Towards cross-lingual alerting for bursty epidemic events

TL;DR

This paper explores cross-lingual alerting for epidemic outbreaks by analyzing multilingual news reports, demonstrating improved detection sensitivity and timeliness through correlated event analysis across languages.

Contribution

It introduces a method for utilizing correlated multilingual news reports to enhance early warning systems for disease outbreaks, with a detailed case study and an available alerting algorithm.

Findings

Improved sensitivity, F1, and timeliness in outbreak detection across 13 languages.

Cross-lingual event correlation enhances early warning capabilities.

Case study on Cholera in Angola 2010 highlights practical challenges.

Abstract

Background: Online news reports are increasingly becoming a source for event based early warning systems that detect natural disasters. Harnessing the massive volume of information available from multilingual newswire presents as many challenges as opportunities due to the patterns of reporting complex spatiotemporal events. Results: In this article we study the problem of utilising correlated event reports across languages. We track the evolution of 16 disease outbreaks using 5 temporal aberration detection algorithms on text-mined events classified according to disease and outbreak country. Using ProMED reports as a silver standard, comparative analysis of news data for 13 languages over a 129 day trial period showed improved sensitivity, F1 and timeliness across most models using cross-lingual events. We report a detailed case study analysis for Cholera in Angola 2010 which highlights the challenges faced in correlating news events with the silver standard. Conclusions: The results show that automated health surveillance using multilingual text mining has the potential to turn low value news into high value alerts if informed choices are used to govern the selection of models and data sources. An implementation of the C2 alerting algorithm using multilingual news is available at the BioCaster portal http://born.nii.ac.jp/?page=globalroundup.