We investigated transmission dynamics of a large human immunodeficiency virus (HIV) outbreak among persons who inject drugs (PWID) in KY and OH during 2017-20 by using detailed phylogenetic, network, recombination, and cluster dating analyses. Using polymerase (pol) sequences from 193 people associated with the investigation, we document high HIV-1 diversity, including Subtype B (44.6 per cent); numerous circulating recombinant forms (CRFs) including CRF02_AG (2.5 per cent) and CRF02_AG-like (21.8 per cent); and many unique recombinant forms composed of CRFs with major subtypes and sub-subtypes [CRF02_AG/B (24.3 per cent), B/CRF02_AG/B (0.5 per cent), and A6/D/B (6.4 per cent)]. Cluster analysis of sequences using a 1.5 per cent genetic distance identified thirteen clusters, including a seventy-five-member cluster composed of CRF02_AG-like and CRF02_AG/B, an eighteen-member CRF02_AG/B cluster, Subtype B clusters of sizes ranging from two to twenty-three, and a nine-member A6/D and A6/D/B cluster. Recombination and phylogenetic analyses identified CRF02_AG/B variants with ten unique breakpoints likely originating from Subtype B and CRF02_AG-like viruses in the largest clusters. The addition of contact tracing results from OH to the genetic networks identified linkage between persons with Subtype B, CRF02_AG, and CRF02_AG/B sequences in the clusters supporting de novo recombinant generation. Superinfection prevalence was 13.3 per cent (8/60) in persons with multiple specimens and included infection with B and CRF02_AG; B and CRF02_AG/B; or B and A6/D/B. In addition to the presence of multiple, distinct molecular clusters associated with this outbreak, cluster dating inferred transmission associated with the largest molecular cluster occurred as early as 2006, with high transmission rates during 2017-8 in certain other molecular clusters. This outbreak among PWID in KY and OH was likely driven by rapid transmission of multiple HIV-1 variants including de novo viral recombinants from circulating viruses within the community. Our findings documenting the high HIV-1 transmission rate and clustering through partner services and molecular clusters emphasize the importance of leveraging multiple different data sources and analyses, including those from disease intervention specialist investigations, to better understand outbreak dynamics and interrupt HIV spread.

BACKGROUND: Very little is known about influenza viruses circulating in the Democratic Republic of Congo (DRC). We aim to characterize genetically and antigenically Influenza A(H3N2) and A(H1N1)pdm09 viruses circulating in the country. METHODS: From August to December 2014, specimens were collected from patients with influenza like-illness (ILI) or severe acute respiratory infection (SARI) in various surveillance sites. Specimens were tested using real time reverse transcription polymerase chain reaction (RT-PCR) method for the detection of influenza viruses. Positive influenza samples with a cycle threshold (Ct) <30 were genetically and antigenically characterized. RESULTS: 32 samples tested were found positive to influenza A with Ct <30. At CDC Atlanta, 28 out of 32 samples (88%) were tested positive for influenza A virus, including 26 seasonal influenza A viruses subtype H3N2 and 2 pandemic influenza A viruses subtype H1N1pdm 2009. The majority of influenza A(H3N2) viruses were antigenically related to the A/Switzerland/9715293/2013 vaccine virus, while two influenza A(H1N1)pdm09 isolates were antigenically characterized as A/California/07/2009-like. All A(H3N2) and A(H1N1)pdm09 virus isolates characterized were sensitive to oseltamivir and zanamivir. CONCLUSION: Two genetically distinct influenza subtypes were co-circulating in the DRCongo. Effective measures against influenza have been suggested.

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.

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in the emergence of many new variant lineages that have exacerbated the COVID-19 pandemic. Some of those variants were designated as variants of concern/interest (VOC/VOI) by national or international authorities based on many factors including their potential impact on vaccines. To ascertain and rank the risk of VOCs and VOIs, we analyzed their ability to escape from vaccine-induced antibodies. The variants showed differential reductions in neutralization and replication titers by post-vaccination sera. Although the Omicron variant showed the most escape from neutralization, sera collected after a third dose of vaccine (booster sera) retained moderate neutralizing activity against that variant. Therefore, vaccination remains the most effective strategy to combat the COVID-19 pandemic.

The report “Genomic Surveillance for SARS-CoV-2 Variants: Predominance of the Delta (B.1.617.2) and Omicron (B.1.1.529) Variants — United States, June 2021–January 2022” contained several errors.

Genomic surveillance is a critical tool for tracking emerging variants of SARS-CoV-2 (the virus that causes COVID-19), which can exhibit characteristics that potentially affect public health and clinical interventions, including increased transmissibility, illness severity, and capacity for immune escape. During June 2021-January 2022, CDC expanded genomic surveillance data sources to incorporate sequence data from public repositories to produce weighted estimates of variant proportions at the jurisdiction level and refined analytic methods to enhance the timeliness and accuracy of national and regional variant proportion estimates. These changes also allowed for more comprehensive variant proportion estimation at the jurisdictional level (i.e., U.S. state, district, territory, and freely associated state). The data in this report are a summary of findings of recent proportions of circulating variants that are updated weekly on CDC's COVID Data Tracker website to enable timely public health action.(†) The SARS-CoV-2 Delta (B.1.617.2 and AY sublineages) variant rose from 1% to >50% of viral lineages circulating nationally during 8 weeks, from May 1-June 26, 2021. Delta-associated infections remained predominant until being rapidly overtaken by infections associated with the Omicron (B.1.1.529 and BA sublineages) variant in December 2021, when Omicron increased from 1% to >50% of circulating viral lineages during a 2-week period. As of the week ending January 22, 2022, Omicron was estimated to account for 99.2% (95% CI = 99.0%-99.5%) of SARS-CoV-2 infections nationwide, and Delta for 0.7% (95% CI = 0.5%-1.0%). The dynamic landscape of SARS-CoV-2 variants in 2021, including Delta- and Omicron-driven resurgences of SARS-CoV-2 transmission across the United States, underscores the importance of robust genomic surveillance efforts to inform public health planning and practice.

Outbreak investigations use data from interviews, healthcare providers, laboratories and surveillance systems. However, integrated use of data from multiple sources requires a patchwork of software that present challenges in usability, interoperability, confidentiality, and cost. Rapid integration, visualization and analysis of data from multiple sources can guide effective public health interventions. We developed MicrobeTrace to facilitate rapid public health responses by overcoming barriers to data integration and exploration in molecular epidemiology. MicrobeTrace is a web-based, client-side, JavaScript application (https://microbetrace.cdc.gov) that runs in Chromium-based browsers and remains fully operational without an internet connection. Using publicly available data, we demonstrate the analysis of viral genetic distance networks and introduce a novel approach to minimum spanning trees that simplifies results. We also illustrate the potential utility of MicrobeTrace in support of contact tracing by analyzing and displaying data from an outbreak of SARS-CoV-2 in South Korea in early 2020. MicrobeTrace is developed and actively maintained by the Centers for Disease Control and Prevention. Users can email microbetrace@cdc.gov for support. The source code is available at https://github.com/cdcgov/microbetrace.

Botulinum neurotoxin (BoNT) binds to and internalizes its light chain into presynaptic compartments with exquisite specificity. While the native toxin is extremely lethal, bioengineering of BoNT has the potential to eliminate toxicity without disrupting neuron-specific targeting, thereby creating a molecular vehicle capable of delivering therapeutic cargo into the neuronal cytosol. Building upon previous work, we have developed an atoxic derivative (ad) of BoNT/C1 through rationally designed amino acid substitutions in the metalloprotease domain of wild type (wt) BoNT/C1. To test if BoNT/C1 ad retains neuron-specific targeting without concomitant toxic host responses, we evaluated the localization, activity, and toxicity of BoNT/C1 ad in vitro and in vivo. In neuronal cultures, BoNT/C1 ad light chain is rapidly internalized into presynaptic compartments, but does not cleave SNARE proteins nor impair spontaneous neurotransmitter release. In mice, systemic administration resulted in the specific co-localization of BoNT/C1 ad with diaphragmatic motor nerve terminals. The mouse LD50 of BoNT/C1 ad is 5 mg/kg, with transient neurological symptoms emerging at sub-lethal doses. Given the low toxicity and highly specific neuron-targeting properties of BoNT/C1 ad, these data suggest that BoNT/C1 ad can be useful as a molecular vehicle for drug delivery to the neuronal cytoplasm.

Cancer is a leading cause of morbidity and death in Puerto Rico. To set a baseline for identifying new trends and patterns of cancer incidence, Puerto Rico Central Cancer Registry staff and CDC analyzed data from Puerto Rico included in U.S. Cancer Statistics (USCS) for 2007-2011, the most recent data available. This is the first report of invasive cancer incidence rates for 2007-2011 among Puerto Rican residents by sex, age, cancer site, and municipality. Cancer incidence rates in Puerto Rico were compared with those in the U.S. population for 2011. A total of 68,312 invasive cancers were diagnosed and reported in Puerto Rico during 2007-2011. The average annual incidence rate was 330 cases per 100,000 persons. The cancer sites with the highest cancer incidence rates included prostate (152), female breast (84), and colon and rectum (43). Cancer incidence rates varied by municipality, particularly for prostate, lung and bronchus, and colon and rectum cancers. In 2011, cancer incidence rates in Puerto Rico were lower for all cancer sites and lung and bronchus, but higher for prostate and thyroid cancers, compared with rates within the U.S. population. Identifying these variations can aid evaluation of factors associated with high incidence, such as cancer screening practices, and development of targeted cancer prevention and control efforts. Public health professionals can monitor cancer incidence trends and use these findings to evaluate the impact of prevention efforts, such as legislation prohibiting tobacco use in the workplace and public places and the Puerto Rico Cessation Quitline in decreasing lung and other tobacco-related cancers.