Purpose: The COVID-19 pandemic and the containment measures such as social distancing, mobility restrictions and quarantine have significantly impacted the delivery of healthcare services, with possible negative effects on low back pain patients. In this study, we used an innovative agent-based model to quantify the effects of COVID-19 on the prevalence and severity of low back pain in the general population.
Methods: Epidemiological data were used to simulate the low back pain evolution in a population of 300,000 agents. Reduced access to treatment due to the containment measures was simulated with a probabilistic approach, in which 500 random scenarios (differing in: length of the lockdown, probability of having access to treatment, time before the resumption of treatment, duration of the effects of the treatment after its interruption) were simulated.
Results: The lockdown may increase the mean pain score higher than 1/10 points for patients suffering from acute low back pain, up to 4-5/10 points for specific individuals. The lockdown also affected the length of pain episodes, possibly impacting chronicity and disability. All the variables describing the random scenarios had a relevant impact in determining both the increase of pain intensity in the population and the length of the effects of the lockdown.
Conclusions: "Optimal lockdown parameters" which minimize the impact on low back pain while preserving the effects on infection spread and mortality could not be identified. Policies favouring a prompt resumption of treatments after the lockdown may be effective in shortening the duration of its negative effects.
Keywords: Agent-based model; COVID-19; Lockdown; Low back pain; Social distancing.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.