Mathematical modeling as a tool for policy decision making: Applications to the COVID-19 pandemic

Abstract

The coronavirus disease 2019 (COVID-19) pandemic highlighted the importance of mathematical modeling in advising scientific bodies and informing public policy making. Modeling allows a flexible theoretical framework to be developed in which different scenarios around spread of diseases and strategies to prevent it can be explored. This work brings together perspectives on mathematical modeling of infectious diseases, highlights the different modeling frameworks that have been used for modeling COVID-19 and illustrates some of the models that our groups have developed and applied specifically for COVID-19. We discuss three models for COVID-19 spread: the modified Susceptible-Exposed-Infected-Recovered model that incorporates contact tracing (SEIR-TTI model) and describes the spread of COVID-19 among these population cohorts, the more detailed agent-based model called Covasim describing transmission between individuals, and the Rule-Based Model (RBM) which can be thought of as a combination of both. We showcase the key methodologies of these approaches, their differences as well as the ways in which they are interlinked. We illustrate their applicability to answer pertinent questions associated with the COVID-19 pandemic such as quantifying and forecasting the impacts of different test-trace-isolate (TTI) strategies.

Percolation across households in mechanistic models of non-pharmaceutical interventions in SARS-CoV-2 disease dynamics

“…Although previous works considered heterogeneous contact structures in epidemiological models [20, 26, 28], and many others accounted for NPIs’ effects on transmissibility [12, 16, 17, 1, 2, 4, 22], few to none made the connection between both phenomena. Strictly speaking, NPIs can affect the underlying network structure over time due to large scale social distancing interventions.…”

“…Since the emergence of SARS-CoV-2, mathematical modelling has become an important tool for planning strategies to combat the pandemic by supporting decision-making and public policies [1, 2, 4, 22]. As a result, a proliferation of SEIR-like age-structured compartmental models assessing the effect of different intervention scenarios have been proposed and discussed [12, 16, 17].…”

Opportunities and Challenges in Developing COVID-19 Simulation Models: Lessons from Six Funded Projects

“…A detailed comparison of the projects is beyond the scope of this study, as our interest lies in identifying challenges and solutions. For such comparisons, we refer the readers to (Panovska-Griffiths et al 2021, Adiga et al 2020. In each project, we asked modelers why they chose a certain technique.…”

COVID-19 scenarios for comparing the effectiveness of age-specific vaccination regimes, exemplified for the city of Aschaffenburg (Germany)

“…Since the beginning of the pandemic, epidemiologists have been using computer simulations in an attempt to meet the demands of decision-makers for scientific assessment of political options and forecasts on the development of the pandemic. A variety of models with different approaches have been adapted or newly developed for the COVID-19 pandemic (Panovska-Griffiths et al 2021). Agent-based models have proved to be capable of representing the complexity of the pandemic in some detail, including public health interventions, such that the number of available models grew rapidly (Lorig et al 2021).…”