The challenges of data in future pandemics

Shadbolt, Nigel; Brett, Alys; Chen, Min; Marion, Glenn; McKendrick, Iain J.; Panovska‐Griffiths, Jasmina; Pellis, Lorenzo; Reeve, Richard; Swallow, Ben

doi:10.1016/j.epidem.2022.100612

Cited by 19 publications

(9 citation statements)

References 67 publications

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“…The main limitation is related to the overall low quality of the available literature (see also Table 1 ), which in most cases did not provide enough audiological and radiological data, making it difficult to achieve conclusive results. In light of the possibility of future viral pandemics, the need to develop better data ecosystems has been stressed, to obtain higher quality research in an emergency context as well [ 50 ]. With reference to a specific clinical manifestation of viral infections, such as SSNHL, the development of epidemic-specific data collection systems could give the opportunity to obtain stronger clinical evidence, potentially shedding light on causative relationships and contributing to optimized therapy.…”

Section: Discussionmentioning

confidence: 99%

Sudden Sensorineural Hearing Loss in the COVID-19 Pandemic: A Systematic Review and Meta-Analysis

et al. 2022

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Introduction: Accumulating data indicate that patients with COVID-19 could be affected by sudden sensorineural hearing loss (SSNHL). The aim of the study was to analyze the epidemiological and clinical trend of SSNHL occurrence during the COVID-19 pandemic by applying a systematic review and meta-analysis approach. Methods: PubMed, Scopus, Web of Science, ScienceDirect, and Cochrane databases were searched. Results: The seven included studies had adequate relevance to the topic and the quality was fair. The mean age at SSNHL onset ranged from 39.23 to 62.18 years during the pandemic year period (PYP); a meta-analysis of four studies comparing these data with those of previous periods in the same institutions found a younger age during the PYP (pooled mean −0.2848). The heterogeneity was high (76.1935%) and no frank asymmetry was observed in the funnel plot. The SARS-CoV-2 positivity rate of SSNHL patients ranged from 0% to 57.53%. Standard steroid treatments were applied without significant adverse effects. Comprehensively, hearing improvement was achieved for more than half of the cases. No studies reported long-term follow-up data. Conclusions: Further prospective analyses on large series and a long-term follow up on COVID-related SSNHL cases are necessary to address the open questions regarding the causative link between COVID-19 infection and SSNHL.

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Section: Discussionmentioning

confidence: 99%

Sudden Sensorineural Hearing Loss in the COVID-19 Pandemic: A Systematic Review and Meta-Analysis

et al. 2022

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“…Among them, the five-stage lifecycle model is the most common, containing the following stages: budding stage, spread stage, outbreak stage, recession stage, and long-tail stage (see Fig 2 for details). With the advent of the Internet and media convergence technology, a wide range of breaking news can be spread and forwarded rapidly [ 21 ]. Therefore, some scholars have sought to clarify the pattern of news information dissemination through the lifecycle model, to understand and guide the social impact of public opinion [ 22 ].…”

Section: Research Reviewmentioning

confidence: 99%

The impact and management of internet-based public opinion dissemination during emergencies: A case study of Baidu News during the first wave of coronavirus disease 2019 (COVID-19)

Su,

Wang

2024

PLoS ONE

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Background and aims The coronavirus disease 2019 (COVID-19) public health emergency has had a huge impact worldwide. We analyzed news headlines and keywords from the initial period of COVID-19, and explored the dissemination timeline of news related to the epidemic, and the impact of Internet-based media on the public using lifecycle theory and agenda-setting theory. We aimed to explore the impact of Baidu news headlines on public attention during the first wave of COVID-19, as well as the management mechanism of regulatory departments for social public opinion. Methods We searched Baidu News using the keywords “Novel Coronavirus” and “COVID-19” from 8 January to 21 February 2020, a total of 45 days, and used Python V3.6 to extract news samples during the first wave of the epidemic. We used text analysis software to structurally process captured news topics and content summaries, applied VOSviewer V6.19 and Ucinet V6.0 to examine key aspects of the data. Results We analyzed the impact of Baidu News headlines on social opinion during the first wave of COVID-19 in the budding, spread, and outbreak stage of the information lifecycle. From clustering visualization and social network analysis perspectives, we explored the characteristics of Baidu News during the initial stage of the COVID-19. The results indicated that agenda-setting coverage through online media helped to mitigate the negative impact of COVID-19. The findings revealed that news reporting generated a high level of public attention toward a specific emergency event. Conclusions The public requires accurate and objective information on the progress of COVID-19 through Baidu News headlines to inform their planning for the epidemic. Meanwhile, government can enhance the management mechanism of news dissemination, correct false and inaccurate news, and guide public opinion in a positive direction. In addition, timely official announcements on the progress of the COVID-19 outbreak and responses to matters of public concern can help calm tensions and maintain social stability.

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“…This data would provide a comprehensive view of patient health, serving as a basis for generating actionable insights for individual patients and contributing to innovative and efficient research. During the pandemic, challenges hampered the realization of this potential: lack of data standardization and slow data sharing [20] .…”

Section: Data – Harmonization and Standardization Of Clinical And Ima...mentioning

confidence: 99%

Using artificial intelligence and predictive modelling to enable learning healthcare systems (LHS) for pandemic preparedness

Ankolekar,

Eppings,

Bottari

et al. 2024

Computational and Structural Biotechnology Journal

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The challenges of data in future pandemics

Cited by 19 publications

References 67 publications

Sudden Sensorineural Hearing Loss in the COVID-19 Pandemic: A Systematic Review and Meta-Analysis

Sudden Sensorineural Hearing Loss in the COVID-19 Pandemic: A Systematic Review and Meta-Analysis

The impact and management of internet-based public opinion dissemination during emergencies: A case study of Baidu News during the first wave of coronavirus disease 2019 (COVID-19)

Using artificial intelligence and predictive modelling to enable learning healthcare systems (LHS) for pandemic preparedness

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