Well-being is an important value for people's lives, and it could be considered as an index of
societal progress. Researchers have suggested two main approaches for the overall …

Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic
status are significant for economic development. The understanding of socioeconomic …

Given still-high levels of coronavirus disease 2019 (COVID-19) susceptibility and
inconsistent transmission-containing strategies, outbreaks have continued to emerge across …

We present a machine learning-based methodology capable of providing real-time
(“nowcast”) and forecast estimates of influenza activity in the US by leveraging data from …

We present a timely and novel methodology that combines disease estimates from
mechanistic models with digital traces, via interpretable machine-learning methodologies, to …

Accurate real-time tracking of influenza outbreaks helps public health officials make timely
and meaningful decisions that could save lives. We propose an influenza tracking model …

Background Over 400,000 people across the Americas are thought to have been infected
with Zika virus as a consequence of the 2015–2016 Latin American outbreak. Official …

Public health thrives on high-quality evidence, yet acquiring meaningful data on a
population remains a central challenge of public health research and practice. Social …

Novel data streams (NDS), such as web search data or social media updates, hold promise
for enhancing the capabilities of public health surveillance. In this paper, we outline a …

Background The inherent difficulty of identifying and monitoring emerging outbreaks caused
by novel pathogens can lead to their rapid spread; and if left unchecked, they may become …