Related Experiment Video
Updated: Jul 26, 2025

Remote Laboratory Management: Respiratory Virus Diagnostics
Published on: April 6, 2019
epiDonate - distributed serverless data infrastructure for epidemiological studies
Jonas S Almeida1, Bhaumik Patel1, Daniel E Russ1
1National Cancer Institute, Division of Cancer Epidemiology Genetics (DCEG) Rockville, Maryland, USA.
Abstract:
Motivation: Epidemiological studies face two important challenges: the need to ingest ever more complex data types, and mounting concerns about participant privacy and data governance. These two challenges are compounded by the expectation that data infrastructure will eventually need to facilitate cross-registration of participants by multiple epidemiological studies. Implementation: The portable web-service epiDonate was developed using the serverless model known as FaaS (Function-as-a-Service). The reference implementation uses nodejs. The implementation relies on a simple tokenization scheme, mediated by a public API, that a) distinguishes admin from participant roles, with b) extensible permission configuration operating a read/write structure. General Features: The critical design feature of epiDonate is the absence of business logic on the server-side (the web service). The simplicity removes the need to customize virtual machines and enables ecosystems of multiple web Applications backed by one or more data donation deployments. Availability: https://episphere.github.io/donate.
Related Concept Videos
Statistical Software for Data Analysis and Clinical Trials
Statistical Methods for Analyzing Epidemiological Data
Introduction to Epidemiology
Study Designs in Epidemiology
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
Steps in Outbreak Investigation
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...

