Evidence map›Paper›PMID 36793037›Full record

ArticleBMC veterinary research2023

Seroprevalence of zoonotic abortive diseases and their associated risk factors in Tunisian sheep.

Kaouther Guesmi, Sana Kalthoum, Aymen Mamlouk, Mohamed Naceur Baccar, Bassem BelHajMohamed, Haikel Hajlaoui, Aymen Toumi, Jamel Cherni, Chédia Seghaier, Lilia Messadi

Abstract read
In one paragraph

Article in BMC veterinary research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–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

17 citing papers in PubMed.

  1. Systematic review ofOne health (Amsterdam, Netherlands) · 2026
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  5. Knowledge mapping of risk mitigation measures against vector-borne diseases.EFSA journal. European Food Safety Authority · 2026
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  7. First report ofOpen veterinary journal · 2026
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  9. Hybrid Whole Genomes ofMicroorganisms · 2025
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  11. Molecular Detection ofInternational journal of microbiology · 2025
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  15. Article
  16. Review
  17. 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

10 authors.

Kaouther GuesmiNational Center for Zoosanitary Vigilance, Ministry of Agriculture, Water Resources and Fisheries, 38 Avenue Charles Nicolle, 1082, Tunis, Tunisia. guesmikaouther09@yahoo.fr.
Sana KalthoumNational Center for Zoosanitary Vigilance, Ministry of Agriculture, Water Resources and Fisheries, 38 Avenue Charles Nicolle, 1082, Tunis, Tunisia.
Aymen MamloukDepartment of Microbiology and Immunology, Institution of Agricultural Research and Higher Education, National School of Veterinary Medicine, Univ. Manouba, 2020, Sidi Thabet, Tunisia.
Mohamed Naceur BaccarNational Center for Zoosanitary Vigilance, Ministry of Agriculture, Water Resources and Fisheries, 38 Avenue Charles Nicolle, 1082, Tunis, Tunisia.
Bassem BelHajMohamedNational Center for Zoosanitary Vigilance, Ministry of Agriculture, Water Resources and Fisheries, 38 Avenue Charles Nicolle, 1082, Tunis, Tunisia.
Haikel HajlaouiNational Center for Zoosanitary Vigilance, Ministry of Agriculture, Water Resources and Fisheries, 38 Avenue Charles Nicolle, 1082, Tunis, Tunisia.
Aymen ToumiState-owned Land Office, Ministry of Agriculture, Water Resources and Fisheries, Tunis, Tunisia.
Jamel CherniNational Center for Zoosanitary Vigilance, Ministry of Agriculture, Water Resources and Fisheries, 38 Avenue Charles Nicolle, 1082, Tunis, Tunisia.
Chédia SeghaierNational Center for Zoosanitary Vigilance, Ministry of Agriculture, Water Resources and Fisheries, 38 Avenue Charles Nicolle, 1082, Tunis, Tunisia.
Lilia MessadiDepartment of Microbiology and Immunology, Institution of Agricultural Research and Higher Education, National School of Veterinary Medicine, Univ. Manouba, 2020, Sidi Thabet, Tunisia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAbortion is a serious problem for sheep flocks and it is responsible for considerable economic losses. The epidemiological situation of abortion causing agents in sheep is poorly documented in Tunisia. This study aims to investigate the status of three abortion causing agents (Brucella spp, Toxoplasma gondii, and Coxiella burnetii) among organized flocks in Tunisia.

resultsA total of 793 sample blood collected from twenty-six flocks in seven governorates in Tunisia, were tested by indirect enzyme-linked immunosorbent assay (i-ELISA) for antibodies against three abortion causing agents (Brucella spp, Toxoplasma gondii, and Coxiella burnetii). Risk factors for individual-level seroprevalence were analyzed using a logistic regression model. Results revealed that 19.7%, 17.2%, and 16.1% of the tested sera were positive for toxoplasmosis, Q fever, and brucellosis, respectively. Mixed infection was found in all the flocks with 3 to 5 responsible abortive agents simultaneously. Logistic regression showed that the management practices (control of new introduction, common grazing and watering point, workers exchange, presence of lambing box on the farm) and the history of infertility and the presence of abortion in neighboring flocks were likely to increase the probability of being infected by the three abortive agents.

conclusionsEvidence of the positive relationship between seroprevalence of abortion causing agents and several risk factors, suggests further investigations to better understand the etiology of infectious abortions in flocks to develop an applicable preventive and control program.

Indexed as

Coxiella burnetiiQ FeverSheep DiseasesAnimalsAntibodies, BacterialFemalePregnancyRisk FactorsSeroepidemiologic StudiesSheepZoonosesAntibodies, BacterialAbortionBrucella sppCoxiella burnetiiELISARisk factorsSeroprevalenceSheepToxoplasma gondiiTunisia

Identifiers

PMID36793037
PMCPMC9930233

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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.