ABSTRACT
Keeping track of scientific challenges, advances and emerging directions is a fundamental part of research. However, researchers face a flood of papers that hinders discovery of important knowledge. In biomedicine, this directly impacts human lives. To address this problem, we present a novel task of extraction and search of scientific challenges and directions, to facilitate rapid knowledge discovery. We construct and release an expert-annotated corpus of texts sampled from full-length papers, labeled with novel semantic categories that generalize across many types of challenges and directions. We focus on a large corpus of interdisciplinary work relating to the COVID-19 pandemic, ranging from biomedicine to areas such as AI and economics. We apply a model trained on our data to identify challenges and directions across the corpus and build a dedicated search engine. In experiments with 19 researchers and clinicians using our system, we outperform a popular scientific search engine in assisting knowledge discovery. Finally, we show that models trained on our resource generalize to the wider biomedical domain and to AI papers, highlighting its broad utility. We make our data, model and search engine publicly available.
ABSTRACT
BACKGROUND: Global influenza virus circulation decreased during the COVID-19 pandemic, possibly due to widespread community mitigation measures. Cambodia eased some COVID-19 mitigation measures in June and July 2020. On 20 August a cluster of respiratory illnesses occurred among residents of a pagoda, including people who tested positive for influenza A but none who were positive for SARS-CoV-2. METHODS: A response team was deployed on 25 August 2020. People with influenza-like illness (ILI) were asked questions regarding demographics, illness, personal prevention measures, and residential arrangements. Respiratory swabs were tested for influenza and SARS-Cov-2 by real-time reverse transcription PCR, and viruses were sequenced. Sentinel surveillance data were analyzed to assess recent trends in influenza circulation in the community. RESULTS: Influenza A (H3N2) viruses were identified during sentinel surveillance in Cambodia in July 2020 prior to the reported pagoda outbreak. Among the 362 pagoda residents, 73 (20.2%) ILI cases were identified and 40 were tested, where 33/40 (82.5%) confirmed positive for influenza A (H3N2). All 40 were negative for SARS-CoV-2. Among the 73 residents with ILI, none were vaccinated against influenza, 47 (64%) clustered in 3/8 sleeping quarters, 20 (27%) reported often wearing a mask, 27 (36%) reported often washing hands, and 11 (15%) reported practicing social distancing. All viruses clustered within clade 3c2.A1 close to strains circulating in Australia in 2020. CONCLUSIONS: Circulation of influenza viruses began in the community following the relaxation of national COVID-19 mitigation measures, and prior to the outbreak in a pagoda with limited social distancing. Continued surveillance and influenza vaccination are required to limit the impact of influenza globally.