This project provides a platform to collect detailed data about diseases outbreaks, directly from patients using their mobile devices. This data serves to warn users about hazardous areas to avoid them, and to visually compare with environmental factors such as temperature and humidity. The platform has been implemented as a prototype that addresses the case of influenza, with data from MODIS, Shizuku, and Japanese health centers for comparison.



Diseases outbreaks are affecting our society every year with significant impact. We try to protect ourselves by studying these diseases and the environment in which they spread. There exist several studies that correlate diseases with environmental factors, but there is no platform that allows to gather fine-grained data and enact the comparison of isolated studies.

At Present

Several research results show some correlation between diseases and environmental measurements such as temperature or humidity (a few documents are available on the NASA web site). These results are usually focused on a single environmental factor, and they mostly base conclusions on past data.


This project has developed a platform that enacts online collection and summarization of data, and tools to simplify their comparison. Its features are:

  • A desktop and mobile web application for patients to register their disease.
  • An infection map that consists of a map of the world and a "heat map" overlay that shows high-risk disease transmission areas.
  • A privacy approach that builds map and reports based on anonymous and aggregate data only.
  • Temperature overlay based on the MODIS Land Surface Temperature (LST) data sets.
  • Humidity overlay based on the SHIZUKU precipitation data sets provided by hi-rezclimate team, ISAC 2014-Tokyo ( with simplified correlation model to humidity.

We believe this platform is applicable to several diseases such as influenzas, dengue, malaria, and other infectious diseases.


The time devoted to this project has focused on influenza, due to the availability of data from various sources.

The prototype is based on some decisions to be able to build a proof of concept within ISAC 2014: The data has been reduced to the Kanto region around Tokyo, to make data processing finish in reasonable time. The privacy approach to avoid showing individual records is a simple area average.

The prototype is available at Crowdy (it may be offline at times for maintenance). It has been tested and working on: Desktop browsers: Firefox and Safari (latest versions at this time). Mobile Safari

Project Information

License: MIT license (MIT)

Source Code/Project URL:


InfectionMap -


  • Yuichi Yazaki
  • Wataru Ohira
  • Eric Platon