Correlates of Co-Infection with Coccidiosis and Avian Malaria in House Finches (Haemorhous mexicanus).

Pathogens have traditionally been studied in isolation within host systems; yet in natural settings they frequently coexist. This raises questions about the dynamics of co-infections and how host life-history traits might predict co-infection versus single infection. To address these questions, we investigated the presence of two parasites, a gut parasite (Isospora coccidians) and a blood parasite (Plasmodium spp.), in House Finches (Haemorhous mexicanus), a common passerine bird in North America. We then correlated these parasitic infections with various health and condition metrics, including hematological parameters, plasma carotenoids, lipid-soluble vitamins, blood glucose concentration, body condition, and prior disease history. Our study, based on 48 birds captured in Tempe, Arizona, US, in October 2021, revealed that co-infected birds exhibited elevated circulating lutein levels and a higher heterophil:lymphocyte ratio (H/L ratio) compared to those solely infected with coccidia Isospora spp. This suggests that co-infected birds experience heightened stress and may use lutein to bolster immunity against both pathogens, and that there are potentially toxic effects of lutein in co-infected birds compared to those infected solely with coccidia Isospora sp. Our findings underscore the synergistic impact of coparasitism, emphasizing the need for more co-infection studies to enhance our understanding of disease dynamics in nature, as well as its implications for wildlife health and conservation efforts.

Pan-Enterovirus Characterization Reveals Cryptic Circulation of Clinically Relevant Subtypes in Arizona Wastewater.

Background: Most seasonally circulating enteroviruses result in asymptomatic or mildly symptomatic infections. In rare cases, however, infection with some subtypes can result in paralysis or death. Of the 300 subtypes known, only poliovirus is reportable, limiting our understanding of the distribution of other enteroviruses that can cause clinical disease. Objective: The overarching objectives of this study were to: 1) describe the distribution of enteroviruses in Arizona during the late summer and fall of 2022, the time of year when they are thought to be most abundant, and 2) demonstrate the utility of viral pan-assay approaches for semi-agnostic discovery that can be followed up by more targeted assays and phylogenomics. Methods: This study utilizes pooled nasal samples collected from school-aged children and long-term care facility residents, and wastewater from multiple locations in Arizona during July-October of 2022. We used PCR to amplify and sequence a region common to all enteroviruses, followed by species-level bioinformatic characterization using the QIIME 2 platform. For Enterovirus-D68 (EV-D68), detection was carried out using RT-qPCR, followed by confirmation using near-complete whole EV-D68 genome sequencing using a newly designed tiled amplicon approach. Results: In the late summer and early fall of 2022, multiple enterovirus species were identified in Arizona wastewater, with Coxsackievirus A6, EV-D68, and Coxsackievirus A19 composing 86% of the characterized reads sequenced. While EV-D68 was not identified in pooled human nasal samples, and the only reported acute flaccid myelitis case in Arizona did not test positive for the virus, an in-depth analysis of EV-D68 in wastewater revealed that the virus was circulating from August through mid-October. A phylogenetic analysis on this relatively limited dataset revealed just a few importations into the state, with a single clade indicating local circulation. Significance: This study further supports the utility of wastewater-based epidemiology to identify potential public health threats. Our further investigations into EV-D68 shows how these data might help inform healthcare diagnoses for children presenting with concerning neurological symptoms.

Large Clusters of Invasive emm49 Group A Streptococcus Identified within and across Arizona Healthcare Facilities through Statewide Genomic Surveillance System, 2019-2021.

A statewide genomic surveillance system for invasive Group A Streptococcus was implemented in Arizona in June 2019, resulting in 1,046 isolates being submitted for genomic analysis to characterize emm-types and identify transmission clusters. Eleven of the 32 identified distinct emm-types comprised >80% of samples, with 29.7% of all isolates being typed as emm49 (and its genetic derivative emm151). Phylogenetic analysis initially identified an emm49 genomic cluster of four isolates that rapidly expanded over subsequent months (June 2019-February 2020). Public health investigations identified epidemiologic links with three different long-term care facilities, resulting in specific interventions. Unbiased genomic surveillance allowed for identification and response to clusters that would have otherwise remained undetected.

Lyssa excreta: Defining parameters for fecal samples as a rabies virus surveillance method.

It is not possible to systematically screen the environment for rabies virus (RABV) using current approaches. We sought to determine under what conditions RABV is detectable from feces and other accessible samples from infected wildlife to broaden the number of biological samples that could be used to test for RABV. We employed a recently-developed quantitative RT-PCR assay called the "LN34 panlyssavirus real-time RT-PCR assay", which is highly sensitive and specific for all variants of RABV. We harvested and tested brain tissue, fecal, and/or mouth swab samples from 25 confirmed RABV positive bats of six species. To determine if rabies RNA lasts in feces sufficiently long post-defecation to use it as a surveillance tool, we tested fecal samples from 10 bats at the time of sample collection and after 24 hours of exposure to ambient conditions, with an additional test on six bats out to 72 hours. To assess whether we could pool fecal pellets and still detect a positive, we generated dilutions of known positives at 1:1, 1:10, 1:50, and 1:200. For six individuals for which matched brain, mouth swab, and fecal samples were tested, results were positive for 100%, 67%, and 67%, respectively. For the first time test to 24 hours, 63% of feces that were positive at time 0 were still positive after 24 hours, and 50% of samples at 72 hours were positive across all three replicates. Pooling tests revealed that fecal positives were detected at 1:10 dilution, but not at 1:50 or 1:200. Our preliminary results suggest that fecal samples hold promise for a rapid and non-invasive environmental screening system.

Knockdown resistance mutations are common and widely distributed in Xenopsylla cheopis fleas that transmit plague in Madagascar.

BACKGROUND: Plague, caused by the bacterium Yersinia pestis, remains an important disease in Madagascar, where the oriental rat flea, Xenopsylla cheopis, is a primary vector. To control fleas, synthetic pyrethroids (SPs) have been used for >20 years, resulting in resistance in many X. cheopis populations. The most common mechanisms of SP resistance are target site mutations in the voltage-gated sodium channel (VGSC) gene. METHODOLOGY/PRINCIPAL FINDINGS: We obtained 25 collections of X. cheopis from 22 locations across Madagascar and performed phenotypic tests to determine resistance to deltamethrin, permethrin, and/or dichlorodiphenyltrichloroethane (DDT). Most populations were resistant to all these insecticides. We sequenced a 535 bp segment of the VGSC gene and identified two different mutations encoding distinct substitutions at amino acid position 1014, which is associated with knockdown resistance (kdr) to SPs in insects. Kdr mutation L1014F occurred in all 25 collections; a rarer mutation, L1014H, was found in 12 collections. There was a significant positive relationship between the frequency of kdr alleles and the proportion of individuals surviving exposure to deltamethrin. Phylogenetic comparisons of 12 VGSC alleles in Madagascar suggested resistant alleles arose from susceptible lineages at least three times. Because genotype can reasonably predict resistance phenotype, we developed a TaqMan PCR assay for the rapid detection of kdr resistance alleles. CONCLUSIONS/SIGNIFICANCE: Our study provides new insights into VGSC mutations in Malagasy populations of X. cheopis and is the first to report a positive correlation between VGSC genotypes and SP resistance phenotypes in fleas. Widespread occurrence of these two SP resistance mutations in X. cheopis populations in Madagascar reduces the viability of these insecticides for flea control. However, the TaqMan assay described here facilitates rapid detection of kdr mutations to inform when use of these insecticides is still warranted to reduce transmission of plague.

Biting midges (Diptera: Ceratopogonidae) as putative vectors of zoonotic Onchocerca lupi (Nematoda: Onchocercidae) in northern Arizona and New Mexico, southwestern United States.

Onchocerca lupi (Rodonaja, 1967) is an understudied, vector-borne, filarioid nematode that causes ocular onchocercosis in dogs, cats, coyotes, wolves, and is also capable of infecting humans. Onchocercosis in dogs has been reported with increasing incidence worldwide. However, despite the growing number of reports describing canine O. lupi cases as well as zoonotic infections globally, the disease prevalence in endemic areas and vector species of this parasite remains largely unknown. Here, our study aimed to identify the occurrence of O. lupi infected dogs in northern Arizona, New Mexico, and Utah, United States and identify the vector of this nematode. A total of 532 skin samples from randomly selected companion animals with known geographic locations within the Navajo Reservation were collected and molecularly surveyed by PCR for the presence of O. lupi DNA (September 2019-June 2022) using previously published nematode primers (COI) and DNA sequencing. O. lupi DNA was detected in 50 (9.4%) sampled animals throughout the reservation. Using positive animal samples to target geographic locations, pointed hematophagous insect trapping was performed to identify potential O. lupi vectors. Out of 1,922 insects screened, 38 individual insects and 19 insect pools tested positive for the presence of O. lupi, all of which belong to the Diptera family. This increased surveillance of definitive host and biological vector/intermediate host is the first large scale prevalence study of O. lupi in companion animals in an endemic area of the United States, and identified an overall prevalence of 9.4% in companion animals as well as multiple likely biological vector and putative vector species in the southwestern United States. Furthermore, the identification of these putative vectors in close proximity to human populations coupled with multiple, local zoonotic cases highlight the One Health importance of O. lupi.

Application of Phylodynamic Tools to Inform the Public Health Response to COVID-19: Qualitative Analysis of Expert Opinions.

BACKGROUND: In the wake of the SARS-CoV-2 pandemic, scientists have scrambled to collect and analyze SARS-CoV-2 genomic data to inform public health responses to COVID-19 in real time. Open source phylogenetic and data visualization platforms for monitoring SARS-CoV-2 genomic epidemiology have rapidly gained popularity for their ability to illuminate spatial-temporal transmission patterns worldwide. However, the utility of such tools to inform public health decision-making for COVID-19 in real time remains to be explored. OBJECTIVE: The aim of this study is to convene experts in public health, infectious diseases, virology, and bioinformatics-many of whom were actively engaged in the COVID-19 response-to discuss and report on the application of phylodynamic tools to inform pandemic responses. METHODS: In total, 4 focus groups (FGs) occurred between June 2020 and June 2021, covering both the pre- and postvariant strain emergence and vaccination eras of the ongoing COVID-19 crisis. Participants included national and international academic and government researchers, clinicians, public health practitioners, and other stakeholders recruited through purposive and convenience sampling by the study team. Open-ended questions were developed to prompt discussion. FGs I and II concentrated on phylodynamics for the public health practitioner, while FGs III and IV discussed the methodological nuances of phylodynamic inference. Two FGs per topic area to increase data saturation. An iterative, thematic qualitative framework was used for data analysis. RESULTS: We invited 41 experts to the FGs, and 23 (56%) agreed to participate. Across all the FG sessions, 15 (65%) of the participants were female, 17 (74%) were White, and 5 (22%) were Black. Participants were described as molecular epidemiologists (MEs; n=9, 39%), clinician-researchers (n=3, 13%), infectious disease experts (IDs; n=4, 17%), and public health professionals at the local (PHs; n=4, 17%), state (n=2, 9%), and federal (n=1, 4%) levels. They represented multiple countries in Europe, the United States, and the Caribbean. Nine major themes arose from the discussions: (1) translational/implementation science, (2) precision public health, (3) fundamental unknowns, (4) proper scientific communication, (5) methods of epidemiological investigation, (6) sampling bias, (7) interoperability standards, (8) academic/public health partnerships, and (9) resources. Collectively, participants felt that successful uptake of phylodynamic tools to inform the public health response relies on the strength of academic and public health partnerships. They called for interoperability standards in sequence data sharing, urged careful reporting to prevent misinterpretations, imagined that public health responses could be tailored to specific variants, and cited resource issues that would need to be addressed by policy makers in future outbreaks. CONCLUSIONS: This study is the first to detail the viewpoints of public health practitioners and molecular epidemiology experts on the use of viral genomic data to inform the response to the COVID-19 pandemic. The data gathered during this study provide important information from experts to help streamline the functionality and use of phylodynamic tools for pandemic responses.

Unique Genomic Epidemiology of COVID-19 in the White Mountain Apache Tribe, April to August 2020, Arizona.

The first case of coronavirus disease 2019 (COVID-19) within the White Mountain Apache Tribe (WMAT) in Arizona was diagnosed almost 1 month after community transmission was recognized in the state. Aggressive contact tracing allowed for robust genomic epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and subsequent phylogenetic analyses implicated only two virus introductions, which resulted in the spread of two unique viral lineages on the reservation. The phylogenies of these lineages reflect the nature of the introductions, the remoteness of the community, and the extraordinarily high attack rates. The timing and space-limited nature of the outbreaks validate the public health tracing efforts involved, which were illustrated by multiple short transmission chains over a period of several weeks, eventually resulting in extinction of the lineages. Comprehensive sampling and successful infection control efforts are illustrated in both the effective population size analyses and the limited mortality outcomes. The rapid spread and high attack rates of the two lineages may be due to a combination of sociological determinants of the WMAT and a seemingly enhanced transmissibility. The SARS-CoV-2 genomic epidemiology of the WMAT demonstrates a unique local history of the pandemic and highlights the extraordinary and successful efforts of their public health response. IMPORTANCE This article discusses the introduction and spread of two unique viral lineages of SARS-CoV-2 within the White Mountain Apache Tribe in Arizona. Both genomic sequencing and traditional epidemiological strategies (e.g., contract tracing) were used to understand the nature of the spread of both lineages. Beyond providing a robust genomic analysis of the epidemiology of the outbreaks, this work also highlights the successful efforts of the local public health response.

A Quantitative Assessment of Staphylococcus aureus Community Carriage in Yuma, Arizona.

BACKGROUND: Disease control relies on pathogen identification and understanding reservoirs. Staphylococcus aureus infection prevention is based upon decades of research on colonization and infection, but diminishing returns from mitigation efforts suggest significant knowledge gaps. Existing knowledge and mitigation protocols are founded upon culture-based detection, with almost no information about pathogen quantities. METHODS: We used culture and a quantitative polymerase chain reaction assay on samples from 3 body sites to characterize colonization more comprehensively than previous studies by describing both prevalence and pathogen quantity. RESULTS: We show a much higher overall prevalence (65.9%) than previously documented, with higher quantities and prevalence associated with the nares, non-Hispanic males (86.9%), and correlating with colonization in other body sites. These results suggest that research and clinical practices likely misclassify over half of colonized persons, limiting mitigation measures and their impact. CONCLUSIONS: This work begins the process of rebuilding foundational knowledge of S aureus carriage with more accurate and wholistic approaches.

LupiQuant: A real-time PCR based assay for determining host-to-parasite DNA ratios of Onchocerca lupi and host Canis lupus from onchocercosis samples.

Onchocerca lupi is a filarial nematode that causes ocular onchocercosis in canines globally including North America and areas of Europe, North Africa, and the Middle East. Reported incidence of this parasite in canines has continued to steadily escalate since the early 21st century and was more recently documented in humans. Whole genome sequencing (WGS) of this parasite can provide insight into gene content, provide novel surveillance targets, and elucidate the origin and range expansion. However, past attempts of whole genome sequencing of other Onchocerca species reported a substantial portion of their data unusable due to the variable over-abundance of host DNA in samples. Here, we have developed a method to determine the host-to-parasite DNA ratio using a quantitative PCR (qPCR) approach that relies on two standard plasmids each of which contains a single copy gene specific to the parasite genus Onchocerca (major body wall myosin gene, myosin) or a single copy gene specific to the canine host (polycystin-1 precursor, pkd1). These plasmid standards were used to determine the copy number of the myosin and pkd1 genes within a sample to calculate the ratio of parasite and host DNA. Furthermore, whole genome sequence (WGS) data for three O. lupi isolates were consistent with our host-to-parasite DNA ratio results. Our study demonstrates, despite unified DNA extraction methods, variable quantities of host DNA within any one sample which will likely affect downstream WGS applications. Our quantification assay of host-to-parasite genome copy number provides a robust and accurate method of assessing canine host DNA load in an O. lupi specimen that will allow informed sample selection for WGS. This study has also provided the first whole genome draft sequence for this species. This approach is also useful for future focused WGS studies of other parasites.

One health genomic surveillance and response to a university-based outbreak of the SARS-CoV-2 Delta AY.25 lineage, Arizona, 2021.

Genomic surveillance and wastewater tracking strategies were used to strengthen the public health response to an outbreak of the SARS-CoV-2 Delta AY.25 lineage associated with a university campus in Arizona. Epidemiologic and clinical data routinely gathered through contact tracing were matched to SARS-CoV-2 genomes belonging to an outbreak of AY.25 identified through ongoing phylogenomic analyses. Continued phylogenetic analyses were conducted to further describe the AY.25 outbreak. Wastewater collected twice weekly from sites across campus was tested for SARS-CoV-2 by RT-qPCR, and subsequently sequenced to identify variants. The AY.25 outbreak was defined by a single mutation (C18804T) and comprised 379 genomes from SARS-CoV-2 positive cases associated with the university and community. Several undergraduate student gatherings and congregate living settings on campus likely contributed to the rapid spread of COVID-19 across the university with secondary transmission into the community. The clade defining mutation was also found in wastewater samples collected from around student dormitories a week before the semester began, and 9 days before cases were identified. Genomic, epidemiologic, and wastewater surveillance provided evidence that an AY.25 clone was likely imported into the university setting just prior to the onset of the Fall 2021 semester, rapidly spread through a subset of the student population, and then subsequent spillover occurred in the surrounding community. The university and local public health department worked closely together to facilitate timely reporting of cases, identification of close contacts, and other necessary response and mitigation strategies. The emergence of new SARS-CoV-2 variants and potential threat of other infectious disease outbreaks on university campuses presents an opportunity for future comprehensive One Health genomic data driven, targeted interventions.

SPARSEMODr: Rapidly simulate spatially explicit and stochastic models of COVID-19 and other infectious diseases.

Building realistically complex models of infectious disease transmission that are relevant for informing public health is conceptually challenging and requires knowledge of coding architecture that can implement key modeling conventions. For example, many of the models built to understand COVID-19 dynamics have included stochasticity, transmission dynamics that change throughout the epidemic due to changes in host behavior or public health interventions, and spatial structures that account for important spatio-temporal heterogeneities. Here we introduce an R package, SPARSEMODr, that allows users to simulate disease models that are stochastic and spatially explicit, including a model for COVID-19 that was useful in the early phases of the epidemic. SPARSEMOD stands for SPAtial Resolution-SEnsitive Models of Outbreak Dynamics, and our goal is to demonstrate particular conventions for rapidly simulating the dynamics of more complex, spatial models of infectious disease. In this report, we outline the features and workflows of our software package that allow for user-customized simulations. We believe the example models provided in our package will be useful in educational settings, as the coding conventions are adaptable, and will help new modelers to better understand important assumptions that were built into sophisticated COVID-19 models.

A sliding window approach to optimize the time-varying parameters of a spatially-explicit and stochastic model of COVID-19.

The implementation of non-pharmaceutical public health interventions can have simultaneous impacts on pathogen transmission rates as well as host mobility rates. For instance, with SARS-CoV-2, masking can influence host-to-host transmission, while stay-at-home orders can influence mobility. Importantly, variations in transmission rates and mobility patterns can influence pathogen-induced hospitalization rates. This poses a significant challenge for the use of mathematical models of disease dynamics in forecasting the spread of a pathogen; to create accurate forecasts in spatial models of disease spread, we must simultaneously account for time-varying rates of transmission and host movement. In this study, we develop a statistical model-fitting algorithm to estimate dynamic rates of SARS-CoV-2 transmission and host movement from geo-referenced hospitalization data. Using simulated data sets, we then test whether our method can accurately estimate these time-varying rates simultaneously, and how this accuracy is influenced by the spatial population structure. Our model-fitting method relies on a highly parallelized process of grid search and a sliding window technique that allows us to estimate time-varying transmission rates with high accuracy and precision, as well as movement rates with somewhat lower precision. Estimated parameters also had lower precision in more rural data sets, due to lower hospitalization rates (i.e., these areas are less data-rich). This model-fitting routine could easily be generalized to any stochastic, spatially-explicit modeling framework, offering a flexible and efficient method to estimate time-varying parameters from geo-referenced data sets.

Genome Sequences of Community Carriage Strains of Staphylococcus aureus from Yuma, Arizona.

Staphylococcus aureus exists as a pathogen and commensal. Individuals with asymptomatic carriage serve as a reservoir for transmission and are at increased risk of infecting themselves. In order to characterize the genomic diversity of S. aureus circulating in the community, we sequenced 166 genomes collected from individuals in Yuma, AZ.

Complete mitochondrial genome of Onchocerca lupi (Nematoda, Onchocercidae).

Onchocerca lupi, Rodonaja 1967, is an emerging, zoonotic filarial nematode parasite that causes ocular disease in dogs, cats, wild canids, and humans. It is the causative agent of ocular onchocercosis in canines with increasing incidence in both North America and the Old World during the early twenty-first century. We report the complete mitochondrial genome of an O. lupi isolate from a dog from Arizona, southwestern USA, and its genetic differentiation from related Onchocerca species. The whole mitochondrial genome was obtained from whole genome sequencing of genomic DNA isolated from an adult worm. This mitogenome is 13,766 bp in size and contains 36 genes and a control region. This mitogenome provides a valuable resource for future studies involving epidemiological surveillance, population genetics, phylogeography, and comparative mitogenomics of this emerging pathogen and other parasitic nematodes.

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.

Characterization of neonatal opioid withdrawal syndrome in Arizona from 2010-2017.

In this paper, we describe a population of mothers who are opioid dependent at the time of giving birth and neonates exposed to opioids in utero who experience withdrawal following birth. While there have been studies of national trends in this population, there remains a gap in studies of regional trends. Using data from the Arizona Department of Health Services Hospital Discharge Database, this study aimed to characterize the population of neonates with neonatal opioid withdrawal syndrome (NOWS) and mothers who were opioid dependent at the time of giving birth, in Arizona. We analyzed approximately 1.2 million electronic medical records from the Arizona Department of Health Services Hospital Discharge Database to identify patterns and disparities across socioeconomic, ethnic, racial, and/or geographic groupings. In addition, we identified comorbid conditions that are differentially associated with NOWS in neonates or opioid dependence in mothers. Our analysis was designed to assess whether indicators such as race/ethnicity, insurance payer, marital status, and comorbidities are related to the use of opioids while pregnant. Our findings suggest that women and neonates who are non-Hispanic White and economically disadvantaged, tend be part of our populations of interest more frequently than expected. Additionally, women who are opioid dependent at the time of giving birth are unmarried more often than expected, and we suggest that marital status could be a proxy for support. Finally, we identified comorbidities associated with neonates who have NOWS and mothers who are opioid dependent not previously reported.

Systematic review: the impact of socioeconomic factors on Aedes aegypti mosquito distribution in the mainland United States.

Aedes aegypti mosquitoes are primary vectors of dengue, yellow fever, chikungunya and Zika viruses. Ae. aegypti is highly anthropophilic and relies nearly exclusively on human blood meals and habitats for reproduction. Socioeconomic factors may be associated with the spread of Ae. aegypti due to their close relationship with humans. This paper describes and summarizes the published literature on the association between socioeconomic variables and the distribution of Ae. aegypti mosquitoes in the mainland United States. A comprehensive search of PubMed/Medline, Scopus, Web of Science, and EBSCO Academic Search Complete through June 12, 2019 was used to retrieve all articles published in English on the association of socioeconomic factors and the distribution of Ae. aegypti mosquitoes. Additionally, a hand search of mosquito control association websites was conducted in an attempt to identify relevant grey literature. Articles were screened for eligibility using the process described in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Initially, 3,493 articles were identified through the database searches and previously known literature. After checking for duplicates, 2,145 articles remained. 570 additional records were identified through the grey literature search for a total of 2,715 articles. These articles were screened for eligibility using their titles and abstracts, and 2,677 articles were excluded for not meeting the eligibility criteria. Finally, the full text for each of the remaining articles (n=38) was read to determine eligibility. Through this screening process, 11 articles were identified for inclusion in this review. The findings for these 11 studies revealed inconsistent relationships between the studied socioeconomic factors and the distribution and abundance of Ae. aegypti. The findings of this review suggest a gap in the literature and understanding of the association between anthropogenic factors and the distribution of Ae. aegypti that could hinder efforts to implement effective public health prevention and control strategies should a disease outbreak occur.

Sample pooling methods for efficient pathogen screening: Practical implications.

Due to the large number of negative tests, individually screening large populations for rare pathogens can be wasteful and expensive. Sample pooling methods improve the efficiency of large-scale pathogen screening campaigns by reducing the number of tests and reagents required to accurately categorize positive and negative individuals. Such methods rely on group testing theory which mainly focuses on minimizing the total number of tests; however, many other practical concerns and tradeoffs must be considered when choosing an appropriate method for a given set of circumstances. Here we use computational simulations to determine how several theoretical approaches compare in terms of (a) the number of tests, to minimize costs and save reagents, (b) the number of sequential steps, to reduce the time it takes to complete the assay, (c) the number of samples per pool, to avoid the limits of detection, (d) simplicity, to reduce the risk of human error, and (e) robustness, to poor estimates of the number of positive samples. We found that established methods often perform very well in one area but very poorly in others. Therefore, we introduce and validate a new method which performs fairly well across each of the above criteria making it a good general use approach.

An Early Pandemic Analysis of SARS-CoV-2 Population Structure and Dynamics in Arizona.

In December of 2019, a novel coronavirus, SARS-CoV-2, emerged in the city of Wuhan, China, causing severe morbidity and mortality. Since then, the virus has swept across the globe, causing millions of confirmed infections and hundreds of thousands of deaths. To better understand the nature of the pandemic and the introduction and spread of the virus in Arizona, we sequenced viral genomes from clinical samples tested at the TGen North Clinical Laboratory, the Arizona Department of Health Services, and those collected as part of community surveillance projects at Arizona State University and the University of Arizona. Phylogenetic analysis of 84 genomes from across Arizona revealed a minimum of 11 distinct introductions inferred to have occurred during February and March. We show that >80% of our sequences descend from strains that were initially circulating widely in Europe but have since dominated the outbreak in the United States. In addition, we show that the first reported case of community transmission in Arizona descended from the Washington state outbreak that was discovered in late February. Notably, none of the observed transmission clusters are epidemiologically linked to the original travel-related case in the state, suggesting successful early isolation and quarantine. Finally, we use molecular clock analyses to demonstrate a lack of identifiable, widespread cryptic transmission in Arizona prior to the middle of February 2020.IMPORTANCE As the COVID-19 pandemic swept across the United States, there was great differential impact on local and regional communities. One of the earliest and hardest hit regions was in New York, while at the same time Arizona (for example) had low incidence. That situation has changed dramatically, with Arizona now having the highest rate of disease increase in the country. Understanding the roots of the pandemic during the initial months is essential as the pandemic continues and reaches new heights. Genomic analysis and phylogenetic modeling of SARS-COV-2 in Arizona can help to reconstruct population composition and predict the earliest undetected introductions. This foundational work represents the basis for future analysis and understanding as the pandemic continues.