Introduction Citizen science (CS) is an emerging approach in public health to harness the collective intelligence of individuals to augment traditional scientific efforts. However, citizens’ viewpoint, especially the hard-to-reach population, is lacking in current outbreak-related literature. We aim to understand the awareness, readiness and feasibility of outbreak-related CS, including digitally enabled CS, in low-income and middle-income countries. Methods This mixed-method study was conducted in nine countries between October 2022 and June 2023. Recruitment through civil society targeted the general population, marginalised/indigenous groups, youth and community health workers. Participants (aged ≥18 years) completed a quantitative survey, and a subset participated in focus group discussions (FGDs). Results 2912 participants completed the survey and 4 FGDs were conducted in each country. Incorporating participants’ perspectives, CS is defined as the practice of active public participation, collaboration and communication in all aspects of scientific research to increase public knowledge, create awareness, build trust and facilitate information flow between citizens, governments and scientists. In Bangladesh, Indonesia, the Philippines, Cameroon and Kenya, majority were unaware of outbreak-related CS. In India and Uganda, majority were aware but unengaged, while in Nepal and Zimbabwe, majority participated in CS before. Engagement approaches should consider different social and cultural contexts, while addressing incentivisation, attitudes and practicality factors. Overall, 76.0% expressed interest in digital CS but needed training to build skills and confidence. Digital CS was perceived as convenient, safer for outbreak-related activities and producing better quality and quantity of data. However, there were concerns over non-inclusion of certain groups, data security and unclear communication. Conclusion CS interventions need to be relatable and address context-specific factors influencing CS participation. Digital CS has the potential to facilitate collaboration, but capacity and access issues must be considered to ensure inclusive and sustainable engagement. Data are available on reasonable request. De-identified data may be made available on written, detailed requests directed to the corresponding author. Requests will be reviewed based on scientific merit, ethical review, legal issues and regulatory requirements.

中文翻译：

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为疫情准备和应对建立公民科学情报：在九个国家进行的混合方法研究，以评估知识、准备情况和可行性

简介 公民科学 (CS) 是公共卫生领域的一种新兴方法，旨在利用个人的集体智慧来增强传统的科学工作。然而，当前与疫情相关的文献缺乏公民的观点，尤其是难以接触到的人群的观点。我们的目标是了解低收入和中等收入国家对疫情相关的 CS（包括数字化 CS）的认识、准备情况和可行性。方法 这项混合方法研究于 2022 年 10 月至 2023 年 6 月在 9 个国家进行。通过民间社会招募的对象是普通人群、边缘化/土著群体、青年和社区卫生工作者。参与者（年龄≥18岁）完成了一项定量调查，其中一部分参加了焦点小组讨论（FGD）。结果 2912 名参与者完成了调查，每个国家进行了 4 次 FGD。结合参与者的观点，CS被定义为公众在科学研究各个方面积极参与、协作和沟通的实践，以增加公众知识、提高认识、建立信任并促进公民、政府和科学家之间的信息流动。在孟加拉国、印度尼西亚、菲律宾、喀麦隆和肯尼亚，大多数人不知道与疫情相关的CS。在印度和乌干达，大多数人知道但没有参与，而在尼泊尔和津巴布韦，大多数人以前参加过CS。参与方法应考虑不同的社会和文化背景，同时解决激励、态度和实用性因素。总体而言，76.0% 的人表示对数字计算机科学感兴趣，但需要培训来培养技能和信心。数字化 CS 被认为对于疫情相关活动来说是方便、安全的，并且可以产生更好质量和数量的数据。然而，人们担心某些群体未被纳入、数据安全和沟通不明确。结论 CS 干预措施需要具有相关性，并解决影响 CS 参与的特定背景因素。数字 CS 具有促进协作的潜力，但必须考虑容量和访问问题，以确保包容性和可持续的参与。可根据合理要求提供数据。根据向相应作者提出的书面详细请求，可以提供去识别化数据。将根据科学价值、伦理审查、法律问题和监管要求对请求进行审查。