Open AccessDynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks
Author(s) -
Daniele Proverbio,
Françoise Kemp,
Stefano Magni,
Andreas Husch,
Atte Aalto,
Laurent Mombaerts,
Alexander Skupin,
Jorge Gonçalves,
Jose AmeijeirasAlonso,
Christophe Ley
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0252019
Subject(s) - psychological intervention , pandemic , risk analysis (engineering) , social distance , outbreak , computer science , contact tracing , covid-19 , isolation (microbiology) , variety (cybernetics) , control (management) , operations research , business , environmental resource management , management science , medicine , economics , engineering , virology , biology , infectious disease (medical specialty) , disease , pathology , artificial intelligence , psychiatry , microbiology and biotechnology
Against the current COVID-19 pandemic, governments worldwide have devised a variety of non-pharmaceutical interventions to mitigate it. However, it is generally difficult to estimate the joint impact of different control strategies. In this paper, we tackle this question with an extended epidemic SEIR model, informed by a socio-political classification of different interventions. First, we inquire the conceptual effect of mitigation parameters on the infection curve. Then, we illustrate the potential of our model to reproduce and explain empirical data from a number of countries, to perform cross-country comparisons. This gives information on the best synergies of interventions to control epidemic outbreaks while minimising impact on socio-economic needs. For instance, our results suggest that, while rapid and strong lockdown is an effective pandemic mitigation measure, a combination of social distancing and early contact tracing can achieve similar mitigation synergistically, while keeping lower isolation rates. This quantitative understanding can support the establishment of mid- and long-term interventions, to prepare containment strategies against further outbreaks. This paper also provides an online tool that allows researchers and decision makers to interactively simulate diverse scenarios with our model.