Spatiotemporal risk of human brucellosis under intensification of livestock keeping based on machine learning techniques in Shaanxi, China.

IF 2.5 4区 医学 Q3 INFECTIOUS DISEASES
Li Shen, Chenghao Jiang, Fangting Weng, Minghao Sun, Chenxi Zhao, Ting Fu, Cuihong An, Zhongjun Shao, Kun Liu
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引用次数: 0

Abstract

As one of the most neglected zoonotic diseases, brucellosis has posed a serious threat to public health worldwide. This study is purposed to apply different machine learning models to improve the prediction accuracy of human brucellosis (HB) in Shaanxi, China from 2008 to 2020, under livestock husbandry intensification from a spatiotemporal perspective. We quantitatively evaluated the performance and suitability of ConvLSTM, RF, and LSTM models in epidemic forecasting, and investigated the spatial heterogeneity of how different factors drive the occurrence and transmission of HB in distinct sub-regions by using Kernel Density Analysis and Shapley Additional Explanations. Our findings demonstrated that ConvLSTM network yielded the best predictive performance with the lowest average RMSE of 13.875 and MAE values of 18.393. RF model generated an underestimated outcome while LSTM model had an overestimated one. In addition, climatic conditions, intensification of livestock keeping and socioeconomic status were identified as the dominant factors that drive the occurrence of HB in Shaanbei Plateau, Guanzhong Plain, and Shaannan Region, respectively. This work provided a comprehensive understanding of the potential risk of HB epidemics in Northwest China driven by both anthropogenic activities and natural environment, which can support further practice in disease control and prevention.

基于机器学习技术的中国陕西畜牧业集约化条件下人感染布鲁氏菌病的时空风险。
作为最容易被忽视的人畜共患病之一,布鲁氏菌病已对全球公共卫生构成严重威胁。本研究旨在应用不同的机器学习模型,从时空角度提高中国陕西省在畜牧业集约化条件下从 2008 年到 2020 年人类布鲁氏菌病(HB)的预测精度。我们定量评估了 ConvLSTM、RF 和 LSTM 模型在疫情预测中的性能和适用性,并利用核密度分析和 Shapley 附加解释研究了不同因素如何驱动 HB 在不同次区域发生和传播的空间异质性。研究结果表明,ConvLSTM 网络的预测性能最佳,平均 RMSE 最低,为 13.875,MAE 值最低,为 18.393。RF 模型产生了低估的结果,而 LSTM 模型则产生了高估的结果。此外,气候条件、畜牧业集约化和社会经济状况分别被认为是陕北高原、关中平原和陕南地区发生 HB 的主导因素。这项工作全面了解了人类活动和自然环境对西北地区 HB 流行的潜在风险,有助于进一步开展疫病防控工作。
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来源期刊
Epidemiology and Infection
Epidemiology and Infection 医学-传染病学
CiteScore
4.10
自引率
2.40%
发文量
366
审稿时长
3-6 weeks
期刊介绍: Epidemiology & Infection publishes original reports and reviews on all aspects of infection in humans and animals. Particular emphasis is given to the epidemiology, prevention and control of infectious diseases. The scope covers the zoonoses, outbreaks, food hygiene, vaccine studies, statistics and the clinical, social and public-health aspects of infectious disease, as well as some tropical infections. It has become the key international periodical in which to find the latest reports on recently discovered infections and new technology. For those concerned with policy and planning for the control of infections, the papers on mathematical modelling of epidemics caused by historical, current and emergent infections are of particular value.
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