More than a quarter of coronavirus-hit countries outside mainland China reported their first COVID-19 case in people who had recently travelled to Italy, research suggests.
Of the 99 countries identified by researchers as being affected in the 11 weeks before the global coronavirus pandemic was declared, almost two thirds of the first cases were linked to travel to Italy (27 per cent), China (22 per cent), or Iran (11 per cent), the study said.
The findings, published in The Lancet Infectious Diseases journal, suggest travel from a small number of countries with substantial transmission of the virus may have caused additional outbreaks around the world, one of the research leaders said.
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The study, by researchers from the Centres for Disease Control (CDC) and Prevention in the US, identified COVID-19 cases reported between 31 December last year through to 10 March – the day before the World Health Organisation declared the pandemic.
The CDC used official websites, press releases, press conference transcripts, and social media feeds of national ministries of health or other government agencies to gather their data.
By 10 March, they said 99 countries and locations outside mainland China had reported cases of COVID-19, and 75 of those identified their first reported case in an individual with history of travel to a country which had at least one case.
22 per cent of coronavirus cases outside China were linked to people travelling to and from the country © Getty Images
Dr Fatimah Dawood, from the CDC, said: “Our findings suggest that travel from just a few countries with substantial SARS-CoV-2 transmission may have seeded additional outbreaks around the world before the characterisation of COVID-19 as a pandemic on 11 March 2020.”
Researchers also looked at cluster frequencies and sizes by transmission settings, and found that while there were clusters of household transmission among early cases, those in occupational or community settings tended to be larger.
Co-author Dr Philip Ricks, from the CDC, said they highlighted a need to look at preventing outbreaks in faith-based settings, as well as continued work to mitigate spread in healthcare settings.
He said: “Four large clusters in our analysis, and large outbreaks reported elsewhere, have been linked with transmission in faith-based settings, highlighting the need to partner with faith-based organisations when designing and implementing community mitigation efforts.
“Six healthcare-associated clusters were also identified, underscoring the need for strict infection prevention and control practices and monitoring healthcare workers for signs of illness.”
The study authors said their work is the first of its kind to use publicly available worldwide case data to describe travel exposure and case cluster characteristics among early cases of the virus in different countries.
But they said they could not put together a complete picture of the virus in its early days because almost all the cases in their study were reported in middle-income and high-income countries from Asia and Europe.
Dr Dawood said: “The epidemiology of COVID-19 in low-income countries and in Africa could differ, as reported in previous influenza pandemics, and accurate data from these settings will be needed to assess the full global effect of the COVID-19 pandemic.”
What is the R number, and why is it relevant to coronavirus?
The reproduction number – often called the R value or R number – is a measure of a disease’s ability to spread. It tells us how many people a single infected person will pass on the disease to.
The R number for COVID-19 that’s being quoted in the media and government briefings is what’s known as the ‘effective’ reproduction number. This value can go up and down.
We can reduce R by making it harder for the disease to spread, by implementing measures such as social distancing, closing restaurants and non-essential shops, and encouraging people to stay at home.
Every disease also has what’s called a ‘basic’ reproduction number, R0, which is the fixed value of R if no measures are put in place. For example, measles is highly contagious, with a R0 as high as 18, while COVID-19 has a R0 of around three.
So if COVID-19 was allowed to spread through the population, an infected person would, on average, give the disease to three other people.
But if all these people are practising physical distancing, then the virus can’t spread so easily and the effective R value goes down.
The crucial thing is to keep R below 1. If we can do this, then the number of new cases dwindles and the outbreak will eventually come to a halt.
Conversely, if R rises above 1, then we run the risk of rapidly escalating case numbers that would require stronger measures to keep the virus under control.
Because of this, R is used by governments to assess how we are doing in our efforts to stop the spread of COVID-19, and to adjust our actions, if needed.