Mathematical modeling of disease transmission has provided quantitative predictions for
health policy, facilitating the evaluation of epidemiological outcomes and the cost …

The use of healthcare data analytics is anticipated to play a significant role in future public
health policy formulation. Therefore, this study examines how big data analytics (BDA) may …

This paper introduces and discusses key issues in the economic evaluation of digital health
interventions. The purpose is to stimulate debate so that existing economic techniques may …

Simulation models play a critical role in informing health policy. Models allow researchers to
anticipate the implications of policies by integrating disparate sources of evidence and …

The potential of system dynamics modeling to advance our understanding of cumulative risk
in the service of optimal health is discussed. The focus is on exploring system dynamics …

This scholarly paper delves into the realm of data science in public health, with a specific
focus on the transformative role of predictive analytics in disease control across the United …

Ensuring the conditions for all people to be healthy, though always the core mission of
public health, has evolved in approaches in response to the changing epidemiology and …

Sensors are becoming ubiquitous in everyday life, generating data at an unprecedented rate
and scale. However, models that assess impacts of human activities on environmental and …

Biomedical data encompasses images, texts, physiological signals, and molecular omics
data. As the costs of various data acquisition methods, such as genomic sequencing …

As we work to move the NIEHS forward, it is important that we critically consider how our
research can have the greatest impact on public health. In last month's Director's …