Abstract Machine learning (ML) methods can be leveraged to prevent the spread of deadly
infectious disease outbreak (eg, COVID-19). This can be done by applying machine learning …

Background Public health surveillance is based on the continuous and systematic collection,
analysis, and interpretation of data. This informs the development of early warning systems …

The novel coronavirus disease (COVID-19) pandemic has impacted every facet of society.
One of the non-pharmacological measures to contain the COVID-19 infection is social …

In the recent years, we have been witnessing a digital revolution in public and global health
creating unprecedented opportunities for epidemic intelligence and public health …

With the massive spike in the use of Online Social Network Sites (OSNSs) platforms such as
Web 2.0, microblogs services and online blogs, etc., valuable information in the form of …

The debate over the COVID-19 pandemic is constantly trending at online conversations
since its beginning in 2019. The discussions in many social media platforms is related not …

Social media platforms are widely used by people to report, access, and share information
during outbreaks and epidemics. Although government agencies and healthcare institutions …

Background The development of technology and information systems has led to important
changes in public health surveillance. Objective This scoping review aimed to assess the …

Social media (SM) based surveillance systems, combined with machine learning (ML) and
deep learning (DL) techniques, have shown potential for early detection of epidemic …

Epidemiology and Public Health have increasingly relied on structured and unstructured
data, collected inside and outside of typical health systems, to study, identify, and mitigate …