Near Real-time Monitoring Research Articles

Automated Targeted Sampling of Waterborne Pathogens and Microbial Source Tracking Markers Using Near-Real Time Monitoring of Microbiological Water Quality

Waterborne pathogens are heterogeneously distributed across various spatiotemporal scales in water resources, and representative sampling is therefore crucial for accurate risk assessment. Since regulatory monitoring of microbiological water quality is usually conducted at fixed time intervals, it can miss short-term fecal contamination episodes and underestimate underlying microbial risks. In the present paper, we developed a new automated sampling methodology based on near real-time measurement of a biochemical indicator of fecal pollution. Online monitoring of β-D-glucuronidase (GLUC) activity was used to trigger an automated sampler during fecal contamination events in a drinking water supply and at an urban beach. Significant increases in protozoan parasites, microbial source tracking markers and E. coli were measured during short-term (<24 h) fecal pollution episodes, emphasizing the intermittent nature of their occurrence in water. Synchronous triggering of the automated sampler with online GLUC activity measurements further revealed a tight association between the biochemical indicator and culturable E. coli. The proposed event sampling methodology is versatile and in addition to the two triggering modes validated here, others can be designed based on specific needs and local settings. In support to regulatory monitoring schemes, it should ultimately help gathering crucial data on waterborne pathogens more efficiently during episodic fecal pollution events.

Monitoring cyanoHABs and water quality in Laguna Lake (Philippines) with Sentinel-2 satellites during the 2020 Pacific typhoon season

Laguna Lake, the largest freshwater lake in the Philippines, is permanently subject to nutrient-driven eutrophication and pollution and experiences harmful algal blooms (cyanoHABs) periodically with serious socio-economic implications. The aim of this study is to evaluate the suitability of the Sentinel-2 imagery of the European Commission's Copernicus Earth Observation programme for lake monitoring during the 2020 Pacific typhoon season (September–November 2020). The Case-2 Regional CoastColour processor is used to atmospherically correct Level 1 data and generate water quality parameters, such as chlorophyll-a (Chl-a) and total suspended matter (TSM) at 10 m. Results show that Super Typhoon Goni and Typhoon Vamco delivered high suspended sediment loads to the reservoir at concentrations above 170 g/m3 compared to pre-storm situations (0–35 g/m3). The typhoons also affect Chl-a, with a mean concentration of 10 mg/m3 and 30 mg/m3 for pre- and post-typhoons, respectively. In addition, the normalized difference chlorophyll index (NDCI) is used in the Google Earth Engine platform for near-real time monitoring of cyanoHABs at 20 m spatial resolution. Satellite maps are key for detecting the distribution of the blooms due to the patchiness of the green algae species, which usually form scum and elongated slicks in the lake. Maximum records of bloom detection during the study period occur in the Central Bay, one of the lake sections with major aquaculture and fisheries activities. The Sentinel-2 mission improves synoptic mapping of cyanoHABs and enables trends in their extent and severity to be documented. These available methods provide an essential tool for rapid detection after extreme events and for regular water quality monitoring, which will assist and benefit the cost-effective management of Laguna Lake.

Evaluation of Covid-19 vaccines: Pharmacoepidemiological aspects

The marketing authorization granted to SARS-Cov-2 vaccines was accompanied by reinforced safety monitoring plans. These plans’ implementation was part of the usual logic of post-marketing surveillance of new and innovative health products. It was especially adapted to the context of post-marketing monitoring of drugs developed according to the usual scientific quality standards but in an accelerated schedule. In Europe, the reinforced surveillance system relies on the complementary strengths of pharmacovigilance and pharmacoepidemiology. If the performances of pharmacovigilance monitoring are incomparable for the detection of safety signals relating to rare events of atypical presentation, it needs to be completed with pharmacoepidemiology activities for more common events, either multifactorial or frequently classified as idiopathic. The pharmacoepidemiological monitoring developed in Europe was elaborated before the first SARS-Cov-2 vaccines where marketed, taking into account the lessons learned from the vaccination campaign against 2009 A (H1N1) influenza. It includes numerous academic studies as well as studies performed within vaccines risk management plans. In terms of safety, those defined a priori mostly concerns a list of pre-established health events of specific interest. Aside of these planned activities, ad-hoc studies will be latter developed on purpose to investigate safety signals or potential signals that could be identified as the result of pharmacovigilance activities. Aside of these regulated activities, as for today, very few studies have been published regarding SARS-Cov-2 vaccines; most of the existing consist in preprints that should be considered with caution. Pharmacoepidemiology of vaccines is thought to allow near-real time monitoring that needs sufficient time to provide with valid results. In the constant urge for information that accompanies COVID-related science, it is important not to make haste the enemy of speed and to let pharmacoepidemiology provides with what it is expected to do: rock-solid scientific information contributing to evidence-based decision-making.

Magmatic Processes at La Soufrière de Guadeloupe: Insights From Crystal Studies and Diffusion Timescales for Eruption Onset

Signals of volcanic unrest do not usually provide insights into the timing, size and style of future eruptions, but detailed analysis of past eruptions may uncover patterns that can be used to understand future eruptive behavior. Here, we examine basaltic-andesitic to andesitic eruption deposits from La Soufrière de Guadeloupe, covering a range of eruption styles, ages and magnitudes. Our work is timely given unrest at La Soufrière de Guadeloupe has increased over the last 25 years. We constrain the timescales of magmatic processes preceding four eruptions: 1657 Cal. CE (Vulcanian), 1010 Cal. CE (Plinian), ∼341 Cal. CE (Strombolian) and 5680 Cal. BCE (La Soufrière de Guadeloupe’s first known Plinian eruption). Using crystal-specific analyses of diffusion in orthopyroxenes, we calculate the timescale occurring between the last recharge/mixing event in the magma reservoir and the eruption. We use backscattered electron images, coupled with EMPA of the outermost crystal rim, to derive magmatic timescales. We model the timescale populations as random processes whose probability distributions provide expected (“mean”) timescales and the associated standard errors for each eruption. This provides a new statistical method for comparing magmatic timescales between disparate eruptions. From this, we obtain timescales of magma storage at La Soufriére de Guadeloupe ranging from 18.8 ± 0.37 days to 361 ± 0.40 days, with no clear distinction between eruption style/size and timescales observed. Based on these data, magmatic interaction timescales are a poor predictor of eruption style/size. This study shows that magmatic processes prior to eruption can occur on relatively short timescales at La Soufrière de Guadeloupe. Further to this basaltic-andesitic to andesitic volcanoes can rapidly produce large-scale eruptions on short timescales. These relatively short timescales calculated for volcanic processes at this system constitute a critical new data set and warrant an urgency in enhancing modeling and interpretation capabilities for near-real time monitoring data. These integrated efforts will improve early warning, eruption forecasting and crisis response management for different scenarios, as well as planning for long-term risk reduction.

Assessing the utility of using current generation high-resolution satellites (Sentinel 2 and Landsat 8) to monitor large water supply dam in South Africa

The Vaal Dam is one of the largest impounded water resources in South Africa with a capacity of 2330 × 106 m3 and surface area of 321.07 km2. The Dam is part of the Vaal river system with a catchment area of about 37 100 km2 and is designed to supply water to the large metropolitan city of Johannesburg in the north and the surrounding areas in the Gauteng Province serving approximately 13 million people. The Dam is biologically productive and experiences frequent algal blooms especially during summer months (February to April). Recent studies have indicated the presence of toxic cyanobacteria genera such as Anabaena, Lyngbya, and Microcystis and these can be of great concern for ecosystem health as well as biodiversity. Currently, ground-based methods are employed to assess and monitor the water quality of the Dam. This method is costly and lacks the temporal and spatial resolution. Therefore, a more efficient observation tools are required for effective monitoring. Satellite remote sensing is an efficient tool that can allow accurate and timely detection of harmful algal blooms (HABs) such as the toxic cyanobacteria genera and other algal types. This study focuses on assessing the utility of using current generation Satellites (Sentinel 2 and Landsat 8) to characterize the water quality and estimate concentrations of chlorophyll a as a proxy for HABs and the total suspended matter (TSM). The optimal correlation between in-situ and chlorophyll a retrieved from blue-green band ratio of Landsat 8 [Rrs (560)/Rrs (443)], and red/NIR of Sentinel 2 [Rrs (705)/Rrs (665)] were found to be the best indices for Chl-a retrieval in the Vaal Dam. Results for Landsat OLI dataset (R2 = 0.89; RMSE = 0.36 μg/L, P < 0.05) and Sentinel MSI dataset (R2 = 0.75; RMSE = 0.48 μg/L, P < 0.05) show high degree of accuracy. Models developed in this study will significantly improve near-real time and long-term water quality monitoring of the Vaal Dam and will effectively help to address public health issues related to water quality.

City-EYE a platform for the surveillance and management of built-up area and infrastructures

Abstract Cities and built-up areas are the main environment of human civilization in the 21st century. The quick development of Space industry and processing capabilities allow near-real time monitoring of large target areas in cities. A proof-of-concept of a platform for the surveillance and management of built-up area and infrastructures (City-EYE) has been developed by Detektia and Insar.sk space companies, supported by scientific validation. The potential of City.EYE lies in the two-level analysis of entire cities and in the integration of different datasets from various SAR sensors and data dating from 1992 to present. The processed PSI data is input to the platform, together with relevant monitoring data (climate, urban development…). A two-scale approach allows monitoring the city and built up areas as a whole while simultaneously monitoring in detail critical infrastructures and buildings. City-EYE is part of a new generation of management platforms that integrate Space data in daily operations.

Improvement of Ficin-Based Inhibitive Enzyme Assay for Toxic Metals Using Response Surface Methodology and Its Application for Near Real-Time Monitoring of Mercury in Marine Waters.

Potentially toxic metals pollution in the Straits of Malacca warrants the development of rapid, simple and sensitive assays. Enzyme-based assays are excellent preliminary screening tools with near real-time potential. The heavy-metal assay based on the protease ficin was optimized for mercury detection using response surface methodology. The inhibitive assay is based on ficin action on the substrate casein and residual casein is determined using the Coomassie dye-binding assay. Toxic metals strongly inhibit this hydrolysis. A central composite design (CCD) was utilized to optimize the detection of toxic metals. The results show a marked improvement for the concentration causing 50% inhibition (IC50) for mercury, silver and copper. Compared to one-factor-at-a-time (OFAT) optimization, RSM gave an improvement of IC50 (mg/L) from 0.060 (95% CI, 0.030–0.080) to 0.017 (95% CI, 0.016–0.019), from 0.098 (95% CI, 0.077–0.127) to 0.028 (95% CI, 0.022–0.037) and from 0.040 (95% CI, 0.035–0.045) to 0.023 (95% CI, 0.020–0.027), for mercury, silver and copper, respectively. A near-real time monitoring of mercury concentration in the Straits of Malacca at one location in Port Klang was carried out over a 4 h interval for a total of 24 h and validated by instrumental analysis, with the result revealing an absence of mercury pollution in the sampling site.

Can VIIRS continue the legacy of MODIS for near real-time monitoring of tropical forest disturbance?

Near real-time monitoring of forest disturbance is a critical tool for combating illegal logging. The only feasible data sources for near real-time monitoring over large area are remote sensing data, and historically the only sensors with repeat times sufficient for near-real time monitoring are from coarse-resolution sensors such as MODIS. The MODIS sensors onboard the Terra and Aqua satellites have provided near daily global observations in the red and NIR spectral bands at 250 m resolution since 1999. While their longevity is impressive, the sensors are nearing the end of their lifespan and the MODIS data record will be continued by the VIIRS sensor onboard Suomi NPP. But because of the spatial and spectral differences between MODIS and VIIRS, it is worth investigating whether VIIRS can replace MODIS as input data for near real-time monitoring. In this article, we compared the performance of the NRT-CCDC (Near Real-Time Continuous Change Detection and Classification) algorithm using the Terra/ and Aqua/MODIS composites at 250 m resolution, Terra/MODIS 250 m and 500 m surface reflectance, Aqua/MODIS 250 m and 500 m surface reflectance, and VIIRS 500 m surface reflectance. We found that the algorithm using composites from both MODIS sensors and Terra/MODIS data at 250 m resolution outperformed the results obtained when using VIIRS data. The results were similar when using 500 m data from Terra/MODIS alone compared to VIIRS data. We found that a morning overpass, like that of Terra, is preferable to an afternoon overpass, which is employed by VIIRS and Aqua. Spatial and temporal resolution of the input data are two key factors in successful near real-time monitoring of forest disturbance.

First Optical Seismometer at the Top of La Soufrière Volcano, Guadeloupe

Abstract Accurate monitoring of volcanic activity demands expertise in fields including geophysics, geology, and geochemistry. Data obtained from the most recent technical advances are particularly vital in pre-eruptive phases. In particular, seismic monitoring in near real time is essential to locating and discriminating early signs among different sources of seismic waves, especially those related to movement and overpressure in underground fluids. Among the major indicators of volcanic restlessness are fumaroles, or gas and steam vents, often located near a volcanic summit. Their activity could be monitored by seismometers in their vicinity, but today’s standard instruments cannot last very long when exposed to the high temperatures and the billowing, sulfurous, acidic gases near a fumarole. Conventional gear may also not be accessible for emergency deployment, or repair, even in pre-eruptive phases. La Soufrière de Guadeloupe Volcano in the Caribbean typifies such challenges. Its last significant event was a phreatic (gas and steam) eruption in 1976 that prompted evacuation of the archipelago’s nearby capital. Since early 2018, the 1467-meter-high stratovolcano has shown signs of increased activity. To provide a hardy, high-resolution monitoring system, we installed a recently developed type of seismometer just 10 m from a vigorous summit fumarole. The sensor is a purely opto-mechanical geophone that is interrogated through a 1.5 km fiber-optic cable by a remote, and thus it is a much safer optic-electronic system down the volcano’s flank. The ESEO Group and the Institut de Physique du Globe de Paris (IPGP) started development of this novel seismometer in 2008. The 2019 Guadeloupe installation is part of the HIgh PERformance SeISmometer (HIPERSIS) project (French Agence Nationale de la Recherche [ANR]). It is, to our knowledge, the first high-resolution optical seismometer ever installed on an active volcano or other active, hazardous zone. We report here the details of this installation, the means we are using for measurements, and our implementation strategy, and we share some of the first results. Such an optical seismometer, as well as a variety of other geophysical sensors built on the same principle, can be installed in a wide variety of sites with fibers up to 50 km long.

NEMO - The NEar real-time MOnitoring system – Harvesting information online for a fireball monitoring and alert system

In the course of the NEar real-time MOnitoring (NEMO) project an information system for bright fireballs on a global scale has been developed. It analyses and combines as much available data as possible from different sources to monitor fireball events, from witness reports via meteor networks to infrasound data.One of near real-time monitoring system's main goals is to deliver information about events in near real-time. For this purpose, the project is supplemented by an alert system. This system is based on Social Media, predominantly on Twitter. Its detection procedure and working principle are presented in this study.

Tracking Evaporation During Levitation Processing of Nickel-Based Superalloys on the ISS

Conducting experiments in an inert shielding-gas environment limits the likelihood for experiencing significant mass loss or compositional shifts due to differential relative evaporation. Species-specific evaporation is proven to be below prescribed limits and near-real time monitoring of the potential for exposure is shown to be an effective tool to ensure astronaut safety. The activity coefficients for key constituents in the alloy are defined as a function of temperature for inclusion in next-generation toxicity tracking software.

An Adaptive and Extensible System for Satellite-Based, Large Scale Burnt Area Monitoring in Near-Real Time

In the case of ongoing wildfire events, timely information on current fire parameters is crucial for informed decision making. Satellite imagery can provide valuable information in this regard, since thermal sensors can detect the exact location and intensity of an active fire at the moment the satellite passes over. This information can be derived and distributed in near-real time, allowing for a picture of current fire activity. However, the derivation of the size and shape of an already affected area is more complex and therefore most often not available within a short time frame. For urgent decision making though, it would be desirable to have this information available in near-real time, and on a large scale. The approach presented here works fully automatic and provides perimeters of burnt areas within two hours after the satellite scene acquisition. It uses the red and near-infrared bands of mid-resolution imagery to facilitate continental-scale monitoring of recently occurred burnt areas. To allow for a high detection capacity independent of the affected vegetation type, segmentation thresholds are derived dynamically from contextual information. This is done by using a Morphological Active Contour approach for perimeter determination. The results are validated against semi-automatically derived burnt areas for five wildfire incidents in Europe. Furthermore, these results are compared with three widely used burnt area datasets on a country-wide scale. It is shown that a high detection quality can be reached in near real-time. The large-scale inter-comparison shows that the results coincide with 63% to 76% of the burnt area in the reference datasets. While these established datasets are only available with a time lag of several months or are created by using manual interaction, the presented approach produces results in near-real time fully automatically. This work is therefore supposed to represent a valuable improvement in wildfire related rapid damage assessment.

Introducing the UCDP Candidate Events Dataset

This article presents a new, monthly updated dataset on organized violence—the Uppsala Conflict Data Program Candidate Events Dataset. It contains recent observations of candidate events, a majority of which are eventually included in the Uppsala Conflict Data Program Georeferenced Event Dataset as part of its annual update after a careful vetting process. We describe the definitions, sources and procedures employed to code the candidate events, and a set of issues that emerge when coding data on organized violence in near-real time. Together, the Uppsala Conflict Data Program Candidate and Georeferenced Event Datasets minimize an inherent trade-off between update speed and quality control. Having monthly updated conflict data is advantageous for users needing near-real time monitoring of violent situations and aiming to anticipate future developments. To demonstrate this, we show that including them in a conflict forecasting system yields distinct improvements in terms of predictive performance: Average precision increases by 20–40% relative to using the Uppsala Conflict Data Program Georeferenced Event Dataset only. We also show that to ensure quality and consistency, revisiting the initial coding making use of sources that become available later is absolutely necessary.

Near Real-Time Automated Early Mapping of the Perimeter of Large Forest Fires from the Aggregation of VIIRS and MODIS Active Fires in Mexico

In contrast with current operational products of burned area, which are generally available one month after the fire, active fires are readily available, with potential application for early evaluation of approximate fire perimeters to support fire management decision making in near real time. While previous coarse-scale studies have focused on relating the number of active fires to a burned area, some local-scale studies have proposed the spatial aggregation of active fires to directly obtain early estimate perimeters from active fires. Nevertheless, further analysis of this latter technique, including the definition of aggregation distance and large-scale testing, is still required. There is a need for studies that evaluate the potential of active fire aggregation for rapid initial fire perimeter delineation, particularly taking advantage of the improved spatial resolution of the Visible Infrared Imaging Radiometer (VIIRS) 375 m, over large areas and long periods of study. The current study tested the use of convex hull algorithms for deriving coarse-scale perimeters from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) active fire detections, compared against the mapped perimeter of the MODIS collection 6 (MCD64A1) burned area. We analyzed the effect of aggregation distance (750, 1000, 1125 and 1500 m) on the relationships of active fire perimeters with MCD64A1, for both individual fire perimeter prediction and total burned area estimation, for the period 2012–2108 in Mexico. The aggregation of active fire detections from MODIS and VIIRS demonstrated a potential to offer coarse-scale early estimates of the perimeters of large fires, which can be available to support fire monitoring and management in near real time. Total burned area predicted from aggregated active fires followed the same temporal behavior as the standard MCD64A1 burned area, with potential to also account for the role of smaller fires detected by the thermal anomalies. The proposed methodology, based on easily available algorithms of point aggregation, is susceptible to be utilized both for near real-time and historical fire perimeter evaluation elsewhere. Future studies might test active fires aggregation between regions or biomes with contrasting fuel characteristics and human activity patterns against medium resolution (e.g., Landsat and Sentinel) fire perimeters. Furthermore, coarse-scale active fire perimeters might be utilized to locate areas where such higher-resolution imagery can be downloaded to improve the evaluation of fire extent and impact.

Application of Landsat 8 OLI for monitoring the coastal waters of the US Virgin Islands

ABSTRACT Previous studies in the US Virgin Islands (USVI) have shown that land-based sources of pollution associated with watershed development coupled with climate is causing coral reef degradation. A good indicator that can be used to assess stress on these environments is the water quality. Conventional assessment methods based on in-situ measurements are timely and costly. Satellite remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic nature of Water Quality Parameters (WQPs, chlorophyll-a), total suspended sediments (TSM), and coloured-dissolved organic matter). However, the interference of multiple optically active WQPs that characterize the water column as well as reflectance from the bottom substrates poses a challenge especially in shallow coastal environments such as the USVI. The optical properties of USVI waters are a function of multiple WQPs with chlorophyll-a values ranging from 0.10 to 2.35 μg L−1 and TSM values from 8.97 to 15.7 mg L−1. In this study, field data were combined with NASA’s Landsat Operational Land Imager (OLI) sensor data to specifically model chlorophyll-a variability in the USVI waters based on spectral indices approach. Landsat OLI spectral-based model produced promising results for characterizing the variability of chlorophyll-a in the USVI (coefficient of determination (R 2) = 0.70; root-mean-square error (RMSE) = 0.042 μg L−1). Model developed in this study will significantly improve near-real time and long-term water quality monitoring in USVI and this will potentially help to provide insight to factors contributing to coral reef decline.

ADVANCE: Towards near real-time monitoring of vaccination coverage, benefits and risks using European electronic health record databases

BackgroundThe Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private partnership aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines using European electronic health record (eHR) databases. This proof-of-concept study aimed to test the feasibility of near real-time (NRT) monitoring of vaccination coverage, benefits and risks based on multiple European eHR databases, using acellular pertussis vaccination in children aged <6 years as test case. MethodsA qualitative feasibility assessment on NRT monitoring was carried out using a survey and face-to-face discussion with ADVANCE data partners. Subsequently, a dynamic cohort study was conducted containing two distinct observation periods: a first period to establish a baseline (Jan 2014 to Mar 2018) and a subsequent 3-month period to test the actual feasibility of weekly NRT monitoring, based on which data latencies were calculated. An interactive web-application was additionally developed to facilitate the visual monitoring of vaccination coverage, the vaccine preventable disease incidence rates (benefits) and the incidence rates of adverse events (risks). ResultsNine databases from four countries (Denmark, Italy, Spain and UK) participated in the qualitative feasibility assessment. Of them, five databases took part in the dynamic cohort study, with 5 databases providing baseline data and 3 databases participating to the NRT monitoring, providing data extractions on an almost weekly basis. The median data latency (time between event date and data release date) was between 1 and 2 weeks except for the benefit and risk events in one of the databases (latency 16 weeks). ConclusionThree European eHR databases successfully demonstrated the feasibility of providing data for weekly NRT monitoring, with short data latencies of 1–2 weeks for most events.

ADVANCE system testing: Benefit-risk analysis of a marketed vaccine using multi-criteria decision analysis and individual-level state transition modelling

BackgroundThe Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private collaboration aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines using electronic health record (eHR) databases in Europe. Proof-of-concept studies were designed to assess the proposed processes and system for generating the required evidence to perform B/R assessment and near-real time monitoring of vaccines. We aimed to test B/R methodologies for vaccines, using the comparison of the B/R profiles of whole-cell (wP) and acellular pertussis (aP) vaccine formulations in children as an example. MethodsWe used multi-criteria decision analysis (MCDA) to structure the B/R assessment combined with individual-level state transition modelling to build the B/R effects table. In the state transition model, we simulated the number of events in two hypothetical cohorts of 1 million children followed from first pertussis dose till pre-school-entry booster (or six years of age, whichever occurred first), with one cohort receiving wP, and the other aP. The benefits were reductions in pertussis incidence and complications. The risks were increased incidences of febrile convulsions, fever, hypotonic-hyporesponsive episodes, injection-site reactions and persistent crying. Most model parameters were informed by estimates (coverage, background incidences, relative risks) from eHR databases from Denmark (SSI), Spain (BIFAP and SIDIAP), Italy (Pedianet) and the UK (RCGP-RSC and THIN). Preferences were elicited from clinical and epidemiological experts. ResultsUsing state transition modelling to build the B/R effects table facilitated the comparison of different vaccine effects (e.g. immediate vaccine risks vs long-term vaccine benefits). Estimates from eHR databases could be used to inform the simulation model. The model results could be easily combined with preference weights to obtain B/R scores. ConclusionExisting B/R methodology, modelling and estimates from eHR databases can be successfully used for B/R assessment of vaccines.

Near-Real Time Monitoring of Vaccine Uptake of Pregnant Women in a Primary Care Sentinel Network: Ontological Case Definition Across Heterogeneous Data Sources.

Vaccination against influenza is important in pregnancy for the health of both mother and unborn baby. Influenza introduces risks to pregnancy and to the baby who relies on maternal antibodies for protection. Because the data associated with pregnancy is fragmented across multiple providers of health care, it is challenging to conduct pregnancy-related public health surveillance using a single data source. We report the integration of a novel ontological approach to identifying pregnancies in routine data with a web-based dashboard that feeds back information to general practices in a sentinel network. As a result, practices receive information about how well they are performing influenza vaccination in pregnancy in near-real-time.

Flood Mapping Based on Synthetic Aperture Radar: An Assessment of Established Approaches

In our changing world, floods are a threat of increasing concern. Within this context, flood mapping is important for both damage assessment and forecast improvement. Due to the suitability of synthetic aperture radar (SAR) for flood mapping, a broad range of SAR-based flood mapping algorithms has been developed during the past years. However, most of these algorithms were presented based on a single test case only and comparisons between methods are rare. This paper presents an in-depth assessment and comparison of the established pixel-based flood mapping approaches, including global and enhanced thresholding, active contour modeling and change detection. The methods were tested on medium-resolution SAR images of different flood events and lakes across the U.K. and Ireland and were evaluated on both accuracy and robustness. Results indicate that the most suited method depends on the area of interest and its characteristics as well as the intended use of the observation product. Due to its high robustness and good performance, tiled thresholding is suited for automated, near-real time flood detection and monitoring. Active contour models can provide higher accuracies but require long computation times that strongly increase with increasing image sizes, making them more appropriate for accurate flood mapping in smaller areas of interest.

Autonomous online measurement of β-D-glucuronidase activity in surface water: is it suitable for rapid E. coli monitoring?

Microbiological water quality is traditionally assessed using culture-based enumeration of faecal indicator bacteria such as Escherichia coli. Despite their relative ease of use, these methods require a minimal 18-24 h-incubation step before the results are obtained. This study aimed to assess the suitability of an autonomous online fluorescence-based technology measuring β-glucuronidase (GLUC) activity for rapid near-real time monitoring of E. coli in water. The analytical precision was determined and compared to an automated microbial detection system, two culture-based assays and quantitative real-time PCR (qPCR). Using replicate measurements of grab samples containing E. coli concentrations between 50 and 2330 CFU.100 mL−1, the autonomous GLUC activity measurement technology displayed an average coefficient of variation (CV) of less than 5% that was 4–8-fold lower than other methods tested. Comparable precision was observed during online in situ monitoring of GLUC activity at a drinking water intake using three independent instruments. GLUC activity measurements were not affected by sewage or sediments at concentrations likely to be encountered during long-term monitoring. Furthermore, significant (p < 0.05) correlations were obtained between GLUC activity and the other assays including defined substrate technology (r = 0.77), membrane filtration (r = 0.73), qPCR (r = 0.55) and the automated microbial detection system (r = 0.50). This study is the first to thoroughly compare the analytical performance of rapid automated detection technologies to established culture and molecular-based methods. Results show that further research is required to correlate GLUC activity to the presence of viable E. coli as measured in terms of CFU.100 mL−1. This would allow the use of autonomous online GLUC activity measurements for rapid E. coli monitoring in water supplies used for drinking water production and recreation.