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Background: During the COVID-19 pandemic, effective contact tracing was recognized as a crucial public health response to mitigate the spread of SARS-CoV-2 and reduce COVID-19-related morbidity and mortality, particularly before widespread vaccination. The World Health Organization (WHO) recommended implementing active surveillance strategies to trace and quarantine contacts of confirmed or suspected COVID-19 cases. Methods: A detailed review and analysis of the COVID-19 contact tracing responses was conducted in five European countries and territories, between March 2021 and August 2022. The countries and territories were selected to ensure geographical representation across the WHO European Region and applied a mixed-methods approach of in-depth interviews with various stakeholders across different administrative levels to identify good practices in COVID-19 contact tracing. The interviews covered 12 themes, including methods and procedures for COVID-19 contact tracing, information technology, quality assurance and key performance indicators. Results: The findings demonstrate that the policy approach, digitalization capabilities and implementation approach varied in the countries and territories and were dynamic throughout the pandemic. The analysis revealed that some practices were applicable across all countries and territories, while others were context-specific, catering to each country's and territory's unique needs. The study highlighted a need for all countries to institutionalize contact tracing as an essential function of existing health systems, to digitalize contact tracing practices and processes, and to build and retain contact tracing capacities for better pandemic preparedness. Conclusion: The lessons related to COVID-19 contact tracing should be utilized to strengthen future outbreak response operations as part of epidemic and pandemic preparedness. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is a growing global public health challenge associated with 4.95 million deaths in 2019 and an estimated 10 million deaths per year by 2050 in the absence of coordinated action. A robust AMR surveillance system is therefore required to avert such a scenario. Based on an analysis of country-level AMR data in 8 Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) countries, we present a list of key recommendations to strengthen AMR surveillance. We propose 10 primary considerations under 3 broad categories, including recommendations on (1) laboratory and testing practices, (2) data management and analysis, and (3) data use. [ABSTRACT FROM AUTHOR]

Modern solutions for precise fault localisation in Low Voltage (LV) Distribution Networks (DNs) often rely on costly tools such as the micro-Phasor Measurement Unit (μ PMU), which is potentially impractical for the large number of nodes in LVDNs. This paper introduces a novel fault detection technique using a distribution network digital twin without the use of μ PMUs. The Digital Twin (DT) integrates data from Smart Meters (SMs) and network topology to create an accurate replica. In using SM voltage-magnitude readings, the pre-built twin compiles a database of fault scenarios and matches them with their unique voltage fingerprints. However, this SM-based voltage-only approach shows only a 70.7% accuracy in classifying fault type and location. Therefore, this research suggests using the cables' Currents Symmetrical Component (CSC). Since SMs do not provide direct current data, a Machine Learning (ML)-based regression method is proposed to estimate the cables' currents in the DT. Validation is performed on a 41-node LV distribution feeder in the Scottish network provided by the industry partner Scottish Power Energy Networks (SPEN). The results show that the current estimation regressor significantly improves fault localisation and identification accuracy to 95.77%. This validates the crucial role of a DT in distribution networks, thus enabling highly accurate fault detection when using SM voltage-only data, with further refinements being conducted through estimations of CSC. The proposed DT offers automated fault detection, thus enhancing customer connectivity and maintenance team dispatch efficiency without the need for additional expensive μ PMU on a densely-noded distribution network. [ABSTRACT FROM AUTHOR]

Due to their many advantages over their counterparts, such as Z-source inverters (ZSIs), split-source inverters (SSIs) have recently received much attention as single-stage boost inverters. This paper discusses a multiphase version of the SSI topology for the first time. Among multiphase systems undergoing a revolution in the research area, five-phase motor drives are a relatively practical selection in industrial applications. Therefore, this paper focuses on a five-phase SSI as an example. The topology, operating principles, modulation techniques, and performance analysis of the analyzed topology are introduced. A modified space-vector modulation (MSVM) scheme is developed to eliminate low-frequency ripples in the input current. There is also a detailed analysis and graphical evaluation of the output currents ripples using the space-vector approach. It is evident that multiphase SSI is suitable for motor drives, especially when a high-output voltage gain is required. In addition to having a nearly identical ripple in output current to a conventional VSI, it has the benefit of performing the boosting action in a single stage with fewer passive components and a low ripple in input current. Finally, the simulation and experimental results have been conducted to demonstrate the viability of the multiphase SSI studied in the theoretical study and analysis. [ABSTRACT FROM AUTHOR]

This article proposes a new active power flow controller for dc–dc multiactive bridge (MAB) converters with minimum current point tracking (MCPT) to minimize conductive losses. Unlike recent efforts in this area, the proposed controller does not require look-up table for implementation nor complex nonlinear converter modeling and is not circuit parameter dependent. The proposed control scheme is also generalized for MAB converters with any number of ports and is derived in per unit form to enable standard implementation for buck/boost/unity-gain operating modes. The proposed MCPT algorithm is based on an innovative adaptive perturb and observe tracking of the minimum current point (MCP) on the MAB converter current characteristic plane. This MCP is tracked while active power regulation is simultaneously achieved based on a new phase shift decoupler to enable direct regulation of individual port active power. Detailed design procedure of the proposed controller is presented and extensive simulation is carried out to validate the effectiveness of the proposed MCPT closed loop controller. Experimental implementation is also provided to substantiate the simulation results. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive and generalized analysis of the bidirectional dual active bridge (DAB) dc–dc converter using triple phase shift (TPS) control to enable closed-loop power regulation while minimizing current stress. The key new achievements are a generic analysis in terms of possible conversion ratios/converter voltage gains (i.e., Buck/Boost/Unity), per unit based equations regardless of DAB ratings, and a new simple closed-loop controller implementable in real time to meet desired power transfer regulation at minimum current stress. Per unit based analytical expressions are derived for converter ac rms current as well as power transferred. An offline particle swarm optimization (PSO) method is used to obtain an extensive set of TPS ratios for minimizing the rms current in the entire bidirectional power range of –1 to 1 per unit. The extensive set of results achieved from PSO presents a generic data pool, which is carefully analyzed to derive simple useful relations. Such relations enable a generic closed-loop controller design that can be implemented in real time avoiding the extensive computational capacity that iterative optimization techniques require. A detailed Simulink DAB switching model is used to validate the precision of the proposed closed-loop controller under various operating conditions. An experimental prototype also substantiates the results achieved. [ABSTRACT FROM AUTHOR]

This paper proposes a linearized large signal state-space model for the fixed-frequency phase-controlled series-parallel resonant converter. The proposed model utilizes state feedback of the output filter inductor current to perform linearization. The model combines multiple-frequency and average state-space modeling techniques to generate an aggregate model with dc state variables that are relatively easier to control and slower than the fast resonant tank dynamics. The main objective of the linearized model is to provide a linear representation of the converter behavior under large signal variation which is suitable for faster simulation and large signal estimation/calculation of the converter state variables. The model also provides insight into converter dynamics as well as a simplified reduced order transfer function for PI closed-loop design. Experimental and simulation results from a detailed switched converter model are compared with the proposed state-space model output to verify its accuracy and robustness. [ABSTRACT FROM AUTHOR]

Inverters with Quasi-Z-Source Networks (QZSN) provide DC-DC boosting and DC-AC conversion in a single stage. It offers reduced cost, complexity, and volume compared with the classical two-stage conversion system, which is composed of a boost converter followed by a Voltage-Source-Inverter (VSI). Further, QZSI provides superior conversion characteristics for single-stage grid-connected photovoltaic transformerless systems. However, the absence of galvanic isolation in these systems makes it possible to allow leakage current through these systems' parasitic capacitances due to the high-frequency Common-Mode Voltage (CMV) generated by the Pulse Width Modulation (PWM) nature of the inverter output voltages. As a result of this current, critical safety issues may arise with PV systems. Many PWM techniques have been presented in recent years for QZSIs. This paper is intended to provide a comprehensive analysis and review study of the characteristics of most of these PWM techniques in terms of CMV and leakage currents. In this study, closed-form equations have been derived to determine the effective CMV and leakage current analyses for all modulation techniques. Analytical and simulation approaches are used to identify schemes with the lowest CMV and current leakage effects. Moreover, the experimental setup is presented by applying the Simple-Boost Modified Space Vector Modulation (SB-MSVM) technique. [ABSTRACT FROM AUTHOR]

This paper proposes a buffered microgrid with a modular grid interface consisting of a modular back-to-back converter. The proposed method provides a flexible strategy that enables both the load and generation expansion of the microgrid, with no sizing constraints on the initial stage. The method maintains the physical separation of the buffered microgrid from the grid by using back-to-back converters, which ensures a safe, secure and seamless operation in both islanded and grid-connected operation modes. The proposed modular structure allows an energy exchange prioritization either between the energy storage systems and the grid or between the energy storage units themselves, depending on the recommended/desired operational strategy. The prioritizations are achieved by using sets of dead zones in the control of the interfacing converters. In order to control the voltage and frequency, an inverse-droop-based dq-frame current control method was implemented in PSCAD/EMTDC to substantiate the proposed method. The simulation results of different scenarios show the operational flexibility, control simplicity and communication-free operation of the microgrid with different types of sources. [ABSTRACT FROM AUTHOR]

Summary: The sustained instability in Afghanistan, along with ongoing disease outbreaks and the impact of the COVID-19 pandemic, has significantly affected the country. During the COVID-19 pandemic, the country's detection and response capacities faced challenges. Case identification was done in all health facilities from primary to tertiary levels but neglected cases at the community level, resulting in undetected and uncontrolled transmission from communities. This emphasizes a missed opportunity for early detection that Event-Based Surveillance (EBS) could have facilitated. Therefore, Afghanistan planned to strengthen the EBS component of the national public health surveillance system to enhance the capacity for the rapid detection and response to infectious disease outbreaks, including COVID-19 and other emerging diseases. This effort was undertaken to promptly mitigate the impact of such outbreaks. We conducted a landscape assessment of Afghanistan's public health surveillance system to identify the best way to enhance EBS, and then we crafted an implementation work plan. The work plan included the following steps: establishing an EBS multisectoral coordination and working group, identifying EBS information sources, prioritizing public health events of importance, defining signals, establishing reporting mechanisms, and developing standard operating procedures and training guides. EBS is currently being piloted in seven provinces in Afghanistan. The lessons learned from the pilot phase will support its overall expansion throughout the country. [ABSTRACT FROM AUTHOR]

Background An effective implementation of antimicrobial resistance (AMR) surveillance projects requires sustainable and multidisciplinary engagement with stakeholders from various backgrounds, interests and aims. The "Capturing Data on Antimicrobial resistance Patterns and Trends in Use in Regions of Asia" (CAPTURA) project, funded by the Fleming Fund, initially targeted 12 countries in South Asia (SA) and Southeast Asia (SEA) to "expand the volume of historical and current data on AMR and antimicrobial usage" and support local agencies through capacity building activities. Methods In this article, we focus on early stakeholder engagement activities and present overall statistics on AMR data collated from 72 laboratories across seven countries. This included 2.3 million records of antimicrobial susceptibility testing (AST) data, which were curated, analyzed, and shared back to the facilities for informed decision making. Results Approximately 98% of the data collated by CAPTURA originated from laboratories based in SA countries. Furthermore, country-wide data were analyzed to identify commonly reported pathogens in each country, followed by descriptions of AST practices and multidrug-resistant (MDR) pathogens. Overall, we found meager adherence to standard guidelines to perform and record AST results, and a significant number of MDR pathogens were reported. Conclusions We conclude that close collaboration with the existing national mechanisms for identifying AMR data sources was crucial for the project's success. Although we show a vast retrospective dataset on AMR is available for data sharing in Asia, there remain critical gaps in data generation/management practice and analysis capacity for AMR data at most facilities. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is a multifaceted global health problem disproportionately affecting low- and middle-income countries (LMICs). The Capturing data on Antimicrobial resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project was tasked to expand the volume of AMR and antimicrobial use data in Asia. The CAPTURA project used 2 data-collection streams: facility data and project metadata. Project metadata constituted information collected to map out data sources and assess data quality, while facility data referred to the retrospective data collected from healthcare facilities. A down-selection process, labelled "the funnel approach" by the project, was adopted to use the project metadata in prioritizing and selecting laboratories for retrospective AMR data collection. Moreover, the metadata served as a guide for understanding the AMR data once they were collected. The findings from CAPTURA's metadata add to the current discourse on the limitation of AMR data in LMICs. There is generally a low volume of AMR data generated as there is a lack of microbiology laboratories with sufficient antimicrobial susceptibility testing capacity. Many laboratories in Asia are still capturing data on paper, resulting in scattered or unused data not readily accessible or shareable for analyses. There is also a lack of clinical and epidemiological data captured, impeding interpretation and in-depth understanding of the AMR data. CAPTURA's experience in Asia suggests that there is a wide spectrum of capacity and capability of microbiology laboratories within a country and region. As local AMR surveillance is a crucial instrument to inform context-specific measures to combat AMR, it is important to understand and assess current capacity-building needs while implementing activities to enhance surveillance systems. [ABSTRACT FROM AUTHOR]

Data on antimicrobial resistance (AMR) from sites not participating in the National AMR surveillance network, conducted by National Public Health Laboratory (NPHL), remain largely unknown in Nepal. The "Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia" (CAPTURA) assessed AMR data from previously untapped data sources in Nepal. A retrospective cross-sectional data review was carried out for the AMR data recorded between January 2017 and December 2019 to analyze AMR data from 26 hospital-based laboratories and 2 diagnostic laboratories in Nepal. Of the 56 health facilities initially contacted to participate in this project activity, 50.0% (28/56) signed a data-sharing agreement with CAPTURA. Eleven of the 28 hospitals were AMR surveillance sites, whereas the other 17, although not part of the National AMR surveillance network, recorded AMR-related data. Data for 663 602 isolates obtained from 580 038 patients were analyzed. A complete record of the 11 CAPTURA priority variables was obtained from 45.5% (5/11) of government hospitals, 63.6% (7/11) of private hospitals, and 54.6% (6/11) of public-private hospitals networked with NPHL for AMR surveillance. Similarly, 80% (8/10) of clinics and 54.6% (6/11) of laboratories outside the NPHL network recorded complete data for the 10 Global Antimicrobial Resistance and Use Surveillance System (GLASS) priority variables and 11/14 CAPTURA priority variables. Retrospective review of the data identified areas requiring additional resources and interventions to improve the quality of data on AMR in Nepal. Furthermore, we observed no difference in the priority variables reported by sites within or outside the NPHL network, thus suggesting that policies could be made to expand the surveillance system to include these sites without substantially affecting the government's budget. [ABSTRACT FROM AUTHOR]

The Institute of Epidemiology, Disease Control and Research (IEDCR) conducts active, case-based national antimicrobial resistance (AMR) surveillance in Bangladesh. The Capturing Data on Antimicrobial Resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project accessed aggregated retrospective data from non-IEDCR study sites and 9 IEDCR sites to understand the pattern and extent of AMR and to use analyzed data to guide ongoing and future national AMR surveillance in both public and private laboratories. Record-keeping practices, data completeness, quality control, and antimicrobial susceptibility test practices were investigated in all laboratories participating in case-based IEDCR surveillance and laboratory-based CAPTURA sites. All 9 IEDCR laboratories recorded detailed case-based data (n = 16 816) in electronic format for a priority subset of processed laboratory samples. In contrast, most CAPTURA sites (n = 18/33 [54.5%]) used handwritten registers to store data. The CAPTURA sites were characterized by fewer recorded variables (such as patient demographics, clinical history, and laboratory findings) with 1 020 197 individual data, less integration of patient records with the laboratory information system, and nonuniform practice of data recording; however, data were collected from all available clinical samples. The analyses conducted on AMR data collected by IEDCR and CAPTURA in Bangladesh provide current data collection status and highlight opportunities to improve ongoing data collection to strengthen current AMR surveillance system initiatives. We recommend a tailored approach to conduct AMR surveillance in high-burden, resource-limited settings. [ABSTRACT FROM AUTHOR]

Background: Event-based surveillance (EBS) is an essential component of Early Warning Alert and Response (EWAR) as per the International Health Regulations (IHR), 2005. EBS was established in Sudan in 2016 as a complementary system for Indicator-based surveillance (IBS). This review will provide an overview of the current EBS structure, functions and performance in Sudan and identify the gaps and ways forward.  METHODS: The review followed the WHO/EMRO guidelines and tools. Structured discussions, observation and review of records and guidelines were done at national and state levels. Community volunteers were interviewed through phone calls. Directors of Health Emergency and Epidemic Control, surveillance officers and focal persons for EBS at the state level were also interviewed. SPSS software was used to perform descriptive statistical analysis for quantitative data, while qualitative data was analysed manually using thematic analysis, paying particular attention to the health system level allowing for an exploration of how and why experiences differ across levels. Written and verbal consents were obtained from all participants as appropriate.Results: Sudan has a functioning EBS; however, there is an underestimation of its contribution and importance at the national and states levels. The link between the national level and states is ad hoc or is driven by the need for reports. While community event-based surveillance (CEBS) is functioning, EBS from health facilities and from non-health sectors is not currently active. The integration of EBS into overall surveillance was not addressed, and the pathway from detection to action is not clear. The use of electronic databases and platforms is generally limited. Factors that would improve performance include training, presence of a trained focal person at state level, and regular follow-up from the national level. Factors such as staff turnover, income in relation to expenses and not having a high academic qualification (Diploma or MSc) were noticed as inhibiting factors.Conclusion: The review recommended revisiting the surveillance structure at national and state levels to put EBS as an essential component and to update guidelines and standard operation procedures SOPs to foster the integration between EBS components and the overall surveillance system. The need for strengthening the link with states, capacity building and re-addressing the training modalities was highlighted. [ABSTRACT FROM AUTHOR]