scholarly journals Digital public health surveillance: a systematic scoping review

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zahra Shakeri Hossein Abad ◽  
Adrienne Kline ◽  
Madeena Sultana ◽  
Mohammad Noaeen ◽  
Elvira Nurmambetova ◽  
...  
Keyword(s):  
Public Health ◽  
Language Processing ◽  
Scoping Review ◽  
Public Health Surveillance ◽  
The United States ◽  
Health Surveillance ◽  
Successful Implementation ◽  
Public Health Action ◽  
Accessible Information ◽  
Scoping Reviews

AbstractThe ubiquitous and openly accessible information produced by the public on the Internet has sparked an increasing interest in developing digital public health surveillance (DPHS) systems. We conducted a systematic scoping review in accordance with the PRISMA extension for scoping reviews to consolidate and characterize the existing research on DPHS and identify areas for further research. We used Natural Language Processing and content analysis to define the search strings and searched Global Health, Web of Science, PubMed, and Google Scholar from 2005 to January 2020 for peer-reviewed articles on DPHS, with extensive hand searching. Seven hundred fifty-five articles were included in this review. The studies were from 54 countries and utilized 26 digital platforms to study 208 sub-categories of 49 categories associated with 16 public health surveillance (PHS) themes. Most studies were conducted by researchers from the United States (56%, 426) and dominated by communicable diseases-related topics (25%, 187), followed by behavioural risk factors (17%, 131). While this review discusses the potentials of using Internet-based data as an affordable and instantaneous resource for DPHS, it highlights the paucity of longitudinal studies and the methodological and inherent practical limitations underpinning the successful implementation of a DPHS system. Little work studied Internet users’ demographics when developing DPHS systems, and 39% (291) of studies did not stratify their results by geographic region. A clear methodology by which the results of DPHS can be linked to public health action has yet to be established, as only six (0.8%) studies deployed their system into a PHS context.

scholarly journals Monitoring the opioid epidemic via social media discussions

2021 ◽  
Author(s):  
Adam Lavertu ◽  
Tymor Hamamsy ◽  
Russ B Altman
Keyword(s):  
Public Health ◽  
Social Media ◽  
Language Processing ◽  
Public Health Surveillance ◽  
The United States ◽  
Health Surveillance ◽  
Opioid Epidemic ◽  
Strongly Correlated ◽  
Drug Classes ◽  
Social Media Platforms

AbstractThe opioid epidemic persists in the United States; in 2019, annual drug overdose deaths increased by 4.6% to 70,980, including 50,042 opioid-related deaths. The widespread abuse of opioids across geographies and demographics and the rapidly changing dynamics of abuse require reliable and timely information to monitor and address the crisis. Social media platforms include petabytes of participant-generated data, some of which, offers a window into the relationship between individuals and their use of drugs. We assessed the utility of Reddit data for public health surveillance, with a focus on the opioid epidemic. We built a natural language processing pipeline to identify opioid-related comments and created a cohort of 1,689,039 geo-located Reddit users, each assigned to a city and state. We followed these users over a period of 10+ years and measured their opioid-related activity over time. We benchmarked the activity of this cohort against CDC overdose death rates for different drug classes and NFLIS drug report rates. Our Reddit-derived rates of opioid discussion strongly correlated with external benchmarks on the national, regional, and city level. During the period of our study, kratom emerged as an active discussion topic; we analyzed mentions of kratom to understand the dynamics of its use. We also examined changes in opioid discussions during the COVID-19 pandemic; in 2020, many opioid classes showed marked increases in discussion patterns. Our work suggests the complementary utility of social media as a part of public health surveillance activities.

Disaggregation of Latina/o Child and Adult Health Data: A Systematic Review of Public Health Surveillance Surveys in the United States

2021 ◽  
Vol 40 (1) ◽  
pp. 61-79
Author(s):  
Carmela Alcántara ◽  
Shakira F. Suglia ◽  
Irene Perez Ibarra ◽  
A. Louise Falzon ◽  
Elliot McCullough ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Systematic Review ◽  
Public Health Surveillance ◽  
The United States ◽  
Health Data ◽  
Health Surveillance ◽  
Adult Health

Structural Transphobia, Homophobia, and Biphobia in Public Health Practice: The Example of COVID-19 Surveillance

2021 ◽  
pp. e1-e7
Author(s):  
Randall L. Sell ◽  
Elise I. Krims
Keyword(s):  
Public Health ◽  
United States ◽  
Race And Ethnicity ◽  
Public Health Surveillance ◽  
Public Health Practice ◽  
The United States ◽  
Health Surveillance ◽  
Essential Information ◽  
And Gender ◽  
Public Health Surveillance System

Public health surveillance can have profound impacts on the health of populations, with COVID-19 surveillance offering an illuminating example. Surveillance surrounding COVID-19 testing, confirmed cases, and deaths has provided essential information to public health professionals about how to minimize morbidity and mortality. In the United States, surveillance has also pointed out how populations, on the basis of geography, age, and race and ethnicity, are being impacted disproportionately, allowing targeted intervention and evaluation. However, COVID-19 surveillance has also highlighted how the public health surveillance system fails some communities, including sexual and gender minorities. This failure has come about because of the haphazard and disorganized way disease reporting data are collected, analyzed, and reported in the United States, and the structural homophobia, transphobia, and biphobia acting within these systems. We provide recommendations for addressing these concerns after examining experiences collecting race data in COVID-19 surveillance and attempts in Pennsylvania and California to incorporate sexual orientation and gender identity variables into their pandemic surveillance efforts. (Am J Public Health. Published online ahead of print June 10, 2021: e1–e7. https://doi.org/10.2105/AJPH.2021.3062727 )

scholarly journals Collection of Data on Race, Ethnicity, Language, and Nativity by US Public Health Surveillance and Monitoring Systems: Gaps and Opportunities

2017 ◽  
Vol 133 (1) ◽  
pp. 45-54 ◽  
Author(s):  
Alfonso Rodriguez-Lainz ◽  
Mariana McDonald ◽  
Maureen Fonseca-Ford ◽  
Ana Penman-Aguilar ◽  
Stephen H. Waterman ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Data Collection ◽  
Public Health Surveillance ◽  
The United States ◽  
Health Surveillance ◽  
Monitoring Systems ◽  
Primary Language ◽  
Use Of Data ◽  
Race Ethnicity

Objective: Despite increasing diversity in the US population, substantial gaps in collecting data on race, ethnicity, primary language, and nativity indicators persist in public health surveillance and monitoring systems. In addition, few systems provide questionnaires in foreign languages for inclusion of non-English speakers. We assessed (1) the extent of data collected on race, ethnicity, primary language, and nativity indicators (ie, place of birth, immigration status, and years in the United States) and (2) the use of data-collection instruments in non-English languages among Centers for Disease Control and Prevention (CDC)–supported public health surveillance and monitoring systems in the United States. Methods: We identified CDC-supported surveillance and health monitoring systems in place from 2010 through 2013 by searching CDC websites and other federal websites. For each system, we assessed its website, documentation, and publications for evidence of the variables of interest and use of data-collection instruments in non-English languages. We requested missing information from CDC program officials, as needed. Results: Of 125 data systems, 100 (80%) collected data on race and ethnicity, 2 more collected data on ethnicity but not race, 26 (21%) collected data on racial/ethnic subcategories, 40 (32%) collected data on place of birth, 21 (17%) collected data on years in the United States, 14 (11%) collected data on immigration status, 13 (10%) collected data on primary language, and 29 (23%) used non-English data-collection instruments. Population-based surveys and disease registries more often collected data on detailed variables than did case-based, administrative, and multiple-source systems. Conclusions: More complete and accurate data on race, ethnicity, primary language, and nativity can improve the quality, representativeness, and usefulness of public health surveillance and monitoring systems to plan and evaluate targeted public health interventions to eliminate health disparities.

scholarly journals Epidemic intelligence in the European Union: strengthening the ties

2008 ◽  
Vol 13 (6) ◽  
pp. 1-2
Author(s):  
D Coulombier
Keyword(s):  
Public Health ◽  
European Union ◽  
Public Health Surveillance ◽  
Union Member ◽  
Health Surveillance ◽  
The European Union ◽  
Public Health Action ◽  
Epidemic Intelligence ◽  
Health Action ◽  
European Union Member States

Public health surveillance remains the cornerstone of the detection of health threats requiring public health action. Two articles in this issue of Eurosurveillance refer to the challenges of epidemic intelligence activities in European Union Member States.

scholarly journals User Privacy Concerns and Expectations of Post-Pandemic Health Surveillance: A Scenario-Based Interview Study (Preprint)

2021 ◽  
Author(s):  
John S. Seberger ◽  
Sameer Patil
Keyword(s):  
Public Health ◽  
General Public ◽  
Public Health Surveillance ◽  
Effective Means ◽  
The United States ◽  
Health Surveillance ◽  
Personal Privacy ◽  
User Privacy ◽  
Privacy Concerns ◽  
Greater Good

BACKGROUND Smartphone-based apps designed and deployed to mitigate the ongoing COVID-19 pandemic are poised to become an infrastructure for post-pandemic public health surveillance. Yet people frequently identify deep-seated privacy concerns about such apps, invoking rationalizations such as contributing to ‘the greater good’ to justify their privacy-related discomfort. We adopt a future-oriented lens and consider participant perceptions of the potential routinization of such apps as a general public health surveillance infrastructure. This work focuses on the need to temper the surveillant achievement of public health with consideration for potential colonization of public health by the exploitative mechanisms of surveillance capitalism. OBJECTIVE This study develops an understanding of people’s perceptions of the potential routinization of apps as an infrastructure for public health surveillance after the COVID-19 pandemic has ended. METHODS We conducted scenario-based interviews (n = 19) with adults in the United States in order to understand how people perceive the short- and long-term privacy concerns associated with a fictional smart-thermometer app deployed to mitigate the ‘outbreak of a contagious disease.’ The scenario indicated that the app would continue functioning ‘after the disease outbreak as dissipated.’ We analyzed participant interviews using reflexive thematic analysis (TA). RESULTS Participants contextualized their perceptions of the app in a core trade-off between public health and personal privacy. They further evidenced the widespread expectation that data collected through health-surveillant apps would be shared with unknown third parties for financial gain. This expectation suggests a perceived alignment between health surveillant technologies and the broader economics of surveillance capitalism. Because of such expectations, participants routinely rationalized the use of the fictional app, which they viewed as always already privacy-invasive, by invoking ‘the greater good.’ We uncover that ‘the greater good’ is multi-faceted and self-contradictory, evidencing participants’ worry that health surveillance apps will contribute to an expansion of exploitative forms of surveillance. CONCLUSIONS While apps may be an effective means of pandemic-mitigation and preparedness, such apps are not exclusively beneficial in their outcomes. The potential routinization of apps as an infrastructure of general public health surveillance fosters end-user exploitation. Through its alignment with surveillance capitalism, such exploitation potentially erodes patient trust in the health care systems and providers that care for them. The inroads to such exploitation are present in participants’ manifestation of digital resignation, hyperbolic scaling, expectation of an infrastructure that works ‘too well,’ and generalized privacy fatalism.

Natural language processing and machine learning methods in public health surveillance: a narrative review (Preprint)

2020 ◽  
Author(s):  
Patrick James Ward ◽  
April M Young
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Online Media ◽  
Traditional Surveillance

BACKGROUND Public health surveillance is critical to detecting emerging population health threats and improvements. Surveillance data has increased in size and complexity, posing challenges to data management and analysis. Natural language processing (NLP) and machine learning (ML) are valuable tools for analysis of unstructured data involving free-text and have been used in innovative ways to examine a variety of health outcomes. OBJECTIVE Given the cross-disciplinary applications of NLP and ML, research on their applications in surveillance have been disseminated in a variety of outlets. As such, the aim of this narrative review was to describe the current state of NLP and ML use in surveillance science and to identify directions in future research. METHODS Information was abstracted from articles describing the use of natural language processing and machine learning in public health surveillance identified through a PubMed search. RESULTS Twenty-two articles met review criteria, 12 involving traditional surveillance data sources and 10 involving online media sources for surveillance. Traditional surveillance sources analyzed with NLP and ML consisted primarily of death certificates (n=6), hospital data (n=5), and online media sources (e.g., Twitter) (n=8). CONCLUSIONS The reviewed articles demonstrate the potential of NLP and ML to enhance surveillance data through improving timeliness of surveillance, identifying cases in the absence of standardized case definitions, and enabling mining of social media for public health surveillance.

scholarly journals The Past, Present, and Future of Public Health Surveillance

Scientifica ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-26 ◽  
Author(s):  
Bernard C. K. Choi
Keyword(s):  
Public Health ◽  
Public Health Surveillance ◽  
Field Investigation ◽  
Health Surveillance ◽  
Modern Concept ◽  
Public Health Action ◽  
The Past ◽  
Epidemiologic Surveillance ◽  
The Future ◽  
Definition Of

This paper provides a review of the past, present, and future of public health surveillance—the ongoing systematic collection, analysis, interpretation, and dissemination of health data for the planning, implementation, and evaluation of public health action. Public health surveillance dates back to the first recorded epidemic in 3180 B.C. in Egypt. Hippocrates (460 B.C.–370 B.C.) coined the terms endemic and epidemic, John Graunt (1620–1674) introduced systematic data analysis, Samuel Pepys (1633–1703) started epidemic field investigation, William Farr (1807–1883) founded the modern concept of surveillance, John Snow (1813–1858) linked data to intervention, and Alexander Langmuir (1910–1993) gave the first comprehensive definition of surveillance. Current theories, principles, and practice of public health surveillance are summarized. A number of surveillance dichotomies, such as epidemiologic surveillance versus public health surveillance, are described. Some future scenarios are presented, while current activities that can affect the future are summarized: exploring new frontiers; enhancing computer technology; improving epidemic investigations; improving data collection, analysis, dissemination, and use; building on lessons from the past; building capacity; enhancing global surveillance. It is concluded that learning from the past, reflecting on the present, and planning for the future can further enhance public health surveillance.

scholarly journals Clinical Microbiology Laboratories' Adoption of Culture-Independent Diagnostic Tests Is a Threat to Foodborne-Disease Surveillance in the United States

2016 ◽  
Vol 55 (1) ◽  
pp. 10-19 ◽  
Author(s):  
Shari Shea ◽  
Kristy A. Kubota ◽  
Hugh Maguire ◽  
Stephen Gladbach ◽  
Amy Woron ◽  
...  
Keyword(s):  
Public Health ◽  
Diagnostic Tests ◽  
Clinical Microbiology ◽  
Public Health Surveillance ◽  
The United States ◽  
Health Surveillance ◽  
Enteric Pathogens ◽  
Public Health Laboratory ◽  
Content Type ◽  
Culture Independent

INTRODUCTION In November 2015, the Centers for Disease Control and Prevention (CDC) sent a letter to state and territorial epidemiologists, state and territorial public health laboratory directors, and state and territorial health officials. In this letter, culture-independent diagnostic tests (CIDTs) for detection of enteric pathogens were characterized as “a serious and current threat to public health surveillance, particularly for Shiga toxin-producing Escherichia coli (STEC) and Salmonella .” The document says CDC and its public health partners are approaching this issue, in part, by “reviewing regulatory authority in public health agencies to require culture isolates or specimen submission if CIDTs are used.” Large-scale foodborne outbreaks are a continuing threat to public health, and tracking these outbreaks is an important tool in shortening them and developing strategies to prevent them. It is clear that the use of CIDTs for enteric pathogen detection, including both antigen detection and multiplex nucleic acid amplification techniques, is becoming more widespread. Furthermore, some clinical microbiology laboratories will resist the mandate to require submission of culture isolates, since it will likely not improve patient outcomes but may add significant costs. Specimen submission would be less expensive and time-consuming for clinical laboratories; however, this approach would be burdensome for public health laboratories, since those laboratories would need to perform culture isolation prior to typing. Shari Shea and Kristy Kubota from the Association of Public Health Laboratories, along with state public health laboratory officials from Colorado, Missouri, Tennessee, and Utah, will explain the public health laboratories' perspective on why having access to isolates of enteric pathogens is essential for public health surveillance, detection, and tracking of outbreaks and offer potential workable solutions which will allow them to do this. Marc Couturier of ARUP Laboratories and Melissa Miller of the University of North Carolina will explain the advantages of CIDTs for enteric pathogens and discuss practical solutions for clinical microbiology laboratories to address these public health needs.

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