During 2020-2023, we sequenced Bayou virus from 2 patients in Louisiana, USA, with hantavirus cardiopulmonary syndrome. Direct virus sequencing demonstrated an inferred evolutionary relationship to previous cases. Our findings demonstrate that separate virus spillovers cause isolated cases and probable wide distribution of Bayou hantavirus in rodents across Louisiana.

New World orthohantaviruses are rodent-borne tri-segmented viruses that cause hantavirus cardiopulmonary syndrome in humans in the Americas. Molecular diagnostics for orthohantaviruses can be improved with more sequence data. Reported here are completed genomes for Lechiguanas, Maciel, and Laguna Negra viruses.

BACKGROUND: In September 2022, Uganda experienced an outbreak of Sudan virus disease (SVD), mainly in central Uganda. As a result of enhanced surveillance activities for Ebola disease, samples from several patients with suspected viral hemorrhagic fever (VHF) were sent to the VHF Program at Uganda Virus Research Institute (UVRI), Entebbe, Uganda, and identified with infections caused by other viral etiologies. Herein, we report the epidemiologic and laboratory findings of Crimean-Congo hemorrhagic fever (CCHF) cases that were detected during the SVD outbreak response. METHODOLOGY: Whole blood samples from VHF suspected cases were tested for Sudan virus (SUDV) by real-time reverse transcription-polymerase chain reaction (RT-PCR); and if negative, were tested for CCHF virus (CCHFV) by RT-PCR. CCHFV genomic sequences generated by metagenomic next generation sequencing were analyzed to ascertain strain relationships. PRINCIPAL FINDINGS: Between September 2022 and January 2023, a total of 2,626 samples were submitted for VHF testing at UVRI. Overall, 13 CCHF cases (including 7 deaths; case fatality rate of 53.8%), aged 4 to 60 years, were identified from 10 districts, including several districts affected by the SVD outbreak. Four cases were identified within the Ebola Treatment Unit (ETU) at Mubende Hospital. Most CCHF cases were males engaged in livestock farming or had exposure to wildlife (n = 8; 61.5%). Among confirmed cases, the most common clinical symptoms were hemorrhage (n = 12; 92.3%), fever (n = 11; 84.6%), anorexia (n = 10; 76.9%), fatigue (n = 9; 69.2%), abdominal pain (n = 9; 69.2%) and vomiting (n = 9; 69.2%). Sequencing analysis showed that the majority of identified CCHFV strains belonged to the Africa II clade previously identified in Uganda. Two samples, however, were identified with greater similarity to a CCHFV strain that was last reported in Uganda in 1958, suggesting possible reemergence. CONCLUSIONS/SIGNIFICANCE: Identifying CCHFV from individuals initially suspected to be infected with SUDV emphasizes the need for comprehensive VHF testing during filovirus outbreak responses in VHF endemic countries. Without expanded testing, CCHFV-infected patients would have posed a risk to health care workers and others while receiving treatment after a negative filovirus diagnosis, thereby complicating response dynamics. Additionally, CCHFV-infected cases could acquire an Ebola infection while in the ETU, and upon release because of a negative Ebola virus result, have the potential to spread these infections in the community.

Background: In the United States (U.S.), hantavirus pulmonary syndrome (HPS) and non-HPS hantavirus infection are nationally notifiable diseases. Criteria for identifying human cases are based on clinical symptoms (HPS or non-HPS) and acute diagnostic results (IgM+, rising IgG+ titers, RT-PCR+, or immunohistochemistry (IHC)+). Here we provide an overview of diagnostic testing and summarize human Hantavirus disease occurrence and genotype distribution in the U.S. from 2008 to 2020. Methods: Epidemiological data from the national hantavirus registry was merged with laboratory diagnostic testing results performed at the CDC. Residual hantavirus-positive specimens were sequenced, and the available epidemiological and genetic data sets were linked to conduct a genomic epidemiological study of hantavirus disease in the U.S. Findings: From 1993 to 2020, 833 human hantavirus cases have been identified, and from 2008 to 2020, 335 human cases have occurred. Among New World (NW) hantavirus cases detected at the CDC diagnostic laboratory (representing 29.2% of total cases), most (85.0%) were detected during acute disease, however, some convalescent cases were detected in states not traditionally associated with hantavirus infections (Connecticut, Missouri, New Jersey, Pennsylvania, Tennessee, and Vermont). From 1993 to 2020, 94.9% (745/785) of U.S. hantaviruses cases were detected west of the Mississippi with 45.7% (359/785) in the Four Corners region of the U.S. From 2008 to 2020, 67.7% of NW hantavirus cases were detected between the months of March and August. Sequencing of RT-PCR-positive cases demonstrates a geographic separation of Orthohantavirus sinnombreense species [Sin Nombre virus (SNV), New York virus, and Monongahela virus]; however, there is a large gap in viral sequence data from the Northwestern and Central U.S. Finally, these data indicate that commercial IgM assays are not concordant with CDC-developed assays, and that “concordant positive” (i.e., commercial IgM+ and CDC IgM+ results) specimens exhibit clinical characteristics of hantavirus disease. Interpretation: Hantaviral disease is broadly distributed in the contiguous U.S, viral variants are localised to specific geographic regions, and hantaviral disease infrequently detected in most Southeastern states. Discordant results between two diagnostic detection methods highlight the need for an improved standardised testing plan in the U.S. Hantavirus surveillance and detection will continue to improve with clearly defined, systematic reporting methods, as well as explicit guidelines for clinical characterization and diagnostic criteria. Funding: This work was funded by core funds provided to the Viral Special Pathogens Branch at CDC. © 2024

Following an Argentine Hemorrhagic Fever (AHF) outbreak in the early 1990s, a rodent survey for Junín virus, a New World Clade B arenavirus, in endemic areas of Argentina was conducted. Since 1990, INEVH has been developing eco-epidemiological surveillance of rodents, inside and outside the Argentine Hemorrhagic Fever endemic area. Samples from rodents captured between 1993 and 2019 that were positive for Arenavirus infection underwent Sanger and unbiased, Illumina-based high-throughput sequencing, which yielded 5 complete and 88 partial Mammarenaviruses genomes. Previously, 11 genomes representing four species of New World arenavirus Clade C existed in public records. This work has generated 13 novel genomes, expanding the New World arenavirus Clade C to 24 total genomes. Additionally, two genomes exhibit sufficient genetic diversity to be considered a new species, as per ICTV guidelines (proposed name Mammarenavirus vellosense). The 13 novel genomes exhibited reassortment between the small and large segments in New World Mammarenaviruses. This work demonstrates that Clade C Mammarenavirus infections circulate broadly among Necromys species in the Argentine Hemorrhagic Fever endemic area; however, the risk for Clade C Mammarenavirus human infection is currently unknown.

BACKGROUND: The Democratic Republic of the Congo has had 15 Ebola virus disease (EVD) outbreaks, from 1976 to 2023. On June 1, 2020, the Democratic Republic of the Congo declared an outbreak of EVD in the western Équateur Province (11th outbreak), proximal to the 2018 Tumba and Bikoro outbreak and concurrent with an outbreak in the eastern Nord Kivu Province. In this Article, we assessed whether the 11th outbreak was genetically related to previous or concurrent EVD outbreaks and connected available epidemiological and genetic data to identify sources of possible zoonotic spillover, uncover additional unreported cases of nosocomial transmission, and provide a deeper investigation into the 11th outbreak. METHODS: We analysed epidemiological factors from the 11th EVD outbreak to identify patient characteristics, epidemiological links, and transmission modes to explore virus spread through space, time, and age groups in the Équateur Province, Democratic Republic of the Congo. Trained field investigators and health professionals recorded data on suspected, probable, and confirmed cases, including demographic characteristics, possible exposures, symptom onset and signs and symptoms, and potentially exposed contacts. We used blood samples from individuals who were live suspected cases and oral swabs from individuals who were deceased to diagnose EVD. We applied whole-genome sequencing of 87 available Ebola virus genomes (from 130 individuals with EVD between May 19 and Sept 16, 2020), phylogenetic divergence versus time, and Bayesian reconstruction of phylogenetic trees to calculate viral substitution rates and study viral evolution. We linked the available epidemiological and genetic datasets to conduct a genomic and epidemiological study of the 11th EVD outbreak. FINDINGS: Between May 19 and Sept 16, 2020, 130 EVD (119 confirmed and 11 probable) cases were reported across 13 Équateur Province health zones. The individual identified as the index case reported frequent consumption of bat meat, suggesting the outbreak started due to zoonotic spillover. Sequencing revealed two circulating Ebola virus variants associated with this outbreak-a Mbandaka variant associated with the majority (97%) of cases and a Tumba-like variant with similarity to the ninth EVD outbreak in 2018. The Tumba-like variant exhibited a reduced substitution rate, suggesting transmission from a previous survivor of EVD. INTERPRETATION: Integrating genetic and epidemiological data allowed for investigative fact-checking and verified patient-reported sources of possible zoonotic spillover. These results demonstrate that rapid genetic sequencing combined with epidemiological data can inform responders of the mechanisms of viral spread, uncover novel transmission modes, and provide a deeper understanding of the outbreak, which is ultimately needed for infection prevention and control during outbreaks. FUNDING: WHO and US Centers for Disease Control and Prevention.

Hantaviruses zoonotically infect humans worldwide with pathogenic consequences and are mainly spread by rodents that shed aerosolized virus particles in urine and feces. Bioinformatics methods for hantavirus diagnostics, genomic surveillance and epidemiology are currently lacking a comprehensive approach for data sharing, integration, visualization, analytics and reporting. With the possibility of hantavirus cases going undetected and spreading over international borders, a significant reporting delay can miss linked transmission events and impedes timely, targeted public health interventions. To overcome these challenges, we built HantaNet, a standalone visualization engine for hantavirus genomes that facilitates viral surveillance and classification for early outbreak detection and response. HantaNet is powered by MicrobeTrace, a browser-based multitool originally developed at the Centers for Disease Control and Prevention (CDC) to visualize HIV clusters and transmission networks. HantaNet integrates coding gene sequences and standardized metadata from hantavirus reference genomes into three separate gene modules for dashboard visualization of phylogenetic trees, viral strain clusters for classification, epidemiological networks and spatiotemporal analysis. We used 85 hantavirus reference datasets from GenBank to validate HantaNet as a classification and enhanced visualization tool, and as a public repository to download standardized sequence data and metadata for building analytic datasets. HantaNet is a model on how to deploy MicrobeTrace-specific tools to advance pathogen surveillance, epidemiology and public health globally.

Uganda experienced five Ebola disease outbreaks caused by Bundibugyo virus (n = 1) and Sudan virus (SUDV) (n = 4) from 2000 to 2021. On 20 September 2022, Uganda declared a fifth Sudan virus disease outbreak in the Mubende district, resulting in 142 confirmed and 22 probable cases by the end of the outbreak declaration on 11 January 2023. The earliest identified cases, through retrospective case investigations, had onset in early August 2022. From the 142 confirmed cases, we performed unbiased (Illumina) and SUDV-amplicon-specific (Minion) high-throughput sequencing to obtain 120 SUDV genome-and coding-complete sequences, representing 95.4% (104/109) of SVD-confirmed individuals within a sequence-able range (Ct ≤30) and 10 genome sequences outside of this range and 6 duplicate genome sequences. A comparison of the nucleotide genetic relatedness for the newly emerged Mubende variant indicated that it was most closely related to the Nakisamata SUDV sequence from 2011, represented a likely new zoonotic spillover event, and exhibited an inter- and intra-outbreak substitution rate consistent with previous outbreaks. The most recent common ancestor for the Mubende variant was estimated to have occurred in October and November 2021. The Mubende variant glycoprotein amino acid sequences exhibited 99.7% similarity altogether and a maximum of 96.1% glycoprotein similarity compared to historical SUDV strains from 1976. Integrating the genetic sequence and epidemiological data into the response activities generated a broad overview of the outbreak, allowing for quick fact-checking of epidemiological connections between the identified patients. IMPORTANCE Ebola disease (EBOD) is a public health threat with a high case fatality rate. Most EBOD outbreaks have occurred in remote locations, but the 2013-2016 Western Africa outbreak demonstrated how devastating EBOD can be when it reaches an urban population. Here, the 2022 Sudan virus disease (SVD) outbreak in Mubende District, Uganda, is summarized, and the genetic relatedness of the new variant is evaluated. The Mubende variant exhibited 96% amino acid similarity with historic SUDV sequences from the 1970s and a high degree of conservation throughout the outbreak, which was important for ongoing diagnostics and highly promising for future therapy development. Genetic differences between viruses identified during the Mubende SVD outbreak were linked with epidemiological data to better interpret viral spread and contact tracing chains. This methodology should be used to better integrate discrete epidemiological and sequence data for future viral outbreaks.