ArticlePLoS computational biology2023
Modelling the spread and mitigation of an emerging vector-borne pathogen: Citrus greening in the U.S.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- How host mobility formulations shape estimates of pathogen dispersal and epidemic risk in non endemic regions.PLoS computational biology · 2026Article
- Optimizing crop clustering to minimize pathogen invasion in agriculture.Scientific reports · 2025Article
- Modelling plant disease spread and containment: Simulation and approximate Bayesian Computation for Xylella fastidiosa in Puglia, Italy.PLoS computational biology · 2025Article
- Assessing delimiting strategies to identify the infested zones of quarantine plant pests and diseases.Scientific reports · 2025Article
- Optimal control prevents itself from eradicating stochastic disease epidemics.PLoS computational biology · 2025Article
- Article
- Predicting the effect of landscape structure on epidemic invasion using an analytical estimate for infection rate.Royal Society open science · 2025Article
- Developing a spatio-temporal model for banana bunchy top disease: leveraging remote sensing and survey data.Frontiers in plant science · 2025Article
- Tamarixia radiata global distribution to current and future climate using the climate change experiment (CLIMEX) model.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predictive models, based upon epidemiological principles and fitted to surveillance data, play an increasingly important role in shaping regulatory and operational policies for emerging outbreaks. Data for parameterising these strategically important models are often scarce when rapid actions are required to change the course of an epidemic invading a new region. We introduce and test a flexible epidemiological framework for landscape-scale disease management of an emerging vector-borne pathogen for use with endemic and invading vector populations. We use the framework to analyse and predict the spread of Huanglongbing disease or citrus greening in the U.S. We estimate epidemiological parameters using survey data from one region (Texas) and show how to transfer and test parameters to construct predictive spatio-temporal models for another region (California). The models are used to screen effective coordinated and reactive management strategies for different regions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.