Digital public health: Automation based on new datasets and the Internet of Things

https://doi.org/10.1016/j.seps.2021.101039Get rights and content

Highlights

This paper presents a successfully applied development of new datasets.

This paper offers an innovative solution through interactive platforms to gather, process, and analyze big data.

The paper's contribution to the literature includes developing and applying a solution to implement the digital public health concept connected to creating and expanding datasets.

This paper supplies intellectual monitoring and “smart” digital public health management based on the IoT.

Abstract

This paper presents a successfully applied development of new datasets and offers an innovative solution through interactive platforms to gather, process, and analyze big data. The paper shows the capabilities, advantages, and perspectives of using datasets in digital public health amid virus threats, e.g., the COVID-19 pandemic. The paper's contribution to the literature includes developing and applying a solution to implement the digital public health concept connected to creating and expanding datasets. There is a general lack of studies examining the practical impact of technology and big data on “smart” digital public health management and its implications and effects; much is still to uncover in the literature. Instead, this paper supplies intellectual monitoring and “smart” digital public health management based on the Internet of Things (IoT). As artificial intelligence becomes accessible to all, our applied research drew on the dataset “COVID-19 and the 2020 economic crisis figure out healthcare system capabilities and ramifications for the economy and business all over the world.” It applies datasets for intellectual monitoring and “smart” digital public health management based on IoT and artificial intelligence, allowing its use in a wide range of scientific studies and real cases.

Keywords

Digital public health
Intellectual monitoring
“Smart” management
Internet of things
Artificial intelligence
Big data
Dataset

JEL classification

H51
I14
I15
I18
L15
O14
O31
O32
O33
O38
P46

Elena G. Popkova – Doctor of Science (Economics), the founder and president of the Institute of Scientific Communications (Russia) and Leading researcher of the Center for applied research of the chair “Economic policy and public-private partnership” of Moscow State Institute of International Relations (MGIMO) (Moscow, Russia). Her scientific interests include the theory of economic growth, sustainable development, globalization, humanization of economic growth, emerging markets, social entrepreneurship, and the digital economy and Industry 4.0. Elena G. Popkova organizes all-Russian and international scientific and practical conferences and is the editor and author of collective monographs, and serves as a guest editor of international scientific journals. She has published more than 300 works in Russian and foreign peer-reviewed scientific journals and books.

Bruno S. Sergi is an instructor at Harvard University with a particular interest focus on emerging markets' economics in Asia and Eastern Europe. At Harvard, he is a faculty affiliate at the Center for International Development and an Associate of the Davis Center for Russian and Eurasian Studies and the Harvard Ukrainian Research Institute. Sergi is the Series Editor of Cambridge Elements in the Economics of Emerging Markets (Cambridge University Press), the Editor of Entrepreneurship and Global Economic Growth (Emerald Publishing), and an Associate Editor of The American Economist. He also teaches Political Economy and International Finance at the University of Messina, Italy, and co-direct the Lab for Entrepreneurship and Development (LEAD), a research lab based in Cambridge, MA, that aims to generate and share knowledge about entrepreneurship development and sustainability. 1

1

The authors would like to acknowledge the editor Prof. Sang-Bing Tsai and two reviewers for their valuable time and specific comments, whose inputs have helped enhance the manuscript's current version, and Piper DeLo for her research assistance.

View full text