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Record W1985977177 · doi:10.3201/eid1408.080083

Rarity of Influenza A Virus in Spring Shorebirds, Southern Alaska

2008· letter· en· W1985977177 on OpenAlexaboutno aff
Kevin Winker, Erica Spackman, David E. Swayne

Bibliographic record

VenueEmerging infectious diseases · 2008
Typeletter
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
FundersJapan Science and Technology AgencyU.S. Department of Agriculture
KeywordsSandpiperCalidrisBayGeographySpring (device)WaterfowlFisheryEcologyBiologyPredationHabitat

Abstract

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To the Editor: Knowledge of avian influenza (AI) virus and its host epidemiology and ecology is essential for effective monitoring and mitigation (1). Applicability of global and continental-scale models will be key for expanding this knowledge base. Research in the Delaware Bay area, eastern United States, suggests an ecologic and epidemiologic viewpoint of AI virus in wild birds in which shorebirds (family Scolopacidae) are predominant hosts in spring; however, research in Alberta, Canada, suggests that waterfowl are such in autumn (2,3). AI virus surveillance in Europe (4) suggests that the spring aspect of this scenario does not apply there. To increase knowledge of AI transport among shorebirds in spring in the North Pacific, we conducted AI virus surveillance during the springs of 2006 and 2007 at the Copper River Delta area of Alaska. Millions of birds congregate at this location in the spring, resulting in the highest spring shorebird concentrations in the New World (5). We also sampled gulls (Laridae), which are common and heretofore unsurveyed for AI in this ecosystem. In 2006 and 2007, 1,050 shorebirds (Western Sandpiper, Calidris mauri, and Least Sandpiper, C. minutilla) and 770 Glaucous-winged Gulls (Larus glaucescens) were sampled during peak spring migration at Hartney Bay, Cordova, Alaska (60°28′N 146°8′W; Table). Fresh fecal samples were obtained from tidal flats within <1 to 90 min after identified flocks were dispersed, and samples were placed in sterile medium (brain heart infusion buffer with 10,000 U/mL penicillin G, 1 mg/mL gentamicin, and 20 μg/mL amphotericin B) and either kept cool (<1 week) before transport to Fairbanks (2006) or placed into liquid nitrogen within 2 h of collection (2007). Samples were stored at –70° C; shipped frozen overnight to Athens, Georgia; and maintained frozen until analyzed. Samples were screened by real-time reverse transcriptase–PCR (RT-PCR) for influenza A virus, and virus isolation was performed on samples that were positive. RNA was extracted by adding 250 μL of sample to 750 μL Trizol LS reagent (Invitrogen, Inc., Carlsbad, CA, USA). Samples were mixed and incubated at room temperature for 10 min. A total of 200 μL of chloroform was then added, incubation was continued for 5 min, and samples were centrifuged for 15 min at 12,000 × g at 4° C. Supernatant was removed, and 50 μL was extracted with the MagMax AI/ND viral RNA extraction kit (Ambion, Inc. Austin, TX, USA). RNA was tested for AI virus matrix (M) gene. A positive test result for this gene indicates the presence of any influenza viruses (6) when an internal positive control is used (7). Positive samples were processed for virus isolation in embryonated chicken eggs by standard methods (8). Real-time RT-PCR results were corroborated by processing 50 randomly selected negative samples for virus isolation with 3 egg passages. Screening for AI virus was conducted on 1,820 samples (Table). Among these, 1 AI virus was identified (A/Glaucous-wingedGull/AK/4906A/2006; H16N?), reflecting an overall prevalence of 0.055% (0% in shorebirds and 0.13% in gulls). Table Species and sample sizes of wild bird hosts screened for avian influenza virus, Cordova, Alaska, May 2006 and May 2007 Results of power analysis (9) suggested that our shorebird samples would detect infection rates >0.9% with 99% probability (95% probability of detecting rates 1%–2% or higher in each year). In gulls, probability of detecting infection rates >1% across both years of the study (>6% in 2006 and >1%–2% in 2007) was 95%. Virus prevalence in spring shorebirds in Alaska was substantially lower than prevalence in spring shorebirds in the Delaware Bay area (3) and more similar to prevalence in spring shorebirds in Europe (4). Our shorebird samples (1,050) were fewer than those in other studies (3; 4,266 samples from 4 species over 16 years, and 4; 3,159 samples from 47 species over 8 years, with 35% from spring), representing 25% and 33% of those studies, respectively. Our study covered only 2 years, but it would detect AI virus infections in shorebirds at rates >1%–2% within each year with 95% probability and at rates >0.9% across years with 99% probability. Thus, the prevalence rate among Copper River Delta shorebirds in our study is lower than that found in the 16-year Delaware Bay study (3). In the Delaware Bay area, 4 shorebird species were sampled: 3 Calidris and 1 Arenaria (3). Precise statistics are unavailable, but the average 16-year prevalence rate was 14.2%, fluctuating annually from ≈2% to ≈38% (3). In Europe AI viruses were absent among spring shorebirds (4). Differences in prevalence rates found among studies may be influenced by species sampled, sampling procedures, and seasonal timing (4). However, with >1,000 spring shorebirds sampled, results suggest that differences might exist between the world’s major migration systems (3,4). Our results corroborate other recent results (10) suggesting that AI prevalence rates among shorebirds at Delaware Bay are not typical within North America. Present evidence indicates (this study; 3,10) that the role of shorebirds in AI virus ecology and epidemiology is heterogeneous within North America and within a genus (Calidris). These findings confirm that knowledge of how AI viruses cycle in wild bird hosts remains incomplete at continental and family-level taxonomic scales. Only further surveillance can fill these knowledge gaps.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.521
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.336
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations37
Published2008
Admission routes1
Has abstractyes

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