Fetal alcohol spectrum disorder and attention deficit hyperactivity disorder stimulant trial in children: an N-of-1 pilot trial to compare stimulant to placebo (FASST): protocol.

INTRODUCTION: Fetal alcohol spectrum disorder (FASD) is a neurodevelopmental disorder caused by alcohol exposure during pregnancy. FASD is associated with neurodevelopmental deviations, and 50%-94% of children with FASD meet the Diagnostic and Statistical Manual of Mental Disorders-fifth edition diagnostic criteria for attention deficit hyperactivity disorder (ADHD). There is a paucity of evidence around medication efficacy for ADHD symptoms in children with FASD. This series of N-of-1 trials aims to provide pilot data on the feasibility of conducting N-of-1 trials in children with FASD and ADHD. METHODS AND ANALYSIS: A pilot N-of-1 randomised trial design with 20 cycles of stimulant and placebo (four cycles of 2-week duration) for each child will be conducted (n=20) in Melbourne, Australia.Feasibility and tolerability will be assessed using recruitment and retention rates, protocol adherence, adverse events and parent ratings of side effects. Each child's treatment effect will be determined by analysing teacher ADHD ratings across stimulant and placebo conditions (Wilcoxon rank). N-of-1 data will be aggregated to provide an estimate of the cohort treatment effect as well as individual-level treatment effects. We will assess the sample size and number of cycles required for a future trial. Potential mediating factors will be explored to identify variables that might be associated with treatment response variability. ETHICS AND DISSEMINATION: The study was approved by the Hospital and Health Service Human Research Ethics Committee (HREC/74678/MonH-2021-269029), Monash (protocol V6, 25 June 2023).Individual outcome data will be summarised and provided to participating carers and practitioners to enhance care. Group-level findings will be presented at a local workshop to engage stakeholders. Findings will be presented at national and international conferences and published in peer-reviewed journals. All results will be reported so that they can be used to inform prior information for future trials. TRIAL REGISTRATION NUMBER: NCT04968522.

Incorporating uncertainty in Indigenous sea Country monitoring with Bayesian statistics: Towards more informed decision-making.

Partnerships in marine monitoring combining Traditional Ecological Knowledge and western science are developing globally to improve our understanding of temporal changes in ecological communities that better inform coastal management practices. A fuller communication between scientists and Indigenous partners about the limitations of monitoring results to identify change is essential to the impact of monitoring datasets on decision-making. Here we present a 5-year co-developed case study from a fish monitoring partnership in northwest Australia showing how uncertainty estimated by Bayesian models can be incorporated into monitoring management indicators. Our simulation approach revealed there was high uncertainty in detecting immediate change over the following monitoring year when translated to health performance indicators. Incorporating credibility estimates into health assessments added substantial information to monitoring trends, provided a deeper understanding of monitoring limitations and highlighted the importance of carefully selecting the way we evaluate management performance indicators.

Does the registry speak your language? A case study of the Global Angelman Syndrome Registry.

Global disease registries are critical to capturing common patient related information on rare illnesses, allowing patients and their families to provide information about their condition in a safe, accessible, and engaging manner that enables researchers to undertake critical research aimed at improving outcomes. Typically, English is the default language of choice for these global digital health platforms. Unfortunately, language barriers can significantly inhibit participation from non-English speaking participants. In addition, there is potential for compromises in data quality and completeness. In contrast, multinational commercial entities provide access to their websites in the local language of the country they are operating in, and often provide multiple options reflecting ethnic diversity. This paper presents a case study of how the Global Angelman Syndrome Registry (GASR) has used a novel approach to enable multiple language translations for its website. Using a "semi-automated language translation" approach, the GASR, which was originally launched in English in September 2016, is now available in several other languages. In 2020, the GASR adopted a novel approach using crowd-sourcing and machine translation tools leading to the availability of the GASR in Spanish, Traditional Chinese, Italian, and Hindi. As a result, enrolments increased by 124% percent for Spain, 67% percent for Latin America, 46% percent for Asia, 24% for Italy, and 43% for India. We describe our approach here, which we believe presents an opportunity for cost-effective and timely translations responsive to changes to the registry and helps build and maintain engagement with global disease communities.

Managing surgical waiting lists through dynamic priority scoring.

Prioritising elective surgery patients under the Australian three-category system is inherently subjective due to variability in clinician decision making and the potential for extraneous factors to influence category assignment. As a result, waiting time inequities can exist which may lead to adverse health outcomes and increased morbidity, especially for patients deemed to be low priority. This study investigated the use of a dynamic priority scoring (DPS) system to rank elective surgery patients more equitably, based on a combination of waiting time and clinical factors. Such a system enables patients to progress on the waiting list in a more objective and transparent manner, at a rate relative to their clinical need. Simulation results comparing the two systems indicate that the DPS system has potential to assist in managing waiting lists by standardising waiting times relative to urgency category, in addition to improving waiting time consistency for patients of similar clinical need. In clinical practice, this system is likely to reduce subjectivity, increase transparency, and improve overall efficiency of waiting list management by providing an objective metric to prioritise patients. Such a system is also likely to increase public trust and confidence in the systems used to manage waiting lists.

Pattern-based assessment of the influence of rainfall characteristics on urban stormwater quality.

Urbanisation increases pollutant generation within catchments and their transport to receiving waters. Changes to rainfall patterns, particularly in the age of climate change, make pollution mitigation a challenging task. Understanding how rainfall characteristics could influence the changes to stormwater pollutant runoff is important for designing effective mitigation strategies. This study employed a pattern-based assessment of relationships between rainfall characteristics and stormwater quality in urban catchments to develop this understanding. The research outcomes showed that rainfall events could be distinctly clustered based on intensity and duration, and each cluster of events would produce different stormwater quality responses. The high-intensity bursts occurring in the latter part of long-duration events were found to produce uniform and low concentrations of suspended solids. One the contrary, high intensity bursts occurring in the initial part of short-duration events triggered the first-flush effect, thus producing high concentrations of suspended solids. Furthermore, the first-flush effect was likely to present when the high intensity bursts occurred in the mid portion of rainfall events and produced variable concentrations of suspended solids. It was also found that the average rainfall intensity plays a key role in mobilising and transporting pollutants accumulated on urban surfaces.

Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics.

Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most statisticians and data scientists. Whether they are dedicated Bayesians or opportunistic users, applied professionals can now reap many of the benefits afforded by the Bayesian paradigm. In this paper, we touch on six modern opportunities and challenges in applied Bayesian statistics: intelligent data collection, new data sources, federated analysis, inference for implicit models, model transfer and purposeful software products. This article is part of the theme issue 'Bayesian inference: challenges, perspectives, and prospects'.

Bayesian design for minimizing prediction uncertainty in bivariate spatial responses with applications to air quality monitoring.

Model-based geostatistical design involves the selection of locations to collect data to minimize an expected loss function over a set of all possible locations. The loss function is specified to reflect the aim of data collection, which, for geostatistical studies, could be to minimize the prediction uncertainty at unobserved locations. In this paper, we propose a new approach to design such studies via a loss function derived through considering the entropy about the model predictions and the parameters of the model. The approach includes a multivariate extension to generalized linear spatial models, and thus can be used to design experiments with more than one response. Unfortunately, evaluating our proposed loss function is computationally expensive so we provide an approximation such that our approach can be adopted to design realistically sized geostatistical studies. This is demonstrated through a simulated study and through designing an air quality monitoring program in Queensland, Australia. The results show that our designs remain highly efficient in achieving each experimental objective individually, providing an ideal compromise between the two objectives. Accordingly, we advocate that our approach could be adopted more generally in model-based geostatistical design.

Angiotensin receptor blockers for the treatment of covid-19: pragmatic, adaptive, multicentre, phase 3, randomised controlled trial.

OBJECTIVE: To determine whether disrupting the renin angiotensin system with angiotensin receptor blockers will improve clinical outcomes in people with covid-19. DESIGN: CLARITY was a pragmatic, adaptive, multicentre, phase 3, randomised controlled trial. SETTING: 17 hospital sites in India and Australia. PARTICIPANTS: Participants were at least 18 years old, previously untreated with angiotensin receptor blockers, with a laboratory confirmed diagnosis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection who had been admitted to hospital for management of covid-19. INTERVENTION: Oral angiotensin receptor blockers (telmisartan in India) or placebo (1:1) for 28 days. MAIN OUTCOME MEASURES: The primary endpoint was covid-19 disease severity using a modified World Health Organization Clinical Progression Scale (WHO scale) at day 14. Secondary outcomes were WHO scale scores at day 28, mortality, intensive care unit admission, and respiratory failure. Analyses were evaluated on an ordinal scale in the intention-to-treat population. RESULTS: Between 3 May 2020 and 13 November 2021, 2930 people were screened for eligibility, with 393 randomly assigned to angiotensin receptor blockers (of which 388 (98.7%) to telmisartan 40 mg/day) and 394 to the control group. 787 participants were randomised: 778 (98.9%) from India and nine (1.1%) from Australia. The median WHO scale score at day 14 was 1 (interquartile range 1-1) in 384 participants assigned angiotensin receptor blockers and 1 (1-1) in 382 participants assigned placebo (adjusted odds ratio 1.51 (95% credible interval 1.02 to 2.23), probability of an odds ratio of >1 (Pr(OR>1)=0.98). WHO scale scores at day 28 showed little evidence of difference between groups (1.02 (0.55 to 1.87), Pr(OR>1)=0.53). The trial was stopped when a prespecified futility rule was met. CONCLUSIONS: In patients admitted to hospital for covid-19, mostly with mild disease, not requiring oxygen, no evidence of benefit, based on disease severity score, was found for treatment with angiotensin receptor blockers, using predominantly 40 mg/day of telmisartan. TRIAL REGISTRATION: ClinicalTrials.gov NCT04394117.

Adaptive monitoring of coral health at Scott Reef where data exhibit nonlinear and disturbed trends over time.

Time series data are often observed in ecological monitoring. Frequently, such data exhibit nonlinear trends over time potentially due to complex relationships between observed and auxiliary variables, and there may also be sudden declines over time due to major disturbances. This poses substantial challenges for modeling such data and also for adaptive monitoring. To address this, we propose methods for finding adaptive designs for monitoring in such settings. This work is motivated by a monitoring program that has been established at Scott Reef; a coral reef off the Western coast of Australia. Data collected for monitoring the health of Scott Reef are considered, and semiparametric and interrupted time series modeling approaches are adopted to describe how these data vary over time. New methods are then proposed that enable adaptive monitoring designs to be found based on such modeling approaches. These methods are then applied to find future monitoring designs at Scott Reef where it was found that future information gain is expected to be similar across a variety of different sites, suggesting that no particular location needs to be prioritized at Scott Reef for the next monitoring phase. In addition, it was found that omitting some sampling sites/reef locations was possible without substantial loss in expected information gain, depending upon the disturbances that were observed. The resulting adaptive designs are used to form recommendations for future monitoring in this region, and for reefs where changes in the current monitoring practices are being sought. As the methods used and developed throughout this study are generic in nature, this research has the potential to improve ecological monitoring more broadly where complex data are being collected over time.

Temperature Sensing and Honey Bee Colony Strength.

Strength auditing of European honey bee (Apis mellifera Linnaeus, 1758 [Hymenoptera: Apidae]) colonies is critical for apiarists to manage colony health and meet pollination contracts conditions. Colony strength assessments used during pollination servicing in Australia typically use a frame-top cluster-count (Number of Frames) inspection. Sensing technology has potential to improve auditing processes, and commercial temperature sensors are widely available. We evaluate the use and placement of temperature sensing technology in colony strength assessment and identify key parameters linking temperature to colony strength. Custom-built temperature sensors measured hive temperature across the top of hive brood boxes. A linear mixed-effect model including harmonic sine and cosine curves representing diurnal temperature fluctuations in hives was used to compare Number of Frames with temperature sensor data. There was a significant effect of presence of bees on hive temperature and range: hives without bees recorded a 5.5°C lower mean temperature and greater temperature ranges than hives containing live bees. Hives without bees reach peak temperature earlier than hives with bees, regardless of colony strength. Sensor placement across the width of the hive was identified as an important factor when linking sensor data with colony strength. Data from sensors nearest to the hive geometric center were found to be more closely linked to colony strength. Furthermore, a one unit increase in Number of Frames was significantly associated with a mean temperature increase of 0.36°C. This demonstrates that statistical models that account for diurnal temperature patterns could be used to predict colony strength from temperature sensor data.

Exploring Symptom Fluctuations and Triggers in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Novel Patient-Centred N-of-1 Observational Designs: A Protocol for a Feasibility and Acceptability Study.

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic condition of unknown aetiology associated with a range of disabling symptoms, including post-exertional malaise, chronic fatigue, musculoskeletal pain, orthostatic intolerance, unrefreshing sleep, and cognitive dysfunction. ME/CFS is a heterogeneous disorder, with significant variation in symptom type and severity between individuals, as well as within individuals over time. The diversity of ME/CFS symptom presentation makes management challenging; treatments supported by data from randomised controlled trials may not work for all individuals due to the variability in experienced symptoms. Studies using quantitative N-of-1 observational designs involve repeated outcome measurements in an individual over time and can generate rigorous individual-specific conclusions about symptom patterns and triggers in individuals with ME/CFS. This study aims to explore the feasibility and acceptability of using novel patient-centred N-of-1 observational designs to explore symptom fluctuations and triggers in ME/CFS at the individual level. METHODS AND ANALYSIS: Individuals with a medical diagnosis of ME/CFS will be recruited through ME/CFS patient organisations to participate in a series of patient-centred N-of-1 observational studies. Using a wrist-worn electronic diary, participants will complete ecological momentary assessments of fatigue, stress, mood, and cognitive demand, three times per day for a period of 6-12 weeks. Personally relevant symptoms and triggers will also be incorporated into the questionnaire design. Physical activity will be objectively measured via an integrated accelerometer. Feasibility and acceptability outcomes will be assessed including the percentage of diary entries completed, as well as recruitment and retention rate, feasibility of analysing and interpreting the data collected, and participant views about participation elicited via a post-study semi-structured interview. DISCUSSION: This study will assess the feasibility and acceptability of patient-centred N-of-1 observational studies to assess diseases with complex presentations such as ME/CFS, as well as provide individual-level evidence about fluctuations and triggers of ME/CFS symptoms that may aid self-management. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry: ACTRN12618001898246. Registered on 22 November 2018.

Comparing pregabalin and gabapentin for persistent neuropathic pain: A protocol for a pilot N-of-1 trial series.

BACKGROUND: Evidence-based management of neuropathic pain is commonly ineffective due to the large variability in response between cases. Patients often have to trial several drugs before finding one that provides adequate relief, leading to increased costs and worsened outcomes. There is thus a need for tools to guide and streamline prescribing decisions in neuropathic pain. N-of-1 trials provide a potentially precise and economical method of selecting between multiple interventions in an individual patient, and merit a feasibility assessment for use in clinical pain practice. AIMS: We aim to evaluate the feasibility of N-of-1 trials to compare pregabalin and gabapentin for individual presentations of neuropathic pain. METHODS: This is a double-blinded multiple crossover study, with recruitment from existing patients at an outpatient pain clinic in New South Wales, Australia. Participants will undergo three 4-week treatment pairs, comprising 2 weeks of pregabalin (150-600 mg/day) and 2 weeks of gabapentin (900-3600 mg/day), in an individually randomised order. Intervention doses will be derived from participants' existing treatment dose. Medications will be taken orally three times daily. The primary outcome will be pain intensity; measures will be self-reported daily in patient diaries. After completing all three cycles, participants and their physicians will be presented with the results of the trial to form an informed decision about their treatment. DISCUSSION: As a stable yet debilitating condition, neuropathic pain is especially amenable to an N-of-1 study design. A successful trial would represent a significant quality of life improvement for the patient, possibly extending over the course of their lifetime.

The impact of functional combined anteversion on hip range of motion: a new optimal zone to reduce risk of impingement in total hip arthroplasty.

AIMS: Pelvic tilt (PT) can significantly change the functional orientation of the acetabular component and may differ markedly between patients undergoing total hip arthroplasty (THA). Patients with stiff spines who have little change in PT are considered at high risk for instability following THA. Femoral component position also contributes to the limits of impingement-free range of motion (ROM), but has been less studied. Little is known about the impact of combined anteversion on risk of impingement with changing pelvic position. METHODS: We used a virtual hip ROM (vROM) tool to investigate whether there is an ideal functional combined anteversion for reduced risk of hip impingement. We collected PT information from functional lateral radiographs (standing and sitting) and a supine CT scan, which was then input into the vROM tool. We developed a novel vROM scoring system, considering both seated flexion and standing extension manoeuvres, to quantify whether hips had limited ROM and then correlated the vROM score to component position. RESULTS: The vast majority of THA planned with standing combined anteversion between 30° to 50° and sitting combined anteversion between 45° to 65° had a vROM score > 99%, while the majority of vROM scores less than 99% were outside of this zone. The range of PT in supine, standing, and sitting positions varied widely between patients. Patients who had little change in PT from standing to sitting positions had decreased hip vROM. CONCLUSION: It has been shown previously that an individual's unique spinopelvic alignment influences functional cup anteversion. But functional combined anteversion, which also considers stem position, should be used to identify an ideal THA position for impingement-free ROM. We found a functional combined anteversion zone for THA that may be used moving forward to place total hip components. Cite this article: Bone Jt Open 2021;2(10):834-841.

Establishment of an International Collaborative Network for N-of-1 Trials and Single-Case Designs.

In this article we briefly examine the unique features of Single-Case Designs (SCDs) (studies in a single participant), their history and current trends, and real-world clinical applications. The International Collaborative Network for N-of-1 Trials and Single-Case Designs (ICN) is a formal collaborative network for individuals with an interest in SCDs. The ICN was established in 2017 to support the SCD scientific community and provide opportunities for collaboration, a global communication channel, resource sharing and knowledge exchange. In May 2021, there were more than 420 members in 31 countries. A member survey was undertaken in 2019 to identify priorities for the ICN for the following few years. This article outlines the key priorities identified and the ICN's progress to date in these key areas including network activities (developing a communications strategy to increase awareness, collecting/sharing a comprehensive set of resources, guidelines and tips, and incorporating the consumer perspective) and scientific activities (writing position papers and guest editing special journal issues, exploring key stakeholder perspectives about SCDs, and working to streamline ethical approval processes for SCDs). The ICN provides a practical means to engage with this methodology through membership. We encourage clinicians, researchers, industry, and healthcare consumers to learn more about and conduct SCDs, and to join us in our mission of using SCDs to improve health outcomes for individuals and populations.

Protocol for the Controlled evaLuation of Angiotensin Receptor blockers for COVID-19 respIraTorY disease (CLARITY): a randomised controlled trial.

BACKGROUND: SARS-CoV-2 binds to membrane-bound angiotensin-converting enzyme 2 (ACE2) which may result in downregulation of membrane-bound ACE2. ACE2 is a key regulator of the renin-angiotensin system (RAS) and is responsible for degrading angiotensin II and thereby counteracting its pro-inflammatory, pro-fibrotic effects mediated through the angiotensin II type 1 receptor (AT1R). As AT1R is directly blocked by angiotensin receptor blockers (ARBs), these agents may offer a safe, low-cost solution for reducing COVID-19 respiratory outcomes. METHODS AND DISCUSSION: CLARITY is a pragmatic, adaptive, two-arm, multi-centre, comparative effectiveness phase III randomised controlled trial that examines whether ARBs reduce COVID-19 severity among high-risk patients. Recruiting in India and Australia, the trial will compare treatment with a maximum tolerated daily dose of an ARB to standard of care. Treatment allocation is blinded in India but open-label in Australia due to interruptions to placebo supply in the latter. The primary endpoint is a 7-point ordinal scale of clinical states, ranging from no limitation of activities (category 1) to death (category 7), assessed on day 14. Secondary outcomes include the 7-point scale assessed at day 28 and 28- and 90-day mortality. The design adapts the sample size based on accumulating data via frequent interim analyses and the use of predictive probability to determine whether the current sample size is sufficient or continuing accrual would be futile. The trial commenced recruitment on 18 August 2020. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04394117 . Registered on 19 May 2020. Clinical Trial Registry of India: CTRI/2020/07/026831).

A Bayesian approach to model the trends and variability in urban stormwater quality associated with catchment and hydrologic parameters.

Stormwater runoff pollution has become a key environmental issue in urban areas. Reliable estimation of stormwater pollutant discharge is important for implementing robust water quality management strategies. Even though significant attempts have been undertaken to develop water quality models, deterministic approaches have proven inappropriate as they do not address the variability in stormwater quality. Due to the random nature of rainfall characteristics and the differences in catchment characteristics, it is difficult to generate the runoff pollutographs to a desired level of certainty. Bayesian hierarchical modelling is an effective tool for developing complex models with a large number of sources of variability. A Bayesian model does not look for a single value of the model parameters, but rather determines a distribution of the model parameters from which all inference is drawn. This study introduces a Bayesian hierarchical linear regression model to describe a catchment specific runoff pollutograph incorporating the associated uncertainties in the model parameters. The model incorporates catchment and rainfall characteristics including the effective impervious area, time of concentration, rain duration, average rainfall intensity and the antecedent dry period as the contributors to random effects.

Thermal Impacts of Apicultural Practice and Products on the Honey Bee Colony.

Hive design and apicultural processes have not been fundamentally changed since the design and commercialization of the Langstroth moveable frame hive in 1854. Colonies of Apis mellifera Linnaeus (Hymentoptera: Apidae) (the honey bee) maintain a brood nest temperature within the narrow range of 34.5-35.5°C, critical for brood development. Apis mellifera invest considerable energy to maintain hive homeostasis through behavioral modification of the hive environment. Human honey-harvesting processes and removal of the honey-filled comb (a source of thermal mass) have a detrimental impact on hive temperature that requires an increased investment of energy to rectify. This additional energy demand on the bees is a form of stress to the colony and diverts workers away from other essential tasks to that of environmental management. We investigated the thermal energy loss resulting from the removal and extraction of honey, the rate of thermal loss of an Australian standard Langstroth 10 frame hive, and the effect of honey and wax as a thermal mass in unoccupied bee hive. The results demonstrate that considerable energy expenditure would be required to rectify the hive thermal environment after honey harvesting or honeycomb frame addition. Honey provides thermal mass in the beehive, acting as a thermal buffer to external temperature change, which may mediate part of the thermal losses from the simplistic design of the Langstroth hive. Identification of these impacts in current apicultural practice and hive design allows for the improvement in the design of beehives and associated practices. These improvements may reduce stress to the bee colony, increasing colony efficiency for pollination and nectar foraging.

Source quantification and risk assessment as a foundation for risk management of metals in urban road deposited solids.

Urban road build-up solids contain toxic metals posing potential risks to human health. Management of human health risks arising from these metals is critical in urban areas. This study collected solids build-up data from 16 study sites with various land use and traffic characteristics. Source quantification was conducted using PCA/APCS receptor model. It was found that soil and asphalt wear are the largest contributors (69.43%) to risk and mainly contribute Al, Cr, Mn, Fe, Ni, Zn and Pb to build-up solids. Brake wear is the second largest contributor accounting for 17.20% and contributes Cd and Cu. Tyre wear is the third major contributor (11.38%) and it primarily contributes Ni, Zn and Cr. Mathematical equations were fitted to estimate the risk against daily traffic volume and land use fractions, and the uncertainty analysis highlighted that risk assessment should account for the variability in metal concentrations rather than a point value of concentrations at a given time and space. Based on source quantification and risk assessment, an integrated risk management model was developed to manage human health risks from toxic metals in build-up solids. This risk model provides guidance for urban planning and land use development to mitigate risk arising from urban road deposited solids.

New conceptualisation of first flush phenomena in urban catchments.

First flush is an important phenomenon commonlyused in stormwater treatment system design where only the highly concentrated initial part of the runoff hydrograph is subject to treatment. Despite the existing methods for estimating the first flush, a robust quantitative definition is difficult to find. This paper discusses a novel approach, where a new parameter is introduced to analyse the variability in the discharge of pollutants at different times throughout a runoff event and thereby enable the identification of first flush. It was found that due to variability in rainfall, the first flush runoff volume varies from event to event. Therefore, a static estimate of the first flush is not applicable for a runoff event. The Monte Carlo simulation undertaken strengthened the analysis by providing credible limits to the outcomes. Accordingly, an interval estimation was obtained in which the first flush runoff can vary, and it was found that most commonly, the first flush can exist through the initial 30%-50% of the runoff. Therefore, in order to treat the stormwater runoff with minimum risk of discharging high loads of pollutants to the receiving water environment, at least the initial 30% of the runoff should be subject to treatment. This understanding provides a fundamental basis for the design of robust stormwater treatment systems.