Dataset Information

A machine learning method to monitor China's AIDS epidemics with data from Baidu trends.

ABSTRACT:

Background

AIDS is a worrying public health issue in China and lacks timely and effective surveillance. With the diffusion and adoption of the Internet, the 'big data' aggregated from Internet search engines, which contain users' information on the concern or reality of their health status, provide a new opportunity for AIDS surveillance. This paper uses search engine data to monitor and forecast AIDS in China.

Methods

A machine learning method, artificial neural networks (ANNs), is used to forecast AIDS incidences and deaths. Search trend data related to AIDS from the largest Chinese search engine, Baidu.com, are collected and selected as the input variables of ANNs, and officially reported actual AIDS incidences and deaths are used as the output variable. Three criteria, the mean absolute percentage error, the root mean squared percentage error, and the index of agreement, are used to test the forecasting performance of the ANN method.

Results

Based on the monthly time series data from January 2011 to June 2017, this article finds that, under the three criteria, the ANN method can lead to satisfactory forecasting of AIDS incidences and deaths, regardless of the change in the number of search queries.

Conclusions

Despite the inability to self-detect HIV/AIDS through online searching, Internet-based data should be adopted as a timely, cost-effective complement to a traditional AIDS surveillance system.

SUBMITTER: Nan Y

PROVIDER: S-EPMC6040727 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

A machine learning method to monitor China's AIDS epidemics with data from Baidu trends.

Nan Yongqing Y Gao Yanyan Y

PloS one 20180711 7

<h4>Background</h4>AIDS is a worrying public health issue in China and lacks timely and effective surveillance. With the diffusion and adoption of the Internet, the 'big data' aggregated from Internet search engines, which contain users' information on the concern or reality of their health status, provide a new opportunity for AIDS surveillance. This paper uses search engine data to monitor and forecast AIDS in China.<h4>Methods</h4>A machine learning method, artificial neural networks (ANNs), ...[more]

PMID: 29995920

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Dataset Information

A machine learning method to monitor China's AIDS epidemics with data from Baidu trends.

Background

Methods

Results

Conclusions

Publications

A machine learning method to monitor China's AIDS epidemics with data from Baidu trends.

Similar Datasets

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