scholarly journals Using a Bayesian Method to Assess Google, Twitter, and Wikipedia for ILI Surveillance

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Danielle Sharpe ◽  
Richard Hopkins ◽  
Robert L. Cook ◽  
Catherine W. Striley
Keyword(s):  
Seasonal Changes ◽  
Bayesian Method ◽  
Influenza Season ◽  
Healthcare Providers ◽  
High Sensitivity ◽  
Change Points ◽  
Influenza Surveillance ◽  
Web Based ◽  
Using Data ◽  
The Web

ObjectiveTo comparatively analyze Google, Twitter, and Wikipedia byevaluating how well change points detected in each web-based sourcecorrespond to change points detected in CDC ILI data.IntroductionTraditional influenza surveillance relies on reports of influenza-like illness (ILI) by healthcare providers, capturing individualswho seek medical care and missing those who may search, post,and tweet about their illnesses instead. Existing research has shownsome promise of using data from Google, Twitter, and Wikipediafor influenza surveillance, but with conflicting findings, studies haveonly evaluated these web-based sources individually or dually withoutcomparing all three of them1-5. A comparative analysis of all threeweb-based sources is needed to know which of the web-based sourcesperforms best in order to be considered to complement traditionalmethods.MethodsWe collected publicly available, de-identified data from the CDCILINet system, Google Flu Trends, HealthTweets.org, and Wikipediafor the 2012-2015 influenza seasons. Bayesian change point analysiswas the method used to detect change points, or seasonal changes,in each of the web-data sources for comparison to change pointsin CDC ILI data. All analyses was conducted using the R package‘bcp’ v4.0.0 in RStudio v0.99.484. Sensitivity and positive predictivevalues (PPV) were then calculated.ResultsDuring the 2012-2015 influenza seasons, a high sensitivity of 92%was found for Google, while the PPV for Google was 85%. A lowsensitivity of 50% was found for Twitter; a low PPV of 43% wasfound for Twitter also. Wikipedia had the lowest sensitivity of 33%and lowest PPV of 40%.ConclusionsGoogle had the best combination of sensitivity and PPV indetecting change points that corresponded with change points found inCDC data. Overall, change points in Google, Twitter, and Wikipediadata occasionally aligned well with change points captured in CDCILI data, yet these sources did not detect all changes in CDC data,which could indicate limitations of the web-based data or signify thatthe Bayesian method is not adequately sensitive. These three web-based sources need to be further studied and compared using otherstatistical methods before being incorporated as surveillance data tocomplement traditional systems.Figure 1. Detection of change points, 2012-2013 influenza seasonFigure 2. Detection of change points, 2013-2014 influenza seasonFigure 3. Detection of change points, 2014-2015 influenza season

scholarly journals What will the next influenza season bring about: seasonal influenza or the new A(H1N1)v? An analysis of German influenza surveillance data

2009 ◽  
Vol 14 (32) ◽  
Author(s):  
H Uphoff ◽  
S Geis ◽  
A Grüber ◽  
A M Hauri
Keyword(s):  
Influenza A ◽  
Seasonal Influenza ◽  
Influenza Season ◽  
Influenza Viruses ◽  
Moderate Intensity ◽  
Influenza Surveillance ◽  
Influenza B ◽  
Low Intensity ◽  
Influenza A H1n1 ◽  
Using Data

For the next influenza season (winter 2009-10) the relative contributions to virus circulation and influenza-associated morbidity of the seasonal influenza viruses A(H3N2), A(H1N1) and B, and the new influenza A(H1N1)v are still unknown. We estimated the chances of seasonal influenza to circulate during the upcoming season using data of the German influenza sentinel scheme from 1992 to 2009. We calculated type and subtype-specific indices for past exposure and the corresponding morbidity indices for each season. For the upcoming season 2009-10 our model suggests that it is unlikely that influenza A(H3N2) will circulate with more than a low intensity, seasonal A(H1N1) with more than a low to moderate intensity, and influenza B with more than a low to median intensity. The probability of a competitive circulation of seasonal influenza A with the new A(H1N1)v is low, increasing the chance for the latter to dominate the next influenza season in Germany.

scholarly journals Comparison of Self-Reported Telephone Interviewing and Web-Based Survey Responses: Findings From the Second Australian Young and Well National Survey

2017 ◽  
Vol 4 (3) ◽  
pp. e37 ◽  
Author(s):  
Alyssa C Milton ◽  
Louise A Ellis ◽  
Tracey A Davenport ◽  
Jane M Burns ◽  
Ian B Hickie
Keyword(s):  
Body Image ◽  
Suicidal Ideation ◽  
National Survey ◽  
High Sensitivity ◽  
Self Report ◽  
Attrition Bias ◽  
Web Based ◽  
Highly Sensitive ◽  
Item Sensitivity ◽  
The Web

Background Web-based self-report surveying has increased in popularity, as it can rapidly yield large samples at a low cost. Despite this increase in popularity, in the area of youth mental health, there is a distinct lack of research comparing the results of Web-based self-report surveys with the more traditional and widely accepted computer-assisted telephone interviewing (CATI). Objective The Second Australian Young and Well National Survey 2014 sought to compare differences in respondent response patterns using matched items on CATI versus a Web-based self-report survey. The aim of this study was to examine whether responses varied as a result of item sensitivity, that is, the item’s susceptibility to exaggeration on underreporting and to assess whether certain subgroups demonstrated this effect to a greater extent. Methods A subsample of young people aged 16 to 25 years (N=101), recruited through the Second Australian Young and Well National Survey 2014, completed the identical items on two occasions: via CATI and via Web-based self-report survey. Respondents also rated perceived item sensitivity. Results When comparing CATI with the Web-based self-report survey, a Wilcoxon signed-rank analysis showed that respondents answered 14 of the 42 matched items in a significantly different way. Significant variation in responses (CATI vs Web-based) was more frequent if the item was also rated by the respondents as highly sensitive in nature. Specifically, 63% (5/8) of the high sensitivity items, 43% (3/7) of the neutral sensitivity items, and 0% (0/4) of the low sensitivity items were answered in a significantly different manner by respondents when comparing their matched CATI and Web-based question responses. The items that were perceived as highly sensitive by respondents and demonstrated response variability included the following: sexting activities, body image concerns, experience of diagnosis, and suicidal ideation. For high sensitivity items, a regression analysis showed respondents who were male (beta=−.19, P=.048) or who were not in employment, education, or training (NEET; beta=−.32, P=.001) were significantly more likely to provide different responses on matched items when responding in the CATI as compared with the Web-based self-report survey. The Web-based self-report survey, however, demonstrated some evidence of avidity and attrition bias. Conclusions Compared with CATI, Web-based self-report surveys are highly cost-effective and had higher rates of self-disclosure on sensitive items, particularly for respondents who identify as male and NEET. A drawback to Web-based surveying methodologies, however, includes the limited control over avidity bias and the greater incidence of attrition bias. These findings have important implications for further development of survey methods in the area of health and well-being, especially when considering research topics (in this case diagnosis, suicidal ideation, sexting, and body image) and groups that are being recruited (young people, males, and NEET).

scholarly journals Changes in the incidence of seasonal influenza in response to COVID-19 social distancing measures: an observational study based on Canada’s national influenza surveillance system

2021 ◽  
Author(s):  
Andrew Pierce ◽  
Margaret Haworth-Brockman ◽  
Diana Marin ◽  
Zulma V. Rueda ◽  
Yoav Keynan
Keyword(s):  
Surveillance System ◽  
Seasonal Influenza ◽  
Influenza Season ◽  
Influenza Surveillance ◽  
Social Distancing ◽  
Primary Focus ◽  
Using Data ◽  
Novel Coronavirus ◽  
Time Frames ◽  
Incident Cases

Abstract Objectives Seasonal influenza is an acute respiratory infection that presents a significant annual burden to Canadians and the Canadian healthcare system. Social distancing measures that were implemented to control the 2019–2020 novel coronavirus outbreak were investigated for their ability to lessen the incident cases of seasonal influenza. Methods We conducted an ecological study using data from Canada’s national influenza surveillance system to investigate whether social distancing measures to control COVID-19 reduced the incident cases of seasonal influenza. Data taken from three separate time frames facilitated analysis of the 2019–2020 influenza season prior to, during, and following the implementation of COVID-19-related measures and enabled comparisons with the same time periods during three preceding flu seasons. The incidence, which referred to the number of laboratory-confirmed cases of specific influenza strains, was of primary focus. Further analysis determined the number of new laboratory-confirmed influenza or influenza-like illness outbreaks. Results Our results indicate a premature end to the 2019–2020 influenza season, with significantly fewer cases and outbreaks being recorded following the enactment of many COVID-19 social distancing policies. The incidence of influenza strains A (H3N2), A (unsubtyped), and B were all significantly lower at the tail end of the 2019–2020 influenza season as compared with preceding seasons (p = 0.0003, p = 0.0007, p = 0.0019). Conclusion Specific social distancing measures and behaviours may serve as effective tools to limit the spread of influenza transmission moving forward, as they become more familiar.

New Perspectives on Sustainable Healthcare Delivery Through Web of Things

2018 ◽  
pp. 166-187 ◽  
Author(s):  
Cristina Elena Turcu ◽  
Corneliu Octavian Turcu
Keyword(s):  
Social Networks ◽  
Patient Care ◽  
Medical Devices ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
Web Based ◽  
Web Of Things ◽  
The Social ◽  
Health Sensors ◽  
The Web

This chapter focuses on examining the adoption of the web of things paradigm in healthcare in order to facilitate the development of new web-based systems in more effective and efficient ways. Nowadays, the increasing number of personal health sensors and medical devices present the opportunity for healthcare providers to interact with patients in entirely new ways. In this context, the WoT paradigm could be closely linked to patient care and has the potential to generate changes in healthcare. WoT could also be applied in the social and insurance fields, etc. The social web of things (SWoT) further extends WoT in order to facilitate continued interaction between physical devices and humans, allowing the integration of smart objects with social networks. Although it opens new social possibilities, it was less applied in the delivery of healthcare. Nevertheless, its successful adoption depends on overcoming some open challenges.

scholarly journals Estimating the undetected burden of influenza hospitalizations in children

2006 ◽  
Vol 135 (6) ◽  
pp. 951-958 ◽  
Author(s):  
C. G. GRIJALVA ◽  
G. A. WEINBERG ◽  
N. M. BENNETT ◽  
M. A. STAAT ◽  
A. S. CRAIG ◽  
...  
Keyword(s):  
Surveillance System ◽  
Clinical Laboratory ◽  
Influenza Season ◽  
Influenza Surveillance ◽  
Surveillance Systems ◽  
Emerging Infections ◽  
Surveillance Network ◽  
Laboratory Surveillance ◽  
Capture Recapture ◽  
Using Data

SUMMARYDuring the 2004–2005 influenza season two independent influenza surveillance systems operated simultaneously in three United States counties. The New Vaccine Surveillance Network (NVSN) prospectively enrolled children hospitalized for respiratory symptoms/fever and tested them using culture and RT–PCR. The Emerging Infections Program (EIP) and a similar clinical-laboratory surveillance system identified hospitalized children who had positive influenza tests obtained as part of their usual medical care. Using data from these systems, we applied capture–recapture analyses to estimate the burden of influenza related-hospitalizations in children aged <5 years. During the 2004–2005 influenza season the influenza-related hospitalization rate estimated by capture–recapture analysis was 8·6/10 000 children aged <5 years. When compared to this estimate, the sensitivity of the prospective surveillance system was 69% and the sensitivity of the clinical-laboratory based system was 39%. In the face of limited resources and an increasing need for influenza surveillance, capture–recapture analysis provides better estimates than either system alone.

scholarly journals Changes in the incidence of seasonal influenza in response to COVID-19 social distancing measures: an observational study based on Canada’s national influenza surveillance system

2020 ◽  
Author(s):  
Andrew Pierce ◽  
Margaret Haworth-Brockman ◽  
Diana Marin ◽  
Zulma V Rueda ◽  
Yoav Keynan
Keyword(s):  
Surveillance System ◽  
Seasonal Influenza ◽  
Influenza Season ◽  
Influenza Surveillance ◽  
Social Distancing ◽  
Canadian Health Care System ◽  
Canadian Health ◽  
Primary Focus ◽  
Using Data ◽  
Novel Coronavirus

Abstract Objectives: Seasonal influenza is an acute respiratory infection that presents a significant annual burden to Canadians and the Canadian health care system. Social distancing measures that were implemented to control the novel coronavirus outbreak were also investigated for their ability to lessen the incidence of seasonal influenza.Methods: We conducted an ecological study using data from Canada’s national influenza surveillance system to investigate whether social distancing measures to control COVID-19 reduced the incidence of seasonal influenza. Data taken from three separate time frames facilitated analysis of the 2019-20 influenza season prior to, during, and following the implementation of COVID-19 related measures and enabled comparisons to the same time periods during three preceding flu seasons. The incidence of specific influenza strains was of primary focus. Further analysis was performed to determine the number of new laboratory-confirmed influenza or influenza like illness outbreaks.Results: Our results indicate a premature end to the 2019-20 influenza season, with a significantly fewer number of cases and outbreaks being recorded following the enactment of many COVID-19 social distancing polices. The incidence of influenza strains A (H3N2), A (unsubtyped), and B were all significantly lower at the tail-end of the 2019-20 influenza season, compared with preceding seasons.Conclusion: Specific social distancing measures and behaviours may serve as effective tools to limit the spread of influenza transmission moving forward, as they become more familiar.

PENERAPAN METODE PROTOTYPING PADA PERANCANGAN APLIKASI SPPD KPPN MEDAN II BERBASIS WEBSITE

2019 ◽  
Vol 11 (1) ◽  
pp. 8-19
Author(s):  
Crystal Jelita Lumban Tobing
Keyword(s):  
Time Saving ◽  
Web Based ◽  
Government Organization ◽  
Manual Method ◽  
Microsoft Word ◽  
Ministry Of Finance ◽  
The Government ◽  
The City ◽  
Employee Data ◽  
The Web

 KPPN Medan II is one of the government organization units at the Ministry of Finance. Where leaders and employees who work at KPPN Medan II always carry out official trips between cities and outside the city. With these conditions, making SPPD documents experiencing the intensity of official travel activities carried out by employees of KPPN Medan II can be said frequently. So that in making SPPD in KPPN Medan II is still using the manual method that is recording through Microsoft Word which in the sense is less effective and efficient. In naming employees who get official assignments, officers manually entering employee data that receives official travel letters are prone to being lost because data is manually written. The web-based SPPD application is built by applying this prototyping method which is expected to facilitate SPPD KPPN Medan II management officers in making SPPD that is effective, efficient, accurate, time-saving, and not prone to losing SPPD data of KPPN Medan II employees who will has made official trips due to the existence of a special database to accommodate all SPPD files.

Rancang Bangun Sistem Penerimaan Dan Mutasi Barang Pada PDAM Tirta Kerta Raharja

Sensi Journal ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. 236-246
Author(s):  
Ilamsyah Ilamsyah ◽  
Yulianto Yulianto ◽  
Tri Vita Febriani
Keyword(s):  
System Analysis ◽  
Object Oriented ◽  
Analysis Method ◽  
Web Based ◽  
Visual Modeling ◽  
Long Time ◽  
The Right ◽  
And Control ◽  
Web Based System ◽  
The Web

The right and appropriate system of receiving and transferring goods is needed by the company. In the process of receiving and transferring goods from the central warehouse to the branch warehouse at PDAM Tirta Kerta Raharja, Tangerang Regency, which is currently done manually is still ineffective and inaccurate because the Head of Subdivision uses receipt documents, namely PPBP and mutation of goods, namely MPPW in the form of paper as a submission media. The Head of Subdivision enters the data of receipt and mutation of goods manually and requires a relatively long time because at the time of demand for the transfer of goods the Head of Subdivision must check the inventory of goods in the central warehouse first. Therefore, it is necessary to hold a design of information systems for the receipt and transfer of goods from the central warehouse to a web-based branch warehouse that is already database so that it is more effective, efficient and accurate. With the web-based system of receiving and transferring goods that are already datatabed, it can facilitate the Head of Subdivision in inputing data on the receipt and transfer of goods and control of stock inventory so that the Sub Head of Subdivision can do it periodically to make it more effective, efficient and accurate. The method of data collection is done by observing, interviewing and studying literature from various previous studies, while the system analysis method uses the Waterfall method which aims to solve a problem and uses design methods with visual modeling that is object oriented with UML while programming using PHP and MySQL as a database.

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