Evidence map›Paper›PMID 34966806›Full record

ArticleFrontiers in veterinary science2021

A Temporal Network Model for Livestock Trade Systems.

Sara Ansari, Jobst Heitzig, Laura Brzoska, Hartmut H K Lentz, Jakob Mihatsch, Jörg Fritzemeier, Mohammad R Moosavi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in veterinary science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 12% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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 3 institutions in 2 countries.

Sara AnsariDepartment of Computer Science and Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
Jobst HeitzigDepartment of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, Germany.
Laura BrzoskaDepartment of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, Germany.
Hartmut H K LentzInstitute of Epidemiology, Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany.
Jakob MihatschDepartment of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, Germany.
Jörg FritzemeierLandkreis Osnabrück, Veterinärdienst für Stadt und Landkreis Osnabrück, Osnabruck, Germany.
Mohammad R MoosaviDepartment of Computer Science and Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
Potsdam Institute for Climate Impact Research · DEShiraz University · IRFriedrich-Loeffler-Institut · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The movements of animals between farms and other livestock holdings for trading activities form a complex livestock trade network. These movements play an important role in the spread of infectious diseases among premises. For studying the disease spreading among animal holdings, it is of great importance to understand the structure and dynamics of the trade system. In this paper, we propose a temporal network model for animal trade systems. Furthermore, a novel measure of node centrality important for disease spreading is introduced. The experimental results show that the model can reasonably well describe these spreading-related properties of the network and it can generate crucial data for research in the field of the livestock trade system.

Indexed as

complex networkepidemiologylivestock tradenode centrality measuretemporal network

Identifiers

PMID34966806
PMCPMC8710670
OpenAlexW3211421504

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.