Simulation of SARS-CoV-2 spread in the United States and India

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In a recent study posted to the medRxiv* preprint server, researchers used an agent-based model (ABM) to simulate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread in the United States and India. They evaluated the efficacy of coronavirus disease 2019 (COVID-19) testing strategies, particularly reverse transcriptase-polymerase chain reaction (RT-PCR) assays and rapid antigen tests (RATs), among the vaccinated populations of both countries having different transmission settings.

Study: SARS-CoV-2 Testing Strategies for Outbreak Mitigation in Vaccinated Populations. Image Credit: Hakim Graphy/ShutterstockStudy: SARS-CoV-2 Testing Strategies for Outbreak Mitigation in Vaccinated Populations. Image Credit: Hakim Graphy/Shutterstock

Despite the widespread availability of COVID-19 vaccines, the emergence of variants of concern (VOCs) that are only partially neutralized by vaccination, waning immunity, and inaccessibility of vaccines, particularly in low- and middle-income countries, makes it apparent that SARS-CoV-2 will continue to pose a threat to public health. Therefore, COVID-19 testing continues to be critical in COVID-19 response and mitigation strategies and preparing for emerging outbreaks.

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

Furthermore, COVID-19 has affected the global population regardless of their socioeconomic status, but its transmission intensity varies greatly by setting. Rather than applying a one-size-fits-all approach, tailored testing strategies specific to the setting may fetch better results. COVID-19 containment strategies cannot also be generalized to all countries because of differences in the transmission intensity. However, to turn the COVID-19 pandemic into global endemic, setting-specific mitigation strategies and using vaccines and testing together is critical.

About the study

In the present study, researchers developed a compartmentalized ABM to simulate COVID-19 cases, hospitalizations, and deaths using several testing and mitigation strategies, including RT-PCR assays, RATs, and vaccinations. 

They obtained data of COVID-19 cases and death counts for the US from the US Centers for Disease Control and Prevention (CDC) and data for India from previous studies. They used this data to estimate the COVID-19 probability of death given age, gender, and comorbidities for both countries.

The model-estimated case-fatality ratio (CFR) for the US and India vis-a-vis the actual CFRs helped the researchers validate the accuracy of their COVID-19 simulations and evaluate the effect of the testing scenarios without any mitigation strategy. The model-estimated CFR for the US and India was 2.66% and 1.85%, respectively; likewise, the actual CFR based on available data for the US and India was 3.05% and 2.11%, respectively. 

Study findings

Regarding COVID-19 testing strategies, the study findings showed that antigen tests were more effective than RT-PCR tests across both transmission settings because they enabled faster action to reduce transmission. The simulations showed a lower peak of daily cases when antigen tests were used compared with RT-PCR assays. However, at standard turnaround times, RATs were more effective in mitigating cases only when 100% of the population was tested weekly.

Although the significance of frequency and coverage varies by setting and the type of test used, the findings emphasized the importance of high-frequency testing when fighting an emerging outbreak driven by a contagious VOC. So while RATs may be effective at maximum frequency, RT-PCR assays can still be effective when used widely as they can identify infectious individuals with low viral loads.

High-frequency testing was overall more important in India but increasing the coverage for improved mitigation made the benefits of frequency most noticeable. Therefore, with limited resources for testing and vaccination, like in the case of India, the authors recommended prioritizing frequency over coverage.

Conclusions 

Taken together, the study findings suggested that the need for widespread and frequent antigen testing was urgent in both countries, provided it was feasible to tailor the benefits of both testing frequency and coverage to community needs. Under budget constraints, antigen testing could be done more frequently or widely to be more effective in containing COVID-19 cases than the use of RT-PCR. Under a limited vaccine allocation strategy, a testing strategy where a small proportion of the population was tested weekly can effectively minimize cases and control sustained transmission in both countries.

The vaccination strategy with high-frequency testing and the impact of continued vaccinations was 16.50% more effective in reducing cases in India than in the US, most likely due to the sustained nature of SARS-CoV-2 transmission observed naturally in India and as COVID-19 infections peaked much earlier in the US.

In both the US and India, maximizing testing frequency was found to be more important; however, wider coverage continues to be necessary during sustained transmission. To conclude, adopting testing strategies tailored to transmission settings would be most effective in reducing COVID-19 cases.

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

  • May 11 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.
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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