Monitoring Of Infectious Diseases Research Articles

Combination-Lock SlipChip Integrating Nucleic Acid Sample Preparation and Isothermal LAMP Amplification for the Detection of SARS-CoV-2.

Nucleic acid analysis with an easy-to-use workflow, high specificity and sensitivity, independence of sophisticated instruments, and accessibility outside of the laboratory is highly desirable for the detection and monitoring of infectious diseases. Integration of laboratory-quality sample preparation on a hand-held system is critical for performance. A SlipChip device inspired by the combination lock can perform magnetic bead-based nucleic acid extraction with several clockwise and counterclockwise rotations. A palm-sized base station was developed to assist sample preparation and provide thermal control of isothermal nucleic acid amplification without plug-in power. The loop-mediated isothermal amplification reaction can be performed with a colorimetric method and directly analyzed by the naked eye or with a mobile phone app. This system achieves good bead recovery during the sample preparation workflow and has minimal residue carryover from the lysis and elution buffers. Its performance is comparable to that of the standard laboratory protocol with real-time qPCR amplification methods. The entire workflow is completed in less than 35 min and the device can achieve 500 copies/mL sensitivity. Thirty clinical nasal swab samples were collected and tested with a sensitivity of 95% and a specificity of 100% for SARS-CoV-2. This combination-lock SlipChip provides a promising fast, easy-to-use nucleic acid test with bead-based sample preparation that produces laboratory-quality results for point-of-care settings, especially in home use applications.

Accuracy of Saliva as a Diagnostic Medium for Hepatitis B Virus Infection: A Quantitative ELISA Analysis

Abstract Context: Diagnosis of hepatitis B virus infection (HBV) has been traditionally serum-based with its attendant risks and invasive procedure. Massive research interests are being directed to the use of saliva for screening, diagnosis, and monitoring of several infectious diseases, including HBV. Various reports suggest that saliva contains biomarkers that are comparable with that of sera. It can also be obtained with minimal risk to the clinician and patient as well. Aim: To determine the diagnostic accuracy of saliva in quantitative detection of hepatitis B surface antigen (HBsAg) using enzyme-linked immunosorbent assay (ELISA). Settings and Design: This cross-sectional analytical study was performed on HBV seropositive patients at the Gastroenterology clinic of the University of Benin Teaching Hospital, Benin City, Edo State. Materials and Methods: Under standardized conditions, equal amounts of blood and saliva samples of 43 HBsAg seropositive patients were analyzed using ELISA to quantitatively detect the concentration of HBsAg. Statistical Analysis Used: The analysis relied on Spearman’s correlation coefficient, linear regression analysis, and Bland–Altman plots to describe the correlational, predictive, and agreements between measurements of HBsAg in sera and saliva. The statistical significance was set at P < 0.05, while a 95% confidence level was used to construct intervals. Results: All participants had detectable levels of HBsAg in both saliva and serum with mean titers of 1.70 ± 0.35 ng/ml and 2.80 ± 0.77 ng/ml, respectively. Correlational and linear regression showed poor fit and predictive relationships of the HBsAg levels. Bland–Altman analysis showed good agreement and no significant bias in their diagnostic agreements. Conclusion: Saliva can be reliably used in screening and diagnosis of HBV infection. There was agreement in their levels independently and within their averages. It may be premature to rely on saliva for quantitative assay of HBsAg in treatment monitoring.

Virus adsorption and elution using cationic polymer brushes: potential applications for passive sampling in wastewater-based epidemiology

Efficient virus adsorption and selective elution of a nonenveloped virus are demonstrated by using cationic polymer brushes. These materials may have potential for passive sampling in wastewater-based epidemiology.

Dynamics and Efficacy: A Comprehensive Evaluation of the Advanced Dengue Fever Surveillance and Early Warning System in Ningbo City, 2023.

To conduct a comprehensive evaluation of the Dengue Fever Surveillance and Early Warning System deployed in Ningbo City during 2023, focusing on its capacity for timely identification and reporting of dengue fever cases, particularly imported cases from endemic regions. A detailed data of patient clinical features and blood profile trends was collected from clinical records and surveillance reports, focusing on the rapid diagnostic processes and surveillance rigor. This study assessed the effectiveness of the system in identifying and reporting dengue cases and identified the limitations of the existing framework through a basic statistical approach. The system demonstrated timely identification and reporting of dengue fever cases, with a particular emphasis on imported cases. However, several limitations were identified, including the need for more precise monitoring criteria and improved coordination with medical entities. The study underscores the critical role of public health bodies in managing disease outbreaks and advocates for enhanced methodologies to refine epidemic control efforts. The findings contribute to the advancement of early warning mechanisms and the improvement of proactive infectious disease monitoring in metropolitan environments, providing valuable insights for fortifying the Dengue Fever Surveillance and Early Warning System in Ningbo City.

Medical support for major international sports events: a literature rewiew

Introduction. The article carries out a critical review of the literature and updates the emphasis in organizing the preparation and holding of major sporting events from the point of view of a healthcare organizer.Target: to identify areas of activity that require further improvement and development in the organization of medical support for major sporting events.Materials and methods. An analysis of the available literary sources of databases was carried out: RSCI, RusMed, Pubmed, Web of Science.Results. The most pressing groups of issues for further study and solution have been identified: the uniqueness, significance and complexity of sporting events; statistics and structure of diseases and injuries; features of the structure and course of medical conditions at sports facilities and events; organizing interaction between different services within the healthcare system and interdepartmental interaction; prevention and monitoring of infectious diseases; features of training of medical personnel.Conclusion. The holding of major sporting events, in turn, is a driver for the development of the healthcare system in the host city and country. Preparing for such an event requires the creation of a vision, operational plans, targeted training of personnel and infrastructure.

Possibilities of a biobank for serological monitoring of infectious morbidity

Currently, monitoring infectious morbidity, control and forecasting the epidemic process is a topical health problem.Aim. To analyze the capabilities of the biobank for serological monitoring of infectious diseases using the Epstein- Barr virus (EBV), which is associated with infectious mononucleosis, as well as somatic pathology, including cancer.Material and methods. Using the quantitative enzyme- linked immunosorbent assay for specific antibodies to various EBV proteins, we studied blood serum samples from healthy individuals (2010, 2016, 2019, 2020, 2021 and 2022) from the collection of the N. F. Gamaleya National Center of Epidemiology and Microbiology.Results. For the first time, the intensity of EBV epidemic process among apparently healthy adult residents of the capital was assessed using samples of biological material and a biobank information database. At the time of examination, 0,8% of individuals were not infected with EBV, and 9,4% suffered reactivation of a chronic infection. There were no significant changes in detection rate of markers over the years.Conclusion. Certified collections of blood sera can be effectively used to study population immunity, the prevalence of individual infections, population protection nationwide, etc.

A Survey on Core Flow Cytometry Facilities: Instrument Maintenance, Usage, and Funding.

Flow cytometry is a powerful tool that finds applications in various fields such as immunology, molecular biology, cancer biology, virology, and infectious disease monitoring. A significant portion of the research in these disciplines is supported by flow cytometry shared resource laboratories (SRLs). There are several types of flow cytometers available for use in SRLs, including analyzers, sorters, imaging flow cytometers, and mass cytometers. Each type has different challenges when it comes to maintenance and life expectancy. An independent online survey was conducted to better understand instrument maintenance and turnover in flow cytometry SRLs. Questions regarding instrument uptime (availability), its usage, routine maintenance, and cost associated with it were addressed. The respondents also answered questions pertaining to the frequency of deep cleaning of the instrument and quality control. In addition, the survey queried about the source of funding used to purchase the instruments and possible reasons for a replacement. Presented herein are the results compiled from 146 core facilities that provide a look at the operation within a typical SRL, with the responses reflecting researchers' experiences with handling flow cytometers.

Climate change and infectious disease surveillance in Nepal: qualitative study exploring social, cultural, political and institutional factors influencing disease surveillance.

To explore the impacts of contextual issues encompassing social, cultural, political and institutional elements, on the operation of public health surveillance systems in Nepal concerning the monitoring of infectious diseases in the face of a changing climate. Semi-structured interviews (n=16) were conducted amongst key informants from the Department of Health Services, Health Information Management System, Department of Hydrology and Meteorology, World Health Organization, and experts working on infectious disease and climate change in Nepal, and data were analysed using thematic analysis technique. Analysis explicates how climate change is constructed as a contingent risk for infectious diseases transmission and public health systems, and treated less seriously than other 'salient' public health risks, having implications for how resources are allocated. Further, analysis suggests a weak alliance among different stakeholders, particularly policy makers and evidence generators, resulting in the continuation of traditional practices of infectious diseases surveillance without consideration of the impacts of climate change. We argue that along with strengthening systemic issues (epidemiological capacity, data quality and inter-sectoral collaboration), it is necessary to build a stronger political commitment to urgently address the influence of climate change as a present and exponential risk factor in the spread of infectious disease in Nepal.

A web-based analytical framework for the detection and visualization space-time clusters of COVID-19

ABSTRACT The COVID-19 pandemic has had a profound impact worldwide and continues to spread due to various mutations of the virus. Many governmental and nonprofit agencies at different levels have quickly developed COVID-19 dashboards to disseminate information on the pandemic to the public. However, most of these systems have mainly distributed “plain” information (e.g. cases, death counts, vaccination), and rarely provided insights that can be gained from spatiotemporal analyses, such as the detection of emerging clusters. The results from these analyses hold tremendous potential for health policymakers as they try to identify ways to slow down transmission. We present a web-based geographic framework to detect and visualize space-time clusters of COVID-19. Our tightly coupled framework integrates the prospective space-time scan statistics and local indicators of spatial association (LISA) with novel 2D and 3D interactive visuals in a cyber environment (http://159.223.164.41/app/). We illustrate the applicability of our approach using COVID-19 data for the continental US. Our framework is portable to other regions that may experience infectious diseases but is also flexible to handle data of different spatial and temporal granularities. This paper fits within an effort to integrate space-time analytics for the monitoring of infectious diseases in web environment, ultimately improving health surveillance systems.

Data-driven adaptive testing resource allocation strategies for real-time monitoring of infectious diseases

Since 2002, with the SARS outbreak, infectious diseases, including the ongoing COVID-19 pandemic, have continued to be a major global public health threat. It is critical to develop effective data science methods to quickly detect disease outbreaks and contain their rapid globalized spread. However, in practice, limited testing availability, and thus insufficient testing data poses significant challenges in effective analysis and real-time monitoring of infectious diseases, especially during early stages of a novel disease outbreak. To tackle these challenges, this article proposes adaptive testing resource allocation strategies integrated with a physics-informed model to dynamically allocate limited testing resources across different communities. The physics-informed model accounts for transmission dynamics and health disparities, enabling effective health risk assessment despite limited data. By integrating nonstationary Multi-Armed Bandit techniques that strike superior balance between exploring the communities with high uncertain risks and exploiting those with high risk levels, the proposed methodology facilitates test allocation to collect high-quality testing data for early outbreak detection. Theoretical analysis is carried out to evaluate the performance of the proposed allocation strategies, ensuring either sublinear or linear dynamic pseudo-regret under regularity assumptions. A comprehensive simulation study is conducted under three transmission scenarios to thoroughly evaluate the proposed methodology.

Cycle Threshold Values as Indication of Increasing SARS-CoV-2 New Variants, England, 2020-2022.

Early detection of increased infections or new variants of SARS-CoV-2 is critical for public health response. To determine whether cycle threshold (Ct) data from PCR tests for SARS-CoV-2 could serve as an early indicator of epidemic growth, we analyzed daily mean Ct values in England, UK, by gene target and used iterative sequential regression to detect break points in mean Ct values (and positive test counts). To monitor the epidemic in England, we continued those analyses in real time. During September 2020-January 2022, a total of 7,611,153 positive SARS-CoV-2 PCR test results with Ct data were reported. Spike (S) gene target (S+/S-)-specific mean Ct values decreased 6-29 days before positive test counts increased, and S-gene Ct values provided early indication of increasing new variants (Delta and Omicron). Our approach was beneficial in the context of the first waves of the COVID-19 pandemic and can be used to support future infectious disease monitoring.

Epizootological monitoring of some bacterial infectious diseases of animals on the territory of the Republic of Kazakhstan

The presence of significant areas used for pastures in Kazakhstan makes it relevant to study the epizootic situation in terms of the incidence of animals during their grazing. The most frequent and dangerous diseases during this period are clostridiosis and listeriosis, which cause significant damage to livestock. Monitoring studies of the dynamics of morbidity among animals for infectious diseases during the grazing period were carried out on the basis of veterinary reporting. Bacteriological studies were carried out in a state laboratory using generally accepted microbiological methods. Analytical and statistical methods were used during the work. Monitoring studies indicate a significant spread of clostridiosis in the territory of Kazakhstan. The highest incidence rate was characterised by emphysematous carbuncle infection, which was recorded throughout the country, with an average frequency of about 40 cases per year. The incidence of braxy and anaerobic enterotoxemia occurred much less frequently and mainly in the southern regions of the country. Listeriosis was also observed only in some regions, but at the same time, a stationary focus of the disease was recorded in the Utylaut region, where cases of the disease are recorded annually. Conducted research made it possible to form the dynamics of the incidence of animals in the pasture period for these diseases, to determine the regions of the country with different intensity of the epizootic situation, as well as to carry out bacteriological isolation of a pure culture of the pathogen from samples taken in the foci of the disease. The studies made it possible to collect information on the features and mechanisms of the occurrence of diseases in the conditions of different regions of Kazakhstan and to develop a multi-vector strategy for preventive measures to eliminate animal diseases during the grazing period.

Construction and effectiveness evaluation of a knowledge-based infectious disease monitoring and decision support system

To improve the hospital's ability to proactively detect infectious diseases, a knowledge-based infectious disease monitoring and decision support system was established based on real medical records and knowledge rules. The effectiveness of the system was evaluated using interrupted time series analysis. In the system, a monitoring and alert rule library for infectious diseases was generated by combining infectious disease diagnosis guidelines with literature and a real medical record knowledge map. The system was integrated with the electronic medical record system, and doctors were provided with various types of real-time warning prompts when writing medical records. The effectiveness of the system's alerts was analyzed from the perspectives of false positive rates, rule accuracy, alert effectiveness, and missed case rates using interrupted time series analysis. Over a period of 12 months, the system analyzed 4,497,091 medical records, triggering a total of 12,027 monitoring alerts. Of these, 98.43% were clinically effective, while 1.56% were invalid alerts, mainly owing to the relatively rough rules generated by the guidelines leading to several false alarms. In addition, the effectiveness of the system's alerts, distribution of diagnosis times, and reporting efficiency of doctors were analyzed. 89.26% of infectious disease cases could be confirmed and reported by doctors within 5 min of receiving the alert, and 77.6% of doctors could complete the filling of 33 items of information within 2 min, which is a reduction in time compared to the past. The timely reminders from the system reduced the rate of missed cases by doctors; the analysis using interrupted time series method showed an average reduction of 4.4037% in the missed-case rate. This study proposed a knowledge-based infectious disease decision support system based on real medical records and knowledge rules, and its effectiveness was verified. The system improved the management of infectious diseases, increased the reliability of decision-making, and reduced the rate of underreporting.

Intestinal Villi-Inspired Mathematically Base-Layer Engineered Microneedles (IMBEMs) for Effective Molecular Exchange during Biomarker Enrichment and Drug Deposition in Diversified Mucosa.

The mucosa-interfacing systems based on bioinspired engineering design for sampling/drug delivery have manifested crucial potential for the monitoring of infectious diseases and the treatment of mucosa-related diseases. However, their efficiency and validity are severely restricted by limited contact area for molecular transfer and dissatisfactory capture/detachment capability. Herein, inspired by the multilayer villus structure of the small intestine that enables high nutrient absorption, a trigonometric function-based periodic pattern was fabricated and integrated on the base layer of the microneedle patch, exhibiting a desirable synergistic effect with needle tips for deep sample enrichment and promising molecular transfer, significantly improving the device-mucosa bidirectional interaction. Moreover, mathematical modeling and finite element analysis were adopted to visualize and quantify the microcosmic molecular transmission process, guiding parameter optimization in actual situation. Encouragingly, these intestinal villi-inspired mathematically base-layer engineered microneedles (IMBEMs) have demonstrated distinguished applicability among mucosa tissue with varying surface curvatures, tissue toughness, and local environments, and simultaneously, have gained favorable support from healthy volunteers receiving preliminary test of IMBEMs patches. Overall, validated by numerous in vitro and in vivo tests, the IMBEMs were confirmed to act as a promising candidate to facilitate mucosa-based sampling and topical drug delivery, indicating highly clinical translation potential.

Isolation, characterization, and pathogenicity assessment of Corynebacterium pseudotuberculosis biovar equi strains from alpacas (Vicugna pacos) in China.

Corynebacterium pseudotuberculosis is a zoonotic pathogen that causes lymphadenitis in humans, livestock, and wildlife. In this study, C. pseudotuberculosis biovar equi strains were isolated from three alpacas. Antibiotic susceptibility tests and pathogenicity tests were also conducted. Moreover, one strain was sequenced using DNBSEQ and Oxford Nanopore technology. The three strains exhibited resistance to aztreonam, fosfomycin, and nitrofurantoin. The median lethal doses (LD50) of strains G1, S2 and BA3 in experimentally infected mice was 1.66 × 105 CFU, 3.78 × 105 CFU and 3.78 × 105 CFU, respectively. The sequencing of strain G1 resulted in the assembly of a chromosomal scaffold comprising 2,379,166 bp with a G + C content of 52.06%. Genome analysis of strain G1 revealed the presence of 48 virulence genes and 5 antibiotic resistance genes (ARGs). Comparative genomic analysis demonstrates a high degree of genetic similarity among C. pseudotuberculosis strains, in contrast to other Corynebacterium species, with a clear delineation between strains belonging to the two biovars (ovis and equi). The data of the present study contribute to a better understanding of the properties of C. pseudotuberculosis biovar equi strains and the potential risk they pose to alpacas and other livestock, as well as the necessity of ongoing surveillance and monitoring of infectious diseases in animals.

The Current Policy Debate around the Regulation of LDTs: What It Means for Infectious Disease Testing and Where It May Be Headed

The debate over federal regulation of diagnostic tests is not new, but scientific advances, societal developments, and global events over the past decade have accelerated efforts by the Food and Drug Administration (FDA) and members of Congress to revise the regulatory oversight of these devices, including laboratory-developed tests (LDTs). Despite years of congressional hearings and public meetings, legislation in the House and Senate, draft guidance from the FDA, and debate in the stakeholder community, LDT regulation remains unchanged, and the path forward remains unclear. LDTs play an essential role in infectious disease (ID) management and treatment, and changes in their regulation will have far-reaching implications for diagnostic laboratories. LDTs are widely used by clinical microbiology laboratories for the diagnosis and monitoring of a myriad infectious diseases, and until three years ago, such testing was conducted largely out of the spotlight. The COVID-19 pandemic changed this by bringing ID tests into the forefront. As the 118th Congress gets under way, the regulation and oversight of diagnostic tests, including LDTs, remains at the forefront of health care policy discussions on Capitol Hill and with the FDA. Change is coming, and it is important that clinical microbiologists, ID physicians, and other laboratorians have a seat at the table when such changes are being discussed.

Wastewater monitoring for detection of public health markers during the COVID-19 pandemic: Near-source monitoring of schools in England over an academic year.

Schools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England. A total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools. We report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30th November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x106 GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR. Passive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases.

No time for complacency on COVID-19 in Europe

No time for complacency on COVID-19 in Europe

Global age-structured spatial modeling for emerging infectious diseases like COVID-19.

Modeling the global dynamics of emerging infectious diseases (EIDs) like COVID-19 can provide important guidance in the preparation and mitigation of pandemic threats. While age-structured transmission models are widely used to simulate the evolution of EIDs, most of these studies focus on the analysis of specific countries and fail to characterize the spatial spread of EIDs across the world. Here, we developed a global pandemic simulator that integrates age-structured disease transmission models across 3,157 cities and explored its usage under several scenarios. We found that without mitigations, EIDs like COVID-19 are highly likely to cause profound global impacts. For pandemics seeded in most cities, the impacts are equally severe by the end of the first year. The result highlights the urgent need for strengthening global infectious disease monitoring capacity to provide early warnings of future outbreaks. Additionally, we found that the global mitigation efforts could be easily hampered if developed countries or countries near the seed origin take no control. The result indicates that successful pandemic mitigations require collective efforts across countries. The role of developed countries is vitally important as their passive responses may significantly impact other countries.

Diseased Fish Detection in the Underwater Environment Using an Improved YOLOV5 Network for Intensive Aquaculture

In intensive aquaculture, the real-time detection and monitoring of common infectious disease is an important basis for scientific fish epidemic prevention strategies that can effectively reduce fish mortality and economic loss. However, low-quality underwater images and low-identification targets present great challenges to diseased fish detection. To overcome these challenges, this paper proposes a diseased fish detection model, using an improved YOLOV5 network for aquaculture (DFYOLO). The specific implementation methods are as follows: (1) the C3 structure is used instead of the CSPNet structure of the YOLOV5 model to facilitate the industrial deployment of the algorithm; (2) all the 3 × 3 convolutional kernels in the backbone network are replaced by a convolutional kernel group consisting of parallel 3 × 3, 1 × 3 and 3 × 1 convolutional kernels; and (3) the convolutional block attention module is added to the YOLOV5 algorithm. Experimental results in a fishing ground showed that the DFYOLO is better than that of the original YOLOV5 network, and the average precision was improved from 94.52% to 99.38% (when the intersection over union is 0.5), for an increase of 4.86%. Therefore, the DFYOLO network can effectively detect diseased fish and is applicable in intensive aquaculture.