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This paper argues that a lonely death is, by definition, a bad death and that society as a whole, as well as individuals in society are obligated to assure a certain degree of well‐being, flourishing, or care among and for fellow individuals. Individuals can then be said to have a right against dying a lonely death. Such a right has corresponding duties. The paper further specifies what such duties may entail based on what individuals may need on their deathbed, specifically focusing on the need for human touch. Assuming that human touch might indeed be needed by some individuals in order to avoid a lonely death, the paper explores potential implications from a public health perspective, particularly during infectious disease outbreaks such as COVID. [ABSTRACT FROM AUTHOR]

The pandemic of novel coronavirus disease 2019 (COVID-19) has been a severe threat to public health. The policy of close contract tracing quarantine is an effective strategy in controlling the COVID-19 epidemic outbreak. In this paper, we developed a mathematical model of the COVID-19 epidemic with confirmed case-driven contact tracing quarantine, and applied the model to evaluate the effectiveness of the policy of contact tracing and quarantine. The model is established based on the combination of the compartmental model and individual-based model simulations, which results in a closed-form delay differential equation model. The proposed model includes a novel form of quarantine functions to represent the number of quarantine individuals following the confirmed cases every day and provides analytic expressions to study the effects of changing the quarantine rate. The proposed model can be applied to epidemic dynamics during the period of community spread and when the policy of confirmed cases-driven contact tracing quarantine is efficient. We applied the model to study the effectiveness of contact tracing and quarantine. The proposed delay differential equation model can describe the average epidemic dynamics of the stochastic-individual-based model, however, it is not enough to describe the diverse response due to the stochastic effect. Based on model simulations, we found that the policy of contact tracing and quarantine can obviously reduce the epidemic size, however, may not be enough to achieve zero-infectious in a short time, a combination of close contact quarantine and social contact restriction is required to achieve zeroinfectious. Moreover, the effect of reducing epidemic size is insensitive to the period of quarantine, there are no significant changes in the epidemic dynamics when the quarantine days vary from 7 to 21 days. [ABSTRACT FROM AUTHOR]

Building fair, equitable, and beneficial partnerships between institutions collaborating in research in low- and middle-income countries (LMIC) and high-income countries (HIC) has become an integral part of research capacity building in global health in recent years. In this paper, we offer an example of an academic collaboration between the University of California Los Angeles, Center for Health Policy and Research (UCLA CHPR) and the University of Philippines, Manila, College of Public Health (UPM CPH) that sought to build an equitable partnership between research institutions. The partnership was built on a project to build capacity for research and produce data for policy action for the prevention and care of non-communicable diseases (NCDs) through primary healthcare in the Philippines. The specific objectives of the project were to: (1) locally adapt the Primary Care Assessment Tool for the Philippines and use the adapted tool to measure facility-level primary care delivery, (2) conduct focus group discussions (FGDs) to gather qualitative observations regarding primary care readiness and capacity, and (3) conduct a comprehensive population-based health survey among adults on NCDs and prior healthcare experience. We describe here the progression of the partnership between these institutions to carry out the project and the elements that helped build a stronger connection between the institutions, such as mutual goal setting, cultural bridging, collaborative teams, and capacity building. This example, which can be used as a model depicting new directionality and opportunities for LMIC-HIC academic partnerships, was written based on the review of shared project documents, including study protocols, and written and oral communications with the project team members, including the primary investigators. The innovation of this partnership includes: LMIC-initiated project need identification, LMIC-based funding allocation, a capacity-building role of the HIC institution, and the expansion of scope through jointly offered courses on global health. [ABSTRACT FROM AUTHOR]

Background The term 'commercial determinants of health' (CDOH) is increasingly focussing attention upon the role of tobacco, alcohol and food and beverage companies and others—as important drivers of non-communicable diseases (NCDs). However, the CDOH do not seem to be clearly represented in the most common social determinants of health (SDOH) frameworks. We review a wide range of existing frameworks of the determinants of health to determine whether and how commercial determinants are incorporated into current SDOH thinking. Methods We searched for papers and non-academic reports published in English since 2000 describing influences on population health outcomes. We included documents with a formal conceptual framework or diagram, showing the integration of the different determinants. Results Forty-eight framework documents were identified. Only one explicitly included the CDOH in a conceptual diagram. Ten papers discussed the commercial determinants in some form in the text only and fourteen described negative impacts of commercial determinants in the text. Twelve discussed positive roles for the private sector in producing harmful commodities. Overall, descriptions of commercial determinants are frequently understated, not made explicit, or simply missing. The role of commercial actors as vectors of NCDs is largely absent or invisible in many of the most influential conceptual diagrams. Conclusions Our current public health models may risk framing public health problems and solutions in ways that obscure the role that the private sector, in particular large transnational companies, play in shaping the broader environment and individual behaviours, and thus population health outcomes. [ABSTRACT FROM AUTHOR]

Objective. To summarize the results of research conducted in Costa Rica in which mathematical and statistical methods were implemented to study the transmission dynamics of mosquito-borne diseases. Methods. Three articles with mathematical and statistical analysis on vector-borne diseases in Costa Rica were selected and reviewed. These papers show the value and relevance of using different quantitative methods to understand disease dynamics and support decision-making. Results. The results of these investigations: 1) show the impact on dengue case reports when a second pathogen emerges, such as chikungunya; 2) recover key parameters in Zika dynamics using Bayesian inference; and 3) show the use of machine learning algorithms and climatic variables to forecast the dengue relative risk in five different locations. Conclusions. Mathematical and statistical modeling enables the description of mosquito-borne disease transmission dynamics, providing quantitative information to support prevention/control methods and resource allocation planning. [ABSTRACT FROM AUTHOR]

While bioethicist Arthur Caplan claims that "The Nazi analogy is equivalent to dropping a nuclear bomb in ethical battles about science and medicine", we claim that such total exclusion of this analogy is equally problematic. Our analysis builds on Roberto Esposito's conceptualization of immunitas and communitas as key elements of biopolitics. Within public health theories and practices there is an inherent tension between exclusion (immunitas) and inclusion (communitas) forces. Taking the immunitas logic to the extreme, as National Socialist medicine did in the name of securing the German race, is a constant danger that needs to be taken seriously into consideration when discussing public health policies. The tension between the silencing of the Holocaust in bioethical debates on one side, and the persistent use of National Socialist medicine metaphors, on the other hand, is the focus of this paper. By delving into the meanings and the implications of this two‐edged discourse, we argue that comparing post‐war bioethics with pre‐war medical practices from a biopolitical perspective has the potential to depict a more nuanced account of continuities and discontinuities in bioethics. [ABSTRACT FROM AUTHOR]

The role of evidence and expertise in policy-making has been of interest to public health professionals and political scientists alike. The public health community often sees its efforts as part of a linear knowledge transfer process and tends to blame itself for inadequate communication or translation of its arguments to policy-makers' language when its efforts fail. Political science, especially theories of the policy process, offer alternative perspectives to explain the success or failure of experts' preferred policy goals. This paper focuses on the concept of epistemic communities (groups of experts with a common policy goal derived from their shared knowledge) in policy-making, drawing on examples from the field of health technology assessment in Europe. By combining the parsimony and the central focus on experts of the linear knowledge transfer model with the recognition of complexity of political science, the epistemic communities concept provides a useful structure for the public health community to analyze its efforts to influence policy. [ABSTRACT FROM AUTHOR]

Perinatal mental health problems, experienced by 15-20% of women, are a significant public health issue associated with adverse effects among childbearing women; yet only 20-25% receive adequate treatment. There has been a recent proliferation of intensive perinatal day treatment programs in the United States. To meet this need in the greater Philadelphia area, we introduce Mother Baby Connections (MBC), an innovative interdisciplinary, attachment-focused, intensive, outpatient perinatal mental health program recently launched at Drexel University. The purpose of this paper is to (1) present an overview of MBC, its theoretical framework for services, and its evidence-based components, highlighting the unique factors that differentiate this program from traditional outpatient treatment, and (2) present clinical outcome data utilizing scores from reliable and valid scales, including enrollment to discharge outcomes from 20 months of MBC operation. In sum, outcomes for 20 predominantly minority women with complete measures showed significant improvements in maternal depression symptom severity, maternal functioning, birth trauma symptoms, perceived stress, parenting stress, and emotional regulation. Effect sizes were medium to large (i.e., 0.42-2.00). We conclude that MBC is a viable model for tailored intensive outpatient treatment to foster maternal mental health and functioning during the perinatal period. [ABSTRACT FROM AUTHOR]

Background: Making inferences about measles distribution patterns at small area level is vital for more focal targeted intervention. However, in statistical literature, the analysis of originally collected data on one resolution with the purpose to make inferences on a different level of spatial resolution is referred to as the misalignment problem. In Namibia the measles data were available in aggregated format at regional level for the period 2005 to 2014. This leads to a spatial misalignment problem if the purpose is to make decisions at constituency level. Moreover, although data on risk covariates of measles could be obtained at constituency level, they were not available each year between 2005 and 2014. Thus, assuming that covariates were constant through the study period would induce measurement errors which might have effects on the analysis results. This paper presents a spatio-temporal model through a multi-step approach in order to deal with misalignment and measurement error. Methods: For the period 2005–2014, measles data from the Ministry of Health and Social Services (MoHSS) were analysed in two steps. First, a multi-step approach was applied to correct spatial misalignment in the data. Second, a classical measurement error model was fitted to account for measurement errors. The time effects were specified using a nonparametric formulation for the linear trend through first order random walk. An interaction between area and time was modelled through type I and type II interaction structures. Results: The study showed that there was high variation in measles risk across constituencies and as well as over the study period (2005–2014). Furthermore, the risk of measles was found to be associated with (i) the number of people aged between 0 and 24 years, (ii) the percentages of women aged 15–49 with an educational level more than secondary, (iii) the percentages of children age 12–23 months who received measles vaccine, (iv) the percentages of malnourished children under 5 years, and (vi) the measles cases for each previous year. Conclusion: The study showed some of the determinants of measles risk and revealed areas at high risk through disease mapping. Additionally, the study showed a non-linear temporal distribution of measles risk over the study period. Finally, it was shown that ignoring the measurement errors may yield misleading results. It was recommended that group and geographically targeted intervention, prevention and control strategies can be tailored on the basis these findings. [ABSTRACT FROM AUTHOR]

Mathematical models become an important and popular tools to understand the dynamics of the disease and give an insight to reduce the impact of malaria burden within the community. Thus, this paper aims to apply a mathematical model to study global stability of malaria transmission dynamics model with logistic growth. Analysis of the model applies scaling and sensitivity analysis and sensitivity analysis of the model applied to understand the important parameters in transmission and prevalence of malaria disease. We derive the equilibrium points of the model and investigated their stabilities. The results of our analysis have shown that if R0≤1, then the disease-free equilibrium is globally asymptotically stable, and the disease dies out; if R0>1, then the unique endemic equilibrium point is globally asymptotically stable and the disease persists within the population. Furthermore, numerical simulations in the application of the model showed the abrupt and periodic variations. [ABSTRACT FROM AUTHOR]

This paper aims to provide an analytical insight on the current state of knowledge on gender-based violence among people with disabilities, a topic where the level of data is relatively low. We briefly discuss the current research on: (a) the prevalence, risk factors and the theoretical approaches for gender-based violence among people with disabilities. (b) Service provision among people with disabilities who experience gender-based violence. (c) We also highlight areas where further research is required, the applicable theoretical approaches and provide an example on how Sweden is attempting to bridge this knowledge gap through implementing the Disability and Intimate-partner violence project (DIS-IPV) project. [ABSTRACT FROM AUTHOR]

The impacts of climate on health and wellbeing occur in time and space and through a range of indirect, complicated mechanisms. This diversity of pathways has major implications for national public health planning and influence on interventions that might help to mitigate and adapt to rapidly changing environmental conditions, nationally and internationally. This paper draws upon evidence from public health and adverse impact studies across climate science, hydrology, agriculture, public health, and the social sciences. It presents a conceptual model to support decision-making by recognizing both the proximal and distal pathways from climate-induced environmental change to national health and wellbeing. The proximal and distal pathways associated with food security, migration and mobility illustrate the diverse climate change influences in different geographic locations over different timescales. We argue that greater realization and articulation of proximal and distal pathways should radically alter how climate change is addressed as a national and international public health challenge. [ABSTRACT FROM AUTHOR]

Background: Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools.Objective: This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings.Conclusion: Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making. [ABSTRACT FROM AUTHOR]

In this paper, we propose and analyze a mathematical model for the dynamics of visceral leishmaniasis with seasonality. Our results show that the disease-free equilibrium is globally asymptotically stable under certain conditions when R0, the basic reproduction number, is less than unity. When R0 > 1 and under some conditions, then our system has a unique positive ω-periodic solution that is globally asymptotically stable. Applying two controls, vaccination and treatment, to our model forces the system to be non-periodic, and all fractions of infected populations settle on a very low level. [ABSTRACT FROM AUTHOR]

Background: Echinococcosis is a complex zoonosis that has domestic and sylvatic lifecycles, and a range of different intermediate and definitive host species. The complexities of its transmission and the sparse evidence on the effectiveness of control strategies in diverse settings provide significant challenges for the design of effective public health policy against this disease. Mathematical modelling is a useful tool for simulating control packages under locally specific transmission conditions to inform optimal timing and frequency of phased interventions for cost-effective control of echinococcosis. The aims of this review of 30 years of Echinococcus modelling were to discern the epidemiological mechanisms underpinning models of Echinococcus granulosus and E. multilocularis transmission and to establish the need to include a human transmission component in such models. Methodology/Principal Findings: A search was conducted of all relevant articles published up until July 2012, identified from the PubMED, Web of Knowledge and Medline databases and review of bibliographies of selected papers. Papers eligible for inclusion were those describing the design of a new model, or modification of an existing mathematical model of E. granulosus or E. multilocularis transmission. A total of 13 eligible papers were identified, five of which described mathematical models of E. granulosus and eight that described E. multilocularis transmission. These models varied primarily on the basis of six key mechanisms that all have the capacity to modulate model dynamics, qualitatively affecting projections. These are: 1) the inclusion of a ‘latent’ class and/or time delay from host exposure to infectiousness; 2) an age structure for animal hosts; 3) the presence of density-dependent constraints; 4) accounting for seasonality; 5) stochastic parameters; and 6) inclusion of spatial and risk structures. Conclusions/Significance: This review discusses the conditions under which these mechanisms may be important for inclusion in models of Echinococcus transmission and proposes recommendations for the design of dynamic human models of transmission. Accounting for the dynamic behaviour of the Echinococcus parasites in humans will be key to predicting changes in the disease burden over time and to simulate control strategies that optimise public health impact. [ABSTRACT FROM AUTHOR]

Background: This paper will determine whether expanding Insite (North America's first and only supervised injection facility) to more locations in Canada such as Montreal, cost less than the health care consequences of not having such expanded programs for injection drug users. Methods: By analyzing secondary data gathered in 2012, this paper relies on mathematical models to estimate the number of new HIV and Hepatitis C (HCV) infections prevented as a result of additional SIF locations in Montreal. Results: With very conservative estimates, it is predicted that the addition of each supervised injection facility (up-to a maximum of three) in Montreal will on average prevent 11 cases of HIV and 65 cases of HCV each year. As a result, there is a net cost saving of CDN$0.686 million (HIV) and CDN$0.8 million (HCV) for each additional supervised injection site each year. This translates into a net average benefit-cost ratio of 1.21: 1 for both HIV and HCV. Conclusions: Funding supervised injection facilities in Montreal appears to be an efficient and effective use of financial resources in the public health domain. [ABSTRACT FROM AUTHOR]

Identification of miRNA-disease association is a fundamental challenge in human health clinic. However, the known miRNA-disease associations are rare and experimental verification methods are expensive and time-consuming. Therefore, there is a strong incentive to develop computational methods. In this paper, we calculate the similarity score for each miRNAs pair by integrating miRNA functional similarity and miRNA family information. We use the disease phenotype similarity data to construct the disease similarity network. Then we introduce a new miRNA-disease association prediction method (NETwork Group Similarity, NetGS) to explore the global network similarity, capturing the relationship between the disease and other diseases, the similarity between the potential disease-related miRNA and other miRNAs. Finally based on the consistency of diffusion profiles we get the miRNA-disease association scores. NetGS is tested by the leave-one-out cross validation and achieves an AUC value of 0.8450, which improves the prediction accuracy. NetGS can also be applied to solve the new miRNA-disease association and obtain reliable accuracy. Moreover, we use NetGS to predict new causing miRNAs of three cancers including breast cancer, lung cancer and Hepatocellular cancer. And the top predictions have been confirmed in the online databases. The encouraging results indicate that NetGS might play an essential role for future scientific research. [ABSTRACT FROM AUTHOR]

There is a growing interest in English-speaking jurisdictions, including Australia, North America, Canada, the United Kingdom and New Zealand, about the prevention of sexual abuse perpetrated by children against other children. The aim of this review was to identify opportunities for research, policy and practice which could enhance the prevention agenda relating to the perpetration of sexual abuse by children through conducting a Critical Interpretive Synthesis. Eleven electronic databases were searched in the period from 22 April to 23 May 2013 and included: SocINDEX, Social Services Abstracts, Applied Social Sciences Index and Abstracts, Family and Society Studies Worldwide, Project Muse, PsychINFO, Family and Society Plus, Jstor, Expanded Academic ASAP, Web of Science and Google Scholar. Key individual journals were also searched, including Child Abuse and Neglect and the Journal of Interpersonal Violence, as well as the grey literature. The search was guided by the research question: How could the prevention agenda relating to sexual abuse perpetrated by children be enhanced? The systematic literature search yielded 3323 titles, and 34 of these papers were included in the final synthesis. The authors identified five domains operating in the evidence base: characteristics, causes, communications, interventions and treatments. A synthesising construct emerged from the review: prevention-enhancing interactions. This construct referred to the potential for enhancing the prevention agenda which exists as the evidence domains interact with one another, and with the public health model of prevention. The authors consider this review to be a timely contribution to the current agenda pertaining to sexual abuse perpetrated by children. It provides researchers, policy makers and practitioners in the field with an evidence-informed conceptualisation of opportunities for enhancing prevention work. [ABSTRACT FROM AUTHOR]

Background and Objective: Conscientious objection to abortion, clinicians’ refusal to perform legal abortions because of their religious or moral beliefs, has been the subject of increasing debate among bioethicists, policymakers, and public health advocates in recent years. Conscientious objection policies are intended to balance reproductive rights and clinicians’ beliefs. However, in practice, clinician objection can act as a barrier to abortion access–impinging on reproductive rights, and increasing unsafe abortion and related morbidity and mortality. There is little information about conscientious objection from a medical or public health perspective. A quantitative instrument is needed to assess prevalence of conscientious objection and to provide insight on its practice. This paper describes the development of a survey instrument to measure conscientious objection to abortion provision. Methods: A literature review, and in-depth formative interviews with stakeholders in Colombia were used to develop a conceptual model of conscientious objection. This model led to the development of a survey, which was piloted, and then administered, in Ghana. Results: The model posits three domains of conscientious objection that form the basis for the survey instrument: 1) beliefs about abortion and conscientious objection; 2) actions related to conscientious objection and abortion; and 3) self-identification as a conscientious objector. Conclusions: The instrument is intended to be used to assess prevalence among clinicians trained to provide abortions, and to gain insight on how conscientious objection is practiced in a variety of settings. Its results can inform more effective and appropriate strategies to regulate conscientious objection. [ABSTRACT FROM AUTHOR]

Background: Systematic reviews and a network meta-analysis show home safety education with or without the provision of safety equipment is effective in promoting poison prevention behaviours in households with children. This paper compares the cost-effectiveness of home safety interventions to promote poison prevention practices.Methods: A probabilistic decision-analytic model simulates healthcare costs and benefits for a hypothetical cohort of under 5 year olds. The model compares the cost-effectiveness of home safety education, home safety inspections, provision of free or low cost safety equipment and fitting of equipment. Analyses are conducted from a UK National Health Service and Personal Social Services perspective and expressed in 2012 prices.Results: Education without safety inspection, provision or fitting of equipment was the most cost-effective strategy for promoting safe storage of medicines with an incremental cost-effectiveness ratio of £2888 (95 % credible interval (CrI) £1990-£5774) per poison case avoided or £41,330 (95%CrI £20,007-£91,534) per QALY gained compared with usual care. Compared to usual care, home safety interventions were not cost-effective in promoting safe storage of other household products.Conclusion: Education offers better value for money than more intensive but expensive strategies for preventing medicinal poisonings, but is only likely to be cost-effective at £30,000 per QALY gained for families in disadvantaged areas and for those with more than one child. There was considerable uncertainty in cost-effectiveness estimates due to paucity of evidence on model parameters. Policy makers should consider both costs and effectiveness of competing interventions to ensure efficient use of resources. [ABSTRACT FROM AUTHOR]

Abstract: Public health monitoring for solitary elderly people must be implemented in a particularly economic way because of their low-income status. The aim of this paper is to propose a model-based method combined with conventional reasoning methods such as multiple regression and the boosting strategy. The role of model-based reasoning is to generate secondary situational information from activity data gathered at home. Current health condition information is then provided as part of an activity-based smart management system for health monitoring. Only one activity sensor per house is considered. In this paper, we also discuss how the Korean government has actually applied this method in smart-care services for more than ten thousand solitary elderly people. The experiments are conducted based on the u-care system, which is composed of an activity sensor connected to a remote server using a wireless sensor network. The remote server includes multi-agents which analyze and diagnose current health conditions. [Copyright &y& Elsevier]

Background: Mathematical models of infection that consider targeted interventions are exquisitely dependent on the assumed mixing patterns of the population. We report on a pilot study designed to assess three different methods (one retrospective, two prospective) for obtaining contact data relevant to the determination of these mixing patterns. Methods: 65 adults were asked to record their social encounters in each location visited during 6 study days using a novel method whereby a change in physical location of the study participant triggered data entry. Using a cross-over design, all participants recorded encounters on 3 days in a paper diary and 3 days using an electronic recording device (PDA). Participants were randomised to first prospective recording method. Results: Both methods captured more contacts than a pre-study questionnaire, but ascertainment using the paper diary was superior to the PDA (mean difference: 4.52 (95% CI 0.28, 8.77). Paper diaries were found more acceptable to the participants compared with the PDA. Statistical analysis confirms that our results are broadly consistent with those reported from large-scale European based surveys. An association between household size (trend 0.14, 95% CI (0.06, 0.22), P < 0.001) and composition (presence of child 0.37, 95% CI (0.17, 0.56), P < 0.001) and the total number of reported contacts was observed, highlighting the importance of sampling study populations based on household characteristics as well as age. New contacts were still being recorded on the third study day, but compliance had declined, indicating that the optimal number of sample days represents a trade-off between completeness and quality of data for an individual. Conclusions: The study's location-based reporting design allows greater scope compared to other methods for examining differences in the characteristics of encounters over a range of environments. Improved parameterisation of dynamic transmission models gained from work of this type will aid in the development of more robust decision support tools to assist health policy makers and planners. [ABSTRACT FROM AUTHOR]

This paper provides an overview of mathematical modeling in public health policy and recommends the teaching of mathematical models in other fields, like law and undergraduate political science studies. First, I describe various facets of public health in terms of their scope and goals. The complex nature of public health lends way to a description of mathematical modeling and the role it can serve. Various mathematical solution concepts are also provided, including the SIR model, reproductive number, and game theory. Finally, I explain why knowledge of simple models is beneficial for students in pre-professional programs in law and political science. While these models are a cornerstone for public policy and health, their analogies are not as common within undergraduate studies in law and political science. This research aims to support extensions of these models. [ABSTRACT FROM AUTHOR]

Background: Mycobacterium ulcerans is know to cause the Buruli ulcer. The association between the ulcer and environmental exposure has been documented. However, the epidemiology of the ulcer is not well understood. A hypothesised transmission involves humans being bitten by the water bugs that prey on mollusks, snails and young fishes. Methods: In this paper, a model for the transmission of Mycobacterium ulcerans to humans in the presence of a preventive strategy is proposed and analysed. The model equilibria are determined and conditions for the existence of the equilibria established. The model analysis is carried out in terms of the reproduction number R0. The disease free equilibrium is found to be locally asymptotically stable for R0 < 1. The model is fitted to data from Ghana. Results: The model is found to exhibit a backward bifurcation and the endemic equilibrium point is globally stable when R0 > 1. Sensitivity analysis showed that the Buruli ulcer epidemic is highly influenced by the shedding and clearance rates of Mycobacterium ulcerans in the environment. The model is found to fit reasonably well to data from Ghana and projections on the future of the Buruli ulcer epidemic are also made. Conclusions: The model reasonably fitted data from Ghana. The fitting process showed data that appeared to have reached a steady state and projections showed that the epidemic levels will remain the same for the projected time. The implications of the results to policy and future management of the disease are discussed. [ABSTRACT FROM AUTHOR]

Background: Infant and child mortality rates are among the health indicators of importance in a given community or country. It is the fourth millennium development goal that by 2015, all the United Nations member countries are expected to have reduced their infant and child mortality rates by two-thirds. Uganda is one of those countries in Sub-Saharan Africa with high infant and child mortality rates, therefore it is important to use sound statistical methods to determine which factors are strongly associated with child mortality which in turn will help inform the design of intervention strategiesMethods: The Uganda Demographic Health Survey (UDHS) funded by USAID, UNFPA, UNICEF, Irish Aid and the United Kingdom government provides a data set which is rich in information on child mortality or survival. Survival analysis techniques are among the well-developed methods in Statistics for analysing time to event data. These methods were adopted in this paper to examine factors affecting under-five child mortality rates (UMR) in Uganda using the UDHS data for 2011 in R and STATA software.Results: Results obtained by fitting the Cox-proportional hazard model with frailty effects and drawing inference using both the frequentists and Bayesian approaches at 5 % significance level, show evidence of the existence of unobserved heterogeneity at the household level but there was not enough evidence to conclude the existence of unobserved heterogeneity at the community level. Sex of the household head, sex of the child and number of births in the past one year were found to be significant. The results further suggest that over the period of 1990-2015, Uganda reduced its UMR by 52 % .Conclusion: Uganda has not achieved the MDG4 target but the 52 % reduction in the UMR is a move in the positive direction. Demographic factors (sex of the household head) and Biological determinants (sex of the child and number of births in the past one year) are strongly associated with high UMR. Heterogeneity or unobserved covariates were found to be significant at the household but insignificant at the community level. [ABSTRACT FROM AUTHOR]

Background: The Public Health Responsibility Deal (RD) in England is a public-private partnership involving voluntary pledges between government, industry, and other organisations to improve public health by addressing alcohol, food, health at work, and physical activity. This paper analyses the RD physical activity (PA) pledges in terms of the evidence of their potential effectiveness, and the likelihood that they have motivated actions among organisations that would not otherwise have taken place. Methods: We systematically reviewed evidence of the effectiveness of interventions proposed in four PA pledges of the RD, namely, those on physical activity in the community; physical activity guidelines; active travel; and physical activity in the workplace. We then analysed publically available data on RD signatory organisations' plans and progress towards achieving the physical activity pledges, and assessed the extent to which activities among organisations could be attributed to the RD. Results: Where combined with environmental approaches, interventions such as mass media campaigns to communicate the benefits of physical activity, active travel in children and adults, and workplace-related interventions could in principle be effective, if fully implemented. However, most activities proposed by each PA pledge involved providing information or enabling choice, which has limited effectiveness. Moreover, it was difficult to establish the extent of implementation of pledges within organisations, given that progress reports were mostly unavailable, and, where provided, it was difficult to ascertain their relevance to the RD pledges. Finally, 15 % of interventions listed in organisations' delivery plans were judged to be the result of participation in the RD, meaning that most actions taken by organisations were likely already under way, regardless of the RD. Conclusions: Irrespective of the nature of a public health policy to encourage physical activity, targets need to be evidence-based, well-defined, measurable and encourage organisations to go beyond business as usual. RD physical activity targets do not adequately fulfill these criteria. [ABSTRACT FROM AUTHOR]

Background: Annually since 2010, the University of Wisconsin Population Health Institute and the Robert Wood Johnson Foundation have produced the County Health Rankings--a "population health checkup" for the nation's over 3,000 counties. The purpose of this paper is to review the background and rationale for the Rankings, explain in detail the methods we use to create the health rankings in each state, and discuss the strengths and limitations associated with ranking the health of communities. Methods: We base the Rankings on a conceptual model of population health that includes both health outcomes (mortality and morbidity) and health factors (health behaviors, clinical care, social and economic factors, and the physical environment). Data for over 30 measures available at the county level are assembled from a number of national sources. Z-scores are calculated for each measure, multiplied by their assigned weights, and summed to create composite measure scores. Composite scores are then ordered and counties are ranked from best to worst health within each state. Results: Health outcomes and related health factors vary significantly within states, with over two-fold differences between the least healthy counties versus the healthiest counties for measures such as premature mortality, teen birth rates, and percent of children living in poverty. Ranking within each state depicts disparities that are not apparent when counties are ranked across the entire nation. Discussion: The County Health Rankings can be used to clearly demonstrate differences in health by place, raise awareness of the many factors that influence health, and stimulate community health improvement efforts. The Rankings draws upon the human instinct to compete by facilitating comparisons between neighboring or peer counties within states. Since no population health model, or rankings based off such models, will ever perfectly describe the health of its population, we encourage users to look to local sources of data to understand more about the health of their community. [ABSTRACT FROM AUTHOR]

The g-formula and agent-based models (ABMs) are 2 approaches used to estimate causal effects. In the current issue of the Journal, Murray et al. (Am J Epidemiol. 2017;186(2):131-142) compare the performance of the g-formula and ABMs to estimate causal effects in 3 target populations. In their thoughtful paper, the authors outline several reasons that a causal effect estimated using an ABM may be biased when parameterized from at least 1 source external to the target population. The authors have addressed an important issue in epidemiology: Often causal effect estimates are needed to inform public health decisions in settings without complete data. Because public health decisions are urgent, epidemiologists are frequently called upon to estimate a causal effect from existing data in a separate population rather than perform new data collection activities. The assumptions needed to transport causal effects to a specific target population must be carefully stated and assessed, just as one would explicitly state and analyze the assumptions required to draw internally valid causal inference in a specific study sample. Considering external validity in important target populations increases the impact of epidemiologic studies. [ABSTRACT FROM AUTHOR]

In this commentary, I review the insights that have been gained using Rothman's sufficient cause model (Am J Epidemiol. 1976;104(6):587-592). Discussion pertains to the relations of the model to similar conceptualizations in other fields of study, the advances and extensions that have been made to the model since the paper's publication, and its relation to questions of actual causation, along with questions concerning the use of the model in the future of epidemiology. [ABSTRACT FROM AUTHOR]

In this paper we review two recent paradigmatic shifts and consider how a two-way flow in innovation has been critical to the emergence of new thinking and new practices. The first area relates to our understanding of the nature of public health systems and the shift from a medical paradigm to a more holistic paradigm which emphasises the social, economic and environmental origins of ill-health and looks to these as key arenas in which to tackle persistent inequalities in populations' health experiences. In respect of this paradigmatic shift, it is argued, developing countries were in advance of their more developed counterparts. Specifically, the Alma Ata Declaration and the Primary Health Care Approach which was central to its implementation pre-figured elements of what was to be called in developed countries The New Public Health such as the need for greater community involvement and recognition of the importance of other sectors in determining health outcomes. But this paradigmatic shift added a new complexity to our understanding which made the identification of appropriate policy responses increasingly difficult. However, a parallel shift was taking place in the cognate field of operational research/systems analysis (OR/ SA) which was adding greatly to our ability to analyse and to identify key points of intervention in complex systems. This led to the emergence of new techniques for problem structuring which overcame many of the limitations of formal mathematical models which characterised the old paradigm. In this paradigmatic shift developed countries have led the way, specifically in the new fields of Community Operational Research and Operational Research for Development, but only by drawing strongly on the experience and philosophies to be found in developing countries. [ABSTRACT FROM AUTHOR]

Background: Schistosomiasis japonica, caused by infection with Schistosoma japonicum, is still recognized as a major public health problem in the Peoples' Republic of China. Mathematical modelling of schistosomiasis transmission has been undertaken in order to assess and project the effects of various control strategies for elimination of the disease. Seasonal fluctuations in transmission may have the potential to impact on the population dynamics of schistosomiasis, yet no model of S. japonicum has considered such effects. In this paper, we characterize the transmission dynamics of S. japonicum using a modified version of Barbour's model to account for seasonal variation (SV), and investigate the effectiveness of the control strategy adopted in Liaonan village of Xingzi county, Jiangxi Province. Methods: We use mathematical tools for stability analysis of periodic systems and derive expressions for the basic reproduction ratio of S. japonicum in humans; we parameterise such expressions with surveillance data to investigate the conditions for persistence or elimination of the disease in the study village. We perform numerical simulations and parametric sensitivity analysis to understand local transmission conditions and compare values of the basic reproductive ratio with and without seasonal fluctuations. Results: The explicit formula of the basic reproduction ratio for the SV-modified Barbour's model is derived. Results show that the value of the basic reproduction ratio, R0, of Liaonan village, Xingzi county is located between 1.064 and 1.066 (very close to 1), for schistosomiasis transmission during 2006 to 2010, after intensification of control efforts. Conclusions: Our modified version of the Barbour model to account for seasonal fluctuations in transmission has the potential to provide better estimations of infection risk than previous models. Ignoring seasonality tends to underestimate R0 values albeit only marginally. In the absence of simultaneous R0 estimations for villages not under control interventions (such villages do not currently exist in China), it is difficult to assess whether control strategies have had a substantial impact on levels of transmission, as the parasite population would still be able to maintain itself at an endemic level, highlighting the difficulties faced by elimination efforts. [ABSTRACT FROM AUTHOR]

The last decade has witnessed a surge in interest for policies to tackle health inequalities. Adequate theoretical development of policy models is needed to understand how to design and evaluate equity-oriented health policies. In this paper we review Graham's typology of policies (focused on the worst-off, on the gap, or on the gradient) and propose an adaptation (targeted, universal with additional targeting, redistributive, and proportionate universalism). For each type, potential scenarios of impact on population health and health inequalities are depicted following the idea of Geoffrey Rose's population curves and strategies, policy examples are given and a simulation with survey data is shown. The proposed typology of scenarios of health inequality reduction can serve as an effective tool to interpret the differential impact of interventions and to reflect on how to adequately design or re-orient a policy and which measures to use to evaluate it. [ABSTRACT FROM AUTHOR]

Introduction: The residents of many Australian rural and remote communities do not have the essential infrastructure and services required to support healthy living conditions and community members choosing healthy lifestyle options. Improving these social determinants of health is seen to offer real opportunities to improve health among such disadvantaged populations. In this paper, we describe the development and trialling of a tool to measure, monitor and evaluate key social determinants of health at community level. Methods: The tool was developed and piloted through a multi-phase and iterative process that involved a series of consultations with community members and key stakeholders and trialling the tool in remote Indigenous communities in the Northern Territory of Australia. Results: The indicators were found to be robust, and by testing the tool on a number of different levels, face validity was confirmed. The scoring system was well understood and easily followed by Indigenous and non-Indigenous study participants. A facilitated small group process was found to reduce bias in scoring of indicators. Conclusion: The Healthy Community Assessment Tool offers a useful vehicle and process to help those involved in planning, service provision and more generally promoting improvements in community social determinants of health. The tool offers many potential uses and benefits for those seeking to address inequities in the social determinants of health in remote communities. Maximum benefits in using the tool are likely to be gained with cross-sector involvement and when assessments are part of a continuous quality improvement program. [ABSTRACT FROM AUTHOR]

Applying research to guide evidence-based practice is an ongoing and significant challenge for public health. Developments in the emerging field of 'translation' have focused on different aspects of the problem, resulting in competing frameworks and terminology. In this paper the scope of 'translation' in public health is defined, and four related but conceptually different 'translation processes' that support evidence-based practice are outlined: (1) reviewing the transferability of evidence to new settings, (2) translation research, (3) knowledge translation, and (4) knowledge translation research. Finally, an integrated framework is presented to illustrate the relationship between these domains, and priority areas for further development and empirical research are identified. [ABSTRACT FROM AUTHOR]

To devise and implement effective health policy, we must define the problem, choose the tools, craft the policy, build consensus, set goals and deadlines, raise funds and take action. Success or failure depends on the perception of risk, the strength of the underlying science, the efficacy of the technology, ownership and intellectual property, the conflict between individual and public health, the choice of weaker (guidelines) and stronger (law) policy instruments, the level of public interest, political opportunity, institutional inertia, mechanisms for enforcement and who foots the bill. All these things considered, this paper is a brief policy-making guide by example, illustrating some achievements and disappointments with reference to cholera, drug-resistant tuberculosis, HIV/AIDS and rabies. [ABSTRACT FROM AUTHOR]

Context: Participatory research (PR) is the co-construction of research through partnerships between researchers and people affected by and/or responsible for action on the issues under study. Evaluating the benefits of PR is challenging for a number of reasons: the research topics, methods, and study designs are heterogeneous; the extent of collaborative involvement may vary over the duration of a project and from one project to the next; and partnership activities may generate a complex array of both short- and long-term outcomes. Methods: Our review team consisted of a collaboration among researchers and decision makers in public health, research funding, ethics review, and community-engaged scholarship. We identified, selected, and appraised a large-variety sample of primary studies describing PR partnerships, and in each stage, two team members independently reviewed and coded the literature. We used key realist review concepts (middle-range theory, demi-regularity, and context-mechanism-outcome configurations [CMO]) to analyze and synthesize the data, using the PR partnership as the main unit of analysis. Findings: From 7,167 abstracts and 591 full-text papers, we distilled for synthesis a final sample of twenty-three PR partnerships described in 276 publications. The link between process and outcome in these partnerships was best explained using the middle-range theory of partnership synergy, which demonstrates how PR can (1) ensure culturally and logistically appropriate research, (2) enhance recruitment capacity, (3) generate professional capacity and competence in stakeholder groups, (4) result in productive conflicts followed by useful negotiation, (5) increase the quality of outputs and outcomes over time, (6) increase the sustainability of project goals beyond funded time frames and during gaps in external funding, and (7) create system changes and new unanticipated projects and activities. Negative examples illustrated why these outcomes were not a guaranteed product of PR partnerships but were contingent on key aspects of context. Conclusions: We used a realist approach to embrace the heterogeneity and complexity of the PR literature. This theory-driven synthesis identified mechanisms by which PR may add value to the research process. Using the middle-range theory of partnership synergy, our review confirmed findings from previous PR reviews, documented and explained some negative outcomes, and generated new insights into the benefits of PR regarding conflicts and negotiation between stakeholders, program sustainability and advancement, unanticipated project activity, and the generation of systemic change. [ABSTRACT FROM AUTHOR]

High tuberculosis (TB) prevalence in Papua New Guinea (PNG) is a serious public health concern. The epidemic in this region is exacerbated by the presence of drug-resistant TB strains as well as HIV infection. This presents a public health threat not only locally but also to Australia due to the high potential for cross-border transmission between PNG’s Western Province and the Australian Torres Strait Islands. We present two mathematical models of TB in the Western Province: a simple model of the underlying TB dynamics, and a detailed model which accounts for the additional effects of HIV and drug resistance. The detailed model is used to make quantitative predictions about the impact of expanding the TB case detection rate under the Directly Observed Treatment, Short-course treatment regimen. This paper provides a framework for future investigation into the economic costs and public health benefits of potential TB interventions in this region, with the eventual aim of providing recommendations to guide policy makers in both PNG and Australia. [ABSTRACT FROM PUBLISHER]

Abstract: A number of proposals for integrating geographical (Geographical Information Systems—GIS) and multidimensional (data warehouse—DW and online analytical processing—OLAP) processing are found in the database literature. However, most of the current approaches do not take into account the use of a GDW (geographical data warehouse) metamodel or query language to make available the simultaneous specification of multidimensional and spatial operators. To address this, this paper discusses the UML class diagram of a GDW metamodel and proposes its formal specifications. We then present a formal metamodel for a geographical data cube and propose the Geographical Multidimensional Query Language (GeoMDQL) as well. GeoMDQL is based on well-known standards such as the MultiDimensional eXpressions (MDX) language and OGC simple features specification for SQL and has been specifically defined for spatial OLAP environments based on a GDW. We also present the GeoMDQL syntax and a discussion regarding the taxonomy of GeoMDQL query types. Additionally, aspects related to the GeoMDQL architecture implementation are described, along with a case study involving the Brazilian public healthcare system in order to illustrate the proposed query language. [Copyright &y& Elsevier]

Communities face exposures to multiple environmental toxicants and other non-chemical stressors. In addition, communities have unique activities and norms that influence exposure and vulnerability. Yet, few studies quantitatively consider the role of cumulative exposure and additive impacts. Community-based risk assessment (CBRA) is a new approach for risk assessment that aims to address the cumulative stressors faced by a particular community, while incorporating a community-based participatory research framework. This paper summarizes an Environmental Protection Agency (EPA) sponsored workshop, “Research Needs for Community-Based Risk Assessment.” This workshop brought together environmental and public health scientists and practitioners for fostering an innovative discussion about tools, methods, models, and approaches for CBRA. This workshop was organized around three topics: (1) Data and Measurement Methods; (2) The Biological Impact of Non-Chemical Stressors and Interaction with Environmental Exposures; and (3) Statistical and Mathematical Modeling. This report summarizes the workshop discussions, presents identified research needs, and explores future research opportunities in this emerging field. [ABSTRACT FROM AUTHOR]

Background: After initially falling in the face of intensified control efforts, reported rates of sexually transmitted chlamydia in many developed countries are rising. Recent hypotheses for this phenomenon have broadly focused on improved case finding or an increase in the prevalence. Because of many complex interactions behind the spread of infectious diseases, dynamic models of infection transmission are an effective means to guide learning, and assess quantitative conjectures of epidemiological processes. The objective of this paper is to bring a unique and robust perspective to observed chlamydial patterns through analyzing surveillance data with mathematical models of infection transmission. Methods: This study integrated 25-year testing volume data from the Canadian province of Saskatchewan with one susceptible-infected-treated-susceptible and three susceptible-infected-treated-removed compartmental models. Calibration of model parameters to fit observed 25-year case notification data, after being combined with testing records, placed constraints on model behaviour and allowed for an approximation of chlamydia prevalence to be estimated. Model predictions were compared to observed case notification trends, and extensive sensitivity analyses were performed to confirm the robustness of model results. Results: Model predictions accurately mirrored historic chlamydial trends including an observed rebound in the mid 1990s. For all models examined, the results repeatedly highlighted that increased testing volumes, rather than changes in the sensitivity and specificity of testing technologies, sexual behaviour, or truncated immunological responses brought about by treatment can, explain the increase in observed chlamydia case notifications. Conclusions: Our results highlight the significant impact testing volume can have on observed incidence rates, and that simple explanations for these observed increases appear to have been dismissed in favor of changes to the underlying prevalence. These simple methods not only demonstrate geographic portability, but the results reassure the public health effort towards monitoring and controlling chlamydia. [ABSTRACT FROM AUTHOR]

Abstract: In the paper, we propose a model that tracks the dynamics of many diseases spread by vectors, such as malaria, dengue, or West Nile virus (all spread by mosquitoes). Our model incorporates demographic structure with variable population size which is described by nonlinear birth rate and linear death rate. The stability of the system is analyzed for the existence of the disease-free and endemic equilibria points. We find the basic reproduction number in terms of measurable epidemiological and demographic parameters is the threshold condition that determines the dynamics of disease infection: if the disease fades out, and for the disease remains endemic. The threshold condition provides important guidelines for accessing control of the vector diseases, and implies that it is an efficient way to halt the spread of vector epidemic by reducing the carrying capacity of the environment for the vector and the host. Moreover, sufficient conditions are also obtained for the global stability of the unique endemic equilibrium . [Copyright &y& Elsevier]

Mathematical modeling of individual and public health based on system models is a vital problem. The approach developed in this paper is based on human organism model and helpful in studying the processes of development, ageing, and death of an organism, depending on internal and external ageing factors. It is useful in overall estimation of the public health in a region by the life expectancy criterion. Quantitative results of such an estimation made on the basis of ecological and demographic data for the city of Tula (Russia) are given. [ABSTRACT FROM AUTHOR]

This paper extends and further validates the quality-of-life/ community-healthcare model and measures developed by Rahtz and Sirgy (2000). The quality of life (QOL) model is based on the theoretical notion that community residents' satisfaction with healthcare services available within their community affects community quality of life and life satisfaction. This study extends the model and, in keeping with past research, posits that the bottom-up spillover from community QOL to life satisfaction is greater for those individuals with low personal health satisfaction, lower income, and old age. Data were collected from 1094 community residents in the East-Coast area of the United States. The results provide good support of the new model. Managerial implications and applications for the new model are discussed. [ABSTRACT FROM AUTHOR]

BACKGROUND: Severe acute respiratory syndrome (SARS) is currently spreading in many countries. This paper proposes a simple approximate mathematical model for public health practitioners to predict the number of SARS cases and deaths. METHODS: The model is based on four parameters: R(o) (basic reproductive number), F (case-fatality rate), i (incubation period), and d (duration of disease). The calculations can be done by hand or by using a computer spreadsheet. RESULTS: The best parameters to fit Canadian data as of 6 April 2003 (before infection controls took effect) are R(o) = 1.5, F = 30%, i = 5 days, d = 14 days. On 6 April (day 40) there were 74 cases and 7 deaths. If this trend continues, SARS numbers in Canada are predicted to be as follows: 387 cases and 34 deaths by 26 April (day 60), 4432 cases and 394 deaths by 26 May (day 90), and 50 500 cases and 4489 deaths by 25 June (day 120). By comparison, the best parameters to fit Hong Kong data as of 10 April 2003 are R(o) = 2.0, F = 20%, i = 5 days, d = 14 days. CONCLUSIONS: Using the proposed mathematical model, it was estimated that about 1.5 to 2 new infectious cases were produced per infectious case every five days. Also, about 20% to 30% of the cases die within 14 days. The case-fatality may therefore be considerably higher than initially thought. The model indicates that SARS can spread very fast when there are no interventions. [ABSTRACT FROM AUTHOR]

Abstract: This paper provides an overview of problems in multivariate modeling of epidemiologic data, and examines some proposed solutions. Special attention is given to the task of model selection, which involves selection of the model form, selection of the variables to enter the model, and selection of the form of these variables in the model. Several conclusions are drawn, among them: a) model and variable forms should be selected based on regression diagnostic procedures, in addition to goodness-of-fit tests; b) variable-selection algorithms in current packaged programs, such as conventional stepwise regression, can easily lead to invalid estimates and tests of effect; and c) variable selection is better approached by direct estimation of the ° of confounding produced by each variable than by significance-testing algorithms. As a general rule. before using a model to estimate effects, one should evaluate the assumptions implied by the model against both the data and prior information. [ABSTRACT FROM AUTHOR]

COVID-19 disease caused by the novel SARS-CoV-2 coronavirus has already brought unprecedented challenges for public health and resulted in huge numbers of cases and deaths worldwide. In the absence of effective vaccine, different countries have employed various other types of non-pharmaceutical interventions to contain the spread of this disease, including quarantines and lockdowns, tracking, tracing and isolation of infected individuals, and social distancing measures. Effectiveness of these and other measures of disease containment and prevention to a large degree depends on good understanding of disease dynamics, and robust mathematical models play an important role in forecasting its future dynamics. In this paper we focus on Ukraine, one of Europe's largest countries, and develop a mathematical model of COVID-19 dynamics, using latest data on parameters characterising clinical features of disease. For improved accuracy, our model includes age-stratified disease parameters, as well as age- and location-specific contact matrices to represent contacts. We show that the model is able to provide an accurate short-term forecast for the numbers and age distribution of cases and deaths. We also simulated different lockdown scenarios, and the results suggest that reducing work contacts is more efficient at reducing the disease burden than reducing school contacts, or implementing shielding for people over 60. [ABSTRACT FROM AUTHOR]

Background: Opioid addiction and overdose rates are reaching unprecedented levels in the U.S., with around 47,736 overdose deaths in 2017. Many stakeholders affect the opioid epidemic, including government entities, healthcare providers and policymakers, and opioid users. Simulation and conceptual modeling can help us understand the dynamics of the opioid epidemic by simplifying the real world and informing policymakers about different health interventions that could reduce the deaths caused by opioid overdose in the United States every year. Objectives: To conduct a scoping review of simulation and conceptual models that propose policies capable of controlling the opioid epidemic. We demonstrate the strengths and limitations of these models and provide a framework for further improvement of future decision support tools. Methods: Using the methodology of a scoping review, we identified articles published after 2000 from eight electronic databases to map the literature that uses simulation and conceptual modeling in developing public health policies to address the opioid epidemic. Results: We reviewed 472 papers of which 14 were appropriate for inclusion. Each used either system dynamics simulation modeling, mathematical modeling, conceptual modeling, or agent-based modeling. All included studies tested and proposed strategies to improve health outcomes related to the opioid epidemic. Factors considered in the models included physicians prescribing opioids, trafficking, users recruiting new users, and doctor shopping; no model investigated the impact of age and spatial factors on the dynamics of the epidemic. Key findings from these studies were (1) prevention of opioid initiation is better than treatment of opioid addiction, (2) the analysis of an intervention's impact should include both benefits and harms, and (3) interventions with short-term benefits might have a counterproductive impact on the epidemic in long run. Conclusions: While most studies examined the role of prescription opioids and trafficking on this epidemic, the transition of patients from prescription opioid use to nonprescription use including heroin and synthetic opioids such as fentanyl impacts the system significantly and results in an epidemic with quite different characteristics than what it had a decade ago. We recommend including the impact of age and geographic location on the opioid epidemic using modeling methods. [ABSTRACT FROM AUTHOR]

Background: Opioid addiction and overdose rates are reaching unprecedented levels in the U.S., with around 47,736 overdose deaths in 2017. Many stakeholders affect the opioid epidemic, including government entities, healthcare providers and policymakers, and opioid users. Simulation and conceptual modeling can help us understand the dynamics of the opioid epidemic by simplifying the real world and informing policymakers about different health interventions that could reduce the deaths caused by opioid overdose in the United States every year. Objectives: To conduct a scoping review of simulation and conceptual models that propose policies capable of controlling the opioid epidemic. We demonstrate the strengths and limitations of these models and provide a framework for further improvement of future decision support tools. Methods: Using the methodology of a scoping review, we identified articles published after 2000 from eight electronic databases to map the literature that uses simulation and conceptual modeling in developing public health policies to address the opioid epidemic. Results: We reviewed 472 papers of which 14 were appropriate for inclusion. Each used either system dynamics simulation modeling, mathematical modeling, conceptual modeling, or agent-based modeling. All included studies tested and proposed strategies to improve health outcomes related to the opioid epidemic. Factors considered in the models included physicians prescribing opioids, trafficking, users recruiting new users, and doctor shopping; no model investigated the impact of age and spatial factors on the dynamics of the epidemic. Key findings from these studies were (1) prevention of opioid initiation is better than treatment of opioid addiction, (2) the analysis of an intervention's impact should include both benefits and harms, and (3) interventions with short-term benefits might have a counterproductive impact on the epidemic in long run. Conclusions: While most studies examined the role of prescription opioids and trafficking on this epidemic, the transition of patients from prescription opioid use to nonprescription use including heroin and synthetic opioids such as fentanyl impacts the system significantly and results in an epidemic with quite different characteristics than what it had a decade ago. We recommend including the impact of age and geographic location on the opioid epidemic using modeling methods. [ABSTRACT FROM AUTHOR]