Researchers design a mathematical model to understand COVID-19 outbreaks

Researchers design a mathematical model to understand COVID-19 outbreaks
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A new study employed a mathematical model to address COVID-19 outbreaks and variants of concern.

A study published in eLife finds that it is a necessity that governments and other stakeholders proactively plan and prepare for future variants of concern (VOCs), which could include developing a universal COVID-19 vaccine that prevents COVID-19 outbreaks and severe disease.

The researchers conducted a model of COVID-19 dynamics in South Africa, where the country had experienced four distinct pandemic waves caused by SARS-CoV-2 and the three VOCs – Beta, Delta and Omicron, by February 2022.

“These repeated pandemic waves have been driven by new VOCs that erode prior immunity from either infection or vaccination, increase transmissibility, or a combination of both,” explained study author Wan Yang, Assistant Professor of Epidemiology at Columbia University Mailman School of Public Health, New York, US. “Although laboratory and field studies provide insights into variant epidemiological characteristics, quantifying the extent of immune erosion and changes to transmissibility for each VOC is challenging.”

Creating a mathematical model of COVID-19 outbreaks

The researchers wanted to understand the characteristics of the different COVID-19 VOCs and COVID-19 outbreaks. The team developed a mathematical model using weekly case and death data from nine South African provinces from March 2020 to the end of February 2022 to reconstruct COVID-19 outbreak dynamics.

They validated the model using three independent datasets and found that estimated cumulative infection rates roughly matched serology data over time. The infection numbers were matched with hospitalisation figures for all four pandemic waves caused by the original SARS-CoV-2, Beta, Delta, and Omicron variants. The modelled infection numbers matched with death rates from all four variants but deaths significantly reduced by the Omicron wave due to prior infection and increasing vaccination rates.

The team utilised data emerging from new variants, Delta and Omicron, and the model predicted the related outbreaks before the real-life observed peak of cases and deaths caused by these variants. The model accurately predicted the remaining cases and deaths in most provinces.

Analysing the transmissibility of variants

Once they validated the model, they estimated epidemiological characteristics for each VOC, including infection-detection rates, infection-fatality rates, population susceptibility and transmissibility, and compared these dynamics across provinces. These ‘model inference estimates’ were then used to quantify the immune erosion and increase in transmissibility for each VOC.

The team found that the Beta variant gradually reduced immunity in roughly 65% of people previously infected with the original SARS-CoV-2 and was 35% more transmissible than the original virus. The findings were supported by the experience of previously infected participants in one of the vaccine trials, who had a similar susceptibility to the Beta variant as those who had no prior infection.

Moreover, the Delta COVID-19 outbreak reduced immunity from prior infection or vaccinations by around 25% and was 50% more transmissible. Additionally, Omicron was consistently reported for its higher transmissibility than previous COVID-19 outbreaks. The researchers reported that Omicron is around 95% more transmissible than SARS-CoV-2 and reduced immunity by 55%.

The results highlight that prior immunity to SARS-CoV-2 does not protect you from new COVID-19 outbreaks. This research illustrates the need for a universal vaccine that can block all variants and prevent severe disease.



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