模拟在线媒体新闻中传播疫情的驱动因素,以改进基于事件的监控
Solene Rodde1,2, Pachka Hammami1,2, Asma Mesdour1,2
1French Agricultural Research Centre for International Development (CIRAD), Montpellier, France.
PloS one
|August 4, 2025
概括
在线媒体监控有助于检测疾病爆发. 国际组织,新闻机构,研究小组和兽医当局是禽流感和非洲猪瘟新闻的关键传播者,指导流行情报工作.
科学领域:
- 兽医流行病学 兽医流行病学
- 公共卫生监督是对公共卫生的监督.
- 计算社会科学 计算社会科学
背景情况:
- 流行病情报 (EI) 依赖于监测各种信息来源,包括在线媒体,以检测和跟踪疾病爆发.
- 从网络上自动提取疾病信息的平台 (PADI-web) 有助于从在线来源收集疫情新闻,以便及时响应.
- 了解在线媒体中的沟通驱动因素对于优化EI流程至关重要.
研究的目的:
- 确定影响在线媒体传播关于动物和动物传染病爆发的因素.
- 通过了解哪些来源最具信息性来提高流行病情报的效率.
主要方法:
- 构建两方网络,代表禽流感 (AI) 和非洲猪瘟 (ASF) 疫情的通信流.
- 使用指数随机图模型 (ERGM) 来分析传播的流行病学,社会经济和文化驱动因素.
- 2018年至2019年间通过PADI-web收集的数据,涵盖全球疫情.
主要成果:
- 国际组织和新闻机构比一般的在线新闻网站更有可能与AI和ASF疫情进行沟通.
- 与新闻网站相比,研究机构 (针对AI) 和兽医当局 (针对ASF) 也表现出更高的沟通可能性.
- 网络分析揭示了AI和ASF基于来源类型和爆发特征的独特通信模式.
结论:
- 关于动物和动物传染病的在线媒体的沟通模式是由特定的来源类型和疫情特征驱动的.
- EI从业者可以通过针对本研究中确定的专业来源来完善监测策略.
- 这些发现支持一种更有效,更有针对性的流行病情报方法,同时也突出了代表性不足的地区潜在的数据差距.
相关概念视频
01:18Steps in Outbreak Investigation
204
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
204
01:26Principles of Disease Surveillance
181
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
181
01:21Causality in Epidemiology
847
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
847
01:25Statistical Methods for Analyzing Epidemiological Data
536
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
536
02:09Bystander Effect
9.6K
The discussion of bullying highlights the problem of witnesses not intervening to help a victim. This is a common occurrence, as the following well-publicized event demonstrates. In 1964, in Queens, New York, a 19-year-old woman named Kitty Genovese was attacked by a person with a knife near the back entrance to her apartment building and again in the hallway inside her apartment building. When the attack occurred, she screamed for help numerous times and eventually died from her stab wounds.
9.6K
01:26Introduction to Epidemiology
1.0K
Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
1.0K