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Article ; Online: Assessing Internet Search Models in Predicting Daily New COVID-19 Cases and Deaths in South Korea.

Husnayain, Atina / Su, Emily Chia-Yu

Studies in health technology and informatics

2024 Volume 310, Page(s) 855–859

Abstract: Search data were found to be useful variables for COVID-19 trend prediction. In this study, we aimed to investigate the performance of online search models in state space models (SSMs), linear regression (LR) models, and generalized linear models (GLMs) ... ...

Abstract	Search data were found to be useful variables for COVID-19 trend prediction. In this study, we aimed to investigate the performance of online search models in state space models (SSMs), linear regression (LR) models, and generalized linear models (GLMs) for South Korean data from January 20, 2020, to July 31, 2021. Principal component analysis (PCA) was run to construct the composite features which were later used in model development. Values of root mean squared error (RMSE), peak day error (PDE), and peak magnitude error (PME) were defined as loss functions. Results showed that integrating search data in the models for short- and long-term prediction resulted in a low level of RMSE values, particularly for SSMs. Findings indicated that type of model used highly impacts the performance of prediction and interpretability of the model. Furthermore, PDE and PME could be beneficial to be included in the evaluation of peaks.
MeSH term(s)	Humans ; COVID-19 ; Internet ; Linear Models ; Republic of Korea/epidemiology
Language	English
Publishing date	2024-01-25
Publishing country	Netherlands
Document type	Journal Article
ISSN	1879-8365
ISSN (online)	1879-8365
DOI	10.3233/SHTI231086
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The association between interest of nutritional supplements and COVID-19 pandemic - evidence from Google Trends.

Lin, Li-Yin / Husnayain, Atina / Chen, Yi-Tui / Kuo, Chao-Yang

BMC public health

2024 Volume 24, Issue 1, Page(s) 109

Abstract: Background: Due to the spread of the coronavirus disease 2019 (COVID-19) pandemic in 2020, the interest of nutritional supplements has emerged. Limited data are available on how the COVID-19 pandemic affects the search interest in nutritional ... ...

Abstract	Background: Due to the spread of the coronavirus disease 2019 (COVID-19) pandemic in 2020, the interest of nutritional supplements has emerged. Limited data are available on how the COVID-19 pandemic affects the search interest in nutritional supplements in Taiwan and worldwide. The study aims to investigate changes in public search interest of nutritional supplements pre- and during the COVID-19 pandemic. Methods: Our World in Data dataset was used to collect both global and local (Taiwan) number of COVID-19 newly confirmed cases and deaths. Google Trends search query was being used to obtain relative search volumes (RSVs) covering a timeframe between 2019 to 2022. Spearman's rank-order correlation coefficients were used to measure relationships between confirmed new cases and deaths and RSVs of nutritional supplements. Multivariate analysis was conducted to examine the effect of domestic and global new cases and deaths on the RSVs of nutritional supplements. Results: The mean RSVs for nutritional supplements were higher during the COVID-19 pandemic period (between 2020 to 2022) compared to the pre-pandemic period (year of 2019) for both Taiwan and worldwide. In terms of seasonal variations, except for vitamin D, the mean RSVs of probiotics, vitamin B complex, and vitamin C in winter were significantly lower compared to other seasons in Taiwan. The RSVs of nutritional supplements were not only affected by domestic cases and deaths but also by global new cases and deaths. Conclusions: The interests in nutritional supplements had substantially increased in response to the COVID-19 pandemic. The RSVs of nutritional supplements in Taiwan were not only influenced by global and domestic pandemic severity but also by seasons.
MeSH term(s)	Humans ; Pandemics ; Search Engine ; COVID-19/epidemiology ; Dietary Supplements ; Vitamins
Chemical Substances	Vitamins
Language	English
Publishing date	2024-01-06
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2041338-5
ISSN	1471-2458 ; 1471-2458
ISSN (online)	1471-2458
ISSN	1471-2458
DOI	10.1186/s12889-023-17607-2
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The association between interest of nutritional supplements and COVID-19 pandemic - evidence from Google Trends

Li-Yin Lin / Atina Husnayain / Yi-Tui Chen / Chao-Yang Kuo

BMC Public Health, Vol 24, Iss 1, Pp 1-

2024 Volume 12

Abstract: Abstract Background Due to the spread of the coronavirus disease 2019 (COVID-19) pandemic in 2020, the interest of nutritional supplements has emerged. Limited data are available on how the COVID-19 pandemic affects the search interest in nutritional ... ...

Abstract	Abstract Background Due to the spread of the coronavirus disease 2019 (COVID-19) pandemic in 2020, the interest of nutritional supplements has emerged. Limited data are available on how the COVID-19 pandemic affects the search interest in nutritional supplements in Taiwan and worldwide. The study aims to investigate changes in public search interest of nutritional supplements pre- and during the COVID-19 pandemic. Methods Our World in Data dataset was used to collect both global and local (Taiwan) number of COVID-19 newly confirmed cases and deaths. Google Trends search query was being used to obtain relative search volumes (RSVs) covering a timeframe between 2019 to 2022. Spearman’s rank-order correlation coefficients were used to measure relationships between confirmed new cases and deaths and RSVs of nutritional supplements. Multivariate analysis was conducted to examine the effect of domestic and global new cases and deaths on the RSVs of nutritional supplements. Results The mean RSVs for nutritional supplements were higher during the COVID-19 pandemic period (between 2020 to 2022) compared to the pre-pandemic period (year of 2019) for both Taiwan and worldwide. In terms of seasonal variations, except for vitamin D, the mean RSVs of probiotics, vitamin B complex, and vitamin C in winter were significantly lower compared to other seasons in Taiwan. The RSVs of nutritional supplements were not only affected by domestic cases and deaths but also by global new cases and deaths. Conclusions The interests in nutritional supplements had substantially increased in response to the COVID-19 pandemic. The RSVs of nutritional supplements in Taiwan were not only influenced by global and domestic pandemic severity but also by seasons.
Keywords	Google Trends ; Nutritional supplements ; Relative search volumes ; COVID-19 ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Applications of Google Search Trends for risk communication in infectious disease management: A case study of the COVID-19 outbreak in Taiwan.

Husnayain, Atina / Fuad, Anis / Su, Emily Chia-Yu

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases

2020 Volume 95, Page(s) 221–223

Abstract: Objective: An emerging outbreak of a novel coronavirus, COVID-19, has now been detected in at least 211 countries worldwide. Given this pandemic situation, robust risk communication is urgently needed, particularly in affected countries. Therefore, this ...

Abstract	Objective: An emerging outbreak of a novel coronavirus, COVID-19, has now been detected in at least 211 countries worldwide. Given this pandemic situation, robust risk communication is urgently needed, particularly in affected countries. Therefore, this study explored the potential use of Google Trends (GT) to monitor public restlessness toward COVID-19 infection in Taiwan. Methods: We retrieved GT data for the specific locations and subregions in Taiwan nationwide using defined search terms related to the coronavirus, handwashing, and face masks. Results: Searches related to COVID-19 and face masks in Taiwan rapidly increased following the announcements of Taiwan's first imported case and reached a peak as locally acquired cases were reported. However, searches for handwashing gradually increased during the period of face-mask shortage. Moreover, high to moderate correlations between Google relative search volumes (RSVs) and COVID-19 cases were found in Taipei (lag-3), New Taipei (lag-2), Taoyuan (lag-2), Tainan (lag-1), Taichung (lag0), and Kaohsiung (lag0). Conclusion: In response to the ongoing outbreak, our results demonstrated that GT could potentially define the proper timing and location for practicing appropriate risk communication strategies for affected populations.
MeSH term(s)	Betacoronavirus ; COVID-19 ; Coronavirus Infections/epidemiology ; Coronavirus Infections/prevention & control ; Coronavirus Infections/therapy ; Disease Outbreaks ; Humans ; Pandemics/prevention & control ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/prevention & control ; Pneumonia, Viral/therapy ; Risk ; SARS-CoV-2 ; Search Engine/trends ; Taiwan/epidemiology
Keywords	covid19
Language	English
Publishing date	2020-03-12
Publishing country	Canada
Document type	Journal Article
ZDB-ID	1331197-9
ISSN	1878-3511 ; 1201-9712
ISSN (online)	1878-3511
ISSN	1201-9712
DOI	10.1016/j.ijid.2020.03.021
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Article ; Online: High variability in model performance of Google relative search volumes in spatially clustered COVID-19 areas of the USA.

Husnayain, Atina / Chuang, Ting-Wu / Fuad, Anis / Su, Emily Chia-Yu

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases

2021 Volume 109, Page(s) 269–278

Abstract: Objective: Incorporating spatial analyses and online health information queries may be beneficial in understanding the role of Google relative search volume (RSV) data as a secondary public health surveillance tool during pandemics. This study ... ...

Abstract	Objective: Incorporating spatial analyses and online health information queries may be beneficial in understanding the role of Google relative search volume (RSV) data as a secondary public health surveillance tool during pandemics. This study identified coronavirus disease 2019 (COVID-19) clustering and defined the predictability performance of Google RSV models in clustered and non-clustered areas of the USA. Methods: Getis-Ord General and local G statistics were used to identify monthly clustering patterns. Monthly country- and state-level correlations between new daily COVID-19 cases and Google RSVs were assessed using Spearman's rank correlation coefficients and Poisson regression models for January-December 2020. Results: Huge clusters involving multiple states were found, which resulted from various control measures in each state. This demonstrates the importance of state-to-state coordination in implementing control measures to tackle the spread of outbreaks. Variability in Google RSV model performance was found among states and time periods, possibly suggesting the need to use different frameworks for Google RSV data in each state. Moreover, the sign of correlation can be utilized to understand public responses to control and preventive measures, as well as in communicating risk. Conclusion: COVID-19 Google RSV model accuracy in the USA may be influenced by COVID-19 transmission dynamics, policy-driven community awareness and past outbreak experiences.
MeSH term(s)	COVID-19 ; Humans ; Pandemics ; Public Health Surveillance ; SARS-CoV-2 ; Search Engine
Language	English
Publishing date	2021-07-14
Publishing country	Canada
Document type	Journal Article
ZDB-ID	1331197-9
ISSN	1878-3511 ; 1201-9712
ISSN (online)	1878-3511
ISSN	1201-9712
DOI	10.1016/j.ijid.2021.07.031
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Article ; Online: Correlation between Google Trends on dengue fever and national surveillance report in Indonesia.

Husnayain, Atina / Fuad, Anis / Lazuardi, Lutfan

Global health action

2019 Volume 12, Issue 1, Page(s) 1552652

Abstract: ... ...

Abstract	Background
MeSH term(s)	Cell Phone ; Dengue/epidemiology ; Disease Outbreaks/statistics & numerical data ; Epidemics/statistics & numerical data ; Forecasting ; Humans ; Indonesia/epidemiology ; Internet ; Population Surveillance/methods ; Social Media/statistics & numerical data ; Social Media/trends
Language	English
Publishing date	2019-06-03
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2540569-X
ISSN	1654-9880 ; 1654-9716
ISSN (online)	1654-9880
ISSN	1654-9716
DOI	10.1080/16549716.2018.1552652
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Predicting New Daily COVID-19 Cases and Deaths Using Search Engine Query Data in South Korea From 2020 to 2021: Infodemiology Study.

Husnayain, Atina / Shim, Eunha / Fuad, Anis / Su, Emily Chia-Yu

Journal of medical Internet research

2021 Volume 23, Issue 12, Page(s) e34178

Abstract: Background: Given the ongoing COVID-19 pandemic situation, accurate predictions could greatly help in the health resource management for future waves. However, as a new entity, COVID-19's disease dynamics seemed difficult to predict. External factors, ... ...

Abstract	Background: Given the ongoing COVID-19 pandemic situation, accurate predictions could greatly help in the health resource management for future waves. However, as a new entity, COVID-19's disease dynamics seemed difficult to predict. External factors, such as internet search data, need to be included in the models to increase their accuracy. However, it remains unclear whether incorporating online search volumes into models leads to better predictive performances for long-term prediction. Objective: The aim of this study was to analyze whether search engine query data are important variables that should be included in the models predicting new daily COVID-19 cases and deaths in short- and long-term periods. Methods: We used country-level case-related data, NAVER search volumes, and mobility data obtained from Google and Apple for the period of January 20, 2020, to July 31, 2021, in South Korea. Data were aggregated into four subsets: 3, 6, 12, and 18 months after the first case was reported. The first 80% of the data in all subsets were used as the training set, and the remaining data served as the test set. Generalized linear models (GLMs) with normal, Poisson, and negative binomial distribution were developed, along with linear regression (LR) models with lasso, adaptive lasso, and elastic net regularization. Root mean square error values were defined as a loss function and were used to assess the performance of the models. All analyses and visualizations were conducted in SAS Studio, which is part of the SAS OnDemand for Academics. Results: GLMs with different types of distribution functions may have been beneficial in predicting new daily COVID-19 cases and deaths in the early stages of the outbreak. Over longer periods, as the distribution of cases and deaths became more normally distributed, LR models with regularization may have outperformed the GLMs. This study also found that models performed better when predicting new daily deaths compared to new daily cases. In addition, an evaluation of feature effects in the models showed that NAVER search volumes were useful variables in predicting new daily COVID-19 cases, particularly in the first 6 months of the outbreak. Searches related to logistical needs, particularly for "thermometer" and "mask strap," showed higher feature effects in that period. For longer prediction periods, NAVER search volumes were still found to constitute an important variable, although with a lower feature effect. This finding suggests that search term use should be considered to maintain the predictive performance of models. Conclusions: NAVER search volumes were important variables in short- and long-term prediction, with higher feature effects for predicting new daily COVID-19 cases in the first 6 months of the outbreak. Similar results were also found for death predictions.
MeSH term(s)	COVID-19 ; Humans ; Infodemiology ; Pandemics ; SARS-CoV-2 ; Search Engine
Language	English
Publishing date	2021-12-22
Publishing country	Canada
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2028830-X
ISSN	1438-8871 ; 1439-4456
ISSN (online)	1438-8871
ISSN	1439-4456
DOI	10.2196/34178
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Applications of Google Search Trends for risk communication in infectious disease management

Atina Husnayain / Anis Fuad / Emily Chia-Yu Su

International Journal of Infectious Diseases, Vol 95, Iss , Pp 221-

A case study of the COVID-19 outbreak in Taiwan

2020 Volume 223

Abstract	Objective: An emerging outbreak of a novel coronavirus, COVID-19, has now been detected in at least 211 countries worldwide. Given this pandemic situation, robust risk communication is urgently needed, particularly in affected countries. Therefore, this study explored the potential use of Google Trends (GT) to monitor public restlessness toward COVID-19 infection in Taiwan. Methods: We retrieved GT data for the specific locations and subregions in Taiwan nationwide using defined search terms related to the coronavirus, handwashing, and face masks. Results: Searches related to COVID-19 and face masks in Taiwan rapidly increased following the announcements of Taiwan's first imported case and reached a peak as locally acquired cases were reported. However, searches for handwashing gradually increased during the period of face-mask shortage. Moreover, high to moderate correlations between Google relative search volumes (RSVs) and COVID-19 cases were found in Taipei (lag-3), New Taipei (lag-2), Taoyuan (lag-2), Tainan (lag-1), Taichung (lag0), and Kaohsiung (lag0). Conclusion: In response to the ongoing outbreak, our results demonstrated that GT could potentially define the proper timing and location for practicing appropriate risk communication strategies for affected populations.
Keywords	Google Trends ; Risk communication ; COVID-19 ; Taiwan ; Infectious and parasitic diseases ; RC109-216 ; covid19
Subject code	001
Language	English
Publishing date	2020-06-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Applications of Google Search Trends for risk communication in infectious disease management

Husnayain, Atina / Fuad, Anis / Su, Emily Chia-Yu

International Journal of Infectious Diseases

A case study of the COVID-19 outbreak in Taiwan

2020 Volume 95, Page(s) 221–223

Keywords	Microbiology (medical) ; Infectious Diseases ; General Medicine ; covid19
Language	English
Publisher	Elsevier BV
Publishing country	us
Document type	Article ; Online
ZDB-ID	1331197-9
ISSN	1878-3511 ; 1201-9712
ISSN (online)	1878-3511
ISSN	1201-9712
DOI	10.1016/j.ijid.2020.03.021
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Zs.A 4516: Show issues

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Article ; Online: Improving Dengue Surveillance System with Administrative Claim Data in Indonesia: Opportunities and Challenges.

Husnayain, Atina / Fuad, Anis / Laksono, Ida Safitri / Su, Emily Chia-Yu

Studies in health technology and informatics

2020 Volume 270, Page(s) 853–857

Abstract: Administrative claim data is believed as one of the promising data set to augment the mandatory surveillance system which suffered from under-reporting and delay in reporting. Therefore, this study aims to examine whether the Indonesian National Health ... ...

Abstract	Administrative claim data is believed as one of the promising data set to augment the mandatory surveillance system which suffered from under-reporting and delay in reporting. Therefore, this study aims to examine whether the Indonesian National Health Insurance (INHI) sample data could complement dengue case-based surveillance system in a more practical way. Afterwards, this analysis also identified several future opportunities and challenges in improving the dengue surveillance system. We utilized the referral care table linked with capitation and non-capitation-based primary care service table from 2015-2016. Data cleaning, query and visualization were performed using Tableau Public and Microsoft Power BI. Result shows that dengue referral pattern is indicating the opportunity to detect dengue cases in an earlier stage and high utilization of referral care disclose the patient behaviour. Therefore, anonymous INHI sample data set potentially to complement dengue traditional surveillance system. A huge number of health facilities as data providers, bridging and interoperability chance and opportunity of early detection are identified as future opportunities. However, we also determine challenges involving how to provide the mechanism for the quick and interoperable reporting system, how to construct supportive regulation and anticipatory approach regarding the change in dengue diagnosis criteria as the implementation of ICD 11 code. Thus, practical approaches should be prepared to support the utilization of INHI sample data.
MeSH term(s)	Dengue ; Humans ; Indonesia
Language	English
Publishing date	2020-06-22
Publishing country	Netherlands
Document type	Journal Article
ISSN	1879-8365
ISSN (online)	1879-8365
DOI	10.3233/SHTI200282
Database	MEDical Literature Analysis and Retrieval System OnLINE

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