Effect of time-varying adherence to non-pharmaceutical interventions on the occurrence of multiple epidemic waves: A modeling study

Abstract

Non-pharmaceutical interventions (NPIs) play a central role in infectious disease outbreak response and control. Their usefulness cannot be overstated, especially during the early phases of a new epidemic when vaccines and effective treatments are not available yet. These interventions can be very effective in curtailing the spread of infectious diseases when adequately implemented and sufficiently adopted by the public. However, NPIs can be very disruptive, and the socioeconomic and cultural hardships that come with their implementation interfere with both the ability and willingness of affected populations to adopt such interventions. This can lead to reduced and unsteady adherence to NPIs, making disease control more challenging to achieve. Deciphering this complex interaction between disease dynamics, NPI stringency, and NPI adoption would play a critical role in informing disease control strategies. In this work, we formulate a general-purpose model that integrates government-imposed control measures and public adherence into a deterministic compartmental epidemic model and study its properties. By combining imitation dynamics and the health belief model to encode the unsteady nature of NPI adherence, we investigate how temporal variations in NPI adherence levels affect the dynamics and control of infectious diseases. Among the results, we note the occurrence of multiple epidemic waves as a result of temporal variations in NPI adherence and a trade-off between the stringency of control measures and adherence. Additionally, our results suggest that interventions that aim at increasing public adherence to NPIs are more beneficial than implementing more stringent measures. Our findings highlight the necessity of taking the socioeconomic and cultural realities of affected populations into account when devising public health interventions.

Revisiting the complex time-varying effect of non-pharmaceutical interventions on COVID-19 transmission in the United States

“…The largest decline was observed in December 2021 and January 2022 when the daily diagnosed cases exceeded 0.6 million people ( Figure 1A ), closely following the epidemic caused by the Delta variant. Long-term implementation of NPIs and successive waves caused pandemic fatigue and reduced people’s adherence to policies ( 44 , 45 ). More importantly, the results showed that the impact of NPIs was more correlated with the intensity of NPIs, with a decline in empirical effect along with the relaxation of NPIs ( Figure 2A ), which was consistent with previous estimation in Europe ( 16 ).…”