System Level Research Articles

Rapid systematic review of interventions to improve antenatal screening rates for syphilis, hepatitis B, and HIV in low- and middle-income countries.

Infectious diseases including syphilis, HIV, and hepatitis B are major contributors to maternal and neonatal morbidity and mortality worldwide, especially in low- and middle-income countries (LMICs). The World Health Organization has prioritized elimination of vertical transmission of these three diseases. To rapidly assess the impact of interventions designed to improve antenatal screening rates for syphilis, HIV, and hepatitis B in LMICs and to identify areas for future implementation research. A comprehensive search was conducted across PubMed, Embase, and EconLit, targeting articles published between January 1, 2013, and June 27, 2023. We included quantitative interventional studies in English, involving pregnant adults (15 years or older) from LMICs. Exclusions were studies based in high-income countries, qualitative studies, or those investigating accuracy of diagnostic methods. From an initial 5549 potential studies, 27 were finalized for review after various screening stages. Data extraction covered aspects such as study design, intervention details, and outcomes. Findings were qualitatively synthesized within a systems thinking framework. The interventions assessed varied in terms of geographic locations, health care system levels, and modalities. The review highlighted the effectiveness of interventions such as community health interventions, service quality improvements, and financial incentives. The study underscores the potential of specific interventions in enhancing antenatal screening rates in LMICs. However, there is a discernible research gap concerning hepatitis B. The findings emphasize the importance of capacity building and health systems strengthening in public health interventions.

Temporal effective stress response of soil elements below the base of an excavation in sensitive clay

Investigations into the temporally evolving stress state below the base of excavations and underground structures are very scarce, in contrast to studies of horizontal earth pressures during the construction stage. Therefore in this work, the measured temporal response in terms of vertical and horizontal effective stresses and displacements below a tunnel slab at the base of an excavation located in a deep sensitive clay deposit is reported. In addition to the measured unloading response over time, the completeness of the site description and complementary measurements enables future benchmarking of numerical models at boundary and element level. Instrument clusters of earth pressure cells and piezometers were installed at three locations in one cross-section. The monitoring data allows the interpretation of effective stress paths and stress ratios, <i>K</i>=σ'<sub>h</sub>/σ'<sub>v</sub>, at soil element level covering the construction and the serviceability stages. The in situ stress ratios enable a unique comparison to prior laboratory studies of <i>K</i> during unloading. The data presented herein on the evolution of <i>K</i> corroborate, although approximately, previous studies at laboratory scale. Furthermore, at system level, the monitoring data reveal the intricate interplay between deformations resulting from excavation and pile driving.

Control of supercritical CO2 Brayton cycle for fast and efficient load variation processes

The supercritical carbon dioxide (S-CO2) cycle is considered a promising power conversion system due to its high efficiency and flexibility. This work presents a dynamic model of a 600 MWe S-CO2 recompression Brayton cycle (RBC) and validates it at both component and system levels. To ensure the safety and stability of the S-CO2 RBC during wide-load operation, some necessary control strategies are designed, including minimum pressure and temperature control, split ratio control, turbine inlet temperature control, and anti-surge control. Moreover, an innovative valve-inventory joint control method is proposed, coupled with an improved inventory tank layout, to achieve both fast and efficient load variation processes. Compared to the control strategy before improvement, the ramp-up and ramp-down rates are significantly increased by 2.65 and 2.24 times, respectively. In addition, the values of key parameters suitable for wide-load operation of the S-CO2 RBC are determined to maximize the cycle efficiency under off-design conditions. The results show that the split ratio should be dynamically adjusted to determine the optimal value that varies with the load, which can improve the cycle efficiency by a maximum of 1.13 %. Finally, the dynamic performance of the S-CO2 RBC is studied during load ramp changes and real-time microgrid load, and the variations in heat exchange, pressure, temperature, and mass flow rate of key components are revealed. Comparative analysis with previous literature demonstrates that the proposed control method provides a wider load regulation range, an increase of 7.78 % in cycle efficiency, and a reduced maximum generation frequency deviation of 0.696 Hz. There is no overpressure or compressor surge risk, and the maximum temperature change rate is only 1.3 ℃·min−1.

Identifying, categorising, and mapping actors involved in resilience in healthcare: a qualitative stakeholder analysis

BackgroundResilience in healthcare is the capacity to adapt to challenges and changes to maintain high-quality care across system levels. While healthcare system stakeholders such as patients, informal carers, healthcare professionals and service managers have all come to be acknowledged as important co-creators of resilient healthcare, our knowledge and understanding of who, how, and in which contexts different stakeholders come to facilitate and support resilience is still lacking. This study addresses gaps in the research by conducting a stakeholder analysis to identify and categorise the stakeholders that are key to facilitating and sustaining resilience in healthcare, and to investigate stakeholder relationships relevant for the enactment of resilient healthcare systems.MethodsThe stakeholder analysis was conducted using a sample of 19 empirical research projects. A narrative summary was written for 14 of the projects, based on publicly available material. In addition, 16 individual interviews were undertaken with researchers from the same sample of 19 projects. The 16 interview transcripts and 14 narratives made up the data material of the study. Application of stakeholder analysis methods was done in three steps: a) identification of stakeholders; b) differentiation and categorisation of stakeholders using an interest/influence grid; and c) investigation and mapping of stakeholder relationships using an actor-linkage matrix.ResultsIdentified stakeholders were Patients, Family Carers, Healthcare Professionals, Ward/Unit Managers, Service or Case Managers, Regulatory Investigators, Policy Makers, and Other Service Providers. All identified stakeholders were categorised as either ‘Subjects’, ‘Players’, or ‘Context Setters’ according to their level of interest in and influence on resilient healthcare. Stakeholder relationships were mapped according to the degree and type of contact between the various groups of stakeholders involved in facilitating resilient healthcare, ranging from ‘Not linked’ to ‘Fully linked’.ConclusionFamily carers and healthcare professionals were found to be the most active groups of stakeholders in the enactment of healthcare system resilience. Patients, managers, and policy makers also contribute to resilience to various degrees. Relationships between stakeholder groups are largely characterised by communication and coordination, in addition to formal collaborations where diverse actors work together to achieve common goals.

XBP1-mediated transcriptional regulation of SLC5A1 in human epithelial cells in disease conditions

BackgroundSodium-Glucose cotransporter 1 and 2 (SGLT1/2) belong to the family of glucose transporters, encoded by SLC5A1 and SLC5A2, respectively. SGLT2 is almost exclusively expressed in the renal proximal convoluted tubule cells. SGLT1 is expressed in the kidneys but also in other organs throughout the body. Many SGLT inhibitor drugs have been developed based on the mechanism of blocking glucose (re)absorption mediated by SGLT1/2, and several have gained major regulatory agencies’ approval for treating diabetes. Intriguingly these drugs are also effective in treating diseases beyond diabetes, for example heart failure and chronic kidney disease. We recently discovered that SGLT1 is upregulated in the airway epithelial cells derived from patients of cystic fibrosis (CF), a devastating genetic disease affecting greater than 70,000 worldwide.ResultsIn the present work, we show that the SGLT1 upregulation is coupled with elevated endoplasmic reticulum (ER) stress response, indicated by activation of the primary ER stress senor inositol-requiring protein 1α (IRE1α) and the ER stress-induced transcription factor X-box binding protein 1 (XBP1), in CF epithelial cells, and in epithelial cells of other stress conditions. Through biochemistry experiments, we demonstrated that the spliced form of XBP1 (XBP1s) acts as a transcription factor for SLC5A1 by directly binding to its promoter region. Targeting this ER stress → SLC5A1 axis by either the ER stress inhibitor Rapamycin or the SGLT1 inhibitor Sotagliflozin was effective in attenuating the ER stress response and reducing the SGLT1 level in these cellular model systems.ConclusionsThe present work establishes a causal relationship between ER stress and SGLT1 upregulation and provides a mechanistic explanation why SGLT inhibitor drugs benefit diseases beyond diabetes.

Training of Deep Joint Transmitter-Receiver Optimized Communication System without Auxiliary Tools

Deep Joint transmitter-receiver optimized communication system (Deep JTROCS) is a new physical layer communication system. It integrates the functions of various signal processing blocks into deep neural networks in the transmitter and receiver. Therefore, Deep JTROCS can approach the optimal state at the system level by the joint training of these neural networks. However, due to the non-differentiable feature of the channel, the back-propagation of Deep JTROCS training gradients is hindered which hinders the training of the neural networks in the transmitter. Although researchers have proposed methods to train transmitters using auxiliary tools such as channel models or feedback links, these tools are not available in many real-world communication scenarios, limiting the application of Deep JTROCS. In this paper, we propose a new method to use undertrained Deep JTROCS to transmit the training signals and use these signals to reconstruct the training gradient of the neural networks in the transmitter, thus avoiding the use of an additional reliable link. The experimental results show that the proposed method outperforms the additional link-based approach in different tasks and channels. In addition, experiments conducted on real wireless channels validate the practical feasibility of the method.

Computing the impact of central clearing on systemic risk.

The paper uses a graph model to examine the effects of financial market regulations on systemic risk. Focusing on central clearing, we model the financial system as a multigraph of trade and risk relations among banks. We then study the impact of central clearing by a priori estimates in the model, stylized case studies, and a simulation case study. These case studies identify the drivers of regulatory policies on risk reduction at the firm and systemic levels. The analysis shows that the effect of central clearing on systemic risk is ambiguous, with potential positive and negative outcomes, depending on the credit quality of the clearing house, netting benefits and losses, and concentration risks. These computational findings align with empirical studies, yet do not require intensive collection of proprietary data. In addition, our approach enables us to disentangle various competing effects. The approach thus provides policymakers and market practitioners with tools to study the impact of a regulation at each level, enabling decision-makers to anticipate and evaluate the potential impact of regulatory interventions in various scenarios before their implementation.

Machine learning predicts system-wide metabolic flux control in cyanobacteria

Metabolic fluxes and their control mechanisms are fundamental in cellular metabolism, offering insights for the study of biological systems and biotechnological applications. However, quantitative and predictive understanding of controlling biochemical reactions in microbial cell factories, especially at the system level, is limited. In this work, we present ARCTICA, a computational framework that integrates constraint-based modelling with machine learning tools to address this challenge. Using the model cyanobacterium Synechocystis sp. PCC 6803 as chassis, we demonstrate that ARCTICA effectively simulates global-scale metabolic flux control. Key findings are that (i) the photosynthetic bioproduction is mainly governed by enzymes within the Calvin–Benson–Bassham (CBB) cycle, rather than by those involve in the biosynthesis of the end-product, (ii) the catalytic capacity of the CBB cycle limits the photosynthetic activity and downstream pathways and (iii) ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is a major, but not the most, limiting step within the CBB cycle. Predicted metabolic reactions qualitatively align with prior experimental observations, validating our modelling approach. ARCTICA serves as a valuable pipeline for understanding cellular physiology and predicting rate-limiting steps in genome-scale metabolic networks, and thus provides guidance for bioengineering of cyanobacteria.

Cytotoxicity and concentration of silver ions released from dressings in the treatment of infected wounds: a systematic review.

Silver-releasing dressings are used in the treatment of infected wounds. Despite their widespread use, neither the amount of silver released nor the potential in vivo toxicity is known. The aim of this study was to evaluate the cytotoxic effects and the amount of silver released from commercially available dressings with infected wounds. The review was conducted according to the PRISMA statement. The Web of Science, PubMed, Embase, Scopus, and CINAHL databases were searched for studies from 2002 through December 2022. The criteria were as follows: population (human patients with infected wounds); intervention (commercial dressings with clinical silver authorized for use in humans); and outcomes (concentrations of silver ions released into tissues and plasma). Any study based on silver-free dressings, experimental dressings, or dressings not for clinical use in humans should be excluded. According to the type of study, systematic reviews, experimental, quasi-experimental, and observational studies in English, Spanish, or Portuguese were considered. The quality of the selected studies was assessed using the JBI critical appraisal tools. Studies that assessed at least 65% of the included items were included. Data were extracted independently by two reviewers. 740 articles were found and five were finally selected (all of them quasi-experimental). Heterogeneity was found in terms of study design, application of silver dressings, and methods of assessment, which limited the comparability between studies. In vivo comparative studies of clinical dressings for control of infection lack a standardized methodology that allows observation of all the variables of silver performance at local and systemic levels, as well as evaluation of its cytotoxicity. It cannot be concluded whether the assessed concentrations of released silver in commercial dressings for the topical treatment of infected wounds are cytotoxic to skin cells. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022351041, PROSPERO [CRD42022351041].

Impact of Immunopathy and Coagulopathy on Multi-Organ Failure and Mortality in a Lethal Porcine Model of Controlled and Uncontrolled Hemorrhage.

Uncontrolled hemorrhage is a major preventable cause of death in patients with trauma. However, the majority of large animal models of hemorrhage have utilized controlled hemorrhage rather than uncontrolled hemorrhage to investigate the impact of immunopathy and coagulopathy on multi-organ failure (MOF) and mortality. This study evaluates these alterations in a severe porcine controlled and uncontrolled hemorrhagic shock (HS) model. Anesthetized female swine underwent controlled hemorrhage and uncontrolled hemorrhage by partial splenic resection followed with or without lactated Ringer solution (LR) or Voluven® resuscitation. Swine were surveyed 6 h after completion of splenic hemorrhage or until death. Blood chemistry, physiologic variables, systemic and tissue levels of complement proteins and cytokines, coagulation parameters, organ function, and damage were recorded and assessed. HS resulted in systemic and local complement activation, cytokine release, hypocoagulopathy, metabolic acidosis, MOF, and no animal survival. Resuscitation with LR and Voluven® after HS improved hemodynamic parameters (MAP and SI), metabolic acidosis, hyperkalemia, and survival but resulted in increased complement activation and worse coagulopathy. Compared with the LR group, the animals with hemorrhagic shock treated with Voluven® had worse dilutional anemia, coagulopathy, renal and hepatic dysfunction, increased myocardial complement activation and renal damage, and decreased survival rate. Hemorrhagic shock triggers early immunopathy and coagulopathy and appears associated with MOF and death. This study indicates that immunopathy and coagulopathy are therapeutic targets that may be addressed with a high-impact adjunctive treatment to conventional resuscitation.

Derivation of an Annualized Claims-Based Major Adverse Cardiovascular Event Estimator in Type 2 Diabetes

BackgroundMajor adverse cardiovascular events (MACE) are a leading cause of morbidity and mortality among adults with type 2 diabetes. Currently, available MACE prediction models have important limitations, including reliance on data that may not be routinely available, narrow focus on primary prevention, limited patient populations, and longtime horizons for risk prediction. ObjectivesThe purpose of this study was to derive and internally validate a claims-based prediction model for 1-year risk of MACE in type 2 diabetes. MethodsUsing medical and pharmacy claims for adults with type 2 diabetes enrolled in commercial, Medicare Advantage, and Medicare fee-for-service plans between 2014 and 2021, we derived and internally validated the annualized claims-based MACE estimator (ACME) model to predict the risk of MACE (nonfatal acute myocardial infarction, nonfatal stroke, and all-cause mortality). The Cox proportional hazards model was composed of 30 covariates, including patient age, sex, comorbidities, and medications. ResultsThe study cohort comprised 6,623,526 adults with type 2 diabetes, mean age 68.1 ± 10.6 years, 49.8% women, and 73.0% Non-Hispanic White. ACME had a concordance index of 0.74 (validation index range: 0.739-0.741). The predicted 1-year risk of the study cohort ranged from 0.4% to 99.9%, with a median risk of 3.4% (IQR: 2.3%-6.5%). ConclusionsACME was derived in a large usual care population, relies on routinely available data, and estimates short-term MACE risk. It can support population risk stratification at the health system and payer levels, participant identification for decentralized clinical trials of cardiovascular disease, and risk-stratified observational studies using real-world data.

Assessment of the synthetic inertial response of an actual solar PV power plant

As the large-scale integration of renewable energy grows, inertia in power systems is reduced, which causes the rate of change of frequency to increase and worsens the frequency nadir during disturbances. There is, therefore, an urgent need to accelerate the development of international standards and regulations that require solar PV systems and other renewable installations to also contribute to stability in the network by emulating inertia. Spain is a pioneer in this field: it is currently the only country that includes the synthetic inertia technical requirement in its grid code. In this context, the present paper analyzes the synthetic inertial response of a PV system model that forms part of an actual PV power plant in Spain under two scenarios, according to its grid code: i) when measurements are conducted at the power conversion PV system level and hence only its control algorithms are executed; and ii) when measurements are conducted at the power plant level and the power plant controller also influences the response of the entire installation. Among its aims, this paper seeks to thoroughly assess the response of an actual PV power conversion system that has the capability of actively contributing to frequency regulation in a network and to critically analyze the suitability of having a power plant controller when the PV facility contributes to power-frequency control by means of an inertial response. The results reveal, at the power conversion PV system level, that the inertia emulation module significantly reduces the response times of the installation to changes in frequency -by more than 68% in the worst case under frequency increases, and by 73% under frequency decreases, thus contributing to more rapid power-frequency regulation in the network. However, at the power plant level, the power plant controller disturbs the PV power conversion system’s behavior and causes the opposite effect: response times increase -up to more than 7% in the most unfavorable case when the inertia module is enabled.

Severity of COVID-19 Infectious and Immune-Based Profile

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes immune system dysregulation and a systemic cytokine storm. Under healthy conditions, T helper cells protect against intracellular pathogens, extracellular parasites, and extracellular bacteria. Objectives: For the novelty of our study, little is known regarding the balance of T cell subtypes and responses in two forms of COVID-19 in our country. We investigated whether there was a relationship between T cell subtype frequency and cytokines by COVID-19 severity. Methods: Forty-six PCR-confirmed severe (n = 30) and moderate (n = 16) COVID-19 patients and 13 sex- and age-matched healthy control (HC) subjects were enrolled. Immunophenotyping of T cell subsets and related serum cytokines was performed using flow cytometry and ELISA, respectively. Results: There was a significantly lower frequency of CD8+Tbet+ (P < 0.01) T cells in the severe group compared to HC. Also, there was a significantly lower frequency of CD4+GATA3+ (P < 0.001) and CD8+Tbet+ (P < 0.001) T cells in the severe group compared to the moderate group. Moreover, receiver-operating characteristic (ROC) curve analysis revealed a considerable correlation between CTL (CD8+T-bet+) subtypes and the severity of the disease. Severe COVID-19 disease was associated with reduced interferon-gamma (IFN-γ) and interleukin (IL)-2 concentration and increased IL-5 and IL-6 concentration. Conclusions: Reduced systemic levels of IL-2 can trigger decreased numbers of Th1 and Th2 cells, and in contrast to elevated IL-5 and IL-6, the numbers of Th2 cells did not increase in these cases.

Modeling Operational Flow Capacity and Evaluating Disaster Interventions for Fuel Distribution

Fuel is an essential commodity in society with an amplified role during disasters. Disasters often cause a spike in demand for fuel and impose physical and operational constraints on fuel distribution. Accordingly, public and private sector stakeholders seek disaster preparedness and response interventions to ensure an adequate supply of fuel for emergency activities. We develop models to quantify downstream operational flow capacity, i.e., the volume of fuel that can be distributed from bulk storage terminals to retail gas stations via tanker trucks. We do this for both steady state conditions and nonsteady state conditions during disasters. The operational flow capacity measures can serve as inputs to optimal relief distribution and resource allocation problems, as well as enable a cost-benefit assessment of interventions aimed at increasing system capacity. We identify the best interventions for each type of bulk storage terminal structure and determine how to prioritize bulk storage terminals for each type of intervention when resources are limited. As the downstream fuel distribution system from bulk storage terminals to retail gas stations is similar across regions, our methodology and insights are generalizable not only within the US but also in countries with comparable distribution systems. To demonstrate impact on practice, we present a case study drawn from the application of our methodology to support US federal disaster preparedness. More generally, we contribute to system level understanding of multiserver tandem cyclic queues with time-limited customers found in relief distribution systems, which is often overlooked in the disaster management literature.

Digitally Recording Comfort Observations in the Last Days of Life.

Background: 37.5% of deaths in our area occur in hospital. There are known high unmet needs of adult patients dying in hospital, this unmet need can be reduced by using an individualised care plan and specialist palliative care review. Intervention: In 2022 UHSussex developed an electronic comfort observation chart and individualised care plan, with a centralised dashboard allowing Palliative Care Teams (SPCT) to view trends, target interventions, and a rolling prospective audit. Results: 3000 patients have had their care supported with electronic comfort observations (e-comfort obs). Over 72% of all deaths in the Trust in the last 3months have been on e-comfort obs, with 2/3 of all deaths in the first 12months on e-comfort obs. The average length of time on e-comfort obs is 4days resulting in 70,000 sets of e-comfort obs recorded since launch. Seven percent of e-comfort obs record moderate or severe symptoms. We have identified benefits to people who are dying, those important to them, ward staff, SPCT and on a systems level. Conclusion: E-comfort obs can be successfully embedded in a large acute Trust. This development should improve quality of end of life care in our hospitals both for individuals and for future patients, through on-going targeted education and intervention. Further work is needed to develop the system further including integrating data from electronic prescribing.

A systems thinking approach to capture the complexity of effective routes to teaching

AbstractSTEM teacher shortage remains a serious problem in secondary education in many European countries, despite many interventions and many research studies over the last decades. The observation that past interventions and research outcomes have not significantly contributed to reduce teacher shortage implies that places to effectively intervene in the teacher education system have not been found yet. In this article, a systems thinking approach is presented to evaluate the fundamental and structural problems of an academic teacher education system regarding STEM student entry. A thorough understanding of the systemic structure of a teacher education system is essential to identify leverage points for STEM teacher recruitment. Based on systems thinking principles and theoretical frameworks, a stepwise research framework was defined, which was tested in the Dutch academic teacher education system. First, potential factors of concern were identified based on the collection of many data such as existing public information, reports and long‐term student entry data. These potential factors of concern were subsequently investigated by student surveys and structured interviews with stakeholders from science faculties and teacher training institutes. Synthesis of the results led to the identification of three leverage points for increasing STEM student entry in teacher training, which were all found at the organizational and structural level of the academic teacher education system. The systems thinking research framework presented in this article provides a valuable framework to address persistent problems in education and enables the identification of novel and potentially more effective interventions.

Quantifying the carbon footprint of energy storage applications with an energy system simulation framework — Energy System Network

Energy storage is a crucial flexibility measure to temporally decouple power generation from power demand and is touted as the missing link in realizing a decarbonized energy system based on renewable energy. Energy storage capacity buildup at all levels of the global energy system is expected to accelerate the decarbonization process. To this end, a coherent mathematical framework to ascertain the carbon footprint of localized energy systems with energy storage is indispensable. This article presents an open-source energy system simulation program — Energy System Network (ESN). A variety of energy system configurations can be simulated with the Python program, which incorporates key energy system components such as generation, grid, storage, and loads. ESN features an integrated bottom-up approach that combines energy system modeling with streamlined life cycle assessment techniques to quantify the carbon footprint of all components in a localized energy system. The lifecycle phases of each component, including production, operation, and end-of-life treatment, can be considered. Carbon footprint values are obtained for two demonstrative case studies with lithium-ion battery applications: energy arbitrage and home energy systems. The metric Levelized Emissions of Energy Supply (LEES) has been used to evaluate the carbon footprint of each application. An unconventional energy arbitrage strategy designed to exploit the grid carbon intensity spreads instead of the energy price spreads manages to achieve a LEES value about 17% lower than the conventional variant. The influence of rooftop solar generation, battery energy storage system, and the energy management strategy on the LEES values for a home energy system is explored. A maximum LEES reduction of over 37% vis-á-vis the base scenario was observed with optimal energy management for the solar generation and the battery system. The open-source availability of ESN can contribute to transparency, comparability, and reproducibility in carbon footprint assessments of localized energy systems with energy storage.

We returned home empty-handed: COVID-19, care, and contested citizenship of Naga migrant workers in northeast India.

COVID-19 highlighted interconnections between matters of identity and citizenship, vulnerability, and inclusion in/exclusion from systems of care in times of crisis. Migrant workers from Nagaland state, northeast India, were disproportionately impacted by the pandemic's socioeconomic consequences. The public health emergency brought into question who is 'Indian' and the citizenship rights attached to that identity, heightening migrants' exclusion from central structures. Communitarian responses in Nagaland enhanced resilience in the face of often inadequate government responses; however, COVID-19 also exposed structural inequalities within and between Naga communities. This study shows that identity-based citizenship regimes and multi-nation federalism interact to increase minorities' exclusion during crises, and that crises can strengthen both divisions and solidarity at the local level in multi-nation federal systems. Inclusion in and exclusion from systems of care are shaped by and can reshape notions of identity and citizenship, underlining the need for inclusive sociopolitical systems to mitigate crises in multi-nation federal states.

Barriers to cervical cancer screening in Africa: a systematic review

IntroductionAfrica has one of the highest burdens of cervical cancer in the world. The unacceptably high incidence and mortality rates could be reduced through implementing a comprehensive approach to its prevention and control that includes screening, which however, is low in most low-and-middle-income countries. Hence, this systematic review aims at exploring factors that prevent women from utilising cervical cancer screening services in the region.MethodsA mixed method systematic review was conducted. A search was performed on PubMed (Medline), EMBASE, CINAHL (EBSCOHOST) and Scopus databases for articles published until May 2019 without time, language or study design limits. Two reviewers critically appraised the included studies independently using the standard quality assessment criteria for evaluating primary research papers. Results of the quantitative and mixed methods studies were transformed into qualitative data and synthesised using thematic analysis.ResultsFrom a potential 2 365 studies, 24 from 11 countries met the eligibility criteria and were selected; eight qualitative, 13 quantitative, and three that used the mixed-method approach. The primary barriers were identified as poor access to screening services, lack of awareness and knowledge on cervical cancer and screening, and socio-cultural influences. Service providers perceived lack of skills, screening equipment and supplies, and staff shortages as the major barriers to the provision of screening services.ConclusionBarriers to cervical cancer screening in Africa are multifaceted and require a holistic approach that will address them concurrently at the health system, individual, interpersonal, community and structural levels. Political will complimented by stakeholder involvement is required in the development and implementation of strategies that will ensure acceptability, availability, accessibility, and affordability of screening to minimise barriers in accessing the service.

When rules turn into tools: An activity theory-based perspective on implementation processes and unintended consequences.

The idea that actions of people, organizations or governments may lead to Unintended Consequences (UICs) is not new. In health, UICs have been reported as a result of various interventions including quality improvement initiatives, health information technology implementation, and knowledge translation, especially those involving translation of broad policies (evidence-based medicine and patient-centred care) or system level improvement into actionable items or tools. While some unintended consequences cannot be anticipated, others may be predictable. In this article, we present a model based on cultural historical activity theory, which may help policy-makers, health leaders, and researchers better anticipate UICs resulting from implementation of new programs or technologies and take action to address them or mitigate their risk of occurrence. We support this model using examples of UICs of implementing family centred care principles, electronic health records, and computerized templates for quality improvement in chronic disease management.