Using the Internet Big Data to Investigate the Epidemiological Characteristics of Allergic Rhinitis and Allergic Conjunctivitis
Huijun Qiu,1,* Rui Zheng,1,* Xinyue Wang,1,* Zhuanggui Chen,2,3 Peiying Feng,2,4 Xuekun Huang,1,2 Yuqi Zhou,2,5 Jin Tao,2,6 Min Dai,2,7 Lianxiong Yuan,8 Xiangdong Wang,9 Luo Zhang,9 Qintai Yang1,2 1Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen Unive...
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Dove Medical Press
2021-05-01
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| Series: | Risk Management and Healthcare Policy |
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| Online Access: | https://www.dovepress.com/using-the-internet-big-data-to-investigate-the-epidemiological-charact-peer-reviewed-fulltext-article-RMHP |
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| author | Qiu H Zheng R Wang X Chen Z Feng P Huang X Zhou Y Tao J Dai M Yuan L Wang X Zhang L Yang Q |
| author_facet | Qiu H Zheng R Wang X Chen Z Feng P Huang X Zhou Y Tao J Dai M Yuan L Wang X Zhang L Yang Q |
| author_sort | Qiu H |
| collection | DOAJ |
| description | Huijun Qiu,1,* Rui Zheng,1,* Xinyue Wang,1,* Zhuanggui Chen,2,3 Peiying Feng,2,4 Xuekun Huang,1,2 Yuqi Zhou,2,5 Jin Tao,2,6 Min Dai,2,7 Lianxiong Yuan,8 Xiangdong Wang,9 Luo Zhang,9 Qintai Yang1,2 1Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 2Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 3Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 4Department of Dermatology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 5Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 6Department of Gastroenterol, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 7Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 8Department of Science and Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 9Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qintai YangDepartment of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, People’s Republic of ChinaTel +86-20-85252252Fax +86-20-85253336Email yangqint@mail.sysu.edu.cnLuo ZhangDepartment of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, No. 16 Hougou Hutong, Chongnei Street, Donghuamen Street, Dongcheng District, Beijing, 100730, People’s Republic of ChinaTel +86-10-65141136Fax +86-10-85115988Email dr.luozhang@139.comBackground: To explore the epidemiological characteristics of allergic rhinitis (AR) and allergic conjunctivitis (AC) based on the Internet big data.Methods: The Baidu index (BDI) of keywords “allergic rhinitis” and “allergic conjunctivitis” in Mandarin, the daily pollen concentration (PC) released by the Beijing Meteorological Bureau and the volumes of outpatient visits (OV) of the Beijing Tongren Hospital (Beijing) and the Third Affiliated Hospital of Sun Yat-sen University (Guangzhou) from 2017 to 2020 were obtained. The temporal and spatial changes of AR and AC were discussed. The correlations between BDI and PC/OV were analyzed by Spearman correlation analysis.Results: The trends of BDI of “AR”/“AC” in Beijing showed obvious seasonal variations, but not in Guangzhou. The BDI of “AR” and “AC” was consistent with the OV in both cities (r1AR-BJ=0.580, P< 0.001; r1AR-GZ=0.360, P=0.031; r1AC-BJ=0.885, P< 0.001; r1AC-GZ=0.694, P< 0.001). The BDI of “AR” and “AC” was highly consistent with the change of the PC in Beijing (r AR-Pollen=0.826, P< 0.001; r AC-Pollen=0.564, P< 0.001). The OV of AR in Beijing and Guangzhou decreased significantly in the first half of 2020, but there was no significant change in AC. In the first half of 2020, the OV of AC in Beijing was significantly higher than that of AR, while that of AC in Guangzhou was slightly higher than that of AR.Conclusion: The BDI could reflect the real-world situation to some extent and has the potential to predict the epidemiological characteristics of AR and AC. The BDI and OV of AR decreased significantly, but those of AC were still at a high level, during the COVID-19 pandemic, in the environment where most people in Beijing and Guangzhou wore masks without eye protection.Keywords: allergic rhinitis, allergic conjunctivitis, Internet, Baidu, big data, COVID-19 |
| first_indexed | 2024-12-20T12:22:15Z |
| format | Article |
| id | doaj.art-e079462cfd644e5da8b8cf5774be4b8e |
| institution | Directory Open Access Journal |
| issn | 1179-1594 |
| language | English |
| last_indexed | 2024-12-20T12:22:15Z |
| publishDate | 2021-05-01 |
| publisher | Dove Medical Press |
| record_format | Article |
| series | Risk Management and Healthcare Policy |
| spelling | doaj.art-e079462cfd644e5da8b8cf5774be4b8e2022-12-21T19:40:56ZengDove Medical PressRisk Management and Healthcare Policy1179-15942021-05-01Volume 141833184164535Using the Internet Big Data to Investigate the Epidemiological Characteristics of Allergic Rhinitis and Allergic ConjunctivitisQiu HZheng RWang XChen ZFeng PHuang XZhou YTao JDai MYuan LWang XZhang LYang QHuijun Qiu,1,* Rui Zheng,1,* Xinyue Wang,1,* Zhuanggui Chen,2,3 Peiying Feng,2,4 Xuekun Huang,1,2 Yuqi Zhou,2,5 Jin Tao,2,6 Min Dai,2,7 Lianxiong Yuan,8 Xiangdong Wang,9 Luo Zhang,9 Qintai Yang1,2 1Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 2Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 3Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 4Department of Dermatology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 5Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 6Department of Gastroenterol, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 7Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 8Department of Science and Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, People’s Republic of China; 9Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qintai YangDepartment of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Guangzhou, 510630, People’s Republic of ChinaTel +86-20-85252252Fax +86-20-85253336Email yangqint@mail.sysu.edu.cnLuo ZhangDepartment of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, No. 16 Hougou Hutong, Chongnei Street, Donghuamen Street, Dongcheng District, Beijing, 100730, People’s Republic of ChinaTel +86-10-65141136Fax +86-10-85115988Email dr.luozhang@139.comBackground: To explore the epidemiological characteristics of allergic rhinitis (AR) and allergic conjunctivitis (AC) based on the Internet big data.Methods: The Baidu index (BDI) of keywords “allergic rhinitis” and “allergic conjunctivitis” in Mandarin, the daily pollen concentration (PC) released by the Beijing Meteorological Bureau and the volumes of outpatient visits (OV) of the Beijing Tongren Hospital (Beijing) and the Third Affiliated Hospital of Sun Yat-sen University (Guangzhou) from 2017 to 2020 were obtained. The temporal and spatial changes of AR and AC were discussed. The correlations between BDI and PC/OV were analyzed by Spearman correlation analysis.Results: The trends of BDI of “AR”/“AC” in Beijing showed obvious seasonal variations, but not in Guangzhou. The BDI of “AR” and “AC” was consistent with the OV in both cities (r1AR-BJ=0.580, P< 0.001; r1AR-GZ=0.360, P=0.031; r1AC-BJ=0.885, P< 0.001; r1AC-GZ=0.694, P< 0.001). The BDI of “AR” and “AC” was highly consistent with the change of the PC in Beijing (r AR-Pollen=0.826, P< 0.001; r AC-Pollen=0.564, P< 0.001). The OV of AR in Beijing and Guangzhou decreased significantly in the first half of 2020, but there was no significant change in AC. In the first half of 2020, the OV of AC in Beijing was significantly higher than that of AR, while that of AC in Guangzhou was slightly higher than that of AR.Conclusion: The BDI could reflect the real-world situation to some extent and has the potential to predict the epidemiological characteristics of AR and AC. The BDI and OV of AR decreased significantly, but those of AC were still at a high level, during the COVID-19 pandemic, in the environment where most people in Beijing and Guangzhou wore masks without eye protection.Keywords: allergic rhinitis, allergic conjunctivitis, Internet, Baidu, big data, COVID-19https://www.dovepress.com/using-the-internet-big-data-to-investigate-the-epidemiological-charact-peer-reviewed-fulltext-article-RMHPallergic rhinitisallergic conjunctivitisinternetbaidubig datacovid-19 |
| spellingShingle | Qiu H Zheng R Wang X Chen Z Feng P Huang X Zhou Y Tao J Dai M Yuan L Wang X Zhang L Yang Q Using the Internet Big Data to Investigate the Epidemiological Characteristics of Allergic Rhinitis and Allergic Conjunctivitis Risk Management and Healthcare Policy allergic rhinitis allergic conjunctivitis internet baidu big data covid-19 |
| title | Using the Internet Big Data to Investigate the Epidemiological Characteristics of Allergic Rhinitis and Allergic Conjunctivitis |
| title_full | Using the Internet Big Data to Investigate the Epidemiological Characteristics of Allergic Rhinitis and Allergic Conjunctivitis |
| title_fullStr | Using the Internet Big Data to Investigate the Epidemiological Characteristics of Allergic Rhinitis and Allergic Conjunctivitis |
| title_full_unstemmed | Using the Internet Big Data to Investigate the Epidemiological Characteristics of Allergic Rhinitis and Allergic Conjunctivitis |
| title_short | Using the Internet Big Data to Investigate the Epidemiological Characteristics of Allergic Rhinitis and Allergic Conjunctivitis |
| title_sort | using the internet big data to investigate the epidemiological characteristics of allergic rhinitis and allergic conjunctivitis |
| topic | allergic rhinitis allergic conjunctivitis internet baidu big data covid-19 |
| url | https://www.dovepress.com/using-the-internet-big-data-to-investigate-the-epidemiological-charact-peer-reviewed-fulltext-article-RMHP |
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