Global Task Research Articles

Stable perceptual phenotype of the magnitude of history biases even in the face of global task complexity.

According to a Bayesian framework, visual perception requires active interpretation of noisy sensory signals in light of prior information. One such mechanism, serial dependence, is thought to promote perceptual stability by assimilating current percepts with recent stimulus history. Combining a delayed orientation-adjustment paradigm with predictable (study 1) or unpredictable (study 2) task structure, we test two key predictions of this account in a novel context: first, that serial dependence should persist even in variable environments, and, second, that, within a given observer and context, this behavioral bias should be stable from one occasion to the next. Relying on data of 41 human volunteers and two separate experimental sessions, we confirm both hypotheses. Group-level, attractive serial dependence remained strong even in the face of volatile settings with multiple, unpredictable types of tasks, and, despite considerable interindividual variability, within-subject patterns of attractive and repulsive stimulus-history biases were highly stable from one experimental session to the next. In line with the hypothesized functional role of serial dependence, we propose that, together with previous work, our findings suggest the existence of a more general individual-specific fingerprint with which the past shapes current perception. Congruent with the Bayesian account, interindividual differences may then result from differential weighting of sensory evidence and prior information.

Cooperative Swarm Intelligence Algorithms for Adaptive Multilevel Thresholding Segmentation of COVID-19 CT-Scan Images

The Coronavirus Disease 2019 (COVID-19) is widespread throughout the world and poses a serious threat to public health and safety. A COVID-19 infection can be recognized using computed tomography (CT) scans. To enhance the categorization, some image segmentation techniques are presented to extract regions of interest from COVID-19 CT images. Multi-level thresholding (MLT) is one of the simplest and most effective image segmentation approaches, especially for grayscale images like CT scan images. Traditional image segmentation methods use histogram approaches; however, these approaches encounter some limitations. Now, swarm intelligence inspired meta-heuristic algorithms have been applied to resolve MLT, deemed an NP-hard optimization task. Despite the advantages of using meta-heuristics to solve global optimization tasks, each approach has its own drawbacks. However, the common flaw for most meta-heuristic algorithms is that they are unable to maintain the diversity of their population during the search, which means they might not always converge to the global optimum. This study proposes a cooperative swarm intelligence-based MLT image segmentation approach that hybridizes the advantages of parallel meta-heuristics and MLT for developing an efficient image segmentation method for COVID-19 CT images. An efficient cooperative model-based meta-heuristic called the CPGH is developed based on three practical algorithms: particle swarm optimization (PSO), grey wolf optimizer (GWO), and Harris hawks optimization (HHO). In the cooperative model, the applied algorithms are executed concurrently, and a number of potential solutions are moved across their populations through a procedure called migration after a set number of generations. The CPGH model can solve the image segmentation problem using MLT image segmentation. The proposed CPGH is evaluated using three objective functions, cross-entropy, Otsu’s, and Tsallis, over the COVID-19 CT images selected from open-sourced datasets. Various evaluation metrics covering peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and universal quality image index (UQI) were employed to quantify the segmentation quality. The overall ranking results of the segmentation quality metrics indicate that the performance of the proposed CPGH is better than conventional PSO, GWO, and HHO algorithms and other state-of-the-art methods for MLT image segmentation. On the tested COVID-19 CT images, the CPGH offered an average PSNR of 24.8062, SSIM of 0.8818, and UQI of 0.9097 using 20 thresholds.

International Decade of Indigenous Languages: the history of formation, legal framework, implementation mechanisms

Introduction. The main objective of this article is to study the historical and legal aspects of the establishment of the International Decade of Indigenous Languages (2022–2032), proclaimed by the United Nations General Assembly, as well as to analyze international instruments, establishing the legal framework and mechanisms for the implementation of the Decade. Materials and Methods. The research methods are based on a system approach. The general research (system, analysis and synthesis) and subject specific methods of knowledge (historical, formal-legal) were applied during the research. The main international legal instruments for the International Decade of Indigenous Languages were used. This article explored a wide range of regulatory sources. Results and Discussion. The article considers the historical stages of formation and development of the International Decade of Indigenous Languages, gives an overview of international legal documents and normative legal acts of the Russian Federation, which constitute the legal framework for the implementation of the Decade. The article also considers the main mechanisms of management, coordination and implementation of the Decade, among which are the following: UNESCO, Global Task Force providing strategic guidance and oversight in the areas of planning, implementation and monitoring of progress towards the goals set by the Global Plan of Action. This document provides a strategic framework, describes the main actions and guidelines for the implementation, monitoring and evaluation of the activities of the UN, national governments, indigenous peoples’ organizations, civil society, academia, the private sector and others. Conclusion. The author concludes that, at the level of the international community, there is a rather serious understanding of the need to preserve and develop languages, the realization of the linguistic rights of indigenous peoples, The International Decade of Indigenous Languages will contribute to this end. The Decade provides a unique opportunity to introduce additional support measures, including by reforming national legislation, language training, digital language development, etc.

OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself—OME-Zarr—along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain—the file format that underlies so many personal, institutional, and global data management and analysis tasks.

Sine cosine algorithm with communication and quality enhancement: Performance design for engineering problems

Abstract In recent years, the sine cosine algorithm (SCA) has become one of the popular swarm intelligence algorithms due to its simple and convenient structure. However, the standard SCA tends to fall into the local optimum when solving complex multimodal tasks, leading to unsatisfactory results. Therefore, this study presents the SCA with communication and quality enhancement, called CCEQSCA. The proposed algorithm includes two enhancement strategies: the communication and collaboration strategy (CC) and the quality enhancement strategy (EQ). In the proposed algorithm, CC strengthens the connection of SCA populations by guiding the search agents closer to the range of optimal solutions. EQ improves the quality of candidate solutions to enhance the exploitation of the algorithm. Furthermore, EQ can explore potential candidate solutions in other scopes, thus strengthening the ability of the algorithm to prevent trapping in the local optimum. To verify the capability of CCEQSCA, 30 functions from the IEEE CEC2017 are analyzed. The proposed algorithm is compared with 5 advanced original algorithms and 10 advanced variants. The outcomes indicate that it is dominant over other comparison algorithms in global optimization tasks. The work in this paper is also utilized to tackle three typical engineering design problems with excellent optimization capabilities. It has been experimentally demonstrated that CCEQSCA works as an effective tool to tackle real issues with constraints and complex search space.

Sponge Grid With Numerous Virtual Energy Storage Systems: Concept, Model, and Decentralized Control

High proportion of energy storage systems (ESSs) and flexible loads signify the main features of a modern power system. ESS with its bi-directional flow characteristic can flexibly change power network operations, thus providing a new solution for voltage regulation and control. However, since ESS resources are dispersed throughout the power system, it is necessary to design an effective aggregation scheme to achieve a concise voltage regulation. In this paper, a novel sponge grid is proposed, which is capable of both local and global tasks to offer greater flexibility and initiative in power system operations. On the one hand, it constructs the source and forms virtual energy storage (VES) systems to satisfy local demands. On the other hand, the sponge grid applies the superposition of a large number of VES systems spontaneous effects to present a collective voltage regulation behavior. Then, a message passing-based decentralized algorithm is proposed and designed for the local voltage regulation in the sponge grid. Various constraints including those representing inequality boundary, state of charge, and complex line flows, are expressed analytically and computed fast by the proposed portable projection approach. The proposed sponge grid model is tested on a modified IEEE 33-bus system to verify its effectiveness and superior performance.

Symmetric cross-entropy multi-threshold color image segmentation based on improved pelican optimization algorithm.

To address the problems of low accuracy and slow convergence of traditional multilevel image segmentation methods, a symmetric cross-entropy multilevel thresholding image segmentation method (MSIPOA) with multi-strategy improved pelican optimization algorithm is proposed for global optimization and image segmentation tasks. First, Sine chaotic mapping is used to improve the quality and distribution uniformity of the initial population. A spiral search mechanism incorporating a sine cosine optimization algorithm improves the algorithm's search diversity, local pioneering ability, and convergence accuracy. A levy flight strategy further improves the algorithm's ability to jump out of local minima. In this paper, 12 benchmark test functions and 8 other newer swarm intelligence algorithms are compared in terms of convergence speed and convergence accuracy to evaluate the performance of the MSIPOA algorithm. By non-parametric statistical analysis, MSIPOA shows a greater superiority over other optimization algorithms. The MSIPOA algorithm is then experimented with symmetric cross-entropy multilevel threshold image segmentation, and eight images from BSDS300 are selected as the test set to evaluate MSIPOA. According to different performance metrics and Fridman test, MSIPOA algorithm outperforms similar algorithms in global optimization and image segmentation, and the symmetric cross entropy of MSIPOA algorithm for multilevel thresholding image segmentation method can be effectively applied to multilevel thresholding image segmentation tasks.

Developing context-specific water, sanitation and hygiene guidance for National Cholera Plans: Qualitative inputs

Globally, cholera continues to cause morbidity and mortality, and the Global Task Force on Cholera Control (GTFCC) works with countries affected by cholera to develop National Cholera Plans (NCPs). Water, sanitation, and hygiene (WASH) can prevent and/or control cholera. However, WASH program success varies, and is not necessarily replicable across contexts. Thus, guidance needs to be developed to assist countries in appropriately designing WASH programming in NCPs. The objective of this project was to develop guidelines for selecting context-specific WASH for cholera response. For that, a literature review of WASH interventions in cholera was completed, a Working Group was convened to collaboratively develop the guidelines, and we conducted key informant interviews (KII) with Working Group experts, representing international and national non-governmental organizations, donors, international organizations and health authorities. Inductive qualitative content analysis of KIIs was completed. KIIs were conducted with 18 informants, and data was coded into 26 subcategories, categorized under: 1) intervention objectives; 2) decision factors; 3) intervention circumstances; 4) influencing factors; and, 5) WASH activities. Based on these categories, we developed guidelines with the following steps: 1) define the disease objective (control, prevention, or elimination); 2) understand and define the broad context (including existing WASH infrastructure and population habits, available funding, outbreak sources and transmission pathways, stakeholder capacity, and access difficulties); and, 3) focus on monitoring of activities, multi-sectoral coordination (including WASH and health), and targeted approaches, both for implementation and future research. Overall, while building upon previous research and guidance, our results expand to include specific guidance for countries incorporating WASH into their NCPs, and highlight the necessity of a broad contextual understanding to select the most appropriate and successful WASH for cholera programming. These results have been used, with GTFCC, to develop a guidance document for including context-specific WASH in NCPs.

Integrated planning and control for formation reconfiguration of multiple spacecrafts: A predictive behavior control approach

This paper addresses the trajectory planning and control problem of multi-spacecraft formation reconstruction in the presence of obstacles. By expressing spacecraft dynamics relative to a leader spacecraft in the formation, an integrated planning and control approach named predictive null-space-based behavior control (PNSBC) is proposed. First, a planner using null-space-based behavior control (NSBC) is designed at an upper layer to resolve multi-task conflicts. Here, both global tasks, e.g. formation keeping, and local tasks, e.g. obstacle avoidance, are considered. Second, a tracking controller is designed at the bottom layer using decentralized model predictive control. Unlike traditional two-layer approaches that treat planning and control separately, the proposed PNSBC integrates the planning and control in two ways: 1) the planner provides reference trajectories for the controller to track; 2) the model predictive control (MPC) controller provides predicted trajectories that can be employed by the planner for future task priority predictions, which extends the capability of NSBC from one-step planning to multi-step predicting. In addition, the computational burden of the MPC controller is greatly reduced by putting the nonlinear obstacle avoidance constraints into the planner as a local task. Simulation results show that such integrated approach has better performance in terms of safety constraint guarantee, fuel consumption and travel distance when compared against traditional non-integrated approaches, or all-in-one MPC methods, while constraints and task objectives are fully satisfied.

Subjective cognitive concerns differ by race/ethnicity among einstein aging study (EAS) participants: Implications for assessment and interpretation of self‐perceived cognitive functioning

AbstractBackgroundSubjective cognitive concerns (SCC) play an important role in the identification of preclinical dementia, especially among individuals who have experienced health disparities. It is critical to discern differential patterns of SCC endorsement among racially/ethnically diverse groups to enhance the ability to accurately capture current and future cognitive status. Moreover, it is important to determine whether the association of SCCs and objective neuropsychological test scores vary by racial/ethnic background.MethodUsing data from the EAS, a longitudinal community residing cohort aged 70+, SCCs were captured using an expanded version of the Cognitive Change Index (CCI‐40), which taps multiple cognitive domains. Objective cognition was measured using the FCSRT and tests from the Uniform Data Set, Neuropsychological Battery (UDSNB3.0). Linear regression models evaluated racial/ethnic differences in SCC at baseline. Additional models for objective cognition examined its association with SCC adjusting for racial/ethnic groups, and furthermore the interaction effects between race/ethnicity and SCC. Covariates included demographics, depressive symptoms, income, and co‐morbidities.ResultWe included 313 participants of non‐Hispanic (NH) White (47%), NH Black (40%) and Hispanic/Latino (13%) racial/ethnic groups who were not demented at baseline. NH Blacks and Hispanic/Latino participants reported significantly more SCC than NH Whites after adjusting for covariates. Higher CCI‐40 scores were associated with worse FCSRT free recall and Trail Making Test Part B performing, adjusting for race and other covariates. When interactions between race/ethnicity and CCI‐40 were included, higher levels of SCC were associated with lower MoCA and FCSRT free recall scores for NH Whites but not for NH Blacks.ConclusionStronger perceptions of self‐reported cognitive decline do not necessarily correspond to worse performance on memory and global cognitive tasks for all racial groups. Although racial/ethnic differences were found in levels of SCC, it is important to investigate factors that may influence self‐perceived cognitive functioning for specific groups (e.g., health status, social support), and the consequential impact on access to healthcare settings (where assessment and diagnosis typically occur). In addition, researchers should consider diversity variables when setting cut points on self‐report questionnaires to enhance diagnostic sensitivity and inform optimal assessment and monitoring needs.

Robust Control of Dual-Linear-Motor-Driven Gantry Stage for Coordinated Contouring Tasks Based on Feed Velocity

Contouring control is one of the most important tasks for the dual-linear-motor-driven gantry system (DLMDGS), whose control performance determines the in various precision machining equipment, mainly industrial machine tools. Nevertheless, there are some limitations in present results, including the insufficient consideration of system uncertainty and the approximation errors introduced by the computation of the path length. To overcome these issues, the effects of the rotational dynamic and uncertainties are studied and further refined in this article, and a robust control scheme with adaptive neural network identification is designed based on the desired contouring velocity. The method improves existing approaches and avoids the imperfection of the previous one, based on tracking control under global task coordinate frame. The effects of various environmental forces are considered and the B-spline wavelet neural network is employed to approximate unknown dynamic caused by the thrust ripples of the three motors. Some experiments on a real system verify the effectiveness and superiority of the proposed velocity-based contouring control method.

Forum: Navigating the Global South Landscape: Insights and Implications for Representation and Inclusion in ISA Journals

Abstract The International Studies Association (ISA) is widely recognized as an American-European-centric professional organization, with Global South scholars traditionally representing a minority of its membership. This pattern largely reflects the development of the International Relations (IR) discipline and its publication trends. In this Forum, we examine the progress made in the representation of Global South scholars within the IR discipline over the past decade, specifically focusing on the ISA as the primary professional body for IR scholars. We tackle some issues the Global South Task Force (GSTF) highlighted to a more assertive representativeness of the Global South within the ISA. Our analysis concentrates on ISA's journals data tracking to capture the current state of affairs and foster dialogue on developing inventive solutions to enhance diversity, intellectual plurality, and scholarly cultures within the IR discipline. Rather than resorting to outright criticism, we adopt a constructive stance, discussing attempted solutions and proposing steps to advance the discipline.

Prioritizing interventions for cholera control in Kenya, 2015-2020.

Kenya has experienced cholera outbreaks since 1971, with the most recent wave beginning in late 2014. Between 2015-2020, 32 of 47 counties reported 30,431 suspected cholera cases. The Global Task Force for Cholera Control (GTFCC) developed a Global Roadmap for Ending Cholera by 2030, which emphasizes the need to target multi-sectoral interventions in priority cholera burden hotspots. This study utilizes the GTFCC's hotspot method to identify hotspots in Kenya at the county and sub-county administrative levels from 2015 through 2020. 32 of 47 (68.1%) counties reported cholera cases during this time while only 149 of 301 (49.5%) sub-counties reported cholera cases. The analysis identifies hotspots based on the mean annual incidence (MAI) over the past five-year period and cholera's persistence in the area. Applying a MAI threshold of 90th percentile and the median persistence at both the county and sub-county levels, we identified 13 high risk sub-counties from 8 counties, including the 3 high risk counties of Garissa, Tana River and Wajir. This demonstrates that several sub-counties are high level hotspots while their counties are not. In addition, when cases reported by county versus sub-county hotspot risk are compared, 1.4 million people overlapped in the areas identified as both high-risk county and high-risk sub-county. However, assuming that finer scale data is more accurate, 1.6 million high risk sub-county people would have been misclassified as medium risk with a county-level analysis. Furthermore, an additional 1.6 million people would have been classified as living in high-risk in a county-level analysis when at the sub-county level, they were medium, low or no-risk sub-counties. This results in 3.2 million people being misclassified when county level analysis is utilized rather than a more-focused sub-county level analysis. This analysis highlights the need for more localized risk analyses to target cholera intervention and prevention efforts towards the populations most vulnerable.

Current state of the coal ash handling problem in Russia and abroad, aspects of the coal ash applications in hydrogen economy

One of the global state tasks, contributing to the implementation of the goal of developing the energy sector of the Russian Federation and given in the Energy Strategy of the Russian Federation for the period until 2035, is to reduce the negative impact of the fuel and energy complex industries on the environment.In this regard, special attention is paid to the coal ash handling problem, which is intensified by tightening of the environmental legislation with the transition to the principles of the best available technologies, greening of the coal power, depletion of the capacity of the coal ash disposal sites, etc. Disposal of ash, slag, ash-and-slag mixtures, formed at combustion of coal, peat and shale, is one of the main problems of the modern solid-fuel thermal power plants in Russia, the number of which makes 172. The average age of the coal-fired TPPs is about 50 years that significantly affects the technical and environmental performance of the ash removal system of TPPs. At the Russian TPPs for the ash and slag conveying hydraulic ash removal systems are the most common, used in the vast majority of cases being technically outdated, uneconomical and ecologically not friendly.Annually 25 … 30 million tons of ash and slag are formed at the coal-fired power plants of the Russian Federation. Currently more than 1.5 billion tons of ash and slag are accumulated at the ash disposal sites of thermal power plants, and every year these figures are growing. About 2/3 of all ash and slag disposals are close to the design filling or are already overfilled. Elimination of objects of the accumulated environmental damage, representing ash disposals of the coal-fired power plants, is one of the conditions for Russia's transition to the standards of “green” economy. The problem of coal-fired power plants in terms of elimination of the accumulated environmental damage can be solved only by implementing the large-scale projects of integrated coal ash processing, obtaining required products.The article provides statistical data for the 2019 relating to the volumes of the coal ash generation and utilization in various countries of the world. An overview of the various applications of the coal combustion by-products, the main of which are ash and slag, in Russia, India, China, EU countries, etc. is presented. The article contains data on the applicability of the coal ash for various technologies of its use according to the Russian Ministry of Energy. A review of scientific and technical information sources on the prospects of using coal ash in hydrogen power engineering for hydrogen sorption and storage is given, as well as a review of traditional methods of hydrogen storage. Terminology in the field of coal ash handling found in scientific and technical information sources is considered, and a classification of coal combustion by-products in Russia and abroad is given. The main recommendations of the author, contributing to the increase in the use of coal ash in Russia, are given.

O024 Development and validation of a “lab in a box” for remote delivery of core reconstructive surgical skills

Abstract Introduction Junior doctors and aspiring surgical trainees can have limited surgical exposure and developmental teaching because of rapid rotations, inconsistent rotas, reduced theatre time, and high working pressures. The global pandemic has also initiated a paradigm shift in education, and the methods we use to deliver education. Our aims are to assess the feasibility and validity of a low cost, remote plastic surgical skills course in comparison to the same course delivered face-to-face. Methods Our bench-model simulation “Lab in a Box” design was delivered to students remotely and in person. The essential and advanced plastic surgery course included suturing, excision, tendon repair, and local flap design. We undertook a pilot course facilitated by an online platform using a two-device set up. Equipment, including synthetic tendons and skin substitutes, were distributed to each participant. Quantitative evaluation included a global rating assessment and task specific criteria using a 1-5 Likert scale. Results were compared to the face-to-face control group. Qualitative feedback was also collected. Results A total of 40 students were recruited. A total cost of less than £30 was achieved. Quantitative feedback demonstrated comparable outcomes in remote training vs face-to-face training. Students reported excellent quality of audio-visual material and equipment, clear feedback, and 100% would recommend this course. Conclusion The simulation training course developed provides high-quality, engaging, reproducible and low-cost surgical skills training that can be delivered via distance learning. This model can be used to improve surgical skills training both in the UK and globally in resource poor environments.

Efficient multi-task learning with adaptive temporal structure for progression prediction

In this paper, we propose a novel efficient multi-task learning formulation for the class of progression problems in which its state will continuously change over time. To use the shared knowledge information between multiple tasks to improve performance, existing multi-task learning methods mainly focus on feature selection or optimizing the task relation structure. The feature selection methods usually fail to explore the complex relationship between tasks and thus have limited performance. The methods centring on optimizing the relation structure of tasks are not capable of selecting meaningful features and have a bi-convex objective function which results in high computation complexity of the associated optimization algorithm. Unlike these multi-task learning methods, motivated by a simple and direct idea that the state of a system at the current time point should be related to all previous time points, we first propose a novel relation structure, termed adaptive global temporal relation structure (AGTS). Then we integrate the widely used sparse group Lasso, fused Lasso with AGTS to propose a novel convex multi-task learning formulation that not only performs feature selection but also adaptively captures the global temporal task relatedness. Since the existence of three non-smooth penalties, the objective function is challenging to solve. We first design an optimization algorithm based on the alternating direction method of multipliers (ADMM). Considering that the worst-case convergence rate of ADMM is only sub-linear, we then devise an efficient algorithm based on the accelerated gradient method which has the optimal convergence rate among first-order methods. We show the proximal operator of several non-smooth penalties can be solved efficiently due to the special structure of our formulation. Experimental results on four real-world datasets demonstrate that our approach not only outperforms multiple baseline MTL methods in terms of effectiveness but also has high efficiency.

How do confidence and self-beliefs relate in psychopathology: a transdiagnostic approach

Confidence is suggested to be a key component in psychiatry and manifests at various hierarchical levels, from confidence in a decision (local confidence), to confidence about performance (global confidence), to higher-order traits such as self-beliefs. Most research focuses on local confidence, but global levels may relate more closely to symptoms. Here, using a transdiagnostic framework, we tested the relationships between self-reported psychopathology, local and global confidence, and higher-order self-beliefs in a general population sample (N = 489). We show contrasting relationships between confidence and psychopathology dimensions. An anxious-depression dimension related to local and global underconfidence. By contrast, a compulsive-intrusive-thoughts dimension related to increased overconfidence at both levels, and showed a decoupling between (1) higher-order self-beliefs and (2) local and global task confidence. The strongest predictor of mental health was a self-beliefs dimension. This study examines higher-order confidence in relation to psychiatric symptoms fluctuating in the general population. Critically, psychopathological symptoms show distinct associations with confidence. Using a transdiagnostic approach, Hoven et al. investigated the relationship between self-reported psychiatric symptoms and metacognition, from confidence to self-beliefs.

Cholera past and future in Nigeria: Are the Global Task Force on Cholera Control’s 2030 targets achievable?

Understanding and continually assessing the achievability of global health targets is key to reducing disease burden and mortality. The Global Task Force on Cholera Control (GTFCC) Roadmap aims to reduce cholera deaths by 90% and eliminate the disease in twenty countries by 2030. The Roadmap has three axes focusing on reporting, response and coordination. Here, we assess the achievability of the GTFCC targets in Nigeria and identify where the three axes could be strengthened to reach and exceed these goals. Using cholera surveillance data from Nigeria, cholera incidence was calculated and used to model time-varying reproduction number (R). A best fit random forest model was identified using R as the outcome variable and several environmental and social covariates were considered in the model, using random forest variable importance and correlation clustering. Future scenarios were created (based on varying degrees of socioeconomic development and emissions reductions) and used to project future cholera transmission, nationally and sub-nationally to 2070. The projections suggest that significant reductions in cholera cases could be achieved by 2030, particularly in the more developed southern states, but increases in cases remain a possibility. Meeting the 2030 target, nationally, currently looks unlikely and we propose a new 2050 target focusing on reducing regional inequities, while still advocating for cholera elimination being achieved as soon as possible. The 2030 targets could potentially be reached by 2030 in some parts of Nigeria, but more effort is needed to reach these targets at a national level, particularly through access and incentives to cholera testing, sanitation expansion, poverty alleviation and urban planning. The results highlight the importance of and how modelling studies can be used to inform cholera policy and the potential for this to be applied in other contexts.

A thermostable, dry formulation inactivated Hikojima whole cell/cholera toxin B subunit oral cholera vaccine

The feared diarrheal disease cholera remains an important global health problem. Use of oral cholera vaccine (OCV) from a global stockpile against both epidemic and endemic cholera is a cornerstone in the World Health Organisations (WHOs) global program for “Ending cholera by 2030”. Three liquid inactivated whole-cell OCVs (Dukoral®, ShancholTM, and Euvichol-Plus®) are WHO prequalified and have proved to be safe and effective. However, their multicomponent composition and cold-chain requirement increase manufacturing, storage and transport costs. ShancholTM and Euvichol-Plus® OCVs used in WHOs global vaccine stockpile also lack the protective cholera toxin B-subunit (CTB) antigen present in Dukoral®, which results in suboptimal efficacy.WHOs Global Task Force on Cholera Control (GTFCC) has identified a thermostable, dry formulation vaccine as a priority for further OCV development. We describe here the development of such a vaccine, based on a lyophilized mixture of a single strain of formalin-killed Hikojima bacteria together with a low-cost, recombinantly produced CTB. The new vaccine, which is easy and inexpensive to manufacture, could be stored for at least 26 months at 25 °C and for at least 8 months at 40 °C with preservation of cell morphology and with no loss of protective Ogawa and Inaba lipopolysaccharides or CTB. It also proved to be well tolerated and to have equivalent oral immunogenicity in mice as ShancholTM and Dukoral® OCVs with regard to both serum and intestinal-mucosal antibody responses.

Vibrio cholerae in rural and urban Bangladesh, findings from hospital-based surveillance, 2000–2021

With more than 100,000 cases estimated each year, Bangladesh is one of the countries with the highest number of people at risk for cholera. Moreover, Bangladesh is formulating a countrywide cholera-control plan to satisfy the GTFCC (The Global Task Force on Cholera Control) Roadmap's goals. With a particular focus on cholera trends, variance in baseline and clinical characteristics of cholera cases, and trends in antibiotic susceptibility among clinical isolates of Vibrio cholerae, we used data from facility-based surveillance systems from icddr,b’s Dhaka, and Matlab Hospitals from years 2000 to 2021. Female patients comprised 3,553 (43%) in urban and 1,099 (51.6%) in rural sites. Of the cases and most patients 5,236 (63.7%) in urban and 1,208 (56.7%) in the rural site were aged 15 years and more. More than 50% of the families belonged to the poor and lower-middle-class; in 2009 (24.4%) were in urban and in 1,791 (84.2%) were in rural sites. In the urban site, 2,446 (30%) of households used untreated drinking water, and 702 (9%) of families disposed of waste in their courtyard. In the multiple logistic regression analysis, the risk of cholera has significantly increased due to waste disposal in the courtyard and the boiling of water has a protective effect against cholera. Rotavirus (9.7%) was the most prevalent co-pathogen among the under-5 children in both sites. In urban sites, the percentage of V. cholerae along with co-existing ETEC and Campylobacter is changing in the last 20 years; Campylobacter (8.36%) and Enterotoxigenic Escherichia coli (ETEC) (7.15%) were the second and third most prevalent co-pathogens. Shigella (1.64%) was the second most common co-pathogen in the rural site. Azithromycin susceptibility increased slowly from 265 (8%) in 2006–2010 to 1485 (47.8%) in 2016–2021, and erythromycin susceptibility dropped substantially over 20 years period from 2,155 (98.4%) to 21 (0.9%). Tetracycline susceptibility decreased in the urban site from 2051 (45.9%) to 186 (4.2%) and ciprofloxacin susceptibility decreased from 2,581 (31.6%) to 1,360 (16.6%) until 2015, then increased 1,009 (22.6%) and 1,490 (18.2%) in 2016–2021, respectively. Since 2016, doxycycline showed 902 (100%) susceptibility. Clinicians need access to up-to-date information on antimicrobial susceptibility for treating hospitalized patients. To achieve the WHO-backed objective of eliminating cholera by 2030, the health systems need to be put under a proper surveillance system that may help to improve water and sanitation practices and deploy oral cholera vaccines strategically.