ArticleThe American journal of tropical medicine and hygiene2020
Analysis of Factors Influencing Cystic Echinococcosis in Northwest Non-Qinghai Tibetan Plateau Regions of China.
Article in The American journal of tropical medicine and hygiene, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Risk Factors Associated With Echinococcosis in the General Chinese Population: A Meta-Analysis and Systematic Review.Frontiers in public health · 2022Pooled it
- Epidemiological characteristics and risk factors for cystic and alveolar echinococcosis in China: an analysis of a national population-based field survey.Parasites & vectors · 2023Article
- The Impact of Environmental and Host Factors on Human Cystic Echinococcosis: A County-Level Modeling Study in Western China.GeoHealth · 2023Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cystic echinococcosis (CE) is an important health problem in northwest non-Qinghai Tibetan Plateau regions of China. Understanding CE risk factors may help in formulating effective prevention and control measures. In the current study, negative binomial regression was used to analyze CE-related factors using prevalence data from 147 counties (cities, districts, and banners) in northwest non-Qinghai Tibetan Plateau regions of China gathered from a national survey conducted in 2012, county economic data, and livestock production data for 2012. The negative binomial regression models indicated
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