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BioDiaspora predicts Hajj and Umrah as two key possible spread points for MERS coronavirus

BioDLogo_whiteBioDiaspora, a start-up company based on the research of company founder, Dr. Kamran Khan of St. Michael’s Hospital, has identified two mass gatherings in the Islamic world as key possible spread points for the life-threatening MERS coronavirus, which emerged in the Middle East in early 2012.

BioDiaspora’s disease-tracking platform, which correlates uses global air traffic patterns to predict the international spread of infectious disease (as described in the original media release from St. Michael’s Hospital):

The first is umrah, a pilgrimage that can be performed at any time of year but is considered particularly auspicious during the month of Ramadan, which this year began on July 9 and ends on Aug. 7. The second is the hajj, a five-day pilgrimage required of all physically and financially able Muslims at least once in their life. It takes place Oct. 13 to 18 this year and is expected to draw more than 3 million people.

Predicted spread of MERS virus based on hajj travel pattters. Source: Potential for the International Spread of Middle East Respiratory Syndrome in Association with Mass Gatherings in Saudi Arabia/PLOS Currents Outbreaks.
Predicted spread of MERS coronavirus based on hajj travel patterns. Source: Potential for the International Spread of Middle East Respiratory Syndrome in Association with Mass Gatherings in Saudi Arabia/PLOS Currents Outbreaks.

It also identified the Mumbai-India corridor as particularly vulnerable to MERS based on the predicted exit traffic of travelers leaving the hajj and returning to their home countries following the mass religious event.

Khan’s research findings, published in PLOS Currents: Outbreaks, have attracted media coverage from the Times of India, CanIndia, Toronto Star‘s Foreign Desk blog (Jennifer Yang), Science Daily.com, DowntoEarth.org and Homeland Security News Wire.

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Kaypok Unveils Root Cause Analysis Solution for Why Consumers Behave

Company to Present on Social Media Behavior and Deep Root Cause Analysis at iStrategy Toronto December 4

TORONTO (December 4, 2012) — Companies are drowning in a sea of big, unstructured, noisy data. Whether it’s social media chatter, email or survey results, how do you filter the noise and take action?

Kaypok Inc., a company spun off from York University research with support and funding from MaRS Innovation, uses a contextual natural language process to automatically interpret the meaning of raw data — without analysts, advance preparation, special databases or lag time.

Read the start-up company profile of Kaypok Inc. on the MaRS Innovation website.

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