Summary: A new mathematical model shows the current COVID-19 pandemic could decline during the summer months, but return in the fall, with a major resurgence next winter. The model takes into account the seasonal variations of other closely related respiratory coronaviruses. Based on other coronavirus data, the model reveals infections were ten times more common between December and April in the northern hemisphere than between July and September. Researchers emphasize this model only attempts to examine possible scenarios, as we are currently unsure how warmer temperatures will affect SARS-CoV-2.
Source: Karolinska Institute
Researchers at Karolinska Institutet in Sweden and the University of Basel in Switzerland have produced a mathematical model that shows that the spread of the new coronavirus can decline in the summer and then return in the autumn and winter. The analysis has been published in the scientific journal Swiss Medical Weekly.
“Even if the spread should decrease in the summer, we cannot conclude that the pandemic is contained because such a decline can be temporary and due to a combination of infection control efforts and seasonal variation in how the virus spreads,” says Jan Albert, professor of infectious disease control at the Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet. “Instead, it can be seen as an opportunity to prepare the healthcare systems and invest in the development of vaccines and antiviral drugs.”
Jan Albert and his colleagues at the University of Basel have tried to predict the effect of seasonal variations in the transmission efficiency of the new coronavirus (SARS-CoV-2) on the northern hemisphere. In their mathematical model, they take into account the likelihood that the spread of the virus will exhibit the same seasonal variation as common and closely related respiratory coronaviruses, namely that it spreads best in the winter.
Could be a new peak in winter 2020/2021
“A possible scenario is that there is a peak in spring 2020 in temperate regions of the Northern Hemisphere, a decline in the summer and a new peak in winter 2020/2021,” says Jan Albert.
The researchers have used the available figures and data on SARS-CoV-2 and four related “common” coronaviruses called HKU1, NL63, OC43 and 229E. Since these related coronaviruses are common cold viruses, there’s a great deal of data on their seasonal variations.
The analysis of the results of more than 52,000 patient samples from Karolinska University Hospital shows that infection with any of the four “common” coronaviruses, HKU1, NL63, OC43 or 229E, was ten times more common in the December to April period than it was in July through September. The researchers have then taken all the available data and used a so-called SIR model, which is often used in mathematical modelling of infectious diseases. Many things that come into play
The researchers emphasise that there’s a lot of uncertainty in the various parameters that they base their analysis on and that it must be remembered that it’s only a model that attempts to examine conceivable scenarios.
“There are many things that come into play in the spread of a virus and that we haven’t been able to factor in, such as what public measures are taken and how successful isolation/quarantine is,” says Jan Albert. “With our analysis, we want to point out that it is important to remember the possibility of seasonality when data on the spread of the pandemic are evaluated.”
About this coronavirus research article
Source: Karolinska Institute Media Contacts: Press Office – Karolinska Institute Image Source: The image is in the public domain.
Potential impact of seasonal forcing on a SARS-CoV-2 pandemic
A novel coronavirus (SARS-CoV-2) first detected in Wuhan, China, has spread rapidly since December 2019, causing more than 100,000 confirmed infections and 4000 fatalities (as of 10 March 2020). The outbreak has been declared a pandemic by the WHO on Mar 11, 2020.
Here, we explore how seasonal variation in transmissibility could modulate a SARS-CoV-2 pandemic. Data from routine diagnostics show a strong and consistent seasonal variation of the four endemic coronaviruses (229E, HKU1, NL63, OC43) and we parameterise our model for SARS-CoV-2 using these data. The model allows for many subpopulations of different size with variable parameters. Simulations of different scenarios show that plausible parameters result in a small peak in early 2020 in temperate regions of the Northern Hemisphere and a larger peak in winter 2020/2021. Variation in transmission and migration rates can result in substantial variation in prevalence between regions.
While the uncertainty in parameters is large, the scenarios we explore show that transient reductions in the incidence rate might be due to a combination of seasonal variation and infection control efforts but do not necessarily mean the epidemic is contained. Seasonal forcing on SARS-CoV-2 should thus be taken into account in the further monitoring of the global transmission. The likely aggregated effect of seasonal variation, infection control measures, and transmission rate variation is a prolonged pandemic wave with lower prevalence at any given time, thereby providing a window of opportunity for better preparation of health care systems.