Returning to a Normal Life via COVID-19 Vaccines in the United States: A Large-scale Agent-Based Simulation Study
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Abstract
In 2020, COVID-19 has claimed more than 300,000 deaths in the United States alone. Although nonpharmaceutical interventions were implemented by federal and state governments in the United States, these efforts have failed to contain the virus. Following the Food and Drug Administration's approval of two COVID-19 vaccines, however, the hope for the return to normalcy has been renewed. This hope rests on an unprecedented nationwide vaccine campaign, which faces many logistical challenges and is also contingent on several factors whose values are currently unknown.
Objective
We study the effectiveness of a nationwide vaccine campaign in response to different vaccine efficacies, the willingness of the population to be vaccinated, and the daily vaccine capacity under two different federal plans. To characterize the possible outcomes most accurately, we also account for the interactions between nonpharmaceutical interventions and vaccines through 6 scenarios that capture a range of possible impacts from nonpharmaceutical interventions.
Methods
We used large-scale, cloud-based, agent-based simulations by implementing the vaccination campaign using COVASIM, an open-source agent-based model for COVID-19 that has been used in several peer-reviewed studies and accounts for individual heterogeneity and a multiplicity of contact networks. Several modifications to the parameters and simulation logic were made to better align the model with current evidence. We chose 6 nonpharmaceutical intervention scenarios and applied the vaccination intervention following both the plan proposed by Operation Warp Speed (former Trump administration) and the plan of one million vaccines per day, proposed by the Biden administration. We accounted for unknowns in vaccine efficacies and levels of population compliance by varying both parameters. For each experiment, the cumulative infection growth was fitted to a logistic growth model, and the carrying capacities and the growth rates were recorded.
Results
For both vaccination plans and all nonpharmaceutical intervention scenarios, the presence of the vaccine intervention considerably lowers the total number of infections when life returns to normal, even when the population compliance to vaccines is as low as 20%. We noted an unintended consequence; given the vaccine availability estimates under both federal plans and the focus on vaccinating individuals by age categories, a significant reduction in nonpharmaceutical interventions results in a counterintuitive situation in which higher vaccine compliance then leads to more total infections.
Conclusions
Although potent, vaccines alone cannot effectively end the pandemic given the current availability estimates and the adopted vaccination strategy. Nonpharmaceutical interventions need to continue and be enforced to ensure high compliance so that the rate of immunity established by vaccination outpaces that induced by infections.
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SciScore for 10.1101/2021.01.31.21250872: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources COMOKIT [38] similarly uses the Gen* toolkit from the same team to redistribute populations from census units down to exact buildings such as the nearest school. Gen*suggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Limitations: There are two main limitations to our current understanding of the COVID-19 pandemic and the vaccination campaign, which affect how …
SciScore for 10.1101/2021.01.31.21250872: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources COMOKIT [38] similarly uses the Gen* toolkit from the same team to redistribute populations from census units down to exact buildings such as the nearest school. Gen*suggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Limitations: There are two main limitations to our current understanding of the COVID-19 pandemic and the vaccination campaign, which affect how our simulations account for (i) the number of vaccines that can be administered each month, and (ii) biological aspects. First, an unprecedented vaccine campaign comes with logistical challenges and uncertainty given the complex array of factors involved. As a result, fewer than the expected number of doses may be administered: federal officials aimed at giving the first dose to 20 million people during December 2020, but various delays resulted in fewer than 3 million people receiving a first dose [58]. It was recently reported that “federal officials say they do not fully understand the cause of the delays” [58] and that the administration “pledged to immediately distribute millions of COVID-19 vaccine doses from a stockpile that the U.S. health secretary has since acknowledged does not exist” [59]. This situation has resulted in views that “much of the narrative earlier this year regarding Warp Speed’s preparation appears to be a sham” [60], reinforced by reports that the Biden administration found no vaccine distribution plan upon taking over from their predecessors [61]. Some of the factors causing a delay are known: there can be shipping delays or delays in administering doses due to a lack of hospital staff members as they are already caring for individuals infected with COVID-19. Other factors may be more surprising, such as ...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from scite Reference Check: We found one citation with an erratum. We recommend checking the erratum to confirm that it does not impact the accuracy of your citation.
DOI Status Title 10.1038/s41591-020-0869-5 Has correction Temporal dynamics in viral shedding and transmissibility of … -
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