Intervention strategies against COVID-19 and their estimated impact on Swedish healthcare capacity

Jasmine M Gardner; Lander Willem; Wouter van der Wijngaart; Shina Caroline Lynn Kamerlin; Nele Brusselaers; Peter Kasson

(which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.11.20062133 doi: medRxiv preprint Socio-geographic differences between countries affect the speed and impact of the pandemic-these include population density, household structure, social contact patterns, and governmental measures implemented to hinder or stop the spread of the virus. While the pandemic is still ongoing and exact statistics are not available, numerical modelling provides timely guidance for healthcare needs given multiple scenarios, as it permits predictions based on available epidemiological and demographic data. 14 Predictive models for COVID-19 have been used to assess the impact of the pandemic and guide national policy. 2 3 15-19 While aggregate population models yield the basic principles of epidemic spread, discrete models that take into account geographic and demographic structure permit more specific assessment of different interventions in national contexts. Individual-based discrete models -also called agent-based models, since every individual of a geographic region is modelled by an agentprovide a flexible platform to analyse the propagation of emerging infectious diseases and the effect of social distancing and similar behavioural changes. 20 In these individual-based models, the behaviour and health state of each individual in a country is modelled, enabling explicit representation of social-contact patterns between individuals in the household, school, workplace and community. These models similarly permit explicit representation of age-and location-specific social distancing such as school closure, increased telework, or geographic quarantine measures.