Modelling the temperature dependent extrinsic incubation period of West Nile Virus using Bayesian time delay models
Journal of Infection·
- DOI
- 10.1016/j.jinf.2024.106296
- PMID
- 39343246
- PMCID
- —
- OpenAlex
- W4402911429
- Study type
- Journal article
- Publisher
- Elsevier BV
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The abstract frames temperature-dependent incubation estimates as relevant to modelling West Nile virus transmission dynamics and to planning interventions. It also notes that WNV can spill over to humans and cause clinical illness, including neuroinvasive disease.
Structured evidence summary
Research question
The article examines how the extrinsic incubation period of West Nile virus in mosquitoes varies with temperature, using Bayesian time-delay modelling of prior experimental data.
Study design
This is a modelling study that re-analysed existing experimental data. The abstract describes Bayesian time-delay models applied to mosquito cohort experiments conducted under different temperature conditions.
Population and setting
The experimental data involved cohorts of Culex pipiens mosquitoes infected with West Nile virus and maintained at varying temperatures. No human study population or geographic setting is specified in the supplied abstract.
Main findings
The abstract reports that a Weibull distribution best represented the incubation-period pattern and that the period shortened with increasing temperature on a log-linear scale. It reports markedly higher disseminated infection proportions at warmer temperatures and a shorter estimated EIP50 at 32°C than at 15°C. It also reports greater incubation-period variability at lower temperatures and faster mosquito infection by WN02 than NY99 at colder temperatures.
Public-health relevance
The abstract frames temperature-dependent incubation estimates as relevant to modelling West Nile virus transmission dynamics and to planning interventions. It also notes that WNV can spill over to humans and cause clinical illness, including neuroinvasive disease.
Important limitations
The evidence is based on re-analysis of existing mosquito experiment data, using Culex pipiens cohorts and temperature treatments described in the abstract. This summary is limited to the supplied single-article abstract and metadata; the original paper is needed for decision-grade interpretation of methods, data sources, assumptions, and uncertainty.
GIDS interpretation
The record is discoverable in this context because the supplied classifiers include West Nile virus and the topics of climate and environment and transmission dynamics. The COVID-19 and influenza classifier entries are present in the metadata but are not supported by the title or abstract content provided.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 9 auditable classifier relationships to diseases, places, topics, and study design.