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Record W4389128401 · doi:10.1101/2023.11.28.23299131

Hepatitis E in Kathmandu Valley: Insights from a Representative Longitudinal Serosurvey

2023· preprint· en· W4389128401 on OpenAlexaff
Nishan Katuwal, Melina Thapa, Sony Shrestha, Krista Vaidya, Isaac I. Bogoch, Jason R. Andrews, Rajeev Shrestha, Dipesh Tamrakar, Kristen Aiemjoy

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicHepatitis Viruses Studies and Epidemiology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSeroprevalenceSeroconversionTransmission (telecommunications)Hepatitis E virusMedicineIncidence (geometry)SerologySubclinical infectionEnvironmental healthVaccinationPopulationHepatitis AHepatitis EDemographyVeterinary medicineGeographyVirologyHepatitisAntibodyImmunologyBiology

Abstract

fetched live from OpenAlex

ABSTRACT Hepatitis-E virus (HEV), an etiologic agent of acute inflammatory liver disease, is a significant cause of morbidity and mortality in South Asia. HEV is considered endemic in Nepal; but data on population-level infection transmission is sparse. We conducted a representative longitudinal serologic study between February 2019 and April 2021 in urban and peri-urban areas of central Nepal to characterize community-level HEV transmission. Individuals were followed up to four times, during which capillary blood samples were collected on dried blood spots and tested for anti-HEV immunoglobulin-G antibodies. Analyzing 2513 dried blood samples from 923 participants aged 0-25 years, we found a seroprevalence of 4.8% and a seroincidence rate of 10.9 per 1000 person-years. Notably, young adults, including women of childbearing age, faced the highest incidence of infection. Geospatial analysis identified potential HEV clusters in Kavre and Kathmandu districts, emphasizing the need for targeted interventions. Water source played a crucial role in HEV transmission, with individuals consuming surface water facing the highest risk of seroconversion. Our findings underscore the endemic nature of HEV in Nepal, emphasizing the importance of safe water practices and potential vaccination strategies for high-risk groups.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.146
GPT teacher head0.367
Teacher spread0.222 · 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 designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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