Evidence map›Paper›PMID 31803777›Full record

ArticleJournal of arthropod-borne diseases2019

Using Ecological Niche Modeling to Predict the Spatial Distribution of

Najmeh Hesami, Mohammad Reza Abai, Hassan Vatandoost, Mostafa Alizadeh, Mahboubeh Fatemi, Javad Ramazanpour, Ahmad Ali Hanafi-Bojd

Open access · diamondAbstract read
PubMed Full text at PMC
In one paragraph

Article in Journal of arthropod-borne diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 19% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Susceptibility ofVeterinary research forum : an international quarterly journal · 2022
    Article
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

7 authors at 1 institution in 1 country.

Najmeh HesamiDepartment of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mohammad Reza AbaiDepartment of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Hassan VatandoostDepartment of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mostafa AlizadehDepartment of Communicable Diseases Control, Deputy for Health, Isfahan University of Medical Sciences, Isfahan, Iran.
Mahboubeh FatemiDepartment of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Javad RamazanpourDepartment of Communicable Diseases Control, Deputy for Health, Isfahan University of Medical Sciences, Isfahan, Iran.
Ahmad Ali Hanafi-BojdDepartment of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Tehran University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMosquitoes are very important vectors of diseases to human. We aimed to establish the first spatial database on the mosquitoes of Isfahan Province, central Iran, and to predict the geographical distribution of species with medical importance.

methodsMosquito larvae were collected from eight counties of Isfahan Province during 2014. Collected data were transferred to a database in ArcGIS and the distribution maps were created. MaxEnt model and jackknife analysis were used to predict the geographical distribution of two medical important species, and to find the effective variables for each species.

resultsTotally, 1143 larvae were collected including 6 species,

conclusionThe mosquito collected and mapped can be considered for transmission of malaria and filariasis in the region. Bearing in mind the results of niche modeling for vector species, more studies on vectorial capacity and resistance status to different insecticides of these species are recommended.

Indexed as

Anopheles maculipennis s.lCulex theileriCulicidaeEcological niche modelingSpatial distribution

Identifiers

PMID31803777
PMCPMC6885139
OpenAlexW2953647773

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.