BACKGROUND:Focused attention on Data to Care underlines the importance of high-quality HIV surveillance data. This study identified the number of total duplicate and exact duplicate HIV case records in 9 separate Enhanced HIV/AIDS Reporting System (eHARS) databases reported by 8 jurisdictions and compared this approach to traditional Routine Interstate Duplicate Review resolution.METHODS:This study used the ATra Black Box System and 6 eHARS variables for matching case records across jurisdictions: last name, first name, date of birth, sex assigned at birth (birth sex), social security number, and race/ethnicity, plus 4 system-calculated values (first name Soundex, last name Soundex, partial date of birth, and partial social security number).RESULTS:In approximately 11 hours, this study matched 290,482 cases from 799,326 uploaded records, including 55,460 exact case pairs. Top case pair overlaps were between NYC and NYS (51%), DC and MD (10%), and FL and NYC (6%), followed closely by FL and NYS (4%), FL and NC (3%), DC and VA (3%), and MD and VA (3%). Jurisdictions estimated that they realized a combined 135 labor hours in time efficiency by using this approach compared with manual methods previously used for interstate duplication resolution.DISCUSSION:This approach discovered exact matches that were not previously identified. It also decreased time spent resolving duplicated case records across jurisdictions while improving accuracy and completeness of HIV surveillance data in support of public health program policies. Future uses of this approach should consider standardized protocols for postprocessing eHARS data.

Interest in sustainable learning has been growing over the past 20 years but it has never been determined whether students—whose learning we are trying to sustain—can perceive either the sustainability of their learning or any of the features of this construct. A four-item survey was developed based on a published definition of “sustainable learning”, and was sent to the 12 graduate students who have completed a new seminar in ethical reasoning. A thematic analysis of the narrative responses was submitted to a degrees-of-freedom analysis to determine the level and type of evidence for student perception of sustainability. Respondents (n = 9) endorsed each of the four dimensions of sustainable learning—and each gave examples for each dimension outside of, and after the end of, the course. One respondent endorsed all dimensions of sustainable learning, but was uncertain whether the course itself led to one particular sustainability dimension. While these results must be considered preliminary because our sample is small and the survey is the first of its kind, they suggest that graduate students can and do perceive each of the four features of sustainability. The survey needs refinement for future/wider use; but this four-dimensional definition could be useful to develop and promote (and assess) sustainable learning in higher education.

A menacing context has emerged when a dread threat persists and requires a community to reorganize its life to help mitigate consequences of threat. This article explores how menacing context links drivers of forced migration, the perception of threat among local families and domestic decision-making about remaining in place, fleeing or combinations of both. Employing a coding scheme based on dread threat theory, this article illustrates through case studies of a cholera epidemic, total war setting and a complex situation with infectious disease, civil strife and drought threats how to transform qualitative data from ethnographic, autobiographical and journalistic sources into a quantitative measurement scale of local perception of threat for use in formal modelling, forecasting and potentially enhanced humanitarian responses to mass displacement.

Background The National HIV/AIDS Strategy calls for active surveillance programs for human immunodeficiency virus (HIV) to more accurately measure access to and retention in care across the HIV care continuum for persons living with HIV within their jurisdictions and to identify persons who may need public health services. However, traditional public health surveillance methods face substantial technological and privacy-related barriers to data sharing. Objective This study developed a novel data-sharing approach to improve the timeliness and quality of HIV surveillance data in three jurisdictions where persons may often travel across the borders of the District of Columbia, Maryland, and Virginia. Methods A deterministic algorithm of approximately 1000 lines was developed, including a person-matching system with Enhanced HIV/AIDS Reporting System (eHARS) variables. Person matching was defined in categories (from strongest to weakest): exact, very high, high, medium high, medium, medium low, low, and very low. The algorithm was verified using conventional component testing methods, manual code inspection, and comprehensive output file examination. Results were validated by jurisdictions using internal review processes. Results Of 161,343 uploaded eHARS records from District of Columbia (N=49,326), Maryland (N=66,200), and Virginia (N=45,817), a total of 21,472 persons were matched across jurisdictions over various strengths in a matching process totaling 21 minutes and 58 seconds in the privacy device, leaving 139,871 uniquely identified with only one jurisdiction. No records matched as medium low or low. Over 80% of the matches were identified as either exact or very high matches. Three separate validation methods were conducted for this study, and they all found ≥90% accuracy between records matched by this novel method and traditional matching methods. Conclusions This study illustrated a novel data-sharing approach that may facilitate timelier and better quality HIV surveillance data for public health action by reducing the effort needed for traditional person-matching reviews without compromising matching accuracy. Future analyses will examine the generalizability of these findings to other applications.

This book springs from a multidisciplinary, multi-organizational, and multi-sector conversation about the privacy and ethical implications of research in human affairs using big data. The need to cultivate and enlist the publics trust in the abilities of particular scientists and scientific institutions constitutes one of this books major themes. The advent of the Internet, the mass digitization of research information, and social media brought about, among many other things, the ability to harvest sometimes implicitly a wealth of human genomic, biological, behavioral, economic, political, and social data for the purposes of scientific research as well as commerce, government affairs, and social interaction. What type of ethical dilemmas did such changes generate? How should scientists collect, manipulate, and disseminate this information? The effects of this revolution and its ethical implications are wide-ranging. This book includes the opinions of myriad investigators, practitioners, and stakeholders in big data on human beings who also routinely reflect on the privacy and ethical issues of this phenomenon. Dedicated to the practice of ethical reasoning and reflection in action, the book offers a range of observations, lessons learned, reasoning tools, and suggestions for institutional practice to promote responsible big data research on human affairs. It caters to a broad audience of educators, researchers, and practitioners. Educators can use the volume in courses related to big data handling and processing. Researchers can use it for designing new methods of collecting, processing, and disseminating big data, whether in raw form or as analysis results. Lastly, practitioners can use it to steer future tools or procedures for handling big data. As this topic represents an area of great interest that still remains largely undeveloped, this book is sure to attract significant interest by filling an obvious gap in currently available literature.

Background: Effective treatment of HIV since 1996 has reduced morbidity and mortality through virologic suppression. Combination antiretroviral therapy (cART) has been recognized as key to the prevention of drug resistance and the transmission of infection. We used eighteen years of virologic outcomes in a long-standing cohort of women to describe longitudinal viral load trajectories; and examine factors associated with sustained viremia and mortality.Methods: We analyzed data from DC WIHS women with > four semiannual visits using a group-based logistic trajectory analysis approach to identify patterns of HIV RNA detection (> 80 copies/mL or lower assay limit, and > 1000 copies/mL). We verified findings using cumulative viral load suppression-years, explored group characteristics using generalized linear modeling with generalized estimating equations for repeated measures, and examined survival using the Kaplan-Meier and Cox proportional hazard analyses.Results: 329 women contributed 6633 visits between 1994 and 2012 and demonstrated high, moderate, and low probability patterns of HIV RNA detection (> 80 copies/mL) in 40.7, 35.6, and 23.7 % of participant visits, respectively. Analysis of cumulative years of viral load suppression supported these observations. Kaplan-Meier survival analysis demonstrated high mortality of 31.1 % with sustained viremia, but no significant difference in mortality between intermittent viremia and non-viremia patterns, 6.9 and 4.9 % respectively. Mortality was associated with higher age, lower CD4+ T lymphocyte count, and sustained viremia by Cox multivariate analysis.Conclusions: This ecologic study demonstrates the effectiveness of viral suppression, and conversely the association between viremia and mortality. In community delivery of cART for HIV care, distinct patterns of sustained viremia, intermittent viremia, and non-viremia were identified over nearly 18 years in the DC WIHS, capturing the dynamics and complexity of sustaining long-term HIV care. Persistent viremia was associated with lower CD4s and mortality, but surprisingly mortality was not different between continuous suppression and intermittent viremia. Classification of long-term virologic patterns such as these observed HIV treatment "careers" may provide a suitable framework to identify modifiable factors associated with treatment resilience and failure. Both individual and population interventions are needed to reduce transmission, prevent the emergence of drug resistance, and improve outcomes of community ART programs.

The use of Big Data—however the term is defined—involves a wide array of issues and stakeholders, thereby increasing numbers of complex decisions around issues including data acquisition, use, and sharing. Big Data is becoming a significant component of practice in an ever-increasing range of disciplines; however, since it is not a coherent “discipline” itself, specific codes of conduct for Big Data users and researchers do not exist. While many institutions have created, or will create, training opportunities (e.g., degree programs, workshops) to prepare people to work in and around Big Data, insufficient time, space, and thought have been dedicated to training these people to engage with the ethical, legal, and social issues in this new domain. Since Big Data practitioners come from, and work in, diverse contexts, neither a relevant professional code of conduct nor specific formal ethics training are likely to be readily available. This normative paper describes an approach to conceptualizing ethical reasoning and integrating it into training for Big Data use and research. Our approach is based on a published framework that emphasizes ethical reasoning rather than topical knowledge. We describe the formation of professional community norms from two key disciplines that contribute to the emergent field of Big Data: computer science and statistics. Historical analogies from these professions suggest strategies for introducing trainees and orienting practitioners both to ethical reasoning and to a code of professional conduct itself. We include two semester course syllabi to strengthen our thesis that codes of conduct (including and beyond those we describe) can be harnessed to support the development of ethical reasoning in, and a sense of professional identity among, Big Data practitioners.

This paper describes initial efforts to use open-source data to capture knowledge about forced migration in Iraq. Our goal is to understand the connection between open-source data and possible leading indicators of forced migration. For our preliminary analyses, we use a corpus of 2.6 million documents. Here we describe the techniques we used and challenges we faced. We conclude with recommendations for those using open-source data for grand-scale data science challenges.

Biosurveillance entails the collection and analysis of information needed to provide early warning of outbreaks of infectious disease, both naturally occurring and intentionally introduced. Data derived from repositories containing various types of sensitive information may be required for this purpose, including individually identifiable, copyrighted, and proprietary information. The Project Argus Biosurveillance Doctrine was developed to ensure that ethical and legal principles guide the collection and handling of such information. Project Argus does not, however, use individually identifiable information or any material derived from individually identifiable information for any phase of the project. Further, Project Argus is not used for purposes of law enforcement, counterterrorism, or public health surveillance. This chapter details why and how the doctrine was developed and summarizes its guiding principles and key elements.

American AnthropologistVolume 113, Issue 3 p. 515-516 Aboriginal Business: Alliances in a Remote Australian Town by Kimberly Christen BOOK REVIEWSSingle Book Reviews Jeff Collmann, Jeff Collmann Georgetown UniversitySearch for more papers by this author Jeff Collmann, Jeff Collmann Georgetown UniversitySearch for more papers by this author First published: 24 August 2011 https://doi.org/10.1111/j.1548-1433.2011.01365_5.xRead the full textAboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume113, Issue3September 2011Pages 515-516 RelatedInformation

The new science of genomics endeavors to chart the genomes of individuals around the world, with the dual goals of understanding the role genetic factors play in human health and solving problems of disease and disability. From the perspective of indigenous peoples and developing countries, the promises and perils of genomic science appear against a backdrop of global health disparity and political vulnerability. These conditions pose a dilemma for many communities when attempting to decide about participating in genomic research or any other biomedical research. Genomic research offers the possibility of improved technologies for managing the acute and chronic diseases that plague their members. Yet, the history of particularly biomedical research among people in indigenous and developing nations offers salient examples of unethical practice, misuse of data, and failed promises. This dilemma creates risks for communities who decide either to participate or not to participate in genomic science research. Some argue that the history of poor scientific practice justifies refusal to join genomic research projects. Others argue that disease poses such great threats to the well-being of people in indigenous communities and developing nations that not participating in genomic research risks irrevocable harm. Thus, some communities particularly among indigenous peoples have declined to participate as subjects in genomic research. At the same time, some communities have begun developing new guidelines, procedures, and practices for engaging with the scientific community that offer opportunities to bridge the gap between genomic science and indigenous and/or developing communities. Four new approaches warrant special attention and further support: consulting with local communities; negotiating the complexities of consent; training members of local communities in science and health care; and training scientists to work with indigenous communities. Implicit is a new definition of "rigorous scientific research," one that includes both community development and scientific progress as legitimate objectives of genomic research. Innovative translational research is needed to develop practical, mutually acceptable methods for crossing the divide between genomic researchers and indigenous communities. This may mean the difference between success and failure in genomic science, and in improving health for all peoples.

Drawing upon an extensive search of publically available literature and discussions at the "National Forum on the Future of the Defense Health Information System," this article documents the evolving mission and political context of the longitudinal health record (LHR) as an instrument for Force Health Protection (FHP). Because of the Gulf War syndrome controversy, the Department of Defense (DoD) launched an ambitious, complex series of programs designed to create a comprehensive, integrated defense health surveillance capability to assure FHP and keep faith with the American people. This "system of systems" includes individual component systems to perform specific functions such as disease surveillance, battlefield assessment, and patient care and consolidates these diverse types of information into centrally accessible archives that serve the interests of occupational health, preventive medicine, medical strategic planning, and longitudinal patient health care. After 25 years of effort and major accomplishments, progress toward a LHR remains uneven and controversy persists.

The privacy and security rules of the Health Insurance Portability and Accountability Act (HIPAA) of 1996 emphasize taking steps for protecting protected health information from unauthorized access and modification. Nonetheless, even organizations highly skilled in data security that comply with regulations and all good practices will suffer and must respond to breaches. This paper reports on a case study in responding to an important breach of the confidentiality and integrity of identifiable patient information of the Kaiser Internet Patient Portal known as “Kaiser Permanente Online” (KP Online). From the perspective of theories about highly reliable organizations, effective health information security programs must respond resiliently to as well as prospectively anticipate security breaches.

We are witnessing a dramatic increase in the use of complex technological systems for better management and exploitation of abundant data from different sources. The Imaging Science and Information Systems (ISIS) Center, a medical research center at Georgetown University is an agile organization that is subject to fast changing requirements and new application deployments. ISIS requires an agile, secure IT infrastructure based on network management best practices that enables rapid business implementations, accommodates innovative deployments and applications, and supports its business plan. Adapting emerging technologies can facilitate communication, productivity and access but, also entails higher security risks, more assets to manage and increased requirements for compliance with established standards and security rules. In this paper we will describe the approaches we took to build and secure an IT infrastructure at the ISIS Center that enables researchers, collaborators, vendors and contractors to work in an environment that hosts systems for different purposes with no compromise to security and data confidentiality.