One Health Trust’s Ramanan Laxminarayan and colleagues created a computational modeling framework that incorporates genomic surveillance techniques to study the effectiveness of different interventions in a two-variant epidemic scenario. Two intervention regimes, single-period and adaptive non-pharmaceutical interventions (NPIs), were assessed for their impacts on the burden of infection.

In a scenario where the second variant of a disease is imported shortly after the emergence of the first variant, a delayed single-period intervention with intermediate strength most effectively flattens the size of the second variant peak whereas an early, strong single-period NPI is best at minimizing the number of cumulative cases of disease. However, when the second variant’s importation time is delayed, the best time to implement single-period NPIs to flatten the peak is at the beginning of the exponential growth phase of the second variant’s peak. Adaptive NPIs of intermediate strength were also shown to minimize the peak size and reduce disease prevalence in the modeling simulations.

These findings demonstrate that intervening early in dynamic outbreak situations may not always be the most effective strategy to reduce the burden of disease in affected populations. Careful consideration of public health goals can inform decisions about interventions in dynamic, two-variant outbreak or epidemic scenarios.

Read the full article, published in PNAS, here.