Predicting Dengue With Baidu

For those who attended my talk on “Crowdsourcing in Health & Healthcare” during HIMSS Asia Pacific 2014 – Digital Healthcare Week in Singapore; this is another example to the topic. (Original article taken from AsianScientist.com

AsianScientist (Nov. 20, 2014) – The habit of Googling for an online diagnosis before visiting the doctor can be a powerful predictor of infectious diseases outbreaks. Now, research published in PLoS One shows that combining information from monitoring internet search metrics such as Baidu (China’s equivalent of Google), with a web-based infectious disease alert system from reported cases and environmental factors hold the key to improving early warning systems and reducing the deadly effects of dengue fever in China.

Dr. Hu Wenbiao, from the Queensland University of Technology (QUT), has spent more than 20 years working in the area of public health and infectious diseases. He said early detection was vital to reducing the impact of infectious diseases.

“Dengue fever is the most rapidly spreading vector-borne disease—with a 30-fold increase in global incidence over the past 50 years, affecting more than 50 million people annually,” Dr. Hu said.

“In China dengue fever has been a major public health concern since it re-emerged in Guangdong province in 1978 and there have been more than 650,000 cases reported since then. Guangdong has seen a significant surge in dengue fever cases this year with already 42,856 reported.”

“What we have found through our research is that affected areas appear to have been expanding in Guangdong over recent years, which indicates potentially increasing risk for unaffected areas in other parts of Guangdong province. The solution is early detection of dengue fever in China to enable prevention and control the disease and reduce sickness and death.”

Working with the Chinese Center for Disease Control and Prevention, researchers at QUT tested the individual performance of internet-based surveillance, an automated dengue fever alert system and monitoring of environmental factors such as temperature, humidity and rainfall.

“What we have found is that internet-based surveillance such as monitoring search engines like Baidu, could accurately predict outbreaks of infectious disease such as dengue fever up to a few weeks faster than traditional surveillance methods,” Dr. Hu said.

“This is because traditional surveillance relies on the patient recognizing the symptoms and seeking treatment before diagnosis, along with the time it takes for a doctor or health professional to alert authorities through their health networks.”

Incorporating internet-based information could further improve the China Infectious Disease Automated-alert and Response System (CIDARS) developed by the Chinese Center of Disease Control and Prevention, according to Dr. Hu.

“Our studies have found the CIDARS achieved 99.8 percent success in detecting dengue fever outbreaks in three days, but one of the limitations is it is difficult to predict dengue fever outbreaks before cases are diagnosed and reported.”

“If we can incorporate internet-based monitoring with CIDARS as well as account for socio-ecological factors such as changes in human movement, temperature, humidity and rainfall, a more rapid response is possible.”

About Adam Chee

Health Informatician
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