scholarly journals PocketAID: The Pocket Atlas of Infectious Diseases Mobile Application

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Bonnie Gale ◽  
Lauren Charles ◽  
Hamid Mansoor ◽  
Chen-Yeou YU
Keyword(s):  
Infectious Disease ◽  
Decision Support ◽  
Infectious Diseases ◽  
Situational Awareness ◽  
Disease Risk ◽  
World Health ◽  
Risk Level ◽  
Demographic Information ◽  
Disease Information ◽  
Android App

ObjectiveThe Pocket Atlas of Infectious Diseases (PocketAID) mobile application developed at Pacific Northwest National Laboratory (PNNL) provides infectious disease education and decision support offline for an enhanced personal situational risk assessment anywhere in the world. The app integrates a user’s location, demographic information, and infectious disease data to present the user with important information including personalized, calculated risk level. PocketAID features a global disease distribution map and epidemiological curve of country-based case counts by year. Filter options allow users to customize disease lists available to aid in situational awareness. PocketAID, first of its kind, is being developed for offline decision support use by Department of Defense’s Defense Threat Reduction Agency (DTRA).IntroductionThere are a wide variety of available web-based apps, such as CDC’s Epidemic Information Exchange, that provide infectious disease information and disease distribution [1]. Publicly available, online data can be used to inform a user of general risks based on disease distribution maps and case count data. Unfortunately, each app contains different aspects of the data, which is often represented in different ways and incompatible formats. This heterogeneity can overwhelm a user with confusing information making it difficult to interpret or gain valuable insight into their own situational risk in a specified location. In addition, online resources do not filter information based on the user’s current location or situational needs and, therefore, reduces the value of information a user may be interpreting.However, information formatted and represented appropriately in a single app could be used to better understand an individual’s situational infectious disease risk. In addition, this information may further educate a user based on a situation or incident to prevent disease spread, especially in higher risk populations. To accomplish these goals, PNNL has developed an offline, Android app that provides the user with simple, easy to understand filterable global infectious disease information integrated with their location to provide personalized situational health risk and decision support in the field.MethodsThis prototype mobile app was a product of PNNL’s Biosurveillance Application Competition, sponsored by DTRA. Our implementation of this prototype consisted of two parallel efforts: data collection and Android app development.Data. Infectious disease information was collected from CDC, WHO, Biosurveillance Resource Directory, and Analytics for Investigation of Disease Outbreaks websites [1-4]. Visualization feature data for global disease distribution and the case count curves was collected from CDC, WHO, and ECDC websites [1, 2, 5]. Data used for the disease filter and risk level warning features were associated to the collected infectious disease information and user inputted demographic information.Application. The prototype app was built using Android operating system. Information about diseases, e.g., transmission mode, symptoms, properties, was stored in SQLite database that was imported into the phone at install time to provide offline information access. We used OSMDroid, an open source project, for map and location services. Downloaded map tiles made zoomable, interactive maps available offline.ResultsPocketAID biosurveillance Android app was targeted for active duty service members, although deemed useful to a much broader audience. Given the various challenges that service members can face during deployment, such as no connectivity in remote areas, the app provides full functionality offline. The general purpose of PocketAID is to provide a user with infectious disease situational awareness and decision support, not be used as an analytic tool to test, treat, or diagnose disease.Upon launch, the user is shown their location on a zoomable, interactive map and a list of diseases that are known to be present in their current country (detected automatically using the device’s GPS). The user can change their location by selecting a country from the location dropdown menu, filtering the populated list of diseases. The user can further filter diseases by disease attributes: symptoms, transmission, and properties. Clicking on a disease redirects the user to a page with more details about the disease, an interactive map of global disease distribution, and epidemiological curve displaying case counts by year for selected disease in selected country.The user can input basic demographic information (i.e., age, gender, occupation, and pregnancy status) in the settings page of the app, which then enables an automated assessment of disease risk. Since specific diseases pose an increased risk to certain groups of people, the app can personalize the user’s risk level. In other words, if a user’s demographic information matches a disease’s risk groups, the user is shown a warning alert.The app was awarded second prize in the competition by judges from across the government for its perceived benefit to biosurveillance, innovation and originality, quality of user experience, and long-term value and sustainability.ConclusionsThe PocketAID provides global disease distribution on a zoomable map, infectious disease background information, disease case counts, offline capabilities, and diseases filtered by the location. This educational app offers a situational health risk assessment for the user through accessing infectious disease information with a disease attribute filter, personalized risk level warning, and user’s GPS or selected location to help improve decision support and reduce situational risk. The app was vetted by domain experts across the US Government, who found it to be useful and valuable.References1. Centers for Disease Control and Prevention [Internet]. Atlanta (GA): U.S. Department of Health & Human Services; [cited 2018 Aug 17]. Available from: https://www.cdc.gov/.2. World Health Organization [Internet]. Geneva (Switzerland): World Health Organization; c2018 [cited 2018 Aug 17]. Available from: http://www.who.int/gho/en/.3. Margevicius KJ, Generous N, Taylor-McCabe KJ, et. al. Advancing a Framework to Enable Characterization and Evaluation of Data Streams Useful for Biosurveillance. PLOS ONE 2014;9(1): e83730. doi: 10.1371/journal.pone.00837304. Analytics for Investigation of Disease Outbreaks [Internet]. Los Alamos (NM): Los Alamos National Security, LLC for the U.S Dept. of Energy's NNSA; c2018 [cited 2018 Aug 17]. Available from: https://aido.bsvgateway.org/.5. Surveillance Atlas of Infectious Diseases [Internet]. Solna (Sweden): European Centre for Disease Prevention & Control; c2018 [cited 2018 Aug 17]. Available from: http://atlas.ecdc.europa.eu/public/index.aspx.

scholarly journals SARS: Political Pathology of the First Post-Westphalian Pathogen

2003 ◽  
Vol 31 (4) ◽  
pp. 485-505 ◽  
Author(s):  
David P. Fidler
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
The United States ◽  
First Century ◽  
World Health ◽  
Health Security ◽  
The World ◽  
Twenty First Century ◽  
The Stability ◽  
Health Organization

In March 2003, the world discovered, again, that I humanity's battle with infectious diseases continues. The twenty-first century began with infectious diseases, especially HIV/AIDS, being discussed as threats to human rights, economic development, and national security. Bioterrorism in the United States in October 2001 increased concerns about pathogenic microbes. The global outbreak of severe acute respiratory syndrome (SARS) in the spring of 2003 kept the global infectious disease challenge at the forefront of world news for weeks. At its May 2003 annual meeting, the World Health organization (WHO) asserted that SARS is “the first severe infectious disease to emerge in the twenty-first century” and “poses a serious threat to global health security, the livelihood of populations, the functioning of health systems, and the stability and growth of economies.”

Triage documentation–based decision support to improve infectious disease risk screening and mitigate exposure

2016 ◽  
Vol 44 (9) ◽  
pp. 1063-1065
Author(s):  
Grace Barajas ◽  
Teresa Zembower ◽  
Christina Silkaitis ◽  
Julie Brennan ◽  
Eileen Brassil ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Decision Support ◽  
Disease Risk ◽  
Risk Screening

scholarly journals The winding road to health: A systematic scoping review on the effect of geographical accessibility to health care on infectious diseases in low- and middle-income countries

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244921
Author(s):  
Fleur Hierink ◽  
Emelda A. Okiro ◽  
Antoine Flahault ◽  
Nicolas Ray
Keyword(s):  
Infectious Disease ◽  
Health Care ◽  
Infectious Diseases ◽  
Disease Burden ◽  
Disease Risk ◽  
Surveillance Systems ◽  
Middle Income ◽  
Middle Income Countries ◽  
Geographical Accessibility ◽  
Physical Accessibility

Background Geographical accessibility to healthcare is an important component of infectious disease dynamics. Timely access to health facilities can prevent disease progression and enables disease notification through surveillance systems. The importance of accounting for physical accessibility in response to infectious diseases is increasingly recognized. Yet, there is no comprehensive review of the literature available on infectious diseases in relation to geographical accessibility to care. Therefore, we aimed at evaluating the current state of knowledge on the effect of geographical accessibility to health care on infectious diseases in low- and middle-income countries. Methods and findings A search strategy was developed and conducted on Web of Science and PubMed on 4 March 2019. New publications were checked until May 28, 2020. All publication dates were eligible. Data was charted into a tabular format and descriptive data analyses were carried out to identify geographical regions, infectious diseases, and measures of physical accessibility among other factors. Search queries in PubMed and Web of Science yielded 560 unique publications. After title and abstract screening 99 articles were read in full detail, from which 64 articles were selected, including 10 manually. Results of the included publications could be broadly categorized into three groups: (1) decreased spatial accessibility to health care was associated with a higher infectious disease burden, (2) decreased accessibility was associated to lower disease reporting, minimizing true understanding of disease distribution, and (3) the occurrence of an infectious disease outbreak negatively impacted health care accessibility in affected regions. In the majority of studies, poor geographical accessibility to health care was associated with higher disease incidence, more severe health outcomes, higher mortality, and lower disease reporting. No difference was seen between countries or infectious diseases. Conclusions Currently, policy-makers and scientists rely on data collected through passive surveillance systems, introducing uncertainty on disease estimates for remote communities. Our results highlight the need for increasing integration of geographical accessibility measures in disease risk modelling, allowing more realistic disease estimates and enhancing our understanding of true disease burden. Additionally, disease risk estimates could be used in turn to optimize the allocation of health services in the prevention and detection of infectious diseases.

scholarly journals Susceptibility of Host Immunity to Infectious Diseases in the Spacecraft Environment

2019 ◽  
Vol 34 (s1) ◽  
pp. s170-s170
Author(s):  
Vienna Tran
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Disease Risk ◽  
Current Knowledge ◽  
Inflammatory Marker ◽  
Genetic Mutation ◽  
Host Immunity ◽  
Technological Advancement ◽  
Cell Counts ◽  
Long Duration

Introduction:The principles of Disaster and Emergency Medicine are applicable beyond the confines of planet Earth. With the accelerating rate of climate change, natural disasters, and overpopulation, as well as the innate human appetite for knowledge and technological advancement, there has recently been an increased interest in the prospect of long-duration spaceflight with a view to colonize extra-terrestrial bodies, such as Mars. However, there is a need to understand the risk of adverse medical events in the hostile environment of space. For example, previous incidences of infectious disease and immune dysregulation during a short-term mission have threatened to jeopardize the crew dynamic and the mission objectives. The risk of infectious diseases to the astronaut is one of the many knowledge gaps that must be addressed before long-duration flight is considered.Aim:To review how spaceflight impacts an astronaut’s in-flight susceptibility to infectious diseases.Methods:Research was guided by the Microbiology section of the NASA Human Research Roadmap Program. Search terms in the University of Adelaide Library Search database collection included: “infectious diseases + spaceflight,” “astronaut + immunity,” “analog,” and “inflammatory marker.”Results:Studies that have been conducted in-flight and on Earth demonstrate that both the astronaut and the microbe are affected by spaceflight. Stress, microgravity, and the isolated nature of the spacecraft have been found to compromise the immunity of the astronaut, as shown by reduced T cell counts and increased viral shedding of dormant viruses. Microbes have demonstrated rapid adaptation mechanisms, including genetic mutation and increased virulence.Discussion:This paper identifies a significant need for further research into host immunity during spaceflight to mitigate infectious disease risk. It is recommended that in-situ studies and terrestrial space analogs are most effective and that current knowledge on the principles of wilderness and expedition medicine be applied where possible.

scholarly journals Measured voluntary avoidance behaviour during the 2009 A/H1N1 epidemic

2015 ◽  
Vol 282 (1818) ◽  
pp. 20150814 ◽  
Author(s):  
Jude Bayham ◽  
Nicolai V. Kuminoff ◽  
Quentin Gunn ◽  
Eli P. Fenichel
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Disease Transmission ◽  
Disease Risk ◽  
Critical Role ◽  
Avoidance Behaviour ◽  
World Health ◽  
Swine Flu ◽  
Mixing Patterns ◽  
Health Organization

Managing infectious disease is among the foremost challenges for public health policy. Interpersonal contacts play a critical role in infectious disease transmission, and recent advances in epidemiological theory suggest a central role for adaptive human behaviour with respect to changing contact patterns. However, theoretical studies cannot answer the following question: are individual responses to disease of sufficient magnitude to shape epidemiological dynamics and infectious disease risk? We provide empirical evidence that Americans voluntarily reduced their time spent in public places during the 2009 A/H1N1 swine flu, and that these behavioural shifts were of a magnitude capable of reducing the total number of cases. We simulate 10 years of epidemics (2003–2012) based on mixing patterns derived from individual time-use data to show that the mixing patterns in 2009 yield the lowest number of total infections relative to if the epidemic had occurred in any of the other nine years. The World Health Organization and other public health bodies have emphasized an important role for ‘distancing’ or non-pharmaceutical interventions. Our empirical results suggest that neglect for voluntary avoidance behaviour in epidemic models may overestimate the public health benefits of public social distancing policies.

scholarly journals Infectious disease outbreaks: how online clinical decision support could help

2018 ◽  
Vol 5 (4) ◽  
pp. 218-220
Author(s):  
Kieran Walsh
Keyword(s):  
Infectious Disease ◽  
Decision Support ◽  
Infectious Diseases ◽  
Clinical Decision Support ◽  
Mobile Apps ◽  
Disease Outbreaks ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Clinical Decision Support Tool

This paper describes an evaluation of how doctors might use an online clinical decision support tool to improve the care that they would provide to patients with infectious disease and what features they would expect in such a clinical decision support tool. Semistructured interviews were conducted by telephone with doctors to evaluate the utility of a clinical decision support tool in helping them to improve the care that they would provide to patients with infectious disease and to assess the features that they would value in such a tool. The doctors were primarily interested in how they could use the tool to improve care. They were short of time and so needed to be able to access the content that they needed really quickly. They expected content that was both evidence based and current, and they used a range of devices to access the content. They used desktops, laptops, mobiles and sometimes mobile apps. Doctors view the utility of clinical decision support in the management of rare infectious diseases from a number of perspectives. However, they primarily see utility in the tools as a result of their capacity to improve clinical practice in infectious diseases.

scholarly journals Risk Factors for Infectious Diseases in Urban Environments of Sub-Saharan Africa: A Systematic Review and Critical Appraisal of Evidence

2019 ◽  
Vol 4 (4) ◽  
pp. 123 ◽  
Author(s):  
Matthew R. Boyce ◽  
Rebecca Katz ◽  
Claire J. Standley
Keyword(s):  
Infectious Disease ◽  
Risk Factors ◽  
Infectious Diseases ◽  
Disease Risk ◽  
Urban Environments ◽  
Health Systems Strengthening ◽  
Sub Saharan Africa ◽  
Original Research ◽  
African Countries ◽  
Sub Saharan

Our world is rapidly urbanizing. According to the United Nations, between 1990 and 2015, the percent of the world’s population living in urban areas grew from 43% to 54%. Estimates suggest that this trend will continue and that over 68% of the world’s population will call cities home by 2050, with the majority of urbanization occurring in African countries. This urbanization is already having a profound effect on global health and could significantly impact the epidemiology of infectious diseases. A better understanding of infectious disease risk factors specific to urban settings is needed to plan for and mitigate against future urban outbreaks. We conducted a systematic literature review of the Web of Science and PubMed databases to assess the risk factors for infectious diseases in the urban environments of sub-Saharan Africa. A search combining keywords associated with cities, migration, African countries, infectious disease, and risk were used to identify relevant studies. Original research and meta-analyses published between 2004 and 2019 investigating geographical and behavioral risk factors, changing disease distributions, or control programs were included in the study. The search yielded 3610 papers, and 106 met the criteria for inclusion in the analysis. Papers were categorized according to risk factors, geographic area, and study type. The papers covered 31 countries in sub-Saharan Africa with East Africa being the most represented sub-region. Malaria and HIV were the most frequent disease focuses of the studies. The results of this work can inform public health policy as it relates to capacity building and health systems strengthening in rapidly urbanizing areas, as well as highlight knowledge gaps that warrant additional research.

Health and Infectious Disease

2008 ◽  
pp. 581-591
Author(s):  
Gian Luca Burci
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
World Health Organization ◽  
International Cooperation ◽  
Legal Aspects ◽  
World Health ◽  
International Dimension ◽  
The World ◽  
Health Organization

This article reviews the main international and institutional legal aspects of cooperation in the fight against the plague of infectious diseases. It makes a particular reference to the role of the World Health Organization (WHO) and other agencies of the UN system. This article underscores the intrinsically international dimension of the realization of the essential importance of international cooperation.

scholarly journals Facilitating the Use of Epidemiological Models for Infectious Disease Surveillance

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Alina Deshpande ◽  
Kristin Margevicius
Keyword(s):  
Infectious Disease ◽  
Decision Support ◽  
Infectious Diseases ◽  
Disease Surveillance ◽  
Disease Modeling ◽  
National Laboratory ◽  
Decision Makers ◽  
Specific Information ◽  
Epidemiological Models ◽  
Infectious Disease Surveillance

Objective1. To develop a comprehensive model characterization frameworkto describe epidemiological models in an operational context.2. To apply the framework to characterize “operational” modelsfor specific infectious diseases and provide a web-based directory,the biosurveillance analytics resource directory (BARD) to the globalinfectious disease surveillance community.IntroductionEpidemiological modeling for infectious disease is useful fordisease management and routine implementation needs to befacilitated through better description of models in an operationalcontext. A standardized model characterization process that allowsselection or making manual comparisons of available models andtheir results is currently lacking. Los Alamos National Laboratory(LANL) has developed a comprehensive framework that can be usedto characterize an infectious disease model in an operational context.We offer this framework and an associated database to stakeholders ofthe infectious disease modeling field as a tool for standardizing modeldescription and facilitating the use of epidemiological models. Such aframework could help the understanding of diverse models by variousstakeholders with different preconceptions, backgrounds, expertise,and needs, and can foster greater use of epidemiological models astools in infectious disease surveillance.MethodsWe define, “operational” as the application of an epidemiologicalmodel to a real-world event for decision support and can be used byexperts and non-experts alike. The term “model” covers three majortypes, risk mapping, disease dynamics and anomaly detection.To develop a framework for characterizing epidemiological modelswe collected information via a three-step process: a literature searchof model characteristics, a review of current operational infectiousdisease epidemiological models, and subject matter expert (SME)panel consultation. We limited selection of operational models tofive infectious diseases: influenza, malaria, dengue, cholera andfoot-and-mouth disease (FMD). These diseases capture a varietyof transmission modes, represent high or potentially high epidemicor endemic burden, and are well represented in the literature. Wealso developed working criteria for what attributes can be used tocomprehensively describe an operational model including a model’sdocumentation, accessibility, and sustainability.To apply the model characterization framework, we built theBARD, which is publicly available (http://brd.bsvgateway.org).A document was also developed to describe the usability requirementsfor the BARD; potential users (and non-users) and use cases areformally described to explain the scope of use.Results1. Framework for model characterizationThe framework is divided into six major components (Figure 1):Model Purpose, Model Objective, Model Scope, Biosurveillance(BSV) goals, Conceptual Model and Model Utility; each of whichhas several sub-categories for characterizing each aspect of a model.2. Application to model characterizationModels for five infectious diseases—cholera, malaria, influenza,FMD and dengue were characterizedusing the framework and are included in the BARD database. Ourframework characterized disparate models in a streamlined fashion.Model information could be binned into the same categories, allowingeasy manual comparison and understanding of the models.3. Development of the BARDOur model characterization framework was implemented into anactionable tool which provides specific information about a modelthat has been systematically categorized. It allows manual categoryto-category comparison of multiple models for a single disease andwhile the tool does not rank models it provides model information ina format that allows a user to make a ranking or an assessment of theutility of the model.ConclusionsWith the model characterization framework we hope to encouragemodel developers to start describing the many features of their modelsusing a common format. We illustrate the application of the frameworkthrough the development of the BARD which is a scientific andnon-biased tool for selecting an appropriate epidemiological modelfor infectious disease surveillance. Epidemiological models are notnecessarily being developed with decision makers in mind. This gapbetween model developers and decision makers needs to be narrowedbefore modeling becomes routinely implemented in decision making.The characterization framework and the tool developed (BARD) area first step towards addressing this gap.Keywordsepidemiological models; database; decision support

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