scholarly journals Use of Internet Search Data to Monitor Rotavirus Vaccine Impact in the United States, United Kingdom, and Mexico

2017 ◽  
Vol 7 (1) ◽  
pp. 56-63 ◽  
Author(s):  
Minesh P Shah ◽  
Benjamin A Lopman ◽  
Jacqueline E Tate ◽  
John Harris ◽  
Marcelino Esparza-Aguilar ◽  
...  
2016 ◽  
Vol 3 (suppl_1) ◽  
Author(s):  
Minesh Shah ◽  
Benjamin Lopman ◽  
Jacqueline Tate ◽  
John Harris ◽  
Marcelino Esparza-Aguilar ◽  
...  

2012 ◽  
Vol 54 (9) ◽  
pp. e115-e118 ◽  
Author(s):  
Rishi Desai ◽  
Benjamin A. Lopman ◽  
Yair Shimshoni ◽  
John P. Harris ◽  
Manish M. Patel ◽  
...  

10.2196/18998 ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. e18998
Author(s):  
Chenjie Xu ◽  
Zhi Cao ◽  
Hongxi Yang ◽  
Ying Gao ◽  
Li Sun ◽  
...  

Background As human society enters an era of vast and easily accessible social media, a growing number of people are exploiting the internet to search and exchange medical information. Because internet search data could reflect population interest in particular health topics, they provide a new way of understanding health concerns regarding noncommunicable diseases (NCDs) and the role they play in their prevention. Objective We aimed to explore the association of internet search data for NCDs with published disease incidence and mortality rates in the United States and to grasp the health concerns toward NCDs. Methods We tracked NCDs by examining the correlations among the incidence rates, mortality rates, and internet searches in the United States from 2004 to 2017, and we established forecast models based on the relationship between the disease rates and internet searches. Results Incidence and mortality rates of 29 diseases in the United States were statistically significantly correlated with the relative search volumes (RSVs) of their search terms (P<.05). From the perspective of the goodness of fit of the multiple regression prediction models, the results were closest to 1 for diabetes mellitus, stroke, atrial fibrillation and flutter, Hodgkin lymphoma, and testicular cancer; the coefficients of determination of their linear regression models for predicting incidence were 80%, 88%, 96%, 80%, and 78%, respectively. Meanwhile, the coefficient of determination of their linear regression models for predicting mortality was 82%, 62%, 94%, 78%, and 62%, respectively. Conclusions An advanced understanding of search behaviors could augment traditional epidemiologic surveillance and could be used as a reference to aid in disease prediction and prevention.


2020 ◽  
Author(s):  
Chenjie Xu ◽  
Zhi Cao ◽  
Hongxi Yang ◽  
Ying Gao ◽  
Li Sun ◽  
...  

BACKGROUND As human society enters an era of vast and easily accessible social media, a growing number of people are exploiting the internet to search and exchange medical information. Because internet search data could reflect population interest in particular health topics, they provide a new way of understanding health concerns regarding noncommunicable diseases (NCDs) and the role they play in their prevention. OBJECTIVE We aimed to explore the association of internet search data for NCDs with published disease incidence and mortality rates in the United States and to grasp the health concerns toward NCDs. METHODS We tracked NCDs by examining the correlations among the incidence rates, mortality rates, and internet searches in the United States from 2004 to 2017, and we established forecast models based on the relationship between the disease rates and internet searches. RESULTS Incidence and mortality rates of 29 diseases in the United States were statistically significantly correlated with the relative search volumes (RSVs) of their search terms (<i>P</i>&lt;.05). From the perspective of the goodness of fit of the multiple regression prediction models, the results were closest to 1 for diabetes mellitus, stroke, atrial fibrillation and flutter, Hodgkin lymphoma, and testicular cancer; the coefficients of determination of their linear regression models for predicting incidence were 80%, 88%, 96%, 80%, and 78%, respectively. Meanwhile, the coefficient of determination of their linear regression models for predicting mortality was 82%, 62%, 94%, 78%, and 62%, respectively. CONCLUSIONS An advanced understanding of search behaviors could augment traditional epidemiologic surveillance and could be used as a reference to aid in disease prediction and prevention.


2020 ◽  
Author(s):  
Francesco Rigoli

Research has shown that stress impacts on people’s religious beliefs. However, several aspects of this effect remain poorly understood, for example regarding the role of prior religiosity and stress-induced anxiety. This paper explores these aspects in the context of the recent coronavirus emergency. The latter has impacted dramatically on many people’s well-being; hence it can be considered a highly stressful event. Through online questionnaires administered to UK and USA citizens professing either Christian faith or no religion, this paper examines the impact of the coronavirus crisis upon common people’s religious beliefs. We found that, following the coronavirus emergency, strong believers reported higher confidence in their religious beliefs while non-believers reported increased scepticism towards religion. Moreover, for strong believers, higher anxiety elicited by the coronavirus threat was associated with increased strengthening of religious beliefs. Conversely, for non-believers, higher anxiety elicited by the coronavirus thereat was associated with increased scepticism towards religious beliefs. These observations are consistent with the notion that stress-induced anxiety enhances support for the ideology already embraced before a stressful event occurs. This study sheds light on the psychological and cultural implications of the coronavirus crisis, which represents one of the most serious health emergencies in recent times.


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