COVID-19 modeling shows that social distancing is a must, must, must

By Dr. Ananya Mandal, MDApr 15 2020

A new study shows that using mathematical modeling and accounting for several factors such as age distribution and density of the population, a clearer picture of COVID-19 infection in a population could be gained.

The study titled, "Level of under-reporting including under-diagnosis before the first peak of COVID-19 in various countries: Preliminary Retrospective Results Based on Wavelets and Deterministic Modeling," is published as an accepted manuscript in the journal Infection Control & Hospital Epidemiology.

Study - Level of under-reporting including under-diagnosis before the first peak of COVID-19 in various countries: Preliminary Retrospective Results Based on Wavelets and Deterministic Modeling. Image Credit: Travelerpix / Shutterstock

What was this study about?

COVID-19 pandemic has reached massive proportions across the world, with over 2 million reported cases and tens of thousands of deaths across the world. There is a global problem of underreporting experts. According to the developers of this new model, a more realistic picture of the viral infection in a community could be obtained despite under-reporting.

Dr. Arni S.R. Srinivasa Rao, director of the Laboratory for Theory and Mathematical Modeling in the Division of Infectious Diseases at the Medical College of Georgia at Augusta University, explained, "Actual pandemic preparedness depends on true cases in the population whether or not they have been identified. With better numbers, we can better assess how long the virus will persist and how bad it will get. Without these numbers, how can health care systems and workers prepare for what is needed?"

The study was conducted in collaboration with Dr. Steven G. Krantz, professor of mathematics at Washington University in St. Louis, Missouri. Rao, also the corresponding author of the study, said, "We wanted to provide info on the real magnitude of the problem, not just the tip of the iceberg."

What did the researchers do?

The team used their mathematical model with data on the number of persons infected with COVID-19. The numbers were obtained from the World Health Organization (WHO). They also included other factors such as the density of the population, the proportion of the population that is living in the urban regions, and in close proximity with each other. The third factor they considered was three age groups of the population, including less than 14 years, 15 to 64 years and over 65 years. In addition, the team also assessed the number of new cases ten after the first peak was reached.

Rao explained that because the rate of infection with the SARS-CoV-2 causing COVID-19 is very high, this model helped them to calculate the "transmission probability." They also included other factors such as the evidence regarding the time the virus survives on different surfaces and in the air. This can further aid the model to sharpen its predictions, explained Rao. For this study, the team looked at data from WHO gathered up to 9^th March 2020.

What did they find?

Italy

Italy was one of the first and worst affected nations with overwhelmed intensive care units and a large number of cases as well as deaths. The deaths among healthcare workers there are also among the highest.

The researchers explained that Italy is a small European nation and the fifth most densely populated nation in Europe. A large part of the population lives in urban areas and thus lives within close proximity to each other. Because the virus is highly infectious, the presence of the people living and working close to each other is, therefore, one of the significant contributors to the country's high infection rate.

From the WHO records, the team found that initially, Italy did a comparatively good job of reporting early on, with 1 case reported for every four cases that Rao and Krantz projected. Up until 9^th March, there were 30,223 cases that were not reported, they wrote. They added that 9^th March was not the peak for the COVID-19 cases in Italy, and still, many cases were reported after that.

South Korea

South Korea was one of the nations that had the highest reported cases and were testing more than any other country. The team found that South Korea was also reporting an average of one in four cases of likely COVID-19.

Spain

Spain is one of the nations that have been hardest hit by the pandemic. Until 19^th March, there were over twenty thousand deaths in the country, and the peak rise in active cases was 27 percent. The model predicted that Spain was reporting only 1 case out of 53 cases that were active COVID-19. If this was used to calculate the estimated number of actual cases, Rao explained that it would come to 87,405 cases that were not reported.

China

China has been accused of underreporting COVID-19 cases. This mathematical model found that one in 149 active cases was reported. Another range suggested that only one on 1,104 cases was being reported in China. This ranges between 12 to 89 million cases that went unreported from China speculate the researchers.

The United States

The viral spread in the United States was much higher after 9^th March, and thus the number of unreported cases could not be predicted at the time of this study. Rao said that by 9^th March, there were 500 cases in the United States, and the model predicted the actual number of cases to be 90,000. They predicted that by 6th April, there would be 561,000 cases, and of these, only 367,000 cases would be reported. There is a prediction of 8,910 deaths by 6th April, says the model. The team calculated that the U.S. is reporting 2 out of 3 cases of COVID-19. Rao explained that 194,000 unreported cases include 3,298 children aged below 14 years, 147,441 aged between 15 and 64 years, and 43,262 aged 65 years and over. These individuals, he added, do not know that they are COVID-19 positive and are not self-isolating and maintaining social distancing. This could mean that they would spread the infection among large populations.

Conclusions and implications

Rao said in his statement, "A model tells us something which has not been directly observed. It's a biological experiment done on computers rather than in a lab." He said that this could be used for several diseases, including non-infectious ones such as heart disease. He called for social distancing among the people with the widespread underreporting that has been revealed. He said, "Social distancing is a must, must, must."