Abstract
Data-centric models of COVID-19 have been attempted, but have certain limitations. In this work, we propose an agent-based model of the epidemic in a confined space of agents representing humans. An extension to the SEIR model allows us to consider the difference between the appearance (black-box view) of the spread of disease and the real situation (glass-box view). Our model allows for simulations of lockdowns, social distancing, personal hygiene, quarantine, and hospitalization, with further considerations of different parameters, such as the extent to which hygiene and social distancing are observed in a population. Our results provide qualitative indications of the effects of various policies and parameters, for instance, that lockdowns by themselves are extremely unlikely to bring an end to an epidemic and may indeed make things worse, that social distancing is more important than personal hygiene, and that the growth of infection is significantly reduced for moderately high levels of social distancing and hygiene, even in the absence of herd immunity.
Highlights
The COVID-19 pandemic has presented humanity with grave social and economic challenges, and a whole host of research questions that are not answered using standard statistical and other methods, in large part on account of the lack of sufficient data about the novel coronavirus SARS-CoV-2
It has been repeatedly stated that maintaining personal hygiene and social distancing are the key to slowing down the spread of COVID-19
We found that social distancing is more important than personal hygiene
Summary
The COVID-19 pandemic has presented humanity with grave social and economic challenges, and a whole host of research questions that are not answered using standard statistical and other methods, in large part on account of the lack of sufficient data about the novel coronavirus SARS-CoV-2. Certain specific aspects of our ABM for COVID-19 are a larger set of possible states that enable distinctions between asymptomatic and symptomatic infections, and parameters to model different levels of hygiene and social distancing. The present work is distinct in that we create an extended agent-based model that allows for qualitative evaluations of the effects of social distancing, personal hygiene, and lockdowns, while taking into account the epidemiological characteristics of COVID-19 [19] and the heterogeneity of populations of people who may become affected. Silva et al [18] propose an agent-based model that allows the simulation of social distancing and the use of masks (as a specific measure of personal hygiene), and study their effects in certain scenarios, with similar but incomplete results. Surges in hospital capacity (including critical care capacity) help reduce the number of severely ill people dying due to a lack of access to medical care, but do not directly affect the overall number of cases to a significant extent (Section 4.6)
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