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Methods & About

Evidence you can trace back to its source

GIDS organizes infectious disease surveillance records published by public health authorities, making them easier to find, understand, and verify while preserving the context of the original reports.

Public data snapshot updated September 1, 2026. Coverage and publication schedules vary by source.

Project & maintainer

What began as a record at home grew into a global surveillance project

GIDS did not begin with a complete roadmap. In 2021, I simply wanted to preserve surveillance data that kept changing and disappearing into scattered webpages and spreadsheets. That personal archive gradually became the public project I still maintain today.

  1. It started with a personal need

    When COVID-19 forced me to study remotely from home, I began organizing China's monthly notifiable infectious disease reports so that each release would not disappear into another webpage or spreadsheet.

  2. The archive became part of the research

    Several years of accumulation supported research with my collaborators on changes in 24 notifiable infectious diseases in China before and during COVID-19.

    Read the 2024 paper
  3. The same approach moved beyond China

    The project began expanding globally. This meant more than adding country pages: it required understanding different reporting systems while keeping the original context of every source visible.

  4. Current

    Making a personal project sustainable

    With help from Codex, I continue to add sources and reshape the collection, standardization, checking, and publication workflows.

Maintainer

Kangguo Li

Doctoral researcher, School of Public Health, Xiamen University

I am pursuing a doctorate in Epidemiology and Health Statistics and expect to graduate in 2027. GIDS is not only a portfolio project for me; it is a long-running way to practice putting public health questions, real-world data, software engineering, and reviewable evidence together.

  • Epidemiology
  • Health statistics
  • Health data
  • Data engineering
  • Health AI

Internships, postdoctoral roles & collaboration

I am looking for internship opportunities in public health, epidemiology, health statistics, health-data platforms, or health AI, and I would also be glad to connect early with potential postdoctoral teams. I hope to join a group that takes data quality, open methods, and practical public health questions seriously, and to do careful, useful work across research and engineering. I can contribute remotely worldwide or work on site in mainland China or Hong Kong.

Data & methods

How data reaches the site

Only public records that pass basic provenance, completeness, and consistency checks are published. These figures describe the current snapshot, not the full global burden of infectious disease.

Countries and regions
83
Diseases tracked
239
Published records
501,369,967
Latest reporting date
2026-09-01

Time coverage 1924-01-01 – 2026-09-01

  1. 01

    Collect

    Retrieve newly published records from configured official health authority sources.

  2. 02

    Standardize

    Align disease names, places, dates, and measures while preserving the original reporting grain.

  3. 03

    Check

    Review completeness, consistency, provenance, and publication conditions before release.

  4. 04

    Publish

    Refresh pages and downloads while retaining source links, limitations, and correction routes.

Official sources

Each dataset retains the responsible authority, source link, and coverage period.

Context stays visible

Reporting systems are not assumed to be directly comparable; original definitions and temporal grain remain visible.

Missing is not zero

Unavailable fields and unreported periods remain missing rather than being silently converted to zero.

Responsible use

How to use GIDS responsibly

These data support surveillance, research, and evidence navigation, but should not be interpreted outside the context of the original reporting system.

01

Not a clinical or outbreak declaration tool

GIDS does not replace guidance from national or local health authorities and should not be used for personal diagnosis or risk decisions.

02

Figures change and systems differ

Case definitions, covered populations, reporting delays, and temporal grain vary. Read the source notes before making cross-jurisdiction comparisons.

03

Automation needs public correction routes

Collection, standardization, and parts of summarization are software-assisted. Reports should include the page, period, and official comparison source.

04

Independence and reuse

GIDS is an independent public-interest project and does not represent linked institutions. Code, public data products, and third-party sources follow their separately stated rules.

Acknowledgements

Acknowledgements and Support

GIDS has benefited from the intellectual guidance, collegial feedback, and practical support of colleagues and mentors. The author gratefully acknowledges the following individuals for their contributions to the development of this project.

Tianmu Chen

School of Public Health, Xiamen University

Provided both thoughtful advice and financial support, enabling the project to continue its development and maintenance.

  • Academic Advice
  • Financial Support

Benjamin Rader

Harvard Medical School; Boston Children's Hospital

Provided valuable comments on the site's structure, content organisation, and overall presentation.

  • Academic Advice

This acknowledgement record will be maintained and expanded as the project continues to develop.