PLoS One . Dissemination of information in event-based surveillance, a case study of Avian Influenza - FluTrackers mentioned

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PLoS One


. 2023 Sep 5;18(9):e0285341.
doi: 10.1371/journal.pone.0285341. eCollection 2023. Dissemination of information in event-based surveillance, a case study of Avian Influenza

Sarah Valentin ^{1 2 3 4} , Bahdja Boudoua ^{1 2} , Kara Sewalk ⁵ , Nejat Arınık ² , Mathieu Roche ^{1 2 3} , Renaud Lancelot ^{1 3} , Elena Arsevska ^{1 3}



Affiliations

• PMID: 37669265
• DOI: 10.1371/journal.pone.0285341

Abstract

Event-Based Surveillance (EBS) tools, such as HealthMap and PADI-web, monitor online news reports and other unofficial sources, with the primary aim to provide timely information to users from health agencies on disease outbreaks occurring worldwide. In this work, we describe how outbreak-related information disseminates from a primary source, via a secondary source, to a definitive aggregator, an EBS tool, during the 2018/19 avian influenza season. We analysed 337 news items from the PADI-web and 115 news articles from HealthMap EBS tools reporting avian influenza outbreaks in birds worldwide between July 2018 and June 2019. We used the sources cited in the news to trace the path of each outbreak. We built a directed network with nodes representing the sources (characterised by type, specialisation, and geographical focus) and edges representing the flow of information. We calculated the degree as a centrality measure to determine the importance of the nodes in information dissemination. We analysed the role of the sources in early detection (detection of an event before its official notification) to the World Organisation for Animal Health (WOAH) and late detection. A total of 23% and 43% of the avian influenza outbreaks detected by the PADI-web and HealthMap, respectively, were shared on time before their notification. For both tools, national and local veterinary authorities were the primary sources of early detection. The early detection component mainly relied on the dissemination of nationally acknowledged events by online news and press agencies, bypassing international reporting to the WAOH. WOAH was the major secondary source for late detection, occupying a central position between national authorities and disseminator sources, such as online news. PADI-web and HealthMap were highly complementary in terms of detected sources, explaining why 90% of the events were detected by only one of the tools. We show that current EBS tools can provide timely outbreak-related information and priority news sources to improve digital disease surveillance.

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Early detection of public health hazards constitutes a fundamental component of efficient outbreak management [22]. It may be the main determinant in selecting the appropriate response, thus minimising morbidity and mortality caused by an infectious disease [23]. Event-based surveillance should not be considered a replacement for traditional indicator-based surveillance, but rather, complementary to routinely collected public health surveillance data.

While the reporting of AI events by the EBS tools was highly effective, timely, and reactive, a bottleneck may arise at the step of manual analysis of the detected events. The strength of EBS relies heavily on adequate human resources to feed decision-making chains based on detected events. Therefore, in our future work, we will explore how the detected events can be useful for risk assessment and risk mapping.
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Role of the sources

Our results highlight three groups of sources regarding their role in the dissemination of outbreak-related information. EBS tools are aggregators. It is important to note that our results did not reflect ProMED-mail intrinsic performance as an EBS tool, that is, expert network sharing outbreak-related information, but as an intermediate source of HealthMap. Local and national authorities and veterinarians were emitters and were the most important primary sources of events. They produce information that is acknowledged at the local/national level, mostly verified by laboratory tests, and is susceptible to being reported in the media. WOAH, online news, press agencies, social media, and several research organisations combined both abilities by collecting information from a wide range of sources and being highly visible by collector sources in the network (online news, EBS tools). Network performance was driven by the presence of a small number of sources with high individual all-degrees, such as WOAH, Reuters, Xinhua, and several social network platforms. These sources played the role of hubs, not only filtering and disseminating information but also ensuring a connection between different groups in the network [19]. The presence of hubs was not the only feature of network performance, as early detection mostly relied on online news sources with individual low all-degrees. Thus, the early components of EBS networks also relied on their ability to monitor a large number of individually low-performant sources.

National online news plays a major role in early detection by disseminating announcements from local and national veterinary authorities, thus making them detectable by EBS tools. Zhang et al. found out that national newspapers (referred to as “local” newspapers in their methods) provided more specific information about the local Zika virus emergence in Brazil than did international newspapers; similar findings were made for outbreak detection in Nepal [12]. In this study, local sources were more likely to identify a unique event than international sources, indicating that international sources were more likely to be redundant by publishing multiple reports about the same event [12]. This emphasises the need to target local and national sources available on the web, going beyond sources published in English. The monitoring of multi-lingual sources, integrated into the two EBS tools in our work, is a prerequisite for maximising access to national and local media. The retrieval and analysis of non-English texts have been enhanced and facilitated by the improvement of methods for multi-lingual text processing, such as textual classification [24, 25] and deep-learning-based translation [26]. We believe that efforts to integrate multi-lingual sources will benefit both the Se and timeliness of EBS tools.

Social platforms, mostly used by HealthMap, include generic platforms such as Twitter, but also specialised blogs such as FluTrackers and AvianFluDiary. Specialised blogs are relevant sources for integration into EBS, as they rely on the collection of information from numerous sources, as highlighted by their high median in-degree, previously filtered by domain-specialised moderators. Health blogs were found to cite less sources than online news in a study evaluating H1N1/Swine Flu coverage in the media [27], which is not in line with the highest in-degree found in our study. However, the difference in the number and nature of sources evaluated (eight online news [27]) makes the study hardly comparable. They also translated news from national languages into English, facilitating access to local field information. In addition, owing to their non-official status, online blogs are more prone to communicate events before official notifications. While the classical method of web monitoring is traditionally keyword-oriented (e.g., systematic monitoring of combinations of keywords), source-based monitoring (i.e., systematic monitoring of a specific source) is a costless and easy way to improve existing EBS tools. For instance, retrieving news directly from official government health websites would enhance the geographic representativeness of news aggregators such as Google News [28, 29].

It is important to note that our results were specific to the model disease and study period. For example, the Bulgarian veterinary authority appeared to be an important source because 22 outbreaks were observed in Bulgaria during the study period, including a new incursion of the Highly Pathogenic Avian Influenza (HPAI) H5N8 subtype [30] widely reported by Bulgarian media.
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[sharon sanders]

Thank you to the authors for documenting that health map uses FluTrackers and Avian Flu Diary as sources. A lot of scholars skip over our contribution to digital disease detection efforts because we have no self promotion campaigns.