Evidence map›Paper›PMID 26030769›Full record

ArticlePloS one2015

Spatial heterogeneity, host movement and mosquito-borne disease transmission.

Miguel A Acevedo, Olivia Prosper, Kenneth Lopiano, Nick Ruktanonchai, T Trevor Caughlin, Maia Martcheva, Craig W Osenberg, David L Smith

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
4.6field-weighted citation impact, top 5% of its field
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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 60 citations in OpenAlex.

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  17. Migration rate estimation in an epidemic network.Applied mathematical modelling · 2021
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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

8 authors at 6 institutions in 2 countries.

Miguel A AcevedoUniversity of Puerto Rico-Río Piedras, Department of Biology, San Juan, PR, USA.
Olivia ProsperDartmouth College, Department of Mathematics, Hanover, NH, USA.
Kenneth LopianoStatistical and Applied Mathematical Sciences Institute, Durham, NC, USA.
Nick RuktanonchaiUniversity of Florida, Department of Biology, Gainesville, FL, USA.
T Trevor CaughlinUniversity of Florida, Department of Biology, Gainesville, FL, USA.
Maia MartchevaUniversity of Florida, Department of Mathematics, Gainesville, FL, USA.
Craig W OsenbergUniversity of Georgia, Odum School of Ecology, Athens, GA, USA.
David L SmithDepartment of Epidemiology and Malaria Research Institute, John Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
University of Florida · USDartmouth College · USJohns Hopkins University · USStatistical and Applied Mathematical Sciences Institute · USUniversity of Georgia · USUniversity of Puerto Rico at Río Piedras · PR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mosquito-borne diseases are a global health priority disproportionately affecting low-income populations in tropical and sub-tropical countries. These pathogens live in mosquitoes and hosts that interact in spatially heterogeneous environments where hosts move between regions of varying transmission intensity. Although there is increasing interest in the implications of spatial processes for mosquito-borne disease dynamics, most of our understanding derives from models that assume spatially homogeneous transmission. Spatial variation in contact rates can influence transmission and the risk of epidemics, yet the interaction between spatial heterogeneity and movement of hosts remains relatively unexplored. Here we explore, analytically and through numerical simulations, how human mobility connects spatially heterogeneous mosquito populations, thereby influencing disease persistence (determined by the basic reproduction number R0), prevalence and their relationship. We show that, when local transmission rates are highly heterogeneous, R0 declines asymptotically as human mobility increases, but infection prevalence peaks at low to intermediate rates of movement and decreases asymptotically after this peak. Movement can reduce heterogeneity in exposure to mosquito biting. As a result, if biting intensity is high but uneven, infection prevalence increases with mobility despite reductions in R0. This increase in prevalence decreases with further increase in mobility because individuals do not spend enough time in high transmission patches, hence decreasing the number of new infections and overall prevalence. These results provide a better basis for understanding the interplay between spatial transmission heterogeneity and human mobility, and their combined influence on prevalence and R0.

Indexed as

Host-Parasite InteractionsMovementAnimalsBasic Reproduction NumberCommunicable DiseasesComputer SimulationCulicidaeHumansPrevalence

Identifiers

PMID26030769
PMCPMC4452543
OpenAlexW2220487465

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.