Prediction of COVID-19 Cases based on Human Behavior using DNN Regressor for Canada

Tripathy, Dharitri; Camorlinga, Sergio

doi:10.1109/iccworkshops50388.2021.9473812

Cited by 3 publications

(5 citation statements)

References 9 publications

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“…It has been used to analyze the relationship between the growth of COVID-19 cases and human behavior such as isolation, wearing masks outside home, and contact with symptomatic persons. Tripathy and Camorlinga ( 2021 ) calculated the mutual information regression score to assess the feature importance and found high relevance between case increase and behavioral features including avoiding gatherings, avoiding guests at home, wearing masks at public transport, and willingness to isolate.…”

Section: Using Big Data To Model Human Behavior In Covid-19mentioning

confidence: 99%

“…Machine learning models including conventional models such as decision tree, support vector machine, and deep learning models such as long short-term memory network (LSTM) (Hochreiter and Schmidhuber, 1997 ) intend to learn a function that can recognize patterns or make predictions from data automatically (Han et al, 2022 ). Researchers have been employing machine learning models to integrate human behavior to forecast confirmed cases due to its ease of inputting multiple features (Ramchandani et al, 2020 ; Rabiolo et al, 2021 ; Rashed and Hirata, 2021 ; Tripathy and Camorlinga, 2021 ). Rabiolo et al ( 2021 ) developed a feed-forward neural network autoregression that integrates Google Trends of searches of symptoms and conventional COVID-19 metrics to forecast the development of the COVID-19 pandemic.…”

Section: Using Big Data To Leverage Human Behavior In Covid-19mentioning

confidence: 99%

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Human behavior in the time of COVID-19: Learning from big data

et al. 2023

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Since the World Health Organization (WHO) characterized COVID-19 as a pandemic in March 2020, there have been over 600 million confirmed cases of COVID-19 and more than six million deaths as of October 2022. The relationship between the COVID-19 pandemic and human behavior is complicated. On one hand, human behavior is found to shape the spread of the disease. On the other hand, the pandemic has impacted and even changed human behavior in almost every aspect. To provide a holistic understanding of the complex interplay between human behavior and the COVID-19 pandemic, researchers have been employing big data techniques such as natural language processing, computer vision, audio signal processing, frequent pattern mining, and machine learning. In this study, we present an overview of the existing studies on using big data techniques to study human behavior in the time of the COVID-19 pandemic. In particular, we categorize these studies into three groups—using big data to measure, model, and leverage human behavior, respectively. The related tasks, data, and methods are summarized accordingly. To provide more insights into how to fight the COVID-19 pandemic and future global catastrophes, we further discuss challenges and potential opportunities.

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Section: Using Big Data To Model Human Behavior In Covid-19mentioning

confidence: 99%

Section: Using Big Data To Leverage Human Behavior In Covid-19mentioning

confidence: 99%

Human behavior in the time of COVID-19: Learning from big data

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Machine learning models including conventional models such as decision tree, support vector machine, and deep learning models such as long short-term memory network (LSTM) (Hochreiter and Schmidhuber 1997) intend to learn a function that can recognize patterns or make predictions from data automatically (Han, Pei, and Tong 2022). Researchers have been employing machine learning models to integrate human behavior to forecast confirmed cases due to its ease of inputting multiple features (Rabiolo et al 2021;Tripathy and Camorlinga 2021;Ramchandani, Fan, and Mostafavi 2020;Rashed and Hirata 2021). Rabiolo et al (2021) developed a feed-forward neural network autoregression that integrates Google Trends of searches of symptoms and conventional COVID-19 metrics to forecast the development of the COVID-19 pandemic.…”

Section: Machine Learning Modelmentioning

confidence: 99%

Human Behavior in the Time of COVID-19: Learning from Big Data

Lyu¹,

Arsal²,

Zhao³

et al. 2023

Preprint

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Since the World Health Organization (WHO) characterized COVID-19 as a pandemic in March 2020, there have been over 600 million confirmed cases of COVID-19 and more than six million deaths as of October 2022. The relationship between the COVID-19 pandemic and human behavior is complicated. On one hand, human behavior is found to shape the spread of the disease. On the other hand, the pandemic has impacted and even changed human behavior in almost every aspect. To provide a holistic understanding of the complex interplay between human behavior and the COVID-19 pandemic, researchers have been employing big data techniques such as natural language processing, computer vision, audio signal processing, frequent pattern mining, and machine learning. In this study, we present an overview of the existing studies on using big data techniques to study human behavior in the time of the COVID-19 pandemic. In particular, we categorize these studies into three groups -using big data to measure, model, and leverage human behavior, respectively. The related tasks, data, and methods are summarized accordingly. To provide more insights into how to fight the COVID-19 pandemic and future global catastrophes, we further discuss challenges and potential opportunities.

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“…Behavioral data have also been used as important predictors of the number of covid‐19 cases. 38 In Italy, Duradoni et al 39 studied the psychological profile of people that were compliant with the government regulations a month after the lockdown started, while Guazzini et al 40 tested changes in the psychological adaptation across the first two waves of the pandemic. In this context, we consider the evolution of the compliance of Italian population, quantifying variations of this compliance over time, across socio‐demographic groups, and studying its associations with the severity of the measures adopted by the Italian government throughout the pandemic.…”

Section: Related Workmentioning

confidence: 99%

“…For example, Krekel et al 37 studied the associations between happiness and level of compliance with government regulations. Behavioral data have also been used as important predictors of the number of covid‐19 cases 38 . In Italy, Duradoni et al 39 studied the psychological profile of people that were compliant with the government regulations a month after the lockdown started, while Guazzini et al 40 tested changes in the psychological adaptation across the first two waves of the pandemic.…”

Section: Related Workmentioning

confidence: 99%

Dynamic modeling of the Italians' attitude towards Covid‐19

Aliverti

Russo

2022

Statistics in Medicine

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We analyze repeated cross‐sectional survey data collected by the Institute of Global Health Innovation, to characterize the perception and behavior of the Italian population during the covid‐19 pandemic, focusing on the period that spans from April 2020 to July 2021. To accomplish this goal, we propose a Bayesian dynamic latent‐class regression model, that accounts for the effect of sampling bias including survey weights into the likelihood function. According to the proposed approach, attitudes towards covid‐19 are described via ideal behaviors that are fixed over time, corresponding to different degrees of compliance with spread‐preventive measures. The overall tendency toward a specific profile dynamically changes across survey waves via a latent Gaussian process regression, that adjusts for subject‐specific covariates. We illustrate the evolution of Italians' behaviors during the pandemic, providing insights on how the proportion of ideal behaviors has varied during the phases of the lockdown, while measuring the effect of age, sex, region and employment of the respondents on the attitude toward covid‐19 .

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Prediction of COVID-19 Cases based on Human Behavior using DNN Regressor for Canada

Cited by 3 publications

References 9 publications

Human behavior in the time of COVID-19: Learning from big data

Human behavior in the time of COVID-19: Learning from big data

Human Behavior in the Time of COVID-19: Learning from Big Data

Dynamic modeling of the Italians' attitude towards Covid‐19

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