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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We discovered that the time evolution of the inverse fractional daily growthof new infections, N/dN, in the current outbreak of COVID-19 is accuratelydescribed by a universal function, namely the two-parameter Gumbel cumulativefunction, in all countries that we have investigated. While the two Gumbelparameters, as determined bit fits to the data, vary from country to country(and even within different regions of the same country), reflecting thediversity and efficacy of the adopted containment measures, the functional formof the evolution of N/dN appears to be universal. The result of the fit in agiven region or country appears to be stable against variations of the selectedtime interval. This makes it possible to robustly estimate the two parametersfrom the data data even over relatively small time periods. In turn, thisallows one to predict with large advance and well-controlled confidence levels,the time of the peak in the daily new infections, its magnitude and duration(hence the total infections), as well as the time when the daily new infectionsdecrease to a pre-set value (e.g. less than about 2 new infections per day permillion people), which can be very useful for planning the reopening ofeconomic and social activities. We use this formalism to predict and comparethese key features of the evolution of the COVID-19 disease in a number ofcountries and provide a quantitative assessment of the degree of success in intheir efforts to countain the outbreak.

Early forecasts of the evolution of the COVID-19 outbreaks and quantitative assessment of the effectiveness of countering measures