How Sickweather Works

Just as Doppler radar scans the skies for indicators of bad weather, Sickweather’s algorithm scans social networks and 3rd party data sources for indicators of illness, allowing you to check for the chance of sickness as easily as you can check for the chance of rain.

Social Listening

Every day thousands of people around the globe update social media sites like Facebook and Twitter when they (or someone close to them) get sick. Posts like "I'm sick," "the doc says I have bronchitis" and "My son has chickenpox." When this information is made publicly available by the user and contains location information, we are able to track and map this data using our patent-pending algorithm.


Sickweather allows its members and 3rd party partners to report directly to our map and forecast anonymously via our mobile apps. Select from a menu of illnesses that we track or post a message to any location you follow in Sickweather Groups. If you report symptoms or illnesses that we aren't tracking, that information will be processed by our algorithm to automatically make suggestions for expanding our tracking capabilities.

Population, Sales & Clinical Data

Our data is regularly correlated and validated against available data from the Centers for Disease Control & Prevention (CDC), point-of-sale data for related medications, and demographic and census data. These data sets help us to know how accurate our other methods are for tracking and forecasting illnesses.

Forecasting & Output

Advanced machine learning models are used to measure the rate of real-time input compared to our extensive archived data (carefully curated since 2011) to predict the rate of illnesses up to 15 weeks in advance with 91% accuracy. We make these predictions and data outputs available via our consumer-facing applications for the general public, as well as our Application Programming Interface (API) and Sickweather Pro SaaS dashboard used by developers, data scientists and epidemiologists across several industries.