scholarly journals Estimation of asthma symptom onset using Internet search queries: A lag-time series analysis (Preprint)

10.2196/18593 ◽  
2020 ◽  
Author(s):  
Yulin Hswen ◽  
Amanda Zhang ◽  
Bruno Ventelou
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Symptom Onset ◽  
Asthma Symptom ◽  
Lag Time ◽  
Internet Search ◽  
Search Queries ◽  
Series Analysis

scholarly journals Suicide‐related Internet search queries in India following media reports of a celebrity suicide: an interrupted time series analysis

2021 ◽  
Vol 20 (1) ◽  
pp. 143-144
Author(s):  
Gregory Armstrong ◽  
Tilahun Haregu ◽  
Vikas Arya ◽  
Lakshmi Vijayakumar ◽  
Mark Sinyor ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Internet Search ◽  
Interrupted Time Series Analysis ◽  
Search Queries ◽  
Series Analysis ◽  
Celebrity Suicide ◽  
Media Reports

scholarly journals Estimation of asthma symptom onset using Internet search queries: A lag-time series analysis (Preprint)

2020 ◽  
Author(s):  
Yulin Hswen ◽  
Amanda Zhang ◽  
Bruno Ventelou
Keyword(s):  
Time Series ◽  
Hospital Admission ◽  
Symptom Onset ◽  
Hospital Admissions ◽  
Pearson Correlation ◽  
Internet Search ◽  
Search Queries ◽  
Risk Of Death ◽  
Search Volume ◽  
Google Search

BACKGROUND Asthma affects over 330 million people worldwide. Timing of the asthma event is extremely important and lack of identification of asthma increases the risk of death. A major challenge for health systems is the length of time between symptom onset and care seeking, which could result in delayed treatment initiation and worsening of symptoms. OBJECTIVE This study evaluates the utility of the Internet search query data for the identification the onset of asthma symptoms. METHODS Pearson correlation coefficients between the time series of hospital admissions and Google searches were computed at lag times from 4 weeks prior to hospital admission to 4 weeks after hospital admission. RESULTS Google search volume for asthma had the highest correlation at 2 weeks before hospital admission. CONCLUSIONS Our findings demonstration Internet search queries can earlier predict asthma events and may be a better use for classifying the measurement of timing of symptom onset.

scholarly journals The Federal Menu Labeling Law and Twitter Discussions about Calories in the United States: An Interrupted Time-Series Analysis

2021 ◽  
Vol 18 (20) ◽  
pp. 10794
Author(s):  
Yulin Hswen ◽  
Alyssa J. Moran ◽  
Siona Prasad ◽  
Anna Li ◽  
Denise Simon ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Google Trends ◽  
Series Data ◽  
Interrupted Time Series Analysis ◽  
Menu Labeling ◽  
Search Queries ◽  
Calorie Labeling ◽  
Series Analysis

Public awareness of calories in food sold in retail establishments is a primary objective of the menu labeling law. This study explores the extent to which we can use social media and internet search queries to understand whether the federal calorie labeling law increased awareness of calories. To evaluate the association of the federal menu labeling law with tweeting about calories we retrieved tweets that contained the term “calorie(s)” from the CompEpi Geo Twitter Database from 1 January through 31 December in 2016 and 2018. Within the same time period, we also retrieved time-series data for search queries related to calories via Google Trends (GT). Interrupted time-series analysis was used to test whether the federal menu labeling law was associated with a change in mentions of “calorie(s)” on Twitter and relative search queries to calories on GT. Before the implementation of the federal calorie labeling law on 7 May 2018, there was a significant decrease in the baseline trend of 4.37 × 10−8 (SE = 1.25 × 10−8, p < 0.001) mean daily ratio of calorie(s) tweets. A significant increase in post-implementation slope of 3.19 × 10−8 (SE = 1.34 × 10−8, p < 0.018) mean daily ratio of calorie(s) tweets was seen compared to the pre-implementation slope. An interrupted time-series (ITS) analysis showed a small, statistically significant upward trend of 0.0043 (SE = 0.036, p < 0.001) weekly search queries for calories pre-implementation, with no significant level change post-implementation. There was a decrease in trend of 1.22 (SE = 0.27, p < 0.001) in search queries for calories post-implementation. The federal calorie labeling law was associated with a 173% relative increase in the trend of mean daily ratio of tweets and a −28381% relative change in trend for search queries for calories. Twitter results demonstrate an increase in awareness of calories because of the addition of menu labels. Google Trends results imply that fewer people are searching for the calorie content of their meal, which may no longer be needed since calorie information is provided at point of purchase. Given our findings, discussions online about calories may provide a signal of an increased awareness in the implementation of calorie labels.

scholarly journals Dynamic Changes of NDVI in the Growing Season of the Tibetan Plateau During the Past 17 Years and Its Response to Climate Change

2019 ◽  
Vol 16 (18) ◽  
pp. 3452 ◽  
Author(s):  
Xianglin Huang ◽  
Tingbin Zhang ◽  
Guihua Yi ◽  
Dong He ◽  
Xiaobing Zhou ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Tibetan Plateau ◽  
Time Series Analysis ◽  
Environmental Changes ◽  
Climatic Factors ◽  
Growing Season ◽  
Lag Time ◽  
The Tibetan Plateau ◽  
Series Analysis

The fragile alpine vegetation in the Tibetan Plateau (TP) is very sensitive to environmental changes, making TP one of the hotspots for studying the response of vegetation to climate change. Existing studies lack detailed description of the response of vegetation to different climatic factors using the method of multiple nested time series analysis and the method of grey correlation analysis. In this paper, based on the Normalized Difference Vegetation Index (NDVI) of TP in the growing season calculated from the MOD09A1 data product of Moderate-resolution Imaging Spectroradiometer (MODIS), the method of multiple nested time series analysis is adopted to study the variation trends of NDVI in recent 17 years, and the lag time of NDVI to climate change is analyzed using the method of Grey Relational Analysis (GRA). Finally, the characteristics of temporal and spatial differences of NDVI to different climate factors are summarized. The results indicate that: (1) the spatial distribution of NDVI values in the growing season shows a trend of decreasing from east to west, and from north to south, with a change rate of −0.13/10° E and −0.30/10° N, respectively. (2) From 2001 to 2017, the NDVI in the TP shows a slight trend of increase, with a growth rate of 0.01/10a. (3) The lag time of NDVI to air temperature is not obvious, while the NDVI response lags behind cumulative precipitation by zero to one month, relative humidity by two months, and sunshine duration by three months. (4) The effects of different climatic factors on NDVI are significantly different with the increase of the study period.

Dynamical Peculiarities of Concatenational Changes in Functional Cardiovascular Parameters

2018 ◽  
Vol 3 (82) ◽  
Author(s):  
Eurelija Venskaitytė ◽  
Jonas Poderys ◽  
Tadas Česnaitis
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Functional State ◽  
The Body ◽  
Functional Changes ◽  
High Intensity Training ◽  
Series Analysis ◽  
Greco Roman ◽  
St Segment ◽  
Standard Lead

Research  background  and  hypothesis.  Traditional  time  series  analysis  techniques,  which  are  also  used  for the analysis of cardiovascular signals, do not reveal the relationship between the  changes in the indices recorded associated with the multiscale and chaotic structure of the tested object, which allows establishing short-and long-term structural and functional changes.Research aim was to reveal the dynamical peculiarities of interactions of cardiovascular system indices while evaluating the functional state of track-and-field athletes and Greco-Roman wrestlers.Research methods. Twenty two subjects participated in the study, their average age of 23.5 ± 1.7 years. During the study standard 12 lead electrocardiograms (ECG) were recorded. The following ECG parameters were used in the study: duration of RR interval taken from the II standard lead, duration of QRS complex, duration of JT interval and amplitude of ST segment taken from the V standard lead.Research  results.  Significant  differences  were  found  between  inter-parametric  connections  of  ST  segment amplitude and JT interval duration at the pre and post-training testing. Observed changes at different hierarchical levels of the body systems revealed inadequate cardiac metabolic processes, leading to changes in the metabolic rate of the myocardium and reflected in the dynamics of all investigated interactions.Discussion and conclusions. It has been found that peculiarities of the interactions of ECG indices interactions show the exposure of the  functional changes in the body at the onset of the workload. The alterations of the functional state of the body and the signs of fatigue, after athletes performed two high intensity training sessions per day, can be assessed using the approach of the evaluation of interactions between functional variables. Therefore the evaluation of the interactions of physiological signals by using time series analysis methods is suitable for the observation of these processes and the functional state of the body.Keywords: electrocardiogram, time series, functional state.

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