The spread of information and other stochastic processes in biology: epidemics, misinformation and collective behaviour.

生物学中信息的传播和其他随机过程：流行病、错误信息和集体行为。

基本信息

批准号：
2445329
负责人：
金额：
--
依托单位：
University of Bath
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2445329
关键词：
spread information other stochastic processes

项目摘要

Non-pharmaceutical interventions, such as mask-wearing and social distancing, are important tools to tackle the spread of emergent pandemic disease. They can be used to slow the progress of an outbreak or suppress it completely if carefully implemented and strictly adhered to. Much of the effectiveness of social distancing strategies rely upon the behaviours of individuals; how conscientiously they follow the advice and how successfully they encourage others to do the same. In the literature, the changes in behaviour arise from the awareness of individuals. This awareness is modelled through the spread of information through contacts. Importantly, there is feedback between changes in behaviour and the progression of the disease itself.Besides that, the spread of awareness has important implications in many complex systems in biology and society. The differences are how the awareness feeds back into other dynamics. In ecology, animals might alert the rest of the community of the presence of invaders or predators - in which case aware individuals would become less vulnerable - or transmit knowledge on food sources' location - increasing the survival rate of those with whom the information has been shared. Furthermore, public opinion regarding a political issue might change as people become more informed about the problem. In recent years, we have seen an increase in the spread of false information designed to influence people's thoughts and views concerning public figures, political issues and health matters - such as climate change and vaccination. Consequently, it is of fundamental interest to develop a means of identifying false information and effective control measures to hinder the transmission of misinformation.My research project concerns the study of information spread processes and their feedback into biological complex systems. So far, using a model for the feedback of awareness and behaviour change on epidemics for a population comprised of trusting and distrusting individuals, we have shown the existence of regions of parameter space in which the disease can be suppressed or merely mitigated. We also studied the stochastic process of information spread in networks and obtained theoretical and numerical results that motivate further work on the topic.To extend the research done so far, we aim to include other information dynamics to make the model more realistic. These might include fading and refreshing mechanisms to account for memory loss and information generation. Due to the complexities of the model, it might be necessary to consider timescale separation frameworks to obtain analytical approximations. In that regard, the work developed by Parsons and Rogers to reduce the manifold dimension for systems with fast-slow dynamics is a prospective tool for initial work. Additionally, we are interested in the spread of misinformation and its effect on society. We are getting in contact with experts on misinformation and human behaviour to develop a realistic model of how people react to and spread (mis-)information. Tim Rogers' expertise will be significant to the analysis of the model on graphs and networks, whilst Kit Yates' experience with stochastic modelling and simulations will be fundamental for the success of the project.

非药物干预措施（例如戴面膜和社会疏远）是应对新兴大流行病的重要工具。如果仔细实施并严格遵守，它们可用于减慢爆发的进度或完全抑制。社会疏远策略的许多有效性都取决于个人的行为；他们如何认真遵守建议，以及他们如何成功地鼓励他人做同样的事情。在文献中，行为的变化来自个人的意识。这种意识是通过通过联系人传播的信息来建立的。重要的是，行为的变化与疾病本身的进展之间存在反馈。看来，意识的传播在生物学和社会中许多复杂系统中具有重要意义。差异是意识如何反馈到其他动态中。在生态学中，动物可能会提醒社区其他地区的入侵者或掠食者的存在 - 在这种情况下，意识到的人会变得脆弱 - 或传递有关食品来源的位置知识 - 增加了与信息共享的人的生存率。此外，随着人们对这个问题的了解，有关政治问题的公众舆论可能会改变。近年来，我们发现，旨在影响人们有关公众人物，政治问题和健康问题（例如气候变化和疫苗接种）的虚假信息的传播增加了。因此，开发一种确定虚假信息和有效控制措施以阻碍错误信息传播的方法是根本的兴趣。到目前为止，使用模型来反馈由信任和不信任的个体组成的人群的意识和行为变化，我们已经展示了可以抑制或仅仅减轻该疾病的参数空间区域的存在。我们还研究了网络中信息传播的随机过程，并获得了理论和数值结果，这些结果激发了该主题的进一步工作。为了扩展到目前为止所做的研究，我们旨在包括其他信息动态，以使模型更现实。这些可能包括褪色和清爽的机制，以解释记忆丢失和信息的产生。由于模型的复杂性，可能有必要考虑时间尺度分离框架以获得分析近似值。在这方面，Parsons和Rogers开发的工作以减少具有快速动态的系统的多种尺寸是初始工作的前瞻性工具。此外，我们对错误信息的传播及其对社会的影响感兴趣。我们正在与有关错误信息和人类行为的专家接触，以开发人们对人们如何反应和传播（错误）信息的现实模型。蒂姆·罗杰斯（Tim Rogers）的专业知识对于在图形和网络上对模型的分析将具有重要意义，而Kit Yates在随机建模和仿真方面的经验将对项目的成功至关重要。