The COVID-19 pandemic remains on the forefront of public health concerns as variants of the virus continue to emerge. Variants of concern, such as the Omicron, Delta, and Alpha waves, have made controlling transmission of COVID-19 extremely difficult.
Scientists have been investigating ways to prevent outbreaks of these novel variants. The variants’ transmissibility, severity, detection rates, and ability to infect those with immunity, all greatly affect the impact COVID-19 can have on our everyday lives.
One method that can be utilized to identify new variants of concern (VOC) is by examining mortality data, which displays when an increased amount of reported vaccine breakthrough deaths (deaths from COVID-19 in fully vaccinated individuals) occur in an area. The issue with using mortality data is that there is significant lag between exposure to the variant and death. This lag in variant identification makes it highly difficult to take any containment measures before the virus has spread.
CEID’s Tobias Brett and Pejman Rohani have been exploring an alternative method of identifying variants: genomic surveillance. The research team created a COVID-19 transmission model to determine if this method can feasibly help contain the spread of variants.
Genomic surveillance involves sequencing, monitoring, and comparing pathogens. By sequencing these variants and identifying certain traits of the virus, this data can be utilized to inform containment measures.
The transmission model examined how quickly VOCs can spread, the average period a person is infected, how many additional people an infected individual will expose to the virus, and the average amount of immunity in the population. The results indicated that there are two important factors affecting the probability that the infection has spread before a new variant is identified, sequencing delay and doubling time. Sequencing delay is the amount of time it takes between exposure to the virus and the virus being fully sequenced, which varies greatly around the world. Doubling time is the time it takes for the number of virus cases to double in an area.
The model data shows that for the majority of countries, who sequence more than 0.5% of infections, genomic surveillance is faster to identify new variants compared to mortality data. The results favor genome sequencing as the monitoring strategy for COVID-19 VOCs. Furthermore, the transmission model found that travel restrictions are unlikely to prevent a variant from entering a country, unless all travelers are quarantined upon arrival at their destination until confirmed to be infection free. If restrictions are imposed after a case has already been detected within the area, this is likely ineffective as the virus has already started to spread.
Findings suggest that if a variant emerges in a country with advanced surveillance it may be easier to contain the virus within this country, rather than trying to prevent spread to other countries with poor monitoring systems.
Click here to learn more about this study.
By: Brenna Daly