A Review of Graph Neural Networks in Epidemic Modeling (preprint)

Since the onset of the COVID-19 pandemic, there has been a growing interest in studying epidemiological models. Traditional mechanistic models mathematically describe the transmission mechanisms of infectious diseases. However, they often fall short when confronted with the growing challenges of today. Consequently, Graph Neural Networks (GNNs) have emerged as a progressively popular tool in epidemic research. In this paper, we endeavor to furnish a comprehensive review of GNNs in epidemic tasks and highlight potential future directions. To accomplish this objective, we introduce hierarchical taxonomies for both epidemic tasks and methodologies, offering a trajectory of development within this domain. For epidemic tasks, we establish a taxonomy akin to those typically employed within the epidemic domain. For methodology, we categorize existing work into \textit{Neural Models} and \textit{Hybrid Models}. Following this, we perform an exhaustive and systematic examination of the methodologies, encompassing both the tasks and their technical details. Furthermore, we discuss the limitations of existing methods from diverse perspectives and systematically propose future research directions. This survey aims to bridge literature gaps and promote the progression of this promising field. We hope that it will facilitate synergies between the communities of GNNs and epidemiology, and contribute to their collective progress.

Detection of co-infection of porcine circovirus and porcine epidemic diarrhea virus

In this study, 650 tissue samples which were collected from 16 pig farms in Hubei Province, were used to detect porcine circovirus (PCV) and Porcine epidemic diarrhea virus (PEDV). The results showed that the positive rates of PCV1, PCV2, PCV3 and PEDV single infection were 1.08%, 4.15%, 2.46% and 6.46%, respectively. In the double infections, PEDV+PCV2 had the highest positive rate of 3.54%, followed by PCV2+PCV3, with a positive rate of 1.54%. In multiple infections, PEDV+PCV2+PCV3 had the highest positive rate of 2.00%. The results indicated that the positive rates of PEDV and PCV were decreased compared with the previous studies, but the prevalence of PEDV and PCV was still wide in Hubei Province, and most of which were co-infection.

The impact of COVID-19 pandemic outbreak on education and mental health of Chinese children aged 7-15 years: an online survey.

BACKGROUND: The emerging of psychological problems triggered by COVID-19 particularly in children have been extensively highlighted and emphasized, but original research in this respect is still lagging behind. Therefore, we designed this study to evaluate the impact of COVID-19 pandemic on mental health and the effectiveness and attitudes towards online education among Chinese children aged 7-15 years. METHODS: A detailed questionnaire, comprising of 62 questions was designed and parents or caretakers of 7 to 15 years old children were invited to participate via WeChat, a multi-purpose messaging, social media and mobile payment app, which is widely used by the Chinese population. A total of 668 parents across different regions of China were included. RESULTS: During COVID-19 pandemic, 20.7 and 7.2% children report experiencing post-traumatic stress disorder (PTSD) and depressive symptoms due to the COVID-19 pandemic. PTSD and SMFQ-P scores are significantly higher in middle school and boarding school students compared to primary and day school students. Multiple logistic regression analysis revealed that school system and province of origin are factors significantly associated with developing PSTD symptoms. 44.3% respondents feel online education is effective in gaining knowledge and improving practical and communications skills. 78.0% believe the online education system is efficient. Overall 79.8% respondents are satisfied and children can adapt to this new education system. During the COVID-19 pandemic, we found 1 in five children have PTSD and 1 in 14 children have depressive symptoms. CONCLUSION: In summary, COVID-19 epidemic has caused PTSD and depression symptoms among Chinese children aged 7 to 15 years. In general, a large proportion of respondents are satisfied with online education, but still a substantial proportion of students are not comfortable with this new form of learning. Authorities should optimize online education systems and implement effective interventions to cope with the psychological effects of COVID-19 on children, as it is affecting the global population and remains uncertain when it will end.