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1.  The Role of the Toxicologic Pathologist in the Post-Genomic Era# 
Journal of Toxicologic Pathology  2013;26(2):105-110.
An era can be defined as a period in time identified by distinctive character, events, or practices. We are now in the genomic era. The pre-genomic era: There was a pre-genomic era. It started many years ago with novel and seminal animal experiments, primarily directed at studying cancer. It is marked by the development of the two-year rodent cancer bioassay and the ultimate realization that alternative approaches and short-term animal models were needed to replace this resource-intensive and time-consuming method for predicting human health risk. Many alternatives approaches and short-term animal models were proposed and tried but, to date, none have completely replaced our dependence upon the two-year rodent bioassay. However, the alternative approaches and models themselves have made tangible contributions to basic research, clinical medicine and to our understanding of cancer and they remain useful tools to address hypothesis-driven research questions. The pre-genomic era was a time when toxicologic pathologists played a major role in drug development, evaluating the cancer bioassay and the associated dose-setting toxicity studies, and exploring the utility of proposed alternative animal models. It was a time when there was shortage of qualified toxicologic pathologists. The genomic era: We are in the genomic era. It is a time when the genetic underpinnings of normal biological and pathologic processes are being discovered and documented. It is a time for sequencing entire genomes and deliberately silencing relevant segments of the mouse genome to see what each segment controls and if that silencing leads to increased susceptibility to disease. What remains to be charted in this genomic era is the complex interaction of genes, gene segments, post-translational modifications of encoded proteins, and environmental factors that affect genomic expression. In this current genomic era, the toxicologic pathologist has had to make room for a growing population of molecular biologists. In this present era newly emerging DVM and MD scientists enter the work arena with a PhD in pathology often based on some aspect of molecular biology or molecular pathology research. In molecular biology, the almost daily technological advances require one’s complete dedication to remain at the cutting edge of the science. Similarly, the practice of toxicologic pathology, like other morphological disciplines, is based largely on experience and requires dedicated daily examination of pathology material to maintain a well-trained eye capable of distilling specific information from stained tissue slides - a dedicated effort that cannot be well done as an intermezzo between other tasks. It is a rare individual that has true expertise in both molecular biology and pathology. In this genomic era, the newly emerging DVM-PhD or MD-PhD pathologist enters a marketplace without many job opportunities in contrast to the pre-genomic era. Many face an identity crisis needing to decide to become a competent pathologist or, alternatively, to become a competent molecular biologist. At the same time, more PhD molecular biologists without training in pathology are members of the research teams working in drug development and toxicology. How best can the toxicologic pathologist interact in the contemporary team approach in drug development, toxicology research and safety testing? Based on their biomedical training, toxicologic pathologists are in an ideal position to link data from the emerging technologies with their knowledge of pathobiology and toxicology. To enable this linkage and obtain the synergy it provides, the bench-level, slide-reading expert pathologist will need to have some basic understanding and appreciation of molecular biology methods and tools. On the other hand, it is not likely that the typical molecular biologist could competently evaluate and diagnose stained tissue slides from a toxicology study or a cancer bioassay. The post-genomic era: The post-genomic era will likely arrive approximately around 2050 at which time entire genomes from multiple species will exist in massive databases, data from thousands of robotic high throughput chemical screenings will exist in other databases, genetic toxicity and chemical structure-activity-relationships will reside in yet other databases. All databases will be linked and relevant information will be extracted and analyzed by appropriate algorithms following input of the latest molecular, submolecular, genetic, experimental, pathology and clinical data. Knowledge gained will permit the genetic components of many diseases to be amenable to therapeutic prevention and/or intervention. Much like computerized algorithms are currently used to forecast weather or to predict political elections, computerized sophisticated algorithms based largely on scientific data mining will categorize new drugs and chemicals relative to their health benefits versus their health risks for defined human populations and subpopulations. However, this form of a virtual toxicity study or cancer bioassay will only identify probabilities of adverse consequences from interaction of particular environmental and/or chemical/drug exposure(s) with specific genomic variables. Proof in many situations will require confirmation in intact in vivo mammalian animal models. The toxicologic pathologist in the post-genomic era will be the best suited scientist to confirm the data mining and its probability predictions for safety or adverse consequences with the actual tissue morphological features in test species that define specific test agent pathobiology and human health risk.
doi:10.1293/tox.26.105
PMCID: PMC3695332  PMID: 23914052
genomic era; history of toxicologic pathology; molecular biology
2.  “Working the System”—British American Tobacco's Influence on the European Union Treaty and Its Implications for Policy: An Analysis of Internal Tobacco Industry Documents 
PLoS Medicine  2010;7(1):e1000202.
Katherine Smith and colleagues investigate the ways in which British American Tobacco influenced the European Union Treaty so that new EU policies advance the interests of major corporations, including those that produce products damaging to health.
Background
Impact assessment (IA) of all major European Union (EU) policies is now mandatory. The form of IA used has been criticised for favouring corporate interests by overemphasising economic impacts and failing to adequately assess health impacts. Our study sought to assess how, why, and in what ways corporations, and particularly the tobacco industry, influenced the EU's approach to IA.
Methods and Findings
In order to identify whether industry played a role in promoting this system of IA within the EU, we analysed internal documents from British American Tobacco (BAT) that were disclosed following a series of litigation cases in the United States. We combined this analysis with one of related literature and interviews with key informants. Our analysis demonstrates that from 1995 onwards BAT actively worked with other corporate actors to successfully promote a business-oriented form of IA that favoured large corporations. It appears that BAT favoured this form of IA because it could advance the company's European interests by establishing ground rules for policymaking that would: (i) provide an economic framework for evaluating all policy decisions, implicitly prioritising costs to businesses; (ii) secure early corporate involvement in policy discussions; (iii) bestow the corporate sector with a long-term advantage over other actors by increasing policymakers' dependence on information they supplied; and (iv) provide businesses with a persuasive means of challenging potential and existing legislation. The data reveal that an ensuing lobbying campaign, largely driven by BAT, helped secure binding changes to the EU Treaty via the Treaty of Amsterdam that required EU policymakers to minimise legislative burdens on businesses. Efforts subsequently focused on ensuring that these Treaty changes were translated into the application of a business orientated form of IA (cost–benefit analysis [CBA]) within EU policymaking procedures. Both the tobacco and chemical industries have since employed IA in apparent attempts to undermine key aspects of European policies designed to protect public health.
Conclusions
Our findings suggest that BAT and its corporate allies have fundamentally altered the way in which all EU policy is made by making a business-oriented form of IA mandatory. This increases the likelihood that the EU will produce policies that advance the interests of major corporations, including those that produce products damaging to health, rather than in the interests of its citizens. Given that the public health community, focusing on health IA, has largely welcomed the increasing policy interest in IA, this suggests that urgent consideration is required of the ways in which IA can be employed to undermine, as well as support, effective public health policies.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
The primary goal of public health, the branch of medicine concerned with the health of communities, is to improve lives by preventing disease. Public-health groups do this by assessing and monitoring the health of communities, by ensuring that populations have access to appropriate and cost-effective health care, and by helping to formulate public policies that safeguard human health. Until recently, most of the world's major public-health concerns related to infectious diseases. Nowadays, however, many major public-health concerns are linked to the goods made and marketed by large corporations such as fast food, alcohol, tobacco, and chemicals. In Europe, these corporations are regulated by policies drawn up both by member states and by the European Commission, the executive organ of the European Union (EU; an economic and political partnership among 27 democratic European countries). Thus, for example, the tobacco industry, which is widely recognized as a driver of the smoking epidemic, is regulated by Europe-wide tobacco control policies and member state level policies.
Why Was This Study Done?
Since 1997, the European Commission has been required by law to assess the economic, social (including health), and environmental consequences of new policy initiatives using a process called an “impact assessment” (IA). Because different types of IA examine the likely effects of policies on different aspects of daily life—a health impact assessment, for example, focuses on a policy's effect on health—the choice of IA can lead to different decisions being taken about new policies. Although the IA tool adopted by the European Commission aims to assess economic, environmental and social impacts, independent experts suggest this tool does not adequately assess health impacts. Instead, economic impacts receive the most attention, a situation that may favour the interests of large businesses. In this study, the researchers seek to identify how and why the EU's approach to IA developed. More specifically, the researchers analyze internal documents from British American Tobacco (BAT), which have been disclosed because of US litigation cases, to find out whether industry has played a role in promoting the EU's system of IA.
What Did the Researchers Do and Find?
The researchers analyzed 714 BAT internal documents (identified by searching the Legacy Tobacco Documents Library, which contains more than 10 million internal tobacco company documents) that concerned attempts made by BAT to influence regulatory reforms in Europe. They also analyzed related literature from other sources (for example, academic publications) and interviewed 16 relevant people (including people who had worked at the European Commission). This analysis shows that from 1995, BAT worked with other businesses to promote European regulatory reforms (in particular, the establishment of a business-orientated form of IA) that favor large corporations. A lobbying campaign, initiated by BAT but involving a “policy network” of other companies, first helped to secure binding changes to the EU Treaty that require policymakers to minimize legislative burdens on businesses. The analysis shows that after achieving this goal, which BAT described as an “important victory,” further lobbying ensured that these treaty changes were translated into the implementation of a business-orientated form of IA within the EU. Both the tobacco industry and the chemical industry, the researchers argue, have since used the IA to delay and/or weaken EU legislation intended to protect public health.
What Do These Findings Mean?
These findings suggest that BAT and its corporate allies have fundamentally altered the way in which EU policy is made by ensuring that all significant EU policy decisions have to be assessed using a business-orientated IA. As the authors note, this situation increases the likelihood that the EU will produce policies that favor big business rather than the health of its citizens. Furthermore, these findings suggest that by establishing a network of other industries to help in lobbying for EU Treaty changes, BAT was able to distance itself from the push to establish a business-orientated IA to the extent that Commission officials were unaware of the involvement of the tobacco industry in campaigns for IA. Thus, in future, to safeguard public health, policymakers and public-health groups must pay more attention to corporate efforts to shape decision-making processes. In addition, public-health groups must take account of the ways in which IA can be used to undermine as well as support effective public-health policies and they must collaborate more closely in their efforts to ensure effective national and international policy.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/0.1371/journal.pmed.1000202.
Wikipedia has a page on public health (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
More information on the European Union (in several languages), on public health in the European Union, and on impact assessment by the European Commission is available
The Legacy Tobacco Documents Library is a public, searchable database of tobacco company internal documents detailing their advertising, manufacturing, marketing, sales, and scientific activities
The World Health Organization provides information about the dangers of tobacco (in several languages)
The Smoke Free Partnership contains more information about smoking prevalence in Europe and about European policies to tackle the public health issues associated with tobacco use
For more information about tobacco industry influence on policy see the 2009 World Health Organization report on tobacco industry interference with tobacco control
doi:10.1371/journal.pmed.1000202
PMCID: PMC2797088  PMID: 20084098
3.  e-Health, m-Health and healthier social media reform: the big scale view 
Introduction
In the upcoming decade, digital platforms will be the backbone of a strategic revolution in the way medical services are provided, affecting both healthcare providers and patients. Digital-based patient-centered healthcare services allow patients to actively participate in managing their own care, in times of health as well as illness, using personally tailored interactive tools. Such empowerment is expected to increase patients’ willingness to adopt actions and lifestyles that promote health as well as improve follow-up and compliance with treatment in cases of chronic illness. Clalit Health Services (CHS) is the largest HMO in Israel and second largest world-wide. Through its 14 hospitals, 1300 primary and specialized clinics, and 650 pharmacies, CHS provides comprehensive medical care to the majority of Israel’s population (above 4 million members). CHS e-Health wing focuses on deepening patient involvement in managing health, through personalized digital interactive tools. Currently, CHS e-Health wing provides e-health services for 1.56 million unique patients monthly with 2.4 million interactions every month (August 2011). Successful implementation of e-Health solutions is not a sum of technology, innovation and health; rather it’s the expertise of tailoring knowledge and leadership capabilities in multidisciplinary areas: clinical, ethical, psychological, legal, comprehension of patient and medical team engagement etc. The Google Health case excellently demonstrates this point. On the other hand, our success with CHS is a demonstration that e-Health can be enrolled effectively and fast with huge benefits for both patients and medical teams, and with a robust business model.
CHS e-Health core components
They include:
1. The personal health record layer (what the patient can see) presents patients with their own medical history as well as the medical history of their preadult children, including diagnoses, allergies, vaccinations, laboratory results with interpretations in layman’s terms, medications with clear, straightforward explanations regarding dosing instructions, important side effects, contraindications, such as lactation etc., and other important medical information. All personal e-Health services require identification and authorization.
2. The personal knowledge layer (what the patient should know) presents patients with personally tailored recommendations for preventative medicine and health promotion. For example, diabetic patients are push notified regarding their yearly eye exam. The various health recommendations include: occult blood testing, mammography, lipid profile etc. Each recommendation contains textual, visual and interactive content components in order to promote engagement and motivate the patient to actually change his health behaviour.
3. The personal health services layer (what the patient can do) enables patients to schedule clinic visits, order chronic prescriptions, e-consult their physician via secured e-mail, set SMS medication reminders, e-consult a pharmacist regarding personal medications. Consultants’ answers are sent securely to the patients’ personal mobile device.
On December 2009 CHS launched secured, web based, synchronous medical consultation via video conference. Currently 11,780 e-visits are performed monthly (May 2011). The medical encounter includes e-prescription and referral capabilities which are biometrically signed by the physician. On December 2010 CHS launched a unique mobile health platform, which is one of the most comprehensive personal m-Health applications world-wide. An essential advantage of mobile devices is their potential to bridge the digital divide. Currently, CHS m-Health platform is used by more than 45,000 unique users, with 75,000 laboratory results views/month, 1100 m-consultations/month and 9000 physician visit scheduling/month.
4. The Bio-Sensing layer (what physiological data the patient can populate) includes diagnostic means that allow remote physical examination, bio-sensors that broadcast various physiological measurements, and smart homecare devices, such as e-Pill boxes that gives seniors, patients and their caregivers the ability to stay at home and live life to its fullest. Monitored data is automatically transmitted to the patient’s Personal Health Record and to relevant medical personnel.
The monitoring layer is embedded in the chronic disease management platform, and in the interactive health promotion and wellness platform. It includes tailoring of consumer-oriented medical devices and service provided by various professional personnel—physicians, nurses, pharmacists, dieticians and more.
5. The Social layer (what the patient can share). Social media networks triggered an essential change at the humanity ‘genome’ level, yet to be further defined in the upcoming years. Social media has huge potential in promoting health as it combines fun, simple yet extraordinary user experience, and bio-social-feedback. There are two major challenges in leveraging health care through social networks:
a. Our personal health information is the cornerstone for personalizing healthier lifestyle, disease management and preventative medicine. We naturally see our personal health data as a super-private territory. So, how do we bring the power of our private health information, currently locked within our Personal Health Record, into social media networks without offending basic privacy issues?
b. Disease management and preventive medicine are currently neither considered ‘cool’ nor ‘fun’ or ‘potentially highly viral’ activities; yet, health is a major issue of everybody’s life. It seems like we are missing a crucial element with a huge potential in health behavioural change—the Fun Theory. Social media platforms comprehends user experience tools that potentially could break current misconception, and engage people in the daily task of taking better care of themselves.
CHS e-Health innovation team characterized several break-through applications in this unexplored territory within social media networks, fusing personal health and social media platforms without offending privacy. One of the most crucial issues regarding adoption of e-health and m-health platforms is change management. Being a ‘hot’ innovative ‘gadget’ is far from sufficient for changing health behaviours at the individual and population levels.
CHS health behaviour change management methodology includes 4 core elements:
1. Engaging two completely different populations: patients, and medical teams. e-Health applications must present true added value for both medical teams and patients, engaging them through understanding and assimilating “what’s really in it for me”. Medical teams are further subdivided into physicians, nurses, pharmacists and administrative personnel—each with their own driving incentive. Resistance to change is an obstacle in many fields but it is particularly true in the conservative health industry. To successfully manage a large scale persuasive process, we treat intra-organizational human resources as “Change Agents”. Harnessing the persuasive power of ~40,000 employees requires engaging them as the primary target group. Successful recruitment has the potential of converting each patient-medical team interaction into an exposure opportunity to the new era of participatory medicine via e-health and m-health channels.
2. Implementation waves: every group of digital health products that are released at the same time are seen as one project. Each implementation wave leverages the focus of the organization and target populations to a defined time span. There are three major and three minor implementation waves a year.
3. Change-Support Arrow: a structured infrastructure for every implementation wave. The sub-stages in this strategy include:
Cross organizational mapping and identification of early adopters and stakeholders relevant to the implementation wave
Mapping positive or negative perceptions and designing specific marketing approaches for the distinct target groups
Intra and extra organizational marketing
Conducting intensive training and presentation sessions for groups of implementers
Running conflict-prevention activities, such as advanced tackling of potential union resistance
Training change-agents with resistance-management behavioural techniques, focused intervention for specific incidents and for key opinion leaders
Extensive presence in the clinics during the launch period, etc.
The entire process is monitored and managed continuously by a review team.
4. Closing Phase: each wave is analyzed and a “lessons-learned” session concludes the changes required in the modus operandi of the e-health project team.
PMCID: PMC3571141
e-Health; mobile health; personal health record; online visit; patient empowerment; knowledge prescription
4.  Bridging the Communication Divide: A Role for Health Psychology in the Genomic Era 
The application of genomics to population health has the potential to revolutionize the practice of medicine. Indeed, discoveries into the genomic basis of cancer and other common chronic diseases have resulted in new and improved predictive tests for identifying individuals at increased risk for these conditions and long before their onset occurs. When used properly, information gained from predictive genomic tests can be combined with other leading indicators (e.g., environmental and behavioral risk factors) to inform medical management decisions, preventive health practices, and risk-reducing strategies. However, genomics remains an emerging science and the translation of genomic discoveries into improved population health management remains elusive. There are divides in the translational science continuum at several junctures, and many of these divides could be narrowed or closed with additional data. For example, we know relatively little about how to effectively communicate with the public about the complex interplay among genomics, behavior, and health. Moreover, there is a need to develop better methods of counseling and educating the public in light of newly emerging knowledge about the genomic basis of health and disease. We assert that the discipline of psychology, and health psychology in particular, is well-poised to continue to make significant contributions to this growing area of science and practice. Through a focus on health-related social and behavioral research, psychology can lead the way in overcoming divides in communication, understanding, and action about genomics for the betterment of both individual and public health practices.
doi:10.1037/a0028971
PMCID: PMC3595505  PMID: 23503693
genetics; genomics; communication; health; behavior
5.  A Niche for Infectious Disease in Environmental Health: Rethinking the Toxicological Paradigm 
Environmental Health Perspectives  2010;118(8):1165-1172.
Objective
In this review we highlight the need to expand the scope of environmental health research, which now focuses largely on the study of toxicants, to incorporate infectious agents. We provide evidence that environmental health research would be strengthened through finding common ground with the tools and approaches of infectious disease research.
Data sources and extraction
We conducted a literature review for examples of interactions between toxic agents and infectious diseases, as well as the role of these interactions as risk factors in classic “environmental” diseases. We investigated existing funding sources and research mandates in the United States from the National Science Foundation and the National Institutes of Health, particularly the National Institute of Environmental Health Sciences.
Data synthesis
We adapted the toxicological paradigm to guide reintegration of infectious disease into environmental health research and to identify common ground between these two fields as well as opportunities for improving public health through interdisciplinary research.
Conclusions
Environmental health encompasses complex disease processes, many of which involve interactions among multiple risk factors, including toxicant exposures, pathogens, and susceptibility. Funding and program mandates for environmental health studies should be expanded to include pathogens in order to capture the true scope of these overlapping risks, thus creating more effective research investments with greater relevance to the complexity of real-world exposures and multifactorial health outcomes. We propose a new model that integrates the toxicology and infectious disease paradigms to facilitate improved collaboration and communication by providing a framework for interdisciplinary research. Pathogens should be part of environmental health research planning and funding allocation, as well as applications such as surveillance and policy development.
doi:10.1289/ehp.0901866
PMCID: PMC2920090  PMID: 20385515
biomarkers; colon cancer; conceptual framework; environmental health; infectious disease; liver cancer; NIEHS; pathogens; toxicology
6.  Disease Surveillance and Achieving Synergy In Public Health Quality Improvement 
Objective
To examine disease surveillance in the context of a new national framework for public health quality and to solicit input from practitioners, researchers, and other stakeholders to identify potential metrics, pivotal research questions, and actions for achieving synergy between surveillance practice and public health quality.
Introduction
National efforts to improve quality in public health are closely tied to advancing capabilities in disease surveillance. Measures of public health quality provide data to demonstrate how public health programs, services, policies, and research achieve desired health outcomes and impact population health. They also reveal opportunities for innovations and improvements. Similar quality improvement efforts in the health care system are beginning to bear fruit. There has been a need, however, for a framework for assessing public health quality that provides a standard, yet is flexible and relevant to agencies at all levels.
The U.S. Health and Human Services (HHS) Office of the Assistant Secretary for Health, working with stakeholders, recently developed and released a Consensus Statement on Quality in the Public Health System that introduces a novel evaluation framework. They identified nine aims that are fundamental to public health quality improvement efforts and six cross-cutting priority areas for improvement, including population health metrics and information technology; workforce development; and evidence-based practices (1).
Applying the HHS framework to surveillance expands measures for surveillance quality beyond typical variables (e.g., data quality and analytic capabilities) to desired characteristics of a quality public health system. The question becomes: How can disease surveillance help public health services to be more population centered, equitable, proactive, health-promoting, risk-reducing, vigilant, transparent, effective, and efficient—the desired features of a quality public health system?
Any agency with a public health mission, or even a partial public health mission (e.g., tax-exempt hospitals), can use these measures to develop strategies that improve both the quality of the surveillance enterprise and public health systems, overall. At this time, input from stakeholders is needed to identify valid and feasible ways to measure how surveillance systems and practices advance public health quality. What exists now and where are the gaps?
Methods
Improving public health by applying quality measures to disease surveillance will require innovation and collaboration among stakeholders. This roundtable will begin a community dialogue to spark this process. The first goal will be to achieve a common focus by defining the nine quality aims identified in the HHS Consensus Statement. Attendees will draw from their experience to discuss how surveillance practice advances the public health aims and improves public health. We will also identify key research questions needed to provide evidence to inform decision-making.
Results
The roundtable will discuss how the current state of surveillance practice addresses each of the aims described in the Consensus Statement to create a snapshot of how surveillance contributes to public health quality and begin to articulate practical measures for assessing quality improvements. Sample questions to catalyze discussion include: —How is surveillance used to identify and address health disparities and, thereby, make public health more equitable? What are the data sources? Are there targets? How can research and evaluation help to enhance this surveillance capability and direct action?—How do we identify and address factors that inhibit quality improvement in surveillance? What are the gaps in knowledge, skills, systems, and resources?—Where can standardization play a positive role in the evaluation of quality in public health surveillance?—How can we leverage resources by aligning national, state, and local goals? —What are the key research questions and the quality improvement projects that can be implemented using recognized models for improvement?—How can syndromic surveillance, specifically, advance the priority aims?
The roundtable will conclude with a list of next steps to develop metrics that resonate with the business practices of public health at all levels.
PMCID: PMC3692848
public health quality; metrics; framework
7.  The Effectiveness of Mobile-Health Technology-Based Health Behaviour Change or Disease Management Interventions for Health Care Consumers: A Systematic Review 
PLoS Medicine  2013;10(1):e1001362.
Caroline Free and colleagues systematically review a fast-moving field, that of the effectiveness of mobile technology interventions delivered to healthcare consumers, and conclude that high-quality, adequately powered trials of optimized interventions are required to evaluate effects on objective outcomes.
Background
Mobile technologies could be a powerful media for providing individual level support to health care consumers. We conducted a systematic review to assess the effectiveness of mobile technology interventions delivered to health care consumers.
Methods and Findings
We searched for all controlled trials of mobile technology-based health interventions delivered to health care consumers using MEDLINE, EMBASE, PsycINFO, Global Health, Web of Science, Cochrane Library, UK NHS HTA (Jan 1990–Sept 2010). Two authors extracted data on allocation concealment, allocation sequence, blinding, completeness of follow-up, and measures of effect. We calculated effect estimates and used random effects meta-analysis. We identified 75 trials. Fifty-nine trials investigated the use of mobile technologies to improve disease management and 26 trials investigated their use to change health behaviours. Nearly all trials were conducted in high-income countries. Four trials had a low risk of bias. Two trials of disease management had low risk of bias; in one, antiretroviral (ART) adherence, use of text messages reduced high viral load (>400 copies), with a relative risk (RR) of 0.85 (95% CI 0.72–0.99), but no statistically significant benefit on mortality (RR 0.79 [95% CI 0.47–1.32]). In a second, a PDA based intervention increased scores for perceived self care agency in lung transplant patients. Two trials of health behaviour management had low risk of bias. The pooled effect of text messaging smoking cessation support on biochemically verified smoking cessation was (RR 2.16 [95% CI 1.77–2.62]). Interventions for other conditions showed suggestive benefits in some cases, but the results were not consistent. No evidence of publication bias was demonstrated on visual or statistical examination of the funnel plots for either disease management or health behaviours. To address the limitation of the older search, we also reviewed more recent literature.
Conclusions
Text messaging interventions increased adherence to ART and smoking cessation and should be considered for inclusion in services. Although there is suggestive evidence of benefit in some other areas, high quality adequately powered trials of optimised interventions are required to evaluate effects on objective outcomes.
Please see later in the article for the Editors' Summary
Editors’ Summary
Background
Every year, millions of people die from cardiovascular diseases (diseases of the heart and circulation), chronic obstructive pulmonary disease (a long-term lung disease), lung cancer, HIV infection, and diabetes. These diseases are increasingly important causes of mortality (death) in low- and middle-income countries and are responsible for nearly 40% of deaths in high-income countries. For all these diseases, individuals can adopt healthy behaviors that help prevent disease onset. For example, people can lower their risk of diabetes and cardiovascular disease by maintaining a healthy body weight, and, if they are smokers, they can reduce their risk of lung cancer and cardiovascular disease by giving up cigarettes. In addition, optimal treatment of existing diseases can reduce mortality and morbidity (illness). Thus, in people who are infected with HIV, antiretroviral therapy delays the progression of HIV infection and the onset of AIDS, and in people who have diabetes, good blood sugar control can prevent retinopathy (a type of blindness) and other serious complications of diabetes.
Why Was This Study Done?
Health-care providers need effective ways to encourage "health-care consumers" to make healthy lifestyle choices and to self-manage chronic diseases. The amount of information, encouragement and support that can be conveyed to individuals during face-to-face consultations or through traditional media such as leaflets is limited, but mobile technologies such as mobile phones and portable computers have the potential to transform the delivery of health messages. These increasingly popular technologies—more than two-thirds of the world's population now owns a mobile phone—can be used to deliver health messages to people anywhere and at the most relevant times. For example, smokers trying to quit smoking can be sent regular text messages to sustain their motivation, but can also use text messaging to request extra support when it is needed. But is "mHealth," the provision of health-related services using mobile communication technology, an effective way to deliver health messages to health-care consumers? In this systematic review (a study that uses predefined criteria to identify all the research on a given topic), the researchers assess the effectiveness of mobile technology-based health behavior change interventions and disease management interventions delivered to health-care consumers.
What Did the Researchers Do and Find?
The researchers identified 75 controlled trials (studies that compare the outcomes of people who do and do not receive an intervention) of mobile technology-based health interventions delivered to health-care consumers that met their predefined criteria. Twenty-six trials investigated the use of mobile technologies to change health behaviors, 59 investigated their use in disease management, most were of low quality, and nearly all were undertaken in high-income countries. In one high-quality trial that used text messages to improve adherence to antiretroviral therapy among HIV-positive patients in Kenya, the intervention significantly reduced the patients’ viral load but did not significantly reduce mortality (the observed reduction in deaths may have happened by chance). In two high-quality UK trials, a smoking intervention based on text messaging (txt2stop) more than doubled biochemically verified smoking cessation. Other lower-quality trials indicated that using text messages to encourage physical activity improved diabetes control but had no effect on body weight. Combined diet and physical activity text messaging interventions also had no effect on weight, whereas interventions for other conditions showed suggestive benefits in some but not all cases.
What Do These Findings Mean?
These findings provide mixed evidence for the effectiveness of health intervention delivery to health-care consumers using mobile technologies. Moreover, they highlight the need for additional high-quality controlled trials of this mHealth application, particularly in low- and middle-income countries. Specifically, the demonstration that text messaging interventions increased adherence to antiretroviral therapy in a low-income setting and increased smoking cessation in a high-income setting provides some support for the inclusion of these two interventions in health-care services in similar settings. However, the effects of these two interventions need to be established in other settings and their cost-effectiveness needs to be measured before they are widely implemented. Finally, for other mobile technology–based interventions designed to change health behaviors or to improve self-management of chronic diseases, the results of this systematic review suggest that the interventions need to be optimized before further trials are undertaken to establish their clinical benefits.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001362.
A related PLOS Medicine Research Article by Free et al. investigates the ability of mHealth technologies to improve health-care service delivery processes
Wikipedia has a page on mHealth (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
mHealth: New horizons for health through mobile technologies is a global survey of mHealth prepared by the World Health Organization’s Global Observatory for eHealth (eHealth is health-care practice supported by electronic processes and communication)
The mHealth in Low-Resource Settings website, which is maintained by the Netherlands Royal Tropical Institute, provides information on the current use, potential, and limitations of mHealth in low-resource settings
More information about Txt2stop is available, the UK National Health Service Choices website provides an analysis of the Txt2stop trial and what its results mean, and the UK National Health Service Smokefree website provides a link to a Quit App for the iPhone
The US Centers for Disease Control and Prevention has launched a text messaging service that delivers regular health tips and alerts to mobile phones
doi:10.1371/journal.pmed.1001362
PMCID: PMC3548655  PMID: 23349621
8.  Are public health professionals prepared for public health genomics? A cross-sectional survey in Italy 
Background
Public health genomics is an emerging multidisciplinary approach, which aims to integrate genome-based knowledge in a responsible and effective way into public health. Despite several surveys performed to evaluate knowledge, attitudes and professional behaviors of physicians towards predictive genetic testing, similar surveys have not been carried out for public health practitioners. This study is the first to assess knowledge, attitudes and training needs of public health professionals in the field of predictive genetic testing for chronic diseases.
Methods
A self-administered questionnaire was used to carry out a cross-sectional survey of a random sample of Italian public health professionals.
Results
A response rate of 67.4% (797 questionnaires) was achieved. Italian public health professionals have the necessary attitudinal background to contribute to the proper use of predictive genetic testing for chronic diseases, but they need additional training to increase their methodological knowledge. Knowledge significantly increases with exposure to predictive genetic testing during postgraduate training (odds ratio (OR) = 1.74, 95% confidence interval (CI) = 1.05–2.88), time dedicated to continuing medical education (OR = 1.53, 95% CI = 1.14–2.04) and level of English language knowledge (OR = 1.36, 95% CI = 1.07–1.72). Adequate knowledge is the strongest predictor of positive attitudes from a public health perspective (OR = 3.98, 95% CI = 2.44–6.50). Physicians show a lower level of knowledge and more public health attitudes than other public health professionals do. About 80% of public health professionals considered their knowledge inadequate and 86.0% believed that it should be improved through specific postgraduate training courses.
Conclusions
Specific and targeted training initiatives are needed to develop a skilled public health workforce competent in identifying genomic technology that is ready for use in population health and in modeling public health genomic programs and primary care services that need to be developed, implemented and evaluated.
doi:10.1186/1472-6963-14-239
PMCID: PMC4064825  PMID: 24885316
Public health genomics; Predictive genetic testing; Public health professionals; Cross-sectional survey; Knowledge and attitudes; Training needs
9.  Communicating Genetic and Genomic Information: Health Literacy and Numeracy Considerations 
Public health genomics  2010;14(4-5):279-289.
Genomic research is transforming our understanding of the role of genes in health and disease. These advances, and their application to common diseases that affect large segments of the general population, suggest that researchers and practitioners in public health genomics will increasingly be called upon to translate genomic information to individuals with varying levels of health literacy and numeracy. This paper discusses the current state of research regarding public understanding of genetics and genomics, the influence of health literacy and numeracy on genetic communication, and behavioral responses to genetic and genomic information. The existing research suggests that members of the general public have some familiarity with genetic and genomic terms, but have gaps in understanding of underlying concepts. Findings from the limited research base to date indicate that health literacy affects understanding of print and oral communications about genetic and genomic information. Numeracy is also likely to be an important predictor of being able to understand and apply this information, although little research has been conducted in this area to date. In addition, although some research has examined behavior change in response to the receipt of information about genetic risk for familial disorders and genomic susceptibility to common, complex diseases, the effects of health literacy and numeracy on these responses have not been examined. Potential areas in which additional research is needed are identified and practical suggestions for presenting numeric risk information are outlined. Public health genomics researchers and practitioners are uniquely positioned to engage in research that explores how different audiences react to and use genomic risk information.
doi:10.1159/000294191
PMCID: PMC2909377  PMID: 20407217
health literacy; numeracy; health behavior change; genetic communication; genomics
10.  Communicating Genetic and Genomic Information: Health Literacy and Numeracy Considerations 
Public Health Genomics  2010;14(4-5):279-289.
Genomic research is transforming our understanding of the role of genes in health and disease. These advances, and their application to common diseases that affect large segments of the general population, suggest that researchers and practitioners in public health genomics will increasingly be called upon to translate genomic information to individuals with varying levels of health literacy and numeracy. This paper discusses the current state of research regarding public understanding of genetics and genomics, the influence of health literacy and numeracy on genetic communication, and behavioral responses to genetic and genomic information. The existing research suggests that members of the general public have some familiarity with genetic and genomic terms but have gaps in understanding of underlying concepts. Findings from the limited research base to date indicate that health literacy affects understanding of print and oral communications about genetic and genomic information. Numeracy is also likely to be an important predictor of being able to understand and apply this information, although little research has been conducted in this area to date. In addition, although some research has examined behavior change in response to the receipt of information about genetic risk for familial disorders and genomic susceptibility to common, complex diseases, the effects of health literacy and numeracy on these responses have not been examined. Potential areas in which additional research is needed are identified and practical suggestions for presenting numeric risk information are outlined. Public health genomics researchers and practitioners are uniquely positioned to engage in research that explores how different audiences react to and use genomic risk information.
doi:10.1159/000294191
PMCID: PMC2909377  PMID: 20407217
Genetic communication; Genomics; Health behavior change; Health literacy; Numeracy
11.  An Epidemiological Network Model for Disease Outbreak Detection 
PLoS Medicine  2007;4(6):e210.
Background
Advanced disease-surveillance systems have been deployed worldwide to provide early detection of infectious disease outbreaks and bioterrorist attacks. New methods that improve the overall detection capabilities of these systems can have a broad practical impact. Furthermore, most current generation surveillance systems are vulnerable to dramatic and unpredictable shifts in the health-care data that they monitor. These shifts can occur during major public events, such as the Olympics, as a result of population surges and public closures. Shifts can also occur during epidemics and pandemics as a result of quarantines, the worried-well flooding emergency departments or, conversely, the public staying away from hospitals for fear of nosocomial infection. Most surveillance systems are not robust to such shifts in health-care utilization, either because they do not adjust baselines and alert-thresholds to new utilization levels, or because the utilization shifts themselves may trigger an alarm. As a result, public-health crises and major public events threaten to undermine health-surveillance systems at the very times they are needed most.
Methods and Findings
To address this challenge, we introduce a class of epidemiological network models that monitor the relationships among different health-care data streams instead of monitoring the data streams themselves. By extracting the extra information present in the relationships between the data streams, these models have the potential to improve the detection capabilities of a system. Furthermore, the models' relational nature has the potential to increase a system's robustness to unpredictable baseline shifts. We implemented these models and evaluated their effectiveness using historical emergency department data from five hospitals in a single metropolitan area, recorded over a period of 4.5 y by the Automated Epidemiological Geotemporal Integrated Surveillance real-time public health–surveillance system, developed by the Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology on behalf of the Massachusetts Department of Public Health. We performed experiments with semi-synthetic outbreaks of different magnitudes and simulated baseline shifts of different types and magnitudes. The results show that the network models provide better detection of localized outbreaks, and greater robustness to unpredictable shifts than a reference time-series modeling approach.
Conclusions
The integrated network models of epidemiological data streams and their interrelationships have the potential to improve current surveillance efforts, providing better localized outbreak detection under normal circumstances, as well as more robust performance in the face of shifts in health-care utilization during epidemics and major public events.
Most surveillance systems are not robust to shifts in health care utilization. Ben Reis and colleagues developed network models that detected localized outbreaks better and were more robust to unpredictable shifts.
Editors' Summary
Background.
The main task of public-health officials is to promote health in communities around the world. To do this, they need to monitor human health continually, so that any outbreaks (epidemics) of infectious diseases (particularly global epidemics or pandemics) or any bioterrorist attacks can be detected and dealt with quickly. In recent years, advanced disease-surveillance systems have been introduced that analyze data on hospital visits, purchases of drugs, and the use of laboratory tests to look for tell-tale signs of disease outbreaks. These surveillance systems work by comparing current data on the use of health-care resources with historical data or by identifying sudden increases in the use of these resources. So, for example, more doctors asking for tests for salmonella than in the past might presage an outbreak of food poisoning, and a sudden rise in people buying over-the-counter flu remedies might indicate the start of an influenza pandemic.
Why Was This Study Done?
Existing disease-surveillance systems don't always detect disease outbreaks, particularly in situations where there are shifts in the baseline patterns of health-care use. For example, during an epidemic, people might stay away from hospitals because of the fear of becoming infected, whereas after a suspected bioterrorist attack with an infectious agent, hospitals might be flooded with “worried well” (healthy people who think they have been exposed to the agent). Baseline shifts like these might prevent the detection of increased illness caused by the epidemic or the bioterrorist attack. Localized population surges associated with major public events (for example, the Olympics) are also likely to reduce the ability of existing surveillance systems to detect infectious disease outbreaks. In this study, the researchers developed a new class of surveillance systems called “epidemiological network models.” These systems aim to improve the detection of disease outbreaks by monitoring fluctuations in the relationships between information detailing the use of various health-care resources over time (data streams).
What Did the Researchers Do and Find?
The researchers used data collected over a 3-y period from five Boston hospitals on visits for respiratory (breathing) problems and for gastrointestinal (stomach and gut) problems, and on total visits (15 data streams in total), to construct a network model that included all the possible pair-wise comparisons between the data streams. They tested this model by comparing its ability to detect simulated disease outbreaks implanted into data collected over an additional year with that of a reference model based on individual data streams. The network approach, they report, was better at detecting localized outbreaks of respiratory and gastrointestinal disease than the reference approach. To investigate how well the network model dealt with baseline shifts in the use of health-care resources, the researchers then added in a large population surge. The detection performance of the reference model decreased in this test, but the performance of the complete network model and of models that included relationships between only some of the data streams remained stable. Finally, the researchers tested what would happen in a situation where there were large numbers of “worried well.” Again, the network models detected disease outbreaks consistently better than the reference model.
What Do These Findings Mean?
These findings suggest that epidemiological network systems that monitor the relationships between health-care resource-utilization data streams might detect disease outbreaks better than current systems under normal conditions and might be less affected by unpredictable shifts in the baseline data. However, because the tests of the new class of surveillance system reported here used simulated infectious disease outbreaks and baseline shifts, the network models may behave differently in real-life situations or if built using data from other hospitals. Nevertheless, these findings strongly suggest that public-health officials, provided they have sufficient computer power at their disposal, might improve their ability to detect disease outbreaks by using epidemiological network systems alongside their current disease-surveillance systems.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040210.
Wikipedia pages on public health (note that Wikipedia is a free online encyclopedia that anyone can edit, and is available in several languages)
A brief description from the World Health Organization of public-health surveillance (in English, French, Spanish, Russian, Arabic, and Chinese)
A detailed report from the US Centers for Disease Control and Prevention called “Framework for Evaluating Public Health Surveillance Systems for the Early Detection of Outbreaks”
The International Society for Disease Surveillance Web site
doi:10.1371/journal.pmed.0040210
PMCID: PMC1896205  PMID: 17593895
12.  The Genomic Applications in Practice and Prevention Network 
Genetics in Medicine  2009;11(7):488-494.
The authors describe the rationale and initial development of a new collaborative initiative, the Genomic Applications in Practice and Prevention Network. The network convened by the Centers for Disease Control and Prevention and the National Institutes of Health includes multiple stakeholders from academia, government, health care, public health, industry and consumers. The premise of Genomic Applications in Practice and Prevention Network is that there is an unaddressed chasm between gene discoveries and demonstration of their clinical validity and utility. This chasm is due to the lack of readily accessible information about the utility of most genomic applications and the lack of necessary knowledge by consumers and providers to implement what is known. The mission of Genomic Applications in Practice and Prevention Network is to accelerate and streamline the effective integration of validated genomic knowledge into the practice of medicine and public health, by empowering and sponsoring research, evaluating research findings, and disseminating high quality information on candidate genomic applications in practice and prevention. Genomic Applications in Practice and Prevention Network will develop a process that links ongoing collection of information on candidate genomic applications to four crucial domains: (1) knowledge synthesis and dissemination for new and existing technologies, and the identification of knowledge gaps, (2) a robust evidence-based recommendation development process, (3) translation research to evaluate validity, utility and impact in the real world and how to disseminate and implement recommended genomic applications, and (4) programs to enhance practice, education, and surveillance.
PMCID: PMC2743616  PMID: 19471162
decision support; genomics; information; medicine; network; public health
13.  Genomics for Disease Treatment and Prevention 
The enormous advances in genetics and genomics of the past decade have the potential to revolutionize health care, including mental health care, and bring about a system predominantly characterized by the practice of genomic and personalized medicine. We briefly review the history of genetics and genomics and present heritability estimates for major chronic diseases of aging and neuropsychiatric disorders. We then assess the extent to which the results of genetic and genomic studies are currently being leveraged clinically for disease treatment and prevention and identify priority research areas in which further work is needed. Pharmacogenomics has emerged as one area of genomics that already has had notable impacts on disease treatment and the practice of medicine. Little evidence, however, for the clinical validity and utility of predictive testing based on genomic information is available, and thus has, to some extent, hindered broader-scale preventive efforts for common, complex diseases. Furthermore, although other disease areas have had greater success in identifying genetic factors responsible for various conditions, progress in identifying the genetic basis of neuropsychiatric diseases has lagged behind. We review social, economic, and policy issues relevant to genomic medicine, and find that a new model of health care based on proactive and preventive health planning and individualized treatment will require major advances in health care policy and administration. Specifically, incentives for relevant stakeholders are critical, as are realignment of incentives and education initiatives for physicians, and updates to pertinent legislation. Moreover, the translational behavioral and public health research necessary for fully integrating genomics into health care is lacking, and further work in these areas is needed. In short, while the pace of advances in genetic and genomic science and technology has been rapid, more work is needed to fully realize the potential for impacting disease treatment and prevention generally, and mental health specifically.
doi:10.1016/j.psc.2010.11.005
PMCID: PMC3073546  PMID: 21333845
genomics; genetic testing; genetic risk assessment; public health genomics; pharmacogenomics
14.  Physical Activity Attenuates the Genetic Predisposition to Obesity in 20,000 Men and Women from EPIC-Norfolk Prospective Population Study 
PLoS Medicine  2010;7(8):e1000332.
Shengxu Li and colleagues use data from a large prospective observational cohort to examine the extent to which a genetic predisposition toward obesity may be modified by living a physically active lifestyle.
Background
We have previously shown that multiple genetic loci identified by genome-wide association studies (GWAS) increase the susceptibility to obesity in a cumulative manner. It is, however, not known whether and to what extent this genetic susceptibility may be attenuated by a physically active lifestyle. We aimed to assess the influence of a physically active lifestyle on the genetic predisposition to obesity in a large population-based study.
Methods and Findings
We genotyped 12 SNPs in obesity-susceptibility loci in a population-based sample of 20,430 individuals (aged 39–79 y) from the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort with an average follow-up period of 3.6 y. A genetic predisposition score was calculated for each individual by adding the body mass index (BMI)-increasing alleles across the 12 SNPs. Physical activity was assessed using a self-administered questionnaire. Linear and logistic regression models were used to examine main effects of the genetic predisposition score and its interaction with physical activity on BMI/obesity risk and BMI change over time, assuming an additive effect for each additional BMI-increasing allele carried. Each additional BMI-increasing allele was associated with 0.154 (standard error [SE] 0.012) kg/m2 (p = 6.73×10−37) increase in BMI (equivalent to 445 g in body weight for a person 1.70 m tall). This association was significantly (pinteraction = 0.005) more pronounced in inactive people (0.205 [SE 0.024] kg/m2 [p = 3.62×10−18; 592 g in weight]) than in active people (0.131 [SE 0.014] kg/m2 [p = 7.97×10−21; 379 g in weight]). Similarly, each additional BMI-increasing allele increased the risk of obesity 1.116-fold (95% confidence interval [CI] 1.093–1.139, p = 3.37×10−26) in the whole population, but significantly (pinteraction = 0.015) more in inactive individuals (odds ratio [OR] = 1.158 [95% CI 1.118–1.199; p = 1.93×10−16]) than in active individuals (OR = 1.095 (95% CI 1.068–1.123; p = 1.15×10−12]). Consistent with the cross-sectional observations, physical activity modified the association between the genetic predisposition score and change in BMI during follow-up (pinteraction = 0.028).
Conclusions
Our study shows that living a physically active lifestyle is associated with a 40% reduction in the genetic predisposition to common obesity, as estimated by the number of risk alleles carried for any of the 12 recently GWAS-identified loci.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In the past few decades, the global incidence of obesity—defined as a body mass index (BMI, a simple index of weight-for-height that uses the weight in kilograms divided by the square of the height in meters) of 30 and over, has increased so much that this growing public health concern is now commonly referred to as the “obesity epidemic.” Once considered prevalent only in high-income countries, obesity is an increasing health problem in low- and middle-income countries, particularly in urban settings. In 2005, at least 400 million adults world-wide were obese, and the projected figure for 2015 is a substantial increase of 300 million to around 700 million. Childhood obesity is also a growing concern. Contributing factors to the obesity epidemic are a shift in diet to an increased intake of energy-dense foods that are high in fat and sugars and a trend towards decreased physical activity due to increasingly sedentary lifestyles.
However, genetics are also thought to play a critical role as genetically predisposed individuals may be more prone to obesity if they live in an environment that has abundant access to energy-dense food and labor-saving devices.
Why Was This Study Done?
Although recent genetic studies (genome-wide association studies) have identified 12 alleles (a DNA variant that is located at a specific position on a specific chromosome) associated with increased BMI, there has been no convincing evidence of the interaction between genetics and lifestyle. In this study the researchers examined the possibility of such an interaction by assessing whether individuals with a genetic predisposition to increased obesity risk could modify this risk by increasing their daily physical activity.
What Did the Researchers Do and Find?
The researchers used a population-based cohort study of 25,631 people living in Norwich, UK (The EPIC-Norfolk study) and identified individuals who were 39 to 79 years old during a health check between 1993 and 1997. The researchers invited these people to a second health examination. In total, 20,430 individuals had baseline data available, of which 11,936 had BMI data at the second health check. The researchers used genotyping methods and then calculated a genetic predisposition score for each individual and their occupational and leisure-time physical activities were assessed by using a validated self-administered questionnaire. Then, the researchers used modeling techniques to examine the main effects of the genetic predisposition score and its interaction with physical activity on BMI/obesity risk and BMI change over time. The researchers found that each additional BMI-increasing allele was associated with an increase in BMI equivalent to 445 g in body weight for a person 1.70 m tall and that the size of this effect was greater in inactive people than in active people. In individuals who have a physically active lifestyle, this increase was only 379 g/allele, or 36% lower than in physically inactive individuals in whom the increase was 592 g/allele. Furthermore, in the total sample each additional obesity-susceptibility allele increased the odds of obesity by 1.116-fold. However, the increased odds per allele for obesity risk were 40% lower in physically active individuals (1.095 odds/allele) compared to physically inactive individuals (1.158 odds/allele).
What Do These Findings Mean?
The findings of this study indicate that the genetic predisposition to obesity can be reduced by approximately 40% by having a physically active lifestyle. The findings of this study suggest that, while the whole population benefits from increased physical activity levels, individuals who are genetically predisposed to obesity would benefit more than genetically protected individuals. Furthermore, these findings challenge the deterministic view of the genetic predisposition to obesity that is often held by the public, as they show that even the most genetically predisposed individuals will benefit from adopting a healthy lifestyle. The results are limited by participants self-reporting their physical activity levels, which is less accurate than objective measures of physical activity.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000332.
This study relies on the results of previous genome-wide association studies The National Human Genome Research Institute provides an easy-to-follow guide to understanding such studies
The International Association for the Study of Obesity aims to improve global health by promoting the understanding of obesity and weight-related diseases through scientific research and dialogue
The International Obesity Taskforce is the research-led think tank and advocacy arm of the International Association for the Study of Obesity
The Global Alliance for the Prevention of Obesity and Related Chronic Disease is a global action program that addresses the issues surrounding the prevention of obesity
The National Institutes of Health has its own obesity task force, which includes 26 institutes
doi:10.1371/journal.pmed.1000332
PMCID: PMC2930873  PMID: 20824172
15.  A Novel Diagnostic Target in the Hepatitis C Virus Genome 
PLoS Medicine  2009;6(2):e1000031.
Background
Detection and quantification of hepatitis C virus (HCV) RNA is integral to diagnostic and therapeutic regimens. All molecular assays target the viral 5′-noncoding region (5′-NCR), and all show genotype-dependent variation of sensitivities and viral load results. Non-western HCV genotypes have been under-represented in evaluation studies. An alternative diagnostic target region within the HCV genome could facilitate a new generation of assays.
Methods and Findings
In this study we determined by de novo sequencing that the 3′-X-tail element, characterized significantly later than the rest of the genome, is highly conserved across genotypes. To prove its clinical utility as a molecular diagnostic target, a prototype qualitative and quantitative test was developed and evaluated multicentrically on a large and complete panel of 725 clinical plasma samples, covering HCV genotypes 1–6, from four continents (Germany, UK, Brazil, South Africa, Singapore). To our knowledge, this is the most diversified and comprehensive panel of clinical and genotype specimens used in HCV nucleic acid testing (NAT) validation to date. The lower limit of detection (LOD) was 18.4 IU/ml (95% confidence interval, 15.3–24.1 IU/ml), suggesting applicability in donor blood screening. The upper LOD exceeded 10−9 IU/ml, facilitating viral load monitoring within a wide dynamic range. In 598 genotyped samples, quantified by Bayer VERSANT 3.0 branched DNA (bDNA), X-tail-based viral loads were highly concordant with bDNA for all genotypes. Correlation coefficients between bDNA and X-tail NAT, for genotypes 1–6, were: 0.92, 0.85, 0.95, 0.91, 0.95, and 0.96, respectively; X-tail-based viral loads deviated by more than 0.5 log10 from 5′-NCR-based viral loads in only 12% of samples (maximum deviation, 0.85 log10). The successful introduction of X-tail NAT in a Brazilian laboratory confirmed the practical stability and robustness of the X-tail-based protocol. The assay was implemented at low reaction costs (US$8.70 per sample), short turnover times (2.5 h for up to 96 samples), and without technical difficulties.
Conclusion
This study indicates a way to fundamentally improve HCV viral load monitoring and infection screening. Our prototype assay can serve as a template for a new generation of viral load assays. Additionally, to our knowledge this study provides the first open protocol to permit industry-grade HCV detection and quantification in resource-limited settings.
Christian Drosten and colleagues develop, validate, and make openly available a prototype hepatitis C virus assay based on the conserved 3' X-tail element, with potential for clinical use in developing countries.
Editors' Summary
Background.
About 3% of the world's population (170 million people) harbor long-term (chronic) infections with the hepatitis C virus (HCV) and about 3–4 million people are newly infected with this virus every year. HCV—a leading cause of chronic hepatitis (inflammation of the liver)—is spread through contact with the blood of an infected person. Globally, the main routes of transmission are the use of unscreened blood for transfusions and the reuse of inadequately sterilized medical instruments, including needles. In affluent countries, where donated blood is routinely screened for the presence of HCV, most transmission is through needle sharing among drug users. The risk of sexual and mother-to-child transmission of HCV is low. Although HCV infection occasionally causes an acute (short-lived) illness characterized by tiredness and jaundice (yellow eyes and skin), most newly infected people progress to a symptom-free, chronic infection that can eventually cause liver cirrhosis (scarring) and liver cancer. HCV infections can be treated with a combination of two drugs called interferon and ribavirin, but these drugs are expensive and are ineffective in many patients.
Why Was This Study Done?
An effective way to limit the global spread of HCV might be to introduce routine screening of the blood that is used for transfusions in developing countries. In developed countries, HCV screening of blood donors use expensive, commercial “RT-PCR” assays to detect small amounts of HCV ribonucleic acid (RNA; HCV stores the information it needs to replicate itself—its genome—as a sequence of “ribonucleotides”). All the current HCV assays, which can also quantify the amount of viral RNA in the blood (the viral load) during treatment, detect a target sequence in the viral genome called the 5′-noncoding region (5′-NCR). However, there are several different HCV “genotypes” (strains). These genotypes vary in their geographical distribution and, even though the 5′-NCR sequence is very similar (highly conserved) in the common genotypes (HCV genotypes 1–6), the existing assays do not detect all the variants equally well. This shortcoming, together with their high cost, means that 5′-NCR RT-PCR assays are not ideal for use in many developing countries. In this study, the researchers identify an alternative diagnostic target sequence in the HCV genome—the 3′-X-tail element—and ask whether this sequence can be used to develop a new generation of tests for HCV infection that might be more appropriate for use in developing countries.
What Did the Researchers Do and Find?
The researchers determined the RNA sequence of the 3′-X-tail element in reference samples of the major HCV genotypes and showed that this region of the HCV genome is as highly conserved as the 5′-NCR. They then developed a prototype X-tail RT-PCR assay and tested its ability to detect small amounts of HCV and to measure viral load in genotype reference samples and in a large panel of HCV-infected blood samples collected in Germany, the UK, Brazil, South Africa, and Singapore. The new assay detected low levels of HCV RNA in all of the genotype reference samples and was also able to quantify high RNA concentrations. The viral load estimates it provided for the clinical samples agreed well with those obtained using a commercial assay irrespective of the sample's HCV genotype. Finally, the X-tail RT-PCR assay gave similar results to a standard assay at a fraction of the cost when used to measure viral loads in a Brazilian laboratory in an independent group of 127 patient samples collected in Brazil.
What Do These Findings Mean?
These findings suggest that the HCV 3′-X-tail element could provide an alternative target for screening blood samples for HCV infection and for monitoring viral loads during treatment, irrespective of HCV genotype. In addition, they suggest that X-tail RT-PCR assays may be stable and robust enough for use in laboratories in emerging countries. Overall, these findings should stimulate the development of a new generation of clinical HCV assays that, because the protocol used in the X-tail assay is freely available, could improve blood safety in developing countries by providing a cheap and effective alternative to existing proprietary HCV assays.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000031.
The World Health Organization has a fact sheet about hepatitis C (in English and French)
The US Centers for Disease Control and Prevention provides information on hepatitis C for the public and for health professionals (information is also available in Spanish)
The US National Institute of Diabetes and Digestive and Kidney Diseases provides basic information on hepatitis C (in English and Spanish)
The MedlinePlus Encyclopedia has a page on hepatitis C; MedlinePlus also provides links to further information on hepatitis C (in English and Spanish)
doi:10.1371/journal.pmed.1000031
PMCID: PMC2637920  PMID: 19209955
16.  A Health Department’s Collaborative Model for Disease Surveillance Capacity Building 
Objective
Highlight one academic health department’s unique approach to optimizing collaborative opportunities for capacity development and document the implications for chronic disease surveillance and population health.
Introduction
Public Health departments are increasingly called upon to be innovative in quality service delivery under a dwindling resource climate as highlighted in several publications of the Institute of Medicine. Collaboration with other entities in the delivery of core public health services has emerged as a recurring theme. One model of this collaboration is an academic health department: a formal affiliation between a health professions school and a local health department. Initially targeted at workforce development, this model of collaboration has since yielded dividends in other core public health service areas including community assessment, program evaluation, community-based participatory research and data analysis.
The Duval County Health Department (DCHD), Florida, presents a unique community-centered model of the academic health department. Prominence in local informatics infrastructure capacity building and hosting a CDC-CSTE applied public health informatics fellowship (APHIF) in the Institute for Public Health Informatics and Research (IPHIR) in partnership with the Center for Health Equity Research, University of Florida & Shands medical center are direct dividends of this collaborative model.
Methods
We examined the collaborative efforts of the DCHD and present the unique advantages these have brought in the areas of entrenched data-driven public health service culture, community assessments, program evaluation, community-based participatory research and health informatics projects.
Results
Advantages of the model include a data-driven culture with the balanced scorecard model in leadership and sub-departmental emphases on quality assurance in public health services. Activities in IPHIR include data-driven approaches to program planning and grant developments, program evaluations, data analyses and impact assessments for the DCHD and other community health stakeholders.
Reports developed by IPHIR have impacted policy formulation by highlighting the need for sub county level data differentiation to address health disparities. Unique community-based mapping of Duval County into health zones based on health risk factors correlating with health outcome measures have been published. Other reports highlight chronic disease surveillance data and health scorecards in special populations.
Partnerships with regional higher institutions (University of Florida, University of North Florida and Florida A&M University) increased public health service delivery and yielded rich community-based participatory research opportunities.
Cutting edge participation in health IT policy implementation led to the hosting of the fledgling community HIE, the Jacksonville Health Information Network, as well as leadership in shaping the landscape of the state HIE. This has immense implications for public health surveillance activities as chronic disease surveillance and public health service research take center stage under new healthcare payment models amidst increasing calls for quality assurance in public health services.
DCHD is currently hosting a CDC-funded fellowship in applied public health informatics. Some of the projects materializing from the fellowship are the mapping of the current public health informatics profile of the DCHD, a community based diabetes disease registry to aid population-based management and surveillance of diabetes, development of a proposal for a combined primary care/general preventive medicine residency in UF-Shands Medical Center, Jacksonville and mobilization of DCHD healthcare providers for the roll-out of the state-built electronic medical records system (Florida HMS-EHR).
Conclusions
Academic health centers provide a model of collaboration that directly impacts on their success in delivering core public health services. Disease surveillance is positively affected by the diverse community affiliations of an academic health department. The academic health department, as epitomized by DCHD, is also better positioned to seize up-coming opportunities for local public health capacity building.
PMCID: PMC3692891
Academic Health Departments; collaborative model; health informatics projects
17.  Geographic Distribution of Staphylococcus aureus Causing Invasive Infections in Europe: A Molecular-Epidemiological Analysis 
PLoS Medicine  2010;7(1):e1000215.
Hajo Grundmann and colleagues describe the development of a new interactive mapping tool for analyzing the spatial distribution of invasive Staphylococcus aureus clones.
Background
Staphylococcus aureus is one of the most important human pathogens and methicillin-resistant variants (MRSAs) are a major cause of hospital and community-acquired infection. We aimed to map the geographic distribution of the dominant clones that cause invasive infections in Europe.
Methods and Findings
In each country, staphylococcal reference laboratories secured the participation of a sufficient number of hospital laboratories to achieve national geo-demographic representation. Participating laboratories collected successive methicillin-susceptible (MSSA) and MRSA isolates from patients with invasive S. aureus infection using an agreed protocol. All isolates were sent to the respective national reference laboratories and characterised by quality-controlled sequence typing of the variable region of the staphylococcal spa gene (spa typing), and data were uploaded to a central database. Relevant genetic and phenotypic information was assembled for interactive interrogation by a purpose-built Web-based mapping application. Between September 2006 and February 2007, 357 laboratories serving 450 hospitals in 26 countries collected 2,890 MSSA and MRSA isolates from patients with invasive S. aureus infection. A wide geographical distribution of spa types was found with some prevalent in all European countries. MSSA were more diverse than MRSA. Genetic diversity of MRSA differed considerably between countries with dominant MRSA spa types forming distinctive geographical clusters. We provide evidence that a network approach consisting of decentralised typing and visualisation of aggregated data using an interactive mapping tool can provide important information on the dynamics of MRSA populations such as early signalling of emerging strains, cross border spread, and importation by travel.
Conclusions
In contrast to MSSA, MRSA spa types have a predominantly regional distribution in Europe. This finding is indicative of the selection and spread of a limited number of clones within health care networks, suggesting that control efforts aimed at interrupting the spread within and between health care institutions may not only be feasible but ultimately successful and should therefore be strongly encouraged.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
The bacterium Staphylococcus aureus lives on the skin and in the nose of about a third of healthy people. Although S. aureus usually coexists peacefully with its human carriers, it is also an important disease-causing organism or pathogen. If it enters the body through a cut or during a surgical procedure, S. aureus can cause minor infections such as pimples and boils or more serious, life-threatening infections such as blood poisoning and pneumonia. Minor S. aureus infections can be treated without antibiotics—by draining a boil, for example. Invasive infections are usually treated with antibiotics. Unfortunately, many of the S. aureus clones (groups of bacteria that are all genetically related and descended from a single, common ancestor) that are now circulating are resistant to methicillin and several other antibiotics. Invasive methicillin-resistant S. aureus (MRSA) infections are a particular problem in hospitals and other health care facilities (so-called hospital-acquired MRSA infections), but they can also occur in otherwise healthy people who have not been admitted to a hospital (community-acquired MRSA infections).
Why Was This Study Done?
The severity and outcome of an S. aureus infection in an individual depends in part on the ability of the bacterial clone with which the individual is infected to cause disease—the clone's “virulence.” Public-health officials and infectious disease experts would like to know the geographic distribution of the virulent S. aureus clones that cause invasive infections, because this information should help them understand how these pathogens spread and thus how to control them. Different clones of S. aureus can be distinguished by “molecular typing,” the determination of clone-specific sequences of nucleotides in variable regions of the bacterial genome (the bacterium's blueprint; genomes consist of DNA, long chains of nucleotides). In this study, the researchers use molecular typing to map the geographic distribution of MRSA and methicillin-sensitive S. aureus (MSSA) clones causing invasive infections in Europe; a MRSA clone emerges when an MSSA clone acquires antibiotic resistance from another type of bacteria so it is useful to understand the geographic distribution of both MRSA and MSSA.
What Did the Researchers Do and Find?
Between September 2006 and February 2007, 357 laboratories serving 450 hospitals in 26 European countries collected almost 3,000 MRSA and MSSA isolates from patients with invasive S. aureus infections. The isolates were sent to the relevant national staphylococcal reference laboratory (SRL) where they were characterized by quality-controlled sequence typing of the variable region of a staphylococcal gene called spa (spa typing). The spa typing data were entered into a central database and then analyzed by a public, purpose-built Web-based mapping tool (SRL-Maps), which provides interactive access and easy-to-understand illustrations of the geographical distribution of S. aureus clones. Using this mapping tool, the researchers found that there was a wide geographical distribution of spa types across Europe with some types being common in all European countries. MSSA isolates were more diverse than MRSA isolates and the genetic diversity (variability) of MRSA differed considerably between countries. Most importantly, major MRSA spa types occurred in distinct geographical clusters.
What Do These Findings Mean?
These findings provide the first representative snapshot of the genetic population structure of S. aureus across Europe. Because the researchers used spa typing, which analyzes only a small region of one gene, and characterized only 3,000 isolates, analysis of other parts of the S. aureus genome in more isolates is now needed to build a complete portrait of the geographical abundance of the S. aureus clones that cause invasive infections in Europe. However, the finding that MRSA spa types occur mainly in geographical clusters has important implications for the control of MRSA, because it indicates that a limited number of clones are spreading within health care networks, which means that MRSA is mainly spread by patients who are repeatedly admitted to different hospitals. Control efforts aimed at interrupting this spread within and between health care institutions may be feasible and ultimately successful, suggest the researchers, and should be strongly encouraged. In addition, this study shows how, by sharing typing results on a Web-based platform, an international surveillance network can provide clinicians and infection control teams with crucial information about the dynamics of pathogens such as S. aureus, including early warnings about emerging virulent clones.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000215.
This study is further discussed in a PLoS Medicine Perspective by Franklin D. Lowy
The UK Health Protection Agency provides information about Staphylococcus aureus
The UK National Health Service Choices Web site has pages on staphylococcal infections and on MRSA
The US National Institute of Allergy and Infectious Disease has information about MRSA
The US Centers for Disease Control and Infection provides information about MRSA for the public and professionals
MedlinePlus provides links to further resources on staphylococcal infections and on MRSA (in English and Spanish)
SRL-Maps can be freely accessed
doi:10.1371/journal.pmed.1000215
PMCID: PMC2796391  PMID: 20084094
18.  Analysis of Existing International Policy Evidence in Public Health Genomics: Mapping Exercise 
Background
In the last decades we have seen a constant growth in the fields of science related to the use of genome-based health information. However, there is a gap between basic science research and the Public Health everyday practice. For a successful introduction of genome-based technologies policy actions on the international level are needed. This work represents the initial stage of the PHGEN II (Public Health Genomics European Network II) project. In order to prepare a base for bridging genomics and Public Health, an inventory study of the existing legislative base dealing with controversies of genome-based knowledge was conducted. The work results in the mapping of the most and the least legislatively covered areas and some preliminary conclusions about the existing gaps.
Design and Methods
The collection of the evidence-based policies was done through the PHGEN II project. The mapping covered the meta-level (international, European general guidelines). The expert opinion of the partners of the project was required to reflect on and grade the collected evidence.
Results
An analysis of the evidence was made by the area of coverage: using the list of important policy areas for successful introduction of genome-based technologies into Public Health and the Public Health Genomics Wheel (originally Public Health Wheel developed by Institute of Medicine).
Conclusions
Severe inequalities in coverage of important issues of Public Health Genomics were found. The most attention was paid to clinical utility and clinical validity of the screening and the protection of human subjects. Important areas such as trade agreements, Public Health Genomics literacy, insurance issues, behaviour modification in response to genomics results etc. were paid less attention to.
For the successful adoption of new technologies on the Public Health level the focus should be not only on the translation to clinical practice, but the translation from bench to Public Health policy and back. Coherent and consistent coverage of all aspects of the translation of genome based information and technologies is of outmost importance.
doi:10.4081/jphr.2012.e8
PMCID: PMC4140310  PMID: 25170444
public health genomics; genomics; translational research; public health; policy; legislation
19.  Combined Impact of Health Behaviours and Mortality in Men and Women: The EPIC-Norfolk Prospective Population Study 
PLoS Medicine  2008;5(1):e12.
Background
There is overwhelming evidence that behavioural factors influence health, but their combined impact on the general population is less well documented. We aimed to quantify the potential combined impact of four health behaviours on mortality in men and women living in the general community.
Methods and Findings
We examined the prospective relationship between lifestyle and mortality in a prospective population study of 20,244 men and women aged 45–79 y with no known cardiovascular disease or cancer at baseline survey in 1993–1997, living in the general community in the United Kingdom, and followed up to 2006. Participants scored one point for each health behaviour: current non-smoking, not physically inactive, moderate alcohol intake (1–14 units a week) and plasma vitamin C >50 mmol/l indicating fruit and vegetable intake of at least five servings a day, for a total score ranging from zero to four. After an average 11 y follow-up, the age-, sex-, body mass–, and social class–adjusted relative risks (95% confidence intervals) for all-cause mortality(1,987 deaths) for men and women who had three, two, one, and zero compared to four health behaviours were respectively, 1.39 (1.21–1.60), 1.95 (1.70–-2.25), 2.52 (2.13–3.00), and 4.04 (2.95–5.54) p < 0.001 trend. The relationships were consistent in subgroups stratified by sex, age, body mass index, and social class, and after excluding deaths within 2 y. The trends were strongest for cardiovascular causes. The mortality risk for those with four compared to zero health behaviours was equivalent to being 14 y younger in chronological age.
Conclusions
Four health behaviours combined predict a 4-fold difference in total mortality in men and women, with an estimated impact equivalent to 14 y in chronological age.
From a large prospective population study, Kay-Tee Khaw and colleagues estimate the combined impact of four behaviors--not smoking, not being physically inactive, moderate alcohol intake, and at least five vegetable servings a day--amounts to 14 additional years of life.
Editors' Summary
Background.
Every day, or so it seems, new research shows that some aspect of lifestyle—physical activity, diet, alcohol consumption, and so on—affects health and longevity. For the person in the street, all this information is confusing. What is a healthy diet, for example? Although there are some common themes such as the benefit of eating plenty of fruit and vegetables, the details often differ between studies. And exactly how much physical activity is needed to improve health? Is a gentle daily walk sufficient or simply a stepping stone to doing enough exercise to make a real difference? The situation with alcohol consumption is equally confusing. Small amounts of alcohol apparently improve health but large amounts are harmful. As a result, it can be hard for public-health officials to find effective ways to encourage the behavioral changes that the scientific evidence suggests might influence the health of populations.
Why Was This Study Done?
There is another factor that is hindering official attempts to provide healthy lifestyle advice to the public. Although there is overwhelming evidence that individual behavioral factors influence health, there is very little information about their combined impact. If the combination of several small differences in lifestyle could be shown to have a marked effect on the health of populations, it might be easier to persuade people to make behavioral changes to improve their health, particularly if those changes were simple and relatively easy to achieve. In this study, which forms part of the European Prospective Investigation into Cancer and Nutrition (EPIC), the researchers have examined the relationship between lifestyle and the risk of dying using a health behavior score based on four simply defined behaviors—smoking, physical activity, alcohol drinking, and fruit and vegetable intake.
What Did the Researchers Do and Find?
Between 1993 and 1997, about 20,000 men and women aged 45–79 living in Norfolk UK, none of whom had cancer or cardiovascular disease (heart or circulation problems), completed a health and lifestyle questionnaire, had a health examination, and had their blood vitamin C level measured as part of the EPIC-Norfolk study. A health behavior score of between 0 and 4 was calculated for each participant by giving one point for each of the following healthy behaviors: current non-smoking, not physically inactive (physical inactivity was defined as having a sedentary job and doing no recreational exercise), moderate alcohol intake (1–14 units a week; a unit of alcohol is half a pint of beer, a glass of wine, or a shot of spirit), and a blood vitamin C level consistent with a fruit and vegetable intake of at least five servings a day. Deaths among the participants were then recorded until 2006. After allowing for other factors that might have affected their likelihood of dying (for example, age), people with a health behavior score of 0 were four times as likely to have died (in particular, from cardiovascular disease) than those with a score of 4. People with a score of 2 were twice as likely to have died.
What Do These Findings Mean?
These findings indicate that the combination of four simply defined health behaviors predicts a 4-fold difference in the risk of dying over an average period of 11 years for middle-aged and older people. They also show that the risk of death (particularly from cardiovascular disease) decreases as the number of positive health behaviors increase. Finally, they can be used to calculate that a person with a health score of 0 has the same risk of dying as a person with a health score of 4 who is 14 years older. These findings need to be confirmed in other populations and extended to an analysis of how these combined health behaviors affect the quality of life as well as the risk of death. Nevertheless, they strongly suggest that modest and achievable lifestyle changes could have a marked effect on the health of populations. Armed with this information, public-health officials should now be in a better position to encourage behavior changes likely to improve the health of middle-aged and older people.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050012.
The MedlinePlus encyclopedia contains a page on healthy living (in English and Spanish)
The MedlinePlus page on seniors' health contains links to many sites dealing with healthy lifestyles and longevity (in English and Spanish)
The European Prospective Investigation into Cancer and Nutrition (EPIC) study is investigating the relationship between nutrition and lifestyle and the development of cancer and other chronic diseases; information about the EPIC-Norfolk study is also available
The US Centers for Disease Control and Prevention provides information on healthy aging for older adults, including information on health-related behaviors (in English and Spanish)
The UK charity Age Concerns provides a fact sheet about staying healthy in later life
The London Health Observatory, which provides information for policy makers and practitioners about improving health and health care, has a section on how lifestyle and behavior affect health
doi:10.1371/journal.pmed.0050012
PMCID: PMC2174962  PMID: 18184033
20.  Whole Genome Sequencing versus Traditional Genotyping for Investigation of a Mycobacterium tuberculosis Outbreak: A Longitudinal Molecular Epidemiological Study 
PLoS Medicine  2013;10(2):e1001387.
In an outbreak investigation of Mycobacterium tuberculosis comparing whole genome sequencing (WGS) with traditional genotyping, Stefan Niemann and colleagues found that classical genotyping falsely clustered some strains, and WGS better reflected contact tracing.
Background
Understanding Mycobacterium tuberculosis (Mtb) transmission is essential to guide efficient tuberculosis control strategies. Traditional strain typing lacks sufficient discriminatory power to resolve large outbreaks. Here, we tested the potential of using next generation genome sequencing for identification of outbreak-related transmission chains.
Methods and Findings
During long-term (1997 to 2010) prospective population-based molecular epidemiological surveillance comprising a total of 2,301 patients, we identified a large outbreak caused by an Mtb strain of the Haarlem lineage. The main performance outcome measure of whole genome sequencing (WGS) analyses was the degree of correlation of the WGS analyses with contact tracing data and the spatio-temporal distribution of the outbreak cases. WGS analyses of the 86 isolates revealed 85 single nucleotide polymorphisms (SNPs), subdividing the outbreak into seven genome clusters (two to 24 isolates each), plus 36 unique SNP profiles. WGS results showed that the first outbreak isolates detected in 1997 were falsely clustered by classical genotyping. In 1998, one clone (termed “Hamburg clone”) started expanding, apparently independently from differences in the social environment of early cases. Genome-based clustering patterns were in better accordance with contact tracing data and the geographical distribution of the cases than clustering patterns based on classical genotyping. A maximum of three SNPs were identified in eight confirmed human-to-human transmission chains, involving 31 patients. We estimated the Mtb genome evolutionary rate at 0.4 mutations per genome per year. This rate suggests that Mtb grows in its natural host with a doubling time of approximately 22 h (400 generations per year). Based on the genome variation discovered, emergence of the Hamburg clone was dated back to a period between 1993 and 1997, hence shortly before the discovery of the outbreak through epidemiological surveillance.
Conclusions
Our findings suggest that WGS is superior to conventional genotyping for Mtb pathogen tracing and investigating micro-epidemics. WGS provides a measure of Mtb genome evolution over time in its natural host context.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Tuberculosis—a contagious bacterial disease that usually infects the lungs—is a major public health problem, particularly in low- and middle-income countries. In 2011, an estimated 8.7 million people developed tuberculosis globally, and 1.4 million people died from the disease. Tuberculosis is second only to HIV/AIDS in terms of global deaths from a single infectious agent. Mycobacterium tuberculosis, the bacterium that causes tuberculosis, is readily spread in airborne droplets when people with active disease cough or sneeze. The characteristic symptoms of tuberculosis include persistent cough, weight loss, fever, and night sweats. Diagnostic tests for the disease include sputum smear analysis (examination of mucus coughed up from the lungs for the presence of M. tuberculosis), mycobacterial culture (growth of M. tuberculosis from sputum), and chest X-rays. Tuberculosis can be cured by taking several antibiotics daily for at least six months, although the recent emergence of multidrug-resistant M. tuberculosis is making tuberculosis harder to treat.
Why Was This Study Done?
Although efforts to reduce the global burden of tuberculosis are showing some improvements, the annual decline in the number of people developing tuberculosis continues to be slow. To develop optimized control strategies, experts need to be able to accurately track M. tuberculosis transmission within human populations. Because M. tuberculosis, like all bacteria, accumulates genetic changes over time, there are many different strains (genetic variants) of M. tuberculosis. Genotyping methods have been developed that identify different bacterial strains by examining specific regions of the bacterial genome (blueprint), but because these methods examine only a small part of the genome, they may not distinguish between related transmission chains. That is, traditional strain genotyping methods may not be able to determine accurately where a tuberculosis outbreak started or how it spread through a population. In this longitudinal cohort study, the researchers compare the ability of whole genome sequencing (WGS), which is rapidly becoming widely available, and traditional genotyping to provide information about a recent German tuberculosis outbreak. In a longitudinal cohort study, a population is followed over time to analyze the occurrence of a specific disease.
What Did the Researchers Do and Find?
During long-term (1997–2010) population-based molecular epidemiological surveillance (disease surveillance that uses molecular techniques rather than reports of illness) in Hamburg and Schleswig-Holstein, the researchers identified a large tuberculosis outbreak caused by M. tuberculosis isolates of the Haarlem lineage using classical strain typing. The researchers examined each of the 86 isolates from this outbreak using WGS and classical genotyping and asked whether the results of these two approaches correlated with contact tracing data (information is routinely collected about the people a patient with tuberculosis has recently met so that these contacts can be tested for tuberculosis and treated if necessary) and with the spatio-temporal distribution of outbreak cases. WGS of the isolates identified 85 single nucleotide polymorphisms (SNPs; genomic sequence variants in which single building blocks, or nucleotides, are altered) that subdivided the outbreak into seven clusters of isolates and 36 unique isolates. The WGS results showed that the first isolates of the outbreak were incorrectly clustered by classical genotyping and that one strain—the “Hamburg clone”—started expanding in 1998. Notably, the genome-based clustering patterns were in better accordance with contact tracing data and with the geographical distribution of cases than clustering patterns based on classical genotyping, and they identified eight confirmed human-to-human transmission chains that involved 31 patients and a maximum of three SNPs. Finally, the researchers used their WGS results to estimate that the Hamburg clone emerged between 1993 and 1997, shortly before the discovery of the tuberculosis outbreak through epidemiological surveillance.
What Do These Findings Mean?
These findings show that WGS can be used to identify specific strains within large tuberculosis outbreaks more accurately than classical genotyping. They also provide new information about the evolution of M. tuberculosis during outbreaks and indicate how WGS data should be interpreted in future genome-based molecular epidemiology studies. WGS has the potential to improve the molecular epidemiological surveillance and control of tuberculosis and of other infectious diseases. Importantly, note the researchers, ongoing reductions in the cost of WGS, the increased availability of “bench top” genome sequencers, and bioinformatics developments should all accelerate the implementation of WGS as a standard method for the identification of transmission chains in infectious disease outbreaks.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001387.
The World Health Organization provides information (in several languages) on all aspects of tuberculosis, including the Global Tuberculosis Report 2012
The Stop TB Partnership is working towards tuberculosis elimination; patient stories about tuberculosis are available (in English and Spanish)
The US Centers for Disease Control and Prevention has information about tuberculosis, including information on tuberculosis genotyping (some information in English and Spanish)
The US National Institute of Allergy and Infectious Diseases also has detailed information on all aspects of tuberculosis
The Tuberculosis Survival Project, which aims to raise awareness of tuberculosis and provide support for people with tuberculosis, provides personal stories about treatment for tuberculosis; the Tuberculosis Vaccine Initiative also provides personal stories about dealing with tuberculosis
MedlinePlus has links to further information about tuberculosis (in English and Spanish)
Wikipedia has a page on whole-genome sequencing (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1001387
PMCID: PMC3570532  PMID: 23424287
21.  Interdisciplinary Education to Integrate Pathology and Epidemiology: Towards Molecular and Population-Level Health Science 
American Journal of Epidemiology  2012;176(8):659-667.
In recent decades, epidemiology, public health, and medical sciences have been increasingly compartmentalized into narrower disciplines. The authors recognize the value of integration of divergent scientific fields in order to create new methods, concepts, paradigms, and knowledge. Herein they describe the recent emergence of molecular pathological epidemiology (MPE), which represents an integration of population and molecular biologic science to gain insights into the etiologies, pathogenesis, evolution, and outcomes of complex multifactorial diseases. Most human diseases, including common cancers (such as breast, lung, prostate, and colorectal cancers, leukemia, and lymphoma) and other chronic diseases (such as diabetes mellitus, cardiovascular diseases, hypertension, autoimmune diseases, psychiatric diseases, and some infectious diseases), are caused by alterations in the genome, epigenome, transcriptome, proteome, metabolome, microbiome, and interactome of all of the above components. In this era of personalized medicine and personalized prevention, we need integrated science (such as MPE) which can decipher diseases at the molecular, genetic, cellular, and population levels simultaneously. The authors believe that convergence and integration of multiple disciplines should be commonplace in research and education. We need to be open-minded and flexible in designing integrated education curricula and training programs for future students, clinicians, practitioners, and investigators.
doi:10.1093/aje/kws226
PMCID: PMC3571252  PMID: 22935517
education, public health professional; health care reform; individualized medicine; interdisciplinary communication; molecular epidemiology; pathology
22.  The Italian Hub of Population Biobanks as a Potential Tool for Improving Public Health Stewardship 
Biopreservation and Biobanking  2013;11(3):173-175.
In Italy, a country that is experiencing the decentralization of health services from central to regional level of government, the Minister of Health is proposing stewardship as a model of governance for the public health system. Stewardship favors efficiency in the policy decision-making process, based on reciprocal trust, and tends to be more ethical. The embryonic proposal to test stewardship in the field of population-based research was advanced during the launching conference Challenges and Opportunities of the Italian Hub of Population Biobanks (HIBP) held in 2012 in Rome. Resources collected by population biobanks (i.e., blood and its derivatives, and/or DNA isolated from any type of biological samples and relative associated data) have, in fact, a recognized scientific value for the investigation of links between genetics, health and life style, and epidemiological outcomes through population biobank-based studies, and are essential to planning effective and qualified interventions for public health. The current economic crisis requires a strong push to rationalize investment in health policies. In particular, population biobank-based studies require financial commitment, often of long duration, for the realization of their goals. Thus, innovative solutions to allow fast integration of scientific knowledge into political health strategy are required. During the conference in Rome, it was proposed to test the stewardship model by its application to the inter-relationship between population biobank-based studies and disease prevention. Stewardship minimizes barriers to innovation and uses information more effectively to better develop new strategies for prevention and/or treatment. In the months following the conference, the proposal was defined more clearly, and the HIBP network became a potential tool for testing and implementing this model in the Italian Public Health prevention system.
doi:10.1089/bio.2012.0064
PMCID: PMC3696929  PMID: 23840926
23.  Towards Web-based representation and processing of health information 
Background
There is great concern within health surveillance, on how to grapple with environmental degradation, rapid urbanization, population mobility and growth. The Internet has emerged as an efficient way to share health information, enabling users to access and understand data at their fingertips. Increasingly complex problems in the health field require increasingly sophisticated computer software, distributed computing power, and standardized data sharing. To address this need, Web-based mapping is now emerging as an important tool to enable health practitioners, policy makers, and the public to understand spatial health risks, population health trends and vulnerabilities. Today several web-based health applications generate dynamic maps; however, for people to fully interpret the maps they need data source description and the method used in the data analysis or statistical modeling. For the representation of health information through Web-mapping applications, there still lacks a standard format to accommodate all fixed (such as location) and variable (such as age, gender, health outcome, etc) indicators in the representation of health information. Furthermore, net-centric computing has not been adequately applied to support flexible health data processing and mapping online.
Results
The authors of this study designed a HEalth Representation XML (HERXML) schema that consists of the semantic (e.g., health activity description, the data sources description, the statistical methodology used for analysis), geometric, and cartographical representations of health data. A case study has been carried on the development of web application and services within the Canadian Geospatial Data Infrastructure (CGDI) framework for community health programs of the New Brunswick Lung Association. This study facilitated the online processing, mapping and sharing of health information, with the use of HERXML and Open Geospatial Consortium (OGC) services. It brought a new solution in better health data representation and initial exploration of the Web-based processing of health information.
Conclusion
The designed HERXML has been proven to be an appropriate solution in supporting the Web representation of health information. It can be used by health practitioners, policy makers, and the public in disease etiology, health planning, health resource management, health promotion and health education. The utilization of Web-based processing services in this study provides a flexible way for users to select and use certain processing functions for health data processing and mapping via the Web. This research provides easy access to geospatial and health data in understanding the trends of diseases, and promotes the growth and enrichment of the CGDI in the public health sector.
doi:10.1186/1476-072X-8-3
PMCID: PMC2651125  PMID: 19159445
24.  Anatomy of the Epidemiological Literature on the 2003 SARS Outbreaks in Hong Kong and Toronto: A Time-Stratified Review 
PLoS Medicine  2010;7(5):e1000272.
Weijia Xing and colleagues reviewed the published epidemiological literature on SARS and show that less than a quarter of papers were published during the epidemic itself, suggesting that the research published lagged substantially behind the need for it.
Background
Outbreaks of emerging infectious diseases, especially those of a global nature, require rapid epidemiological analysis and information dissemination. The final products of those activities usually comprise internal memoranda and briefs within public health authorities and original research published in peer-reviewed journals. Using the 2003 severe acute respiratory syndrome (SARS) epidemic as an example, we conducted a comprehensive time-stratified review of the published literature to describe the different types of epidemiological outputs.
Methods and Findings
We identified and analyzed all published articles on the epidemiology of the SARS outbreak in Hong Kong or Toronto. The analysis was stratified by study design, research domain, data collection, and analytical technique. We compared the SARS-case and matched-control non-SARS articles published according to the timeline of submission, acceptance, and publication. The impact factors of the publishing journals were examined according to the time of publication of SARS articles, and the numbers of citations received by SARS-case and matched-control articles submitted during and after the epidemic were compared. Descriptive, analytical, theoretical, and experimental epidemiology concerned, respectively, 54%, 30%, 11%, and 6% of the studies. Only 22% of the studies were submitted, 8% accepted, and 7% published during the epidemic. The submission-to-acceptance and acceptance-to-publication intervals of the SARS articles submitted during the epidemic period were significantly shorter than the corresponding intervals of matched-control non-SARS articles published in the same journal issues (p<0.001 and p<0.01, respectively). The differences of median submission-to-acceptance intervals and median acceptance-to-publication intervals between SARS articles and their corresponding control articles were 106.5 d (95% confidence interval [CI] 55.0–140.1) and 63.5 d (95% CI 18.0–94.1), respectively. The median numbers of citations of the SARS articles submitted during the epidemic and over the 2 y thereafter were 17 (interquartile range [IQR] 8.0–52.0) and 8 (IQR 3.2–21.8), respectively, significantly higher than the median numbers of control article citations (15, IQR 8.5–16.5, p<0.05, and 7, IQR 3.0–12.0, p<0.01, respectively).
Conclusions
A majority of the epidemiological articles on SARS were submitted after the epidemic had ended, although the corresponding studies had relevance to public health authorities during the epidemic. To minimize the lag between research and the exigency of public health practice in the future, researchers should consider adopting common, predefined protocols and ready-to-use instruments to improve timeliness, and thus, relevance, in addition to standardizing comparability across studies. To facilitate information dissemination, journal managers should reengineer their fast-track channels, which should be adapted to the purpose of an emerging outbreak, taking into account the requirement of high standards of quality for scientific journals and competition with other online resources.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Every now and then, a new infectious disease appears in a human population or an old disease becomes much more common or more geographically widespread. Recently, several such “emerging infectious diseases” have become major public health problems. For example, HIV/AIDS, hepatitis C, and severe acute respiratory syndrome (SARS) have all emerged in the past three decades and spread rapidly round the world. When an outbreak (epidemic) of an emerging infectious disease occurs, epidemiologists (scientists who study the causes, distribution, and control of diseases in populations) swing into action, collecting and analyzing data on the new threat to human health. Epidemiological studies are rapidly launched to identify the causative agent of the new disease, to investigate how the disease spreads, to define diagnostic criteria for the disease, to evaluate potential treatments, and to devise ways to control the disease's spread. Public health officials then use the results of these studies to bring the epidemic under control.
Why Was This Study Done?
Clearly, epidemics of emerging infectious diseases can only be controlled rapidly and effectively if the results of epidemiological studies are made widely available in a timely manner. Public health bulletins (for example, the Morbidity and Mortality Weekly Report from the US Centers from Disease Control and Prevention) are an important way of disseminating information as is the publication of original research in peer-reviewed academic journals. But how timely is this second dissemination route? Submission, peer-review, revision, re-review, acceptance, and publication of a piece of academic research can be a long process, the speed of which is affected by the responses of both authors and journals. In this study, the researchers analyze how the results of academic epidemiological research are submitted and published in journals during and after an emerging infectious disease epidemic using the 2003 SARS epidemic as an example. The first case of SARS was identified in Asia in February 2003 and rapidly spread around the world. 8,098 people became ill with SARS and 774 died before the epidemic was halted in July 2003.
What Did the Researchers Do and Find?
The researchers identified more than 300 journal articles covering epidemiological research into the SARS outbreak in Hong Kong, China, and Toronto, Canada (two cities strongly affected by the epidemic) that were published online or in print between January 1, 2003 and July 31, 2007. The researchers' analysis of these articles shows that more than half them were descriptive epidemiological studies, investigations that focused on describing the distribution of SARS; a third were analytical epidemiological studies that tried to discover the cause of SARS. Overall, 22% of the journal articles were submitted for publication during the epidemic. Only 8% of the articles were accepted for publication and only 7% were actually published during the epidemic. The median (average) submission-to-acceptance and acceptance-to-publication intervals for SARS articles submitted during the epidemic were 55 and 77.5 days, respectively, much shorter intervals than those for non-SARS articles published in the same journal issues. After the epidemic was over, the submission-to-acceptance and acceptance-to-publication intervals for SARS articles was similar to that of non-SARS articles.
What Do These Findings Mean?
These findings show that, although the academic response to the SARS epidemic was rapid, most articles on the epidemiology of SARS were published after the epidemic was over even though SARS was a major threat to public health. Possible reasons for this publication delay include the time taken by authors to prepare and undertake their studies, to write and submit their papers, and, possibly, their tendency to first submit their results to high profile journals. The time then taken by journals to review the studies, make decisions about publication, and complete the publication process might also have delayed matters. To minimize future delays in the publication of epidemiological research on emerging infectious diseases, epidemiologists could adopt common, predefined protocols and ready-to-use instruments, which would improve timeliness and ensure comparability across studies, suggest the researchers. Journals, in turn, could improve their fast-track procedures and could consider setting up online sections that could be activated when an emerging infectious disease outbreak occurred. Finally, journals could consider altering their review system to speed up the publication process provided the quality of the final published articles was not compromised.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000272.
The US National Institute of Allergy and Infectious Diseases provides information on emerging infectious diseases
The US Centers for Control and Prevention of Diseases also provides information about emerging infectious diseases, including links to other resources, and information on SARS
Wikipedia has a page on epidemiology (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
The World Health Organization has information on SARS (in several languages)
doi:10.1371/journal.pmed.1000272
PMCID: PMC2864302  PMID: 20454570
25.  Emerging issues in public health genomics 
This review highlights emerging areas of interest in public health genomics. First, recent advances in newborn screening (NBS) are described, with a focus on practice and policy implications of current and future efforts to expand NBS programs (e.g., via next-generation sequencing). Next, research findings from the rapidly progressing field of epigenetics and epigenomics are detailed, highlighting ways in which our emerging understanding in these areas could guide future intervention and research efforts in public health. We close by considering various ethical, legal and social issues posed by recent developments in public health genomics; these include policies to regulate access to personal genomic information; the need to enhance genetic literacy in both health professionals and the public; and challenges in ensuring that the benefits (and burdens) from genomic discoveries and applications are equitably distributed. Needs for future genomics research that integrates across basic and social sciences are also noted.
doi:10.1146/annurev-genom-090413-025514
PMCID: PMC4229014  PMID: 25184533
Newborn screening; epigenetics; epigenomics; bioethics; health education

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