Context-specific Data Research Articles

Evaluating essential medicines for treating childhood cancers: availability, price and affordability study in Ghana

IntroductionAccess to childhood cancer medicines is a critical global health challenge. There is a lack of sufficient context-specific data in Ghana on access to essential medicines for treating childhood cancers. Here, we present an analysis of essential cancer medicine availability, pricing, and affordability using the pediatric oncology unit of a tertiary hospital as the reference point.MethodData on prices and availability of 20 strength-specific essential cancer medicines and eight non-cancer medicines were evaluated using the modified World Health Organization (WHO)/Health Action International method. Two pharmacies in the hospital and four private pharmacies around the hospital were surveyed. We assessed their median price ratio using the WHO international reference price guide. The number of days wages per the government daily wage salary was used to calculate the affordability of medicines.ResultsThe mean availability of essential cancer medicines and non-cancer medicines at the hospital pharmacies were 27 and 38% respectively, and 75 and 84% respectively for private pharmacies. The median price ratio of cancer medicines was 1.85, and non-cancer medicines was 3.75. The estimated cost of medicines for treating a 30 kg child with Acute lymphoblastic leukaemia was GHȻ 4928.04 (US$907.56) and GHȻ 4878.00 (US$902.62) for Retinoblastoma, requiring 417 and 413-days wages respectively for the lowest-paid unskilled worker in Ghana.ConclusionThe mean availability of cancer medicines at the public and private pharmacies were less than the WHO target of 80%. The median price ratio for cancer and non-cancer medicines was less than 4, yet the cost of medicines appears unaffordable in the local setting. A review of policies and the establishment of price control could improve availability and reduce medicines prices for the low-income population.

Factors influencing mothers\u2019 decisions regarding obstetrical care in Western Kenya: a mixed-methods study

BackgroundSiaya County in Western Kenya has one of the highest maternal mortality rates in Kenya. We sought to elucidate factors that influence mothers’ decisions regarding where to seek obstetrical care, to inform interventions that seek to promote effective use of obstetric services and reduce maternal mortalities. To guide our research, we used the “Three Delays Model”, focusing on the first delay—seeking care. While interventions to reduce maternal mortalities have focused on addressing delays in accessing and receiving care, context-specific data on drivers of the first delay are scarce.MethodsWe used a mixed-method study to assess how maternal decision-making of birth location is influenced by personal, contextual, and cultural factors. We conducted structured interviews with women aged 14 years or older living in Siaya, Bondo, and Yala, rural districts in Western Kenya. We then conducted focus group interviews with a subset of women to elucidate this question: How do drivers of the first delay (i.e., seeking care) affect the decision to seek home versus hospital delivery, potentially negatively influencing maternal mortality.ResultsThree hundred and seven women responded to the surveys, and 67 women (22%) from this group participated in focus group interviews. Although we focused on type 1 delays, we discovered that several factors that impact type 2 and type 3 delays directly contribute to type 1 delays. Our findings highlighted that factors influencing women’s decisions to seek care are not simply medical or cultural but rather contextual, involving many elements of life, particularly in rural communities.ConclusionsIt is imperative to address multiple-level factors that influence women’s decisions to seek care and have in-hospital deliveries. To curtail maternal mortality in rural Western Kenya and comparable settings, targeted interventions must take into consideration these important influencers.

Operationalisation of the Randomized Embedded Multifactorial Adaptive Platform for COVID-19 trials in a low and lower-middle income critical care learning health system.

The Randomized Embedded Multifactorial Adaptive Platform (REMAP-CAP) adapted for COVID-19) trial is a global adaptive platform trial of hospitalised patients with COVID-19. We describe implementation in three countries under the umbrella of the Wellcome supported Low and Middle Income Country (LMIC) critical care network: Collaboration for Research, Implementation and Training in Asia (CCA). The collaboration sought to overcome known barriers to multi centre-clinical trials in resource-limited settings. Methods described focused on six aspects of implementation: i, Strengthening an existing community of practice; ii, Remote study site recruitment, training and support; iii, Harmonising the REMAP CAP- COVID trial with existing care processes; iv, Embedding REMAP CAP- COVID case report form into the existing CCA registry platform, v, Context specific adaptation and data management; vi, Alignment with existing pandemic and critical care research in the CCA. Methods described here may enable other LMIC sites to participate as equal partners in international critical care trials of urgent public health importance, both during this pandemic and beyond.

IDENTIFYING RELEVANT PATHWAYS AND BIOMARKERS IN CROHN’S DISEASE USING CONTEXTUALIZED METABOLIC NETWORK MODEL

Abstract Background Candidate markers for Crohn’s Disease (CD) may be identified via gene expression-based construction of metabolic networks (MN). These can computationally describe gene-protein-reaction associations for entire tissues and also predict the flux of reactions (rate of turnover of specific molecules via a metabolic pathway). Recon3D is the most comprehensive human MN to date. We used publicly available CD transcriptomic data along with Recon3D to identify metabolites as potential diagnostic and prognostic biomarkers. Methods Terminal ileal gene expression profiles (36,372 genes; 218 CD. 42 controls) from the RISK cohort (Risk Stratification and Identification of Immunogenetic and Microbial Markers of Rapid Disease Progression in Children with Crohn’s Disease) and their transcriptomic abundances were used. Recon3D was pruned to only include RISK dataset transcripts which determined metabolic reaction linkage with transcriptionally active genes. Flux balance analysis (FBA) was then run using RiPTiDe with context specific transcriptomic data to further constrain genes (Figure 1). RiPTiDe was independently run on transcriptomic data from both CD and controls. From the pruned and constricted MN obtained, reactions were extracted for further analysis. Results After applying the necessary constraints to modify Recon3D, 527 CD and 537 control reactions were obtained. Reaction comparison with a publicly available list of healthy small intestinal epithelial reactions (n=1282) showed an overlap of 80 CD and 84 control reactions. These were then further grouped based on their metabolic pathways. RiPTiDe identified context specific metabolic pathway activity without supervision and the percentage of forward, backward, and balanced reactions for each metabolic pathway (Figure 2). The metabolite concentrations in the small intestine was altered among CD patients. Notably, the citric acid cycle and malate-aspartate shuttle were affected, highlighting changes in mitochondrial metabolic pathways. This is illustrated by changes in the number of reactions at equilibrium between CD and control. Conclusions The results are relevant as cytosolic acetyl-CoA is needed for fatty acid synthesis and is obtained by removing citrate from the citric acid cycle. An intermediate removal from the cycle has significant cataplerotic effects. The malate-aspartate shuttle also allows electrons to move across the impermeable membrane in the mitochondria (fatty acid synthesis location). These findings are reported by previously published studies where gene expression for fatty acid synthesis is altered in CD patients along with mitochondrial metabolic pathway changes, resulting in altered cell homeostasis. In-depth analysis is currently underway with our work supporting the utility of potential metabolic biomarkers for CD diagnosis, management and improved care.

Experience and practice of the Emergency Operations Center, Chinese Center for Disease Control and Prevention: a case study of response to the H7N9 outbreak

BackgroundEmergency Operations Center (EOC) is a place to provide response to public health emergencies. Chinese Center for Disease Control and Prevention (China CDC)’s EOC was officially established in 2016, which has been the core department for the public health emergencies and risk response. In recent years, we have been continuously improving the function of EOC through many incidents. In the study, we hope to share the construction status, operation management experience of China CDC’s EOC and the response process in the human avian influenza A (H7N9) outbreak.Main textThe China CDC’s EOC mainly focus on building the five core elements including sites/places and facilities, information and data, plans and procedures, training and exercises, and logistics. Based on summarizing previous emergency response, the China CDC’s EOC established its own incident management and the standardized response procedures. The event-specific data, context-specific data and event management data could be obtained through various source. The logistics department of the EOC also provides comprehensive support. The well-trained staff is another necessary conditions for its operation. Through sharing the response process of H7N9 outbreak, it further explains the EOC’s functions in the five phases of outbreak response, such as the formulation of the incident response framework, monitoring, personnel dispatch and resource mobilization.ConclusionsThe EOC contributes to faster and more efficient responses during emergencies which enable a greater reduction in morbidity and mortality. Compared with the traditional incident response process, under the command and coordination of China CDC’s EOC, each group involved in the response has a clearer goal, responsibilities and tasks at each stage. Meanwhile, each group also gave full play to its own expertise and advantages. As a whole, incident response tended to be more specialized and precise, which generally improves the efficiency of incident response. However, different countries and regions have different response processes to the events. We still suggested that appropriate emergency operation plan should be made according to the complexity of incident response in the region when constructing response mechanism, through our experience. And the China CDC’s EOC is still at growing and groping phase.Graphic abstract

A Systematic Review of Methodological Approaches for Evaluating Real-World Effectiveness of Covid-19 Vaccines: Advising Resource-Constrained Settings

Background: Real-world effectiveness studies are important for monitoring performance of COVID-19 vaccination programmes and informing COVID-19 prevention and control policies. We aimed to synthesise methodological approaches used in COVID-19 vaccine effectiveness studies, in order to evaluate which approaches are most appropriate to implement in low- and middle-income countries (LMICs). Methods: For this rapid systematic review, we searched PubMed and Scopus for articles published from inception to July 7, 2021, without language restrictions. We included any type of peer-reviewed observational study measuring COVID-19 vaccine effectiveness, for any population. We excluded randomised control trials and modelling studies. All data used in the analysis were extracted from included papers. We used a standardised data extraction form, modified from STrengthening the Reporting of OBservational studies in Epidemiology (STROBE). Study quality was assessed using the REal Life EVidence AssessmeNt Tool (RELEVANT) tool. This study is registered with PROSPERO, CRD42021264658. Findings: Our search identified 3,214 studies, of which 26 were eligible for analysis. All studies were conducted in 7 high-income countries and the majority assessed mRNA vaccines (81% mRNA only, 15% mRNA and viral vector). Twenty-one of the 26 studies (81%) used a cohort study design. There was significant heterogeneity for full vaccination effectiveness estimates across studies (infection: n=17, mean=79%; hospitalisation: n=7, mean=89%; death: n=3, mean=92%). Follow-up time for all studies was short (mean=9.5 weeks). Across studies, short follow-up time and limited assessment and mitigation of potential confounders, including previous SARS-CoV-2 infection and healthcare seeking behaviour, were major limitations. Interpretation: This review summarises methodological approaches for evaluating real-world effectiveness of COVID-19 vaccines and highlights the lack of such studies in LMICs, as well as the importance of context-specific vaccine effectiveness data. Further research in LMICs will refine guidance for conducting real-world COVID-19 vaccine effectiveness studies in resource-constrained settings. Funding: Health Systems Research Institute.

Forecasting surgical costs: Towards informed financial consent and financial risk reduction

BackgroundHealth care expenditure is increasing around the world and surgery is a major cause of financial hardship to patients and their families. Using pancreatoduodenectomy (PD), one of the most complex, morbid and costly operation as an example, this study aimed to identify the cost drivers of surgery, estimate relative contribution of these drivers, and derive and validate a cohort-specific cost forecasting tool. MethodsData on the costs of 1406 patients undergoing PD in three tertiary hospitals in India, Italy and the United States were analysed. Cost drivers were identified and cost models developed using a 4-stage process. ResultsThere was a significant difference in overall cost of PD between the 3 cohorts. The cost drivers common to the 3 cohorts included duration of hospital stay and the outcome of death (Clavien-Dindo 5). Significant cohort-specific cost drivers included co-morbidities, operating theatre utilisation times and operative blood loss, development of pancreatectomy-specific complications (POPF, DGE, PPH), and need for interventional radiology to manage complications. Based on this, a cost forecasting tool was developed. ConclusionsDrivers of costs for a surgical procedure (e.g. PD) are different between hospitals. Developing cost models/nomograms to predict the expected cost of surgery and perioperative care will not be applicable between hospitals. However, the approach could be used to develop context-specific data that will provide patients (at the time of the informed financial consent) and funding agencies with a more realistic cost estimate for a given operation. The developed cost forecasting tool warrants future validation.

Context-specific network modeling identifies new crosstalk in β-adrenergic cardiac hypertrophy.

Cardiac hypertrophy is a context-dependent phenomenon wherein a myriad of biochemical and biomechanical factors regulate myocardial growth through a complex large-scale signaling network. Although numerous studies have investigated hypertrophic signaling pathways, less is known about hypertrophy signaling as a whole network and how this network acts in a context-dependent manner. Here, we developed a systematic approach, CLASSED (Context-specific Logic-bASed Signaling nEtwork Development), to revise a large-scale signaling model based on context-specific data and identify main reactions and new crosstalks regulating context-specific response. CLASSED involves four sequential stages with an automated validation module as a core which builds a logic-based ODE model from the interaction graph and outputs the model validation percent. The context-specific model is developed by estimation of default parameters, classified qualitative validation, hybrid Morris-Sobol global sensitivity analysis, and discovery of missing context-dependent crosstalks. Applying this pipeline to our prior-knowledge hypertrophy network with context-specific data revealed key signaling reactions which distinctly regulate cell response to isoproterenol, phenylephrine, angiotensin II and stretch. Furthermore, with CLASSED we developed a context-specific model of β-adrenergic cardiac hypertrophy. The model predicted new crosstalks between calcium/calmodulin-dependent pathways and upstream signaling of Ras in the ISO-specific context. Experiments in cardiomyocytes validated the model’s predictions on the role of CaMKII-Gβγ and CaN-Gβγ interactions in mediating hypertrophic signals in ISO-specific context and revealed a difference in the phosphorylation magnitude and translocation of ERK1/2 between cardiac myocytes and fibroblasts. CLASSED is a systematic approach for developing context-specific large-scale signaling networks, yielding insights into new-found crosstalks in β-adrenergic cardiac hypertrophy.

Hidden healthcare populations: using intersectionality to theorise the experiences of LGBT+ people in Nigeria, Africa

ABSTRACT Minority population groups are often excluded or marginalised within health systems and in health research and policy. This article argues that theories of intersectionality can help us to understand these issues and develops the concept of ‘hidden healthcare populations’ – using the case of people who identify as Lesbian, Gay, Bisexual, Transgender Plus (LGBT+) in Nigeria, in sub-Saharan Africa. The findings present original qualitative data from a seldom heard population group about instances of abuse, rejection and marginalisation by healthcare providers working in public and private healthcare facilities, and the attempts of LGBT+ people to resist and survive in that context. We extend theoretical understandings of intersectionality in global public health and explore how the concept relates to the social determinants of health. The article has significant implications for policy and healthcare education and responds to a call from the World Health Organisation to generate context-specific data to guide interventions targeted at minority population groups. Additionally, our discussion has wider significance because it highlights the Western-centric nature of much theory in health policy – and offers analysis and reinterpretation that incorporates queer, postcolonial, African perspectives.

Relative validity of a brief dietary survey to assess food intake and adherence to national dietary guidelines among Sri Lankan adults

BackgroundSuboptimal diet is the leading cause of global morbidity and mortality. Addressing this problem requires context-specific solutions informed by context-specific data collected by context-specific tools. This study aimed to assess the relative validity of a newly developed brief dietary survey to estimate food intake and adherence to the Food Based Dietary Guidelines for Sri Lankans.MethodsBetween December 2018 and February 2019, we interviewed 94 Sri Lankan adults living in Colombo (Western Province), Kalutara (Western Province), and Trincomalee (Eastern Province). We assessed the relative validity of the Sri Lankan Brief Dietary Survey (SLBDS) with Wilcoxon rank-sum tests, Spearman’s Rho correlation coefficients, Bland–Altman plots, and Cohen’s kappa tests using a 24-h Dietary Recall (24DR) as reference.ResultsNinety-four adults (40.7 years ±12.6; 66% female) completed both surveys during the same interview. With the exception of ‘Fish, pulses, meat and eggs’ food group median intake, which was underestimated by the SLBDS compared to the 24DR, there was no strong evidence of difference between median intakes reported by the two methods. Correlation coefficients were highest for ‘Milk and dairy products’ (0.84) at the food group level and for ‘dosa’, ‘hoppers’, ‘milk rice’, and ‘dried fish’ (1.00) among individual food and beverages. Visual exploration of Bland-Altman plots showed acceptable agreement between the SLBDS and 24DR, with the SLBDS tending to overestimate consumption as the number of servings of ‘Rice, bread, other cereals and yams’ and ‘Vegetables’ consumed increased and slightly underestimate consumption as the number of servings of ‘Fish, pulses, meat and eggs’, ‘Milk and dairy products’, and ‘Nuts’ increased. Kappa values ranged from from 0.59 (95% CI: 0.32–0.86) for ‘Vegetables’ to 0.81 (95% CI: 0.66–0.96) for ‘Fruit’ indicating a moderate to strong level of agreement.ConclusionsHaving been developed for and relatively validated with the study population in question, our study shows that the SLBDS can be used as a fit for purpose research tool. Additional research is needed to assess SLBDS test-retest reliability and to validate further the reporting of salt, oil, and coconut intake.

PeskAAS: A near-real-time, open-source monitoring and analytics system for small-scale fisheries.

Small-scale fisheries are responsible for landing half of the world's fish catch, yet there are very sparse data on these fishing activities and associated fisheries production in time and space. Fisheries-dependent data underpin scientific guidance of management and conservation of fisheries systems, but it is inherently difficult to generate robust and comprehensive data for small-scale fisheries, particularly given their dispersed and diverse nature. In tackling this challenge, we use open source software components including the Shiny R package to build PeskAAS; an adaptable and scalable digital application that enables the collation, classification, analysis and visualisation of small-scale fisheries catch and effort data. We piloted and refined this system in Timor-Leste; a small island developing nation. The features that make PeskAAS fit for purpose are that it is: (i) fully open-source and free to use (ii) component-based, flexible and able to integrate vessel tracking data with catch records; (iii) able to perform spatial and temporal filtering of fishing productivity by fishing method and habitat; (iv) integrated with species-specific length-weight parameters from FishBase; (v) controlled through a click-button dashboard, that was co-designed with fisheries scientists and government managers, that enables easy to read data summaries and interpretation of context-specific fisheries data. With limited training and code adaptation, the PeskAAS workflow has been used as a framework on which to build and adapt systematic, standardised data collection for small-scale fisheries in other contexts. Automated analytics of these data can provide fishers, managers and researchers with insights into a fisher's experience of fishing efforts, fisheries status, catch rates, economic efficiency and geographic preferences and limits that can potentially guide management and livelihood investments.

Reconstruction of a Context-Specific Model Based on Genome-Scale Metabolic Simulation for Identification of Prochloraz Resistance Mechanisms in Penicillium digitatum.

Penicillium digitatum is the most destructive postharvest pathogen of citrus fruits, causing substantial economic losses. Prochloraz-resistant strains have emerged due to overuse of imidazole fungicides in agriculture. To study the prochloraz resistance mechanisms at the system level, a genome-scale metabolic model (GEM, iPD1512) of P. digitatum was reconstructed and constrained based on context-specific transcriptome data of the prochloraz-resistant strain, PdF6, from our previous work, a newly sequenced, context-specific transcriptome result of the major facilitator superfamily transporter-encoding gene mfs2 knockout mutant PdF6Δmfs2, and experimentally derived growth rate data. Through the model, iPD1512, the processes of prochloraz resistance in P. digitatum were well simulated. In detail, the growth rates of both wild-type and mutant P. digitatum under different prochloraz concentrations were simulated using constraint-based reconstruction and analysis. The growth rates of the mutant strains (sterol regulatory element-binding protein-encoding gene sreA knockout mutant PdF6ΔsreA and PdF6Δmfs2) were calculated and confirmed to be consistent with the simulation results. Furthermore, correlations between genes and prochloraz resistance were predicted and showed a great difference when compared with correlation results based on p-values from the hypothesis testing used by comparative transcriptomics. To sum up, in contrast to traditional transcriptome analysis, the GEM provides a systemic and dynamic drug resistance mechanism, which might help to detect some key upstream regulatory genes, but with small expression changes, and might provide more efficient targets to control prochloraz-resistant P. digitatum.

Costs of providing HIV care and optimal allocation of HIV resources in Guyana.

Great strides in responding to the HIV epidemic have led to improved access to and uptake of HIV services in Guyana, a lower-middle-income country with a generalized HIV epidemic. Despite efforts to scale up HIV treatment and adopt the test and start strategy, little is known about costs of HIV services across the care cascade. We collected cost data from the national laboratory and nine selected treatment facilities in five of the country's ten Regions, and estimated the costs associated with HIV testing and services (HTS) and antiretroviral therapy (ART) from a provider perspective from January 1, 2016 to December 31, 2016. We then used the unit costs to construct four resource allocation scenarios. In the first two scenarios, we calculated how close Guyana would currently be to its 2020 targets if the allocation of funding across programs and regions over 2017-2020 had (a) remained unchanged from latest-reported levels, or (b) been optimally distributed to minimize incidence and deaths. In the next two, we estimated the resources that would have been required to meet the 2020 targets if those resources had been distributed (a) according to latest-reported patterns, or (b) optimally to minimize incidence and deaths. The mean cost per test was US$15 and the mean cost per person tested positive was US$796. The mean annual cost per of maintaining established adult and pediatric patients on ART were US$428 and US$410, respectively. The mean annual cost of maintaining virally suppressed patients was US$648. Cost variation across sites may suggest opportunities for improvements in efficiency, or may reflect variation in facility type and patient volume. There may also be scope for improvements in allocative efficiency; we estimated a 28% reduction in the total resources required to meet Guyana's 2020 targets if funds had been optimally distributed to minimize infections and deaths. We provide the first estimates of costs along the HIV cascade in the Caribbean and assessed efficiencies using novel context-specific data on the costs associated with diagnostic, treatment, and viral suppression. The findings call for better targeting of services, and efficient service delivery models and resource allocation, while scaling up HIV services to maximize investment impact.

Longitudinal Assessment of Childhood Dietary Patterns: Associations with Body Mass Index z-Score among Children in the Samoan Ola Tuputupua'e (Growing Up) Cohort.

Background: Intervention strategies to prevent childhood obesity in the Pacific Islands encourage eating a variety of local and traditional foods, but context-specific data to support this approach are limited. The objective was to assess the association between 2-year adherence to modern and neotraditional dietary patterns and body mass index z-scores (BMIz) among Samoan children. Methods: A convenience sample of 214 Samoan biological mother-child dyads who participated in the Ola Tuputupua'e "Growing Up" cohort study in 2015 and 2017 was included. At each time point, modern and neotraditional dietary patterns were identified using food frequency data and factor analysis. Children were assigned to categories based on diet pattern adherence: consistently high, high to low, low to high, and consistently low. Associations between 2-year adherence to dietary patterns, BMIz (in 2017 and 2015-2017), and weight and height z-scores were examined using linear models adjusted for potential confounders. Results: Consistently high adherence to the modern pattern was associated with a 0.36 standard deviation (SD)-adjusted change in BMIz between 2015 and 2017 (95% confidence interval [CI]: 0.04-0.69, p = 0.03). While the estimates for the individual components of BMI were imprecise, on average, children with consistently high adherence to the modern pattern had a 0.13 SD greater change in weight z-score (95% CI: -0.10 to 0.37) and 0.15 SD lower change in height z-score (95% CI: -0.43 to 0.13). The change in BMIz between 2015 and 2017 did not significantly differ by adherence to the neotraditional pattern. Conclusion: A neotraditional dietary pattern, comprising local produce, should be encouraged as a possible childhood obesity prevention strategy in Samoa.

What is the evidence for the impact of gardens and gardening on health and well-being: a scoping review and evidence-based logic model to guide healthcare strategy decision making on the use of gardening approaches as a social prescription

ObjectiveTo systematically identify and describe studies that have evaluated the impact of gardens and gardening on health and well-being. A secondary objective was to use this evidence to build evidence-based...

Utility of ecological momentary assessments to collect data on fear of crime

ABSTRACT Smartphone technology provides a unique opportunity to collect context-specific data from individuals. Very few published studies have attempted to gather context-specific information on fear of crime using smartphone technology. With our pilot study in Lahore, Pakistan, we examined the utility of administration of Ecological Momentary Assessments (EMAs) via our smartphone application to collect real-time and context-dependent information on transit users’ experiences. The results demonstrate that EMAs and smartphones can provide a unique opportunity to collect context-specific data on individuals’ fear of crime, perceived risk of victimisation, perceptions of incivility, and their suggestions for improvements to the design and management of the public transit system.

IoT meets BPM: a bidirectional communication architecture for IoT-aware process execution

Business processes are frequently executed within application systems that involve humans, computer systems as well as objects of the Internet of Things (IoT). Nevertheless, the usage of IoT technology for system supported process execution is still constrained by the absence of a common system architecture that manages the communication between both worlds. In this paper, we introduce an integrated approach for IoT-aware business process execution that exploits IoT for BPM by providing IoT data in a process-compatible way, providing an IoT data provenance framework, considering IoT data for interaction in a pre-defined process model, and providing wearable user interfaces with context-specific IoT data provision. The approach has been implemented on top of contemporary BPM modeling concepts and system technology. The introduced technique has evaluated extensively in different use cases in industry.

A Place-Based Approach to Agricultural Nonmaterial Intangible Cultural Ecosystem Service Values

Though agricultural landscape biodiversity and ecosystem service (ES) conservation is crucial to sustainability, agricultural land is often underrepresented in ES studies, while cultural ES associated with agricultural land is often limited to aesthetic and tourism recreation value only. This study mapped 7 nonmaterial-intangible cultural ES (NICE) valuations of 34 rural farmers in western Taiwan using the Social Values for Ecosystem Services (SolVES) methodology, to show the effect of farming practices on NICE valuations. However, rather than a direct causal relationship between the environmental characteristics that underpin ES, and respondents’ ES valuations, we found that environmental data is not explanatory enough for causality within a socio-ecological production landscape where one type of land cover type (a micro mosaic of agricultural land cover) predominates. To compensate, we used a place-based approach with Google Maps data to create context-specific data to inform our assessment of NICE valuations. Based on 338 mapped points of 7 NICE valuations distributed among 6 areas within the landscape, we compared 2 groups of farmers and found that farmers’ valuations about their landscape were better understood when accounting for both the landscape’s cultural places and environmental characteristics, rather than environmental characteristics alone. Further, farmers’ experience and knowledge influenced their NICE valuations such that farm areas were found to be sources of multiple NICE benefits demonstrating that farming practices may influence ES valuation in general.

Access to WHO Essential Medicines for Childhood Cancer Care in Trinidad and Tobago: A Health System Analysis of Barriers and Enablers.

PURPOSEImproving access to essential medicines is necessary to reduce global mortality resulting from childhood cancer. However, there is a lack of context-specific data in many low- to middle-income countries on the determinants of access to essential childhood cancer medicines. We conducted a mixed-methods case study of the barriers to and enablers of access to WHO essential medicines for childhood cancer care in Trinidad and Tobago, in response to domestic calls for policy attention and reform.METHODSWe interviewed stakeholders (N = 9) across the pharmaceutical supply system using a novel analytic framework and qualitative interview guide. Interviews were recorded, transcribed, and analyzed with constant comparative methods to capture emergent themes. Quantitatively, we examined alignment of the national essential medicines list with the 2017 WHO Essential Medicines List for Children (EMLc). National buyer prices for EMLc cancer medicines were compared with median international prices, with calculation of median price ratios to assess procurement efficiency.RESULTSPrincipal barriers identified included a lack of data-driven procurement, low supplier incentive to engage in tenders, reactive rather than proactive processes in response to stockouts, and siloed information systems. Recurring themes of regionalization, standardization, and proactivity emerged as priorities for policy reform. Quantitative analysis of the national essential medicines list and median price ratios for procured medicines aligned with findings reported qualitatively.CONCLUSIONOur study contributes to global efforts to improve childhood cancer care by identifying policy-relevant evidence on access to essential childhood cancer medicines and providing a model for future studies in other jurisdictions.

Integrated querying and version control of context-specific biological networks.

MotivationBiomolecular data stored in public databases is increasingly specialized to organisms, context/pathology and tissue type, potentially resulting in significant overhead for analyses. These networks are often specializations of generic interaction sets, presenting opportunities for reducing storage and computational cost. Therefore, it is desirable to develop effective compression and storage techniques, along with efficient algorithms and a flexible query interface capable of operating on compressed data structures. Current graph databases offer varying levels of support for network integration. However, these solutions do not provide efficient methods for the storage and querying of versioned networks.ResultsWe present VerTIoN, a framework consisting of novel data structures and associated query mechanisms for integrated querying of versioned context-specific biological networks. As a use case for our framework, we study network proximity queries in which the user can select and compose a combination of tissue-specific and generic networks. Using our compressed version tree data structure, in conjunction with state-of-the-art numerical techniques, we demonstrate real-time querying of large network databases.ConclusionOur results show that it is possible to support flexible queries defined on heterogeneous networks composed at query time while drastically reducing response time for multiple simultaneous queries. The flexibility offered by VerTIoN in composing integrated network versions opens significant new avenues for the utilization of ever increasing volume of context-specific network data in a broad range of biomedical applications.Availability and Implementation VerTIoN is implemented as a C++ library and is available at http://compbio.case.edu/omics/software/vertion and https://github.com/tjcowman/vertionContacttyler.cowman@case.edu