Evidence map›Paper›PMID 29291075›Full record

ArticleRoyal Society open science2017

Model-based risk assessment and public health analysis to prevent Lyme disease.

Nasser Sharareh, Nasim S Sabounchi, Amanda Roome, Rita Spathis, Ralph M Garruto

Open access · goldAbstract read
In one paragraph

Article in Royal Society open science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

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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 at 1 institution in 1 country.

Nasser ShararehSystems Science and Industrial Engineering Department, The State University of New York at Binghamton, Binghamton, NY, USA.ORCID 0000-0001-9552-2028
Nasim S SabounchiSystems Science and Industrial Engineering Department, The State University of New York at Binghamton, Binghamton, NY, USA.
Amanda RoomeAnthropology Department, The State University of New York at Binghamton, Binghamton, NY, USA.
Rita SpathisAnthropology Department, The State University of New York at Binghamton, Binghamton, NY, USA.
Ralph M GarrutoAnthropology Department, The State University of New York at Binghamton, Binghamton, NY, USA.
Binghamton University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The number of Lyme disease (LD) cases in the northeastern United States has been dramatically increasing with over 300 000 new cases each year. This is due to numerous factors interacting over time including low public awareness of LD, risk behaviours and clothing choices, ecological and climatic factors, an increase in rodents within ecologically fragmented peri-urban built environments and an increase in tick density and infectivity in such environments. We have used a system dynamics (SD) approach to develop a simulation tool to evaluate the significance of risk factors in replicating historical trends of LD cases, and to investigate the influence of different interventions, such as increasing awareness, controlling clothing risk and reducing mouse populations, in reducing LD risk. The model accurately replicates historical trends of LD cases. Among several interventions tested using the simulation model, increasing public awareness most significantly reduces the number of LD cases. This model provides recommendations for LD prevention, including further educational programmes to raise awareness and control behavioural risk. This model has the potential to be used by the public health community to assess the risk of exposure to LD.

Indexed as

environmental riskhuman behaviourLyme diseasereservoirsystem dynamics modellingvector

Identifiers

PMID29291075
PMCPMC5717649
OpenAlexW2769504449

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.