Design Of Monitoring Programs Research Articles

Stable spatial patterns of concentrations of antibiotic resistant bacteria in irrigation water

Irrigation waters serve as vectors for the spread of antibiotic-resistant bacteria which presents a worldwide health concern. Determining the concentrations of those bacteria in waters used for irrigation is therefore an important monitoring target. The objective of this work was to determine the existence of persistent spatial patterns in antibiotic-resistant bacteria in an irrigation waterbody and compare the patterns with patterns of water quality parameters. Escherichia coli, total coliforms, and total heterotrophic bacteria concentrations were measured in water samples collected from 20 sites across an irrigation waterbody on nine sampling dates. The Empirical Orthogonal Function (EOF) analysis was used to detect persistent spatial patterns of tetracycline- and cefotaxime-resistant bacteria as well as water quality parameters. The average concentrations of both generic and antibiotic-resistant bacteria were an order of magnitude higher in bank sampling sites than interior sites. From the EOF analysis results, sampling locations were identified which could provide the best estimates of the average concentrations for each bacterial group. Patterns in temperature (rs = -0.638 to -0.749), dissolved oxygen (rs = -0.173 to -0.675), and pH (rs = -0.483 to -0.770) showed the strongest negative correlations with patterns in bacteria concentrations while all other water quality patterns tended to be positively correlated. Results of this work show that the EOF analysis can be a powerful tool in the design of effective monitoring programs which assess antibiotic resistance in irrigation waters by identifying locations which are closest to the spatiotemporal average.

Effective ecological monitoring using passive acoustic sensors: Recommendations for conservation practitioners

AbstractPassive acoustic recorders have emerged as powerful tools for ecological monitoring. However, effective monitoring is not simply an act of recording sounds. To have meaning for conservation and management, acoustic monitoring needs to be properly planned and analyzed to yield high quality information. Here, we provide a set of considerations for the design of an effective acoustic monitoring program. We argue that such a program, has the following attributes: (1) has established appropriate partnerships with landowners, Traditional Owners, researchers, or other relevant stakeholders, (2) is based on clear objectives and questions, (3) is explicit in its target sound signals, (4) has considered in‐field sensor placement for a range of factors, including experimental design, statistical power, background noise, and potential impacts on human privacy and animal disturbance, (5) has a justified recording schedule and periodicity, (6) has methods to process sound data in line with objectives, and (7) has protocols for permanent data storage and access. Acoustic monitoring is increasingly used in large‐scale programs and will be important in addressing global biodiversity targets and new biodiversity markets. It is critical that new monitoring programs are designed to effectively and efficiently capture data that address pertinent and emerging issues in conservation.

The Contribution of Open Source Software in Identifying Environmental Crimes Caused by Illicit Waste Management in Urban Areas

This study focuses on the analysis, implementation and integration of techniques and methods, also based on mathematical algorithms and artificial intelligence (AI), to acquire knowledge of some phenomena that produce pollution with an impact on environmental health, and which start from illicit practices that occur in urban areas. In many urban areas (or agroecosystems), the practice of illegal waste disposing by commercial activities, by abandoning it in the countryside rather than spending economic resources to ensure correct disposal, is widespread. This causes an accumulation of waste in these areas (which can also be protected natural areas), which are then also set on fire to reduce their volume. Obviously, the repercussions of such actions are many. The burning of waste releases contaminants into the environment such as dioxins, polychlorinated biphenyls and furans, and deposits other elements on the soil, such as heavy metals, which, by leaching and percolating, contaminate water resources such as rivers and aquifers. The main objective is the design and implementation of monitoring programs against specific illicit activities that take into account territorial peculiarities. This advanced approach leverages AI and GIS environments to interpret environmental states, providing an understanding of ongoing phenomena. The methodology used is based on the implementation of mathematical and AI algorithms, integrated into a GIS environment to address even large-scale environmental issues, improving the spatial and temporal precision of the analyses and allowing the customization of monitoring programs in urban and peri-urban environments based on territorial characteristics. The results of the application of the methodology show the percentages of the different types of waste found in the agroecosystems of the study area and the degree of concentration, allowing the identification of similar areas with greater criticality. Subsequently, through network and nearest neighbour analysis, it is possible to start targeted checks.

Characterizing personalized ecologies

AbstractPeople have unique sets of direct sensory interactions with wild species, which change through their days, weeks, seasons, and lifetimes. Despite having important influences on their health and well‐being and their attitudes towards nature, these personalized ecologies remain surprisingly little studied and are poorly understood. However, much can be inferred about personalized ecologies by considering them from first principles (largely macroecological), alongside insights from research into the design and effectiveness of biodiversity monitoring programmes, knowledge of how animals respond to people, and studies of human biology and demography. Here I first review how three major sets of drivers, opportunity, capability and motivation, shape people's personalized ecologies. Second, I then explore the implications of these mechanisms for how more passively and more actively practical improvements can be made in people's personalized ecologies. Particularly in light of the declines in the richness of these ecologies that are being experienced in much of the world (the so‐called ‘extinction of experience’), and the significant consequences, marked improvement in many people's interactions and experiences with nature may be key to the future of biodiversity.

Ecological indicators to monitor offshore wind interactions with fisheries resources

Abstract Offshore wind development (OWD) will generate much needed renewable energy, but it will also introduce several stressors to the marine ecosystem. Therefore, there is a need to develop information-rich monitoring programs to assess ecological impacts and inform solutions to mitigate adverse effects. This paper evaluates potential indicators of OWD impacts on fisheries resources that could be considered for monitoring programs, including indices of aggregate biomass, sensitive species, fish size, and trophic dynamics. Short-term (year-to-year) variability and the direction and strength of long-term trends were explored at both the scale of the US Southern New England wind energy area (WEA) and at the scale of the Southern New England region. The majority of candidate OWD indicators exhibited substantial temporal variability at either the WEA scale, the region scale, or both, highlighting the importance of addressing temporal variability in the design and duration of monitoring programs. Recommendations are provided to advance informative monitoring approaches both in the USA and elsewhere where such approaches are urgently needed. Among these is a recommendation for a minimum of 3–5 years of baseline data collection and continued monitoring for the lifetime of the wind project. This will enable an understanding of the temporal structure inherent to the time series of ecological indicators measured so that OWD impacts can be disentangled from those caused by other ecosystem pressures.

How we count counts: Examining influences on detection during shoreline surveys of marine debris

Shoreline surveys are a common approach for documenting loads of marine macrodebris (≥ 2.5 cm). When surveys are conducted repeatedly over time and space, patterns in source, abundance, geographic distribution, and composition can be detected. Yet to realize their full potential, monitoring programs that rely on surveys must grapple with high variability in debris abundance, and appropriately manage uncertainty when reporting estimates of debris quantity. A potentially important source of bias in estimating debris loads from shoreline monitoring datasets is variability in debris detection rates. With this in mind, we conducted field experiments using common strip-transect marine debris survey protocols, designed to test detection of macrodebris. We quantified how protocol, shoreline, and debris characteristics influence the detectability of marine macrodebris. Detection rates varied according to debris distance from observer (0–5 m), number of observers, debris characteristics (size, color), and shoreline substrate. Our results highlight considerations for monitoring program design. Comparisons across datasets should be approached cautiously given differences in survey protocols and sources of bias that may affect debris density estimates should be quantified and addressed. We hope these results will inform marine debris monitoring efforts that are optimized for intended data use and impact.

Bridging gaps in groundwater management in International River Basin Districts (IRBDs) – through harmonized monitoring and data sharing

Study regionEurope, with focus on Scandinavia (Denmark, Norway, Sweden), the Baltic countries (Estonia, Latvia, Lithuania), Finland, Poland, and Ukraine. Study focusThe Water Framework Directive (WFD) aims to obtain harmonised holistic Europe-wide water management based on an integrated river basin management model. This study analyses the efficiency of national groundwater monitoring programmes in meeting cross-border demands for harmonised data in IRBDs. Emphasis is placed on the core parameters, oxygen content, pH, conductivity, nitrate, and ammonium, specified by the WFD to be monitored in surveillance monitoring programmes. The findings offer recommendations for national water authorities on infirmities in groundwater management and how they could improve data transparency and availability for enhanced long-term management of shared resources. New hydrological insights for the regionA questionnaire distributed to nine European countries indicates large national differences in the extent of groundwater monitoring. This study highlights several key recommendations for moving forward with transborder groundwater management. Firstly, it is imperative that all nations adhere to ISO standards for field practices and analysis. Secondly, transborder collaborative projects to harmonise e.g., design of monitoring programmes, sampling, and analysis and cooperation on data analysis must be established. Lastly, there is a need to enhance the accessibility of groundwater data and associated metadata. The achievement of the WFD objectives encounters obstacles, due to weak transborder integration and the effects related to administrative boundaries.

Spatiotemporal patterns of multiple pesticide residues in central Argentina streams

Pollution of surface waters is a global threat, with particular concern about pesticides due to their severe negative effects on ecosystem functioning and human health. The aims of this study were to identify the spatiotemporal patterns of water and sediment quality, and the key variables related to the variation in pesticide pollution (122 compounds), in headwater streams (surrounding land uses: crop or mixed crop-livestock systems) and floodplain streams (surrounding land uses: urban development or natural wetland) of the Paraná River basin in the central area of Argentina. We found significant differences in water and sediment quality related to local land uses among headwater streams, but not among floodplain streams. These differences were more noticeable during spring than during autumn. Pesticides were widespread in all the streams, independently of the surrounding land use, reflecting the combination of local inputs and the role of floodplain hydrological connectivity in transporting pollutants from upstream sources. The most frequently detected compound was atrazine (75 %), whereas the highest concentration of an individual compound was observed for the glyphosate metabolite aminomethylphosphonic acid (AMPA, up to 4 μg L−1). The significant explanatory variables for pesticide pollution were turbidity, chromophoric dissolved organic matter (CDOM), sub-basin area, side slope of streams (positive relations), wetland cover, and precipitations (negative relations). Our results can be useful for the design of monitoring programs that capture the spatial and temporal variability of pesticide pollution.

Potential upslope and latitudinal range shifts for Andean potato weevils Premnotrypes species, in the tropical Andes of South America

Premnotrypes is a weevil species complex that occurs in the high Andes of South America. Most of the species are considered to be crop pests, associated with potato production, thus constituting a major potential pest in Andean regions. Changes in temperature patterns affect the ontogeny and physiology of crop pests directly, which will in turn affect the pest populations. Here, we used ecological niche modeling (ENM) to assess the potential geographic distribution of seven economically important Premnotrypes species under current conditions and two under future scenarios of conditions scenarios (SSP 4.5 and SPP 8.5) for 2050 and 2090. Current-time niche models predicted suitable areas across the tropical Andes. For P. vorax, ENMs showed suitable areas across the Andes of Peru, Colombia, and Venezuela. For P. lathithorax, ENMs showed suitable areas only in the Andes of Peru and Bolivia. Finally, for P. solaniperda, P. solanivorax, P. pusillus, P. suturicallus, and P. percei, ENMs indicated suitable areas across central and southeastern Peru. Under future conditions, for all seven species, ENMs anticipated range shifts to higher latitudes and upslope migration, thus reducing suitable areas in the eastern Andes. Our novel results offer a guide for designing monitoring programs for potato pests and developing optimal pest control and mitigation strategies.

Spatial Variation of Tetracycline-Resistant E. coli and Relationships with Water Quality Variables in Irrigation Water: A Pilot Study

Irrigation waters may facilitate the spread of antibiotic-resistant bacteria or genes to humans and animals. Monitoring of resistance in irrigated waters has become common; however, many studies do not incorporate a spatial component into sampling designs. The objective of this work was to assess spatiotemporal variations in tetracycline-resistant E. coli in an irrigation pond. Water samples were collected at 10 locations and two different water depths, and in situ and laboratory water quality measurements were performed. The percentage of E. coli resistant to the low (4 μg mL−1) and high (16 μg mL−1) tetracycline doses varied by date and location but were observed to be as high as 12.7% and 6.3% of the total population throughout the study, respectively. While significant differences were not observed between resistance levels measured at different depths, on one date resistant E. coli were only detected in samples collected at depth. Nitrate, fluorescent dissolved organic matter, and dissolved oxygen concentrations were found to be the leading control variables for the percentage of resistant E. coli. This work demonstrates that there may be substantial spatial variability in concentrations of antibiotic-resistant E. coli in irrigation ponds which should be accounted for in the design of monitoring programs.

Non-Indigenous Species Dynamics in Time and Space within the Coastal Waters of The Netherlands

Information on temporal and spatial trends with regard to the introduction of non-indigenous species (NIS) is often sparsely available. These trends may potentially help improve the design and focus of monitoring programs, give insights into new pathways and hotspots, and facilitate horizon scanning. We provide an overview of 215 marine and brackish water NIS recorded in The Netherlands. Temporal trends over the most recent three decades for taxonomic groups, species origin, introduction vectors, and water systems were analysed. We attempt to explain the observed patterns and discuss factors that hamper their explanation. A shift in the region of origin from Pacific to W Atlantic can potentially be linked to legislation prohibiting Pacific oyster imports, whereas a subsequent shift backwards cannot. Case studies illustrate that NIS may not be first detected in the water systems where they were originally introduced. Additionally, it is shown that changes in allegedly native species’ distribution or seasonal pattern should be linked to an introduced cryptic NIS instead. We also discuss the shortcomings of monitoring programs that were originally not focused on NIS, the importance of naturalists’ observations, and the added value of a more recent network that is focused on NIS detection in the coastal waters of The Netherlands.

Evaluating adaptive management frameworks for data-limited crustacean fisheries

Crustacean fisheries represent an increasingly important contribution to global landings, food security and economic growth, especially in developing countries. However, many productive and valuable crustacean fisheries in Asian countries are characterized by limited data availability, scientific capacity, and fisheries management. Adaptive management frameworks, which use past and emerging information to provide stock status information and management advice, have been touted as particularly applicable for managing capacity- and data-limited fisheries because they employ methods that can improve data collection and result in evaluations of stock and ecosystem status with varying levels of data and capacity. Here, we examined the application of three adaptive fisheries management frameworks (FISHE, FishPath, and DLMtool) to three typical Asian crustacean fisheries that offered contrasting data types and availability, governance, and management and socio-economic contexts. Our aim was to evaluate their suitability for crustacean fisheries and identify particular data and modeling needs and management gaps in these fisheries. We found that while each of the frameworks could effectively recommend suitable monitoring, assessment, and management options given particular contextual factors, there were also limitations with each approach. For example, FISHE took a more wholistic view of ecosystem and fisheries heath, while the other frameworks were more focused on particular aspects of management such as stock assessment (FishPath) and management strategy evaluation (MSE; DLMtool). Applications of each approach also highlighted particular challenges in collecting commercial catch data due to limited monetary investment and poorly designed monitoring programs, which further hindered the implementation of catch and effort limits. The three frameworks also shared common challenges when applied to crustacean species, mainly associated with misalignment with the unique life-histories of crustaceans compared to finfish. By comparing the outputs of the three frameworks, we highlighted their respective strengths and weaknesses and propose an integrated framework that incorporates elements of each of the three frameworks. This integration offers a more comprehensive adaptive roadmap tailored to crustacean fisheries, which involves a mix of qualitative and quantitative approaches that could be applied depending on contextual factors and capacities. To further improve the applicability of adaptive frameworks to crustacean fisheries, we suggest considering crustacean's unique life history and the effects of climate change and other environmental factors, strengthening participatory processes, and balancing socio-economic and ecological objectives.

Informing Volunteer Water Quality Monitoring Program Design and Watershed Planning: Case Study of StreamSmart Data Analysis in the Upper White River Basin, Arkansas

AbstractThe watershed group H2Ozarks founded the StreamSmart Citizen Science Program to establish baseline and long‐term water quality data for the Upper White River Basin, Arkansas. StreamSmart volunteers collect water samples and conduct habitat and macroinvertebrate community assessments at >20 sites across a land use‐land cover (LULC) gradient. Since 2020, H2Ozarks has adaptively assessed the program to ensure that the investment in water quality data meets core goals, with particular interest in planning tools and aligning expectations of volunteer effort with the level of training and support. Study objectives were to use StreamSmart data to 1) facilitate understanding of water quality response to stressors in the basin using a range of methods (Spearman rank correlation, non‐parametric changepoint analysis, and categorical and regression tree analysis) and 2) explore implications for program design and watershed planning. Water chemistry‐LULC relationships were in‐line with prior regional studies, as well as global patterns. Detected thresholds and hierarchy provide potential targets for managing LULC change to protect water quality, but further analysis is warranted to refine these relationships. Macroinvertebrate stressor‐response was most detectable for sensitive and less sensitive taxa and for habitat index components, suggesting potential to streamline these programmatic elements. Study findings for StreamSmart should also be informative for other small‐scale volunteer monitoring programs with limited resources, but which actively evaluate the types of data and program activities that yield a maximum scientific return on investment.

Monitoring mesocarnivores with tracks and technology using multi‐method modeling

AbstractMesocarnivores play important ecological roles and are valued by diverse stakeholders. These species are often the focus of conservation efforts or are managed for sustainable harvest. Management actions require accurate population monitoring, but such monitoring is challenging because mesocarnivores are elusive and persist at low densities. We addressed this challenge by evaluating 2 monitoring methods (scent stations and motion‐sensitive cameras) using multi‐method modeling. We estimated occurrence probabilities and habitat relationships for 8 mesocarnivore species by fitting occupancy models to data collected at 75 sites from October to December 2021 across a 3,200‐km2system in New Hampshire, USA. We assessed the relative estimated precision of the methodological approaches and their costs. We also evaluated tradeoffs in occurrence estimation and uncertainty among study designs by analyzing simulations run across various numbers of study sites and 2 study durations. Cameras cost roughly 10 times more than scent stations but strongly outperformed them in terms of species' detectability and parameter estimate precision. Multi‐method models yielded the most precise estimates of occurrence probability and habitat relationships. Parameter estimates were on average twice as precise for camera and multi‐method models compared to scent stations. Additionally, the estimated precision and direction (positive or negative) of habitat relationships varied with the method employed. Longer camera deployments, additional study sites, and multi‐method approaches nearly always reduced uncertainty, but these reductions were species‐specific and generally most pronounced for more rarely detected species. Overall, our results demonstrate the utility of motion‐sensitive cameras traps for monitoring mesocarnivores while revealing the additional benefits of multi‐method modeling. Our results also provide guidance for designing monitoring programs for mesocarnivores while navigating tradeoffs between study design, cost, and uncertainty. Despite its benefits, multi‐method modeling remains uncommon as a general monitoring approach. We suggest managers consider this approach in light of existing datasets and design monitoring programs that integrate traditional methods with emergent technologies.

Temporal Stability of Salmonella enterica and Listeria monocytogenes in Surface Waters Used for Irrigation in the Mid-Atlantic United States

Enteric bacterial pathogen levels can influence the suitability of irrigation water sources for fruits and vegetables. We hypothesize that stable spatial patterns of Salmonella enterica and Listeria monocytogenes levels may exist across surface water sources in the Mid-Atlantic U.S. Water samples were collected at four streams and two pond sites in the mid-Atlantic U.S. over 2 years, biweekly during the fruit and vegetable growing seasons, and once a month during nongrowing seasons. Two stream sites and one pond site had significantly different mean concentrations in growing and nongrowing seasons. Stable spatial patterns were determined for relative differences between the site concentrations and average concentration of both pathogens across the study area. Mean relative differences were significantly different from zero at four of the six sites for S. enterica and three of six sites for L. monocytogenes. There was a similarity between the mean relative difference distribution between sites over growing season, nongrowing season, and the entire observation period. Mean relative differences were determined for temperature, oxidation-reduction potential, specific electrical conductance, pH, dissolved oxygen, turbidity, and cumulative rainfall. A moderate-to-strong Spearman correlation (rs > 0.657) was found between spatial patterns of S. enterica and 7-day rainfall, and between relative difference patterns of L. monocytogenes and temperature (rs = 0.885) and dissolved oxygen (rs = -0.885). Persistence in ranking sampling sites by the concentrations of the two pathogens was also observed. Finding spatially stable patterns in pathogen concentrations highlights spatiotemporal dynamics of these microorganisms across the study area can facilitate the design of an effective microbial water quality monitoring program for surface irrigation water.

Tenets for Implementing Electronic Patient-Reported Outcomes for Remote Symptom Monitoring During Cancer Treatment.

Symptoms are common in patients receiving systemic treatment for metastatic cancer. Monitoring patients with electronic patient-reported outcomes (ePROs) detects severe and worsening symptoms early, enabling care teams to intervene and prevent downstream complications and thereby improving outcomes. The Centers for Medicare & Medicaid Services will require patient-reported outcome (PRO) monitoring in the upcoming Enhancing Oncology Model, and many practices will likely attempt to implement PROs in patient care for the first time. To assist practices with the design and implementation of ePRO remote symptom monitoring programs, tenets were drawn from prior ePRO program experiences and research. Successful implementation requires a quality improvement approach to change management with attention to software functionality, measured outcomes, personnel deployment, leadership and culture, workflow, equity, and patient engagement. Specific approaches in each of these areas can optimize program participation and effectiveness. Continuous program monitoring to identify and address barriers is essential to success. Initial challenges with personnel acceptance and patient participation are common and can be overcome by using these tenets. Remote symptom monitoring with ePROs is a key component of quality cancer care and population health management that requires organizational commitment and a deliberate approach by practices using established tenets to assure successful implementation.

Detections of cyanobacteria harmful algal blooms (cyanoHABs) in New York State, United States (2012–2020)

Gorney RM, June SG, Stainbrook KM, Smith AJ. 2023. Detections of cyanobacteria harmful algal blooms (cynanoHABs) in New York State, United States (2012–2020). Lake Reserv Manage. 39:21–36. Patterns in frequency, intensity, and duration of cyanobacteria harmful algal blooms (cyanoHABs) were evaluated in New York State from 2012 to 2020. The dataset included information from formal monitoring efforts, beach closures, and public reports. The total dataset included more than 24,000 records from 655 waterbodies and included cyanoHAB reports from 477 lakes. Nearly half of those lakes (49.6%) had only 1 year in which a cyanoHAB was documented. Less than 1% (6 lakes) had cyanoHABs documented in every year of the study. We noted a significant increase in the number of cyanoHABs reports each year (P < 0.001), but not an overall increase in intensity, based on evaluation of chlorophyll levels in mid-lake samples collected on a routine basis. The analysis indicated that cyanoHABs duration did not lengthen over the study period, based on beach closure data captured on a daily observation basis. This study addresses the limitations of monitoring data for analysis of patterns in cyanoHABs, based on the structure of the programs and frequency of observations. We provide retrospective feedback on the design of monitoring programs to improve future data collection and our ability to evaluate cyanoHABs in a wide range of waterbodies.

Health Monitoring for Laboratory Salamanders.

Laboratory animal health monitoring programs are necessary to protect animal health and welfare, the validity of experimental data, and human health against zoonotic infections. Health monitoring programs should be designed based on a risk assessment and knowledge about the biology and transmission of salamander pathogens. Both traditional and molecular diagnostic platforms are available for salamanders, and they provide complementary information. A comprehensive approach to health monitoring leverages the advantages of multiple platforms to provide a more complete picture of colony health and pathogen status. This chapter presents key considerations in the design and implementation of a colony health monitoring program for laboratory salamanders, including protocols for necropsy and sample collection.

8.B. Workshop: The Dutch GOR-Covid-19 health monitor: a five-year research program to inform public health policy

Abstract Societies can be confronted with disasters and major incidents that form a serious threat to population well-being, safety and health. The Covid-19 pandemic challenged governments at different levels in many countries across the world for over two years to address a variety of public health risks. This also applies to the Netherlands, a densely populated high income country in Europe with approximately 17 million citizens. Experience with previous crises - such as the Bijlmermeer Airplane Disaster in Amsterdam (1992), the Q fever outbreak (2007-2011), the MH17 airplane disaster in Ukraine (2014) and gas-mining induced earthquake problems in the north of the Netherlands (ongoing) - shaped the current Dutch public health response structure and knowledge base, designed to assist local and national authorities to anticipate disaster-related population health risks. During the Covid-19 pandemic this structure was used as a starting point to develop and implement a five-year monitoring program: the integrated GOR-Covid-19 health monitor; GOR stands for “Gezondheidsonderzoek bij rampen” (disaster health research). The main objective of the GOR-Covid-19 monitor is to collect and promote the uptake of reliable and timely monitoring information for the benefit of regional and national public health decision-making in the Netherlands, focusing on the public health impact of the Covid-19 crisis (virus infections and mitigation measures) among children and adolescents, adults and public mental health care, a potentially vulnerable group including homeless and former drug addicts. The monitor is carried out under coordination of the “Network GOR”, comprised of the National Institute for Public Health and the Environment, GGD GHOR Netherlands (on behalf of the 25 municipal health regions), Nivel, and ARQ National Psychotrauma Centre. The current workshop consists of five presentations by members of Network GOR. The first contribution gives an overview of the research objectives and the outline of the study protocol of the monitoring program. The other contributions focus on particular study components, that are shaped and aligned during the timeline of the monitor. One presenter will share the findings from the first series of systematic literature reviews. Two contributions are based on a combination of surveys in representative samples and an analysis of primary care registry data: one with an emphasis on quarterly results (short-cycle monitoring), the other on (bi-)annual reports, which zoom in on long-term developments and differences between subgroups based on vulnerability factors and geography (long-cycle monitoring). The fifth contribution details the participatory stakeholder-engagement process designed and implemented to promote that monitor findings are used for local and national public health sense-making and decision-making. Key messages • The workshop describes the background and design of a national longitudinal monitoring program to track the public health impact of the Covid-19 pandemic in the Netherlands. • An overview is given of the first findings on the health impact of the pandemic for different populations and related vulnerability factors as well as the stakeholder engagement process.

Total Maximum Daily Loads and Escherichia coli Trends in Texas Freshwater Streams

AbstractFecal indicator bacteria are routinely used to assess surface water sanitary quality. The State of Texas uses Total Maximum Daily Loads to address water bodies that exceed the allowable fecal indicator bacteria criteria. The effectiveness of these processes in decreasing the fecal indicator bacteria concentrations has been debated due to the diversity and nature of fecal indicator bacteria sources. We assessed actual and flow‐adjusted trends in measured Escherichia coli (E. coli) concentrations at 721 freshwater stream sites from 2001 through 2021. We also compared odds of statistical improvement of E. coli concentrations at sites before and after the adoption of Total Maximum Daily Loads (adopted from 2008 through 2014). Results indicate non‐significant differences in the odds of statistically detected improvements in E. coli concentration between pre‐Total Maximum Daily Load and post‐Total Maximum Daily Load sites. Although the State of Texas and numerous watershed stakeholders have made efforts to address water quality impairments, these results join a body of evidence that water quality improvements are stagnating in the state. Furthermore, this study leverages water quality data used for state water quality standards assessment purposes and highlights that robust monitoring program design is needed to effectively assess the progress of water quality planning efforts.