covid-19

The dataset contains 877 records with 67 variables, documenting various COVID-19-related indicators in Indonesia. The data spans daily case statistics, including new cases, cumulative cases, recoveries, and fatalities. It also tracks government response measures, such as school and workplace closures, public event restrictions, travel controls, and mask mandates. Additionally, it includes vaccination statistics, government response indices, and mobility changes in different sectors (retail, workplaces, and residential areas).

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138 Views

The dataset contains 877 records with 67 variables, documenting various COVID-19-related indicators in Indonesia. The data spans daily case statistics, including new cases, cumulative cases, recoveries, and fatalities. It also tracks government response measures, such as school and workplace closures, public event restrictions, travel controls, and mask mandates. Additionally, it includes vaccination statistics, government response indices, and mobility changes in different sectors (retail, workplaces, and residential areas).

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86 Views

MaskTIF is collected from different scenarios from ETIF and contains 3,000 thermal infrared face images. The collection time was during the severe COVID-19 epidemic period, and contains a large number of mask-wearing samples.

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52 Views

This dataset includes long-term symptom prevalence data for 27 physical and mental health symptoms associated with Long COVID, extracted from 136 studies spanning up to three years. Key symptoms include fatigue, joint pain, myalgia, respiratory issues (dyspnea, cough), sensory impairments (anosmia, ageusia), neurological symptoms (brain fog), and mental health challenges (anxiety, depression, insomnia).

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167 Views

Please cite the following paper when using this dataset:

Vanessa Su and Nirmalya Thakur, “COVID-19 on YouTube: A Data-Driven Analysis of Sentiment, Toxicity, and Content Recommendations”, Proceedings of the IEEE 15th Annual Computing and Communication Workshop and Conference 2025, Las Vegas, USA, Jan 06-08, 2025 (Paper accepted for publication, Preprint: https://arxiv.org/abs/2412.17180).

Abstract:

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133 Views

The massive damage caused by COVID-19 worldwide over the past two years has highlighted the importance of predicting the spread of infectious diseases. Therefore, with advances in deep learning, numerous and diverse methods have been considered for predicting the spread of infectious diseases. However, these studies have shown that the long-term prediction abilities of deep learning models are insufficient to predict the course and propagation of COVID-19 outbreaks.

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76 Views

The COronaVIrus Disease of 2019 (COVID19) pandemic poses a significant global challenge, with millions

affected and millions of lives lost. This study introduces a privacy conscious approach for early detection of COVID19,

employing breathing sounds and chest X-ray images. Leveraging Blockchain and optimized neural networks, proposed

method ensures data security and accuracy. The chest X-ray images undergo preprocessing, segmentation and feature

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189 Views

This research utilized data from the Oxford University Our World in Data Covid 19 Dataset. This dataset contains data points collected on an ongoing basis from Johns Hopkins University, Center for Systems Science and Engineering COVID-19 data, European Centre for Disease Control, and OXFORD COVID-19 Government Response Tracker, from January 2020 to the present.

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309 Views

The first part of the data set contains the monthly recorded spread of covid-19 across the 6 geopolitical zones of Nigeria for the period of March 2020 to September 2022.

The second part of the data set contains the recorded covid-19 spread during religious festivals across the 6 geopolitical zones of Nigeria.

The third part contains the projected population densities of the 36 states of Nigeria alongside the number of covid-19 test centres in each state.

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348 Views

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