Worldwide evolution of vaccinable and non-vaccinable viral skin infections: a Google Trends analysis (Preprint)

2021 ◽  
Author(s):  
Thierry Simonart ◽  
Xuän-Lan Lam Hoai ◽  
Viviane De Maertelaer
Keyword(s):  
Foot And Mouth Disease ◽  
Google Trends ◽  
Surveillance Systems ◽  
Search Term ◽  
Skin Infections ◽  
African Countries ◽  
Web Searches ◽  
Field Methods ◽  
Internet Searches ◽  
Traditional Surveillance

BACKGROUND Most common viral skin infections are not reportable conditions. Studying the population dynamics of these viral epidemics using traditional field methods is costly and time consuming, especially over wide geographical areas OBJECTIVE To explore the evolution, seasonality and distribution of vaccinable and non-vaccinable viral skin infections through analysis of Google Trends. METHODS Worldwide search trends from 2004 through May 2021 for viral skin infections were extracted from Google Trends, quantified and analysed. RESULTS Time series decomposition showed that total search term volume for warts, zoster, roseola, measles, hand, foot, and mouth disease (HFMD), varicella and rubella increased worldwide over the study period while the interest for Pityriasis rosea and herpes simplex decreased. Internet searches for HFMD, varicella and measles exhibited the highest seasonal patterns. The interest for measles and rubella was more pronounced in African countries while the interest for HFMD and roseola was more pronounced in East Asia. CONCLUSIONS Harnessing data generated by web searches may increase the timeliness of traditional surveillance systems and strengthens the suspicion that the incidence of some vaccinable viral skin infections such as varicella, measles, rubella may be globally increasing. CLINICALTRIAL Ethics approval for this type of study was not required as none of the queries in the Google database can be associated with any identity and/or physical location, as specified in Google’s privacy policy (www.google.com/privacypolicy.html).

scholarly journals Tracking and predicting hand, foot, and mouth disease (HFMD) epidemics in China by Baidu queries

2017 ◽  
Vol 145 (8) ◽  
pp. 1699-1707 ◽  
Author(s):  
Q. Y. XIAO ◽  
H. J. LIU ◽  
M. W. FELDMAN
Keyword(s):  
Predictive Model ◽  
Pearson Correlation ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Surveillance Systems ◽  
Pearson Correlation Coefficient ◽  
Search Queries ◽  
Foot And Mouth ◽  
The Mean ◽  
Traditional Surveillance

SUMMARYHand, foot, and mouth disease (HFMD) is highly prevalent in China, and more efficient methods of epidemic detection and early warning need to be developed to augment traditional surveillance systems. In this paper, a method that uses Baidu search queries to track and predict HFMD epidemics is presented, and the outbreaks of HFMD in China during the 60-month period from January 2011 to December 2015 are predicted. The Pearson correlation coefficient (R) of the predictive model and the mean absolute percentage errors between observed HFMD case counts and the predicted number show that our predictive model gives excellent fit to the data. This implies that Baidu search queries can be used in China to track and reliably predict HFMD epidemics, and can serve as a supplement to official systems for HFMD epidemic surveillance.

scholarly journals “Dr. Google, I am in Pain”—Global Internet Searches Associated with Pain: A Retrospective Analysis of Google Trends Data

2020 ◽  
Vol 17 (3) ◽  
pp. 954 ◽  
Author(s):  
Mikołaj Kamiński ◽  
Igor Łoniewski ◽  
Wojciech Marlicz
Keyword(s):  
Abdominal Pain ◽  
Back Pain ◽  
Seasonal Variations ◽  
Google Trends ◽  
Search Term ◽  
Search Volume ◽  
Internet Users ◽  
Internet Searches ◽  
Relative Search Volume ◽  
Over Time

We aimed to rank the most common locations of pain among Google users globally and locally and analyze secular and seasonal trends in pain-related searches in the years 2004–2019. We used data generated by Google Trends (GT) to identify and analyze global interest in topics (n = 24) related to locations of pain and how these progressed over time. We analyzed secular trends and time series decomposition to identify seasonal variations. We also calculated the interest in all topics with reference to the relative search volume (RSV) of “Abdominal pain”. Google users were most commonly interested in “Headache” (1.30 [times more frequently than “Abdominal pain”]), “Abdominal pain” (1.00), and “Back pain” (0.84). “Headache” was the most frequent search term in n = 41 countries, while “Abdominal pain” was the most frequent term in n = 27 countries. The interest in all pain-related topics except “Dyspareunia” increased over time. The sharpest increase was observed for “Abdominal pain” (5.67 RSV/year), and “Toothache” (5.52 RSV/year). Most of the topics revealed seasonal variations. Among pain-related topics, “Headache,” “Abdominal pain,” and “Back pain” interested most Google users. GT is a novel tool that allows retrospective investigation of complaints among Internet users.

Crowdsourcing Covid-19 signals in sub-Saharan Africa: Leveraging digital contributor networks for participatory surveillance of Covid-19 symptoms and deaths (Preprint)

2020 ◽  
Author(s):  
Ngozi A Erondu ◽  
Sagal A Ali ◽  
Mohamed Ali ◽  
Schadrac C Agbla
Keyword(s):  
Public Health ◽  
Sub Saharan Africa ◽  
Specific Information ◽  
Surveillance Systems ◽  
Health Seeking ◽  
African Countries ◽  
Cross Sectional Survey ◽  
Local Networks ◽  
The World ◽  
Sub Saharan

BACKGROUND In sub-Saharan Africa, underreporting of cases and deaths has been attributed to various factors including, weak disease surveillance, low health-seeking behaviour of flu like symptoms, and stigma of Covid-19. There is evidence that SARS-CoV-2 spread mimics transmission patterns of other countries across the world. Since the Covid-19 pandemic has changed the way research can be conducted and in light of restrictions on travel and risks to in-person data collection, innovative approaches to collecting data must be considered. Nearly 50% of Africa’s population is a unique mobile subscriber and it is one of the fastest growing smart-phone marketplaces in the world; hence, mobile phone platforms should be considered to monitor Covid-19 trends in the community. OBJECTIVE We demonstrate the use of digital contributor platforms to survey individuals about cases of flu-like symptoms and instances of unexplained deaths in Ethiopia, Kenya, Nigeria, Somalia, and Zimbabwe. METHODS Rapid cross-sectional survey of individuals with severe flu and pneumonia symptoms and unexplained deaths in Ethiopia, Kenya, Nigeria, Somalia and Zimbabwe RESULTS Using a non-health specific information platform, we found COVID-19 signals in five African countries, specifically: •Across countries, nearly half of the respondents (n=739) knew someone who had severe flu or pneumonia symptoms in recent months. •One in three respondents from Somalia and one in five from Zimbabwe respondents said they knew more than five people recently displaying flu and/or pneumonia symptoms. •In Somalia there were signals that a large number of people might be dying outside of health facilities, specifically in their homes or in IDP or refugee camps. CONCLUSIONS Existing digital contributor platforms with local networks are a non-traditional data source that can provide information from the community to supplement traditional government surveillance systems and academic surveys. We demonstrate that using these distributor networks to for community surveys can provide periodic information on rumours but could also be used to capture local sentiment to inform public health decision-making; for example, these insights could be useful to inform strategies to increase confidence in Covid19 vaccine. As Covid-19 continues to spread somewhat silently across sub-Saharan Africa, regional and national public health entities should consider expanding event-based surveillance sources to include these systems.

Using novel methodologies to support burden of disease estimates

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
T Hald
Keyword(s):  
International Development ◽  
Traditional Approach ◽  
Source Population ◽  
Surveillance Systems ◽  
Data Generation ◽  
Time Data ◽  
African Countries ◽  
Indirect Measure ◽  
True Incidence ◽  
Laboratory Capacity

Abstract A challenge to estimating burden of diarrheal diseases, particularly in LMICs, where laboratory capacity and surveillance systems are limited, is obtaining valid estimates of etiology proportions of cases. A commonly used method is systematic review of studies reporting pathogen isolation in diarrhea cases. However, studies often differ in design, source population, timeframe, and pathogens included, hampering extrapolation to the target population. In a study co-funded by the Bill and Melinda Gates Foundation and the UK Department for International Development, we explore a novel approach for estimating diarrhea etiology proportions in urban and rural populations in four African countries. We analyse sewage samples using short-read next-generation sequencing (NGS) to determine abundance of genes that can be mapped to specific bacterial genera, providing an estimate of the relative abundance of specific pathogens in each sample. In parallel to collecting sewage samples, a questionnaire-based population survey will estimate diarrheal incidence. By combining results, pathogen-specific incidence will be estimated and compared with incidence estimates from the traditional approach. The application NGS to human sewage has great potential for surveillance of foodborne infections, particularly in resource-poor settings where laboratory capacity for bacterial isolation is limited. First, NGS is a one method takes all approach, as it is based on detection of RNA/DNA, a language common across pathogens. Second, it is culture independent, allowing for real-time data generation and standardized sharing. Finally, few samples are needed to survey large populations for several pathogens at the same time. Thus, surveillance based on NGS of sewage may prove to be an indirect measure of incidence. Although it will not provide an estimate for the true incidence in the population, it will increase our understanding of the burden and as such be a proxy and novel way of ranking diseases.

scholarly journals Conservation research output in sub-Saharan Africa is increasing, but only in a few countries

Oryx ◽  
2020 ◽  
pp. 1-10
Author(s):  
P. Christy Pototsky ◽  
Will Cresswell
Keyword(s):  
South African ◽  
Agricultural Land ◽  
Research Output ◽  
Sub Saharan Africa ◽  
Search Term ◽  
African Countries ◽  
Research Papers ◽  
North American Country ◽  
Conservation Research ◽  
Sub Saharan

Abstract We tested if peer-reviewed conservation research output has increased in sub-Saharan African countries over the last 30 years in response to increased development. We carried out a bibliometric analysis to identify the number of conservation research papers published by national authors of 41 sub-Saharan African countries during 1987–2017, to provide an index of national conservation research output. We identified country-specific development factors influencing these totals, using general linear modelling. There were positive relationships between conservation research output and population size, GDP, literacy rate, international tourism receipts and population growth rate, and negative relationships with urban population and agricultural land cover, in total explaining 77% of variation. Thirty-eight per cent of countries contributed < 30 conservation research papers (of 12,701) in 30 years. Analysis of trends in primary authorship in a random subsample of 2,374 of these papers showed that primary authorship by sub-Saharan African authors has increased significantly over time but is now at a lower rate than primary authorship for authors from countries outside the country associated with the search term, usually a European or North American country. Overall, 46% of papers had national primary authors, but 67% of these were South African. The results show that conservation research output in sub-Saharan Africa overall is increasing but only significantly in a few countries, and is still dominated by non-national scientists, probably as a result of a lack of socio-economic development.

scholarly journals Infodemiology of systemic lupus erythematous using Google Trends

Lupus ◽  
2017 ◽  
Vol 26 (8) ◽  
pp. 886-889 ◽  
Author(s):  
M Radin ◽  
S Sciascia
Keyword(s):  
Big Data ◽  
Northern Hemisphere ◽  
Lupus Erythematosus ◽  
Kendall Test ◽  
Google Trends ◽  
Data Monitoring ◽  
Search Term ◽  
Systemic Lupus ◽  
Search Terms ◽  
Google Search

Objective People affected by chronic rheumatic conditions, such as systemic lupus erythematosus (SLE), frequently rely on the Internet and search engines to look for terms related to their disease and its possible causes, symptoms and treatments. ‘Infodemiology’ and ‘infoveillance’ are two recent terms created to describe a new developing approach for public health, based on Big Data monitoring and data mining. In this study, we aim to investigate trends of Internet research linked to SLE and symptoms associated with the disease, applying a Big Data monitoring approach. Methods We analysed the large amount of data generated by Google Trends, considering ‘lupus’, ‘relapse’ and ‘fatigue’ in a 10-year web-based research. Google Trends automatically normalized data for the overall number of searches, and presented them as relative search volumes, in order to compare variations of different search terms across regions and periods. The Menn–Kendall test was used to evaluate the overall seasonal trend of each search term and possible correlation between search terms. Results We observed a seasonality for Google search volumes for lupus-related terms. In the Northern hemisphere, relative search volumes for ‘lupus’ were correlated with ‘relapse’ (τ = 0.85; p = 0.019) and with fatigue (τ = 0.82; p = 0.003), whereas in the Southern hemisphere we observed a significant correlation between ‘fatigue’ and ‘relapse’ (τ = 0.85; p = 0.018). Similarly, a significant correlation between ‘fatigue’ and ‘relapse’ (τ = 0.70; p < 0.001) was seen also in the Northern hemisphere. Conclusion Despite the intrinsic limitations of this approach, Internet-acquired data might represent a real-time surveillance tool and an alert for healthcare systems in order to plan the most appropriate resources in specific moments with higher disease burden.

Assessing E-Government Success Strategies using Internet Search Data

2013 ◽  
pp. 289-307
Author(s):  
Katherine M. Boland ◽  
John G. McNutt
Keyword(s):  
Longitudinal Data ◽  
Google Trends ◽  
Success Strategies ◽  
Internet Search ◽  
Dynamic Nature ◽  
Government Programs ◽  
Search Data ◽  
Research Questions ◽  
Internet Searches ◽  
Citizen Response

Evaluating e-government programs can be a challenging task. While determining program features and capacity are relatively straightforward processes, exploring the more dynamic nature of citizen response to e-government is difficult. Fortunately, recent advances in Internet search technology offer researchers new opportunities to address these research questions. Innovations, such as Google Trends and Google Insights for Search, have made longitudinal data on Internet searches accessible to scholars. The availability of this data opens a number of possible research avenues regarding e-government.

Seasonal variations and public search interests in Toxoplasma: a 16-year retrospective analysis of big data on Google Trends

2020 ◽  
Author(s):  
Lei Liu ◽  
Peng Wang ◽  
Su-Qin Jiang ◽  
Zi-Rong Zhong ◽  
Ting-Zheng Zhan ◽  
...  
Keyword(s):  
New Zealand ◽  
Google Trends ◽  
Seasonal Patterns ◽  
Search Term ◽  
Internet Search ◽  
Search Volume ◽  
The Usa ◽  
Search Data ◽  
Relative Search Volume ◽  
The Uk

Abstract Background This study aims to understand whether there is a seasonal change in the internet search interest for Toxoplasma by using the data derived from Google Trends (GT). Methods The present study searched for the relative search volume (RSV) for the search term ‘Toxoplasma’ in GT within six major English-speaking countries (Australia, New Zealand [Southern Hemisphere] and Canada, Ireland, the UK and the USA [Northern Hemisphere] from 1 January 2004 to 31 December 2019, utilizing the category of ‘health’. Data regarding the RSV of Toxoplasma was obtained and further statistical analysis was performed in R software using the ‘season’ package. Results There were significantly seasonal patterns for the RSV of the search term ‘Toxoplasma’ in five countries (all p&lt;0.05), except for the UK. A peak in December–March and a trough in July–September (Canada, Ireland, the UK and the USA) were observed, while a peak in June/August and a trough in December/February (Australia, New Zealand) were also found. Moreover, the presence of seasonal patterns regarding RSV for ‘Toxoplasma’ between the Southern and Northern Hemispheres was also found (both p&lt;0.05), with a reversed meteorological month. Conclusions Overall, our study revealed the seasonal variation for Toxoplasma in using internet search data from GT, providing additional evidence on seasonal patterns in Toxoplasma.

Predicting Public Interest in Nonsurgical Cosmetic Procedures Using Google Trends

2019 ◽  
Vol 40 (11) ◽  
pp. 1253-1262 ◽  
Author(s):  
Jonathan D Tijerina ◽  
Shane D Morrison ◽  
Ian T Nolan ◽  
Matthew J Parham ◽  
Rahim Nazerali
Keyword(s):  
Hyaluronic Acid ◽  
Public Interest ◽  
The United States ◽  
Google Trends ◽  
Search Term ◽  
Data Set ◽  
Fat Transfer ◽  
Laser Hair Removal ◽  
Search Terms ◽  
Search Volume

Abstract Background Google Trends (GT) provides cost-free, customizable analyses of search traffic for specified terms entered into Google’s search engine. GT may inform plastic surgery marketing decisions and resource allocation. Objectives The aim of this study was to determine GT’s utility in tracking and predicting public interest in nonsurgical cosmetic procedures and to examine trends over time of public interest in nonsurgical procedures. Methods GT search volume for terms in 6 ASPS and ASAPS nonsurgical procedure categories (Botox injections, chemical peel, laser hair removal, laser skin resurfacing, microdermabrasion and soft tissue fillers [subcategories: collagen, fat, and hyaluronic acid]) were compared with ASPS and ASAPS case volumes for available dates between January 2004 and March 2019 with the use of univariate linear regression, taking P &lt; 0.01 as the cutoff for significance. Results Total search volume varied by search term within the United States and internationally. Significant positive correlations were demonstrated for 17 GT terms in all 6 ASPS and ASAPS categories: “Botox®,” “collagen injections,” “collagen lip injections” with both databases; and “chemical skin peel,” “skin peel,” “acne scar treatment,” “CO2 laser treatment,” “dermabrasion,” “collagen injections,” “collagen lip injections,” “fat transfer,” “hyaluronic acid fillers,” “hyaluronic acid injection,” “hyaluronic acid injections,” “Juvederm®,” and “fat transfer” with just 1 database. Many search terms were not significant, emphasizing the need for careful selection of search terms. Conclusions Our analysis further elaborates on recent characterization of GT as a powerful and intuitive data set for plastic surgeons, with the potential to accurately gauge global and national interest in topics and procedures related to nonsurgical cosmetic procedures.

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