Backtracking infection models suggest the first COVID-19 case occurred earlier than previously thought.
Researchers from Kent University in the UK have shown that the first coronavirus disease (COVID-19) patient likely dates back to October 2019. They also found that the spread to other continents of its causative pathogen – the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) – occurred faster and sooner.
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Earlier origin and faster global spread of COVID-19
Since the onset of the COVID-19 pandemic, researchers have attempted to retrace the infectious routes of the SARS-CoV-2. Key questions have focused on the dates the virus arrived in different countries. The first officially identified case occurred in early December 2019, but new research is now showing the first cases likely occurred sooner.
Researchers from Kent University led by David Roberts published their findings on the likely beginnings of the COVID-19 pandemic in the open-access journal PLOS Pathogens.
Using a mathematical model initially developed for conservation science examining species extinction events based on sightings, Roberts and colleagues repurposed models using scenarios to retrace the COVID-19 timeline.
To date back to the origins of COVID-19, the team reversed the mathematical models and used data from the earliest known cases across 203 countries.
Findings indicated that the first case occurred in China between early October and mid-November 2019. The most likely scenario showed that the first case arose on November 17, and the disease spread globally by January 2020.
Additionally, models also identified when COVID-19 spread to the first 5 countries outside of China.
Estimates show that the first case beyond China was in Japan on January 3, 2020, and the first European case was in Spain on January 12, 2020. In North America, the first case of infection occurred in the US on January 16, 2020.
This suggests that the pandemic arose sooner and spread faster as well as further than previously recognized.
Adapting interdisciplinary methods, but with caution
The adaptation and use of extinction-based models to understand the current pandemic is particularly insightful as viral infection patterns may possess similar characteristics to population extinctions. This includes data on population dynamics, genetic diversity, and environmental factors involved.
The method we used was originally developed by me and a colleague to date extinctions, however, here we use it to date the origination and spread of COVID-19. This novel application within the field of epidemiology offers a new opportunity to understand the emergence and spread of diseases as it only requires a small amount of data.”
David Roberts, lead author of the study.
However, caution must be used when interpreting the results of such analyses as correlations and causations may be confounded by the difference in the nature of the data. Nevertheless, computational models across different disciplines of science may provide new information for studying epidemiological dynamics.
The scientists noted that this novel method could be further applied to understand the spread of COVID-19 across other countries and in tracing the spread of new SARS-CoV-2 variants as well. The quality and quantity of data available will improve model accuracy to examine patterns of infection in hindsight, which can then be used to project potential patterns into the future.
A better understanding of the exact origins of COVID-19 could improve the knowledge of how the virus spreads, and how fast it is able to do so. This, in turn, can help shape policies of containment.