cdc-data

Enables Python developers to leverage Debezium's CDC capabilities with custom event handlers and seamless integration.

Automated script developed in Mage.ai to monitor and validate the status of AWS DMS CDC tasks, ensuring data integrity and synchronization. Sends notifications for any detected validation issues.

Data on US ILI, influenza pos lab tests, and total influenza cases from 1998-2019

Interactive geovisualizations of NY cancer data using Plotly

Data decoding, encoding, conversion, and translation utilities.

The Machine Learning APP for "2020-BRFSS-Codebook-CDC".

A simple dashboard to visualize new cases of COVID-19 detected in each of US counties alongside vaccination rate in the area

Visualization of data taken by the Department of Public Health (DPH) and Centers for Disease Control and Prevention (CDC) of new COVID-19 cases in the state of Massachusetts as well as nationwide. Trends of COVID cases depending on vaccine product taken, gender, age group, and vaccination status are visualized. Updated daily.

Sample Microservices to demonstrate CDC events capture across multiple applications. Prototype of Event driven based microservices.

A wrapper for the CDC Wonder Detailed Mortality API meant to alleviate some of its many issues and provide a way of accessing the CDC's data with ease.

Files related to the CDC text classification challenge

Hybrid Quantum-Classical ML platform for early disease detection using biomedical data. Integrates Quantum Variational Classifier (QVC) and SVM with Quantum Kernel for disease classification, benchmarking, and exploring quantum-enhanced healthcare AI. Built with Python, Qiskit/PennyLane & Scikit-learn.

Set up mysql cdc with debezium connect and redpanda

Analysis and visualization of the diabetes mortality statistics in the different states of the US, using the latest data avilable in HealthData.gov obtained from the CDC.

CrateDB destination connector for Estuary.

A practical Change Data Capture pipeline that captures PostgreSQL changes with Debezium, streams them through Kafka, and applies them to DuckDB

Streamlit to search for NHANES tables and generate a python script to import those tables.

Analyzing 3.5M+ CDC birth records to explore how maternal health factors influence infant birth outcomes using Python, Pandas, and data analytics.

A lightweight distributed CDC engine built in Java from scratch to process low-level PostgreSQL logical replication streams natively. Custom WAL parser that translates mutations into structured events for Kafka pipelines without heavy polling overhead. Features atomic LSN tracking for fault-tolerant at-least-once delivery. - (My Own Debezium 😉)

Reproducible analysis of U.S. metabolic disease: state obesity trends, county spatial epidemiology (Moran's I / LISA), and socioeconomic confounders, built on CDC BRFSS, PLACES, and Census ACS.