Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics.

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

Using genomic epidemiology of SARS-CoV-2 to support contact tracing and public health surveillance in rural Humboldt County, California.

BACKGROUND: During the COVID-19 pandemic within the United States, much of the responsibility for diagnostic testing and epidemiologic response has relied on the action of county-level departments of public health. Here we describe the integration of genomic surveillance into epidemiologic response within Humboldt County, a rural county in northwest California. METHODS: Through a collaborative effort, 853 whole SARS-CoV-2 genomes were generated, representing ~58% of the 1,449 SARS-CoV-2-positive cases detected in Humboldt County as of March 12, 2021. Phylogenetic analysis of these data was used to develop a comprehensive understanding of SARS-CoV-2 introductions to the county and to support contact tracing and epidemiologic investigations of all large outbreaks in the county. RESULTS: In the case of an outbreak on a commercial farm, viral genomic data were used to validate reported epidemiologic links and link additional cases within the community who did not report a farm exposure to the outbreak. During a separate outbreak within a skilled nursing facility, genomic surveillance data were used to rule out the putative index case, detect the emergence of an independent Spike:N501Y substitution, and verify that the outbreak had been brought under control. CONCLUSIONS: These use cases demonstrate how developing genomic surveillance capacity within local public health departments can support timely and responsive deployment of genomic epidemiology for surveillance and outbreak response based on local needs and priorities.

Severe Acute Respiratory Syndrome Coronavirus 2 and Respiratory Virus Sentinel Surveillance, California, USA, May 10, 2020-June 12, 2021.

State and local health departments established the California Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Respiratory Virus Sentinel Surveillance System to conduct enhanced surveillance for SARS-CoV-2 and other respiratory pathogens at sentinel outpatient testing sites in 10 counties throughout California, USA. We describe results obtained during May 10, 2020‒June 12, 2021, and compare persons with positive and negative SARS-CoV-2 PCR results by using Poisson regression. We detected SARS-CoV-2 in 1,696 (19.6%) of 8,662 specimens. Among 7,851 specimens tested by respiratory panel, rhinovirus/enterovirus was detected in 906 (11.5%) specimens and other respiratory pathogens in 136 (1.7%) specimens. We also detected 23 co-infections with SARS-CoV-2 and another pathogen. SARS-CoV-2 positivity was associated with male participants, an age of 35-49 years, Latino race/ethnicity, obesity, and work in transportation occupations. Sentinel surveillance can provide useful virologic and epidemiologic data to supplement other disease monitoring activities and might become increasingly useful as routine testing decreases.

Microbial Source Tracking Approach to Investigate Fecal Waste at the Strawberry Creek Watershed and Clam Beach, California, USA.

Clam Beach is located in Northern California, USA, and is listed as an impaired waterway by the federal government. The scope of this study was to investigate this beach and surrounding watershed to determine, if possible, the source of the impairment by conducting an 11-h beach study and 8-week watershed study. We used traditional fecal indicator bacteria (FIB) and microbial source tracking (MST) methods to help identify source(s) of the FIB. Our study was focused on four possible contributors: human, ruminant, canine, and bird. A total of 169 samples were collected, analyzed, and compared to the California Department of Health single sample maximum (SSM) objective. In the beach study, 29 (44%) samples exceeded at least one SSM objective, which would have resulted in a resample per state regulations for recreational primary contact use. MST methods showed that the most abundant marker detected was bird, in 65% of the samples, but varied by sample location, which is likely due to a natural population of nearshore birds regularly observed along Clam Beach. The watershed study highlighted the potential influence from ruminants throughout the region, while humans did not appear to be a significant contributor. Health risk to humans appears to be low.

Isolation and characterization of a Rickettsia from the ovary of a Western black-legged tick, Ixodes pacificus.

A rickettsial isolate was obtained from a partially engorged Ixodes pacificus female, which was collected from Humboldt County, California. The isolate was provisionally named Rickettsia endosymbiont Ixodes pacificus (REIP). The REIP isolate displayed the highest nucleotide sequence identity to Rickettsia species phylotype G021 in I. pacificus (99%, 99%, and 100% for ompA, 16S rRNA, and gltA, respectively), a bacterium that was previously identified in I. pacifiucs by PCR. Analysis of sequences from complete opening frames of five genes, 16S rRNA, gltA, ompA, ompB, and sca4, provided inference to the bacteria's classification among other Rickettsia species. The REIP isolate displayed 99.8%, 99.4%, 99.2%, 99.5%, and 99.6% nucleotide sequence identity for 16S rRNA, gltA, ompA, ompB, and sca4 gene, respectively, with genes of 'R. monacensis' str. IrR/Munich, indicating the REIP isolate is closely related to 'R. monacensis'. Our suggestion was further supported by phylogenetic analysis using concatenated sequences of 16S rRNA, gltA, ompA, ompB, and sca4 genes, concatenated sequences of dksA-xerC, mppA-purC, and rpmE-tRNAfMet intergenic spacer regions. Both phylogenetic trees implied that the REIP isolate is most closely related to 'R. monacensis' str. IrR/Munich. We propose the bacterium be considered as 'Rickettsia monacensis' str. Humboldt for its closest phylogenetic relative (=DSM 103975 T = ATCC TSD-94 T).