Mapping Community Opioid Exposure Through Wastewater-Based Epidemiology as a Means to Engage Pharmacies in Harm Reduction Efforts

Rapid opioid overdose response system technologies

PURPOSE OF REVIEW

Opioid overdose events are a time sensitive medical emergency, which is often reversible with naloxone administration if detected in time. Many countries are facing rising opioid overdose deaths and have been implementing rapid opioid overdose response Systems (ROORS). We describe how technology is increasingly being used in ROORS design, implementation and delivery.

RECENT FINDINGS

Technology can contribute in significant ways to ROORS design, implementation, and delivery. Artificial intelligence-based modelling and simulations alongside wastewater-based epidemiology can be used to inform policy decisions around naloxone access laws and effective naloxone distribution strategies. Data linkage and machine learning projects can support service delivery organizations to mobilize and distribute community resources in support of ROORS. Digital phenotyping is an advancement in data linkage and machine learning projects, potentially leading to precision overdose responses. At the coalface, opioid overdose detection devices through fixed location or wearable sensors, improved connectivity, smartphone applications and drone-based emergency naloxone delivery all have a role in improving outcomes from opioid overdose. Data driven technologies also have an important role in empowering community responses to opioid overdose.

SUMMARY

This review highlights the importance of technology applied to every aspect of ROORS. Key areas of development include the need to protect marginalized groups from algorithmic bias, a better understanding of individual overdose trajectories and new reversal agents and improved drug delivery methods.

Utilizing a National Wastewater Monitoring Program to Address the U.S. Opioid Epidemic: A Focus on Metro Atlanta, Georgia

The opioid epidemic has continued to be an ongoing public health crisis within Metro Atlanta for the last three decades. However, estimating opioid use and exposure in a large population is almost impossible, and alternative methods are being explored, including wastewater-based epidemiology. Wastewater contains various contaminants that can be monitored to track pathogens, infectious diseases, viruses, opioids, and more. This commentary is focusing on two issues: use of opioid residue data in wastewater as an alternative method for opioid exposure assessment in the community, and the adoption of a streamlined approach that can be utilized by public health officials. Opioid metabolites travel through the sanitary sewer through urine, fecal matter, and improper disposal of opioids to local wastewater treatment plants. Public health officials and researchers within various entities have utilized numerous approaches to reduce the impacts associated with opioid use. National wastewater monitoring programs and wastewater-based epidemiology are approaches that have been utilized globally by researchers and public health officials to combat the opioid epidemic. Currently, public health officials and policy makers within Metro Atlanta are exploring different solutions to reduce opioid use and opioid-related deaths throughout the community. In this commentary, we are proposing a new innovative approach for monitoring opioid use and analyzing trends by utilizing wastewater-based epidemiologic methods, which may help public health officials worldwide manage the opioid epidemic in a large metro area in the future.

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

The US Environmental Protection Agency Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool is a fast, freely available, online screening application that allows researchers and regulators to extrapolate toxicity information across species. For biological targets in model systems such as human cells, mice, rats, and zebrafish, toxicity data are available for a variety of chemicals. Through the evaluation of protein target conservation, this tool can be used to extrapolate data generated from such model systems to thousands of other species lacking toxicity data, yielding predictions of relative intrinsic chemical susceptibility. The latest releases of the tool (versions 2.0-6.1) have incorporated new features that allow for the rapid synthesis, interpretation, and use of the data for publication plus presentation-quality graphics. Among these features are customizable data visualizations and a comprehensive summary report designed to summarize SeqAPASS data for ease of interpretation. This paper describes the protocol to guide users through submitting jobs, navigating the various levels of protein sequence comparisons, and interpreting and displaying the resulting data. New features of SeqAPASS v2.0-6.0 are highlighted. Furthermore, two use-cases focused on transthyretin and opioid receptor protein conservation using this tool are described. Finally, SeqAPASS' strengths and limitations are discussed to define the domain of applicability for the tool and highlight different applications for cross-species extrapolation.

Standards to support an enduring capability in wastewater surveillance for public health: Where are we?

The COVID-19 pandemic highlighted a wide range of public health system challenges for infectious disease surveillance. The discovery that the SARS-CoV-2 virus was shed in feces and can be characterized using PCR-based testing of sewage samples offers new possibilities and challenges for wastewater surveillance (WWS). However, WWS standardization of practices is needed to provide actionable data for a public health response. A workshop was convened consisting of academic, federal government, and industry stakeholders. The objective was to review WWS sampling protocols, testing methods, analyses, and data interpretation approaches for WWS employed nationally and identify opportunities for standardizing practices, including the development of documentary standards or reference materials in the case of SARS-CoV-2 surveillance. Other WWS potential future threats to public health were also discussed. Several aspects of WWS were considered and each offers the opportunity for standards development. These areas included sampling strategies, analytical methods, and data reporting practices. Each of these areas converged on a common theme, the challenge of results comparability across facilities and jurisdictions. For sampling, the consensus solution was the development of documentary standards to guide appropriate sampling practices. In contrast, the predominant opportunity for analytical methods was reference material development, such as PCR-based standards and surrogate recovery controls. For data reporting practices, the need for establishing the minimal required metadata, a metadata vocabulary, and standardizing data units of measure including measurement threshold definitions was discussed. Beyond SARS-CoV-2 testing, there was general agreement that the WWS platform will continue to be a valuable tool for a wide range of public health threats and that future cross-sector engagements are needed to guide an enduring WWS capability.

Assessment of Commonly Measured Wastewater Parameters to Estimate Sewershed Populations for Use in Wastewater-Based Epidemiology: Insights into Population Dynamics in New York City during the COVID-19 Pandemic

Understanding per capita rates of disease incidence or prevalence from wastewater surveillance data requires an estimate of the population contributing to wastewater samples, given that populations in large urban areas are dynamic, especially if major events, such as the onset of the COVID-19 pandemic, cause large population shifts. To assess whether commonly measured wastewater parameters can be used to estimate sewershed populations, we used wastewater data collected from New York City's (NYC) 14 wastewater treatment facilities to evaluate the relationship between influent loads of four wastewater parameters-ammonia, total Kjeldahl nitrogen, total suspended solids, and five-day carbonaceous biochemical oxygen demand-and census-based population estimates of the corresponding sewersheds during 2019, when populations were assumed to be relatively stable. Ammonia mass load had the most consistent relationship with sewershed population, regardless of wet weather contributions to NYC's predominantly combined sewer system. Changes in ammonia loads due to COVID-19 restrictions enacted in March 2020 generally reflected population shifts in sewersheds serving areas of Manhattan and Brooklyn, for which previous studies report decreased commuter mobility and residential populations. Our findings highlight the utility of ammonia mass load in influent wastewater as a population indicator to normalize wastewater-based epidemiology data and track sewershed population dynamics.

Monitoring human arboviral diseases through wastewater surveillance: Challenges, progress and future opportunities

Arboviral diseases are caused by a group of viruses spread by the bite of infected arthropods. Amongst these, dengue, Zika, west nile fever and yellow fever cause the greatest economic and social impact. Arboviral epidemics have increased in frequency, magnitude and geographical extent over the past decades and are expected to continue increasing with climate change and expanding urbanisation. Arboviral prevalence is largely underestimated, as most infections are asymptomatic, nevertheless existing surveillance systems are based on passive reporting of loosely defined clinical syndromes with infrequent laboratory confirmation. Wastewater-based surveillance (WBS), which has been demonstrated to be useful for monitoring diseases with significant asymptomatic populations including COVID19 and polio, could be a useful complement to arboviral surveillance. We review the current state of knowledge and identify key factors that affect the feasibility of monitoring arboviral diseases by WBS to include viral shedding loads by infected persons, the persistence of shed arboviruses and the efficiency of their recovery from sewage. We provide a simple model on the volume of wastewater that needs to be processed for detection of arboviruses, in face of lower arboviral shedding rates. In all, this review serves to reflect on the key challenges that need to be addressed and overcome for successful implementation of arboviral WBS.

Oxidative Stress Indices Changes in the Hearts of Rat Pups in Response to Maternal Buprenorphine Treatment during Gestation and Lactation

This study aimed to assess the effects of Buprenorphine (BUP) on oxidative parameters in pups born to mothers exposed to the drug during gestation and lactation. Pregnant and lactating rats received BUP, 0.5 or 0.1 mg/kg subcutaneously for 21 and 28 days, respectively. At the end of the study, the pups were anesthetized, and the hearts were dissected out to measure oxidative stress indices, including the levels of Malondialdehyde (MDA), Nitric oxide (NO), Glutathione (GSH), and the activity of Superoxide dismutase (SOD). Our findings indicated that BUP did not alter MDA, NO, GSH levels, nor SOD activity in the cardiac tissue of pups exposed to this drug during the fetal period and through breast milk. We suggest performing additional studies to determine the association between BUP and oxidative modifications in cardiac tissues of pups born to mothers under BUP therapy during gestation and lactation.

Identification of biomarkers in wastewater-based epidemiology: Main approaches and analytical methods

Wastewater-based epidemiology (WBE) has become popular to estimate the use of drugs of abuse and recently to establish the incidence of CoVID 19 in large cities. However, its possibilities have been expanded recently as a technique that allows to establish a fingerprint of the characteristics of a city, such as state of health/disease, healthy/unhealthy living habits, exposure to different types of contaminants, etc. with respect to other cities. This has been thanks to the identification of human biomarkers as well as to the fingerprinting and profiling of the characteristics of the wastewater catchment that determine these circumstances. The purpose of this review is to analyze the different methodological schemes that have been developed to perform this biomarker identification as well as the most characteristic analytical techniques in each scheme, their advantages and disadvantages and the knowledge gaps identified. We also discussed the future scope for development.

Current and future perspectives for wastewater-based epidemiology as a monitoring tool for pharmaceutical use

The medical and societal consequences of the misuse of pharmaceuticals clearly justify the need for comprehensive drug utilization research (DUR). Wastewater-based epidemiology (WBE) employs the analysis of human metabolic excretion products in wastewater to monitor consumption patterns of xenobiotics at the population level. Recently, WBE has demonstrated its potential to evaluate lifestyle factors such as illicit drug, alcohol and tobacco consumption at the population level, in near real-time and with high spatial and temporal resolution. Up until now there have been fewer WBE studies investigating health biomarkers such as pharmaceuticals. WBE publications monitoring the consumption of pharmaceuticals were systematically reviewed from three databases (PubMed, Web of Science and Google Scholar). 64 publications that reported population-normalised mass loads or defined daily doses of pharmaceuticals were selected. We document that WBE could be employed as a complementary information source for DUR. Interest in using WBE approaches for monitoring pharmaceutical use is growing but more foundation research (e.g. compound-specific uncertainties) is required to link WBE data to routine pharmacoepidemiologic information sources and workflows. WBE offers the possibility of i) estimating consumption of pharmaceuticals through the analysis of human metabolic excretion products in wastewater; ii) monitoring spatial and temporal consumption patterns of pharmaceuticals continuously and in near real-time; and iii) triangulating data with other DUR information sources to assess the impacts of strategies or interventions to reduce inappropriate use of pharmaceuticals.

"Waste Not, Want Not" - Leveraging Sewer Systems and Wastewater-Based Epidemiology for Drug Use Trends and Pharmaceutical Monitoring

During the current global COVID-19 pandemic and opioid epidemic, wastewater-based epidemiology (WBE) has emerged as a powerful tool for monitoring public health trends by analysis of biomarkers including drugs, chemicals, and pathogens. Wastewater surveillance downstream at wastewater treatment plants provides large-scale population and regional-scale aggregation while upstream surveillance monitors locations at the neighborhood level with more precise geographic analysis. WBE can provide insights into dynamic drug consumption trends as well as environmental and toxicological contaminants. Applications of WBE include monitoring policy changes with cannabinoid legalization, tracking emerging illicit drugs, and early warning systems for potent fentanyl analogues along with the resurging wave of stimulants (e.g., methamphetamine, cocaine). Beyond drug consumption, WBE can also be used to monitor pharmaceuticals and their metabolites, including antidepressants and antipsychotics. In this manuscript, we describe the basic tenets and techniques of WBE, review its current application among drugs of abuse, and propose methods to scale and develop both monitoring and early warning systems with respect to measurement of illicit drugs and pharmaceuticals. We propose new frontiers in toxicological research with wastewater surveillance including assessment of medication assisted treatment of opioid use disorder (e.g., buprenorphine, methadone) in the context of other social burdens like COVID-19 disease.

Implementing building-level SARS-CoV-2 wastewater surveillance on a university campus

The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long-term care facilities, schools, and residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater-based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university's fall residential semester. In multiple cases, wastewater surveillance enabled the identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in the identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.

Implementing building-level SARS-CoV-2 wastewater surveillance on a university campus

The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long-term care facilities, schools, and residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater-based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university's fall residential semester. In multiple cases, wastewater surveillance enabled the identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in the identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.

Methodological approaches for the prediction of opioid use-related epidemics in the United States: a narrative review and cross-disciplinary call to action

The opioid crisis in the United States has been defined by waves of drug- and locality-specific Opioid use-Related Epidemics (OREs) of overdose and bloodborne infections, among a range of health harms. The ability to identify localities at risk of such OREs, and better yet, to predict which ones will experience them, holds the potential to mitigate further morbidity and mortality. This narrative review was conducted to identify and describe quantitative approaches aimed at the "risk assessment," "detection" or "prediction" of OREs in the United States. We implemented a PubMed search composed of the: (1) objective (eg, prediction), (2) epidemiologic outcome (eg, outbreak), (3) underlying cause (ie, opioid use), (4) health outcome (eg, overdose, HIV), (5) location (ie, US). In total, 46 studies were included, and the following information extracted: discipline, objective, health outcome, drug/substance type, geographic region/unit of analysis, and data sources. Studies identified relied on clinical, epidemiological, behavioral and drug markets surveillance and applied a range of methods including statistical regression, geospatial analyses, dynamic modeling, phylogenetic analyses and machine learning. Studies for the prediction of overdose mortality at national/state/county and zip code level are rapidly emerging. Geospatial methods are increasingly used to identify hotspots of opioid use and overdose. In the context of infectious disease OREs, routine genetic sequencing of patient samples to identify growing transmission clusters via phylogenetic methods could increase early detection capacity. A coordinated implementation of multiple, complementary approaches would increase our ability to successfully anticipate outbreak risk and respond preemptively. We present a multi-disciplinary framework for the prediction of OREs in the US and reflect on challenges research teams will face in implementing such strategies along with good practices.

Analysis of 39 drugs and metabolites, including 8 glucuronide conjugates, in an upstream wastewater network via HPLC-MS/MS

Pharmaceutical compounds ingested by humans are metabolized and excreted in urine and feces. These metabolites can be quantified in wastewater networks using wastewater-based epidemiology (WBE) methods. Standard WBE methods focus on samples collected at wastewater treatment plants (WWTPs). However, these methods do not capture more labile classes of metabolites such as glucuronide conjugates, products of the major phase II metabolic pathway for drug elimination. By shifting sample collection more upstream, these unambiguous markers of human exposure are captured before hydrolysis in the wastewater network. In this paper, we present an HPLC-MS/MS method that quantifies 8 glucuronide conjugates in addition to 31 parent and other metabolites of prescription and synthetic opioids, overdose treatment drugs, illicit drugs, and population markers. Calibration curves for all analytes are linear (r2 > 0.98), except THC (r2 = 0.97), and in the targeted range (0.1-1,000 ng mL-1) with lower limits of quantification (S/N = 9) ranging from 0.098 to 48.75 ng mL-1. This method is fast with an injection-to-injection time of 7.5 min. We demonstrate the application of the method to five wastewater samples collected from a manhole in a city in eastern Massachusetts. Collected wastewater samples were filtered and extracted via solid-phase extraction (SPE). The SPE cartridges are eluted and concentrated in the laboratory via nitrogen-drying. The method and case study presented here demonstrate the potential and application of expanding WBE to monitoring labile metabolites in upstream wastewater networks.