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

We present a simple, fast, and easily interpretable procedure that results in faster detection of outbreaks in multiple spatial regions. Disease counts from neighboring regions are aggregated to compute a Poisson CUSUM statistic for each region. Instead of controlling the average run length error criterion in the testing process, we instead utilize the false discovery rate. Additionally, p-values are used to make decisions instead of traditional critical-values. The use of the false discovery rate and p-values in testing allows us to utilize more powerful multiple testing methodologies. The procedure is successfully applied to detect the 2011 Salmonella Newport outbreak in Germany.

An Improved EWMA-Based Method for Outbreak Detection in Multiple Regions