English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Data assimilation is used to optimally fit a classical epidemiology model tothe Johns Hopkins data of the Covid-19 pandemic. The optimisation is based onthe confirmed cases and confirmed deaths. This is the only data available withreasonable accuracy. Infection and recovery rates can be infered from the modelas well as the model parameters. The parameters can be linked with governmentactions or events like the end of the holiday season. Based on this numberspredictions for the future can be made and control targets specified. Withother words: We look for a solution to a given model which fits the given datain an optimal sense. Having that solution, we have all parameters.

Adjoint-based Data Assimilation of an Epidemiology Model for the Covid-19 Pandemic in 2020