ArticleThe Journal of infectious diseases2016
Bridging the Gap Between Experimental Data and Model Parameterization for Chikungunya Virus Transmission Predictions.
Article in The Journal of infectious diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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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.
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Who cites it
10 citing papers in PubMed.
- Intra-vector infection dynamics challenge how to model the extrinsic incubation period for major arboviruses: dengue, Zika, and chikungunya.PLoS computational biology · 2025Article
- Identifying Knowledge Gaps through the Systematic Review of Temperature-Driven Variability in the Competence ofPathogens (Basel, Switzerland) · 2023Article
- The Extrinsic Incubation Period of Zika Virus in Florida MosquitoesPathogens (Basel, Switzerland) · 2021Article
- Article
- Age-structured vectorial capacity reveals timing, not magnitude of within-mosquito dynamics is critical for arbovirus fitness assessment.Parasites & vectors · 2020Article
- Temperature impacts on dengue emergence in the United States: Investigating the role of seasonality and climate change.Epidemics · 2019Article
- Modelling and Analyzing Virus Mutation Dynamics of Chikungunya Outbreaks.Scientific reports · 2019Article
- Article
- Practical unidentifiability of a simple vector-borne disease model: Implications for parameter estimation and intervention assessment.Epidemics · 2018Article
- ColonizedViruses · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Chikungunya virus (CHIKV) has experienced 2 major expansion events in the last decade. The most recently emerged sublineage (ECSA-V) was shown to have increased efficiency in a historically secondary vector, Aedes albopictus, leading to speculation that this was a major factor in expansion. Subsequently, a number of experimental studies focused on the vector competence of CHIKV, as well as transmission modeling efforts. Mathematical models have used these data to inform their own investigations, but some have incorrectly parameterized the extrinsic incubation period (EIP) of the mosquitoes, using vector competence data. Vector competence and EIP are part of the same process but are not often correctly reported together. Thus, the way these metrics are used for model parameterization can be problematic. We offer suggestions for bridging this gap for the purpose of standardization of reporting and to promote appropriate use of experimental data in modeling efforts.
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Registered trials
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