Focus, vigilance, resilience: towards stronger infectious disease surveillance, threat detection and response in the EU/EEA.

This perspective summarises and explains the long-term surveillance framework 2021-2027 for infectious diseases in the European Union/European Economic Area (EU/EEA) published in April 2023. It shows how shortcomings in the areas of public health focus, vigilance and resilience will be addressed through specific strategies in the coming years and how these strategies will lead to stronger surveillance systems for early detection and monitoring of public health threats as well as informing their effective prevention and control. A sharper public health focus is expected from a more targeted list of notifiable diseases, strictly public-health-objective-driven surveillance standards, and consequently, leaner surveillance systems. Vigilance should improve through mandatory event reporting, more automated epidemic intelligence processing and increased use of genomic surveillance. Finally, EU/EEA surveillance systems should become more resilient by modernising the underlying information technology infrastructure, expanding the influenza sentinel surveillance system to other respiratory viruses for better pandemic preparedness, and increasingly exploiting potentially more robust alternative data sources, such as electronic health records and wastewater surveillance. Continued close collaboration across EU/EEA countries will be key to ensuring the full implementation of this surveillance framework and more effective disease prevention and control.

Outbreak detector: a web application to boost disease surveillance systems and timely detection of infectious disease epidemics.

OBJECTIVE: Digital technologies have improved the performance of surveillance systems through early detection of outbreaks and epidemic control. The aim of this study is to introduce an outbreak detection web application called OBDETECTOR (Outbreak Detector), which as a professional web application has the ability to process weekly or daily reported data from disease surveillance systems and facilitates the early detection of disease outbreaks. RESULTS: OBDETECTOR generates a histogram that exhibits the trend of infection within a time range selected by the user. The output comprises red triangles and plus signs, where the former denotes outbreak days determined by the algorithm applied to the data, and the latter represents days identified as outbreaks by the researcher. The graph also displays threshold values and its symbols enable researchers to compute evaluation criteria for outbreak detection algorithms, including sensitivity and specificity. OBDETECTOR allows users to modify algorithm parameters based on their research objectives immediately after loading data. The implementation of automatic web applications results in immediate reporting, precise analysis, and prompt alert notification. Moreover, Public Health authorities and other stakeholders of surveillance can benefit from the widespread accessibility and user-friendliness of these tools, enhancing their knowledge and skills for better engagement in surveillance programs.

Clinical diagnostic value of targeted next­generation sequencing for infectious diseases (Review).

As sequencing technology transitions from research to clinical settings, due to technological maturity and cost reductions, metagenomic next­generation sequencing (mNGS) is increasingly used. This shift underscores the growing need for more cost­effective and universally accessible sequencing assays to improve patient care and public health. Therefore, targeted NGS (tNGS) is gaining prominence. tNGS involves enrichment of target pathogens in patient samples based on multiplex PCR amplification or probe capture with excellent sensitivity. It is increasingly used in clinical diagnostics due to its practicality and efficiency. The present review compares the principles of different enrichment methods. The high positivity rate of tNGS in the detection of pathogens was found in respiratory samples with specific instances. tNGS maintains high sensitivity (70.8­95.0%) in samples with low pathogen loads, including blood and cerebrospinal fluid. Furthermore, tNGS is effective in detecting drug­resistant strains of Mycobacterium tuberculosis, allowing identification of resistance genes and guiding clinical treatment decisions, which is difficult to achieve with mNGS. In the present review, the application of tNGS in clinical settings and its current limitations are assessed. The continued development of tNGS has the potential to refine diagnostic accuracy and treatment efficacy and improving infectious disease management. However, further research to overcome technical challenges such as workflow time and cost is required.

[Expert consensus on the key technologies for a multi-point trigger intelligent surveillance and early warning system for infectious diseases].

An effective infectious disease surveillance and early warning system is a crucial component of public health safety and is essential for preventing and controlling outbreaks of infectious diseases. Enhancing surveillance and early warning capabilities is an urgent priority for advancing high-quality disease prevention and control efforts. Combining the research findings and practical experiences of experts in epidemiology, clinical medicine, disease prevention and control, data science, and computer science, and following multiple rounds of expert discussions, we have developed a consensus on the key technologies for a multi-point trigger intelligent surveillance and early warning system for infectious diseases. This consensus primarily covers the related concepts and definitions of the multi-point trigger intelligent surveillance and early warning system for infectious diseases, the key technical framework, sources, acquisition, and governance of multi-channel warning data, classification of early warning methods, multi-point trigger intelligent surveillance and early warning paths, multi-point trigger warning and comprehensive assessment, response to warning signals, and evaluation of early warning effectiveness. It aims to provide technical references for the construction and application of a multi-point trigger intelligent surveillance and early warning system for infectious diseases.

Monoclonal Antibody Generation Using Single B Cell Screening for Treating Infectious Diseases.

The screening of antigen-specific B cells has been pivotal for biotherapeutic development for over four decades. Conventional antibody discovery strategies, including hybridoma technology and single B cell screening, remain widely used based on their simplicity, accessibility, and proven track record. Technological advances and the urgent demand for infectious disease applications have shifted paradigms in single B cell screening, resulting in increased throughput and decreased time and labor, ultimately enabling the rapid identification of monoclonal antibodies with desired biological and biophysical properties. Herein, we provide an overview of conventional and emergent single B cell screening approaches and highlight their potential strengths and weaknesses. We also detail the impact of innovative technologies-including miniaturization, microfluidics, multiplexing, and deep sequencing-on the recent identification of broadly neutralizing antibodies for infectious disease applications. Overall, the coronavirus disease 2019 (COVID-19) pandemic has reinvigorated efforts to improve the efficiency of monoclonal antibody discovery, resulting in the broad application of innovative antibody discovery methodologies for treating a myriad of infectious diseases and pathological conditions.

A modified quality control protocol for infectious disease serology based on the Westgard rules.

When traditional statistical quality control protocols, represented by the Westgard protocol were applied to infectious disease serology, the rejection limits were questioned because of the high rejection probability. We first define the probability of false rejection (Pfr) and error detection (Ped) for infectious disease serology. QC data in 6 months were collected and the Pfr of each rule in the Westgard protocol and Rilibak protocol was evaluated. Then, as improvements, we chose different rules for negative and positive QC data to constitute an asymmetric protocol, furthermore, while reagent lot changes, the mean value of QC protocol is reset with the first 15 QC results of new lot reagent. QC materials and Standard Reference Materials were tested synchronously in the next 6 months, to verify whether the Pfr and Ped of the asymmetric protocol could meet the requirement. Protocol 1 exhibited the higher level of rejection rate among the two protocols, especially after reagent lot changes; Pfr below the lower control limit (LCL) was 1.39-21.78 times higher than the upper control limit (UCL); false rejections were more likely to occur in negative QC data, with Pfr-total of 27-65%. The asymmetric protocol can significantly reduce the proportion of analytes with Pfr by over 20%. Systematic error due to reagent lot changes and random error due to routine QC data variation were considered potential factors for excessive Pfr. Asymmetric QC protocol that can reduce Pfr by different control limits for negative and positive QC data.

A Digital Approach to Improve Infection Screening Among Solid Organ Transplant Candidates.

BACKGROUND: Pretransplant infection screening (IS) of potential organ recipients is essential to optimal outcome of solid organ transplantation (SOT). METHODS: A pre-post study was performed during 2020-2023 to investigate the impact of the STREAM (Solid organ TRansplant stEwArdship and Multidisciplinary approach) intervention to improve IS in SOT. The intervention, performed in 2022, included the implementation of IS through educational meetings, local guidelines, and the availability of a digital screening tool. The objective of the study was the assessment of IS completion, including a list of 17 laboratory tests and the investigation of vaccination status. The reduction of unnecessary tests was also analyzed. The test of proportions and a multilevel multivariate Poisson regression model were used to compare IS completion before and after STREAM. infectious diseases (ID) consultation and urgent evaluation were investigated as predictors of IS completion. RESULTS: A total of 171 patients were enrolled, including liver (44%), heart (32%), and kidney (24%) transplant candidates. Mean age was 56 ± 11 years, and most patients (77%) were males. Ninety-five (56%) patients were included before the intervention and 76 (44%) after STREAM. IS completion increased after STREAM (IRR 1.41, p < 0.001) with significant improvement recorded for seven (39%) IS items. Unnecessary tests decreased by 43% after the intervention. ID consultation (IRR 1.13, p = 0.02) and urgent evaluation (p = 0.68, p < 0.001) were predictors of IS improvement. CONCLUSIONS: STREAM was successful in improving IS completion. Further research is needed to investigate the impact of this intervention on posttransplant infections.

Towards the development of cost-effective point-of-care diagnostic tools for poverty-related infectious diseases in sub-Saharan Africa.

In this review, we examine the current landscape of point-of-care testing (POCT) diagnostic tools designed for poverty-related infectious diseases (PRIDs) in sub-Saharan Africa (sSA) while delineating key avenues for future advancements. Our analysis encompasses both established and emerging diagnostic methods for PRIDs, addressing the persistent challenges in POCT tool development and deployment, such as cost, accessibility, and reliability. We emphasize recent advancements in POCT diagnostic tools as well as platforms poised to enhance diagnostic testing in sSA. Recognizing the urgency for affordable and widely accessible POCT diagnostic tools to detect PRIDs in sSA, we advocate for a multidisciplinary approach. This approach integrates current and emerging diagnostic methods, explicitly addressing challenges hindering point-of-care (POC) tool development. Furthermore, it recognizes the profound impact of misdiagnosis on public and global health, emphasizing the need for effective tools. To facilitate the successful development and implementation of POCT diagnostic tools in sSA, we propose strategies including the creation of multi-analyte detection POCT tools, the implementation of education and training programs, community engagement initiatives, fostering public-private collaborations, and the establishment of reliable supply chains. Through these concerted efforts, we aim to accelerate the development of POCT in the sSA region, ensuring its effectiveness and accessibility in addressing the diagnostic challenges associated with PRIDs.

Modeling the transmission mitigation impact of testing for infectious diseases.

A fundamental question of any program focused on the testing and timely diagnosis of a communicable disease is its effectiveness in reducing transmission. Here, we introduce testing effectiveness (TE)-the fraction by which testing and post-diagnosis isolation reduce transmission at the population scale-and a model that incorporates test specifications and usage, within-host pathogen dynamics, and human behaviors to estimate TE. Using TE to guide recommendations, we show that today's rapid diagnostics should be used immediately upon symptom onset to control influenza A and respiratory syncytial virus but delayed by up to two days to control omicron-era severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, while rapid tests are superior to reverse transcription quantitative polymerase chain reaction (RT-qPCR) to control founder-strain SARS-CoV-2, omicron-era changes in viral kinetics and rapid test sensitivity cause a reversal, with higher TE for RT-qPCR despite longer turnaround times. Last, we illustrate the model's flexibility by quantifying trade-offs in the use of post-diagnosis testing to shorten isolation times.

Creation of Standardized Common Data Elements for Diagnostic Tests in Infectious Disease Studies: Semantic and Syntactic Mapping.

BACKGROUND: It is necessary to harmonize and standardize data variables used in case report forms (CRFs) of clinical studies to facilitate the merging and sharing of the collected patient data across several clinical studies. This is particularly true for clinical studies that focus on infectious diseases. Public health may be highly dependent on the findings of such studies. Hence, there is an elevated urgency to generate meaningful, reliable insights, ideally based on a high sample number and quality data. The implementation of core data elements and the incorporation of interoperability standards can facilitate the creation of harmonized clinical data sets. OBJECTIVE: This study's objective was to compare, harmonize, and standardize variables focused on diagnostic tests used as part of CRFs in 6 international clinical studies of infectious diseases in order to, ultimately, then make available the panstudy common data elements (CDEs) for ongoing and future studies to foster interoperability and comparability of collected data across trials. METHODS: We reviewed and compared the metadata that comprised the CRFs used for data collection in and across all 6 infectious disease studies under consideration in order to identify CDEs. We examined the availability of international semantic standard codes within the Systemized Nomenclature of Medicine - Clinical Terms, the National Cancer Institute Thesaurus, and the Logical Observation Identifiers Names and Codes system for the unambiguous representation of diagnostic testing information that makes up the CDEs. We then proposed 2 data models that incorporate semantic and syntactic standards for the identified CDEs. RESULTS: Of 216 variables that were considered in the scope of the analysis, we identified 11 CDEs to describe diagnostic tests (in particular, serology and sequencing) for infectious diseases: viral lineage/clade; test date, type, performer, and manufacturer; target gene; quantitative and qualitative results; and specimen identifier, type, and collection date. CONCLUSIONS: The identification of CDEs for infectious diseases is the first step in facilitating the exchange and possible merging of a subset of data across clinical studies (and with that, large research projects) for possible shared analysis to increase the power of findings. The path to harmonization and standardization of clinical study data in the interest of interoperability can be paved in 2 ways. First, a map to standard terminologies ensures that each data element's (variable's) definition is unambiguous and that it has a single, unique interpretation across studies. Second, the exchange of these data is assisted by "wrapping" them in a standard exchange format, such as Fast Health care Interoperability Resources or the Clinical Data Interchange Standards Consortium's Clinical Data Acquisition Standards Harmonization Model.

Prospective Spatiotemporal Cluster Detection Using SaTScan: Tutorial for Designing and Fine-Tuning a System to Detect Reportable Communicable Disease Outbreaks.

Staff at public health departments have few training materials to learn how to design and fine-tune systems to quickly detect acute, localized, community-acquired outbreaks of infectious diseases. Since 2014, the Bureau of Communicable Disease at the New York City Department of Health and Mental Hygiene has analyzed reportable communicable diseases daily using SaTScan. SaTScan is a free software that analyzes data using scan statistics, which can detect increasing disease activity without a priori specification of temporal period, geographic location, or size. The Bureau of Communicable Disease's systems have quickly detected outbreaks of salmonellosis, legionellosis, shigellosis, and COVID-19. This tutorial details system design considerations, including geographic and temporal data aggregation, study period length, inclusion criteria, whether to account for population size, network location file setup to account for natural boundaries, probability model (eg, space-time permutation), day-of-week effects, minimum and maximum spatial and temporal cluster sizes, secondary cluster reporting criteria, signaling criteria, and distinguishing new clusters versus ongoing clusters with additional events. We illustrate how to support health equity by minimizing analytic exclusions of patients with reportable diseases (eg, persons experiencing homelessness who are unsheltered) and accounting for purely spatial patterns, such as adjusting nonparametrically for areas with lower access to care and testing for reportable diseases. We describe how to fine-tune the system when the detected clusters are too large to be of interest or when signals of clusters are delayed, missed, too numerous, or false. We demonstrate low-code techniques for automating analyses and interpreting results through built-in features on the user interface (eg, patient line lists, temporal graphs, and dynamic maps), which became newly available with the July 2022 release of SaTScan version 10.1. This tutorial is the first comprehensive resource for health department staff to design and maintain a reportable communicable disease outbreak detection system using SaTScan to catalyze field investigations as well as develop intuition for interpreting results and fine-tuning the system. While our practical experience is limited to monitoring certain reportable diseases in a dense, urban area, we believe that most recommendations are generalizable to other jurisdictions in the United States and internationally. Additional analytic technical support for detecting outbreaks would benefit state, tribal, local, and territorial public health departments and the populations they serve.

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Infectious diseases are a great threat to human health. Rapid and accurate detection of pathogens is important in the diagnosis and treatment of infectious diseases. Metagenomics next-generation sequencing (mNGS) is an unbiased and comprehensive approach for detecting all RNA and DNA in a sample. With the development of sequencing and bioinformatics technologies, mNGS is moving from research to clinical application, which opens a new avenue for pathogen detection. Numerous studies have revealed good potential for the clinical application of mNGS in infectious diseases, especially in difficult-to-detect, rare, and novel pathogens. However, there are several hurdles in the clinical application of mNGS, such as: (1) lack of universal workflow validation and quality assurance; (2) insensitivity to high-host background and low-biomass samples; and (3) lack of standardized instructions for mass data analysis and report interpretation. Therefore, a complete understanding of this new technology will help promote the clinical application of mNGS to infectious diseases. This review briefly introduces the history of next-generation sequencing, mainstream sequencing platforms, and mNGS workflow, and discusses the clinical applications of mNGS to infectious diseases and its advantages and disadvantages.

Advances in Nucleic Acid Assays for Infectious Disease: The Role of Microfluidic Technology.

Within the fields of infectious disease diagnostics, microfluidic-based integrated technology systems have become a vital technology in enhancing the rapidity, accuracy, and portability of pathogen detection. These systems synergize microfluidic techniques with advanced molecular biology methods, including reverse transcription polymerase chain reaction (RT-PCR), loop-mediated isothermal amplification (LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR), have been successfully used to identify a diverse array of pathogens, including COVID-19, Ebola, Zika, and dengue fever. This review outlines the advances in pathogen detection, attributing them to the integration of microfluidic technology with traditional molecular biology methods and smartphone- and paper-based diagnostic assays. The cutting-edge diagnostic technologies are of critical importance for disease prevention and epidemic surveillance. Looking ahead, research is expected to focus on increasing detection sensitivity, streamlining testing processes, reducing costs, and enhancing the capability for remote data sharing. These improvements aim to achieve broader coverage and quicker response mechanisms, thereby constructing a more robust defense for global public health security.

Utility of microbial cell free DNA next-generation sequencing for diagnosis and management of infectious diseases.

Microbial cell-free DNA (mcfDNA) sequencing is a promising tool to identify infectious pathogens when traditional methods fail to identify the causative agent. We performed a retrospective observational cohort study to evaluate clinical outcomes among pediatric and adult patients who underwent mcfDNA testing. 127 mcfDNA tests were reviewed from 112 patients. Baseline characteristics included 61 (54.5 %) adults, 52 (40.9 %) tests were from female patients, and 67 (52.8 %) tests were obtained from patients designated as immunocompromised. Of all tests obtained, 59 (46.4 %) were deemed clinically relevant. 41 (32.3 %) of tests also led to a change in antimicrobial management for the corresponding patient. No statistically significant association was ascertained between patient-specific factors and clinically relevant test results. Testing in certain clinical scenarios or high-risk settings may be useful, however further studies are needed to assess the cost-benefit of this approach.

Sample-to-result molecular diagnostic platforms and their suitability for infectious disease testing in low- and middle-income countries.

INTRODUCTION: Diagnostics are an essential, undervalued part of the health-care system. For many diseases, molecular diagnostics are the gold standard, but are not easy to implement in Low- and Middle-Income Countries (LMIC). Sample-to-result (S2R) platforms combining all procedures in a closed system could offer a solution. In this paper, we investigated their suitability for implementation in LMIC. AREAS COVERED: A scorecard was used to evaluate different platforms on a range of parameters. Most platforms scored fairly on the platform itself, ease-of-use and test consumables; however, shortcomings were identified in cost, distribution and test panels tailored to LMIC needs. The diagnostic coverage for common infectious diseases was found to have a wider coverage in high-income countries (HIC) than LMIC. A literature study showed that in LMIC, these platforms are mainly used as diagnostic tools or evaluation of diagnostic performance, with a minority assessing the operational characteristics or the clinical utility. In this narrative review, we identified various points for adaptation of S2R platforms to LMIC conditions. EXPERT OPINION: For S2R platforms to be suitable for implementation in LMIC some modifications by the manufacturers could be considered. Furthermore, strengthening health systems and digitalization are vital; as are smaller, cheaper, faster, and sustainable technologies.

Diagnostics for Public Health - Infectious Disease Surveillance and Control.

AbstractAccurate diagnostics are critical in public health to ensure successful disease tracking, prevention, and control. Many of the same characteristics are desirable for diagnostic procedures in both medicine and public health: for example, low cost, high speed, low invasiveness, ease of use and interpretation, day-to-day consistency, and high accuracy. This review lays out five principles that are salient when the goal of diagnosis is to improve the overall health of a population rather than that of a particular patient, and it applies them in two important use cases: pandemic infectious disease and antimicrobial resistance.