Wastewater-Based Epidemiology and Long-Read Sequencing to Identify Enterovirus Circulation in Three Municipalities in Maricopa County, Arizona, Southwest United States between June and October 2020

We used wastewater-based epidemiology and amplicon-based long-read high-throughput sequencing for surveillance of enteroviruses (EVs) in Maricopa County, Arizona, Southwest United States. We collected 48 samples from 13 sites in three municipalities between 18 June and 1 October 2020, and filtered (175 mL each; 0.45 µm pore size) and extracted RNA from the filter-trapped solids. The RNA was converted to cDNA and processed through two workflows (Sanger sequencing (SSW) and long-read Illumina sequencing (LRISW)) each including a nested polymerase chain reaction (nPCR) assay. We subjected the ~350 bp amplicon from SSW to Sanger sequencing and the ~1900–2400 bp amplicon from LRISW to Illumina sequencing. We identified EV contigs from 11 of the 13 sites and 41.67% (20/48) of screened samples. Using the LRISW, we detected nine EV genotypes from three species (Enterovirus A (CVA4, EV-A76, EV-A90), Enterovirus B (E14) and Enterovirus C (CVA1, CVA11, CVA13, CVA19 and CVA24)) with Enterovirus C representing approximately 90% of the variants. However, the SSW only detected the five Enterovirus C types. Similarity and phylogenetic analysis showed that multiple Enterovirus C lineages were circulating, co-infecting and recombining in the population during the season despite the SARS-CoV-2 pandemic and the non-pharmaceutical public health measures taken to curb transmission.

A Combined Digital PCR and Next Generation DNA-Sequencing Based Approach for Tracking Nearshore Pollutant Dynamics Along the Southwest United States/Mexico Border

Ocean currents, multiple fecal bacteria input sources, and jurisdictional boundaries can complicate pollution source tracking and associated mitigation and management efforts within the nearshore coastal environment. In this study, multiple microbial source tracking tools were employed to characterize the impact and reach of an ocean wastewater treatment facility discharge in Mexico northward along the coast and across the Southwest United States- Mexico Border. Water samples were evaluated for fecal indicator bacteria (FIB), Enterococcus by culture-based methods, and human-associated genetic marker (HF183) and Enterococcus by droplet digital polymerase chain reaction (ddPCR). In addition, 16S rRNA gene sequence analysis was performed and the SourceTracker algorithm was used to characterize the bacterial community of the wastewater treatment plume and its contribution to beach waters. Sampling dates were chosen based on ocean conditions associated with northern currents. Evidence of a gradient in human fecal pollution that extended north from the wastewater discharge across the United States/Mexico border from the point source was observed using human-associated genetic markers and microbial community analysis. The spatial extent of fecal contamination observed was largely dependent on swell and ocean conditions. These findings demonstrate the utility of a combination of molecular tools for understanding and tracking specific pollutant sources in dynamic coastal water environments.

Comparison of Aerosol Optical Depth from MODIS Product Collection 6.1 and AERONET in the Western United States

Recent observations reveal that dust storms are increasing in the western USA, posing imminent risks to public health, safety, and the economy. Much of the observational evidence has been obtained from ground-based platforms and the visual interpretation of satellite imagery from limited regions. Comprehensive satellite-based observations of long-term aerosol records are still lacking. In an effort to develop such a satellite aerosol dataset, we compared and evaluated the Aerosol Optical Depth (AOD) from Deep Blue (DB) and Dark Target (DT) product collection 6.1 with the Aerosol Robotic Network (AERONET) program in the western USA. We examined the seasonal and monthly average number of Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua DB AOD retrievals per 0.1∘×0.1∘ from January 2003 to December 2017 across the region’s different topographic, climatic, and land cover conditions. The number of retrievals in the southwest United States was on average greater than 37 days per 90 days for all seasons except summer. Springtime saw the highest number of AOD retrievals across the southwest, consistent with the peak season for synoptic-scale dust events. The majority of Arizona, New Mexico, and western Texas showed the lowest number of retrievals during the monsoon season. The majority of collocating domains of AOD from the Aqua sensor showed a better correlation with AERONET AOD than AOD from Terra, and the correlation coefficients exhibited large regional variability across the study area. The correlation coefficient between the couplings Aqua DB AOD-AERONET AOD and Terra DB AOD-AERONET AOD ranges from 0.1 to 0.94 and 0.001 to 0.94, respectively. In the majority of the sites that exhibited less than a 0.6 correlation coefficient and few matched data points at the nearest single pixel, the correlations gradually improved when the spatial domain increased to a 50 km × 50 km box averaging domain. In general, the majority of the stations revealed significant correlation between MODIS and AERONET AOD at all spatiotemporal aggregating domains, although MODIS generally overestimated AOD compared to AERONET. However, the correlation coefficient in the southwest United States was the lowest and in stations from a higher latitude was the highest. The difference in the brightness of the land surface and the latitudinal differences in the aerosol inputs from the forest fires and solar zenith angles are some of the factors that manifested the latitudinal correlation differences.

St. Louis Encephalitis Virus in the Southwestern United States: A Phylogeographic Case for a Multi-Variant Introduction Event

Since the reemergence of St. Louis Encephalitis (SLE) Virus (SLEV) in the Southwest United States, identified during the 2015 outbreak in Arizona, SLEV has been seasonally detected within Culex spp. populations throughout the Southwest United States. Previous work revealed the 2015 outbreak was caused by an importation of SLEV genotype III, which had only been detected previously in Argentina. However, little is known about when the importation occurred or the transmission and genetic dynamics since its arrival into the Southwest. In this study, we sought to determine whether the annual detection of SLEV in the Southwest is due to enzootic cycling or new importations. To address this question, we analyzed 174 SLEV genomes (142 sequenced as part of this study) using Bayesian phylogenetic analyses to estimate the date of arrival into the American Southwest and characterize the underlying population structure of SLEV. Phylogenetic clustering showed that SLEV variants circulating in Maricopa and Riverside counties form two distinct populations with little evidence of inter-county transmission since the onset of the outbreak. Alternatively, it appears that in 2019, Yuma and Clark counties experienced annual importations of SLEV that originated in Riverside and Maricopa counties. Finally, the earliest representatives of SLEV genotype III in the Southwest form a polytomy that includes both California and Arizona samples. We propose that the initial outbreak most likely resulted from the importation of a population of SLEV genotype III variants, perhaps in multiple birds, possibly multiple species, migrating north in 2013, rather than a single variant introduced by one bird.

Assessing Vegetation Response to Multi-Scalar Drought across the Mojave, Sonoran, Chihuahuan Deserts and Apache Highlands in the Southwest United States

Understanding the patterns and relationships between vegetation productivity and climatic conditions is essential for predicting the future impacts of climate change. Climate change is altering precipitation patterns and increasing temperatures in the Southwest United States. The large-scale and long-term effects of these changes on vegetation productivity are not well understood. This study investigates the patterns and relationships between seasonal vegetation productivity, represented by Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI), and the Standardized Precipitation Evapotranspiration Index (SPEI) across the Mojave, Sonoran, and Chihuahuan Deserts and the Apache Highlands of the Southwest United States over 16 years from 2000 to 2015. To examine the spatiotemporal gradient and response of vegetation productivity to dry and wet conditions, we evaluated the linear trend of different SPEI timescales and correlations between NDVI and SPEI. We found that all four ecoregions are experiencing more frequent and severe drought conditions in recent years as measured by negative SPEI trends and severe negative SPEI values. We found that changes in NDVI were more strongly correlated with winter rather than summer water availability. Investigating correlations by vegetation type across all four ecoregions, we found that grassland and shrubland productivity were more dependent on summer water availability whereas sparse vegetation and forest productivity were more dependent on winter water availability. Our results can inform resource management and enhance our understanding of vegetation vulnerability to climate change.