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Books on the topic 'Pandemic Data'

Author: Grafiati
Published: 5 June 2025
Last updated: 24 June 2025

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1

Niranjanamurthy, M., Siddhartha Bhattacharyya, and Neeraj Kumar, eds. Intelligent Data Analysis for COVID-19 Pandemic. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1574-0.

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2

Hewage, Chaminda, Yogachandran Rahulamathavan, and Deepthi Ratnayake, eds. Data Protection in a Post-Pandemic Society. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-34006-2.

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3

Gamerman, Dani, Marcos O. Prates, Thaís Paiva, and Vinícius D. Mayrink. Building a Platform for Data-Driven Pandemic Prediction. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003148883.

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4

Dishman, Lihua, and Morgyne Brantley. Conducting a Doctoral Qualitative Study During a Pandemic: Pivoting to Online Data Collections and Data Analyses. SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529600513.

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5

Mishra, Sushruta, Pradeep Kumar Mallick, Hrudaya Kumar Tripathy, Gyoo-Soo Chae, and Bhabani Shankar Prasad Mishra, eds. Impact of AI and Data Science in Response to Coronavirus Pandemic. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2786-6.

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6

Strangfeld, Jennifer. Going Remote: When a Global Pandemic Intervenes in Gathering Interview Data. SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529602173.

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7

Shibuya, Kazuhiko. The Rise of Artificial Intelligence and Big Data in Pandemic Society. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0950-4.

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8

Okthariza, Noory. Pergerakan orang di Jakarta saat pandemic COVID-19: Analisis data facebook disease prevention map. CSIS Indonesia, 2020.

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9

Shiu-Yee, Karen, Alice Gaughan, Laura Rush, and Ann McAlearney. Online Qualitative Data Collection and Management: Primary Care Physicians’ Response to the COVID-19 Pandemic. SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529603545.

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10

Datoon, Rodmyr, Aileen Lapitan, Mark Llanco, Jeanarah Gapas, Susan Bacud, and Dania Laborte. Collecting Socioeconomic Agricultural Data Through Internet-Based Surveys and FGDs During the COVID-19 Pandemic. SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529603682.

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11

Cameranesi, Margherita, Kayla Kostal, Maria Baranowski, Lindsay McCombe, and Shahin Shooshtari. Doing Mixed-Methods Longitudinal Research During the COVID-19 Pandemic: Outlining Challenges and Fieldwork Adaptations Involving Remote Data Collection. SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529603699.

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12

Tamagawa, Masami. Challenges in Collecting Data to Investigate the Impact of the COVID-19 Pandemic on Members of the Japanese LGBTQ+ Community, Who Are Private and Diverse. SAGE Publications Ltd, 2025. https://doi.org/10.4135/9781036215880.

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13

Pae, Yŏng. P'osŭt'ŭ k'orona sidae, teit'ŏ ro ingnŭn Taehan Min'guk: Sutcha wa kŭrim esŏ ch'ajanaen mirae sam ŭi insait'ŭ. P'ŭllut'o, 2021.

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14

Ostrowska, Dorota, and Tamara L. Falicov. Shaping Film Festivals in a Changing World. Amsterdam University Press, 2025. https://doi.org/10.5117/9789463725576.

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This volume is a collective attempt on the part of a community of academics, film festival curators, and archivists to come to terms with practical and intellectual challenges of the pandemic and post-pandemic realities affecting cultures of film festivals. The collection draws contours of critical inquiry orienting current film festival research and practice to explore new directions in archiving and decolonizing practices and big data analysis in the post-Covid-19 context and beyond. The four-part study gathers the voices of academics and practitioners who engage in a dialogue to articulate critical areas for both study and practice of film festivals, and identifies conceptual tools to address them: “Archival Turn,” “Decolonizing Film Festival Studies,” “Post-Covid-19 and Film Festival Studies” and “Data Visualization and Film Festival Research and Practice.”
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15

Shumilina, Vera, Tat'yana Sidorina, Mikhail Onopchenko, et al. Problems of the labor market of the Russian Federation and its legal support in the context of economic recession and pandemic. AUS PUBLISHERS, 2021. http://dx.doi.org/10.26526/978-0-6487435-8-3.

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Today, in a modern market economy, one of the main factors of production is the labor market. The labor market and its mechanisms regulate the levels of employment of the population, supply and demand for labor, the level of wages, and the characteristics of the distribution of labor.
 To study the labor market, it is necessary to collect statistical data and analyze them. Labor market statistics are an important component of socio-economic statistics. It is closely related to other sections of socio-economic statistics, such as population statistics, statistics of economic sectors, the system of national accounts, etc. The conclusions drawn from the statistical study of the labor market characterize the state and development of the economy and are necessary for making informed economic and social decisions.
 The main branch of law that regulates relations in the labor market is labor law. It is one of the leading, complex and most important branches of law in the Russian Federation.
 In the conditions of economic recession and pandemic, new problems of the labor market of the Russian Federation and its legal support have emerged.
 This monograph, dedicated to modern problems of the labor market, is the result of the joint work of teachers and students of the Department of Economic Security, Accounting and Law of the Don State Technical University.
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16

Hu, Margaret. Pandemic Surveillance: Privacy, Security, and Data Ethics. Elgar Publishing Limited, Edward, 2022.

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17

Fishman, Neal. Viral Data in SOA: An Enterprise Pandemic. Pearson Education, Limited, 2021.

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18

Kumar, Neeraj, Siddhartha Bhattacharyya, and M. Niranjanamurthy. Intelligent Data Analysis for COVID-19 Pandemic. Springer, 2022.

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19

Fishman, Neal A. Viral Data in Soa: An Enterprise Pandemic. Pearson Education, Limited, 2009.

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20

Kumar, Neeraj, Siddhartha Bhattacharyya, and M. Niranjanamurthy. Intelligent Data Analysis for COVID-19 Pandemic. Springer Singapore Pte. Limited, 2021.

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21

Viral data in SOA: An enterprise pandemic. IBM Press/Pearson, 2009.

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22

Viral data in SOA: An enterprise pandemic. IBM Press/Pearson, 2010.

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23

Gamerman, Dani, Marcos O. Prates, Thais Paiva, and Vinicius D. Mayrink. Building a Platform for Data-Driven Pandemic Prediction. Taylor & Francis Group, 2021.

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24

Asimakopoulou, Eleana, and Nik Bessis. Data Science Advancements in Pandemic and Outbreak Management. IGI Global, 2021.

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25

Asimakopoulou, Eleana, and Nik Bessis. Data Science Advancements in Pandemic and Outbreak Management. IGI Global, 2021.

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26

Asimakopoulou, Eleana, and Nik Bessis. Data Science Advancements in Pandemic and Outbreak Management. IGI Global, 2021.

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27

Asimakopoulou, Eleana, and Nik Bessis. Data Science Advancements in Pandemic and Outbreak Management. Engineering Science Reference, 2021.

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28

Asimakopoulou, Eleana, and Nik Bessis. Data Science Advancements in Pandemic and Outbreak Management. IGI Global, 2021.

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29

Gamerman, Dani, Marcos O. Prates, Thais Paiva, and Vinicius D. Mayrink. Building a Platform for Data-Driven Pandemic Prediction. Taylor & Francis Group, 2021.

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30

e Sá Farinha, Carla Sofia, Paulo Jorge Nogueira, and Andreia Silva Costa, eds. Public Health Data Challenges of the COVID-19 Pandemic. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88976-845-5.

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31

Availability of statistical data to address the COVID-19 pandemic. FAO, 2020. http://dx.doi.org/10.4060/ca9915en.

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32

Spiegelhalter, David, and Masters Anthony. Covid by Numbers: Making Sense of the Pandemic with Data. Penguin Books, Limited, 2021.

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33

Spiegelhalter, David, and Masters Anthony. Covid by Numbers: Making Sense of the Pandemic with Data. Penguin Books, Limited, 2023.

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34

Ghani, Arfan. Innovations in Computer Vision and Data Classification: From Pandemic Data Analysis to Environmental and Health Monitoring. Springer, 2024.

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35

Gamerman, Dani, Marcos O. Prates, Thais Paiva, and Vinicius D. Mayrink. Building a Platform for Data-Driven Pandemic Prediction: From Data Modelling to Visualisation - the CovidLP Project. Taylor & Francis Group, 2021.

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36

Gamerman, Dani, Marcos O. Prates, Thais Paiva, and Vinicius D. Mayrink. Building a Platform for Data-Driven Pandemic Prediction: From Data Modelling to Visualisation - the CovidLP Project. Taylor & Francis Group, 2021.

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37

Building a Platform for Data-Driven Pandemic Prediction: From Data Modelling to Visualisation - the CovidLP Project. Taylor & Francis Group, 2021.

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38

Mishra, Bhabani Shankar Prasad, Pradeep Kumar Mallick, Gyoo-Soo Chae, Sushruta Mishra, and Hrudaya Kumar Tripathy. Impact of AI and Data Science in Response to Coronavirus Pandemic. Springer, 2022.

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39

Cerdeiro, Diego A., and Andras Komaromi. Supply Spillovers During the Pandemic: Evidence from High-Frequency Shipping Data. International Monetary Fund, 2020.

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40

MISHRA, Sushruta, Pradeep Kumar MALLICK, Hrudaya Kumar TRIPATHY, GYOO-SOO CHAE, and Bhabani Shankar Prasad MISHRA. Impact of AI and Data Science in Response to Coronavirus Pandemic. Springer Singapore Pte. Limited, 2021.

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41

Mahalle, Parikshit N., Gitanjali Rahul Shinde, Soumi Majumder, and Haribhau R. Bhapkar. Quality of Work-Life During Pandemic: Data Analysis and Mathematical Modeling. Springer Singapore Pte. Limited, 2022.

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42

Mahalle, Parikshit N., Gitanjali Rahul Shinde, Soumi Majumder, and Haribhau R. Bhapkar. Quality of Work-Life During Pandemic: Data Analysis and Mathematical Modeling. Springer, 2022.

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43

Cerdeiro, Diego A., and Andras Komaromi. Supply Spillovers During the Pandemic: Evidence from High-Frequency Shipping Data. International Monetary Fund, 2020.

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44

Cerdeiro, Diego A., and Andras Komaromi. Supply Spillovers During the Pandemic: Evidence from High-Frequency Shipping Data. International Monetary Fund, 2020.

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45

Harnessing the Potential of Big Data in Post-Pandemic Southeast Asia. Asian Development Bank, 2022.

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46

Johnson, Anthony. Small Business Pandemic: The Essentials of Data Science and Business-Analytics for Entrepreneurs in the Post-Pandemic Era. Independently Published, 2020.

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47

News, PM Medical Health. 2006 Great Influenza Pandemic Guide: Federal Pandemic Influenza Plan, H5N1 Bird Flu, Public Health Guidelines, Drugs, Vaccines, CDC Data. Progressive Management, 2005.

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48

Cabrol, Marcelo, Ricardo Baeza-Yates, Natalia González Alarcón, and Cristina Pombo. Is Data Privacy The Price We Must Pay to Survive a Pandemic? Inter-American Development Bank, 2020. http://dx.doi.org/10.18235/0002292.

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49

Data resources and analysis to understand the COVID-19 pandemic and its impacts. FAO, 2020. http://dx.doi.org/10.4060/ca9522en.

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50

National Academies of Sciences, Engineering, and Medicine. Genomic Epidemiology Data Infrastructure Needs for SARS-CoV-2: Modernizing Pandemic Response Strategies. National Academies Press, 2020.

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