#USA, #Wastewater Data for Avian #Influenza #H5 (#CDC, April 17 '26)

 

{Excerpt}

(...)

Time Period: April 05, 2026 - April 11, 2026

-- A(H5) Detection: 6 site(s) (1.3%)

-- No Detection: 454 site(s) (98.7%)

-- No samples: 103 site(s)

(...)

Source: 

Link: https://www.cdc.gov/wastewater/emerging-viruses/h5.html

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#USA, #Wastewater Data for Avian #Influenza #H5 (#CDC, April 10 '26, summary)

 

{Excerpt}

(...)

Time Period: March 29, 2026 - April 04, 2026

-- A(H5) Detection: 7 site(s) (1.6%)

-- No Detection: 430 site(s) (98.4%)

-- No samples: 125 site(s)

(...)

Source: 

Link: https://www.cdc.gov/wastewater/emerging-viruses/h5.html

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Divergent avian #strains drive an off-season #influenza A #peak in municipal #wastewater

 

Abstract

Wastewater sequencing is an increasingly valuable tool in tracking the spread of infectious disease agents across space and time in areas of dense human settlement. Among pathogens that can be readily detected by this approach is influenza A, which follows predictable patterns of prevalence through the winter months in North America. Here, we leverage routine surveillance of a municipal wastewater treatment plant in Northern California to describe an atypical, off-season spike in influenza A concentrations that rivals that of the winter respiratory virus season. Drawing upon metagenomic data generated through hybrid-capture sequencing, we assemble and subsequently characterize fragments of divergent influenza genomes that appear to derive predominantly from the avian H16 clade. These strains exhibit close evolutionary relationships to influenza isolated from migratory shorebirds, hinting at potential host species and mechanisms of geographic spread. Analysis of read abundances suggest that these avian strains dominate the pool of influenza circulating during the summer months, when typical human-infecting strains are essentially absent. Together, our results expand the value of wastewater sequencing to encompass sensitive tracking of outbreaks within animals in interface regions where human settlement abuts wildlands, increasing overall pandemic preparedness.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This project was supported by a gift from the Sergey Brin Family Foundation to A.B.B.

Source: 

Link: https://www.medrxiv.org/content/10.64898/2026.04.02.26350079v1

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#USA, #Wastewater Data for Avian #Influenza #H5 (#CDC, April 3 '26)

 

{Excerpt}

(...)

Time Period: March 22, 2026 - March 28, 2026

-- H5 Detection: 8 site(s) (1.7%)

-- No Detection: 458 site(s) (98.3%)

-- No samples in last week: 105 site(s)

(...)

Source: 

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

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Rapid #identification of #COVID #wastewater #surges in the absence of case data

 

ABSTRACT

Genetic testing of community wastewater (wastewater surveillance) is a valuable tool for following trends in the abundance of SARS-CoV-2 and other infectious disease pathogens over time. Wastewater surveillance is increasingly important in the absence of corresponding epidemiological data, particularly for infectious diseases with limited timely data on clinical case incidences. Due to the inherent noise in wastewater data, a single sample is not sufficient to identify a sustained trend in the abundance of a target. This challenge is magnified in resource-limited settings where samples may be collected only once or twice per week. In this work, we collected 24-h composite samples of wastewater daily from a single facility for nearly 4 years. We use this high-frequency data set to describe a method for identifying trends in SARS-CoV-2 abundance in wastewater based on a variety of collection frequencies. Our results indicate that collecting two 24-h composites per week for 2 weeks is sufficient to accurately identify a SARS-CoV-2 surge. We conclude that low-frequency wastewater sampling performs reasonably well in identifying trends in a timely fashion.

Source: 

Link: https://journals.asm.org/doi/full/10.1128/msphere.00652-25?af=R

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#USA, #Wastewater Data for Avian #Influenza #H5 (#CDC, March 27 '26)

 

{Excerpt}

(...)

Time Period: March 15, 2026 - March 21, 2026

-- H5 Detection: 9 site(s) (2.0%)

-- No Detection: 436 site(s) (98.0%)

-- No samples in last week: 130 site(s)

(...)

Source: 

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

_____

#USA, #Wastewater Data for Avian #Influenza #H5 (#CDC, March 20 '26)

 

{Excerpt}

Time Period: March 08, 2026 - March 14, 2026

-- H5 Detection: 8 site(s) (1.8%)

-- No Detection: 444 site(s) (98.2%)

-- No samples in last week: 120 site(s)

(...)

Source: 

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

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Early #Detection and #Surveillance of the #SARS-CoV-2 #Variant #BA32 — Worldwide, November 2024–February 2026 (US CDC, MMWR, March 19 '26)

 

Summary

-- What is already known about this topic?

- CDC tracks SARS-CoV-2 variants internationally using digital public health surveillance and in the United States using genomic surveillance, including wastewater and traveler-based surveillance. 

- The highly divergent SARS-CoV-2 variant BA.3.2 was first detected in a respiratory sample collected on November 22, 2024, in South Africa.

-- What is added by this report?

- As of February 11, 2026, BA.3.2 had been reported in 23 countries. 

- Detections began increasing in September 2025. 

- In the United States, BA.3.2 was detected in nasal swabs from four travelers, three airplane wastewater samples, clinical samples from five patients, and 132 wastewater samples from 25 U.S. states.

-- What are the implications for public health practice?

- Monitoring the spread of BA.3.2 provides valuable information about the potential for this new SARS-CoV-2 lineage to evade immunity from a previous infection or vaccination.

Abstract

The SARS-CoV-2 variant BA.3.2 was first identified in South Africa on November 22, 2024. BA.3.2 has approximately 70–75 substitutions and deletions in the gene sequence of the spike protein relative to JN.1 and its descendant, LP.8.1, the antigens used in the 2025–26 COVID-19 vaccines. CDC is using a multimodal SARS-CoV-2 genomic surveillance approach to monitor the emergence and spread of BA.3.2 and other SARS-CoV-2 variants internationally and within the United States. The first U.S. BA.3.2 detection occurred on June 27, 2025, through CDC’s Traveler-Based Genomic Surveillance program in a participant traveling to the United States from the Netherlands. The first U.S. detection of BA.3.2 in a clinical specimen collected from a patient was reported on January 5, 2026. As of February 11, 2026, BA.3.2 had been detected in voluntarily self-collected nasal swabs from four U.S. travelers, clinical samples from five patients, three airplane wastewater samples, and 132 wastewater surveillance samples from 25 states. BA.3.2 has been reported by at least 23 countries. SARS-CoV-2 continues to cause substantial morbidity and mortality worldwide. BA.3.2 mutations in the spike protein have the potential to reduce protection from a previous infection or vaccination. Continued genomic surveillance is needed to track SARS-CoV-2 evolution and determine its potential effect on public health.

Source: 

Link: https://www.cdc.gov/mmwr/volumes/75/wr/mm7510a1.htm?s_cid=OS_mm7510a1_e&ACSTrackingID=USCDC_921-DM153709&ACSTrackingLabel=Week%20in%20MMWR%3A%20Vol.%2075%2C%20March%2019%2C%202026&deliveryName=USCDC_921-DM153709

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Developing and #Benchmarking #OneHealth Genomic #Surveillance #Tools for #Influenza A Virus in #Wastewater

 

Abstract

Influenza A viruses (IAV) remain a persistent One Health threat, and whole-genome sequencing from wastewater offers a promising surveillance tool. However, IAV is at low abundance in wastewater, making it difficult to sequence. We benchmarked four targeted enrichment methods suited for whole-genome sequencing including custom and off-the-shelf amplicon and probe-based methods. Our custom HA tiled-amplicon panel was sensitive, fast, and cost-effective, making it suitable for monitoring low-abundance seasonal variants of known subtypes. However, its reliance on conserved and intact primer-binding sites limited primer design to fewer subtypes. A previously published universal amplicon method targeted all IAV subtypes, but it performed poorly in wastewater due to its reliance on intact genome segments. Probe-capture methods were resilient to RNA degradation and mismatches, potentially enabling broader surveillance and detection of emerging strains. However, probes were costly, labor-intensive, and less sensitive than tiled-amplicon. When testing compatibility of sequencing methods with upstream virus concentration and extraction methods, ultrafiltration-based virus concentration outperformed large-volume direct extraction with all four sequencing methods. This set of benchmarking comparisons and custom panels provides needed information for the translation of IAV genomic sequencing into a routine component of wastewater surveillance.

Competing Interest Statement

The authors have declared no competing interest.

Funder Information Declared

University of California, Berkeley, L22CR4507

NIH Common Fund, 4R00GM144747-03

Source: 

Link: https://www.biorxiv.org/content/10.1101/2025.09.19.676942v2

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A Tale of Two Lenses: #Emergency department indoor - #air hybrid-capture #metagenomics complements #wastewater by adding a human-focused respiratory #virus perspective

 

Abstract

Background: 

Continuous, non-invasive viral surveillance is essential to monitor emerging pathogens and guide public health responses. Most environmental surveillance studies use targeted qPCR approaches, and comparisons between wastewater and indoor air surveillance remain limited. We aimed to compare the utility of emergency department indoor air and urban wastewater for tracking circulating viruses and resolving genomic information. 

Methods: 

We conducted a matched-pair study comparing 19 weekly indoor air samples from the central ventilation exhaust shaft of an emergency department and 19 24-hour composite municipal wastewater samples in Leuven, Belgium, from December 2024 to April 2025. Both sample sets were processed using probe-based hybrid-capture viral metagenomics targeting over 3000 viral species, using influenza A as a clinically relevant test case. 

Findings: 

Wastewater captured higher overall viral diversity (233 versus 106 species) and more complete genomes compared to indoor air, showing a relatively stable composition, mainly of enteric and animal-associated viruses. Indoor air demonstrated lower overall diversity but was enriched for respiratory viruses, including influenza A, coronaviruses, metapneumovirus, and respiratory syncytial virus, and more frequently achieved high genome coverage for these pathogens. Although both sample types permitted influenza A subtype characterization, influenza A genomes from wastewater were often less well covered. When coverage thresholds were met, indoor air supported targeted antiviral resistance-site screening for influenza A and RSV-A. 

Interpretation: 

Wastewater and indoor air generate distinct but complementary viromes. Wastewater acts as a diverse, population-level monitor for One-Health applications, whereas indoor air serves as a targeted, human-centric sentinel system facilitating further genomic characterization for respiratory viruses.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

Mustafa Karatas is supported by a Research Foundation Flanders (FWO) fundamental research scholarship (number: 11P7I24N). C.G., L.C., E.H., S.G. and E.A. acknowledge support from the DURABLE project. The DURABLE project has been funded by the European Union, under the EU4Health Programme (EU4H), project no. 101102733. Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. The computing power in this work was provided by the VSC (Flemish Supercomputer Centre), financed by the FWO and the Flemish government department EWI.

Source: MedRxIV, https://www.medrxiv.org/

Link: https://www.medrxiv.org/content/10.64898/2026.03.13.26348311v1

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#USA, #Wastewater Data for Avian #Influenza #H5 (#CDC, March 13 '26)

{Excerpt}

Time Period: March 01, 2026 - March 07, 2026

-- H5 Detection: 8 site(s) (1.6%)

-- No Detection: 491 site(s) (98.4%)

-- No samples in last week: 77 site(s)

(...)

Source: US Centers for Disease Control and Prevention, 

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

____

Deep untargeted #wastewater #metagenomic #sequencing from #sewersheds across the #USA

 

Abstract

Wastewater monitoring enables non-invasive, population-scale tracking of community infections independent of healthcare-seeking behavior and clinical diagnosis. Metagenomic sequencing extends this capability by enabling broad, pathogen-agnostic detection, genomic characterization, and identification of novel or unexpected threats. Here, we present data from CASPER (the Coalition for Agnostic Sequencing of Pathogens from Environmental Reservoirs), a U.S.-based wastewater metagenomic sequencing network designed for deep, untargeted pathogen monitoring at national scale. This release includes 1,206 samples collected between December 2023 and December 2025 from 27 sites across nine states, covering 13 million people. Deep sequencing (~1 billion read pairs per sample) generated 1.2 trillion read pairs (347 terabases), enabling detection of even rare taxa, with CASPER representing 66% of all untargeted wastewater sequencing data currently available on the NCBI Sequence Read Archive. Virus abundance trends correlate with nationwide wastewater PCR and clinical data for SARS-CoV-2, influenza A, and respiratory syncytial virus, while the pathogen-agnostic approach captures emerging threats, including avian influenza H5N1 during initial dairy cattle outbreaks, West Nile virus, and measles, among hundreds of viral taxa. As the largest publicly available untargeted wastewater sequencing dataset to date, CASPER provides a shared and growing resource for pathogen surveillance and microbial ecology.

Competing Interest Statement

D.H.O. received support for this project from Inkfish and Heart of Racing. D.H.O. is a managing partner of Pathogenuity LLC, a consultancy that advises on topics including environmental monitoring for pathogens. P.C.S. hold several patents related to diagnostic and surveillance technologies and is a co-founder and equity holder in Delve Biosciences and Lyra Labs, a board member and equity holder in Polaris Genomics, and an equity holder of NextGenJane. P.C.S was formerly a co-founder of Sherlock Biosciences and board member of Danaher Corporation, until December 2024. All potential conflicts are managed in accordance with institutional policy.

Funding Statement

L.J.J. was supported by the Draper Scholar program at The Charles Stark Draper Laboratory. J.K., O.S.H., R.F-O., S.L.G., W.J.B., H.B., D.P.R., K.S., J.D.F., and M.R.M. received support for this work from Coefficient Giving via a gift to SecureBio. C.R., A.T-M., E.E.C., M.C.J., and D.H.O. were supported by Inkfish and Heart of Racing. L.J.J., J.P., and P.C.S. were supported by the CDC Pathogen Genomics Centers of Excellence (contract INTF5104H78W22195346) and a CDC Broad Agency Announcement (contract 75D30123C17983). J.E.L. and G.A. were supported by a subcontract under CDC Broad Agency Announcement contract 75D30123C17983. H.M.S-G. and A.A. were supported in part by the National Institute on Drug Abuse of the National Institutes of Health under Award Number U01DA053941, and by the University of Miami Initiative on Virology and Infectious Disease and SecureBio. R.P. was supported by the Illinois Department of Public Health and the Chicago Department of Public Health. This work used Expanse at the San Diego Supercomputer Center through allocation BIO240238 to J.A.R. from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by U.S. National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.

Source: 

Link: https://www.medrxiv.org/content/10.64898/2026.03.05.26345726v1

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#USA, #Wastewater Data for Avian #Influenza #H5 (CDC, Mar. 6 '26)

 

{Excerpt}

Time Period: February 22, 2026 - February 28, 2026

-- H5 Detection: 9 site(s) (2.0%)

-- No Detection: 443 site(s) (98.0%)

-- No samples in last week: 147 site(s)

(...)

Source: 

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

____

#USA, #Wastewater Data for Avian #Influenza #H5 (#CDC, Feb. 27 '26)

 

{Excerpt}

Time Period: February 15, 2026 - February 21, 2026

-- H5 Detection: 4 site(s) (0.8%)

-- No Detection: 495 site(s) (99.2%)

-- No samples in last week: 110 site(s)

(...)

Source: US CDC, https://www.cdc.gov/

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

____

#Wastewater #Surveillance for #SARS-CoV-2 in Rural #Kentucky, 2021–2023

 

Abstract

Wastewater testing for SARS-CoV-2 provided useful public health information during the COVID-19 pandemic yet was underutilized in rural communities. We addressed this gap by implementing wastewater surveillance and assessing its performance in 10 communities in Eastern Kentucky. We collected wastewater samples 1–2 times weekly at 10 wastewater treatment plants (WWTPs) from May 2021 until April 2023 and measured SARS-CoV-2 RNA concentrations using polymerase chain reaction testing. We calculated time-lagged correlations between wastewater concentrations and county-level reported COVID-19 cases by site. We developed a generalized linear model to estimate COVID-19 incidence from wastewater SARS-CoV-2 concentrations. The 10 participating WWTPs served 2430 to 35,575 customers, and 90% were in rural counties. We cumulatively analyzed 818 wastewater samples. Correlations between wastewater SARS-CoV-2 concentrations and COVID-19 cases were significant at seven of the WWTPs and were strongest during the Delta variant period. The incidence density model predicted more COVID-19 cases during the latter study period (May 2022–April 2023) than were officially reported. Wastewater surveillance data in these rural communities corroborated clinical case data and may have more accurately described community disease levels later in the pandemic.

Source: 

Link: https://www.mdpi.com/1999-4915/18/3/282

____

#USA, #Wastewater Data for Avian #Influenza #H5 (CDC, Feb. 20 '26)

 

{Excerpt}

Time Period: February 08, 2026 - February 14, 2026

-- H5 Detection: 9 site(s) (1.9%)

-- No Detection: 466 site(s) (98.1%)

-- No samples in last week: 171 site(s)

The H5 detections at sewershed IDs 809 and 912 in Michigan are false detections resulting from a data error. These will be corrected in the next update.

(...)

Source: 

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

____

#USA, #Wastewater Data for Avian #Influenza #H5 (CDC, Feb. 16 '26)

 

{Excerpt}

Time Period: February 01, 2026 - February 07, 2026

-- H5 Detection: 8 site(s) (1.7%)

-- No Detection: 475 site(s) (98.3%)

-- No samples in last week: 166 site(s)

The H5 detections at sewershed IDs 809 and 912 in Michigan are false detections resulting from a data error. These will be corrected in the next update.

(...)

Source: 

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

____

#USA, #Wastewater Data for Avian #Influenza #H5 (#CDC, Feb. 6 '26)

 

{Excerpt}

Time Period: January 25, 2026 - January 31, 2026

-- H5 Detection: 4 site(s) (0.9%)

-- No Detection: 458 site(s) (99.1%)

-- No samples in last week: 192 site(s)

The H5 detections at sewershed IDs 809 and 912 in Michigan are false detections resulting from a data error. These will be corrected in the next update.

(...)

Source: 

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

____

#USA, #Wastewater Data for Avian #Influenza #H5 (#CDC, Jan. 30 '26)

 

{Excerpt}

Time Period: January 18, 2026 - January 24, 2026

-- H5 Detection: 4 site(s) (0.9%)

-- No Detection: 437 site(s) (99.1%)

-- No samples in last week: 204 site(s)

(...)

Source: 

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

____

#USA, #Wastewater Data for Avian #Influenza #H5 (#CDC, Jan. 23 '26)

 

{Excerpt}

Time Period: January 11, 2026 - January 17, 2026

-- H5 Detection: 6 site(s) (1.1%)

-- No Detection: 519 site(s) (98.9%)

-- No samples in last week: 78 site(s)

(...)

Source: 

Link: https://www.cdc.gov/nwss/rv/wwd-h5.html

____