Panel data analysis of spatial effects carbapenem-resistant organisms in mainland China
Abstract Carbapenem-Resistant Organisms (CROs) pose a serious threat to human health, which is a significant concern and urgently requires further research. However, the spatial effects of CROs are under explored. Data were obtained from the China Antimicrobial Resistance Surveillance System, coveri...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-09712-6 |
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| author | Dongdong Zou Ruxin Kou Yuanyang Wu Jinwen Hu Qianqian Xu Haixia Wang Xinping Zhang |
| author_facet | Dongdong Zou Ruxin Kou Yuanyang Wu Jinwen Hu Qianqian Xu Haixia Wang Xinping Zhang |
| author_sort | Dongdong Zou |
| collection | DOAJ |
| description | Abstract Carbapenem-Resistant Organisms (CROs) pose a serious threat to human health, which is a significant concern and urgently requires further research. However, the spatial effects of CROs are under explored. Data were obtained from the China Antimicrobial Resistance Surveillance System, covering the prevalence of carbapenem-resistant Klebsiella pneumoniae (CRKP), Pseudomonas aeruginosa (CRPA), and Acinetobacter baumannii (CRAB) in 30 provinces from 2014 to 2023.Spatial Durbin Model (SDM) and effect decomposition were used to determine the spatial effects of CROs and their influencing factors including urbanization rate (UR), the number of health institutions (HOS), annual GDP per capita (PGDP), annual pesticide usage (PUSE) and PM2.5. Spillover of spatial effects were observed among CROs significantly. CRKP and CRPA demonstrated spatial clustering; CRPA and CRAB exhibited negative spatial effect spillovers. It implies that regions with high levels of CROs and the dynamic changes between regions should be given more attention first. This study has further identified significant associations between the spatial effects of CROs and various factors, including the aggregation and mobility of population, socioeconomic factors, as well as soil and air pollution. It is crucial to recognize the roles of these factors in the spatial spread of CROs, as it provides a new perspective for the prevention and control of CROs. |
| format | Article |
| id | doaj-art-2df9f5322704487fa533962f1796e57c |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
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| spelling | doaj-art-2df9f5322704487fa533962f1796e57c2025-08-20T03:05:27ZengNature PortfolioScientific Reports2045-23222025-07-0115111210.1038/s41598-025-09712-6Panel data analysis of spatial effects carbapenem-resistant organisms in mainland ChinaDongdong Zou0Ruxin Kou1Yuanyang Wu2Jinwen Hu3Qianqian Xu4Haixia Wang5Xinping Zhang6Medical and Health Management, Hua Zhong University of Science and TechnologyMedical and Health Management, Hua Zhong University of Science and TechnologyMedical and Health Management, Hua Zhong University of Science and TechnologyMedical and Health Management, Hua Zhong University of Science and TechnologyMedical and Health Management, Hua Zhong University of Science and TechnologyMedical and Health Management, Hua Zhong University of Science and TechnologyMedical and Health Management, Hua Zhong University of Science and TechnologyAbstract Carbapenem-Resistant Organisms (CROs) pose a serious threat to human health, which is a significant concern and urgently requires further research. However, the spatial effects of CROs are under explored. Data were obtained from the China Antimicrobial Resistance Surveillance System, covering the prevalence of carbapenem-resistant Klebsiella pneumoniae (CRKP), Pseudomonas aeruginosa (CRPA), and Acinetobacter baumannii (CRAB) in 30 provinces from 2014 to 2023.Spatial Durbin Model (SDM) and effect decomposition were used to determine the spatial effects of CROs and their influencing factors including urbanization rate (UR), the number of health institutions (HOS), annual GDP per capita (PGDP), annual pesticide usage (PUSE) and PM2.5. Spillover of spatial effects were observed among CROs significantly. CRKP and CRPA demonstrated spatial clustering; CRPA and CRAB exhibited negative spatial effect spillovers. It implies that regions with high levels of CROs and the dynamic changes between regions should be given more attention first. This study has further identified significant associations between the spatial effects of CROs and various factors, including the aggregation and mobility of population, socioeconomic factors, as well as soil and air pollution. It is crucial to recognize the roles of these factors in the spatial spread of CROs, as it provides a new perspective for the prevention and control of CROs.https://doi.org/10.1038/s41598-025-09712-6 |
| spellingShingle | Dongdong Zou Ruxin Kou Yuanyang Wu Jinwen Hu Qianqian Xu Haixia Wang Xinping Zhang Panel data analysis of spatial effects carbapenem-resistant organisms in mainland China Scientific Reports |
| title | Panel data analysis of spatial effects carbapenem-resistant organisms in mainland China |
| title_full | Panel data analysis of spatial effects carbapenem-resistant organisms in mainland China |
| title_fullStr | Panel data analysis of spatial effects carbapenem-resistant organisms in mainland China |
| title_full_unstemmed | Panel data analysis of spatial effects carbapenem-resistant organisms in mainland China |
| title_short | Panel data analysis of spatial effects carbapenem-resistant organisms in mainland China |
| title_sort | panel data analysis of spatial effects carbapenem resistant organisms in mainland china |
| url | https://doi.org/10.1038/s41598-025-09712-6 |
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