Joel O. Wertheim

The paper analyzes the spread of H5N1 B3.13 in U.S. dairy cattle using genomic data and movement networks, finding that cattle movement, not birds, drives the outbreak.

This study tracks the emergence and molecular evolution of H5N1 influenza viruses in U.S. dairy cattle, identifying increased mutation rates and positive selection after spillover from birds.

The paper uses phylogenetic analysis to examine natural selection in zoonotic viruses, finding no evidence of pre-zoonotic adaptation for human transmission but detecting selection changes in the 1977 H1N1 reemergence.

The paper identifies the recent origin and geographical distribution of bat viruses ancestral to SARS-CoV and SARS-CoV-2, showing they circulated in Asia before spilling over into humans.

Reanalysis of public environmental metatranscriptomes from the Huanan market links SARS-CoV-2 positivity to one wildlife stall containing raccoon dog, civet and bamboo rat genetic material.

This study analyzes MPXV genomic data from NYC during the 2022 outbreak, identifying NYC-specific lineages and estimating multiple infections, while highlighting gaps in epidemiological-genetic concordance.

The paper introduces a heuristic method to adaptively select a genetic distance threshold for HIV transmission network inference, demonstrating its utility in identifying clusters with different risk factors.

This study evaluates subsampling strategies to optimize ancestral trait reconstruction in HIV-1 subtype C datasets, showing that subsampling by collection date, location, and risk group improves representativeness and reduces computational burden.

The paper detects and characterizes the SARS-CoV-2 lineage B.1.526 in New York, showing its rapid growth and potential impact on neutralization.

January 2020 cases in Germany and Washington State were contained, while separate later introductions from China seeded the first sustained SARS-CoV-2 transmission networks in Italy and Washington State.

StrainHub constructs pathogen transmission networks using phylogenetic trees and metadata to identify key nodes for infection control.

FAVITES simulates epidemic datasets for fast-evolving pathogens like HIV, enabling study of transmission networks and intervention impacts.