Evidence map›Paper›PMID 42717360›Full record

ArticleJournal of animal science and biotechnology2026

Global spatiotemporal patterns of bovine mastitis pathogens from 2000 to 2025: a meta-analysis for precision dairy health.

Kai Yang, Guiqiu Hu, Zimo Pei, Meng Lan, Yu Cao, Xuanting Liu, Juxiong Liu, Dewei He, Wenjin Guo, Shoupeng Fu

Abstract read
In one paragraph

Article in Journal of animal science and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Kai Yang *State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun, 130062, China.
Guiqiu Hu *State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun, 130062, China.
Zimo PeiState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun, 130062, China.
Meng LanState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun, 130062, China.
Yu CaoState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun, 130062, China.
Xuanting LiuJilin Provincial Key Laboratory of Nutrition and Functional Food and College of Food Science and Engineering, Jilin University, Changchun, 130062, China.
Juxiong LiuState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun, 130062, China.
Dewei HeState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun, 130062, China.
Wenjin GuoState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun, 130062, China. guowenjin@jlu.edu.cn.ORCID https://orcid.org/0000-0002-7679-7138
Shoupeng FuState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, College of Veterinary Medicine, Jilin University, Changchun, 130062, China. fushoupeng@jlu.edu.cn.

Funding

National Key Research and Development Program of China 025YFF1000800National Natural Science Foundation of China 32372959National Natural Science Foundation of China 32372961National Natural Science Foundation of China 32472984Yunnan International Joint Laboratory for Exploration and Utilization of Aromatic Chinese Medicinal Materials in Agriculture 202503AP140024
6 · The paper itself

Abstract

backgroundBovine mastitis is the most prevalent and economically damaging disease affecting dairy production worldwide. The disease can reduce milk yield and quality, shorten productive herd life, and compromise animal welfare and farm profitability. Although the spectra of responsible pathogens vary widely across regions, climates, and farming systems, long-term global spatiotemporal data that could guide mastitis resistance breeding and precision nutritional strategies remain limited. This meta-analysis aimed to characterize the spatiotemporal dynamics of bovine mastitis pathogens and to evaluate their associations with geography, climate, cattle breed, and husbandry systems.

resultsA total of 137 studies published between 2000 and 2025 were included, covering 37 countries and 208,510 dairy cows. The pooled prevalence estimates and 95% confidence intervals for the five dominant pathogens were as follows: Staphylococcus aureus, 19.59% (95% CI: 17.00%-22.47%); Streptococcus spp., 17.29% (95% CI: 15.14%-19.66%); Escherichia coli, 13.86% (95% CI: 11.22%-17.00%); Coagulase-negative staphylococci, 15.49% (95% CI: 10.12%-22.99%); and Klebsiella spp., 9.92% (95% CI: 7.38%-13.20%). Overall, the pathogen spectrum clearly changed temporally over the 25-year period, with Klebsiella spp. exhibiting the most pronounced upward signal. Subgroup analyses suggested pathogen-specific variability across geographies and climates. The highest prevalence of S. aureus was observed in plateau climates and Africa. At the continent level, Streptococcus spp. were more prevalent in Europe and Asia, whereas climactically, they were more prevalent in plateau and tropical climates. Coagulase-negative staphylococci had the highest continental prevalence in Europe, while climate-specific estimates of its prevalence were relatively high in tropical and subtropical zones.

conclusionsThis study provides long-term global evidence of the substantial temporal and geographic variability of the patterns of various bovine mastitis pathogens, including pathogen-specific evidence for geographic and climatic differences. These spatiotemporal patterns provide important etiological evidence for the targeted genetic improvement of mastitis resistance and pathogen-specific nutritional interventions. These findings provide essential etiological evidence for integrating multidisciplinary technologies including animal breeding, animal nutrition and farm health management to improve bovine mammary health, raise production efficiency and advance the sustainable development of dairy farming.

Indexed as

Bovine mastitisDisease resistance breedingMeta-analysisPathogen spectrumPrecision nutritionSpatiotemporal analysis

Identifiers

PMID42717360
PMCPMC13560248

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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.