Random differences in the timing of interventions like social distancing can make a big difference in how severe the coronavirus crisis is and how long it lasts, research suggests.

Researchers from Queen Mary University of London used a novel modelling approach to explore how non-pharmaceutical interventions (NPI), and declines in public compliance to them might affect the course of the Covid-19 pandemic.

They found the progress of epidemics is highly variable, and sensitive to the timing of early interventions.

According to the research this suggests that countries adopting the same interventions could still see different outbreak trajectories due to minor changes in when NPI are applied.

The findings indicate that in order to contain the virus, early management of interventions, continued monitoring and increasing intervention on a fast timescale, are needed.

The researchers also found that if governments respond and provide timely interventions, the impact of decreasing public compliance is reduced.

Dr Rob Knell, reader in evolutionary ecology at Queen Mary and author of the study, said: “From our analysis we find that small, random differences in the timing of management interventions can make big differences in how severe the epidemic is and how long it lasts, suggesting that countries with apparently similar government strategies might experience very different epidemics for no easily discernible reason.

“We also find that early and rapid responses are crucial in suppressing the SARS-CoV-2 pandemic and, interestingly, that declines in public compliance don’t have major effects on mortality so long as the government continues to monitor the situation and intervenes when case numbers start to rise.”

The new model is based on the Management Strategy Evaluation (MSE), which was originally used for assessing fisheries management schemes.

It makes similar predictions to the one currently used by the Government from Professor Neil Ferguson of Imperial college, but provides an approach that can easily be adapted to different scenarios.

Dr Knell, added: “Because this new model doesn’t need a supercomputer it allows us to explore a wider range of management options for the pandemic, and investigate other scenarios such as declining compliance with social distancing measures over time.

“We have made the computer code for the model fully available and would like to encourage other workers to use this, for example to explore the epidemic trajectories for different countries or management interventions.”