生物多样性 ›› 2020, Vol. 28 ›› Issue (5): 579-586.DOI: 10.17520/biods.2020155

• 综述 • 上一篇    下一篇

生态位模型在流行病学中的应用

王然1,2,乔慧捷1,*()   

  1. 1 中国科学院动物研究所动物生态与保护生物学院重点实验室, 北京 100101
    2 中国科学院大学, 北京 100049
  • 收稿日期:2020-04-16 接受日期:2020-05-26 出版日期:2020-05-20 发布日期:2020-06-19
  • 通讯作者: 乔慧捷
  • 基金资助:
    科技部重点研发计划(2017YFC1200603)

Matters needing attention about invoking ecological niche model in epidemiology

Ran Wang1,2,Huijie Qiao1,*()   

  1. 1 Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101
    2 University of Chinese Academy of Sciences, Beijing 100049
  • Received:2020-04-16 Accepted:2020-05-26 Online:2020-05-20 Published:2020-06-19
  • Contact: Huijie Qiao

摘要:

随着新冠肺炎(COVID-19)疫情在全球逐渐开始蔓延, 对其传播范围以及强度的风险评估工作越来越受到人们的重视。作为生态学和生物地理学中常用的研究手段, 生态位模型也被应用到该项工作中来。虽然预测流行病的传播热点和趋势是生态位模型的应用方向之一, 但由于新冠病毒(SARS-CoV-2)自身特点, 生态位模型并非预测其潜在传播范围的有力工具。本文回顾了近些年来生态位模型在各种流行病学研究中的应用, 比较了疫病传播中常用生态位建模方法的优势与不足, 分析了适用生态位建模的疫病案例以及不适用于生态位建模的疫病特点, 明确指出, 生态位模型只能用于分析流行病在传播过程中受自然环境干扰的部分, 如中间宿主的潜在分布等。而对于包括COVID-19在内的主要通过人传人的流行病, 生态位模型尚无有效的手段进行预测。尽管生态位模型可用于分析流行病的传播范围, 但在使用时需要根据疾病特点有针对性地选择合适的建模方法与建模对象。为了量化疫病传播风险, 还需要考虑其他干扰因素, 以便准确测试和评估生态位模型。若不加选择地滥用生态位模型的工具, 反而会误导决策者的判断。总之, 在应用生态位模型进行研究工作, 特别是预测流行病的传播范围时, 首先要考虑建模对象是否满足生态学假设。

关键词: 生态位模型, 流行病, 疫病生态学, 传播, 疫病模型

Abstract:

The outbreak of COVID-19 has spurred a number of risk assessments within the scientific community regarding its spread and intensity. A popular ecological tool, ecological niche models (ENMs) are often used in these studies, and have been used to predict potential hotspots and trends of epidemics. However, ENMs are not the best tool for predicting COVID-19 spread due to the virus’ characteristics. This article reviews the application of ENMs for various epidemiological studies in recent decades, comparing advantages and disadvantages of ENM methods for predicting disease characteristics and other models. ENMs can only be used to analyze the impact of environmental disturbances of intermediate hosts during the epidemic transmission process, but SARS-CoV-2 is more reliant on human transmission, leading to poor ENM performance. Therefore, we must choose the appropriate modeling method for the transmission pathways of the disease to accurately predict the epidemic trend. Under appropriate conditions, ENMs can analyze the spread range of epidemics but we must include other interference factors to test and evaluate ENMs accurately. Misusing ENMs would mislead decision-makers. Therefore, when applying ENMs to predict the spread of infectious diseases, the primary consideration must be whether the scientific question meets the ecological assumptions.

Key words: ecological niche model, epidemiology, disease ecology, transmission, disease model