanan Wholesale Seafood Market, but the study’s authors say the market cluster probably did not mark the beginning of the pandemic because COVID oldest documented 19 cases had no connection with the market.
Regional newspaper reports suggest that COVID-19 diagnoses in Hubei date back to at least 17 November 2019, suggesting that the virus was already actively circulating when Chinese authorities enacted public health measures.
In the new study, the researchers used evolutionary analysis of the molecular clock to try to locate when the first, or index, case of SARS-CoV-2 occurred. “Molecular clock” is a term for a technique that uses the rate of gene mutation to deduce when two or more life forms diverged – in this case, when the common ancestor of all SARS-CoV-2 variants existed, estimated in this study until mid-November 2019.
The molecular dating of the most recent common ancestor is often considered synonymous with an index case of an emerging disease. However, said co-author Michael Worobey, PhD, professor of ecology and evolutionary biology at the University of Arizona: “The index case may be earlier than the common ancestor – the first real case of this outbreak may have occurred days, weeks or even many 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 average number of people infected with SARS-CoV-2 in China was less than one until November 4, 2019. Thirteen days later, there were four individuals and only nine on December 1, 2019 The first hospitalizations in Wuhan with a condition later identified as COVID-19 occurred in mid-December.
The study authors used a variety of analytical tools to model how the SARS-CoV-2 virus may have behaved during the initial outbreak and in the early days of the pandemic, when it was a largely unknown entity and the scope of the public health threat was still unknown. not fully understood.
These tools included simulations of epidemics 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 other 70.3%, the virus infected relatively few people before dying. The average of the failed epidemic ended just eight days after the index case.
“Usually, scientists use viral genetic diversity to get the moment when a virus started to spread,” said Wertheim. “Our study added a crucial layer to this approach, modeling how long the virus could have circulated before giving rise to the observed genetic diversity.
“Our approach produced some surprising results. We saw that more than two-thirds of the epidemics we tried to simulate were extinguished. That means 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 finding supports the notion that humans are constantly bombarded with zoonotic pathogens.
Wertheim noted that even with SARS-CoV-2 circulating in China in the fall of 2019, the researchers’ model suggests that it was circulating at low levels until at least December of that year.
“Given this, it is difficult to reconcile these low levels of viruses in China with claims of infections in Europe and the United States at the same time,” said Wertheim. “I am quite skeptical of COVID-19’s claims outside of China at that time.”
The original strain of SARS-CoV-2 became epidemic, the authors write, because it was widely dispersed, which favors persistence, and because it thrived in urban areas where transmission was easier. In simulated epidemics involving less dense rural communities, epidemics were extinguished 94.5 to 99.6 percent of the time.
Since then, the virus has undergone several mutations, with several variants becoming more transmissible.
“Pandemic surveillance was not prepared for a virus like SARS-CoV-2,” said Wertheim. “We were looking for the next SARS or MERS, something that would kill people at a high rate, but in retrospect, we see how a highly transmissible virus with a modest death rate can also bring 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 Arizona and the National Science Foundation (concession 2028040).