Venous blood collection systems using evacuated tubes: a systematic review focusing on safety, efficacy and economic implications of integrated vs. combined systems.

Venous blood collection systems (VBCSs) are combinations of in-vitro diagnostics and medical devices, usually available as integrated set. However, purchasing and using a combination of devices from different sets is considered by clinical laboratories as an option to achieve specific sampling tasks or reduce costs. This systematic review aimed to retrieve available evidence regarding safety, efficacy, and economic aspects of VBCSs, focusing on differences between integrated and combined systems. The literature review was carried out in PubMed. Cited documents and resources made available by scientific organisations were also screened. Extracted evidence was clustered according to Quality/Efficacy/Performance, Safety, and Costs/Procurement domains and discussed in the current European regulatory framework. Twenty documents published between 2010 and 2021 were included. There was no evidence to suggest equivalence between combined and integrated VBCSs in terms of safety and efficacy. Scientific society's consensus documents and product standards report that combined VBCS can impact operators' and patients' safety. Analytical performances and overall efficacy of combined VBCSs are not guaranteed without whole system validation and verification. EU regulatory framework clearly allocates responsibilities for the validation and verification of an integrated VBCS, but not for combined VBCSs, lacking information about the management of product nonconformities and post-market surveillance. Laboratory validation of combined VBCS demands risk-benefit and cost-benefit analyses, a non-negligible organisational and economic burden, and investment in knowledge acquisition. Implications in terms of laboratory responsibility and legal liability should be part of a comprehensive assessment of safety, efficacy, and cost carried out during device procurement.

[Effects of tetramethylpyrazine on pharmacokinetics in plasma and brain dialysate and neuropathic pain in rat model of spared sciatic nerve injury].

This study aims to explore the effects of tetramethylpyrazine(TMP) on pharmacokinetics in plasma and brain dialysate and neuropathic pain in the rat model of partial sciatic nerve injury(SNI), and to investigate the correlation between the analgesic effect of TMP and its concentrations in the plasma and brain dialysate. Male SD rats were randomized into Sham, SNI, and SNI+TMP groups. Mechanical stimulation with von frey filaments and cold spray method were employed to evaluate the mechanical sensitivity and cold sensitivity of rats. Another two groups, Sham+TMP and SNI+TMP, were used to intubate the common jugular vein and implant microdialysis probes into the anterior cingulate gyrus(ACC), respectively.After intraperitoneal injection of TMP at a dose of 80 mg·kg~(-1), automatic blood collection and intracerebral microdialysis(perfusion rate of 1 µL·min~(-1)) systems were used to collect the blood and brain dialysate for 24 h. HSS T3 C_(18) reversed-phase chromatographic column(2.1 mm×50 mm, 2.5 µm) was used for liquid chromatographic separation. Gradient elution was carried out with the mobile phase of methanol-water(containing 0.005% formic acid) at a flow rate of 0.25 mL·min~(-1). Electrospray ion source was used for mass spectrometry, and the scanning mode was multi-reaction monitoring under the positive ion mode. The ion pairs for quantitative analysis were TMP m/z 137/122 and aspirin m/z 179/137, respectively. DAS 2.11 was used to calculate the pharmacokinetic parameters. The optimal time of TMP to exert the analgesia effect and inhibit cold pain sensitivity was 60 min after treatment. The TMP in the plasma and brain dialysate of SNI rats showed the T_(max) of 15 min and 30 min, the C_(max) of(2 866.43±135.39) and(1 462.14±197.38) µg·L~(-1), the AUC_(0-t) of(241 463.30±28 070.31) and(213 115.62±32 570.07) µg·min·L~(-1), the MRT_(0-t) of(353.13±47.73) and(172.16±12.72) min, and the CL_Z of 0.73 and 0.36 L·min·kg~(-1), respectively. The analgesic effect of TMP had a significant correlation with the blood drug concentration in the ACC, which indicated that this method was suitable for the detection of TMP in rat plasma and brain dialysate. The method is accurate, reliable, and sensitive and can realize the important value of the application of correlation analysis theory of "automatic blood collection-microdialysis/PK-PD" in the research on neuropathic pain.

Developing a remote gamma-ray spectra collection system (RGSCS) by coupling a high purity Germanium (HPGe) detector with a cosmicguard background reduction device.

Despite being widely used for high-resolution spectral analysis and quantifying low activity in natural samples, the operations and data analysis of High Purity Germanium (HPGe) gamma-ray detectors are seldom fully automated due to the excessive costs associated with commercially available automatic sample changing systems. This paper introduces the design and implementation of a cost-effective, customized remote gamma-ray spectra collection system centered around the HPGe detector coupled to a cosmic-ray veto background reduction device. The HPGe detector system, equipped with a Lynx DSA, is seamlessly integrated with an economically viable automatic sample changer. This sample vial changer is controlled by a high-torque NEMA 34 stepper servo motor from Vention. Web control of the rotary actuator is facilitated through a CAD-based programming tool. The remote-controlled sample pick-and-place procedure is executed using a robotic arm (Trossen Robotics, Viper X 250). The DYNAMIXEL servomotors of the robotic arm are programmed using Python software supported by the Robotic Operating System. Beyond its technical construction, this system is uniquely fashioned for academic research, providing invaluable hands-on experience in gamma spectrometry to both junior researchers and students.

Using a multi-stakeholder co-design process to develop a health service organisation-wide patient reported outcome measure collection system.

PURPOSE: Limited examples exist of successful Patient Reported Outcome Measure (PROM) implementation across an entire healthcare organisation. The aim of this study was to use a multi-stakeholder co-design process to develop a PROM collection system, which will inform implementation of routine collection of PROMs across an entire healthcare organisation. METHODS: Co-design comprised semi-structured interviews with clinicians (n = 11) and workshops/surveys with consumers (n = 320). The interview guide with clinicians focused on their experience using PROMs, preferences for using PROMs, and facilitators/barriers to using PROMs. Co-design activities specific to consumers focused on: (1) how PROMs will be administered (mode), (2) when PROMs will be administered (timing), (3) who will assist with PROMs collection, and (4) how long a PROM will take to complete. Data were analysed using a manifest qualitative content analysis approach. RESULTS: Core elements identified during the co-design process included: PROMs collection should be consumer-led and administered by someone other than a clinician; collection at discharge from the healthcare organisation and at 3-6 months post discharge would be most suitable for supporting comprehensive assessment; PROMs should be administered using a variety of modes to accommodate the diversity of consumer preferences, with electronic as the default; and the time taken to complete PROMs should be no longer than 5-10 min. CONCLUSION: This study provides new information on the co-design of a healthcare organisation-wide PROM collection system. Implementing a clinician and patient informed strategy for PROMs collection, that meets their preferences across multiple domains, should address known barriers to routine collection.

The Design of a Circularly Polarized Antenna Array with Flat-Top Beam for an Electronic Toll Collection System.

Electronic toll collection (ETC), known as a non-stop toll collection system which can automatically realize payment by setting the identification antenna at the entrance, is always suffering from information exchange interruption caused by beam switching. A circularly polarized sector beam antenna array operating at 5.8 GHz with flat-top coverage is proposed, based on the weighted constrained method of the maximum power transmission efficiency (WCMMPTE). By setting the test receiving antennas at the specific angles of the ETC antenna array to be designed, constraints on the received power are introduced to control the radiation pattern and obtain the optimized distribution of excitations for antenna elements. A 1-to-16 feeding network, based on the microstrip transmission line theory is designed to feed a 4 × 4 antenna array. Simulation results show that the half-power beamwidth covers an angular range of -30° to 30° while the axial ratio is below 3dB, which meets the ETC requirements. Furthermore, the gain fluctuation among the needed range of -30° to 30° is lower than 0.7 dB, which is suitable for the ETC system to achieve a stable signal strength and uninterrupted communication.

Spatial-temporal clogging development in leachate collection systems of landfills: Insight into chemical and biological clogging characteristics.

The clogging of leachate collection systems (LCSs) is a typical challenge for landfills operation. Although clogging occurs in different LCS components, its spatial-temporal distributions remain unclear. This study aimed to systematically investigate the dynamic clogging development in simulated LCSs by monitoring changes in clogging characteristics over time. Results revealed that clogging accumulated in all components of the simulated LCS during a 215-day period, including chemical clogging and bio-clogging. Distinct spatial variations in clogging components were observed along the leachate flow of the simulated LCS, with the geotextile being severely clogged due to bio-clogging (70.1 ± 3.0%-80.0 ± 0.5%). Additionally, chemical clogging mainly occurred at the top (85.4 ± 0.8%-95.0 ± 0.9%) and middle (91.2 ± 0.8%-94.9 ± 1.1%) gravel layers. Nevertheless, the percentage of chemical clogging decreased from 72.0 ± 2.1% (day 42) to 42.5 ± 2.7% (day 215) at the bottom gravel layer. Chemical clogging was the main type in the pipe, accounting for 69.6 ± 0.5% (day 215). In addition, the ratios of bio-clogging to chemical clogging changed over time in all LCS components. The spatial-temporal characteristics of clogging across LCS components can enhance the understanding of clogging mechanisms, facilitate the design optimization of LCSs, and promote the formulation of effective control strategies.

Bacterial distinctions in practical rural sewage collection systems caused by the location, season, and system type.

Bacteria in rural sewage collection systems have the important influences on operation and maintenance risks, such as sedimentation blockage and harmful gas accumulation, and pollutant pre-treatment ability. It is necessary to analyze and interpret the influence on bacterial communities caused by the location (sewage, biofilms, and deposits), season (winter and spring, summer and autumn), and system type (sewers and ditches) to better understand the bacterial characteristics in rural sewage collection systems. To achieve the above purpose, 96 samples obtained from practical rural sewage collection systems in eight villages were analyzed by 16S rRNA whole region sequencing methods. The results indicate that locations and seasons caused significant influences on the overall bacterial communities, which were mainly affected by temperature, sewage quality and bacterial survival preference, and 13 genera of sulfate-reducing bacteria (SRB), 2 genera of ammonia-oxidizing bacteria (AOB), 2 genera of nitrite-oxidizing bacteria (NOB), and 9 genera of water-related pathogenic bacteria (WPB) were detected in rural sewage collection systems. SRB, AOB, NOB, and WPB tended to inhabit in biofilms or deposits rather than in sewage. The total relative abundance of SRB in summer and autumn (∼2.19%) was higher than in winter and spring (∼0.41%), and the WPB distribution in different seasons showed significant distinction. Additionally, some of SRB, AOB, NOB, and WPB also showed significant differences in sewers and ditches. Overall, this study provided a deeper understanding of bacteria in rural sewage collection systems and could further provide the basic parameter for the operation and maintenance risk control.

Reducing blood sample hemolysis in the emergency department using S-Monovette® in aspiration mode.

Background: Blood sample hemolysis continues to be a significant problem in clinical practice. In vitro hemolysis rates up to 77% have been reported in literature. The use of manual aspiration techniques for blood sampling has previously been shown to reduce the burden of erythrocyte injury in the pre-analytical phase compared to the vacuum collection technique. This study compares the hemolysis rates between two blood sampling methods: 5.0 ml BD Vacutainer® SST™ (BDV) and 4.9 ml S-Monovette® serum gel tubes in aspiration mode (SMA). Methods: This was a prospective randomised controlled study conducted in an Emergency department (ED). A convenience sample of 191 adult patients, aged 18-90 years old, presenting at the ED and requiring blood samples for serum electrolyte was included in the study. Paired blood samples were obtained through an intravenous cannula from each patient with randomised order of blood draw using SMA or BDV. Patient data was obtained and hemolysis index (HI), serum lactate dehydrogenase (LDH), and serum potassium (K) levels measured. Results: The adjusted mean HI (35.2 vs 21.5 mg/dL, p < 0.001), serum K (4.38 vs 4.16 mmol/L, p < 0.001) and LDH levels (259.6 vs 228.4 U/L, p < 0.001) were significantly higher in blood samples taken using BDV compared to SMA. The frequency of severely hemolyzed (>150 mg/dL) samples was also higher in blood collected using BDV (16.2%) compared to SMA (0%). Conclusions: The burden of hemolysis in blood samples taken from IV cannulae can be effectively reduced with the use of manual aspiration using the S-Monovette® blood collection system as compared to BD-Vacutainer.

Sanitary installations and wastewater plumbing as reservoir for the long-term circulation and transmission of carbapenemase producing Citrobacter freundii clones in a hospital setting.

BACKGROUND: Accumulating evidence shows a role of the hospital wastewater system in the spread of multidrug-resistant organisms, such as carbapenemase producing Enterobacterales (CPE). Several sequential outbreaks of CPE on the geriatric ward of the Ghent University hospital have led to an outbreak investigation. Focusing on OXA-48 producing Citrobacter freundii, the most prevalent species, we aimed to track clonal relatedness using whole genome sequencing (WGS). By exploring transmission routes we wanted to improve understanding and (re)introduce targeted preventive measures. METHODS: Environmental screening (toilet water, sink and shower drains) was performed between 2017 and 2021. A retrospective selection was made of 53 Citrobacter freundii screening isolates (30 patients and 23 environmental samples). DNA from frozen bacterial isolates was extracted and prepped for shotgun WGS. Core genome multilocus sequence typing was performed with an in-house developed scheme using 3,004 loci. RESULTS: The CPE positivity rate of environmental screening samples was 19.0% (73/385). Highest percentages were found in the shower drain samples (38.2%) and the toilet water samples (25.0%). Sink drain samples showed least CPE positivity (3.3%). The WGS data revealed long-term co-existence of three patient sample derived C. freundii clusters. The biggest cluster (ST22) connects 12 patients and 8 environmental isolates taken between 2018 and 2021 spread across the ward. In an overlapping period, another cluster (ST170) links eight patients and four toilet water isolates connected to the same room. The third C. freundii cluster (ST421) connects two patients hospitalised in the same room but over a period of one and a half year. Additional sampling in 2022 revealed clonal isolates linked to the two largest clusters (ST22, ST170) in the wastewater collection pipes connecting the rooms. CONCLUSIONS: Our findings suggest long-term circulation and transmission of carbapenemase producing C. freundii clones in hospital sanitary installations despite surveillance, daily cleaning and intermittent disinfection protocols. We propose a role for the wastewater drainage system in the spread within and between rooms and for the sanitary installations in the indirect transmission via bioaerosol plumes. To tackle this problem, a multidisciplinary approach is necessary including careful design and maintenance of the plumbing system.

Captadores de niebla y recolección de agua en un ecosistema de páramo colombiano

Los captadores de niebla son usados para interceptar agua contenida en la niebla y abastecer de agua a comunidades que habitan en lugares donde este recurso escasea. Se evaluó el uso de captadores de niebla para la captación de agua en un área ubicada en el páramo Pan de Azúcar, Duitama-Boyacá. Se instalaron 60 captadores de niebla, 24 de ellos, con dispositivos para medir los volúmenes de agua interceptados. Los volúmenes de agua captados, se midieron en periodos de 24 horas, por 26 días, durante un año y se usó el modelo geométrico para diferenciar el agua proveniente de la niebla. La precipitación registrada fue mayor a la reportada en la literatura. La precipitación mensual osciló entre 51 y 1198 mm y la temperatura media mensual entre los 6 y 8 °C. Los volúmenes de agua promedio colectados por los 24 captadores de niebla estuvieron entre los 0,02 Lm-2dia-1 hasta los 4,4Lm-2dia-1. Los aportes de agua provenientes de la niebla oscilaron entre los 0,02 y 1,77 mmdía-1. La dirección del viento no afectó la captación de agua y aún se presenta incertidumbre al separar el aporte real de agua proveniente de la niebla a partir de la lluvia orográfica, lo cual, sigue siendo un desafío en los ecosistemas de páramo, por lo que se debe ampliar la investigación, para mejorar los diseños y las eficiencias de los captadores de niebla.

Fog collectors are used to intercept water contained in fog and supply water to communities that live in places where this resource is scarce. We evaluated the use of mist collectors to collect water in an area located in the Pan de Azúcar paramo, Duitama-Boyacá. We installed 60 mist collectors, 24 of them with devices to measure the volumes of water intercepted. The volumes of water captured were measured in periods of 24 hours for 26 days during one year and we used the geometric model to differentiate the water from the fog. The recorded precipitation was higher than that reported in the literature. Monthly rainfall ranged between 51 and 1198mm and mean monthly temperature ranged between 6 and 8°C. The average volumes of water collected by the fog collectors were below 0.5Lm-2day-1 with a maximum of 4.4Lm-2day-1. The contributions of water from the mist ranged between 0.02 and 1.77 mmday-1. The direction of the wind did not affect the capture of water and there is still uncertainty when separating the real contribution of water from the fog from the orographic rain, which continues to be a challenge in the paramo ecosystems, for which it is necessary to expand research, to improve the designs and efficiencies of fog collectors.

Data collection systems for active safety surveillance of vaccines during pregnancy in low- and middle-income countries: developing and piloting an assessment tool (VPASS).

BACKGROUND: There is an urgent need for active safety surveillance to monitor vaccine exposure during pregnancy in low- and middle-income countries (LMICs). Existing maternal, newborn, and child health (MNCH) data collection systems could serve as platforms for post-marketing active surveillance of maternal immunization safety. To identify sites using existing systems, a thorough assessment should be conducted. Therefore, this study had the objectives to first develop an assessment tool and then to pilot this tool in sites using MNCH data collection systems through virtual informant interviews. METHODS: We conducted a rapid review of the literature to identify frameworks on population health or post-marketing drug surveillance. Four frameworks that met the eligibility criteria were identified and served to develop an assessment tool capable of evaluating sites that could support active monitoring of vaccine safety during pregnancy. We conducted semi-structured interviews in six geographical sites using MNCH data collection systems (DHIS2, INDEPTH, and GNMNHR) to pilot domains included in the assessment tool. RESULTS: We developed and piloted the "VPASS (Vaccines during Pregnancy - sites supporting Active Safety Surveillance) assessment tool" through interviews with nine stakeholders, including central-level systems key informants and site-level managers from DHIS2 and GNMNHR; DHIS2 in Kampala (Uganda) and Kigali (Rwanda); GNMNHR from Belagavi (India) and Lusaka (Zambia); and INDEPTH from Nanoro (Burkina Faso) and Manhica (Mozambique). The tool includes different domains such as the system's purpose, the scale of implementation, data capture and confidentiality, type of data collected, the capability of integration with other platforms, data management policies and data quality monitoring. Similarities among sites were found regarding some domains, such as data confidentiality, data management policies, and data quality monitoring. Four of the six sites met some domains to be eligible as potential sites for active surveillance of vaccinations during pregnancy, such as a routine collection of MNCH individual data and the capability of electronically integrating individual MNCH outcomes with information related to vaccine exposure during pregnancy. Those sites were: Rwanda (DHIS2), Manhica (IN-DEPTH), Lusaka (GNMNHR), and Belagavi (GNMNHR). CONCLUSION: This study's findings should inform the successful implementation of active safety surveillance of vaccines during pregnancy by identifying and using active individual MNCH data collection systems in LMICs.

Deep Learning-Based Driver's Hands on/off Prediction System Using In-Vehicle Data.

Driver's hands on/off detection is very important in current autonomous vehicles for safety. Several studies have been conducted to create a precise algorithm. Although many studies have proposed various approaches, they have some limitations, such as robustness and reliability. Therefore, we propose a deep learning model that utilizes in-vehicle data. We also established a data collection system, which collects in-vehicle data that are auto-labeled for efficient and reliable data acquisition. For a robust system, we devised a confidence logic that prevents outliers' sway. To evaluate our model in more detail, we suggested a new metric to explain the events, considering state transitions. In addition, we conducted an extensive experiment on the new drivers to demonstrate our model's generalization ability. We verified that the proposed system achieved a better performance than in previous studies, by resolving their drawbacks. Our model detected hands on/off transitions in 0.37 s on average, with an accuracy of 95.7%.

Spatiotemporal difference of leachate production and its impact on the development and dynamics of LCS clogging.

Due to the complexity of industrial solid waste, heavy metals and organics can be enriched in leachate. While leachate is difficult to handle, it can also cause clog of the leachate collection system (LCS), increasing the risk of leakage. Therefore, it is necessary to study the clogging process of LCS in industrial solid waste landfills (ISWLs). In this study, the prediction of the clogging process and hydraulic conductivity evolution of the LCS in ISWL were carried out through laboratory experiments and model simulations. The results show that the LCS of ISWLs in China faces severe clogging challenges. First, the rate of clogging is inversely proportional to the rate of leachate production. Then, it was found that the main influencing factor was infiltration conditions (precipitation and capping systems). Under accelerated infiltration conditions, the time for complete clogging of the leachate drainage pipes was shortened from the initial 26-735 years to 11-315 years. The time to complete LCS clogging was shortened from the initial 78-2205 years to 32-945 years. In addition, the acceleration of the clogging process was fully consistent with the increase in leachate production. In particular, when the net infiltration volume increases from 0 to 50 mm, the clogging process is significantly accelerated. After greater than 50 mm, the effect on the clogging process gradually decreases. This provides a reliable theoretical basis for accurately predicting the clogging process of LCS.

Integrating Geographic Information System network analysis and nighttime light satellite imagery to optimize landfill regionalization on a regional level.

More than half of financial resources allocated for municipal solid waste management are typically spent on waste collection and transportation. An optimized landfill siting and waste collection system can save fuel costs, reduce collection truck emissions, and provide higher accessibility with lower traffic impacts. In this study, a data-driven analytical framework is developed to optimize population coverage by landfills using network analysis and satellite imagery. Two scenarios, SC1 and SC2, with different truck travel times were used to simulate generation-site-disposal-site distances in three Canadian provinces. Under status quo conditions, Landfill Regionalization Index (LFRI) ranging from 0 to 2 population centers per landfill in all three jurisdictions. LFRI consistently improved after optimization, with average LFRI ranging from 1.3 to 2.0 population centers per landfill. Lower average truck travel times and better coverage of the population centers are generally observed in the optimized systems. The proposed analytical method is found effective in improving landfill regionalization. Under SC1 and SC2, LFRI percentages of improvement ranging from 58.3% to 64.5% and 22.7% to 59.4%, respectively. Separation distance between the generation and disposal sites and truck capacity appear not a decisive factor in the optimization process. The proposed optimization framework is generally applicable to regions with different geographical and demographical attributes, and is particularly applicable in rural regions with sparsely located population centers.

Design of automatic urine collection system for medical system applications.

BACKGROUND: The results of urine tests are often affected by improper midstream urine collection time, urine spilling, and urine pollution, all of which can lead to an increase in the test error. OBJECTIVE: To solve this problem, aiming at improving the toilet environment at the hospitals and public physical examination centers, this paper designs an automatic urine collection system. It can automatically adjust the position of the urine cup with an infrared remote controller, or manually, adjust the position of the urine cup in special situations according to the needs of the user. It also has an alarm function. METHODS: The overall size and shape are designed based on the squatting pan, suitable for disposable plastic urine cups of different shapes and sizes. It can realize the automatic collection of midstream urine, manual collection in exceptional cases, emergency stops, and rescue calls. RESULTS: Through the trial survey, there was a significant difference between the statistical results of using the device and not using the device (t= 13.937, P= 0.000). 96% of the subjects thought that the design of the system was reasonable, 22% thought that it was inconvenient to use, and 91.7% of the medical staff thought that the system met the sampling requirements. CONCLUSIONS: Therefore, the trial evaluation is satisfactory, and the proposed collection system is suitable for use in hospitals at all levels and public health examination centers with a large amount of inspection.

The first mile problem in the circular economy supply chains - Collecting recyclable textiles from consumers.

This paper presents the first mile problem of the circular economy supply chains: organizing the collection of used materials from individual consumers. Efficient solving of this problem is a prerequisite for recycling, as it ensures that adequate volumes of used materials, in this study end-of-life textiles, can be transformed into high-quality raw materials. Textile features affect the collection system design and make used textiles differ from other household waste fractions, such as glass or plastic. The aim is to investigate how to collect textile waste from consumers in a way that addresses the specific features of textiles, and the scarce resources of the collector organizations, but results in the largest collected yields to eventually drive up the recycling rates of used textiles. The study takes a supply chain view to reverse flows of textiles. Key experts from a sample of textile organizations were interviewed to understand their collection practices and possible future solutions, and a data analysis model was constructed to provide accurate prediction of end-of-life textile volumes. This study proposes how the first mile problem of end-of-life textiles, the collection from households, can be modelled in a situation where no historical volume data is available. The practical contribution lies in the urgent need for textile collection solutions, as municipal actors and waste companies in Europe are searching for efficient solutions to respond to the requirement of separate used textile collection by 2025. The study demonstrates how a circular economy problem with multiple unknows and uncertainties can be modelled quantitatively.

Comparison of high-frequency in-pipe SARS-CoV-2 wastewater-based surveillance to concurrent COVID-19 random clinical testing on a public U.S. university campus.

Wastewater-based epidemiology (WBE) is utilized globally as a tool for quantifying the amount of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within communities, yet the efficacy of community-level wastewater monitoring has yet to be directly compared to random Coronavirus Disease of 2019 (COVID-19) clinical testing; the best-supported method of virus surveillance within a single population. This study evaluated the relationship between SARS-CoV-2 RNA in raw wastewater and random COVID-19 clinical testing on a large university campus in the Southwestern United States during the Fall 2020 semester. Daily composites of wastewater (24-hour samples) were collected three times per week at two campus locations from 16 August 2020 to 1 January 2021 (n = 95) and analyzed by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) targeting the SARS-CoV-2 E gene. Campus populations were estimated using campus resident information and anonymized, unique user Wi-Fi connections. Resultant trends of SARS-CoV-2 RNA levels in wastewater were consistent with local and nationwide pandemic trends showing peaks in infections at the start of the Fall semester in mid-August 2020 and mid-to-late December 2020. A strong positive correlation (r = 0.71 (p < 0.01); n = 15) was identified between random COVID-19 clinical testing and WBE surveillance methods, suggesting that wastewater surveillance has a predictive power similar to that of random clinical testing. Additionally, a comparative cost analysis between wastewater and clinical methods conducted here show that WBE was more cost effective, providing data at 1.7% of the total cost of clinical testing ($6042 versus $338,000, respectively). We conclude that wastewater monitoring of SARS-CoV-2 performed in tandem with random clinical testing can strengthen campus health surveillance, and its economic advantages are maximized when performed routinely as a primary surveillance method, with random clinical testing reserved for an active outbreak situation.

Detecting colon polyps in endoscopic images using artificial intelligence constructed with automated collection of annotated images from an endoscopy reporting system.

BACKGROUND: Artificial intelligence (AI) has made considerable progress in image recognition, especially in the analysis of endoscopic images. The availability of large-scale annotated datasets has contributed to the recent progress in this field. Datasets of high-quality annotated endoscopic images are widely available, particularly in Japan. A system for collecting annotated data reported daily could aid in accumulating a significant number of high-quality annotated datasets. AIM: We assessed the validity of using daily annotated endoscopic images in a constructed reporting system for a prototype AI model for polyp detection. METHODS: We constructed an automated collection system for daily annotated datasets from an endoscopy reporting system. The key images were selected and annotated for each case only during daily practice, not to be performed retrospectively. We automatically extracted annotated endoscopic images of diminutive colon polyps that had been diagnosed (study period March-September 2018) using the keywords of diagnostic information, and additionally collect the normal colon images. The collected dataset was devised into training and validation to build and evaluate the AI system. The detection model was developed using a deep learning algorithm, RetinaNet. RESULTS: The automated system collected endoscopic images (47,391) from colonoscopies (745), and extracted key colon polyp images (1356) with localized annotations. The sensitivity, specificity, and accuracy of our AI model were 97.0%, 97.7%, and 97.3% (n = 300), respectively. CONCLUSION: The automated system enabled the development of a high-performance colon polyp detector using images in endoscopy reporting system without the efforts of retrospective annotation works.

Identification of sampling points for the detection of SARS-CoV-2 in the sewage system.

A suitable tool for monitoring the spread of SARS-CoV-2 is to identify potential sampling points in the wastewater collection system that can be used to monitor the distribution of COVID-19 disease affected clusters within a city. The applicability of the developed methodology is presented through the description of the 72,837 population equivalent wastewater collection system of the city of Nagykanizsa, Hungary and the results of the analytical and epidemiological measurements of the wastewater samples. The wastewater sampling was conducted during the 3rd wave of the COVID-19 epidemic. It was found that the overlap between the road system and the wastewater network is high, it is 82 %. It was showed that the proposed methodological approach, using the tools of network science, determines confidently the zones of the wastewater collection system and provides the ideal monitoring points in order to provide the best sampling resolution in urban areas. The strength of the presented approach is that it estimates the network based on publicly available information. It was concluded that the number of zones or sampling points can be chosen based on relevant epidemiological intervention and mitigation strategies. The algorithm allows for continuous effective monitoring of the population infected by SARS-CoV-2 in small-sized cities.

SARS-CoV-2 concentrations in a wastewater collection system indicated potential COVID-19 hotspots at the zip code level.

Wastewater based epidemiology (WBE) has been successfully applied for SARS-CoV-2 surveillance at the city and building levels. However, sampling at the city level does not provide sufficient spatial granularity to identify COVID-19 hotspots, while data from building-level sampling are too narrow in scope for broader public health application. The objective of this study was to examine the feasibility of using wastewater from wastewater collection systems (WCSs) to monitor COVID-19 hotspots at the zip code level. In this study, 24-h composite wastewater samples were collected from five manholes and two wastewater treatment plants (WWTPs) in the City of Lincoln, Nebraska. By comparing to the reported weekly COVID-19 case numbers, we identified different hotspots responsible for two COVID-19 surges during the study period. One zip code was the only sampling locations that was consistently tested positive during the first COVID-19 surge. In comparison, nearly all the zip codes tested exhibited virus concentration increases that overlapped with the second COVID-19 surge, suggesting broader spread of the virus at that time. These findings demonstrate the feasibility of using WBE to monitor COVID-19 at the zip code level. Highly localized disease surveillance methods can improve public health prevention and mitigation measures at the community level.