The Emerging Role of Blockchain Technology Applications in Routine Disease Surveillance Systems to Strengthen Global Health Security
Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
Big Data and Cognitive Computing
Abstract
Blockchain technology has an enormous scope to revamp the healthcare system in many
ways as it improves the quality of healthcare by data sharing among all the participants, selective
privacy and ensuring data safety. This paper explores the basics of blockchain, its applications,
quality of experience and advantages in disease surveillance over the other widely used real-time
and machine learning techniques. The other real-time surveillance systems lack scalability, security,
interoperability, thus making blockchain as a choice for surveillance. Blockchain o ers the capability
of enhancing global health security and also can ensure the anonymity of patient data thereby aiding
in healthcare research. The recent epidemics of re-emerging infections such as Ebola and Zika have
raised many concerns regarding health security which resulted in strengthening the surveillance
systems. We also discuss how blockchains can help in identifying the threats early and reporting
them to health authorities for taking early preventive measures. Since the Global Health Security
Agenda addresses global public health threats (both infectious and NCDs); strengthen the workforce
and the systems; detect and respond rapidly and e ectively to the disease threats; and elevate global
health security as a priority. The blockchain has enormous potential to disrupt many current practices
in traditional disease surveillance and health care research
Description
Table of Contents
Keywords
Blockchain, Disease surveillance, Infectious diseases, Global health security, Epidemics, Public health, Health care, Quality of Experience
Citation
Chattu, V.K.; Nanda, A.; Chattu, S.K.; Kadri, S.M.; Knight, A.W. The Emerging Role of Blockchain Technology Applications in Routine Disease Surveillance Systems to Strengthen Global Health Security. Big Data Cogn. Comput. 2019, 3, 25. https://doi.org/10.3390/bdcc3020025