​​Two methods developed by South African scientists to detect a population-level signal of immune evasion by variants of concern, such as Omicron, will greatly improve public health authorities' timely response to new variants.

In a paper published in the prestigious journal Science today, the scientists describe two methods for analysing reinfection trends in routine surveillance data from laboratories. On a population-level, this means that indicators of immune evasion by a potential variant of concern can be picked up even before verification from laboratory analysis.

The methods were used to monitor reinfection risk during the second, third, and fourth SARS-CoV-2 waves in South Africa. In November 2021, the researchers provided the first evidence of Omicron's ability to evade the immune response from prior infection. In December they released a preprint highlighting the increase in reinfection risk.

Prof Juliet Pulliam, director of the South African Centre for Epidemiological Modelling and Analysis (SACEMA) hosted at Stellenbosch University and first author, says they wanted to determine whether there is epidemiological evidence of increased risk of reinfection with the Omicron variant as compared to the Beta and Delta variants. This is an important question, as an increase of reinfections would serve as an indication that the new variant has developed the ability to evade natural immunity from previous infection.

She says during the first three waves that hit South Africa, their routine surveillance monitoring detected a low number of suspected reinfections consistent with reinfections with the “wild type" virus. The first reinfections were detected in June 2020, and the number of suspected reinfections increased gradually to approximately 30 thousand – or about 1% of those eligible for reinfection – by the end of the third wave.

By mid-November 2021, they observed that the rate of increase of the number of reinfections was rapidly outstripping expectations based on what was seen in earlier waves: “The actual number of reinfections we were seeing in mid-November was low – on average about 23 per day – but because of the robust methods we have developed, we could tell that this was substantially higher than what would have been expected in the absence of an immune escape variant (about ten per day)," she explains.  

The timing of this deviation in the epidemiological data was later associated with the emergence of the Omicron variant, identified by South African scientists and announced to the public on 25 November 2021.

While the main finding of the peer-reviewed paper being published in Science today remains the same as in the preprint, it includes data through the end of January 2022. According to Prof Pulliam, this shows that the reinfection risk appears to have stabilised at this higher level now that Omicron is the dominant variant.

On the approaches used, she says both account for two important factors that have confounded other analysis of reinfection risk: “First, that the number of people eligible for reinfection increases through time, and second that the risk of infection – including for people who were previously infected – changes with the amount of virus circulating in the population through time.

“Our approaches looked for changes in reinfections above and beyond what would be expected just from these two phenomena – that is, looking for a signal that something has changed in the way that the virus infects people with previous infection."

She says the first approach predicts the number of reinfections expected if the virus is behaving as it has in the past and compares the expected number to what is observed. The second approach uses a more detailed model to reconstruct the underlying reinfection dynamics and estimates the risk of reinfection through time.

The data for these analyses were collected through South Africa's National Notifiable Medical Conditions Surveillance System and collated by researchers at the National Institute for Communicable Diseases (NICD). The analysis is based on 2,942,248 individuals with laboratory-confirmed positive SARS-CoV-2 test results at least 90 days prior to 31 January 2022. Of these, 105,323 were suspected reinfections.

Prof Pulliam says their methods work best in contexts with low vaccination coverage but good population-surveillance data. Further work is needed to adapt the methods to areas with high vaccination rates.

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Source: Increased risk of SARS-CoV-2 reinfection associated with emergence of Omicron in South Africa, ​Science. DOI: 10.1126/science.abn4947​