Research

We sequence nasopharyngeal swabs from patients presenting with ILI. We analyze the sequences for signatures of antiviral resistance and vaccine immune escape. We create phylogenetic and phylodynamic trees to examine seasonal evolution and spread. Led by PI Vel Murugan we are also studying vaccine effectiveness among diverse populations in Arizona.

Relevant Publications Include:

1. Faleye TOC, Adams D, Adhikari S, Sandrolini H, Halden RU, Varsani A, Scotch M. Use of hemagglutinin and neuraminidase amplicon-based high-throughput sequencing with variant analysis to detect co-infection and resolve identical consensus sequences of seasonal influenza in a university setting. BMC Infect Dis. 2021 Aug 13;21(1):810.

2. Wang X, Stelzer-Braid S, Scotch M, Rawlinson WD. Detection of respiratory viruses directly from clinical samples using next-generation sequencing: A literature review of recent advances and potential for routine clinical use. Rev Med Virol. 2022 Sep;32(5):e2375.

We process cloacal swabs of wild birds for sequencing of low pathogenic avian influenza viruses. We create phylogenetic and phylodynamic trees to examine evolution and spread among North American flyways.

Relevant Publications Include:

1. Scotch M, Lam TT, Pabilonia KL, Anderson T, Baroch J, Kohler D, DeLiberto TJ. Diffusion of influenza viruses among migratory birds with a focus on the Southwest United States. Infect Genet Evol. 2014 Aug;26:185-93.

2. Morin CW, Stoner-Duncan B, Winker K, Scotch M, Hess JJ, Meschke JS, Ebi KL, Rabinowitz PM. Avian influenza virus ecology and evolution through a climatic lens. Environ Int. 2018 Oct;119:241-249.

The goal of the Pandemic Environmental Surveillance Center for Assessing Pathogen Emergence (Pandemic ESCAPE) is the timely detection of emergent pathogens across a variety of settings through cost-effective and easy-to-implement environmental surveillance (ES). ES uses environmental samples, to discover and monitor pathogens. Pandemic ESCAPE will advance ES technology, data interpretation, and adoption to promote its widespread deployment across the United States. 

We also monitors SARS-CoV-2 in clinical samples and wastewater. We sequence the virus to understand evolution and spread.

Relevant Publications Include:

1. Fontenele RS, Kraberger S, Hadfield J, ..., Halden RU, Scotch M, Varsani A. High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants. Water Res. 2021 Oct 15;205:117710.

2. Holland LA, Kaelin EA, Maqsood R, Estifanos B, Wu LI, Varsani A, Halden RU, Hogue BG, Scotch M, Lim ES. An 81-Nucleotide Deletion in SARS-CoV-2 ORF7a Identified from Sentinel Surveillance in Arizona (January to March 2020). J Virol. 2020 Jul 1;94(14):e00711-20. 

We study the evolution and spread of different RNA viruses using publicly available sequences from GenBank or GISAID. We use Bayesian inference (via BEAST v1.10.x) to examine local and global transmission. 

Relevant Publications Include:

1. Scotch M, Tahsin T, Weissenbacher D, O'Connor K, Magge A, Vaiente M, Suchard MA, Gonzalez-Hernandez G. Incorporating sampling uncertainty in the geospatial assignment of taxa for virus phylogeography. Virus Evol. 2019 Feb 28;5(1):vey043.

2. Adam DC, Scotch M, MacIntyre CR. Bayesian Phylogeography and Pathogenic Characterization of Smallpox Based on HA, ATI, and CrmB Genes. Mol Biol Evol. 2018 Nov 1;35(11):2607-2617. 

We partner with Dr. Graciela Gonzalez and her lab at Cedars-Sinai to use natural language processing and text mining for enrichment of virus sequence metadata in GenBank or GISAID that is often incomplete or missing. We search the biomedical literature to identify metadata that relates to the location of the infected host, patient demographics, co-morbidities, and clinical outcomes.

Relevant Publications Include:

1. Magge A, Weissenbacher D, O'Connor K, Tahsin T, Gonzalez-Hernandez G, Scotch M. GeoBoost2: a natural language processing pipeline for GenBank metadata enrichment for virus phylogeography. Bioinformatics. 2020 Dec 22;36(20):5120-5121.

2. Magge A, Weissenbacher D, Sarker A, Scotch M, Gonzalez-Hernandez G. Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature. Pac Symp Biocomput. 2019;24:100-111.

We partner with infection modelers such as Drs. Sirish Namilae, Ashok Srinivasan, Abba Gumel, and Raina MacIntyre. This includes pedestrian dynamics and epidemiologic compartmental models.

Relevant Publications Include:

1. Namilae S, Wu Y, Mubayi A, Srinivasan A, Scotch M. Identifying mitigation strategies for COVID-19 superspreading on flights using models that account for passenger movement. Travel Med Infect Dis. 2022 May-Jun;47:102313.

2. Ngonghala CN, Iboi E, Eikenberry S, Scotch M, MacIntyre CR, Bonds MH, Gumel AB. Mathematical assessment of the impact of non-pharmaceutical interventions on curtailing the 2019 novel Coronavirus. Math Biosci. 2020 Jul;325:108364.