- Netzwerk: RatSWD
- Disziplin: Sozial, Wirtschaft, Gesundheit
- Forschungsmethode: Quantitativ
- Forschungsdesign: Weitere Daten (z. B. Einzelinterview, Web Scraping, Laborwerte etc.), Sekundäranalyse
- Erhebungsstatus: Ergebnisse veröffentlicht, Erhebung abgeschlossen
Ziele der Studie
This paper develops a quantitative model incorporating factors which influence the infection rates, simultaneously. The framework allows to combine a wide variety of data and mechanisms in a timely fashion, making it useful to predict the effects of various interventions. The researchers apply the model to Germany, where new infections fell by almost 80% during the month of May 2021. The analysis shows that, aside from seasonality, frequent and large-scale rapid testing caused the bulk of this decrease, which is in line with prior predictions.
At the core of the agent-based model are physical contacts between heterogeneous agents. Each contact between an infectious individual and somebody susceptible to the disease bears the risk of transmitting the virus. Contacts occur in up to four networks: Within the household, at work, at school, or in other settings (leisure activities, grocery shopping, medical appointments, etc.). Some contacts recur regularly, others occur at random. Empirical applications can take the population and household structure from census data and the network-specific frequencies of contacts from diary data measuring contacts before the pandemic. Within each network, meeting frequencies depend on age and geographical location. The four contact networks are chosen so that the most common NPIs can be modeled in great detail. NPIs affect the number of contacts or the risk of transmitting the disease upon having physical contact. The effect of different NPIs will generally vary across contact types. For example, a mandate to work from home will reduce the number of work contacts to zero for a fraction of the working population. The model includes several other features, which are crucial to describe the evolution of the pandemic in 2020-2021. New virus strains with different profiles regarding infectiousness can be introduced. Agents may receive a vaccination. With a probability of 75%, vaccinated agents become immune and they do not transmit the virus.
Die Daten dieser Studie stehen bisher nicht zur offenen Nachnutzung zur Verfügung. Bitte wenden Sie sich an die Ansprechpersonen des Projekts.