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Previous studies show that SARS-CoV-2 waste shedding rates vary by community and are influenced by multiple factors; however, differences in shedding rates across multiple variants have yet to be evaluated. The purpose of this work is to build on previous research that evaluated waste shedding rates for early SARS-CoV-2 and the Delta variant, and update population level waste shedding rates for the more-recent Omicron variant in six communities. Mean SARS-CoV-2 waste shedding rates were found to increase with the predominance of the Delta variant and subsequently decrease with Omicron infections. Interestingly, the Delta stage had the highest mean shedding rates and was associated with the most severe disease symptoms reported in other clinical studies, while Omicron, exhibiting reduced symptoms, had the lowest mean shedding rates. Additionally, shedding rates were most consistent across communities during the Omicron stage. This is the first paper to identify waste shedding rates specific to the Omicron variant and fills a knowledge gap critical to disease prevalence modeling.

Domestic cats, an important companion animal, can be infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). This has aroused concern regarding the ability of domestic cats to spread the virus that causes coronavirus disease 2019. We systematically demonstrated the pathogenesis and transmissibility of SARS-CoV-2 in cats. Serial passaging of the virus between cats dramatically attenuated the viral transmissibility, likely owing to variations of the amino acids in the receptor-binding domain sites of angiotensin-converting enzyme 2 between humans and cats. These findings provide insight into the transmissibility of SARS-CoV-2 in cats and provide information for protecting the health of humans and cats. Article Summary Line: Domestic cats are susceptible to SARS-CoV-2 and have attenuated transmissibility after serial passaging.

Humans, animals, and the environment face a universal crisis: antimicrobial resistance (AR). Addressing AR and its multi-disciplinary causes across many sectors including in human and veterinary medicine remains underdeveloped. One barrier to AR efforts is an inconsistent process to incorporate the plenitude of stakeholders about what AR is and how to stifle its development and spread—especially stakeholders from the animal agriculture sector, one of the largest purchasers of antimicrobial drugs. In 2019, The Wellcome Trust released Reframing Resistance: How to communicate about antimicrobial resistance effectively (Reframing Resistance), which proposed the need to establish a consistent and harmonized messaging effort that describes the AR crisis and its global implications for health and wellbeing across all stakeholders. Yet, Reframing Resistance does not specifically engage the animal agriculture community. This study investigates the gap between two principles recommended by Reframing Resistance and animal agriculture stakeholders. For this analysis, the research group conducted 31 semi-structured interviews with a diverse group of United States animal agriculture stakeholders. Participants reported attitudes, beliefs, and practices about a variety of issues, including how they defined AR and what entities the AR crisis impacts most. Exploration of Reframing Resistance’s Principle 2, “explain the fundamentals succinctly” and Principle 3, “emphasis that this is universal issue; it can affect anyone, including you” reveals disagreement in both the fundamentals of AR and consensus of “who” the AR crisis impacts. Principle 2 may do better to acknowledge that animal agriculture stakeholders espouse a complex array of perspectives that cannot be summed up in a single perspective or principle. As a primary tool to combat AR, behavior change must be accomplished first through outreach to stakeholder groups and understanding their perspectives.

Measurement error, although ubiquitous, is uncommonly acknowledged and rarely assessed or corrected in epidemiologic studies. This review offers a straightforward guide to common problems caused by measurement error in research studies and a review of several accessible bias-correction methods for epidemiologists and data analysts. Although most correction methods require criterion validation including a gold standard, there are also ways to evaluate the impact of measurement error and potentially correct for it without such data. Technical difficulty ranges from simple algebra to more complex algorithms that require expertise, fine tuning, and computational power. However, at all skill levels, software packages and methods are available and can be used to understand the threat to inferences that arises from imperfect measurements.

Carbapenem-resistant Acinetobacter baumannii (CRAB), an opportunistic pathogen primarily associated with hospital-acquired infections, is an urgent public health threat (1). In health care facilities, CRAB readily contaminates the patient care environment and health care providers' hands, survives for extended periods on dry surfaces, and can be spread by asymptomatically colonized persons; these factors make CRAB outbreaks in acute care hospitals difficult to control (2,3). On May 28, 2020, a New Jersey hospital (hospital A) reported a cluster of CRAB infections during a surge in patients hospitalized with coronavirus disease 2019 (COVID-19). Hospital A and the New Jersey Department of Health (NJDOH) conducted an investigation, and identified 34 patients with hospital-acquired multidrug-resistant CRAB infection or colonization during February-July 2020, including 21 (62%) who were admitted to two intensive care units (ICUs) dedicated to caring for COVID-19 patients. In late March, increasing COVID-19-related hospitalizations led to shortages in personnel, personal protective equipment (PPE), and medical equipment, resulting in changes to conventional infection prevention and control (IPC) practices. In late May, hospital A resumed normal operations, including standard IPC measures, as COVID-19 hospitalizations decreased, lessening the impact of personnel and supply chain shortages on hospital functions. CRAB cases subsequently returned to a pre-COVID-19 baseline of none to two cases monthly. The occurrence of this cluster underscores the potential for multidrug-resistant organisms (MDROs) to spread during events when standard hospital practices might be disrupted; conventional IPC strategies should be reinstated as soon as capacity and resources allow.

Antimicrobial use (AMU) in animal agriculture contributes to antimicrobial resistance (AMR) in humans, which imposes significant health and economic costs on society. Economists call these costs negative externalities, societal costs that are not properly reflected in market prices. We review the relevant literature and develop a model to quantify the external costs of AMU in animal agriculture on AMR in humans. Parameters required for this estimate include ( a) the health and economic burden of AMR in humans,( b) the impact of AMU in animal agriculture on AMR in animals, ( c) the fraction of AMR in humans attributable to animal agriculture, and ( d) AMU in animals. We use a well-documented historic case to estimate an externality cost of about US$1,500 per kilogram of fluoroquinolones administered in US broiler chicken production. Enhanced data collection, particularly on the third and fourth parameters, is urgently needed to quantify more fully the externalities of AMU in animal agriculture.

Wastewater-based epidemiology (WBE) has been utilized as an early warning tool to anticipate disease outbreaks, especially during the COVID-19 pandemic. However, COVID-19 disease models built from wastewater-collected data have been limited by the complexities involved in estimating SARS-CoV-2 fecal shedding rates. In this study, wastewater from six municipalities in Arizona and Florida with distinct demographics were monitored for SARS-CoV-2 RNA between September 2020 and December 2021. Virus concentrations with corresponding clinical case counts were utilized to estimate community-wide fecal shedding rates that encompassed all infected individuals. Analyses suggest that average SARS-CoV-2 RNA fecal shedding rates typically occurred within a consistent range (7.53-9.29 log

Infectious disease surveillance systems support early warning, promote preparedness, and inform public health response. Pathogens that have human, animal, and environmental reservoirs should be monitored through systems that incorporate a One Health approach. In 2016, Thailand's federal government piloted an avian influenza (AI) surveillance system that integrates stakeholders from human, animal, and environmental sectors, at the central level and in four provinces to monitor influenza A viruses within human, waterfowl, and poultry populations. This research aims to describe and evaluate Thailand's piloted AI surveillance system to inform strategies for strengthening and building surveillance systems relevant to One Health. We assessed this surveillance system using the United States Centers for Disease Control and Prevention's (U.S. CDC) "Guidelines for Evaluating Public Health Surveillance Systems" and added three novel metrics: transparency, interoperability, and security. In-depth key informant interviews were conducted with representatives among six Thai federal agencies and departments, the One Health coordinating unit, a corporate poultry producer, and the Thai Ministry of Public Health-U.S. CDC Collaborating Unit. Thailand's AI surveillance system demonstrated strengths in acceptability, simplicity, representativeness, and flexibility, and exhibited challenges in data quality, stability, security, interoperability, and transparency. System efforts may be strengthened through increasing laboratory integration, improving pathogen detection capabilities, implementing interoperable systems, and incorporating sustainable capacity building mechanisms. This innovative piloted surveillance system provides a strategic framework that can be used to develop, integrate, and bolster One Health surveillance approaches to combat emerging global pathogen threats and enhance global health security.

Humans, animals, and the environment face a universal crisis: antimicrobial resistance (AR). Addressing AR and its multi-disciplinary causes across many sectors including in human and veterinary medicine remains underdeveloped. One barrier to AR efforts is an inconsistent process to incorporate the plenitude of stakeholders about what AR is and how to stifle its development and spread—especially stakeholders from the animal agriculture sector, one of the largest purchasers of antimicrobial drugs. In 2019, The Wellcome Trust released Reframing Resistance: How to communicate about antimicrobial resistance effectively (Reframing Resistance), which proposed the need to establish a consistent and harmonized messaging effort that describes the AR crisis and its global implications for health and wellbeing across all stakeholders. Yet, Reframing Resistance does not specifically engage the animal agriculture community. This study investigates the gap between two principles recommended by Reframing Resistance and animal agriculture stakeholders. For this analysis, the research group conducted 31 semi-structured interviews with a diverse group of United States animal agriculture stakeholders. Participants reported attitudes, beliefs, and practices about a variety of issues, including how they defined AR and what entities the AR crisis impacts most. Exploration of Reframing Resistance’s Principle 2, “explain the fundamentals succinctly” and Principle 3, “emphasis that this is universal issue; it can affect anyone, including you” reveals disagreement in both the fundamentals of AR and consensus of “who” the AR crisis impacts. Principle 2 may do better to acknowledge that animal agriculture stakeholders espouse a complex array of perspectives that cannot be summed up in a single perspective or principle. As a primary tool to combat AR, behavior change must be accomplished first through outreach to stakeholder groups and understanding their perspectives.

Wastewaters routinely contain antibiotic-resistant bacteria (ARB) and genes (ARG) that are removed to a varying degree during wastewater treatment. This study investigated the removal of the erythromycin ribosome methylase class F (erm(F)) and class 1 integron-integrase (intI1) genes at each stage from two water resource recovery facilities in southern Arizona. Although genes were significantly reduced by Bardenpho treatment, erm(F) and intI1 were still observed in ≥ 9 and 7 out of 12 secondary effluent samples. Primary processes via sedimentation or dissolved air flotation, as well as chlorine disinfection, did not significantly impact erm(F) and intI1 concentrations. Therefore, Bardenpho treatment was critical to reduce erm(F) and intI1. Concentrations of erm(F) and intI1 were compared with each other and other markers for anthropogenic pollution. Results from this study support intI1 as one suitable marker to measure erythromycin resistance genes in wastewater, as intI1 was found at higher concentrations, persisted more throughout treatment, and correlated with erm(F) at nearly every treatment stage. PRACTITIONER POINTS: Bardenpho treatment was the key process responsible for the reduction of intI1 and erm(F) genes during wastewater treatment. Primary treatment and chlorine disinfection did not impact erm(F) and intI1 gene concentrations. The intI1 gene is a suitable marker for measuring erm(F) genes in wastewater.

Background: During food animal production, animals are exposed to, colonized by, and sometimes infected with bacteria that may contaminate animal products with susceptible and multidrug-resistant organisms (MDRO). The United States’ Organic Foods Production Act resulted in decreased antibiotic use in some animal production operations. Some studies have reported that decreased antibiotic use is associated with reduced MDRO on meat. Objectives: The aim of this study was to investigate associations of meat production and processing methods with MDRO and overall bacterial contamination of retail meats. Methods: Bacterial contamination data from 2012 to 2017 for chicken breast, ground beef, ground turkey, and pork chops were downloaded from the National Antimicrobial Resistance Monitoring System. Poisson regression models with robust variance were used to estimate associations with MDRO contamination and any contamination (adjusted for year and meat type) overall, and according to bacteria genus (Salmonella, Campylobacter, Enterococcus, Escherichia coli) and meat type. Results: A total of 39,349 retail meat samples were linked to 216 conventional, 123 split (conventional and organic), and three organic processing facilities. MDRO contamination was similar in conventionally produced meats processed at split vs. conventional facilities but was significantly lower in organically produced meats processed at split facilities [adjusted prevalance ratio (aPR)=0.43; 95% CI: 0.30, 0.63]. Meat processed by split vs. conventional processors had higher or similar MDRO contamination for all tested bacterial genera except Campylobacter (aPR=0.29; 95% CI: 0.13, 0.64). The prevalence of any contamination was lower in samples processed at split vs. conventional facilities for aggregated samples (aPR=0.70; 95% CI: 0.68, 0.73) and all meat types and bacterial genera. Discussion: Organically produced and processed retail meat samples had a significantly lower prevalence of MDRO than conventionally produced and processed samples had, whereas meat from split processors had a lower prevalence of any contamination than samples from conventional processors had. Additional studies are needed to confirm findings and clarify specific production and processing practices that might explain them. https://doi.org/10.1289/EHP7327

Wastewater-based epidemiology (WBE) was utilized to monitor SARS-CoV-2 RNA in sewage collected from manholes specific to individual student dormitories (dorms) at the University of Arizona in the fall semester of 2020, which led to successful identification and reduction of SARS-CoV-2 transmission events. Positive wastewater samples triggered clinical testing of residents within that dorm; thus, SARS-CoV-2 infected individuals were identified regardless of symptom expression. This current study examined clinical testing data to determine the abundance of asymptomatic versus symptomatic cases in these defined communities. Nasal and nasopharyngeal swab samples processed via antigen and PCR tests indicated that 79.2% of SARS-CoV-2 infections were asymptomatic, and only 20.8% of positive cases reported COVID-19 symptoms at the time of testing. Clinical data was paired with corresponding wastewater virus concentrations, which enabled calculation of viral shedding rates in feces per infected person. Mean shedding rates averaged from positive wastewater samples across all dorms were 7.30 ± 0.67 log10 genome copies per gram of feces (gc/g-feces) based on the N1 gene. Quantification of SARS-CoV-2 fecal shedding rates from infected individuals has been the critical missing component necessary for WBE models to measure and predict SARS-CoV-2 infection prevalence in communities. The findings from this study can be utilized to create models that can be used to inform public health prevention and response actions., Graphical abstract Unlabelled Image

The University of Arizona utilized wastewater-based epidemiology paired with clinical testing as a surveillance strategy to monitor COVID-19 prevalence in a dormitory community. Positive SARS-CoV-2 RNA detection in wastewater led to prompt testing of all residents and the identification and isolation of three infected individuals which averted potential disease transmission.TextWastewater-based epidemiology (WBE) utilizes concentrations of SARS-CoV-2 in sewage to monitor population-level COVID-19 infections(1–3). Currently, WBE is a promising indicator to support public health decisions(3,4). In this case study, WBE was used to detect a COVID-19 outbreak in a student dormitory (henceforth Dorm A) at the University of Arizona (UArizona).The StudyUArizona incorporated wastewater surveillance as a potential early-warning tool for COVID-19 outbreaks on campus. Grab samples (1L) were collected from a sewer manhole specific to Dorm A, between August 18-31 to monitor SARS-CoV-2 RNA in wastewater. Upon positive detection of viral RNA in wastewater samples, clinical testing was conducted on every individual living in the dorm. UArizona performed two clinical testing modalities, antigen (1 hour turnaround) test via anterior nasal swab and RT-PCR (48-72 hour turnaround) via nasopharyngeal swab samples. Individuals were subject to clinical testing via two routes: Campus Health Services (CHS) if experiencing symptoms or Test All Test Smart (TATS) regardless of symptoms. Refer to Appendix for method details.Article Summary LineWastewater-based epidemiology with subsequent clinical testing identified individuals infected with COVID-19 living in a dormitory and further spread of disease was prevented with public health action.

Direct-to-consumer food marketing is a growing niche in the United States food supply chain. Food animal producers who use direct marketing may employ different production models and standard practices from producers selling animal products to the conventional food system. Direct-to-consumer food supply chains (generally and specifically regarding food animal products) are relatively unexplored in food safety and health research. We conducted a cross-sectional, market-basket analysis of the Maryland direct-to-consumer poultry supply chain to assess food safety. We analyzed 40 direct-to-consumer commercial poultry meat products (one product per farm) forEscherichia coli, Staphylococcus aureusandSalmonella spp.using culture-based methods. Isolates underwent antimicrobial susceptibility testing.E. coliandS. aureuswere recovered from 9/40 (23%) and 12/40 (30%) of poultry meat samples, respectively. Of interest for comparing direct-market and mainstream supply chains for food safety risks, noSalmonellaisolates were recovered from any direct-market sampled poultry products and no multidrug resistance was observed inE. coliandS. aureusisolates. Microbial outcomes were compared to a survey of poultry production and processing practices within the same study population.ImportanceThis study demonstrates substantially lower rates of antimicrobial-resistant (AMR) microbial pathogens in the market-basket products from Maryland direct-market broiler poultry supply chain compared to rates of AMR in the conventional supply chain for similar retail meat products from NARMS. We further describe the landscape of the statewide supply chain for direct-market poultry, focusing on characteristics related to risk management strategies applied to microbial food safety. These findings are of public health significance for both the research and policy communities; these data provide an initial evidence base for more targeted research evaluating potential risk factors for microbial food safety in the direct-to-consumer supply chain. These data will also assist the Maryland Department of Agriculture and other state-level agencies with oversight of food safety issues to guide policy efforts for direct-market poultry production and sales.

Wastewater-based epidemiology has potential as an early-warning tool for determining the presence of COVID-19 in a community. The University of Arizona (UArizona) utilized WBE paired with clinical testing as a surveillance tool to monitor the UArizona community for SARS-CoV-2 in near real-time, as students re-entered campus in the fall. Positive detection of virus RNA in wastewater lead to selected clinical testing, identification, and isolation of three infected individuals (one symptomatic and two asymptomatic) that averted potential disease transmission. This case study demonstrated the value of WBE as a tool to efficiently utilize resources for COVID-19 prevention and response. Thus, WBE coupled with targeted clinical testing was further conducted on 13 dorms during the course of the Fall semester (Table 3). In total, 91 wastewater samples resulted in positive detection of SARS-CoV-2 RNA that successfully provided an early-warning for at least a single new reported case of infection (positive clinical test) among the residents living in the dorm. Overall, WBE proved to be an accurate diagnostic for new cases of COVID-19 with an 82.0% positive predictive value and an 88.9% negative predictive value. Increases in positive wastewater samples and clinical tests were noted following holiday-related activities. However, shelter-in-place policies proved to be effective in reducing the number of daily reported positive wastewater and clinical tests. This case study provides evidence for WBE paired with clinical testing and public health interventions to effectively contain potential outbreaks of COVID-19 in defined communities., Graphical abstract Unlabelled Image