Analysis of public attention characteristics of rare diseases on the Internet.

Corresponding author: Yang Jing, yangjlm@126.com

DOI: 10.12201/bmr.202304.00002

•  

  Abstract: Objective/Significance To realize the characteristics of public attention to rare diseases related information, in order to provide ideas for future research and policy formulation. Methods/Process With “rare diseases” as the keyword, the “search index” data were collected from January 1, 2012 to December 31, 2021, and summarized by year and month for secondary analysis. “Population portraits” were collected from September 1 to September 30, 2022, and the top 10 regions in terms of online attention to rare diseases were collected in each year from 2013 to 2021. Results/Conclusion From the perspective of time, the search index of rare diseases showed an increasing trend from 2012 to 2021, and it is highest on International Rare Disease Day. From the perspective of population distribution, the middle-aged women between 20 and 40 years old are the main concern group, and the proportion of female search volume is higher than that of male, 63.76% and 36.24% respectively. From the perspective of region, the province with the highest attention of rare diseases is Guangdong, and the top 3 cities are Beijing, Shanghai and Guangzhou. The publics attention to rare diseases shows an increasing trend on the whole. The differences of time distribution, gender, age and region affect the attention to rare diseases, among which the publicity of news media, policy release and the high proportion of children can increase the attention to rare diseases. In order to increase the public attention to rare diseases, we should strengthen the publicity and education of rare diseases.

  Key words: rare diseases; search index; attention

  Submit time: 3 April 2023

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
• html

• 图表

• Zhang Xiaoxing, Zhou Tingting, PAN JAY. Implications on the Model of Drug Guarantee for Rare Diseases at Domestic and Abroad. 2020. doi: 10.12201/bmr.202009.00016

  Zhu Xiaoxiao, Qian Aibing. Analysis of Network Attention Characteristics of Breast Cancer Prevention and Treatment Health Information Based on Baidu Index. 2020. doi: 10.12201/bmr.201906.00001

  wangyuanru, huzixin, xiejinping, shaorong. Analysis of the European Unions Orphan Drug Designation Policy and Its Enlightenment to China. 2022. doi: 10.12201/bmr.202207.00031

  Li Ru-yin, Zhang Xiao-xing. Research on Health Information Attention Behavior of WeChat Users Based on grounded theory. 2020. doi: 10.12201/bmr.202004.00037

  Zeng hongwu, Dai shuqiu. Medical Internet of Things: monitoring of intelligent vital signs in chronic diseases. 2022. doi: 10.12201/bmr.202206.00008

  Deng Lan, Du Tongzhou. An Efficient, Secure and Multi-keyword Search Scheme on Encrypted Electronic Medical Records. 2021. doi: 10.12201/bmr.202105.00008

  YANG Ziliang, ZHAO Zixiong, ZHANG Yewu, MA Jiaqi. A Research on the Construction of a Case Epidemiological Portrait Labeling System for Respiratory Infectious Diseases. 2022. doi: 10.12201/bmr.202112.00010

  HU Haiyang, ZHAO Congpu, Ma Lian, JIANG Huizhen, ZHANG Jing, ZHU Weiguo. Attention Mechanism And Dilated Convolution Neural Networks for Named Entity Recognition. 2021. doi: 10.12201/bmr.202102.00004

  FENG Hao-ran, LIANG Di. Public Partnerships of the Global Fund to fight AIDS, tuberculosis and malaria and the implications for China. 2022. doi: 10.12201/bmr.202210.00020

  HU Guang-yu, TAO Chenglin, Zeng De-wei, Lin De-nan. Measure of specialty case-mix index based on standardization of patient groups distribution. 2020. doi: 10.12201/bmr.202005.00251

• ID	Submit time	Number	Download
  1	2022-12-16	bmr.202304.00002V1	Download

• Public  Anonymous  To author only Submit Comments