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The emergence of COVID-19 vaccine resistance depends on human choices

The probability of the emergence of SARS-CoV-2 vaccine-resistant variants depends on the number of daily infections permitted by society, and the rate and penetrance of vaccination. Rapidly vaccinating all eligible people while maintaining strict physical distancing measures can prevent the evolution of vaccine resistance.

The problem

Vaccination has been the most successful tool in the fight against the COVID-19 pandemic1. Given this success, during mass vaccination campaigns many countries resolved to relax other protective measures such as enforced social (or physical) distancing. However, the continued viral evolution of SARS-CoV-2 raises concerns that vaccine resistance will emerge2. Several variants, such as Delta or Omicron, are already partially resistant to current vaccines3. Therefore, we sought to quantify the probability of the emergence of vaccine resistance, given the speed and penetrance of vaccination campaigns and given the dynamic social distancing applied (which allows a fixed number of new infections per day to determine the strength of the distancing measures).

The solution

Dynamic social distancing roughly balances the basic reproductive ratio (R) of SARS-CoV-2 in the absence of a vaccine at around 1. However, once mass vaccination campaigns commence, social distancing measures become relaxed as the proportion of the population that is immunized expands. As a consequence, the basic reproductive ratio of potential vaccine-resistant variants (MT) continually increases, which creates an undesirable selection pressure for the genesis of an escape variant (Fig. 1). In our modelling, we found evidence that selection for vaccine resistance can be prevented if countries maintain a fixed level of social distancing until high vaccination rates achieve herd immunity.

Fig. 1: Basic reproductive ratios and probabilities for emergence of vaccine resistance in the USA.
figure 1

© 2022, Lobinska, G. et al.

a, The reproductive rate (R) of the sensitive wild-type (WT) SARS-CoV-2 has been maintained R ~ 1. The reproductive rate of potential vaccine resistant variants (MT) with partial (q = 0.4) or complete escape (q = 1) increases as social distancing is relaxed during the mass vaccination campaign. b, The probability for the emergence of vaccine resistance grows over time.

We analysed vaccination and infection data from the beginning of the pandemic from six countries: Brazil, France, Germany, Israel, the UK and the USA. Israel achieved a peak vaccination rate of 20,000 people per million per day, with the other countries reaching a peak rate of about 10,000. By contrast, the average vaccination rates were lower — around 4,000–5,000 per million per day — with Israel leading (5,391) and the USA trailing (3,964). The average number of new infections during the period of mass vaccination was highest in UK and lowest in Germany (about 343 and 148 daily new cases per million, respectively). After assuming each new infection had a probability of 10−7 to generate a potential escape variant (which we estimated on the basis of probabilistic calculations), we computed — dependent on our model assumptions — that the overall probability that the UK would initiate a wave of vaccine resistance was 36%, whereas for Germany this probability was 15%.

The crucial message from our comparison between the UK and Germany is that limiting the number of new infections during fast mass-vaccination programmes reduces the probability that vaccine resistance will emerge. Therefore, maintaining stronger social distancing measures in Germany during their rapid vaccination campaign reduced the probability that a vaccine-resistance variant would emerge in that country, as compared to the UK.

In addition, other factors affected the emergence of vaccine resistance, such as vaccine hesitancy, booster vaccination campaigns and using an alternatively designed vaccine4 (which would combine several viral antigens, thereby forcing the virus to make multiple mutations to acquire a vaccine-resistance phenotype5).

The implications

Our findings have implications for policymakers who aim to reduce the probability that vaccine resistance will emerge. In particular, they indicate that social distancing should be maintained as long as herd immunity has not been achieved. In practice, many countries have instead set the tolerated threshold of new infection cases per day to be proportional to their hospital capacity. As current vaccines seem to protect against severe COVID-19 complications and death, and most individuals in developed countries are immunized, many countries therefore now tolerate higher numbers of infection by new variants such as Omicron before imposing new social distancing measures. Our analysis highlights the danger that each of these infections is an opportunity for the virus to mutate into further vaccine-resistant variants.

Mass booster vaccination can also prevent the emergence of vaccine resistance, and policymakers should aim to make boosters available as widely as possible to reduce the number of new infections from waning immunity.

Finally, vaccine hesitancy has prevented the achievement of herd immunity in many countries. Hence, many infections that could have been avoided occur and constitute an opportunity for vaccine resistance to evolve. Reducing vaccine hesitancy is another crucial step to prevent the emergence of vaccine resistance.

Gabriela Lobinska 1 and Martin A. Nowak 2

1Weizmann Institute of Science, Rehovot, Israel. 2Harvard University, Cambridge, MA, USA.

Expert opinion

“The authors use a mathematical model to explore how different combinations of vaccination rates, and dynamic lockdowns, may affect the likelihood of emergence of an immune evasive variant of the novel coronavirus. The approach they implement is suitable for this investigation, and they show robust results of potential interest to a wide audience. Overall, the quality of the study is high, and I commend the authors on their efforts.”

Brody Foy, Harvard Medical School & Massachusetts General Hospital, Boston, MA, USA.

Behind the paper

When I joined Robert May in 1989 as a post-doc in Oxford, I wanted to develop a mathematical theory to describe the dynamics of virus infections and evolution. At the time I focused on HIV and its interaction with drug treatment and the immune response. But the appearance of the SARS-CoV-2 pandemic and its counter-measures have led to an unprecedented worldwide ‘experiment’ in viral dynamics5 and represented an unfortunate ‘opportunity’ to apply those mathematical principles. M.A.N.

Our project started with Ady Pauzner’s observation that the reproductive ratio of SARS-CoV-2 has been around 1 for much of the pandemic because of dynamic social distancing. We wondered how this social control would affect viral evolution. We were thrilled to find that policy decisions have tangible potential to curtail the evolution of SARS-CoV-2. Thus, the evolution of an infectious agent on a global scale can be affected by human decisions. Working on this paper has felt empowering with regard to participating in the fight against the pandemic. G.L. and M.A.N.

From the editor

"When we first read this work, we were struck by its potential importance for managing the ongoing pandemic. The authors model COVID-19 viral evolution, using biologically realistic assumptions. They find that even with vaccination underway, contact reduction is necessary to prevent the evolution of a vaccine-resistant variant. With the recent emergence of the Omicron variant, this message is more timely than ever." Charlotte Payne, Senior Editor, Nature Human Behaviour

References

  1. Our World in Data. COVID-19 data explorer, https://ourworldindata.org/coronavirus-data-explorer (2022).This database collects global infection, vaccination and mortality data of SARS-CoV-2.

  2. Starr T. N. et al. Prospective mapping of viral mutations that escape antibodies used to treat COVID-19. Science 371, 850–854 (2021). A deep mutagenesis scanning study of the SARS-CoV-2 spike protein aiming to identify potential escape mutants.

  3. Keeton R. et al. T cell responses to SARS-CoV-2 spike cross-recognize Omicron. Nature https://doi.org/10.1038/s41586-022-04460-3 (2022). This paper explores the potential of the Omicron variant for vaccine escape.

  4. COVID-19 vaccine tracker, https://covid19.trackvaccines.org/vaccines/approved/ (2022). This website summarizes information about currently used vaccines around the world.

  5. Nowak, M. A. & May, R. M. Virus Dynamics (Oxford Univ. Press, 2000). This book explores basic equations of virus dynamics.

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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This is a summary of: Lobinska, G. et al. Evolution of resistance to COVID-19 vaccination with dynamic social distancing. Nat. Hum. Behav., https://doi.org/10.1038/s41562-021-01281-8 (2022).

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The emergence of COVID-19 vaccine resistance depends on human choices. Nat Hum Behav 6, 181–182 (2022). https://doi.org/10.1038/s41562-022-01313-x

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