Norovirus is the leading cause of acute gastroenteritis worldwide, responsible for up to 90% of viral gastroenteritis outbreaks and an estimated 10.6 billion USD in annual economic losses in the U.S. Despite its well-documented seasonality, wastewater surveillance in the Eastern Upper Peninsula of Michigan reveals persistent GI norovirus detection year-round, diverging from national clinical trends that consistently show far greater GII prevalence. To characterize norovirus dynamics in this region, 250 mL wastewater influent grab samples were collected once per week across 14 sites, concentrated using a PEG-based method, and analyzed via digital droplet PCR (ddPCR) for GI and GII concentrations. Across the study period, the rate of positive sites per month ranged from 57 to 100% for GI and 74 to 97% for GII, with mean positivity rates of 85.4% (GI) and 88.7% (GII), indicating that both genogroups were detected frequently at comparable levels. GI was more prevalent in winter and spring (December–May), whereas GII was more prevalent during spring and summer (March–August). Mean GI gene copies per 100 mL ranged from 12,898 (October) to 532,792 (February), while mean GII concentrations ranged from 29,806 (December) to 1,100,215 (May). These patterns contrast with national clinical data, where GI contributes to a small minority of reported norovirus cases. This study explores potential environmental and behavioral factors contributing to this regional pattern. GI norovirus demonstrates greater resistance to wastewater treatment and environmental stability, which may facilitate its persistence in the region. Additionally, congregate living settings, such as college campuses and correctional facilities, may contribute to sustained GI prevalence through foodborne transmission and asymptomatic viral shedding. Overall, these findings suggest that environmental and social factors influence norovirus seasonality and genogroup distribution in this region, underscoring the need for improved monitoring and expanded multi-site wastewater and epidemiological research to better understand norovirus persistence in similar communities.

Sports drinks, also known as electrolyte drinks, are a popular beverage choice among consumers and come in a wide variety of flavors and electrolyte compositions. They may vary substantially in their additives, which typically include sweeteners, coloring agents, flavoring agents, and additional vitamins and nutrients. The determination of electrolyte elements is important for accurate product labeling and quality control; however, conventional instrumentation, such as inductively coupled plasma optical emission spectroscopy (ICP-OES), may be costly to both acquire and operate, especially given its relatively high consumption of argon gas. Here we present a rapid and cost-effective method using microwave plasma atomic emission spectroscopy (MP-AES), which utilizes a nitrogen plasma that may be supplied with either a conventional gas source (dewar or cylinder gas) or a nitrogen generator on-site. Using a simple “dilute and shoot” method, electrolyte elements can be determined without prior sample digestion with good reproducibility and excellent limits of detection across a variety of sample matrices. Thus, MP-AES offers a simple multi-element alternative to ICP-OES for sports drink analysis without costly argon consumption.

This study explores the integration of genome sequencing and digital droplet polymerase chain reaction (ddPCR)-based methods for tracking the diversity of COVID-19 variants in wastewater. The research focuses on monitoring various Omicron subvariants during a period of significant viral evolution. Genome sequencing, particularly using Oxford Nanopore Technology (ONT), provides a detailed view of emerging variants, surpassing the limitations of PCR-based detection kits that rely on known sequences. Of the 43 samples analyzed, 39.5% showed matching results between the GT Molecular ddPCR kits and sequencing, though only 4% were exact matches. Some mismatches occurred due to newer subvariants like XBB and BQ.1, which the ddPCR kits could not detect. This emphasized the limitations of ddPCR kits, which rely on known variant sequences, while sequencing provides real-time data on emerging variants, offering a more comprehensive view of circulating strains. This study highlights the effectiveness of combining these methodologies to enhance early detection and inform public health strategies, especially in regions with limited clinical sequencing capabilities.

With the recent legalization of cannabis in multiple jurisdictions and widespread use as a medical treatment, there has been an increased focus on product safety and the potential impacts of contaminants on human health. One factor that has received little attention is the possible exposure to potentially hazardous levels of toxic elements from rolling (smoking) papers. The elemental composition of rolling papers is largely unregulated, with a minority of jurisdictions regulating papers only when they are part of a final cannabis product. This study reports the concentrations of 26 elements in commercially available rolling papers and estimates potential maximum exposures relative to USP232 and ICH Q3D dosages in pharmaceutical compounds. Exposure estimates indicate that the concentrations of several elements in some products, particularly Cu, Cr, and V, may present a potential hazard to frequent users. Several elements, including Ag, Ca, Ba, Cu, Ti, Cr, Sb, and possibly others, are likely present in elevated quantities in some papers due to product design and manufacturing processes. Our results further suggest that Cu-based pigments are used by a number of manufacturers and that regular use of these products might result in exposures as high as 4.5-11 times the maximum exposure limits. Further research to quantify the contribution of rolling papers to elemental exposure under realistic smoking conditions is warranted.

The rapid growth of the cannabis market in the United States has led to increasing focus on the consumer product safety of the myriad of new products entering commerce. The cannabis plant is widely accepted to be an efficient accumulator of potentially toxic elements, and its resinous nature makes it well suited to accumulate surface contaminants. Unfortunately, limited data are currently available on the occurrence of many elements in consumer cannabis, and even fewer studies have examined surface adhered particulate matter. As part of this study, 26 elements (silver, aluminum, arsenic, barium, beryllium, calcium, cadmium, cobalt, chromium, copper, iron, mercury, potassium, magnesium, manganese, molybdenum, sodium, nickel, lead, antimony, selenium, thorium, thallium, uranium, vanadium, and zinc) were quantified in hemp produced for cannabidiol and commercially available hemp marketed for smoking. Additionally, surface adhered particulate matter was examined as a potential contributor of elemental impurities, and various methodologies were compared. Results confirm that hemp entering commerce in the United States contains a variety of elemental impurities and frequently contains adhered particulate matter such as soil minerals, agricultural additives, microplastics/textile fibers, and materials from harvesting/processing equipment. Consumer exposure potential for some elements such as copper was found to be high enough to warrant additional investigation as to the possible health effects and may justify additional oversight from regulators, who should consider expanding testing panels to a larger suite of elements than arsenic, cesium, mercury, and lead.

The prevalence of COVID-19 in the community has become more difficult to gauge utilizing clinical testing due to a decrease in reported test results stemming from the availability of at-home test kits and a reduction in the number of cases seeking medical treatment. The purpose of this study was to examine the trend of diminishing correlation between reported clinical cases of COVID-19 and wastewater-based surveillance epidemiological data as home testing became available in the Eastern Upper Peninsula of Michigan. Wastewater grab samples were collected weekly from 16 regional locations from June 2021-December 2022. Samples were analyzed for SARS-CoV-2 N1 and N2 viral particles using reverse transcriptase digital droplet polymerase chain reaction (RT ddPCR). N1 and N2 gene copies were correlated with clinical cases. The t-test was used to determine correlation deterioration point. Clinical cases post-deterioration were calculated for high-correlated pre-deterioration locations using linear regression. Correlation between the wastewater-based surveillance of SARS-CoV-2 and reported clinical cases deteriorated after February 1, 2022. This corresponds with the timeframe in which commercially available at-home test kits became available in the United States. The increase in at-home testing for SARS-CoV-2 likely contributed to the decrease in reported clinical positive tests in early 2022, providing an unrealistic picture of the presence of Covid-19 in the community. As measures to reduce exposure such as personal masking, clinical testing, social isolating, and quarantining continue to decline, wastewater surveillance for the presence of SARS-CoV-2 may be the best method for public health professionals to remain aware of virus dynamics in localized regions. Time-series modeling adds another layer of information when clinical data is unobtainable or underreported.

This study explores the integration of genome sequencing and polymerase chain reaction (PCR) based methods for tracking the diversity of Covid-19 variants in wastewater. The research focuses on monitoring various Omicron subvariants during a period of significant viral evolution. Genome sequencing, particularly using Oxford Nanopore Technology (ONT), provides a detailed view of emerging variants, surpassing the limitations of PCR-based detection kits that rely on known sequences. This study highlights the effectiveness of combining these methodologies to enhance early detection and inform public health strategies, especially in regions with limited clinical sequencing capabilities.

Wastewater-based epidemiology is being used as a tool to monitor the spread of COVID-19 and provide an early warning for the presence or increase of clinical cases in a community. The majority of wastewater-based epidemiology for COVID-19 tracking has been utilized in sewersheds that service populations in the tens-to-hundreds of thousands. Few studies have been conducted to assess the usefulness of wastewater in predicting COVID-19 clinical cases specifically in rural areas. This study collected samples from 16 locations across the Eastern Upper Peninsula of Michigan from June to December 2021. Sampling locations included 12 rural municipalities, a Tribal housing community and casino, a public university, three municipalities that also contained a prison, and a small island with heavy tourist traffic. Samples were analyzed for SARS-CoV-2 N1, N2, and variant gene copies using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR). Wastewater N1 and N2 gene copies and clinical case counts were correlated to determine if wastewater results were predictive of clinical cases. Significant correlation between N1 and N2 gene copies and clinical cases was found for all sites (⍴= 0.89 to 0.48). N1 and N2 wastewater results were predictive of clinical case trends within 0-7 days. The Delta variant was detected in the Pickford and St. Ignace samples more than 12-days prior to the first reported Delta clinical cases in their respective counties. Locations with low correlation could be attributed to their high rates of tourism. This is further supported by the high correlation seen in the public university, which is a closed population. Long-term wastewater monitoring over a large, rural geographic area is useful for informing the public of potential outbreaks in the community regardless of asymptomatic cases and access to clinical testing.

The St. Marys River is the sole surface outlet from Lake Superior, flowing over 100 km to Lake Huron, and forming part of the international border between Canada (Ontario) and the United States (MI). The river system has been severely impacted by modifications to the hydrology as well as local industrial and municipal discharges, and was designated in 1985 as an Area of Concern (AOC). Since that time, sediments on the Canadian side of the river have been systematically re-sampled, but the US side of the river has received less attention. This paper discusses two recent projects, one completed in 2003 and one completed in 2005, that sought to revisit a variety of sediment localities within the St. Marys River to update sediment contaminant data, and to expand sampling into additional areas of interest on the US side of the border: Munuscong Lake at the southern end of the AOC, and the Little Rapids adjacent to Sugar Island. The primary focus was on surficial sediment contamination, particularly metals shown to be elevated during previous sampling (chromium, nickel, copper). Results show that while Cr, Ni and Cu contamination remains slightly elevated in surficial sediments at some sites in the St. Marys River, the overall trend shows metal concentrations declining to levels consistent with background levels in sediments found in Lake Superior, Whitefish Bay and the St. Marys River.