Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
April 12, 2026Scientific ReportsOpen Access

A data-parsimonious model for long-term risk assessments of West Nile virus spillover

View Full Paper
Ask AI
Bookmark
Share

Authors

SHSaman HosseiniLCLee W. CohnstaedtMMMatin Marjani

Discussion

Loading...

Member takes

Overview

Novel model predicts West Nile virus outbreak timing and severity in various regions, supporting proactive efforts.

Key Points

  • The research aims to create a model for predicting West Nile virus spillover without relying on limited surveillance data.
  • Developed a probabilistic model combining temperature-driven compartments and kernel density estimation.
  • Constructed a joint probability density function and Poisson rate surface based on mosquito abundance.
  • Calibrated the model using human incidence records.
  • Evaluated across multiple counties with varying ecologies and climates.
  • Produced reliable forecasts for West Nile virus outbreaks several months in advance.
  • Demonstrated strong agreement in performance metrics across the evaluated regions.
  • Supported proactive mitigation efforts in areas at risk of spillover.

Cite This Study

Hosseini et al. (2026) studied this question.

synapsesocial.com/papers/69db36e64fe01fead37c4eb7https://doi.org/10.1038/s41598-026-47413-w
View Full Paper
Ask AI
Bookmark
Share