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A study on the epidemiological characteristics and SARIMA-SVR model prediction of mushroom poisoning in Guizhou Province from 2017 to 2024
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Shuai HUANG1, Chao-fei ZOU2, Yan-rong HU1, Mu-li WU1, An-zhong WU3, Pei-pei ZUO3, Qian-qian ZHOU3, Qing-yuan CHEN4, Jun LI1, Hua GUO1, 3
Modern Preventive Medicine | 2026, 53(8) : 1488 - 1493
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Modern Preventive Medicine | 2026, 53(8): 1488-1493
• Disease Control and Prevention •
A study on the epidemiological characteristics and SARIMA-SVR model prediction of mushroom poisoning in Guizhou Province from 2017 to 2024
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Shuai HUANG1, Chao-fei ZOU2, Yan-rong HU1, Mu-li WU1, An-zhong WU3, Pei-pei ZUO3, Qian-qian ZHOU3, Qing-yuan CHEN4, Jun LI1, Hua GUO1, 3
Affiliations
  • School of Public Health, the Key Laboratory of Environmental Pollution and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou 561113, China
Published: 2026-04-25 doi: 10.20043/j.cnki.MPM.202510122
Outline
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Objective

To analyze the epidemiological characteristics of mushroom poisoning in Guizhou Province from 2017 to 2024. To compare the predictive performance of the Seasonal Autoregressive Integrated Moving Average model (SARIMA) versus the combined Seasonal Autoregressive Integrated Moving Average-Support Vector Regression (SARIMA-SVR) model in forecasting incidence trends.

Methods

Data on mushroom poisoning events from 2017 to 2024 were obtained from the Foodborne Disease Outbreak Surveillance System of Guizhou Province for descriptive epidemiological analysis. Using data from 2017 to 2023 as the training ser and data from 2024 as the testing set, SARIMA and SARIMA-SVR combined models were constructed. Model performance was evaluated using mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE).

Results

A total of 2 694 mushroom poisoning outbreaks were reported during 2017 to 2024 Guizhou Province, involving 8 987 cases and 31 deaths. Mushroom poisoning is highly prevalent summer and autumn (June to September), with higher rates observed in the northeastern region. The most affected age group was 20 to 59 years, and households were primary setting of occurrence. In terms of model predictive performance, the SARIMA model could relatively well capture the overall trend of incidence, but the SARIMA—SVR combined model exhibited superior predictive performance.

Conclusion

Mushroom poisoning remains highly prevalent in Guizhou Province, exhibiting distinct seasonal and geographical patterns. The SARIMA-SVR combined model provides better forecasting accuracy and can serve as a valuable tool for surveillance, early warning, and preventive interventions.

Mushroom poisoning  /  Epidemiological characteristic  /  Time series  /  SARIMA  /  SARIMA—SVR
黄帅, 邹朝飞, 胡燕榕, 吴牡丽, 吴安忠, 左佩佩, 周倩倩, 陈庆园, 李军, 郭华. 2017—2024年贵州省蘑菇中毒流行特征及SARIMA—SVR模型预测研究. 现代预防医学, 2026 , 53 (8) : 1488 -1493 . DOI: 10.20043/j.cnki.MPM.202510122
Shuai HUANG, Chao-fei ZOU, Yan-rong HU, Mu-li WU, An-zhong WU, Pei-pei ZUO, Qian-qian ZHOU, Qing-yuan CHEN, Jun LI, Hua GUO. A study on the epidemiological characteristics and SARIMA-SVR model prediction of mushroom poisoning in Guizhou Province from 2017 to 2024[J]. Modern Preventive Medicine, 2026 , 53 (8) : 1488 -1493 . DOI: 10.20043/j.cnki.MPM.202510122
Year 2026 volume 53 Issue 8
22
11
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Article Info
doi: 10.20043/j.cnki.MPM.202510122
  • Receive Date:2025-10-14
  • Online Date:2026-11-02
  • Published:2026-04-25
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  • Received:2025-10-14
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    School of Public Health, the Key Laboratory of Environmental Pollution and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou 561113, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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