SynthesisVeterinary medicine and science2024
Global and regional seroprevalence of coxiellosis in small ruminants: A systematic review and meta-analysis.
Synthesis in Veterinary medicine and science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Global and regional seroprevalence of coxiellosis in small ruminants: A systematic review and meta-analysis.Veterinary medicine and science · 2024Pooled it
- Seroprevalence of Q-fever among domestic ruminants, humans and ticks in Ethiopia: A systematic review and meta-analysis.Veterinary and animal science · 2026Review
- Evaluation of seroprevalence and risk factors for Q fever (Open veterinary journal · 2026Article
- Seroprevalence of Q fever among humans and animals in East Africa: a systematic review and meta-analysis.One health outlook · 2026Review
- Molecular detection of Coxiella burnetii in vaginal and rectal swab samples of small ruminants from Kermanshah Province, western Iran.BMC veterinary research · 2026Article
- Q Fever-Related Community Infections: United States Exposure toPathogens (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCoxiellosis is a neglected zoonosis for occupationally exposed people in many parts of the world. Sheep and goats are two important small ruminants that act as reservoirs for human contamination; however, there is a lack of comprehensive data on the epidemiological aspects of coxiellosis in sheep and goats at regional and global levels. The aim of this study was to systematically review the available articles on seroprevalence of coxiellosis in sheep and goats and estimate the overall seroprevalence in different regions.
methodsA systematic search strategy was performed in five electronic repositories for articles published until December 2021. Relevant data were extracted from the selected articles based on the inclusion criteria. A random effect meta-analysis model was used to analyse the data. Results are presented as the prevalence of seropositivity as a percentage and 95% confidence intervals.
resultsThe global pooled seroprevalence of coxiellosis in sheep was 17.38% (95% confidence interval [CI]: 15.59%-19.17%). Overall, the regional level pooled prevalence estimates in sheep ranged from 15.04% (95% CI: 7.68%-22.40%) to 19.14% (95% CI: 15.51%-22.77%), depending on region. The global pooled seroprevalence of coxiellosis in goats was 22.60% (95% CI: 19.54%-25.66%). Overall, the regional level pooled prevalence estimates in goats ranged from 6.33% (95% CI: 2.96%-9.71%) to 55.13% (95% CI: 49.61%-60.65%), depending on the region. The prevalence estimates also varied significantly in both sheep and goats depending on age, sex, and rearing systems of the animals (p < 0.001).
conclusionSeroprevalence of coxiellosis in both sheep and goats is considerable. Routine monitoring of the sheep and goat populations is needed to prevent spillover infection in other livestock and humans.
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Registered trials
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.