Online dashboard and data analysis approach for assessing COVID-19 case and death data.
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ABSTRACT:
SUBMITTER: Florez H
PROVIDER: S-EPMC7450472 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Publications
Online dashboard and data analysis approach for assessing COVID-19 case and death data.
F1000Research 20200608
The 2019-2020 global pandemic has been caused by a disease called coronavirus disease 2019 (COVID-19). This disease has been caused by the Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2). By April 30 2020, the World Health Organization reported 3,096,626 cases and 217,896 deaths, which implies an exponential growth for infection and deaths worldwide. Currently, there are various computer-based approaches that present COVID-19 data through different types of charts, which is very use ...[more]
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Project description:BackgroundThe COVID-19 outbreak has affected the lives of millions of people by causing a dramatic impact on many health care systems and the global economy. This devastating pandemic has brought together communities across the globe to work on this issue in an unprecedented manner.ObjectiveThis case study describes the steps and methods employed in the conduction of a remote online health hackathon centered on challenges posed by the COVID-19 pandemic. It aims to deliver a clear implementation road map for other organizations to follow.MethodsThis 4-day hackathon was conducted in April 2020, based on six COVID-19-related challenges defined by frontline clinicians and researchers from various disciplines. An online survey was structured to assess: (1) individual experience satisfaction, (2) level of interprofessional skills exchange, (3) maturity of the projects realized, and (4) overall quality of the event. At the end of the event, participants were invited to take part in an online survey with 17 (+5 optional) items, including multiple-choice and open-ended questions that assessed their experience regarding the remote nature of the event and their individual project, interprofessional skills exchange, and their confidence in working on a digital health project before and after the hackathon. Mentors, who guided the participants through the event, also provided feedback to the organizers through an online survey.ResultsA total of 48 participants and 52 mentors based in 8 different countries participated and developed 14 projects. A total of 75 mentorship video sessions were held. Participants reported increased confidence in starting a digital health venture or a research project after successfully participating in the hackathon, and stated that they were likely to continue working on their projects. Of the participants who provided feedback, 60% (n=18) would not have started their project without this particular hackathon and indicated that the hackathon encouraged and enabled them to progress faster, for example, by building interdisciplinary teams, gaining new insights and feedback provided by their mentors, and creating a functional prototype.ConclusionsThis study provides insights into how online hackathons can contribute to solving the challenges and effects of a pandemic in several regions of the world. The online format fosters team diversity, increases cross-regional collaboration, and can be executed much faster and at lower costs compared to in-person events. Results on preparation, organization, and evaluation of this online hackathon are useful for other institutions and initiatives that are willing to introduce similar event formats in the fight against COVID-19.
| S-EPMC7872325 | biostudies-literature
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Project description:This paper reports the results of a recent survey of Chinese WeChat networkers (n = 2015, August 2020) about China's mental health conditions under COVID-19. The purpose of the survey was to measure symptoms of depression, anxiety, and somatization by using a standard 18-item battery and assess how the results were related to an individual's socioeconomic status, lifestyle, and social capital under an ongoing pandemic. The survey reveals that the pandemic has had a significant impact, as the respondents had more serious mental symptoms when their residential communities exhibited a greater exposure to the spread of the virus. The socioeconomic status of the respondents was negatively associated with the mental symptoms. It modified the impact of COVID-19, and its effect was substantially mediated by measures of lifestyle and social capital.
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Project description:The novel Coronavirus disease (COVID-19) was first identified in Wuhan, China in December 2019 but later spread to other parts of the world. The disease as at the point of writing this paper has been declared a pandemic by the World Health Organization (WHO). The application of mathematical models, artificial intelligence, big data, and similar methodologies are potential tools to predict the extent of the spread and effectiveness of containment strategies to stem the transmission of this disease. In societies with constrained data infrastructures, modeling and forecasting COVID-19 becomes an extremely difficult endeavor. Nonetheless, we propose an online forecasting mechanism that streams data from the Nigeria Center for Disease Control to update the parameters of an ensemble model which in turn provides updated COVID-19 forecasts every 24 hours. The ensemble combines an Auto-Regressive Integrated Moving Average model (ARIMA), Prophet - an additive regression model developed by Facebook, and a Holt-Winters Exponential Smoothing model combined with Generalized Autoregressive Conditional Heteroscedasticity (GARCH). The outcomes of these efforts are expected to provide academic thrust in guiding the policymakers in the deployment of containment strategies and/or assessment of containment interventions in stemming the spread of the disease in Nigeria.
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