Healthcare Surveillance Research Articles

1.L. Scientific session: Public Health data in support of healthy ageing policies

Abstract As Europe grapples with an ageing population, the imperative of health policies that promote healthy ageing is increasingly critical. This workshop aims to explore the significant role of public health data in shaping and supporting such policies. By integrating insights from administrative records to sophisticated research infrastructures, we will highlight the multifaceted uses of data in public health, particularly in the realms of non-communicable diseases and health-related behaviours in older populations. The session will open by examining how administrative records have been utilised within Lombardy’s regional health system to understand the epidemiology and access to care for people living with dementia. The discussion will then cover the advantages and challenges associated with integrating health data from diverse sources, emphasising the importance of quality, privacy, and the potential for real-time surveillance and response systems in healthcare. Following this, the focus will shift to the determinants of good health among older adults, presenting findings from a comprehensive cross-sectional study that identifies key factors contributing to what can be termed as “superhero” health status: seniors who maintain excellent physical and mental health. This analysis will delve into socioeconomic, behavioural, and environmental factors that influence health outcomes in the elderly, providing evidence-based recommendations for public health interventions and highlighting the potentialities of ad hoc surveys in examining health outcomes during emergencies. Thirdly, the workshop will also address the impact of significant life transitions on health behaviours, specifically the transition to retirement and its effects on alcohol consumption. Leveraging longitudinal data from a pan-European multidisciplinary research infrastructure, it will be demonstrated how retirement affects daily habits and lifestyles, including changes in alcohol consumption patterns. This segment will explore the implications of these findings for public health planning and policy formulation. In conclusion, there will be a discussion about healthcare system policies that support healthy ageing and the global impact of ageing on economics and health economics. These discussions will draw from the presented data sources and studies to suggest ways in which public health policies can be designed to reduce disparities and improve overall health outcomes among the elderly. This workshop is designed to provide a comprehensive overview of how data-driven insights can inform effective public health strategies and interventions to support an ageing society. By exploring various aspects of health data application, from individual behaviour to systemic policy adjustments, the session aims to highlight the critical role of data in promoting sustainable health and well-being in older adults, especially in the context of increasing life expectancy and prolonged retirement periods. Key messages • Harnessing data from diverse sources is crucial for understanding and enhancing healthy ageing processes. • Utilising longitudinal studies and robust data to design informed public health policies is essential for effective ageing interventions.

Factors associated with cervical cancer screening among women of reproductive age in Ghana

BackgroundCervical cancer remains a leading cause of cancer-related deaths among women in Ghana and other Sub-Sahara African (SSA) countries. Despite the importance of early diagnosis for timely treatment and death prevention, cervical cancer screening among women in developing countries remain very low. Nonetheless, there is a paucity of research examining the factors associated with screening uptake among women of reproductive age in Ghana. Thus, this study fills the scholarly void and contributes to the existing literature by examining the determinants of cervical cancer screening in Ghana.MethodsUtilizing data from the 2022 Ghana Demographic and Health Survey (GDHS) (N = 15,014 women), and by employing logistic regression models for a cross-sectional analysis, this study evaluated the factors associated with cervical cancer screening in Ghana.ResultsWomen with tertiary educational attainment (OR = 4.140; 95%CI: 2.960 5.789; p < 0.001), from the richer (OR = 1.968; p < 0.001) and richest households (OR = 2.492; p < 0.001), the married/living with partner (OR = 1.773; 95%CI:1.372 2.290; p < 0.001), the widowed/divorced/separated (OR = 1.888; 95%CI:1.320 2.701; p < 0.001), owners of valid health insurance card (OR = 1.356; 95%CI:1.086 1.693; p < 0.01), visitation to health facility in the past 12 months (OR = 1.312; 95%CI: 1.082 1.590; p < 0.001), those who watched television at least once in a week (OR = 1.395; 95%CI: 1.055 1.846; p < 0.001), as well as those who listened to radio at least once in a week (OR = 1.509; 95%CI: 1.228 1.853; p < 0.001), were all significantly more associated with cervical cancer screening in the study context. Also, ethnicity, religion, and the region of residence significantly predicted cervical cancer screening in the study context.ConclusionCervical cancer screening in Ghana can be improved by addressing socioeconomic and geographical disparities in the country’s healthcare system. To ensure early detection, timely treatment or care and prevention of cervical cancer-related deaths in the country, there must be coordinated efforts by the government of Ghana to improve healthcare access and surveillance systems for cervical cancer cases, particularly, in geographically disadvantage areas.

Improving Detection of Hospital Adverse Events Using Machine Learning on Real-World Narrative EMR Data

ObjectiveAdministrative data often underrepresents hospital adverse events (AEs) due to limitations in International Classification of Diseases (ICD) coding. By leveraging electronic medical records (EMRs), we aim to mitigate these discrepancies and enhance the precision of healthcare surveillance and performance evaluations. To this end, we have developed a machine learning (ML)-based approach that utilizes EMR text data to detect common AEs. MethodsWe sampled adult admissions from four Calgary hospitals (2017 - 2022). Registered nurses assessed charts for 17 AEs, and the results were used as reference standard. We compared two AE detection methods: the standard ICD-based method following Canadian guidelines, and our ML algorithm applied to EMR narratives. Sensitivity, positive predictive value (PPV), negative predictive value (NPV), and specificity for both methods were calculated and compared against the reference standard. ResultsWe analyzed 9,566 patients, of whom 1,506 were identified with AEs. Of the 17 AEs, the sensitivity in ICD-coded data ranged from 0-37%, and in EMRs, it was between 75-100%. Both showed low PPV (0-50% ICD vs.1-34% EMR). ICD data had high specificity ranging from 99-100% and NPV (99%-100%), while EMRs had specificity between 68-94% and an NPV of 100%. Conclusion and ImplicationsML significantly enhances sensitivity for AE detection compared to ICD-10-CA coding, despite both methods experiencing low PPV due to imbalances in EMR data. This marked improvement in sensitivity highlights ML's potential to transform AE surveillance and reporting, promising significant advancements in patient safety and healthcare quality by enabling more accurate and comprehensive identification of AEs.

Family doctors play a crucial role in a comprehensive healthcare surveillance system.

Family doctors play a crucial role in a comprehensive healthcare surveillance system.

Эффективность использования новой роботической системы Versius для выполнения операций у детей: результаты клинических испытаний

Authors represent the Russia’s first research demonstrating the results of the use of the Versius modular &amp; portable surgical robot by “CMR Surgical,” Ltd. (Cambridge, Cambridgeshire, United Kingdom) in surgical interventions on pediatric patients that they’ve obtained as part of the clinical trials complex approved by the Federal Service for Surveillance in Healthcare of Russia (“Roszdravnadzor”). The purpose of this research was to obtain practical evidence of the clinical safety and effectiveness of the use of the new Versius® Surgical Robotic System in minimally invasive surgical interventions on children. The criteria for the safety and effectiveness of the method were the absence of complications caused by the Surgical Robotic System (SRS) operation or the surgical technique as well as the absence of dropping into either laparoscopy or open surgery technique. Material and methods used: non-randomized single-center controlled trial had been carried out in children aged 1 to 18 y/o. Areas of application for surgical procedures included urology, abdominal and thoracic surgeries. Results: the number of patients who had undergone the robot-assisted surgeries had totaled 55 (27 (49%) m/28 (51%) f). The patient’s median age of the surgical intervention was 11.5 [7.0; 15.0] y/o; the median weight was 45.5 [27.0; 59.0] kilograms; the median surgical intervention duration was 140.0 [85.0; 175.0] minutes; patients’ stay in the intensive care unit had averaged for 23.0 [19.0; 24.0] hours; the average hospitalization duration was 8.0 [4.0; 14.0] days. Surgical interventions weren’t accompanied by any of the intraoperative complications such as bleeding, organ perforation and/or injury to adjacent anatomical structures. Conversions to either laparoscopic or open surgery technique also weren’t recorded. The equipment technical problems with SRS such as sudden system power-off, synchronous interaction of joysticks/manipulators interruption, robotic arms blocking, manipulators’ uncontrolled movement and/or traumatic effects on the tissues of the abdominal wall/chest weren’t recorded as well. Conclusion: the preliminary results obtained from the clinical trials complex affirm the potential ability of the Versius® Surgical Robotic System to performing robotic surgical interventions on pediatric patients aged 1 to 18 years old.

Organized Optimization Integration Validation Model for Internet of Things (IoT)-Based Real-Time Applications

Emerging technology like the Internet of Things (IoT) has great potential for use in real time in many areas, including healthcare, agriculture, logistics, manufacturing, and environmental surveillance. Many obstacles exist alongside the most popular IoT applications and services. The quality of representation, modeling, and resource projection is enhanced through interactive devices/interfaces when IoT is integrated with real-time applications. The architecture has become the most significant obstacle due to the absence of standards for IoT technology. Essential considerations while building IoT architecture include safety, capacity, privacy, data processing, variation, and resource management. High levels of complexity minimization necessitate active application pursuits with variable execution times and resource management demands. This article introduces the Organized Optimization Integration Validation Model (O2IVM) to address these issues. This model exploits k-means clustering to identify complexities over different IoT application integrations. The harmonized service levels are grouped as a single entity to prevent additional complexity demands. In this clustering, the centroids avoid lags of validation due to non-optimized classifications. Organized integration cases are managed using centroid deviation knowledge to reduce complexity lags. This clustering balances integration levels, non-complex processing, and time-lagging integrations from different real-time levels. Therefore, the cluster is dissolved and reformed for further integration-level improvements. The volatile (non-clustered/grouped) integrations are utilized in the consecutive centroid changes for learning. The proposed model’s performance is validated using the metrics of execution time, complexity, and time lag.

Mapping Digital Public Health Interventions Among Existing Digital Technologies and Internet-Based Interventions to Maintain and Improve Population Health in Practice: Scoping Review.

The rapid progression and integration of digital technologies into public health have reshaped the global landscape of health care delivery and disease prevention. In pursuit of better population health and health care accessibility, many countries have integrated digital interventions into their health care systems, such as web-based consultations, electronic health records, and telemedicine. Despite the increasing prevalence and relevance of digital technologies in public health and their varying definitions, there has been a shortage of studies examining whether these technologies align with the established definition and core characteristics of digital public health (DiPH) interventions. Hence, the imperative need for a scoping review emerges to explore the breadth of literature dedicated to this subject. This scoping review aims to outline DiPH interventions from different implementation stages for health promotion, primary to tertiary prevention, including health care and disease surveillance and monitoring. In addition, we aim to map the reported intervention characteristics, including their technical features and nontechnical elements. Original studies or reports of DiPH intervention focused on population health were eligible for this review. PubMed, Web of Science, CENTRAL, IEEE Xplore, and the ACM Full-Text Collection were searched for relevant literature (last updated on October 5, 2022). Intervention characteristics of each identified DiPH intervention, such as target groups, level of prevention or health care, digital health functions, intervention types, and public health functions, were extracted and used to map DiPH interventions. MAXQDA 2022.7 (VERBI GmbH) was used for qualitative data analysis of such interventions' technical functions and nontechnical characteristics. In total, we identified and screened 15,701 records, of which 1562 (9.94%) full texts were considered relevant and were assessed for eligibility. Finally, we included 185 (11.84%) publications, which reported 179 different DiPH interventions. Our analysis revealed a diverse landscape of interventions, with telemedical services, health apps, and electronic health records as dominant types. These interventions targeted a wide range of populations and settings, demonstrating their adaptability. The analysis highlighted the multifaceted nature of digital interventions, necessitating precise definitions and standardized terminologies for effective collaboration and evaluation. Although this scoping review was able to map characteristics and technical functions among 13 intervention types in DiPH, emerging technologies such as artificial intelligence might have been underrepresented in our study. This review underscores the diversity of DiPH interventions among and within intervention groups. Moreover, it highlights the importance of precise terminology for effective planning and evaluation. This review promotes cross-disciplinary collaboration by emphasizing the need for clear definitions, distinct technological functions, and well-defined use cases. It lays the foundation for international benchmarks and comparability within DiPH systems. Further research is needed to map intervention characteristics in this still-evolving field continuously. PROSPERO CRD42021265562; https://tinyurl.com/43jksb3k. RR2-10.2196/33404.

Participatory Disease Surveillance for the Early Detection of Cholera-Like Diarrheal Disease Outbreaks in Rural Villages in Malawi: Prospective Cohort Study.

Cholera-like diarrheal disease (CLDD) outbreaks are complex and influenced by environmental factors, socioeconomic conditions, and population dynamics, leading to limitations in traditional surveillance methods. In Malawi, cholera is considered an endemic disease. Its epidemiological profile is characterized by seasonal patterns, often coinciding with the rainy season when contamination of water sources is more likely. However, the outbreak that began in March 2022 has extended to the dry season, with deaths reported in all 29 districts. It is considered the worst outbreak in the past 10 years. This study aims to evaluate the feasibility and outcomes of participatory surveillance (PS) using interactive voice response (IVR) technology for the early detection of CLDD outbreaks in Malawi. This longitudinal cohort study followed 740 households in rural settings in Malawi for 24 weeks. The survey tool was designed to have 10 symptom questions collected every week. The proxies' rationale was related to exanthematic, ictero-hemorragica for endemic diseases or events, diarrhea and respiratory/targeting acute diseases or events, and diarrhea and respiratory/targeting seasonal diseases or events. This work will focus only on the CLDD as a proxy for gastroenteritis and cholera. In this study, CLDD was defined as cases where reports indicated diarrhea combined with either fever or vomiting/nausea. During the study period, our data comprised 16,280 observations, with an average weekly participation rate of 35%. Maganga TA had the highest average of completed calls, at 144.83 (SD 10.587), while Ndindi TA had an average of 123.66 (SD 13.176) completed calls. Our findings demonstrate that this method might be effective in identifying CLDD with a notable and consistent signal captured over time (R2=0.681404). Participation rates were slightly higher at the beginning of the study and decreased over time, thanks to the sensitization activities rolled out at the CBCCs level. In terms of the attack rates for CLDD, we observed similar rates between Maganga TA and Ndindi TA, at 16% and 15%, respectively. PS has proven to be valuable for the early detection of epidemics. IVR technology is a promising approach for disease surveillance in rural villages in Africa, where access to health care and traditional disease surveillance methods may be limited. This study highlights the feasibility and potential of IVR technology for the timely and comprehensive reporting of disease incidence, symptoms, and behaviors in resource-limited settings.

Bridging the Gap: Specialized Training Programs for Infection Prevention Specialists Increase Certification Success

Background: The role of the infection preventionist (IP) is complex and encompasses a range of responsibilities requiring extensive knowledge in infection control practices, data analysis, surveillance, performance improvement and collaboration with multidisciplinary teams. Infection prevention certification (CIC) by the certification Board of Infection Control (CBIC) is a standardized marker of knowledge and competencies required for practice in the field. In a 2020 survey of IPs, less than half were certified or planned to become certified. Of those that do take the certification exam, less than three quarters pass on their initial exam attempt. Methods: From 2017 to 2023, fifty-two new IPs were enrolled in a competency-based training program which combined didactic and applied learning on core IP job functions, and a structured mentoring program. The initial didactic phase consisted of evidence-based learning modules with validation of competency through post-training testing and practical demonstration. Education was provided by an advanced practice IP via remote webinars, which included discussion of questions, skills coaching, and review of post-tests. Novice IPs were partnered with at least two preceptors: one advanced practice lead preceptor guided the novice IPs through assigned education modules and oversaw program management and training benchmarks. A second, near-peer preceptor or mentor collaborated with the novice IP in the facility setting. Initial training focused on facility operations, surveillance, rounding and other facility specific activities. Facility mentors were responsible for combining education module topics with practical application of skills. Mentors guided novice IPs through National Healthcare Surveillance network (NHSN) surveillance training and validated surveillance and infection coding until the novice IP had an interrater reliability validation assessing surveillance competency. After the initial training phase, the novice IPs began preparation for certification. This phase included additional training modules aligned with the CBIC certification content outline and practice exams. Results: All 52 novice IPs completed the training program and attempted the CIC examination. The initial pass rate for the certification exam among IPs in the supervised training and mentorship program was 98.1% (n=51). This is 33% higher than the initial pass rate published by CBIC, which was 73.9% (Figure 1). Conclusions: Organizing evidence-based guidelines into topic-specific modules builds a foundation of infection prevention and control knowledge, which is enhanced through remote instruction and direct application of skills under a preceptor’s supervision. This method allows IPs to be introduced to concepts covered in the board certification exam upon hire and support certification with improved outcome

The place of metformin in the treatment of carbohydrate metabolism disorders and insulin resistance during, before and after pregnancy: resolution of the expert council

Due to its effect on insulin resistance, ease of administration and favorable safety profile, metformin has been included in the recommendations of foreign medical communities for the management of pregnant women with hyperglycemia since 2008. However, in Russia, the use of any oral hypoglycemic agents during pregnancy is still contraindicated. However, recent studies demonstrate the safety and positive effects of metformin on pregnancy in patients with pregestational diabetes mellitus, polycystic ovary syndrome and gestational diabetes mellitus. In 2023, the Federal Service for Surveillance in Healthcare of the Ministry of Health of Russia updated the instructions for the medical use of Glucophage® and Glucophage®Long: pregnancy was excluded from the “Contraindications” section and moved to the “With caution” section. This resolution is intended to evaluate studies of the effectiveness and safety of metformin, as well as to study the experience of foreign colleagues and Russian legal aspects of prescribing metformin in the stages of preparation for pregnancy, during it and in the post-gravid period.

A Review of Conductive Hydrogel-Based Wearable Temperature Sensors.

Conductive hydrogel has garnered significant attention as an emergent candidate for diverse wearable sensors, owing to its remarkable and tailorable properties such as flexibility, biocompatibility, and strong electrical conductivity. These attributes make it highly suitable for various wearable sensor applications (e.g., biophysical, bioelectrical, and biochemical sensors) that can monitor human health conditions and provide timely interventions. Among these applications, conductive hydrogel-based wearable temperature sensors are especially important for healthcare and disease surveillance. This review aims to provide a comprehensive overview of conductive hydrogel-based wearable temperature sensors. First, this work summarizes different types of conductive fillers-based hydrogel, highlighting their recent developments and advantages as wearable temperature sensors. Next, this work discusses the sensing characteristics of conductive hydrogel-based wearable temperature sensors, focusing on sensitivity, dynamic stability, stretchability, and signal output. Then, state-of-the-art applications are introduced, ranging from body temperature detection and wound temperature detection to disease monitoring. Finally, this work identifies the remaining challenges and prospects facing this field. By addressing these challenges with potential solutions, this review hopes toshed some light on future research and innovations in this promising field.

РОБОТ-АССИСТИРОВАННЫЕ ОПЕРАЦИИ В ДЕТСКОЙ АБДОМИНАЛЬНОЙ ХИРУРГИИ: ПЕРВОНАЧАЛЬНЫЙ ОПЫТ

Purpose of this research was to apply the possibilities of robot-assisted surgery technology in children with abdominal pathology in terms of assessing feasibility and evaluating postoperative results. Material and methods used: the scientific study was carried out at the Irkutsk Oblast Regional Children's Clinical Hospital (Irkutsk, Russia) in Dec. 2022-June 2023. During this period, 11 robot-assisted procedures were performed on the abdominal organs. The study was conducted within the framework of the Clinical Trials Program for Medical Products approved by the Federal Service for Surveillance in Healthcare of the Russian Federation. All surgical procedures were implemented according to the same principles and patterns that the Authors have gathered previously with the Versius Surgical Robot. In all cases, the three robotic ports were used: a single 12-mm trocar for optics (intervened at the umbilicus) and two 5-mm trocars for robotic arms. Additionally, another 5-mm laparoport was installed for the assistant surgeon to work during the robotic intervention. During the study, patients' perioperative parameters related to data charts, surgical details and both early and long-term outcomes were recorded. Results: the total number of patients involved in robotic interventions on the abdominal organs was 11, 4 (36,4%) boys/7 (63,6%) girls. The mean age at the time of surgery was 10,9±5.1 y/o (Me 12.0 [7.0; 15.0] y/o), mean weight at the time of surgery was 39.7±18.0 kg (Me 43.0 [24.0; 53.8] kg). The distribution of reasons for surgical interventions was as follows: 3 (27,3%) patients with Nissen fundoplication, 3 (27,3%) patients with cholecystectomy, 2 (18,2%) patients with Heller esophagomyotomy with Dor fundoplication, 2 (18,2%) patients with splenic cyst fenestration and a single (9%) patient with enucleation of ovarian teratoma. The mean duration was 100±52.4 min (Me 70.0 [65.0; 122.5] min). None of the operations were accompanied by any intraoperative complications. There were also no conversions into laparoscopic and/or open surgeries. In the long-term period after the operations, the number of significant complications in the form of recurrence of symptoms of the initial disease did not increase, patients showed no digestive problems during the entire follow-up period as well. Conclusion: Russia’s initial experience with robotic-assisted abdominal surgery confirmed that robotics can be safely and effectively used in children. Fundoplication, esophagomyotomy and cholecystectomy are by far the most commonly performed basic interventions in pediatric surgery. Obviously, this is the first stage in the development of robotic abdominal surgery in children hence it would further involve a more complex procedure.

Healthcare and Epidemiological Surveillance Costs of Hepatitis A Outbreaks in Spain in Regions with and without Universal Hepatitis A Vaccination of Children during 2010-2018.

The aim of this study was to evaluate and compare hepatitis A outbreak-associated healthcare and epidemiological surveillance costs in Spain in two types of autonomous regions during 2010-2018: (1) regions with a prevention strategy based on universal hepatitis A vaccination of children and vaccination of high-risk population groups (Catalonia) and (2) regions with a prevention strategy based on vaccinating high-risk population groups (Castile and Leon, Murcia, Navarra, Community of Madrid, Community of Valencia). Healthcare costs were determined based on the resources used to treat hepatitis A outbreak-associated cases and hospitalizations. Epidemiological surveillance costs were calculated from the resources used during surveillance activities. The ratios for total, healthcare and epidemiological surveillance costs (regions without universal hepatitis A vaccination of children vs. Catalonia) were used to compare the two hepatitis A prevention strategies. From 2010 to 2018, the total, healthcare and epidemiological surveillance costs per million population were 1.75 times (EUR 101,671 vs. EUR 58,032), 1.96 times (EUR 75,500 vs. EUR 38,516) and 1.34 times greater (EUR 26,171 vs. EUR 19,515) in regions without universal hepatitis A vaccination of children than in Catalonia, respectively. The ratios tended to increase over time during 2010-2018. In 2015-2018, total, healthcare and epidemiological surveillance costs per million population were 2.68 times (EUR 69,993 vs. EUR 26,158), 2.86 times (EUR 53,807 vs. EUR 18,825) and 2.21 times greater (EUR 16,186 vs. EUR 7333) in regions without universal hepatitis A vaccination of children than in Catalonia, respectively. These findings suggest that universal hepatitis A vaccination of children could reduce hepatitis A outbreak-associated costs.

An empirical IoT and cloud-based customizable healthcare surveillance system

An empirical IoT and cloud-based customizable healthcare surveillance system

DIRED: Dual Indicator Random Early Detection for Congestion Control in WSN

SummaryWireless Sensor Networks (WSNs) find applications in diverse fields such as environmental monitoring, healthcare, and military surveillance. Nonetheless, one of the primary challenges encountered by WSNs is congestion. Congestion arises in WSNs when there is a high volume of traffic on the network, leading to significant repercussions. These repercussions encompass packet loss, heightened latency durations, and diminished network efficiency. This paper presents an innovative congestion control mechanism named Dual Indicator Random Early Detection (DIRED). DIRED leverages two indicators, namely queue length and packet loss rate, to dynamically adjust the dropping probability of packets, thereby mitigating congestion and enhancing network performance. For the successful execution of the DIRED model, a congestion control algorithm is introduced. This strategy efficiently prevents the deterioration of network performance that can commonly arise from extremely low packet drop probabilities. Simulations are conducted to evaluate the proposed DIRED model, comparing it with the KACO and KFOA techniques. The results demonstrate that DIRED outperforms KACO and KFOA in terms of network performance, achieving a more optimal balance between performance metrics and packet‐dropping probability.

Modern engineering solutions for an original domestic nitric oxide generator (“Tianox”)

Nitric oxide (NO) is a biologically active molecule approved for the treatment of persistent pulmonary hypertension in newborns in the USA, Japan, and most European countries in 1999 – 2008. Inhaled NO is currently used to treat a spectrum of cardiopulmonary disorders, including pulmonary hypertension in children and adults. A commercially available NO delivery system uses pressurized cylinders as a source of NO. Current cylinder-based delivery systems are widely used around the world, but they are bulky, expensive and dependent on a reliable supply chain. The aim of the work was to present an original domestic generator for NO inhalation therapy. Over the past few years, to overcome the limitations of the balloon technology, specialists from the Federal State Unitary Enterprise “Russian Federal Nuclear Center – All-Russian Research Institute of Experimental Physics” have developed a plasma-chemical NO generator that produces NO from ambient air using a nonequilibrium spark discharge plasma. In this case, a diffuse discharge mode is implemented, which ensures the most efficient synthesis of NO with the participation of excited nitrogen molecules (N2+) according to a chain mechanism similar to the Zeldovich – Semenov chain reaction. The result is a high-quality NO-containing gas mixture that does not contain toxic by-products (electrode material, ozone, etc.) usually formed in the known systems of this type. Conclusion. Based on the developed generator, the Federal State Unitary Enterprise “Russian Federal Nuclear Center – All-Russian Research Institute of Experimental Physics” designed and created the world’s first commercially available device for inhalation therapy, “Tianox”. The device was approved for circulation on the territory of the Russian Federation by order of the Federal Service for Surveillance in Healthcare (2020) based on the results of technical and clinical tests. Serial production of “Tianox” meets the requirements of ISO 13485-2016 and GOST ISO 13485-2017.

Detection of Novel Influenza Viruses Through Community and Healthcare Testing: Implications for Surveillance Efforts in the United States.

Novel influenza viruses pose a potential pandemic risk, and rapid detection of infections in humans is critical to characterizing the virus and facilitating the implementation of public health response measures. We use a probabilistic framework to estimate the likelihood that novel influenza virus cases would be detected through testing in different community and healthcare settings (urgent care, emergency department, hospital, and intensive care unit [ICU]) while at low frequencies in the United States. Parameters were informed by data on seasonal influenza virus activity and existing testing practices. In a baseline scenario reflecting the presence of 100 novel virus infections with similar severity to seasonal influenza viruses, the median probability of detecting at least one infection per month was highest in urgent care settings (72%) and when community testing was conducted at random among the general population (77%). However, urgent care testing was over 15 times more efficient (estimated as the number of cases detected per 100,000 tests) due to the larger number of tests required for community testing. In scenarios that assumed increased clinical severity of novel virus infection, median detection probabilities increased across all healthcare settings, particularly in hospitals and ICUs (up to 100%) where testing also became more efficient. Our results suggest that novel influenza virus circulation is likely to be detected through existing healthcare surveillance, with the most efficient testing setting impacted by the disease severity profile. These analyses can help inform future testing strategies to maximize the likelihood of novel influenza detection.

Cholera and diarrheal diseases in Cuamba District, Niassa Province, Mozambique: Systematic healthcare facility-based surveillance strengthening, characteristics of suspected cholera and diarrheal patients, and incidence of diarrheal diseases.

Mozambique is one of the countries in Africa that is continuously at risk of cholera outbreaks due to poor sanitation, hygiene, and limited access to potable water in some districts. The Mozambique Cholera Prevention and Surveillance (MOCA) project was implemented in Cuamba District, Niassa Province to prevent and control cholera outbreaks through a preemptive cholera vaccination, strengthened surveillance system for cholera and diarrheal diseases, and better understanding of cholera-related healthcare seeking behavior of local populations, which may further guide the national cholera control and prevention strategies. This article presents the surveillance component of the MOCA project. A prospective healthcare facility (HCF)-based surveillance of cholera and diarrheal disease was conducted in six HCFs in the District of Cuamba from March 2019 to December 2020. A systematic surveillance procedure has been put in place with capacity building in selected sentinel HCFs and a basic microbiology laboratory established on-site. Patients presenting with suspected cholera or other diarrheal symptoms were eligible for enrollment. Clinical data and rectal swab samples were collected for laboratory confirmation of Vibrio Cholerae and other pathogens. A total of 419 eligible patients from six HCFs were enrolled. The median age was 19.8 years with a similar age distribution between sentinel sites. The majority were patients who exhibited diarrhea symptoms not suspected of cholera (88.8%; n = 410). Among those, 59.2% (210/397) were female and 59.9% (235/392) were 15 years and above. There were 2 cholera cases, coming outside of the catchment area. The incidence of diarrheal diseases ranged from 40-103 per 100,000 population. No Vibrio cholerae was isolated among surveillance catchment population and Escherichia coli spp. (82/277; 29.6%) was the most common pathogen isolated. Efforts were made to strengthen the systematic surveillance of suspected cholera with standardised patient screening, enrolment, and diagnostics. The first basic microbiology laboratory in Niassa Province established in Cuamba District under the MOCA project needs to be integrated into the national network of laboratories for sustainability. No reports of laboratory confirmed cholera cases from the surveillance catchment area may be highly related to the pre-emptive oral cholera vaccine (OCV) mass vaccination campaign conducted in 2018 and the use of drugs by local populations prior to visiting the sentinel HCFs. Continued systematic cholera surveillance is needed to closely monitor the cholera endemicity and epidemics, and further evaluate the long-term impact of this vaccination. High incidence of diarrheal illnesses needs to be addressed with improved water, sanitation, and hygiene (WaSH) conditions in Cuamba District. Efforts integrated with the prioritization of prevention measures are fundamental for the control of cholera in the country.

Comparison of an algorithm, and coding data, with traditional surveillance to identify surgical site infections in Australia: a retrospective multi-centred cohort study

Surveillance of healthcare-associated infections (HAIs) in Australia is disparate, resource intensive, unsustainable, and provides limited information. Traditional HAI surveillance is time intensive and agreement levels between clinicians have been shown to be variable. To compare two methods: a semi-automated algorithm, and coding data, against traditional surgical site infection (SSI) surveillance methods. This retrospective multi-centre cohort study included all patients undergoing a hip (HPRO) or knee (KPRO) prosthesis and coronary artery bypass graft (CABG) surgery during a two-year period at two large metropolitan hospitals. Routine SSI data were obtained via the infection prevention and control (IPC) team, a previously developed algorithm was applied to all patient records, and the ICD-10-AM data were searched for those categorized as having an SSI. Overall, 1447, 1416, and 1026 patients who underwent HPRO, KPRO, and CABG, respectively, were included. The highest sensitivity values were generated by the algorithm: HPRO deep or organ-space (D/O) 0.87 (95% confidence interval: 0.66-0.96), CABG 0.86 (0.64-0.96), and HPRO all SSI 0.77 (0.57-89); the lowest sensitivity was Code CABG D/O 0.03 (0.00-0.21). The highest PPV values were generated by the algorithm: HPRO D/O 0.97 (0.77-0.99), CABG D/O 0.97 (0.76-0.99), and the Code HPRO D/O 0.9 (0.66-0.99). Both the algorithm and coding data resulted in a substantial reduction in the number of medical records required to review. The application of algorithms to enhance SSI surveillance demonstrates high accuracy in identifying patient records that require review by IPC teams to determine the presence of an SSI. Coding data alone should not be used to identify SSIs.

Crimean-Congo hemorrhagic fever virus prevalence in livestock of Jabalpur, Madhya Pradesh, Central India and its implications for public health

The rise of Crimean-Congo Hemorrhagic Fever (CCHF), poses a significant global health challenge, urging immediate action and continuous surveillance. With no available vaccines, monitoring pathogen presence is critical to identify at-risk areas promptly. A study was designed to assess the incidence of CCHF virus in goats and cattle using commercial ELISA IgG kits in tribal-dominated regions. Overall, 16% of the samples (n = 63/393) were positive for CCHF virus-specific IgG antibodies, whereas sero-prevalence detected in cattle 11.6% [95% CI:7–17.7] and in goats 18.9% [95% CI: 13.76–24.01], respectively. Statistically, Animal gender and age didn't significantly affect prevalence (p-value >0.05). Our finding indicates unnoticed CCHF virus circulation. Notably, lack of public awareness about zoonotic diseases in the study region was recorded. To combat this emerging tick-borne disease effectively, it's crucial to screen individuals with hemorrhagic manifestations in healthcare settings and active surveillance of ticks to prevent unwarranted public health outbreaks and design preventive interventions.