Scientists create new compliance-based model for SARS-CoV-2 transmission

The coronavirus disease 2019 (COVID-19) pandemic has been endemic worldwide for over a year and has caused widespread disease resulting in millions of deaths. It finally appears as though it is beginning to be brought under control by a mixture of mass vaccination programs, repurposed drugs, and monoclonal antibody treatments. However, as the disease retreats, governments have begun to dismantle social distancing programs, restrictions on social gatherings, and other disease-preventing measures. Unfortunately, as variants of concern continue to emerge, including the increasingly worrying Delta strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), this may backfire.

In spite of the security vaccines offer, there is strong evidence that the SARS-CoV-2 Delta strain can not only still infect vaccinated individuals, but those individuals remain contagious. Rates of death fall significantly, but the disease is still a significant danger to over 80s and the immunocompromised.

Researchers from Utrecht University have been investigating the interactions between compliance social distance measurements, infection, and vaccination coverage in order to inform public health policy further. A research paper covering their work is available on the medRxiv* preprint server.

Variants

The waves of variants that spread over the globe, including the Alpha, Beta and Gamma variants, caused new restrictions to be introduced across Europe. Despite this, the Delta variant emerged in 2020 and quickly became the dominant strain, underscoring the danger and continued transmission despite the restrictions.

Vaccination

Vaccination programs showed success in countries like the United Kingdom and Germany but faced trouble in many others. Vaccine hesitancy is often mentioned in relation to the US, but other countries show far lower vaccine acceptance rates. Kuwait, for example, rests at 23.6%. In addition, more remote countries can suffer from logistical challenges, especially considering the need for constant refrigeration.

Modeling

In order to examine the effect of the various factors, the researchers created a socio-epidemiological model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. They use a susceptible-exposed-infectious-recovered (SEIR) framework to model transmission.

This assumes the vaccine provides perfect protection to a fraction of individuals in the susceptible category and has no effect on any others. This is not an ideal model of reality – multiple studies have shown an intricate and complex relationship between infection, recovery, and the vaccine.

Epidemic dynamics with and without interventions targeting compliance of vaccinated and non-vaccinated individuals. The original variant of the virus circulates. All panels show relative difference in the cumulative number of new infections as compared to the no-vaccination scenario. a and b Vaccination rollout not supplemented with compliance interventions three and six months into the vaccination rollout, respectively. c and d Vaccination rollout supplemented with compliance interventions targeting non-vaccinated individuals three and six months into the vaccination rollout, respectively. e and f Vaccination rollout supplemented with compliance interventions targeting vaccinated individuals three and six months into the vaccination rollout, respectively. g and h Vaccination rollout supplemented with compliance interventions targeting both vaccinated and non-vaccinated individuals three and six months into the vaccination rollout, respectively. Magenta curves mark boundaries between parameter regions with different sign of the cumulative number of new infections. The scale of x-axis is not linear since the axes were obtained by conversion of the vaccine uptake rate to the vaccination coverage following three and six months after the start of the vaccination rollout.
Epidemic dynamics with and without interventions targeting compliance of vaccinated and non-vaccinated individuals. The original variant of the virus circulates. All panels show relative differences in the cumulative number of new infections as compared to the no-vaccination scenario. a and b Vaccination rollout not supplemented with compliance interventions three and six months into the vaccination rollout, respectively. c and d Vaccination rollout supplemented with compliance interventions targeting non-vaccinated individuals three and six months into the vaccination rollout, respectively. e and f Vaccination rollout supplemented with compliance interventions targeting vaccinated individuals three and six months into the vaccination rollout, respectively. g and h Vaccination rollout supplemented with compliance interventions targeting both vaccinated and non-vaccinated individuals three and six months into the vaccination rollout, respectively. Magenta curves mark boundaries between parameter regions with different sign of the cumulative number of new infections. The scale of x-axis is not linear since the axes were obtained by conversion of the vaccine uptake rate to the vaccination coverage following three and six months after the start of the vaccination rollout.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Rather than perfect protection, it is far more common for the vaccine to reduce severity and transmission likelihood. However, there are many other factors involved in the transmission, so some simplification is required.

The model is based upon a society currently undergoing a lockdown with limited contact between people and recommendations to reduce daily contact further. Non-vaccinated individuals are split into compliant and non-compliant to the lockdown, with the number of daily contacts based on these categories. Individuals will switch between the categories. Vaccinated individuals will not comply with social distancing measures. As cases of SARS-CoV-2 infection grow, more individuals will comply.

The transmission rate was based on the transmission of the original variant, Alpha, and Delta variant. To begin the modeling, the state of the epidemic and compliance was based on the Netherlands in November 2020 (prior to vaccination). The proportion of individuals in each category of the SEIR framework was decided by seroprevalence data, which set the recovered population at 8%. 65% of the population was set as compliant.

Vaccination rate

The authors set two vaccination rates based on different dates of sampling in the Netherlands. When the vaccination rate was set as fast, the population gained immunity quickly. On the other hand, when the vaccination rate was set as slow, they still gained immunity, just slowly.

The researchers found that when compliance with social distancing and other measures reduces as vaccine coverage grows, the new rate of transmission is strongly dependant upon the speed of the vaccine rollout. Slow vaccine rollout combined with low compliance actually shows worse short-term transmission than no vaccination at all, and could even result in another 'wave' or peak of instances of COVID-19.

The authors' findings are supported by previous studies suggesting similar effects of waning compliance. The authors highlight the importance of their findings in informing public health policy and urge social distancing measures and other restrictions to be maintained during the early phases of vaccination programs.

For many countries, this advice may come too late, but it could be invaluable advice for those that remain.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Journal references:

Article Revisions

  • Apr 29 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
Sam Hancock

Written by

Sam Hancock

Sam completed his MSci in Genetics at the University of Nottingham in 2019, fuelled initially by an interest in genetic ageing. As part of his degree, he also investigated the role of rnh genes in originless replication in archaea.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Hancock, Sam. (2023, April 29). Scientists create new compliance-based model for SARS-CoV-2 transmission. News-Medical. Retrieved on November 21, 2024 from https://www.news-medical.net/news/20210928/Scientists-create-new-compliance-based-model-for-SARS-CoV-2-transmission.aspx.

  • MLA

    Hancock, Sam. "Scientists create new compliance-based model for SARS-CoV-2 transmission". News-Medical. 21 November 2024. <https://www.news-medical.net/news/20210928/Scientists-create-new-compliance-based-model-for-SARS-CoV-2-transmission.aspx>.

  • Chicago

    Hancock, Sam. "Scientists create new compliance-based model for SARS-CoV-2 transmission". News-Medical. https://www.news-medical.net/news/20210928/Scientists-create-new-compliance-based-model-for-SARS-CoV-2-transmission.aspx. (accessed November 21, 2024).

  • Harvard

    Hancock, Sam. 2023. Scientists create new compliance-based model for SARS-CoV-2 transmission. News-Medical, viewed 21 November 2024, https://www.news-medical.net/news/20210928/Scientists-create-new-compliance-based-model-for-SARS-CoV-2-transmission.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Genetic risk factors for long-COVID uncovered in a large multi-ethnic study