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

Author

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  • Gabler, Janos

    (IZA)

  • Raabe, Tobias

    (quantilope)

  • Röhrl, Klara

    (University of Bonn)

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.

Suggested Citation

  • Gabler, Janos & Raabe, Tobias & Röhrl, Klara, 2020. "People Meet People: A Microlevel Approach to Predicting the Effect of Policies on the Spread of COVID-19," IZA Discussion Papers 13899, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp13899
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    References listed on IDEAS

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    1. Donsimoni Jean Roch & Glawion René & Plachter Bodo & Wälde Klaus, 2020. "Projecting the spread of COVID-19 for Germany," German Economic Review, De Gruyter, vol. 21(2), pages 181-216, June.
    2. Florian Dorn & Janos Gabler & Hans-Martin von Gaudecker & Andreas Peichl & Tobias Raabe & Klara Röhrl, 2020. "Wenn Menschen (keine) Menschen treffen: Simulation der Auswirkungen von Politikmaßnahmen zur Eindämmung der zweiten Covid-19-Welle," ifo Schnelldienst Digital, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 1(15), pages 01-07, November.
    3. Florian Dorn & Janos Gabler & Hans-Martin von Gaudecker & Andreas Peichl & Tobias Raabe & Klara Röhrl, 2020. "Wenn Menschen (keine) Menschen treffen: Simulation der Auswirkungen von Politikmaßnahmen zur Eindämmung der zweiten Covid-19-Welle," ifo Schnelldienst Digital, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 1(15), November.
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    Cited by:

    1. Gabler, Janos & Raabe, Tobias & Röhrl, Klara & Gaudecker, Hans-Martin von, 2021. "Der Effekt von Homeoffice auf die Entwicklung der Covid-19-Pandemie in Deutschland," IZA Standpunkte 100, Institute of Labor Economics (IZA).
    2. Harshana Weligampola & Lakshitha Ramanayake & Yasiru Ranasinghe & Gayanthi Ilangarathna & Neranjan Senarath & Bhagya Samarakoon & Roshan Godaliyadda & Vijitha Herath & Parakrama Ekanayake & Janaka Eka, 2023. "Pandemic Simulator: An Agent-Based Framework with Human Behavior Modeling for Pandemic-Impact Assessment to Build Sustainable Communities," Sustainability, MDPI, vol. 15(14), pages 1-26, July.
    3. Gabler, Janos & Raabe, Tobias & Röhrl, Klara & Gaudecker, Hans-Martin von, 2020. "Die Bedeutung individuellen Verhaltens über den Jahreswechsel für die Weiterentwicklung der Covid-19-Pandemie in Deutschland," IZA Standpunkte 99, Institute of Labor Economics (IZA).
    4. Florian Dorn & Janos Gabler & Hans-Martin von Gaudecker & Andreas Peichl & Tobias Raabe & Klara Röhrl, 2020. "Wenn Menschen (keine) Menschen treffen: Simulation der Auswirkungen von Politikmaßnahmen zur Eindämmung der zweiten Covid-19-Welle," ifo Schnelldienst Digital, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 1(15), November.

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    More about this item

    Keywords

    COVID-19; agent based simulation model; public health measures;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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