COVID-19: Challenges and Advisory

Udgata, Siba K.; Suryadevara, Nagender Kumar

doi:10.1007/978-981-15-7654-6_1

Cited by 6 publications

(3 citation statements)

References 27 publications

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“…In this epidemic control measure, basic data (e.g, demographics) about the individuals are collected at the time of both voluntarily and involuntarily checkups [58]. This data assist in analyzing the causes of the spread as well as the estimation of lethality of the virus for different age-groups [59].…”

Section: Basic Data (Eg Demographics) Collection At the Time Of Botmentioning

confidence: 99%

Towards Privacy Paradigm Shift Due to the Pandemic: A Brief Perspective

Majeed

Lee

2021

Inventions

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With the advent of the pandemic (e.g., novel corona virus disease 2019 (COVID-19)), a tremendous amount of data about individuals are collected by the health authorities on daily basis for curbing the disease’s spread. The individuals’ data collection/processing at a massive scale for community well-being with the help of digital solutions (e.g., mobile apps for mobility and proximity analysis, contact tracing through credit card usage history, facial recognition through cameras, and crowd analysis using cellular networks data etc.) raise several privacy concerns. Furthermore, the privacy concerns that are arising mainly due to the fine-grained data collection has hindered the response to tackle this pandemic in many countries. Hence, acquiring/handling individuals data with privacy protection has become a vibrant area of research in these pandemic times. This paper explains the shift in privacy paradigm due to the pandemic (e.g., COVID-19) which involves more and detailed data collection about individuals including locations and demographics. We explain technical factors due to which the people’s privacy is at higher risk in the COVID-19 time. In addition, we discuss privacy concerns in different epidemic control measures (ECMs) (e.g., contact tracing, quarantine monitoring, and symptoms reporting etc.) employed by the health authorities to tackle this disease. Further, we provide an insight on the data management in the ECMs with privacy protection. Finally, the future prospects of the research in this area tacking into account the emerging technologies are discussed. Through this brief article, we aim to provide insights about the vulnerability to user’s privacy in pandemic times, likely privacy issues in different ECMs adopted by most countries around the world, how to preserve user’s privacy effectively in all phases of the ECMs considering relevant data in loop, and conceptual foundations of ECMs to fight with future pandemics in a privacy preserving manner.

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Section: Basic Data (Eg Demographics) Collection At the Time Of Botmentioning

confidence: 99%

Towards Privacy Paradigm Shift Due to the Pandemic: A Brief Perspective

Majeed

Lee

2021

Inventions

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“…10 The pandemic has gone beyond provincial, radical, conceptual, spiritual, social, and pedagogical boundaries. 11 The Islamic perspective offers at least two concepts to understand pandemics. First, the pandemic is a natural calamity, or an absolute truth of divine planning (sunnatullāh), which happens only for the will of Allah.…”

Section: The Pandemic In the Islamic Worldmentioning

confidence: 99%

COVID-19 Pandemic in Indonesia: Some Reflections from Bażl Al-Māʿūn by Ibn Ḥajr al-ʿAsqalānī

Qudsy

Pabbajah²,

Jubba³

et al. 2022

AFKAR

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History and pandemics are two inseparable entities, yet often forgotten. The occurrence of a pandemic in a certain time and place has always become a critical object of study and documentation, thus generating innumerable research literature. This research attempts to re-state the urgency of historical literature as a source of knowledge on dealing with the Covid-19 crisis through the religious scholars’ approach. The data were compiled through observation and literature review with content analysis method on Bażl al-Māʿūn of Ibn Ḥajr al-ʿAsqalānī, a classic book containing pandemic studies sourced from hadith and the history of the early Muslim community. The result of this study reveals that classical religious literature as historical knowledge could provide contextual solutions for society. The study of the historical works not only gives clues on the past events but also provides material to contextualise the attempt to build newly-induced awareness in the community. Learning from past events teaches society that pandemics are recurring events. Some similarities and differences are seen in every part of the pandemic. Thus, religious scholars serve as agents who disseminate the lesson learned from the past to prevent the recurrence of similar events in the future. This way, people of today should refer to the past to set some appropriate strategies for coping with the pandemic. Likewise, a historical account mentions the relevance of some terminologies that are currently used around Covid-19.

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“…We cannot blame the doctors since they are responsible for many people and have few resources. However, we can assist or ease the burden on them by developing a model that predicts whether a person is potentially positive or negative [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

A Novel Weighted Consensus Machine Learning Model for COVID-19 Infection Classification Using CT Scan Images

2021

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As COVID-19 has spread rapidly, detection of the COVID-19 infection from radiology and radiography images is probably one of the quickest ways to diagnose the patients. Many researchers found the necessity to utilize chest X-ray and chest computed tomography imaging to diagnose COVID-19 infection. In this paper, our objective is to minimize the false negatives and false positives in the detection process. Reduction in the number of false negatives minimizes community spread of the COVID-19 pandemic. Reducing false positives help people avoid mental trauma and wasteful expenses. This paper proposes a novel weighted consensus model to minimize the number of false negatives and false positives without compromising accuracy. In the proposed novel weighted consensus model, the accuracy of individual classification models is normalized. While predicting, different models predict different classes, and the sum of the normalized accuracy for a particular class is then considered based on a predefined threshold value. We used traditional Machine Learning classification algorithms like Linear Regression, Support Vector Machine, k -Nearest Neighbours, Decision Tree, and Random Forest for the weighted consensus experimental evaluation. We predicted the classes, which provided better insights into the condition. The proposed model can perform as well as the existing state-of-the-art technique in terms of accuracy (99.64%) and reduce false negatives and false positives.

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COVID-19: Challenges and Advisory

Cited by 6 publications

References 27 publications

Towards Privacy Paradigm Shift Due to the Pandemic: A Brief Perspective

Towards Privacy Paradigm Shift Due to the Pandemic: A Brief Perspective

COVID-19 Pandemic in Indonesia: Some Reflections from Bażl Al-Māʿūn by Ibn Ḥajr al-ʿAsqalānī

A Novel Weighted Consensus Machine Learning Model for COVID-19 Infection Classification Using CT Scan Images

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