Scraping the Web for Public Health Gains: Ethical Considerations from a ‘Big Data’ Research Project on HIV and Incarceration

Rennie, Stuart; Buchbinder, Mara; Juengst, Eric T.; Brinkley‐Rubinstein, Lauren; Blue, Colleen; Rosen, David L.

doi:10.1093/phe/phaa006

Cited by 23 publications

(11 citation statements)

References 18 publications

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“…In parallel with these changes in research practice, high profile cases of data misuse have emerged, exposing research participants to privacy breaches and risk of harm ( Fuller, 2019 ). In response, debate has increased about the role and effectiveness of the Research Ethics Committee (REC) as the chief ethical research oversight mechanism in research, given the specific challenges presented by research with big data ( Ferretti et al, 2020 ; Rennie et al, 2020 ). RECs, also known as Institutional Review Boards (IRBs) and Research Ethics Boards (REBs), were created in the 20th century to protect the safety and interests of human participants in research ( Friesen et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

Ferretti

Ienca

Velarde

et al. 2021

Journal of Empirical Research on Human Research Ethics

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Big data trends in health research challenge the oversight mechanism of the Research Ethics Committees (RECs). The traditional standards of research quality and the mandate of RECs illuminate deficits in facing the computational complexity, methodological novelty, and limited auditability of these approaches. To better understand the challenges facing RECs, we explored the perspectives and attitudes of the members of the seven Swiss Cantonal RECs via semi-structured qualitative interviews. Our interviews reveal limited experience among REC members with the review of big data research, insufficient expertise in data science, and uncertainty about how to mitigate big data research risks. Nonetheless, RECs could strengthen their oversight by training in data science and big data ethics, complementing their role with external experts and ad hoc boards, and introducing precise shared practices.

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Section: Introductionmentioning

confidence: 99%

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

Ferretti

Ienca

Velarde

et al. 2021

Journal of Empirical Research on Human Research Ethics

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“…The health ministry press releases are collected on the Wikipedia page for Covid-Testing (see https://en.wikipedia.org/wiki/COVID-19_testing ). Webscraping press releases or metadata of public institutions to gain lacking data on public health issues has been applied to link incarceration and HIV rates [ 22 ] and to detect community autism spectrum disorder rates [ 23 ]. Further, Wikipedia has been deemed helpful for public health needs [ 24 ] and especially for modelling trends of the Coronavirus outbreak (Doğaner, 2020) [ 25 ].…”

Section: Methodsmentioning

confidence: 99%

Early days of the pandemic—The association of economic and socio-political country characteristics with the development of the COVID-19 death toll

Holz

Mayerl

2021

PLoS ONE

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This article examines cross-national differences in growth of deaths by COVID-19 over time in the first phase of the pandemic, during the time period of 31st December 2019 to 2nd April 2020. We seek to understand and explain country level reaction in the initial period of the pandemic. We explore socio-economic and socio-political country characteristics as determinants of deaths per day and we examine whether country characteristics act as moderating factors for different growth patterns of deaths per day over time. The country characteristics include variables about economy, globalization, health care and demography. We examine data published by the European Center of Disease Prevention and Control (ECDC) in combination with World Bank data and a webscraping approach. Using a conditional growth model specified as a multilevel regression model with deaths by COVID-19 per day as the outcome variable, we show that economic variables are not significantly associated with decrease or increase of deaths by COVID-19. In contrast, variables about national health care mitigate the impact of the pandemic. Demography shows expected effects with an increase of growth of deaths in countries with a higher percentage of people older than 65 years. Globalization predicts the death toll as well: Social interaction between people is deadly on a short-term scale (in the form of tourism). Our results mirror frequent demands for global investment in national health systems.

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“…However, it is worthwhile to point out that an expressed concern in the field of web scraping due to the fact that scrapers can obtain personal information and publish it to an open database [21] – [23] . This becomes even more sensitive when medical records are retrieved by the scraper.…”

Section: Literature Reviewmentioning

confidence: 99%

COVID-Scraper: An Open-Source Toolset for Automatically Scraping and Processing Global Multi-Scale Spatiotemporal COVID-19 Records

et al. 2021

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In 2019, COVID-19 quickly spread across the world, infecting billions of people and disrupting the normal lives of citizens in every country. Governments, organizations, and research institutions all over the world are dedicating vast resources to research effective strategies to fight this rapidly propagating virus. With virus testing, most countries publish the number of confirmed cases, dead cases, recovered cases, and locations routinely through various channels and forms. This important data source has enabled researchers worldwide to perform different COVID-19 scientific studies, such as modeling this virus's spreading patterns, developing prevention strategies, and studying the impact of COVID-19 on other aspects of society. However, one major challenge is that there is no standardized, updated, and high-quality data product that covers COVID-19 cases data internationally. This is because different countries may publish their data in unique channels, formats, and time intervals, which hinders researchers from fetching necessary COVID-19 datasets effectively, especially for fine-scale studies. Although existing solutions such as John's Hopkins COVID-19 Dashboard and 1point3acres COVID-19 tracker are widely used, it is difficult for users to access their original dataset and customize those data to meet specific requirements in categories, data structure, and data source selection. To address this challenge, we developed a toolset using cloud-based web scraping to extract, refine, unify, and store COVID-19 cases data at multiple scales for all available countries around the world automatically. The toolset then publishes the data for public access in an effective manner, which could offer users a real time COVID-19 dynamic dataset with a global view. Two case studies are presented about how to utilize the datasets. This toolset can also be easily extended to fulfill other purposes with its open-source nature.

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Scraping the Web for Public Health Gains: Ethical Considerations from a ‘Big Data’ Research Project on HIV and Incarceration

Cited by 23 publications

References 18 publications

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

Early days of the pandemic—The association of economic and socio-political country characteristics with the development of the COVID-19 death toll

COVID-Scraper: An Open-Source Toolset for Automatically Scraping and Processing Global Multi-Scale Spatiotemporal COVID-19 Records

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