People Meet People: A Microlevel Approach to Predicting the Effect of Policies on the Spread of COVID-19

Janos Gabler, Tobias Raabe () and Klara Röhrl ()
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Janos Gabler: IZA
Tobias Raabe: quantilope
Klara Röhrl: University of Bonn

No 13899, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Governments worldwide are adopting nuanced policy measures to reduce the number of Covid-19 cases with minimal social and economic costs. Epidemiological models have a hard time predicting the effects of such fine grained policies. We propose a novel simulation-based model to address this shortcoming. We build on state-of-the-art agent-based simulation models but replace the way contacts between susceptible and infected people take place. Firstly, we allow for heterogeneity in the types of contacts (e.g. recurrent or random) and in the infectiousness of each contact type. Secondly, we strictly separate the number of contacts from the probabilities that a contact leads to an infection. The number of contacts changes with social distancing policies, the infection probabilities remain invariant. This allows us to model many types of fine grained policies that cannot easily be incorporated into other models. To validate our model, we show that it can accurately predict the effect of the German November lockdown even if no similar policy has been observed in the time series that were used to estimate the model parameters.

Keywords: COVID-19; agent based simulation model; public health measures (search for similar items in EconPapers)
JEL-codes: C63 I18 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2020-11
New Economics Papers: this item is included in nep-cmp, nep-hea and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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