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Predicting COVID-19 new cases in California with Google Trends data and a machine learning approach. 利用谷歌趋势数据和机器学习方法预测加利福尼亚州的 COVID-19 新病例。

Informatics for health & social care Pub Date : 2024-01-02 Epub Date: 2024-02-14 DOI: 10.1080/17538157.2024.2315246

Amir Habibdoust, Maryam Seifaddini, Moosa Tatar, Ozgur M Araz, Fernando A Wilson

{"title":"Predicting COVID-19 new cases in California with Google Trends data and a machine learning approach.","authors":"Amir Habibdoust, Maryam Seifaddini, Moosa Tatar, Ozgur M Araz, Fernando A Wilson","doi":"10.1080/17538157.2024.2315246","DOIUrl":"10.1080/17538157.2024.2315246","url":null,"abstract":"Background: Google Trends data can be a valuable source of information for health-related issues such as predicting infectious disease trends.Objectives: To evaluate the accuracy of predicting COVID-19 new cases in California using Google Trends data, we develop and use a GMDH-type neural network model and compare its performance with a LTSM model.Methods: We predicted COVID-19 new cases using Google query data over three periods. Our first period covered March 1, 2020, to July 31, 2020, including the first peak of infection. We also estimated a model from October 1, 2020, to January 7, 2021, including the second wave of COVID-19 and avoiding possible biases from public interest in searching about the new pandemic. In addition, we extended our forecasting period from May 20, 2020, to January 31, 2021, to cover an extended period of time.Results: Our findings show that Google relative search volume (RSV) can be used to accurately predict new COVID-19 cases. We find that among our Google relative search volume terms, \"Fever,\" \"COVID Testing,\" \"Signs of COVID,\" \"COVID Treatment,\" and \"Shortness of Breath\" increase model predictive accuracy.Conclusions: Our findings highlight the value of using data sources providing near real-time data, e.g., Google Trends, to detect trends in COVID-19 cases, in order to supplement and extend existing epidemiological models.","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":" ","pages":"56-72"},"PeriodicalIF":0.0,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139731396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of a multifunctional technology system in a memory care unit: Opportunities for innovation in dementia care. 记忆护理单元中多功能技术系统的评估：痴呆症护理创新的机会。

Informatics for health & social care Pub Date : 2016-12-01 Epub Date: 2016-01-28 DOI: 10.3109/17538157.2015.1064428

Amanda Lazar, George Demiris, Hilaire J Thompson

{"title":"Evaluation of a multifunctional technology system in a memory care unit: Opportunities for innovation in dementia care.","authors":"Amanda Lazar, George Demiris, Hilaire J Thompson","doi":"10.3109/17538157.2015.1064428","DOIUrl":"https://doi.org/10.3109/17538157.2015.1064428","url":null,"abstract":"Introduction: Stimulating recreational and leisure activities (RLAs) are essential to physical and mental well-being; however, people living in memory care units (MCUs) may lack access to them. Technology has the potential to facilitate and enrich activity engagement in this context.Objectives: In this 6-month study, we evaluated a commercially available system designed to encourage the engagement of people with dementia in activities and social interactions, using a mixed-methods approach in a MCU.Methods: Quantitative measures included those to evaluate cognition, depression, quality of life, and resource utilization. We qualitatively evaluated the system using semi-structured interviews with family members and staff. Five residents with dementia, four family members, and seven staff were included in the 6-month study.Results: Staff and family members reported benefits for residents such as enjoyment, interactions and connections with others, and mental stimulation. Findings also highlight challenges such as technical and ethical concerns. Factors that influence system use and integration are also discussed.Conclusion: It was feasible to introduce a system designed for recreation and engagement in a MCU, and staff, family members, and residents experienced benefits. However, barriers existed in the introduction and use of the system.","PeriodicalId":101409,"journal":{"name":"Informatics for health & social care","volume":"41 4","pages":"373-86"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/17538157.2015.1064428","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71490975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

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