Physical activity is higher in communities that include supportive features for walking and bicycling. In 2016, the Community Preventive Services Task Force released a systematic review of built environment approaches to increase physical activity. The results of the review recommended approaches that combine interventions to improve pedestrian and bicycle transportation systems with land use and environmental design strategies. Because the recommendation was multifaceted, the Centers for Disease Control and Prevention determined that communities could benefit from an assessment tool to address the breadth of the Task Force recommendations. The purpose of this article is to describe the systematic approach used to develop the Active Communities Tool. First, we created and refined a logic model and community theory of change for tool development. Second, we reviewed existing community-based tools and abstracted key elements  from 42 tools. The review indicated that no tool encompassed the breadth of the Community Guide recommendations for communities. Third, we developed a new tool and pilot tested its use with 9 diverse teams with public health and planning expertise. Final revisions followed from pilot team and expert input. The Active Communities Tool comprises 6 modules addressing all 8 interventions recommended by the Task Force. The tool is designed to help cross-sector teams create an action plan for improving community built environments that promote physical activity and may help to monitor progress toward achieving community conditions known to promote physical activity. The built environment influences physical activity through the pedestrian and bicycle transportation system  and both land use and environmental design .This report describes the process of developing the Active Communities Tool to implement the recommended built environment components that affect physical activity.The Active Communities Tool, developed by using a sound protocol, is available for public use. The overarching process may be applicable in other public health settings; namely, to develop an assessment tool that can help community members select intervention targets and monitor changes over time.Lack of physical activity is a leading contributor to death in the United States –3. One oWhen communities include supportive features for walking and bicycling, physical activity is higher . BarrierFollowing this, in December 2016, the Community Preventive Services Task Force (Task Force) released a recommendation on built environment approaches to increase physical activity . The TasThe Centers for Disease Control and Prevention, Division of Nutrition, Physical Activity, and Obesity (CDC) supports communities and states to implement the Community Guide built environment recommendation . TherefoThe development of ACT followed a series of steps: convening an advisory panel, reviewing existing tools, diagramming how community changes occur, and mapping candidate items for the tool to those changes to develop a draft tool.First, the authors convened an ad hoc national external advisory group to provide individual-level feedback on the development process . AdvisorSecond, to inform development of ACT, we identified relevant tools through web and PubMed searches, and from those recommended by the research team, advisory group, and pilot teams. We conducted a detailed review of 42 community-based tools on the built environment and policy characteristics that might address any of the Community Guide recommended interventions. We sought existing tools that included the following characteristics: user-friendly questions ; evidence for reliability, validity, and sensitivity to change; positive user experiences; and a format that could be easily programmed into a survey system. From these tools, we abstracted the following key elements where available: advantages, disadvantages, updates, costs, psychometrics, and candidate items. Although most reviewed tools focused on the community level, we also reviewed state-level tools with the intent of modifying them for communities. The review indicated that no tool encompassed the breadth of the Community Guide recommendations , and tooThird, we developed a first draft of ACT that contained modules based on the 8 intervention categories in the Task Force recommendation  . The draFollowing the initial draft of ACT, we met with the external national advisory group to further develop the theory of change diagrams, to identify missing questions, and to receive feedback on the initial draft of the tool. On the basis of this process and advisory group recommendations, we further revised the tool from 8 to 6 modules for ease of use . SpecifiFollowing the development of ACT, we invited 9 teams to pilot test the tool based on their knowledge, interest, or past experience as part of multidisciplinary teams to promote access and opportunity for physical activity through community, transportation, and the built environment. The 9 teams had recent experience in built environment interventions, including 5 that reported prior work on Complete Streets, 9 on master planning, 8 on Safe Routes to School, and 8 on zoning.In April 2018, a webinar introduced pilot teams to ACT and addressed questions about the pilot testing process. Teams then pilot-tested the tool. All teams completed descriptive information about their community. We asked half of the teams to complete the pedestrian, bicycle, and transit modules, and we asked the other half to complete the land use and environmental design modules . Some teMost teams used the tool to assess their own community, but a few teams working at state government agencies completed the tool to assess other communities with which they were less familiar. Seven teams assessed one municipality while the other 2 teams applied it to an entire county. The teams used the tool to assess the following locations: Bloomfield, Connecticut; city and county of Honolulu, Hawaii; Des Moines, Iowa; Duluth, Minnesota; Albuquerque, New Mexico; Tulsa, Oklahoma; Hamilton County, Tennessee; St. George City, Utah; and Tacoma, Washington. All teams included representatives from public health and planning; 8 of the 9 teams included a transit representative. In addition, some teams brought in other experts to complete the modules, such as a school representative for the school module or a parks representative for the parks and recreational facilities module. The median time it took pilot teams to complete each module ranged from 30 to 150 minutes . Almost By using the completed module data, we reviewed individual items that had missing responses, “do not know” responses, or multiple responses (when there should have only been one response) for indication of problems. We also reviewed items that lacked variability to assess whether the question should be retained. The detailed feedback provided at the end of each module provided clarifying remarks to revise items.A final call with the pilot teams provided context around the questions that needed revision or questions that were missing. During this discussion, some members of pilot teams said that the definitions provided clarity of the terms in the modules and encouraged expanding the use of them. Some members viewed the experience as an opportunity to create new partnerships, because completing the tool required multidisciplinary expertise. Several members also said that completing the tool was educational for them, in that they better understood how certain environment and policy decisions the tool asked about might affect physical activity. For example, one pilot tester wrote, “In general, considering the questions asked in the document has been helpful, and they reveal to me possible metrics against which we can measure our work. It is also a helpful reminder that the differences in jurisdictions have impacts on the accessibility, creation, and maintenance of pedestrian and bike facilities, and it points to the need for policies and procedures that speak to each other across jurisdictional boundaries.”The pilot teams provided actionable feedback in several critical areas. First, 2 pilot teams tried completing the assessment at a county level and found it challenging, because numerous municipalities were contained in the assessed county, with variations in policies and environments across jurisdictions. We added clarity to encourage users that wanted to complete the assessment for a county or region to do so separately for each of the municipalities located within the larger geographic area. Second, in some instances the yes/no questions made it impossible to capture important nuances. We therefore reviewed every question with only 2 response options and considered ways of expanding the options for improved sensitivity. Third, the feedback from several pilot teams revealed areas where regional variation in environments and contexts might not be sufficiently addressed by the tool, such as snow removal or water rights. However, to keep the modules at a reasonable length we did not expand further into these specialized topics that were not relevant in most communities.We completed a second revision of the tool based on the feedback of the pilot teams and shared this revised tool with the pilot teams. We hosted a webinar for advisors to provide additional feedback on the tool and discussed how the final version could be used. Feedback from the advisory group and other experts led to further edits to the tool.The final version of the ACT comprises 6 modules, as follows, that integrate questions about the 8 recommended intervention areas :Module 1 – Street design and connectivityModule 2 – Infrastructure to accommodate pedestrians and bicyclistsModule 3 – Public transportationModule 4 – Land use planningModule 5 – Parks and recreational facilitiesModule 6 – SchoolsIn addition to the tool, ACT includes an action planning guide to facilitate its use and to improve community environments to promote physical activity.ACT is freely available to the public for download and use . The tooA companion document, titled “A Guide for Developing an Action Plan to Improve Community Built Environments that Promote Physical Activity,” informs the action planning process specific to improving community built environments for physical activity . The “hobackground on the development of ACT,examples of disciplines to engage in when using ACT,a description of key steps to completing ACT,information, including resources, on how to develop an action plan with ACT results, andresources to develop an evaluation and remain sustainable for the long term.The tool is not a scorecard to rank communities. Rather, it is a way to assess current conditions and identify areas for action. Although promotions and programs are important components of community interventions to promote and increase physical activity, they are not addressed in these modules. The tool ascertains characteristics relevant to all intervention examples highlighted by the Community Guide , and detThe tool is also not a street-level audit. Instead, the tool focuses on the policies, plans, resources, and select community-level aspects of the built environment necessary to achieve community conditions known to promote physical activity, as described by the Community Guide . The tooAlthough the tool is meant to be comprehensive, it could still miss important community-level policies not identified through the Community Guide . For exaThe process we used to develop, pilot, refine, and finalize ACT did not include testing the questions for validity. For example, to test validity of questions on the existence of specific plans and the content in those plans, the document could be found and checked. Similarly, the report of certain policies could be cross-checked against published community codes and ordinances. The validity of other questions would be much harder to document, such as how often a specific plan was consulted or whether the community uses best practices for design for people who walk, bicycle, or use transit. Internal reliability was also not tested, which could involve having 2 people knowledgeable about the community independently complete the assessment. Practitioners who follow our example for the development of a community-based tool are encouraged to include evidence for validity when meaningful, such as documenting verification of answers from published plans or policies.Several future efforts could be applied to the tool. First, testing of the tool is needed to assess validity, reliability, and sensitivity to change over time. If psychometrically sound, it could be implemented as an evaluation tool that is used repeatedly to assess change over time. Future iterations of the tool could allow attachment of files, such as copies of policies and plans, to corroborate findings and provide some evidence of validity. Second, the revised ACT was not retested with communities. It would be beneficial to test ACT with a larger representative sample of communities. Third, the tool could be expanded to link to guidance for next steps in specific intervention areas. For example, if a community indicates that Complete Streets is not addressed in their planning documents, guidance on how to initiate action in their community and links to other resources could be prompted by their answers. Best practices and exemplary plans or policies identified by the tool could be linked and highlighted to assist others. Fourth, a scoring system could be developed to allow communities to benchmark against other communities of similar size and type .ACT  addresse


Despite being first described over 300 years ago, rickets remains an ongoing important public health concern. Rickets remains a significant and preventable cause of global morbidity and, sadly, even mortality. The most common form, nutritional rickets, is still widespread, and there are vast numbers of ongoing cases across the world . While oHochberg and Hochberg took an evolutionary approach, reflecting on the strongly conserved nature of the vitamin D receptor gene from phytoplankton to mammals, the changes in skin pigmentation with historical migration, and the natural selection disadvantages in those with severe Vitamin D deficiency, both for childhood rickets sufferers  and in pregnancy. Lessons for today’s society conclude their thought provoking article, including the role that technology and modern lifestyles play in reducing our sunlight exposure and thus exposing us to greater risk of Vitamin D deficiency. This article was penned before COVID-19, but given the number of countries across the globe that have used lockdowns and prolonged periods of home isolation to help reduce the spread of the novel coronavirus, it is even more apt to now consider how important adequate supplementation is for prevention, and how lifestyle factors play a vital part of in our risk of developing Vitamin D deficiency.The contributors to this Research Topic have demonstrated varied approaches to considering the issue of rickets. Wheeler et al. also chose to focus on the historical perspective of rickets, and how despite centuries of knowledge, nutritional rickets continues to be seen in the 21st century. While rickets was first described as a clinical entity in the 17th century, there are references to rickets in medical writings from Ancient Greek and Roman times, and skeletal changes consistent with rickets seen in skeletons from pre-industrial Europe. It is the spike in rickets seen with industrialization that provides the greatest lessons for us today, with overcrowding, increased time indoors, poor air quality and reduced calcium intake likely contributing greatly to the increase in presentations at that time. With the discovery of Vitamin D and the effectiveness of cod liver oil in the early 20th century, we now had a means of treating nutritional rickets.Wheeler et al. conclude by drawing parallels between eras, with many of the conditions that drove rickets in previous centuries echoed in today’s society, such as: reduced exposure to sunlight, the end result of increased time spent indoors; protection from the sun due to valid concerns about the risk of skin cancers; and increased migration of those with deeper skin pigmentation to subtropical and temperate climes. As with the Hochberg’s article, by exploring the mirroring of today’s risk factors with those from the past, hopefully it will encourage us as clinicians to drive public health campaigns to counteract modern changes in lifestyle with increased fortification of foodstuffs with Vitamin D, and ensuring adequate supplementation in high risk groups, particularly at times of high demand for Vitamin D such as pregnancy and infancy .Michigami and Ozono explored the fundamental molecule implicated in rickets by examining the roles of phosphate in the skeleton. They discussed the number of different ways that hypophosphatemia may be involved in the pathophysiology of rickets. Most directly, phosphate is required for the formation of hydroxyapatite, the basis of mineralization. However, phosphate is also required for apoptosis of hypertrophic chondrocytes in the growth plate, and without this there is disorganization of the process of endochondral ossification, and therefore development of rickets. Finally, the role of phosphate in regulation of gene expression was discussed, including the intriguing finding that phosphate has a role in promoting FGFR transcription, which in turn leads to increased production of FGF23. Therefore, it may be that, in some forms of hypophosphatemic rickets, impaired phosphate sensing may be driving the clinical phenotype.By contrast, Nicolescu et al. provided some clinical perspective, highlighting that even with rare forms of rickets, novel therapeutics are increasingly available to help ameliorate the biochemical, and hopefully in future, the clinical features of these conditions. They describe a case of Vitamin D resistant rickets with a heterozygous mutation in the VDR gene, and outline the treatment challenges with conventional therapy of high dose calcium and calcitriol replacement. They also note previous case reports where the use of cinacalcet, a calcimimetic, has been successful, as the skeletal changes are driven at least in part by the secondary hyperparathyroidism that results from reduced gut absorption and subsequent low serum calcium. They chose a strategy of intravenous calcium absorption, and then added cinacalcet once the calcium levels had stabilized. This led to a normalization of PTH, calcium, phosphate and ALP levels, with improved clinical state (able to ambulate) and resolution of rachitic features on Xray. Clearly there is a need for more systematic study of this approach, which given the rare nature of this condition will require the collaboration of many specialist Paediatric bone centres. This approach will also allow exploration of concerns over the use of cincalcet on the QT interval. In general, for rare bone disorders, it is only by undertaking multicentre studies that we will be able to properly evaluate novel management strategies and assess both their efficacy and safety.Finally in this series, Overall, our topic demonstrates that rickets remains an active, if not growing, area of clinical need. Promotion of public health strategies for prevention of nutritional rickets remains essential, and learning from the lessons of the past will help us improve the future for many children across the globe. Improved molecular understanding of the role of crucial molecules like phosphate will hopefully led to novel therapeutic approaches, such as we have seen with the recent development of monoclonal antibody therapy for X-Linked hypophosphatemic rickets (XLH). Finally, only by collaborating across sites and countries can we explore the outcomes of novel therapeutics in rare hereditary forms of rickets. Hopefully this Research Topic will stimulate us all, as clinicians and/or researchers, to continue to strive to eliminate nutritional rickets and improve outcomes in hereditary rickets, for the benefit of millions of young people around the world.All authors conceived the manuscript. PS wrote the preliminary draft and all authors were involved in its editing. All authors contributed to the article and approved the submitted version.CM and PS are members of the advisory board for Kyowa Kirin and have received speaker fees.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This region is the most polymorphic region of the human genome, and the levels of polymorphism seen exceed most other genes. Some of the genes have several thousand variants and are now termed hyperpolymorphic, rather than just simply polymorphic. The IPD-IMGT/HLA Database has provided a stable, highly accessible, user-friendly repository for this information, providing the scientific and medical community access to the many variant sequences of this gene system, that are critical for the successful outcome of transplantation. The number of currently known variants, and dramatic increase in the number of new variants being identified has necessitated a dedicated resource with custom tools for curation and publication. The challenge for the database is to continue to provide a highly curated database of sequence variants, while supporting the increased number of submissions and complexity of sequences. In order to do this, traditional methods of accessing and presenting data will be challenged, and new methods will need to be utilized to keep pace with new discoveries.The IPD-IMGT/HLA Database,  Over twenty years ago, the HLA Informatics group of the Anthony Nolan Research Institute, released the IMGT/HLA Database . Since tThe genes included in the IPD-IMGT/HLA Database lie within the MHC and the extended MHC region. The MHC is a region in the genome of all jawed vertebrates, and encodes core components of the immune system . In humahttp://www.ebi.ac.uk/ipd/mhc/align.php), and will also be used for the IPD-IMGT/HLASequence alignments: access to an alignment tool, which filter pre-generated alignments to the user's specification. Provides alignments at the protein, cDNA and gDNA level. The original alignment tools were developed to view a smaller number of alleles over a smaller sequence range. The increased number of new alleles and sequence coverage has necessitated the development of new faster, more interactive versions of this tool to better aid the user in selecting and viewing the alignments, these are currently been utilised by the IPD-MHC project  website.The IPD-IMGT/HLA Database receives submissions from laboratories in over 46 countries and active website uses from users in over 150 countries, see Figure Submissions are processed on a monthly basis and every 3 months, the publicly available copy of the database is updated, along with all tools and data repositories. As part of the release process, key files included in the release are sent to a third-party for quality review, and to identify potential errors in allele assignment or formatting errors in various file formats. Many of these formats were originally designed when the complexity and volume of data was much lower. With the increase in sequence complexity every effort is made to ensure sequences with complex indels or splice variants are accurately included in these formats. The inclusion of new and complex features is not always straightforward, and despite these checks, sometimes errors may be found in file formats. To help record, track and fix these, the GitHub repository provides an issue tracker that allows users to report these potential issues, which can be investigated and acted upon by the team where necessary. The existing formats are all reviewed regularly to ensure that they are still fit for purposes and suitable for the increased volume and complexity of the data. The processes for the annotation and subsequent publication of the data in multiple formats or via the website are also under constant review. At the current time the code used for the management of the database and publication of the numerous file formats is not available as part of the GitHub repository.One of the major challenges facing the IPD-IMGT/HLA Database over more recent years has been the developments in sequencing technologies . Over thA key aim is to expand the coverage of the region, to cover the remaining pseudogenes. These are often duplicated fragments of the expressed genes, and whilst their functional role can be debated, the inclusion of their sequences aid in their identification in NGS typing, where they can be mistaken for expressed alleles.With this increase in the volume of submissions, has also come an increase in the complexity of the submissions. Figure The challenge for the IPD-IMGT/HLA Database is to continue to provide a highly curated database of sequence variants, while supporting the increased number of submissions and complexity of sequences. In order to do this, traditional methods of accessing and presenting data will be challenged, and new methods utilizing new computing technologies will need to be utilized to keep pace with a shifting user focus. Recent studies , 51 havehttps://www.ebi.ac.uk/ipd/imgt/hla/.The IPD-IMGT/HLA Database can be accessed at ftp://ftp.ebi.ac.uk/pub/databases/ipd/imgt/hla/.The IPD-IMGT/HLA Database provides an FTP site for the retrieval of sequences in a number of pre-formatted files. The sequences are provided as FASTA, PIR and MSF formats, as well as an archive of the sequence alignments and a flat file formatted copy of the database. The FTP directory is available at the following address: https://github.com/ANHIG/IMGTHLA . This repository contains a branch for each database release and a Latest branch which contains the most recent files as well as all compressed archives.Both current and previous releases are archived in a Git repository and available at: hla@alleles.org.For more information about the database, queries or to subscribe to the IPD mailing lists please contact


On March 15, the SARS-Cov2 outbreak had affected more than 160,000 people worldwide and 6,000 people had died. While the World Health Organization had declared a public health emergency as early as the 30th of January, and subsequent evidence had highlighted the threat of a global pandemic, it took many more weeks for many governments and individuals to put into place and adopt precautionary measures. Some observers were therefore surprised about the discrepancy between the available official warnings and individual perceptions of the risks associated with COVID-19.When confronted with novel pathogens, humans generate several beliefs about the short- and long-term consequences of the new threat. For example, they estimate their likelihood of being exposed, getting infected or infecting others, but also the severity of the emerging event, the controllability of the epidemic, and the efficiency of psychological and physiological coping responses Rogers, . NumerouBuilding on evidence from past epidemics and three decades of research in psychology suggesting that various cognitive biases influence beliefs about life hazards, we propose that such cognitive biases have contributed to the discrepancy between early warnings about the danger of SARS-CoV-2 and slow growth of consideration for these warnings. Specifically, we focus on belief updating biases, which result from the way the human brain creates and updates beliefs about the world in the face of evidence. We critically discuss this idea with respect to other types of cognitive biases such as oversensitivity to rare events, cognitive myopia, and risk aversion.Our mind is woven by our beliefs about the world. At every moment, our beliefs define what we expect, what we perceive and what we choose. An influential theory, known as the Bayesian brain and predictive coding theory, proposes that our brain continuously develops predictive models about its environment , influenza A virus subtype H1N1 (H1N1) and Middle East respiratory syndrome (MERS-CoV). During the 2009 influenza A virus subtype H1N1 pandemic for example, epidemiologists pointed out risks of infection ranging from 11 to 19%. However, the majority of people believed that they were unlikely to get infected and to infect others . Avoiding these short-term risks could come at the expense of the long-term health benefits of containing the outbreak  and at the same time concurrently to their judgement underweight these events during decision-making  , which may correspond to an underweighting of the initial probability judgment. On the other hand side, an initial underestimation is less used to update beliefs, and could lead to neglect on the behavioral level. Here we propose that the difference in the absolute update of beliefs, and not whether these beliefs were over- or underestimations, has influenced risk assessment during early phases of the SARS-Cov-2 outbreak characterized by great uncertainty of information nurturing such updating biases (Johnson and Fowler, From an evolutionary perspective, biased beliefs represent a conundrum. On the one hand, unrealistic optimism appears to be a good coping mechanism in environments where the rewards are higher than the costs. Maintaining deflationary beliefs about risk is a kind of coping mechanism that allows individuals to protect themselves from the emotional manifestations associated with a threat, which is adaptive when the threat is distant and ambiguous. On the other hand, it can become dangerous when the costs are higher than the rewards. Our ancestral environment was strewn with great dangers and an error in judgment could quickly prove fatal. It is therefore plausible that the human brain is equipped with feedback mechanisms allowing is to adapt to situations in which an overly positive perspective would be harmful.Interestingly, unrealistic optimism bias in belief updating diminishes when there is an immediate threat in the environment (Garrett et al., The challenge today is to maintain relatively high individual risk perceptions despite the prolongation of the crisis. It has been shown that a prolonged exposure to a threat increases feelings of familiarity, progressively reducing perceived risk (Chaudhary et al., This effort should go along with more research in social and cognitive neuroscience. For example, future work in this field could shed light on how the evolution of distant to immediate health risks affects human beliefs about risk, and how the brain encodes the updating of these beliefs. It is also completely unknown how individual differences in temporal and spatial discounting moderate belief updating about risks of infection and of infecting others in the context of a pandemic and its evolution.On another level, public health policies must maintain a good level of information and explanation, so that the population upholds appropriate beliefs about the risks associated with this crisis. For example, nudge theory applications propose using cognitive biases to influence individuals' behaviors, and may play a major role in guiding worldwide health strategies against the coronavirus Thaler, . These aAs the previous health, geopolitical, and climatic cataclysms, this epidemic challenges neurocognitive models about economic power, industrial independence, or even the solidity of our healthcare systems. We call for more research to shed light on how humans around the world are adjusting their way of understanding the dangers associated with the pandemic. This is important to understand if and how this unprecedented health crisis in the 21st century opens the window into the human brain's remarkable capacities for adaptation, and to detect potential cognitive traps that can potentially hinder preparations for future waves of outbreaks and the adoption of early precautionary measures.HB wrote the first draft of the manuscript. All authors contributed to the final text.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


An incursion of an important exotic transboundary animal disease requires a prompt and intensive response. The routine analysis of up-to-date data, as near to real time as possible, is essential for the objective assessment of the patterns of disease spread or effectiveness of control measures and the formulation of alternative control strategies. In this paper, we describe the Standard Analysis of Disease Investigation (SADI), a toolbox for informing disease outbreak response, which was developed as part of New Zealand's biosecurity preparedness. SADI was generically designed on a web-based software platform, Integrated Real-time Information System (IRIS). We demonstrated the use of SADI for a hypothetical foot-and-mouth disease (FMD) outbreak scenario in New Zealand. The data standards were set within SADI, accommodating a single relational database that integrated the national livestock population data, outbreak data, and tracing data. We collected a well-researched, standardised set of 16 epidemiologically relevant analyses for informing the FMD outbreak response, including farm response timelines, interactive outbreak/network maps, stratified epidemic curves, estimated dissemination rates, estimated reproduction numbers, and areal attack rates. The analyses were programmed within SADI to automate the process to generate the reports at a regular interval (daily) using the most up-to-date data. Having SADI prepared in advance and the process streamlined for data collection, analysis and reporting would free a wider group of epidemiologists during an actual disease outbreak from solving data inconsistency among response teams, daily “number crunching,” or providing largely retrospective analyses. Instead, the focus could be directed into enhancing data collection strategies, improving data quality, understanding the limitations of the data available, interpreting the set of analyses, and communicating their meaning with response teams, decision makers and public in the context of the epidemic. Concurrent with globalisation and cross-border movements, the opportunity for the emergence of new infectious pathogens in a country has increased substantially , 2. SomeWhen trying to follow the course of an epidemic and judge the effects of control measures, the routine analysis of up-to-date data, as near to real time as possible, is essential to allow objective assessment of the patterns of disease spread, assessment of the effectiveness of control measures, and the formulation of alternative control strategies . This o and the Responses to animal health epidemics increasingly deal with “big data”. Some of the challenges of dealing with big data are encompassed in the often described four Vs: volume (relatively large datasets), velocity (the speed that new data is accumulated), variety (integration of multiple sources of data), and veracity  –10. AddiData sources for responses typically include laboratory results from traditional and molecular diagnostic methods, animal movement records sourced from national animal movement databases or farmer records, questionnaire interview data, targeted risk based sampling, and opportunistic sampling data. All these data must be underpinned by national farm or animal level demographic datasets.The key to achieving real-time assessment of ongoing control measures is the presence of a decision support tool, i.e., a data warehouse capable of integrating all data sources and with functions of automated analyses and reporting tailored to the outbreak, and available as early as possible. The components of decision support tools that can be used in animal health have been previously described , 11, 12.Mycoplasma bovis eradication programme since 2017. The aim of this paper is to describe SADI using a hypothetical FMD outbreak as an example. FMD was chosen because it is the major threat to New Zealand livestock industries due to its high contagiousness and significant economic impact. SADI could be modified and applied to other diseases, for example, HPAI or ASF.As part of New Zealand's biosecurity preparedness, a tool named real-time Standard Analysis of Disease Investigation (SADI) has been developed for performing standardised analyses during disease outbreaks. Our focus was development of a data warehouse together with a standardised set of analyses for use by epidemiologists seconded into a large FMD response, should one occur. Their usual role outside of the response may not include infectious disease epidemiology or the use of programming languages. Therefore, SADI has a simple, user-friendly interface so that the focus can be on improving data quality, understanding the limitations of the data available and interpreting the set of analyses and their meaning in the context of the epidemic. Our goal was to standardise and automate the analyses and increase the time available to interpret and communicate outbreak metrics and patterns. SADI has been used for domestic and international training of epidemiologists in biosecurity outbreaks, and in the ongoing SADI was developed as a customised project within an application, Integrated Real-time Information System (IRIS)Integration, data management, and analysis were conducted within IRIS.IRIS is a secure, web based, data management application, based on a dynamic data storage system. All data administration and processing are achieved via a web portal. Multiple portals can be added and customised according to organisational needs. Data can be accessed from any remote location with an internet connection, using any device with a browser. Data storage uses the adaptive object model , and accThe application can import and store virtually any type of data including, but not limited to text, images, vector, and raster spatial data. Data are imported into the system using industry standard formats. The framework allows third party applications to communicate with it via web services. Data can then be filtered, sorted and grouped to create customised views. Project managers have the flexibility to change and modify data schemas as their requirements change over time.The reporting engine is powered by the R statistical softwareReports can be scheduled to be automatically updated as frequently as required, for example every 24 h, to ensure that the interpretation and the assessments are made based on the most up-to-date data.For our FMD epidemic scenario, three datasets are required to perform the standardised analyses: an outbreak dataset, a tracing dataset, and a population dataset. They are linked by a common field, a unique farm identifier. For other types of diseases, additional datasets  could be included, if required. The data frame can flexibly be modified, such as accommodating additional fields or using animals as epidemiological units. The database was designed so data fields were comprehensive without redundancy, to avoid data inconsistency within the system.The outbreak dataset would be supplied from field investigations performed on confirmed infected farms . This data for individual farms can be entered into the platform directly in the field, using for example, a handheld device. The data for multiple farms can also be imported into the platform after transcribing field questionnaire data into a comma separated value (CSV) file. Alternatively, the data can be imported indirectly from an external response database. The design of the outbreak data is described in As no actual FMD outbreak data was available in New Zealand during the development of this tool, the authors simulated hypothetical outbreak data from the New Zealand Standard Model for FMD (NZSM) –17.The tracing dataset required is described in Again, as no actual infected farms were available during development of SADI, tracing data were simulated by the NZSM.The population dataset needs to be collected prior to outbreak responses and updated regularly, as part of disease preparedness. For New Zealand livestock population, the data were sourced from AgriBase® which is a commercially available, comprehensive, spatially explicit, farm level, demographic database, describing commercial and non-commercial properties holding production animals in New Zealand , 19. TheA set of standard analyses was collected by reviewing literature or gathering opinions from MPI staff. The use of these analyses is for summarising and visualising data for response or tracing teams; describing the current situation for informing intelligence and public awareness; building hypotheses about risk factors; or measuring efficiency and effectiveness of the ongoing response efforts.For each analysis, a report template composed of a variable table, data queries and an R code was created within SADI. A variable table listed a set of input parameters that were necessary for conducting this particular analysis and would accommodate parameter values entered by an analyst, as shown in This set of analyses were programmed to run at an optimal interval  so that the updated analyses would reflect new data values that were entered after the last analyses.The list of analytic reports that were collected for the use of FMD outbreak response and incorporated in SADI is shown in With a hypothetical FMD outbreak scenario, infection and detection in 51 farms in New Plymouth and South Taranaki were simulated over 5 weeks. An animated figure showing the spread of this hypothetical FMD epidemic between farms is available as a eff) was approaching 1, which had a similar indication as the EDR  enable them to understand the limitations of the data, interpret the analyses produced and provide more immediate advice to other response teams and decision makers. Highly specialised epidemiologists and in particular those with experience with data science, R coding and disease outbreak investigation can be used to refine the analyses in place. To the best of our knowledge, this is the first time such a tool was developed for the livestock population in New Zealand.M. bovis in New Zealand (2017). For the M. bovis outbreak, additional analytical reports were developed to meet the specific needs of M. bovis epidemiology and response activities. The outcomes of the tool have been communicated widely among the epidemiologists, response teams, tracing teams and decision makers, and demonstrated its value in providing timely information. Particularly, SADI has shown its advantage in timeliness as well as consistency in automatically providing up-to-date reports over 2 years with minimum resource use, in comparison with other systems or the traditional manual approaches.Although the system has not been used for real FMD data, it was tested with various simulated FMD incursion scenarios through a series of internal and external workshops involving epidemiologists and programmers. These workshops have helped improving the system, detecting any misfunctions to be fixed and discussing limitations of the system. SADI has also been used for the real outbreaks of The ready availability of near-real time graphs, maps and models present some challenges. During a large disease outbreak, staff who are unfamiliar or undertrained, or imported foreign veterinarians may not understand the implicit biases and caveats, misrepresenting the progress of the disease control operation. It is therefore important that these reports are intuitive and clear. There is also a need for cartography standards for outbreak situation reports.Also, the outbreak data would typically become available with a lag equivalent to the incubation period plus detection delay. Due to this lag, there is a varying extent of difference between real-time analyses using the incomplete data available on the date of analysis and the retrospective analyses using the complete data. Typically, this results in the underestimation of disease risks shortly before the date of analysis e.g., . The anaFor FMD, a standard set of useful analyses has been described . Even thLarge biosecurity events can occur unpredictably and can put significant, competing demands on the resources of the regulatory authority well beyond usual levels. For high impact diseases such as FMD, many countries have contingency plans in place to allow a pre-programmed set of rapid actions, and set in place a structure for decision making early in the response. This is important because the economic impacts resulting from FMD outbreaks can be enormous –36.However, even with the presence of response plans, mounting an effective response to a large animal health outbreak can be challenging. Animal health professionals and in particular epidemiologists are well-suited for many roles in disease response and are usually in short supply. To compound this, new and existing staff may have no experience of the disease being controlled, may be unfamiliar with required data sources, data collection and collation methods, or the specific analyses required. Defining the data requirement, setting up data collection strategies and defining and then performing analyses all during the response is not ideal, and is an approach likely to fail.SADI can form an integral part of the suite of intelligence tools used by epidemiologists during a response. As noted earlier, many of the data sources used in a response are common to syndromic scanning surveillance. An example would be a national farm demographic dataset which can additionally be used by an epidemic outbreak model. Multiple uses avoid development of tools for siloed applications .As the volume and complexity of infectious disease data increases, professionals must synthesise highly disparate data to facilitate communication with the public and inform decision makers . The neeThe exploration of data integration including alternative data sources is potentially valuable in augmenting the operation of the tools and improving the response efficiency. The way that data are generated has changed radically over the last 30 years, mainly as a result of the emergence of electronic methods of measuring, recording, storing, and distributing data . SyndromWhile the amount of data potentially available for integration and analysis continues to increase, the development of suitable analytical tools for converting this raw data into useful knowledge has been much slower , 38.Key themes in the development of effective visualisation and analytical tools for infectious disease epidemiology have been described . These iAdditional to these themes, analytics which are targeted to the objectives of a response and best approaches used in an animal control or eradication program are essential. For example to control an epidemic of FMD, it is essential to understand the mechanisms by which FMD virus is being spread . A substSADI with simulated outbreak datasets can be used as training materials. The authors have produced simulated FMD outbreaks using InterSpread Plus  with delThe datasets presented in this article may be available on request. Restrictions apply to the availability of these data, which were used under license for this study.All authors have contributed to the work and approved of publication.RS was employed by the company AsureQuality. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Homelessness is a complex public health issue that affects some of the most vulnerable populations in the United States. This study takes a holistic approach to better understand and analyze the multiple factors and their interconnections that contribute to the complexity of this problem. A systems analysis was conducted by utilizing the system dynamics method, which allows analyzing and comparing trends and behavior of system outcomes for different “what if” scenarios, interventions, and policy implications. Three leverage points were identified in this study to increase the effectiveness and efficiency of the current strategies to address homelessness: (1) increasing the number of affordable permanent housing units, (2) increasing the utilization of transitional housing units or shelters by the individuals experiencing homelessness, and (3) providing preventative services to at-risk populations before the onset of homelessness. Our results demonstrate that the most effective strategy is an amalgam of the solutions identified by these three leverage points. In addition, a policy analysis was conducted to study and estimate the effectiveness of various potential scenarios. This research provides data-driven and model-based insights into how decision-makers can utilize a systems approach to analyze new policy implications and create effective solutions to homelessness. Homelessness is a complex public health issue that requires a comprehensive understanding of the various factors that impact individuals’ lives. According to the United States Department of Housing and Urban Development (HUD), about 554,000 people in the country are experiencing homelessness on any given night—including 58,000 families with children . PreviouHowever, there is a lack of knowledge in the literature about how to systematically address poor access to permanent housing, remove barriers to service utilization, and better understand public health policy implications to further prevent homelessness. Hence, a system-level solution is warranted to consider a holistic approach instead of symptoms and event sequences ,12. SystIn this paper, we utilize system dynamics to model, simulate, and provide an assessment of the current state of homelessness in Long Beach, California (CA). This work offers a deeper understanding of the behavior that the system can produce in response to various policy implications and events. By utilizing system dynamics, we aim to examine: (1) how barriers in service utilization may affect the current and future states of homelessness and (2) whether effective policies for homelessness prevention can act as a catalyst in alleviating homelessness.Homelessness is a multifaceted issue that significantly affects individuals’ and families’ well-being and social/economic mobility. Scholars have found a disconnect between individuals’ needs and available services. For instance, May  found thOn a macro level, cities across the United States are addressing homelessness through a variety of housing and service programs, including transitional housing, Housing First, Permanent Supportive Housing (PSH), rapid re-housing, and shelters. Over the last decade, a shift has occurred in social service delivery, placing a greater emphasis on permanent housing solutions (such as permanent supportive housing and rapid re-housing) and less emphasis on transitional housing programs. The emerging evidence-based studies demonstrate that Housing First, PSH, and rapid re-housing programs are an effective solution to homelessness in which consumers access housing faster and are more likely to remain stably housed . DespiteOften, several factors contribute to homelessness, leading to increased complexity of this problem. For instance, at the micro level, health-related issues such as a physical or behavioral health crisis or any long-term disabling condition may place individuals at risk of homelessness . A persoAt the macro level, structural contributors to homelessness also include broader sociopolitical factors and events that can trigger homelessness as a result of economic stratification . For exaAccording to HUD’s annual Point-in-Time national count, 30–33% of individuals experiencing homelessness have been found to be mentally ill each year, over the past ten years ,23. GiveCoordinated and system-oriented approaches are necessary to provide effective solutions to homelessness. From a systems theory perspective, when systems work together, the whole is greater than the sum of the parts . SystemsIn this study, a systems perspective has been applied to model and assess the complexity and interconnections of the main factors that affect homelessness, which include: (1) permanent housing initiatives and policies for the vulnerable population experiencing homelessness, (2) the extent of temporary and transitional housing services utilization by the homeless population, and (3) factors that contribute to the risk of experiencing housing insecurity before the onset of homelessness. This work applies the system dynamics (SD) approach to examine how the limited availability of services, barriers in service utilization, and the complexity of underlying causes of homelessness may affect the current and future states of this problem, and whether integrated system-level policies can effectively reduce homelessness in communities in a sustainable manner.It is evident that homelessness is a complex problem arising in a dynamic system and cannot be solved with static methods. Dynamic systems involve continuous change to which they respond and adapt behavior over time, translating to nonlinearities in the system behavior. Hence, alleviating homelessness warrants utilizing dynamic and comprehensive approaches such as system dynamics to obtain a deeper understanding of structural elements of the system and their emerging effects, as well as the potential system responses to policy changes.System dynamics is a powerful system-analysis tool that utilizes computer simulation to replicate and model complex problems dynamically and illustrate system’s behavior change over time. What system dynamics does is uniquely beyond acknowledging the complexity of the problem. With SD models, we are able to represent the feedback process, time delays, and nonlinearities to determine the dynamic of the system. The development of a SD model involves two high-level stages, including building and testing a model to explain the reasons for the dynamic behavior of the system and designing and testing policies that could be integrated with the model to alleviate the problem at hand ,29. The System dynamics models use stocks, flows, and feedback concepts to focus our attention on implications of feedback, interconnections and causalities, delays, and accumulations over time ,14. In Sinflow and water leaving the tub through a drain represents outflow. The water accumulated in the tub represents stock that is determined by the inflow and outflow rates. In stock-and-flow maps, accumulation of stocks at a given point in time (t) is analogous to water level in the tub and equals the integration of net flow between the initial time (t0) and time t, plus the initial stock level at t0. This can be formulated as:t. In the bathtub example, if the goal is to drain the water in the tub or to keep the water level as low as possible, one solution is to improve drainage (increase the outflow rate), another solution is to control the incoming water (reduce the inflow rate), and a third solution is a combination of the two aforementioned approaches. A stock-and-flow model can be developed for homelessness in a similar manner:d represents change, transitioning into homelessness is considered inflow, and transitioning out of homelessness represents outflow at time t. By definition and mathematically, using the stock-and-flow logic, homelessness will end in a community (homeless count = 0) when the sum of outflows from homelessness exceeds the sum of inflows into homelessness for a long enough time period. This goal can be achieved by (1) increasing the outflow rate while the inflow rate remains unchanged, (2) reducing the inflow rate while the outflow rate remains unchanged, or (3) increasing the outflow rate and reducing the inflow rate concurrently.A basic example of a dynamic system is a bathtub, which is frequently used in introducing the SD approach. Water flowing through a faucet into the tub represents The SD model needs to be supported by data from the real system. Longitudinal data from homeless counts only provides information that can be used to estimate the population experiencing homelessness at a point in time (stock), which is the aggregate of all inflows and outflows of the system. However, communities with insight into a system’s inflows and outflows can develop data-driven realistic policies and objectives for permanent housing availability trends (outflow), work with policymakers on preventative measures to manage inflow (before people transition into homelessness), and develop a timeframe for eliminating homelessness. Such analysis could prove useful resource allocation and strategic planning for policymakers and social service providers.Moreover, when developing a system dynamics model, its boundaries must be clearly defined to identify all the components that should be included in the model based on the problem definition and scope ,14. There are three different types of homelessness identified in the literature: (1) transitionally homeless, who experience relatively short and less frequent stays in temporary housing services and shelters, (2) episodically homeless, who have short but more frequent transitions into and out of homelessness, and (3) chronically homeless, who have fewer but significantly long stays . As noteIn this study, we focus on the chronically homeless population as they are disproportionately represented in the majority (69%) of individuals living unsheltered on any given night . OverallSystem dynamics models heavily rely on three sources of information, including numerical data, written reports or operations manuals, and the expert opinion of key informants in the system. Data on these three main areas leads to descriptive data analysis and building the explanatory SD model, followed by policy design and evaluation . In accoThe model uses publicly available data for chronic homelessness in the city of Long Beach, CA, where chronic homelessness is defined as “An unaccompanied individual or a family with a head of household with a disabling condition who (1) has been continuously homeless for a year or more, or (2) has experienced at least four separate episodes of homelessness in the past three years, where the combined episodes total a length of 12 months or more” . HoweverIt is worth noting that in complex problems such as homelessness, where accurate data is unavailable, numerical estimations are applied. In addition, since no model can provide “complete” accuracy, attention should be paid to the trends, insights, and relative changes rather than exact numbers. Furthermore, although SD is known to be a powerful approach in modeling interdependencies and causal loops in a system, it is not possible to capture all the details and dynamic complexities in a single SD model. For example, this study only focuses on chronic homelessness, however, there are many individuals and families who are experiencing homelessness but are not considered in the census or point-in-time count data. Those who may be couch surfing with family and friends, doubling up with strangers, or those who relocate too frequently are experiencing housing insecurity but do not appear in the data and analysis of the system state.In the first stage of this study, we examined the impact of increasing the annual availably rate of the permanent housing units. This is the rate at which people in temporary housing facilities and shelters are transitioned to permanent housing units (transitioning out rate). This is analogous to increasing the outflow rate in the bathtub model. Annual transitioning out rates of 15%, 25%, and 35% were analyzed, assuming that the preventative services and temporary housing utilization rates remain unchanged. As expected, the homeless count drops incrementally by increasing the transitioning out rates driven by different housing policies and initiatives. However, the system fails to reach 0 homeless count over the simulation time window of 30 years even with a 35% annual rate of providing affordable permanent housing. Additionally, due to the constant demand for permanent housing assistance, the system is at capacity, leading to a strained and overburdened state.As policy interventions testing is implemented by means of flows in system dynamics modeling, in order to conduct a comprehensive policy experiment for the developed model, we studied how increased permanent housing availability, improvement in prevention before the onset of homelessness, and expanded utilization of temporary housing and shelters can affect the current state of homelessness in the model. In order to assess the system performance in response to different policy changes, a performance measure was developed. Time to achieve 30% drop in homeless count was applied as the performance measure of the simulation model. The results demonstrate the notable impact of improvement in prevention and public health policies on effectiveness of housing policies and initiatives as it translates to reduced and managed demand for both temporary and permanent housing units. Combined with increased utilization of the temporary housing assistance and the current affordable housing policies, the system may achieve further improved outcomes. For instance, the system achieves a 30% drop in homeless count within 16 years with 5% improvement in prevention initiatives, 5% increase in temporary housing assistance utilization, and transitioning out rate of 15%. In a different scenario, if the preventative initiatives and utilization of the temporary housing assistance improve by 10% each, while transitioning out rate is at only 15%, the system reaches a 30% drop in homeless count in 10 years. However, when the prevention initiatives remain unchanged and at their current state with no improvement, the system can never reach the 30% drop in the homeless count even by increasing the availability of affordable housing units from 5% to 15%. Moreover, in another scenario, when the improvement for prevention-focused policies and the transitioning out rate are 5% and 15% respectively, the 10% increase of the utilization rate of transitional housing only improves the time to achieve a 30% drop in homeless count by 1 year compared to the case with a 5% increase of the utilization rate of transitional housing. It is worth noting that by undertaking more aggressive prevention initiatives, the goals for alleviating homelessness can be achieved more effectively and efficiently in a much shorter time span.Although system dynamics does not remove the complexity of a problem, it helps develop a detailed map of the system with all the interconnections and identify the high leverage points in the system. The high leverage points of a system are defined as the ability to fundamentally improve the performance of a system, while simultaneously reducing the likelihood of negative unintended consequences. System dynamics accomplishes this by providing a simulation model to analyze policy implications and predict the system behavior in a data-driven quantifiable fashion.Three leverage points were identified in the system based on the simulation analysis in this study. The first one is providing permanent housing units for vulnerable populations experiencing housing insecurity. This leverage point remains as the most effective and critical solution to homelessness; however, its impact could be minimal or even futile in an overburdened system with increasing demand patterns.The second leverage point is providing preventative services to at-risk populations before the onset of homelessness. This could range from affordable or state-funded mental and physical health services, as well as rehabilitation centers for substance abuse. Providing such services could prevent or significantly delay the onset of homelessness for the vulnerable population. In addition, there are several policies that could be put in place to help an individual who loses employment to find a new job before the onset of housing insecurity due to delayed rent or mortgage payment. The emphasis of this leverage point is solely on proactive strategies to prevent transitioning into homelessness or to delay the onset of it. This could potentially lead to a balanced supply–demand system, where demand does not follow an increasing pattern and hence, meeting the demand for permanent housing for the in-need individuals could be an achievable goal. With improved public health and reduced demand, the housing policies and initiatives will be more effective in housing the homeless population. In the bathtub example, this leverage point is analogous to decreasing the inflow rate. It is worth noting that the prevention policies in this study do not consider a specific area and the emphasis is on the dynamic of prevention rather than a particular focus.The third leverage point identified in this study is the utilization of available shelters and temporary housing services by the population experiencing housing insecurity. The Long Beach Continuum of Care identifies three paths to permanent housing, of which two reflect utilization of emergency shelters and transitional housing . AvailabIdentifying and addressing these barriers can increase the utilization of the intermediate services, which at the system-level can effectively accelerate the transition to permanent housing and reduce homelessness.Homelessness is a complex issue for many communities and requires adaptive and system-level approaches to intervention and measurement. Maintaining adequate income and secure housing can be extremely challenging for many households. Managing outflow through housing policies and approaches such as Housing First (HF) has been the main focus of the current solutions to homelessness in major urban cities and communities of the United States. Unfortunately, these initiatives have not sustainably reduced homelessness in many communities. However, if combined with preventative strategies oriented around public health to avert the transition of vulnerable populations into homelessness and support at-risk populations, it can lead to significant results in alleviating homelessness. New policies for affordable and accessible housing, discharge planning from incarceration, subsidized mental health support, domestic violence protection services, and subsidized preventative healthcare plans are some examples of targeted preventative initiatives that can decrease the rate of transitioning from an “at-risk of homelessness” state into homelessness. Although the causal relationship between the prevention-oriented approaches and homelessness is intuitively understood, there is still a lack of sufficient research on the depth and breadth of downstream impacts of the prevention initiatives to address homelessness. This work is a call to action for further research to study the effectiveness and efficiency of specific prevention-centered policies from a systems perspective that takes into account the structural causal loops and interconnections within the system.Providing affordable and accessible housing remains the main focus of the solutions to end homelessness, however, our results demonstrate that if it is accompanied with improvements in prevention-centered policies, the outcome could be substantial. Strategies with increased rates of transitioning the population residing at temporary housing units and shelter into permanent housing units can have a significant impact on the state of homelessness only if combined with strong prevention initiatives. Furthermore, improving the process of timely identification and transitioning of the housing insecure population to temporary housing can increase the efficiency of these policies for permanently transitioning homeless individuals out of homelessness.Canada, Australia, and the United Kingdom are among some of the countries that have instituted wide-scale preventative efforts to reduce homelessness. For example, Canada is at the beginning stages of the move towards a stronger focus on prevention, aided by a social innovation agenda to identify, design, test, and evaluate preventative interventions to determine the most effective approaches . In AustThe findings in this work contribute to several implications for public health policies. Similar to results from Goodman and colleagues , who fouIn terms of limitations, to capture a clearer picture of the system, we need to understand how permanent housing services are being utilized to transition individuals from the “housing insecure” state to the “housed” state for each community. The model can then be modified based on these findings as the process may differ from one locality to another depending on the available services and processes developed by local agencies. Additionally, the model boundaries can be expanded beyond a specific region to capture relocations across county and state boundaries. Also, this study does not account for policy resistance and push-back from different subsystems and agencies. Based on the underlying structure developed in this study, future work can focus on identifying and obtaining a better understanding of the sources of policy resistance for different policy implications to develop more effective and sustainable solutions. Another limitation of this work is that the developed system dynamics model collectively analyzes the improvement in preventative initiatives and their impact and does not differentiate between various prevention programs and their extent. Moreover, the model developed in this study is a high-level model aimed to provide insights from a systems perspective into the effectiveness of the solutions to homelessness. However, this imposes a trade-off; although studying policy implications in smaller and limited-scope models is prudent, it may lead to underestimating less evident system structures in large complex problems. To address this challenge, once we fully understand the results provided by a small model, a more detailed model can be developed to further analyze undelineated policy implications. Lastly, we would like to emphasize that to precisely portray the system elements that play a decisive role in alleviating homelessness, the model construction process should include several model extension and simplification phases.With system dynamics models, we are able to represent the feedback process, time delays, and nonlinearities to determine the system’s behavior and patterns subject to new policy changes, which could help better understand how different policies and strategies in the real system would affect the at-risk population or individuals experiencing homelessness. This study is the first step in modeling and studying the impact of various high-level policy implications and their combined effect on homelessness. Further work is needed to expand the model and study the impact of various prevention policies and initiatives related to the contributing factors to homelessness.


The cognitive interpersonal model was outlined initially in 2006 in a paper describing the valued and visible aspects of anorexia nervosa . In 2013, we summarised many of the cognitive and emotional traits underpinning the model . In this paper, we describe in more detail the perpetuating aspects of the model, which include the inter- and intrapersonal related consequences of isolation, depression, and chronic stress that accumulate in the severe and enduring stage of the illness. Since we developed the model, we have been using it to frame research and development at the Maudsley. We have developed and tested interventions for both patients and close others, refining the model through iterative cycles of model/intervention development in line with the Medical Research Council (MRC) framework for complex interventions. For example, we have defined the consequences of living with the illness on close others  and characterised the intense emotional reactions and behaviours that follow. For the individual with an eating disorder, these counter-reactions can allow the eating disorder to become entrenched. In addition, the consequent chronic stress from starvation and social pain set in motion processes such as depression, neuroprogression, and neuroadaptation. Thus, anorexia nervosa develops a life of its own that is resistant to treatment. In this paper, we describe the underpinnings of the model and how this can be targeted into treatment. The Medical Research Council has described a framework for the process of development of complex interventions . This inThe first iteration of the cognitive interpersonal model for AN outlined core valued and visible maintaining factors of the illness  2]; the; the2]; This next iteration of the model describes in more detail the development of the severe and enduring form of AN . CurrentIn this paper, we consider in more depth these three domains that contribute to the development of the severe enduring form of illness. Difficulties with interpersonal relationships predispose to the development of AN and are also secondary consequences of the disorder, contributing to the perseverance of the illness. Social anxiety is a common precursor of eating disorders . In someFurthermore, people with AN are more likely to report early maladaptive schema (pervasive negative themes regarding the self and one’s relationship with others ) and difProblems in social cognition also can arise as secondary consequences of starvation. Anomalies in social cognition are most pronounced in the acute phase of illness and are less marked after recovery . The anoA mental health professional with lived experience of AN used one word to epitomize the illness: “isolation” . HoweverThe anxiety engendered by the overt “ill state” and the frustration caused by the resistance to implement the obvious solution “to eat” fuels a profound and mixed emotional reaction in both professionals (nurses on inpatient units)  and famiThese diverse reactions can cause divisions amongst family members. Some family members shoulder an overly high burden, whilst others become disempowered and disengaged. Aspects of the caregiving experience are summarised in systematic reviews . High peCarers’ own practical and emotional reactions to the illness can cause harm to the family unit as relationship ruptures occur in response to accommodating and enabling behaviours  or diverThe protracted course of the illness and the entanglement between eating and social function means that close others have the potential to remediate these difficulties. Therefore, it is important that carers and close others are involved across the lifespan and not excluded from the treatment process. Clinicians explain this exclusion through concerns around confidentiality, but this is considered a misinterpretation of the law .A hypothesis that follows from the cognitive interpersonal model is that the toxic consequences that accrue from the isolation and loneliness of an eating disorder can be ameliorated by skills training for family members or close others across the lifespan . ImproviThese materials explain how the patients’ primary and secondary difficulties in social cognition make relationships difficult. For example, the reduced facial expressivity of eating disorder patients ,24 makesThe three basic elements of carer skill-sharing interventions include:(1) Psychoeducation about the illness and framing patient presentation within the cognitive–interpersonal model, highlighting predisposing, precipitating, and perpetuating factors.(2) Information about how carers might be able to moderate and mould the energy and insight from their own emotional reactions to foster a calm, compassionate, and collaborative context (a life skill that they can role model to the person with the eating disorder). (3) Introduction to effective support and behaviour change skills such as motivational interviewing, the use of risk-taking experiments, and exposure to fear . Interventions based on this model have been delivered in a range of different formats including workshops and guided self-help interventions with individual or group support. An improved understanding about the illness reduces carer distress and burden ,45,47,48Treatment for individuals with AN based on the cognitive interpersonal model, the Maudsley Model of Anorexia Treatment for Adults (MANTRA) ,55, alsoThe repeated patterns of behaviour that underpin the development of AN, such as avoiding high caloric, highly palatable foods, becomes habitual. Initially, these behaviours are initiated to achieve a specific goal and are reinforced as they are positively rewarding. With daily repetition, the actions become automatic and entrenched until they are activated with no conscious effort in response to a stimulus or cue . A recenIn addition, fear and/or disgust responses to food represents a key challenge to weight restoration . People Exposure is the standard treatment for fear learning. The underlying mechanism involves developing new learning to the threatening stimulus (as opposed to habituation to anxiety) and updating the fear pathways in the brain ,68. TherOther training approaches developed to target risk factors show some promise in proof-of-concept studies. These include cognitive remediation approaches that focus on cultivating a flexible, big picture style of thinking , cognitiAnother maintaining factor in the model is the impact of chronic starvation leading to anhedonia and accentuating existing co-morbidities. Emotional distress is common as both a predisposition and a secondary consequence that perpetuates the illness ,78,79. TDepressive symptomatology may follow a persistent trajectory over the lifetime, independently from eating disorder symptoms ,84. ApprAnxiety traits are also linked to eating disorders. Obsessive–compulsive personality traits, obsessive–compulsive disorders, and anxiety ,93,94 ofIn a longitudinal study, the neural correlates of disordered eating and obsessive–compulsive disorder at age 14 included an increase in grey matter volume in the orbitofrontal cortex, the right dorsolateral prefrontal cortex, and the ventral striatum . HoweverThe chronic stress profile associated with enduring AN  is similTreatments targeting nutritional recovery are less effective for improving mood ,122,123.Interest in pharmacological approaches is starting to increase, as summarised in a recent review . There iAlthough not the topic of this paper, given the similarities between staging models for other psychiatric disorders , it may In this latest iteration of the cognitive interpersonal model, we have described treatments targeting modifiable elements. Increasing social connection through encouraging a collaborative inclusive approach towards recovery, by increasing the knowledge and skills of family members, decreases the need for high-intensity care (day or inpatient) and reduces carer burden and patient isolation ,51,136. However, it is too early for this model to be ossified. The field of eating disorders has been starved of resources for research, and so the evidence is limited. Nevertheless, we think that by using this framework in order to identify targets and by using high-quality randomised controlled trials, we will be able to develop more effective treatments through an iterative process.