Evidence map›Paper›PMID 25139524›Full record

ArticleBMC infectious diseases2014

A spatial simulation model for dengue virus infection in urban areas.

Stephan Karl, Nilimesh Halder, Joel K Kelso, Scott A Ritchie, George J Milne

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Article in BMC infectious diseases, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  20. Using Multiple Scale Spatio-Temporal Patterns for Validating Spatially Explicit Agent-Based Models.International journal of geographical information science : IJGIS · 2019
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Stephan Karl
Nilimesh Halder
Joel K Kelso
Scott A Ritchie
George J MilneSchool of Computer Science and Software Engineering, The University of Western Australia, 35 Stirling Highway, Crawley, Perth, WA 6009, Australia. george.milne@uwa.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe World Health Organization estimates that the global number of dengue infections range between 80-100 million per year, with some studies estimating approximately three times higher numbers. Furthermore, the geographic range of dengue virus transmission is extending with the disease now occurring more frequently in areas such as southern Europe. Ae. aegypti, one of the most prominent dengue vectors, is endemic to the far north-east of Australia and the city of Cairns frequently experiences dengue outbreaks which sometimes lead to large epidemics.

methodA spatially-explicit, individual-based mathematical model that accounts for the spread of dengue infection as a result of human movement and mosquito dispersion is presented. The model closely couples the four key sub-models necessary for representing the overall dynamics of the physical system, namely those describing mosquito population dynamics, human movement, virus transmission and vector control. Important features are the use of high quality outbreak data and mosquito trapping data for calibration and validation and a strategy to derive local mosquito abundance based on vegetation coverage and census data.

resultsThe model has been calibrated using detailed 2003 dengue outbreak data from Cairns, together with census and mosquito trapping data, and is shown to realistically reproduce a further dengue outbreak. The simulation results replicating the 2008/2009 Cairns epidemic support several hypotheses (formulated previously) aimed at explaining the large-scale epidemic which occurred in 2008/2009; specifically, while warmer weather and increased human movement had only a small effect on the spread of the virus, a shorter virus strain-specific extrinsic incubation time can explain the observed explosive outbreak of 2008/2009.

conclusionThe proof-of-concept simulation model described in this study has potential as a tool for understanding factors contributing to dengue spread as well as planning and optimizing dengue control, including reducing the Ae. aegypti vector population and for estimating the effectiveness and cost-effectiveness of future vaccination programmes. This model could also be applied to other vector borne viral diseases such as chikungunya, also spread by Ae. aegypti and, by re-parameterisation of the vector sub-model, to dengue and chikungunya viruses spread by Aedes albopictus.

Indexed as

AedesAnimalsAustraliaDengueDengue VirusDisease OutbreaksEuropeHumansInsect VectorsModels, TheoreticalUrban HealthWeather

Identifiers

PMID25139524
PMCPMC4152583

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LicenceCC BY
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Registered trials

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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.