The use of artificial intelligence (AI) to generate automated early warnings in epidemic
surveillance by harnessing vast open-source data with minimal human intervention has the …

Abstract On April 23, 2022, the Ministry of Health of the Democratic Republic of the Congo
announced an EVD outbreak after discovering 2 confirmed cases and identifying 267 …

Predicting, issuing early warnings, and assessing risks associated with unnatural epidemics
(UEs) present significant challenges. These tasks also represent key areas of focus within …

Objectives This study aims to create an enhanced EPIRISK tool in order to correctly predict
COVID-19 severity in various countries. The original EPIRISK tool was developed in 2018 to …

In order to prevent and control the increasing number of serious epidemics, the ability to
predict the risk caused by emerging outbreaks is essential. However, most current risk …

Background: Novel surveillance approaches using digital technologies, including the
Internet of Things (IoT), have evolved, enhancing traditional infectious disease surveillance …

Emerging infections are a continual threat to public health security, which can be improved
by use of rapid epidemic intelligence and open-source data. Artificial intelligence systems to …

Background With double pressures of endemic and imported emerging infectious diseases
(EIDs), China's ability to detect, prevent and control the unknown virus is of regional and …

Between April 2018 and November 2020, the Democratic Republic of Congo (DRC)
experienced its 11th Ebola virus disease (EVD) outbreak. Tanzania's cross-border …

The frequency of serious epidemics has continued to increase in the last decade. The ability
to predict the risk of outbreaks can improve prevention and control. There are few prediction …