Saturday, March 28, 2020

Science Versus the Rumour Mill

"Predicting the development of the outbreak as early and as reliably as possible is critical for action to prevent its spread."
"Internet surveillance data provided an accurate and timely prediction about the outbreak and progression of COVID-19."
Cuilian Le, Shanton University, Shanton, China

"[Two popular search engines and a popular social-media platform] were able to predict the disease outbreak one to two weeks earlier than the traditional surveillance systems."
"COVID-19 is a rapidly spreading infectious disease. It is important to predict the development of this outbreak as early and as reliably as possible, in order to take action to prevent its spread."
"The availability of early information about infectious diseases through Internet search engines and social media will be helpful for making decisions related to disease control and prevention."
"This study reveals the advantages of Internet surveillance using Sina Weibo Index, Google Trends and Baidu Index to monitor a new infectious disease."
"Reliable data can be obtained early at low cost."
Research study, Eurosurveillance journal 
Medical workers from outside Wuhan check their mobile phones at a riverside park by the Yangtze River in Wuhan of Hubei province, the epicentre of China’s coronavirus disease (COVID-19) outbreak, March 26, 2020. Reuters/Stringer
There is the meticulous research that is carried out by researchers based on data, that is time-consuming and precise and reliable. And then there is another kind of 'research' which is really observational, taking note of the number of times that individuals seek information online through popular search engines about the very same topic that scientists are focusing on. The surge of public interest enquiries, however, is much more immediate in the results obtained by observing their numbers to alert to a pending health concern of great magnitude.

And if the health community takes its cue from the sudden surge of public interest, to react swiftly and appropriately to stem a rising tide of infections, they would have the benefit of acting earlier with the end result that they have the opportunity to respond more swiftly with a more effectively reactive outcome. A new study suggests that search engine traffic is able to predict virus hotspots well before the spread of an infection sends rising numbers of people to hospitals. 

Published in Eurosurveillance, a journal on infectious disease surveillance that is peer-reviewed and associated with the European Centre for Disease Prevention and Control, this novel method of tracking an impending public medical concern to enable the health community tr respond efficiently and more immediately before the issue becomes an emergency, speaks directly to the lag in response currently at issue in the case of the global pandemic of the novel coronavirus epidemic.

The traffic generated by public enquiries on the outbreak suggests that search engine traffic provides a reliable measurement of emerging viral hotspots far in advance of hospitals being besieged by patients struck down by an epidemic. Monitoring search engine enquiries routinely could have given health authorities a much earlier window on the viral contamination whose spread has arrested the world in a chaotic effort to stem the tide. Which has become a dread public health threat, and destabilized the global marketplace in the process.

Researchers first examined daily numbers of new laboratory-confirmed cases and suspected cases of the novel coronavirus from the National Health commission of China in the first several months of the COVID-19 emergence in Wuhan, China. February 4 represented the peak of daily new laboratory-confirmed cases while February 5 represented the peak of daily new suspected cases. This was compared with search enquiries and social media posts in China using Google, Baidu, and Sina Weibo, for the weeks prior to the laboratory virus data.

January 25 represented the peak number of searches in Baidu for "coronavirus" and "pneumonia", and the same date resulted for the peaks for the same keywords on Google Trends. The translation of that data is that the peak of apparent citizen concern related to a spreading viral illness was eight to ten days sooner than laboratory-confirmed cases and five to seven days earlier than new suspected cases.

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