Global prevalence and species diversity of tick-borne pathogens in buffaloes worldwide: a systematic review and meta-analysis

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Abstract

Background

Buffaloes are important contributors to the livestock economy in many countries, particularly in Asia, and tick-borne pathogens (TBPs) commonly infect buffaloes, giving rise to serious pathologies other than their zoonotic potential.

Methods

The present investigation focuses on the prevalence of TBPs infecting buffaloes worldwide. All published global data on TBPs in buffaloes were collected from different databases (e.g., PubMed, Scopus, ScienceDirect, and Google Scholar) and subjected to various meta-analyses using OpenMeta[Analyst] software, and all analyses were conducted based on a 95% confidence interval.

Results

Over 100 articles discussing the prevalence and species diversity of TBPs in buffaloes were retrieved. Most of these reports focused on water buffaloes ( Bubalus bubalis), whereas a few reports on TBPs in African buffaloes ( Syncerus caffer) had been published. The pooled global prevalence of the apicomplexan parasites Babesia and Theileria, as well as the bacterial pathogens Anaplasma, Coxiella burnetii, Borrelia, Bartonella, and Ehrlichia in addition to Crimean-Congo hemorrhagic fever virus, were all evaluated based on the detection methods and 95% confidence intervals. Interestingly, no Rickettsia spp. were detected in buffaloes with scarce data. TBPs of buffaloes displayed a fairly high species diversity, which underlines the high infection risk to other animals, especially cattle. Babesia bovis, B. bigemina, B. orientalis, B. occultans and B. naoakii, Theileria annulata, T. orientalis complex ( orientalis/sergenti/buffeli), T. parva, T. mutans, T. sinensis, T. velifera, T. lestoquardi-like, T. taurotragi, T. sp. (buffalo) and T. ovis, and Anaplasma marginale, A. centrale, A. platys, A. platys-like and “ Candidatus Anaplasma boleense” were all were identified from naturally infected buffaloes.

Conclusions

Several important aspects were highlighted for the status of TBPs, which have serious economic implications for the buffalo as well as cattle industries, particularly in Asian and African countries, which should aid in the development and implementation of prevention and control methods for veterinary care practitioners, and animal owners.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-023-05727-y.

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Most cited references 179

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Measuring inconsistency in meta-analyses.

Julian P. T. Higgins, Simon Thompson, Jonathan Deeks … (2003)

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Quantifying heterogeneity in a meta-analysis.

Julian P T Higgins, Simon G Thompson (2002)

The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.

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Meta-analysis in clinical trials revisited.

Rebecca DerSimonian, Nan Laird (2015)

In this paper, we revisit a 1986 article we published in this Journal, Meta-Analysis in Clinical Trials, where we introduced a random-effects model to summarize the evidence about treatment efficacy from a number of related clinical trials. Because of its simplicity and ease of implementation, our approach has been widely used (with more than 12,000 citations to date) and the "DerSimonian and Laird method" is now often referred to as the 'standard approach' or a 'popular' method for meta-analysis in medical and clinical research. The method is especially useful for providing an overall effect estimate and for characterizing the heterogeneity of effects across a series of studies. Here, we review the background that led to the original 1986 article, briefly describe the random-effects approach for meta-analysis, explore its use in various settings and trends over time and recommend a refinement to the method using a robust variance estimator for testing overall effect. We conclude with a discussion of repurposing the method for Big Data meta-analysis and Genome Wide Association Studies for studying the importance of genetic variants in complex diseases.

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Author and article information

Contributors

El-Sayed El-Alfy: sydnabil@mans.edu.eg

Ibrahim Abbas: ielsayed@mans.edu.eg

Rana Elseadawy: ranamagdy6666@gmail.com

Somaya Saleh: soma.saleh2010@gmail.com

Bassem Elmishmishy: dr_b_elmishmishy@mans.edu.eg

Shimaa Abd El-Salam El-Sayed: Shimaa_a@mans.edu.eg

Mohamed Abdo Rizk: dr_moh_abdo2008@mans.edu.eg

Journal

Journal ID (nlm-ta): Parasit Vectors

Journal ID (iso-abbrev): Parasit Vectors

Title: Parasites & Vectors

Publisher: BioMed Central (London )

ISSN (Electronic): 1756-3305

Publication date (Electronic): 30 March 2023

Publication date PMC-release: 30 March 2023

Publication date Collection: 2023

Volume: 16

Electronic Location Identifier: 115

Affiliations

[1 ]GRID grid.10251.37, ISNI 0000000103426662, Parasitology Department, Faculty of Veterinary Medicine, , Mansoura University, ; Mansoura, 35516 Egypt

[2 ]GRID grid.10251.37, ISNI 0000000103426662, Department of Biochemistry and Chemistry of Nutrition, Faculty of Veterinary Medicine, , Mansoura University, ; Mansoura, 35516 Egypt

[3 ]GRID grid.10251.37, ISNI 0000000103426662, Department of Internal Medicine, Infectious and Fish Diseases, Faculty of Veterinary Medicine, , Mansoura University, ; Mansoura, 35516 Egypt

Article

Publisher ID: 5727

DOI: 10.1186/s13071-023-05727-y

PMC ID: 10061416

PubMed ID: 36998029

SO-VID: 050901df-4641-42b1-a61c-c5ee020bfb11

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 14 December 2022

Date accepted : 3 March 2023

Funding

Funded by: Mansoura University

Open Access :

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

Custom metadata

ScienceOpen disciplines: Parasitology

Keywords: tick-borne pathogens,buffaloes,meta-analysis,babesia,theileria,anaplasma

Data availability:

ScienceOpen disciplines: Parasitology

Keywords: tick-borne pathogens, buffaloes, meta-analysis, babesia, theileria, anaplasma

Global prevalence and species diversity of tick-borne pathogens in buffaloes worldwide: a systematic review and meta-analysis

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Abstract

Background

Methods

Results

Conclusions

Graphical Abstract

Supplementary Information

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Ticks and tick-borne pathogens

Most cited references 179

Measuring inconsistency in meta-analyses.

Quantifying heterogeneity in a meta-analysis.

Meta-analysis in clinical trials revisited.

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Contributors

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