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[Preprint]. 2021 Mar 21:2021.02.28.21252642.
doi: 10.1101/2021.02.28.21252642.

Modeling COVID-19 Nonpharmaceutical Interventions: Exploring periodic NPI strategies

Raffaele Vardavas #  1 , Pedro Nascimento de Lima #  1 , Lawrence Baker #  1
Affiliations

Modeling COVID-19 Nonpharmaceutical Interventions: Exploring periodic NPI strategies

Raffaele Vardavas et al. medRxiv. .

Abstract

We developed a COVID-19 transmission model used as part of RAND's web-based COVID-19 decision support tool that compares the effects of nonpharmaceutical public health interventions (NPIs) on health and economic outcomes. An interdisciplinary approach informed the selection and use of multiple NPIs, combining quantitative modeling of the health/economic impacts of interventions with qualitative assessments of other important considerations (e.g., cost, ease of implementation, equity). This paper provides further details of our model, describes extensions, presents sensitivity analyses, and analyzes strategies that periodically switch between a base NPI level and a higher NPI level. We find that a periodic strategy, if implemented with perfect compliance, could have produced similar health outcomes as static strategies but might have produced better outcomes when considering other measures of social welfare. Our findings suggest that there are opportunities to shape the tradeoffs between economic and health outcomes by carefully evaluating a more comprehensive range of reopening policies.

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Figures

Figure 4:
Figure 4:
Initial disease progression stages
Figure 5:
Figure 5:
Figure 6:
Figure 6:
Model flow of disease progression of the infected symptomatic with transitions that lead to the recovered state R and the died state D shown respectively in panels a and b.
Figure 7:
Figure 7:
Partial rank correlation coefficient values associatewith each input parameter for our three model outputs,
Figure 8:
Figure 8:
Cumulative Deaths CART decision tree.
Figure 9:
Figure 9:
Cumulative Diagnosed CART decision tree.
Figure 10:
Figure 10:
Hospitalized CART decision tree.
Figure 11:
Figure 11:
CART Importance scores for each model outputs and associated with each input parameter.
Figure 1:
Figure 1:
COVID-19 PBM disease states
Figure 2:
Figure 2:. Model Dynamics with Fixed and Periodic NPIs.
Fixed NPI strategies are coded with an “F” followed by the intervention level included in the NPI. Periodic NPI strategies are coded with a “P” followed by the maximum NPI level in the periodic strategy and the period in days. In that case, P-3–14 means that the state will switch between the NPI level 3 and 1 every 14 days.
Figure 3:
Figure 3:. Tradeoff surface implied by alternative policies.
The vertical axis presents the number of Deaths / 100k at the end of the simulation run (Feb. 2021) in California, and the horizontal axis contains several proxies that represent alternative criteria to evaluate the costs of NPIs. Across all these criteria, we find that periodic NPIs tend to dominate fixed NPIs. The plot demonstrates that strategies with fixed NPIs generally are dominated by periodic NPI strategies.
See this image and copyright information in PMC

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References

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