Global COVID infections can be 6 times higher than reported: study
Published : Thursday, 19 November, 2020 at 6:35 PM Count : 222
According to modeling studies, the actual worldwide number of infections in the COVID-19 pandemic can be up to 6 times the reported number of cases.
Researchers, including researchers at the Australian National University (ANU) and the University of Melbourne, found that infection rates in 15 countries averaged 6.2 times higher than reported cases from March to August.
Data published in the journal Royal Society Open Science show that COVID-19 infection rates in the United Kingdom, France, Belgium and Italy are much higher than reported, and up to 17 times higher in Italy.
According to the analysis, Australia showed the highest level of detection among the 15 countries at the end of April, but the infection rate may have been five times higher than officially reported at the end of August.
The study estimated the true number of infections in 11 European countries, Australia, Canada, South Korea, and the United States, totaling more than 800 million people, the researchers say.
"COVID-19 infection was found to be much higher than confirmed cases in many countries, which has important implications for both control and probability of infection," said study co-author ANU Professor Quentin Grafton.
"For example, our analysis found that more than 5.4 million people in the UK, 8% of the population, are or are infected with the coronavirus," Grafton said.
In Australia, the model shows that the actual infection rate (infection and recovery) at the end of August was five times higher than reported, indicating that 0.48% of the population, or up to 130,000, could have been infected. He said.
This is much higher than the confirmed percentage of the population of 0.10 percent, Grafton said.
"These findings confirm the continued prevalence and lifelong health effects of infected people, how to implement and manage blockades, and how we are at the top. And so on, it raises serious questions about how to deal with every aspect of the coronavirus pandemic, in a wider range of this pandemic," he said.
The analysis used "backcasting," a process that examines COVID-19-related deaths and compares them to the time from infection to symptom and the time from symptom to death.
The authors state that this method can provide a 95% confidence interval around the estimated true (population) infection rate.
"Simply put, to analyze statistics on the number of people who died of COVID-I9 in a particular country and to see how many people had to be infected to reach that number of deaths. I worked in the direction," said Stephen Phipps of Ikigai Research.
"Our method is a novel and easy-to-use method for estimating true infection rates whenever we have reliable data on the number of deaths from COVID-19," said Phipps.
"Our approach is particularly advantageous where there are few or limited capabilities to predict infection rates, but for public health planning purposes, population measurement of COVID-19 infection is required, "Grafton added.