Effects of non-pharmaceutical interventions and mutations on COVID-19 resurgence

By Dr. Ramya Dwivedi, Ph.D.Sep 7 2021

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected more than 221 million people and caused over 4.57 million deaths. The implementation of non-pharmaceutical interventions (NPIs) such as social distancing, mask-wearing, lockdowns, and travel bans have helped control the first wave of the COVID-19 pandemic.

Study: How control and relaxation interventions and virus mutations influence the resurgence of COVID-19. Image Credit: DisobeyArt/ Shutterstock

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Despite these successful interventions during the first wave, the COVID-19 outbreak came back stronger in the second wave in many countries. The effects of controlling these interventions and their relaxations on COVID-19 and its resurgence are unclear. Coupled with the rapid mutations in the virus, the dynamic epidemiological processes of COVID-19  get further complicated.

A recent study available on the preprint server medRxiv* addresses these effects in detail to develop a deeper understanding of their influence on the resurgence of COVID-19 by developing a dynamic event-driven generalized SEIR (susceptible-exposed-infectious-recovered) model SPEIQRD.

The researchers applied the model in the first and second waves in 2020 in Germany, France, and Italy as a case study. In the absence of sufficient vaccination, herd immunity, and effective antiviral pharmaceutical treatments, they found that interventions' early or fast relaxation (including public activity restrictions) results in a COVID-19 resurgence. Importantly, this study is the first attempt to simulate the impact of virus mutations (such as delta and lambda) with a transmissibility increase of 20 to 100% on the second waves and resurgence infections and the effect of control and relaxation interventions.

Focusing on specific aspects and a 'qualitative to descriptive' analysis of the second waves of the pandemic, the researchers divided the study into four main questions.

A preprint version of the study is available on the medRxiv* server while the article undergoes peer review.

How do epidemiological attributes change over the first to the second wave in different countries?

To understand this, the researchers quantified and analyzed epidemiological attributes such as the infection rate, incubation rate, quarantine rate, recovery rate, mortality rate, and subsequently behaviors and patterns between waves in Germany, France, and Italy. They concluded that weaker interventions combined with stronger deconfinement activities were associated with the second wave in these countries.

How do different severity, numbers, and timing of interventions individually and cumulatively affect the trends of the two waves?

These effects of severity, number, and timing of interventions and social activities on the behaviors and trends of two waves characterize the dynamic processes of the first-to-second wave evolution and their sensitivity.  They inferred the individual and cumulative impact of control and relaxation interventions (early/late, more/less), which affected the daily cases in each wave. The researchers demonstrated the different dynamics and trends in each country, the control and relaxation events that generate opposite effects - either suppressing or speeding up the COVID-19 curves, and the inappropriate relaxations that may have contributed to the wave differences and COVID-19 resurgence in the three countries.

How would different control and relaxation intervention strategies influence the next 30-day trends following the second waves?

Further, the researchers simulated different scenarios to evaluate how control and relaxation intervention strategies influence the next 30-day trends following the second waves? The scenarios reflected different response strategies and behaviors by governments, individuals, and societies to the second waves, such as enforcing or relaxing interventions and restrictions on socio-economic activities to different extents. They concluded that it would not be safe to reopen society at a large scale at the end of the second wave (i.e., the beginning of December 2020) - because there would still be considerable infected individuals.

How would more infectious virus mutants influence the second waves under hard or soft interventions?

Again, they simulated and evaluated the influence of more infectious virus mutants (such as delta and lambda) with different transmissibility levels on the second waves when the actual strong and weak interventions are carried from their first and second waves. Then, they predicted the next 30-day case trends following the second wave if different transmissibility levels of virus mutants appeared. They showed an overwhelming outcome of highly infectious coronavirus mutations in the community when no effective control measures are adopted and vaccination is insufficient.

The researchers also demonstrated that their model predicts the future well.  This study focuses on (1) describing the epidemiological characteristics of second waves, (2) comparing the epidemiological attributes of first and second waves, and (3) forecasting resurgence, including the impact of external factors.

The findings and analyses from this study provide evidence for governments and policymakers to manage the pandemic and resurgences systematically. The research is also useful in the increasing debates on whether elimination (zero COVID, such as the practices undertaken in countries like China), eradication or suppression ("living with the virus" at an acceptable level, like the approaches undertaken in countries like the UK and US) and when full reopening, are reasonable in practice, the researchers write.

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.