Constructing public health evidence knowledge graph for decision-making support from COVID-19 literature of modelling study

Construction and evaluation of a domain-specific knowledge graph for knowledge discovery

Purpose

This study aims to evaluate a method of building a biomedical knowledge graph (KG).

Design/methodology/approach

This research first constructs a COVID-19 KG on the COVID-19 Open Research Data Set, covering information over six categories (i.e. disease, drug, gene, species, therapy and symptom). The construction used open-source tools to extract entities, relations and triples. Then, the COVID-19 KG is evaluated on three data-quality dimensions: correctness, relatedness and comprehensiveness, using a semiautomatic approach. Finally, this study assesses the application of the KG by building a question answering (Q&A) system. Five queries regarding COVID-19 genomes, symptoms, transmissions and therapeutics were submitted to the system and the results were analyzed.

Findings

With current extraction tools, the quality of the KG is moderate and difficult to improve, unless more efforts are made to improve the tools for entity extraction, relation extraction and others. This study finds that comprehensiveness and relatedness positively correlate with the data size. Furthermore, the results indicate the performances of the Q&A systems built on the larger-scale KGs are better than the smaller ones for most queries, proving the importance of relatedness and comprehensiveness to ensure the usefulness of the KG.

Originality/value

The KG construction process, data-quality-based and application-based evaluations discussed in this paper provide valuable references for KG researchers and practitioners to build high-quality domain-specific knowledge discovery systems.

Pandemic prevention and personality psychology: Gender differences in preventive health behaviors during COVID-19 and the roles of agreeableness and conscientiousness

One of the greatest public health crises in recent times, the COVID-19 pandemic, has come with a myriad of challenges in terms of health communication and public cooperation to prevent the spread of the disease. Understanding which are the key determinants that make certain individuals more cooperative is key in effectively tackling pandemics and similar future challenges. In the present study (N = 800), we investigated whether gender differences in compliance with preventive health behaviors (PHB) at the onset of the COVID-19 pandemic could be established, and, if so, whether the personality traits of agreeableness and conscientiousness could help explain this presumed relationship. Consistent with our theorizing, we found women to score higher than men on agreeableness and conscientiousness, and to be more willing to comply with a set of PHB. Importantly, both personality traits were found to mediate the gender-compliance link. This means that women's greater compliance levels with PHB could, at least in part, be attributed to their higher agreeableness and conscientiousness scores. A greater understanding of the determinants of PHB in terms of gender and associated personality traits may help identify options for developing more effective communication campaigns, both in terms of communication channel selection and message content.