Difference between revisions of "Journal:Strengthening public health surveillance through blockchain technology"

From LIMSWiki
Jump to navigationJump to search
m (→‎Notes: Cats)
 
(One intermediate revision by the same user not shown)
Line 83: Line 83:
This technology has a potential to give real-time data/information by sensing potential outbreaks or bioterrorism. Hence, if vaccinations, antibiotics, and other disease control measures are instituted promptly, massive casualties can be prevented. For example, fake news on social media against vaccination have critically impacted public health in recent years.<ref name="JervelundHowSoc18">{{cite journal |title=How social media is transforming the spreading of knowledge: Implications for our perceptions concerning vaccinations and migrant health |journal=Scandanavian Journal of Public Health |author=Jervelund, S.S. |volume=46 |issue=2 |pages=167-169 |year=2018 |doi=10.1177/1403494818760139}}</ref> Huckle and White reported a blockchain-based approach to identify the origins of such harmful content and identify the population at risk in digital communication.<ref name="HuckleFake17">{{cite journal |title=Fake News: A Technological Approach to Proving the Origins of Content, Using Blockchains |journal=Big Data |author=Huckle, S.; White, M. |volume=5 |issue=4 |pages=356–71 |year=2017 |doi=10.1089/big.2017.0071}}</ref> This highlights the potential of blockchain to improve public health surveillance in the era of digitalization.
This technology has a potential to give real-time data/information by sensing potential outbreaks or bioterrorism. Hence, if vaccinations, antibiotics, and other disease control measures are instituted promptly, massive casualties can be prevented. For example, fake news on social media against vaccination have critically impacted public health in recent years.<ref name="JervelundHowSoc18">{{cite journal |title=How social media is transforming the spreading of knowledge: Implications for our perceptions concerning vaccinations and migrant health |journal=Scandanavian Journal of Public Health |author=Jervelund, S.S. |volume=46 |issue=2 |pages=167-169 |year=2018 |doi=10.1177/1403494818760139}}</ref> Huckle and White reported a blockchain-based approach to identify the origins of such harmful content and identify the population at risk in digital communication.<ref name="HuckleFake17">{{cite journal |title=Fake News: A Technological Approach to Proving the Origins of Content, Using Blockchains |journal=Big Data |author=Huckle, S.; White, M. |volume=5 |issue=4 |pages=356–71 |year=2017 |doi=10.1089/big.2017.0071}}</ref> This highlights the potential of blockchain to improve public health surveillance in the era of digitalization.


Today manyt countries use machine learning techniques in surveillance. However, there are certain unique and added advantages of blockchain technology over machine learning techniques. For example, blockchain predominantly blocks malicious activities, like data hacking and duplication.<ref name="RahoutiBitcoin18">{{cite journal |title=Bitcoin Concepts, Threats, and Machine-Learning Security Solutions |journal=IEEE Access |author=Rahouti, M.; Xiong, K.; Ghani, N. |volume=6 |pages=67189-67205 |year=2018 |doi=10.1109/ACCESS.2018.2874539}}</ref> Additionally, the combination of blockchain technology with [[artificial intelligence]] (AI) is the proverbial "cherry on top" for the medical research and health sectors.<ref name="MamoshinaConverg17">{{cite journal |title=Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare |journal=Oncotarget |author=Mamoshina, P.; Ojomoko, L.; Yanovich, Y. et al. |volume=9 |issue=5 |pages=5665-5690 |year=2017 |doi=10.18632/oncotarget.22345 |pmid=29464026 |pmc=PMC5814166}}</ref>
Today many countries use machine learning techniques in surveillance. However, there are certain unique and added advantages of blockchain technology over machine learning techniques. For example, blockchain predominantly blocks malicious activities, like data hacking and duplication.<ref name="RahoutiBitcoin18">{{cite journal |title=Bitcoin Concepts, Threats, and Machine-Learning Security Solutions |journal=IEEE Access |author=Rahouti, M.; Xiong, K.; Ghani, N. |volume=6 |pages=67189-67205 |year=2018 |doi=10.1109/ACCESS.2018.2874539}}</ref> Additionally, the combination of blockchain technology with [[artificial intelligence]] (AI) is the proverbial "cherry on top" for the medical research and health sectors.<ref name="MamoshinaConverg17">{{cite journal |title=Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare |journal=Oncotarget |author=Mamoshina, P.; Ojomoko, L.; Yanovich, Y. et al. |volume=9 |issue=5 |pages=5665-5690 |year=2017 |doi=10.18632/oncotarget.22345 |pmid=29464026 |pmc=PMC5814166}}</ref>


There is also tremendous scope for integration with [[geographical information system]]s (GIS) to expedite routine epidemic investigations, as well as drug and vaccine supply chain management. The other critical aspect is that by ensuring transparency and correct reporting, as in the case of reporting deaths from an outbreak, blockchain overcomes the existing limitations of local health information systems. The following illustration (Figure 3) shows how the application of blockchain in surveillance systems enhances activities for ensuring health security.
There is also tremendous scope for integration with [[geographic information system]]s (GIS) to expedite routine epidemic investigations, as well as drug and vaccine supply chain management. The other critical aspect is that by ensuring transparency and correct reporting, as in the case of reporting deaths from an outbreak, blockchain overcomes the existing limitations of local health information systems. The following illustration (Figure 3) shows how the application of blockchain in surveillance systems enhances activities for ensuring health security.





Latest revision as of 17:36, 12 May 2020

Full article title Strengthening public health surveillance through blockchain technology
Journal AIMS Public Health
Author(s) Bhattacharya, Sudip; Singh, Amarjeet; Hossain, Md Mahbub
Author affiliation(s) Himalayan Institute of Medical Sciences, Postgraduate Institute of Medical Education and Research,
Texas A & M University
Primary contact Email: docbilu at gmail dot com
Year published 2019
Volume and issue 6(3)
Page(s) 326-333
DOI 10.3934/publichealth.2019.3.326
ISSN 2327-8994
Distribution license Creative Commons Attribution 4.0 International
Website http://www.aimspress.com/article/10.3934/publichealth.2019.3.326
Download http://www.aimspress.com/article/10.3934/publichealth.2019.3.326/pdf (PDF)

Abstract

Blockchain technology is a decentralized system of recording data and performing transactions which is increasingly being used across many industries, including healthcare. It has several unique features like the validation of transaction processes, prevention of systems failure from any single point of transaction, and approval of data sharing with optimal security, to name a few. At the hospital level, blockchain technologies are used in electronic medical records systems, insurance claims systems, billing management processes, and so on. Moreover, this technology is helpful to manage logistic and human resources to achieve the quality of care in learning health systems. In many countries, blockchain is being used to promote patient-centered care by sharing patient data for remote monitoring and management. Furthermore, blockchain technology has the potential to strengthen disease surveillance systems in cases of disease outbreaks resulting in local and global health emergencies. In such conditions, blockchain can be used to identify health security concerns, analyze preventive measures, and facilitate decision-making processes to act rapidly and effectively. Despite its limitations, research, and practice based on blockchain technology have shown promises to strengthen health systems around the world, with a potential to reduce the global burden of diseases, mortality, morbidity, and economic costs.

Keywords: blockchain technology, telemedicine, medical informatics, disease outbreaks, population surveillance

Introduction

In the twenty-first century, many scientific innovations have changed the means of day-to-day communication, transactions, and decision-making. Blockchain is such a technology, which is being considered as one of the most significant inventions since the development of the internet.[1] It is also popularly termed as the next generation of “internet of things.”[2] The rise of Bitcoin and other cryptocurrencies have certainly helped blockchain to gain the spotlight across the globe. However, experts believe that blockchain is more than cryptocurrencies and that it may offer greater benefits to the users of complex systems.[1][3] Blockchain technology is commonly used for online money transfers and bank payments. It is also used in automobile manufacturing, cybersecurity, exit poll development, educational endevors, insurance systems, and time trend forecasting.[4] Recently, blockchain technology has gained popularity several other domains, including health systems. This is because it offers a safer and decentralized database that can operate independently from a centralized administrator.[3] According to Angraal et al., a unique selling point of the blockchain system is that once digital validation takes place, the network itself streamlines and validates the subsequent process of transaction. It safeguards the transaction history and allows data to be transferred directly between third parties.[5]

In this article, we discuss how blockchain technology works and how it can be used in complex situations like strengthening public health surveillance.

Blockchain and its applications

A blockchain is defined as “a distributed system (decentralized) which performs the dual function of recording and storing the records of the transaction. In this blockchain, the data is located in a network of personal computers called ‘nodes’ without any central control.” (Figure 1). The main advantage of this decentralized technology is that all the dealings or variations in the data are captured with real-time updates across the network.[6] The information that gets stored in each node is similar and permanent. It can't be distorted. Hence, this technology is transparent and autonomous, and as such it improves the quality of shared data between different stakeholders.[7] In this system, to validate the transaction, cryptographic algorithms are used.[8] This is different from a “trust-in-the-third-party” mechanism, where an online transaction takes place when two willing parties approve the transaction by use of a digital signature.[2] Moreover, blockchain overcomes the challenge of “single point failure,” which is common in centralized information management systems.[9] Currently, however, the average centralized healthcare system lacks the advantages offered by blockchain, including transparency and trust, data security and privacy, cost-effectiveness, and verifiability of data, as well as fast and real-time data transfer to all trusted parties.[10]


Fig1 Bhattacharya AIMSPubHlth2019 6-3.png

Figure 1. Centralized (a) and decentralized network (b)

Types and uses of blockchain

There are two main types of blockchains:

1. Open-access blockchains, which makes all records visible to the stakeholders; and

2. Limited-access blockchains, which restricts the access of data/information.[11]

Open-access blockchains are more appropriate to the health sector. Presently, cryptocurrency such as Bitcoin (some of the most popular applications of blockchain technology) depends on this type of technology.[12]

Blockchain technology in healthcare

Blockchain has commonly been used in four primary ways in healthcare: in electronic medical record (EMR) implementations at the hospital level, for resource management in health systems, for patient-level applications, and for disease surveillance at the community level.

1. Hospitals and EMRs: Blockchain is one of the popular technologies used in EMRs found in modern hospital ecosystems in industrialized nations. Blockchain's ability to improve decentralization, data provenance, and robustness has made it suitable for storing, managing, and sharing protected health information in EMRs.[13] For example, an electronic health chain (or interoperable health blockchain) could be based on a blockchain-based EMR system which uses IBM's Hyperledger Fabric modular blockchain framework.[14] This technology helps to achieve scalable data security and optimize the performance of the EMR system. Arguably, blockchain may also be considered for improving transactions in billing and managing insurance claims, as well as surveillance measures like nosocomial infection surveillance.[14] The advantage of this technology is that a lot of data can rapidly be stored, processed, and shared with stakeholders without any link failure/delay.[15] According to Peterson et al., it can also reform health database interoperability with built-in authentication controls, which lowers the risk of data theft.[12]

2. Resource management in health systems: Blockchain can facilitate managing logistics and human resources in healthcare systems. For example, counterfeit medications and instruments below standard can be supplied to healthcare systems from external vendors. Use of blockchain can validate the quality standards at different nodes of the supply chain and inform the respective authorities about suspected discrepancies.[16] Moreover, human resource management in the digital age requires storing and using employee data for attendance, vacation scheduling, performance appraisal, and security measures with complex authentication processes. Use of blockchain can make such processes efficient and contribute to the development of smarter health services organizations.

3. Patient-level applications: Due to its decentralized features protecting data safety concerns, blockchain is increasingly being used to share health data with patients and their caregivers. Such patient empowerment initiatives are also fostering meaningful use of health information technology and improving patient-provider communication across digital platforms.[17] Furthermore, blockchain-based mHealth interventions are enabling remote patient monitoring through use of biosensors, thus bridging the access gaps in patient-level health services.[18]

4. Community disease surveillance: Surveillance is defined as the “systematic, ongoing collection, collation, and analysis of data and the timely dissemination of information to those who need to know so that the action can be taken.”[19] It is done for both communicable diseases and non-communicable diseases by all national health systems according to their national priorities as per WHO's International Health Regulations (IHR). For example, deadly viruses like Nipah can travel across the globe within 36 hours and may lead to a pandemic, further compromised by rapid and uncontrolled urbanization and globalization.[20] Communicable disease surveillance is an ongoing, complex, and inefficient process, because a huge number of self-regulating organizations report to a centralized information system. As such, it remains a challenging task to maintain seamless information flow in a timely manner.[21][22] Moreover, sufficient incentive is rarely provided to routine staff.

The sequence of events that occur after a healthcare worker reports a potential case is depicted in Figure 2.


Fig2 Bhattacharya AIMSPubHlth2019 6-3.png

Figure 2. Sequence of events in disease surveillance system

Blockchain could help independent organizations to manage data more efficiently during pandemics.[23] It could also help track information for ongoing public health emergencies, like road traffic accidents, illicit drug use, opioid misuse, and so on.[24] When blockchain technology is used in a public health domain, these networks might be able to automate secure data sharing and storage at different levels of healthcare organizations.

This technology has a potential to give real-time data/information by sensing potential outbreaks or bioterrorism. Hence, if vaccinations, antibiotics, and other disease control measures are instituted promptly, massive casualties can be prevented. For example, fake news on social media against vaccination have critically impacted public health in recent years.[25] Huckle and White reported a blockchain-based approach to identify the origins of such harmful content and identify the population at risk in digital communication.[26] This highlights the potential of blockchain to improve public health surveillance in the era of digitalization.

Today many countries use machine learning techniques in surveillance. However, there are certain unique and added advantages of blockchain technology over machine learning techniques. For example, blockchain predominantly blocks malicious activities, like data hacking and duplication.[27] Additionally, the combination of blockchain technology with artificial intelligence (AI) is the proverbial "cherry on top" for the medical research and health sectors.[28]

There is also tremendous scope for integration with geographic information systems (GIS) to expedite routine epidemic investigations, as well as drug and vaccine supply chain management. The other critical aspect is that by ensuring transparency and correct reporting, as in the case of reporting deaths from an outbreak, blockchain overcomes the existing limitations of local health information systems. The following illustration (Figure 3) shows how the application of blockchain in surveillance systems enhances activities for ensuring health security.


Fig3 Bhattacharya AIMSPubHlth2019 6-3.png

Figure 3. Application of block chain in surveillance system

As shown in Figure 3, the disease control actions of prevention, detection, and response, aided by blockchain, have their scope broadened for real-time surveillance and detection of non-communicable diseases (NCD). This also lends to the goals of the Global Health Security Agenda (GHSA) and its Action Package working groups.[29]

By applying real-time surveillance, defining and tracking the early risk factors for NCDs can be improved. Additionally, by building up the capacity of medical units, the challenges of emergency response can be overcome through effective supply chain systems.[30] A summary of other NCD real-time surveillance activities within the framework of the GHSA are shown in Table 1.

Table 1. Real time surveillance for NCDs within the Global Health Security Agenda
GHSA category GHSA action package NCD-related activity
Detect Real-time surveillance

1. Strengthen cancer registries
2. Support tobacco use surveillance
3. Birth defects surveillance due to zika virus
4. Include NCD indicators in current surveillance systems
5. Support inclusion of electronic medical records
6. Implement for health data

Limitations

Blockchain technology has several limitations which include use of the technology without adequate security and privacy measures, lack of frameworks for implementation and regulation, and concerns for cost-effectiveness and interoperability.[31] These challenges can be overcome by gradual improvements in scalability and upgradeability.

Discussions and conclusions

The case of Taiwan is an excellent example of the application of this revolutionary blockchain technology.[32] In Estonia, the complete public health infrastructure is being operated using blockchain.[33] Other examples include countries such as the United Kingdom, United States, and Canada, where such real-time surveillance systems have been implemented in many of their departments. In England, at the national level, they have implemented it in their Emergency Department Syndromic Surveillance System (EDSSS). Emergency department syndromic surveillance has also been implemented by Canada at the regional level. Another excellent example of this application is the European Antimicrobial Resistance Surveillance Network.[23][34] Hence, we may conclude that blockchain applications can retain the prime characteristics of ideal disease surveillance. It can be more effective and rapid than traditional surveillance in terms of coverage, durability, consensus, selective privacy, uniqueness, and timing. Blockchain technology holds great promise in overpopulated and low-income countries like India, Pakistan, and Africa (where the health systems are prone to epidemic and pandemic) by strengthening the capacity of the countries with simplified early warning surveillance for diseases of epidemic potential by reducing the mortality, morbidity, and economic costs. It is high time to incorporate blockchain technology within the existing surveillance systems of at least low-income countries in order to strengthen their health systems.

Acknowledgements

We acknowledge all the present and previous authors (working in the field of blockchain technology, especially Dr Vijay Kumar Chattu), contributors and sources, who helped us directly or indirectly for preparing this manuscript. All the authors had contributed equally during preparation of this manuscript (concept, design, literature review, and editing).

Conflict of interest

All authors declare no conflicts of interest in this paper.

References

  1. 1.0 1.1 Chen, G.; Xu, B.; Lu, M. et al. (2018). "Exploring blockchain technology and its potential applications for education". Smart Learning Environments 5: 1. doi:10.1186/s40561-017-0050-x. 
  2. 2.0 2.1 Alam, T. (2019). "IoT-Fog: A Communication Framework using Blockchain in the Internet of Things". International Journal of Recent Technology and Engineering 7 (6): 833-838. http://www.ijrte.org/download/volume-7-issue-6/. 
  3. 3.0 3.1 Meinert, E.; Alturkistani, A.; Foley, K.A. et al. (2019). "Blockchain Implementation in Health Care: Protocol for a Systematic Review". JMIR Research Protocols 8 (2): e10994. doi:10.2196/10994. PMC PMC6384534. PMID 30735146. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6384534. 
  4. Campbell-Verduyn, M. (2017). Bitcoin and Beyond: Cryptocurrencies, Blockchains, and Global Governance. Routledge. pp. 221. ISBN 9780415792141. 
  5. Angraal, S.; Krumholz, H.M.; Schulz, W.L. et al. (2017). "Blockchain Technology: Applications in Health Care". Circulation: Cardiovascular Quality and Outcomes 10 (9): e003800. doi:10.1161/CIRCOUTCOMES.117.003800. PMID 28912202. 
  6. Rathee, G.; Sharma, A.; Kumar, R. et al. (2019). "A Secure Communicating Things Network Framework for Industrial IoT using Blockchain Technology". Ad Hoc Networks 94: 101933. doi:10.1016/j.adhoc.2019.101933. 
  7. Crosby, M.; Nachiappan; Pattenayak, P. et al. (2016). "BlockChain Technology: Beyond Bitcoin" (PDF). Applied Innovation Review (2): 6–19. http://scet.berkeley.edu/wp-content/uploads/AIR-2016-Blockchain.pdf. 
  8. Sharma, A.; Kumar, R. (2019). "Service-Level Agreement—Energy Cooperative Quickest Ambulance Routing for Critical Healthcare Services". Arabian Journal for Science and Engineering 44: 3831–3848. doi:10.1007/s13369-018-3687-z. 
  9. Li, I.-C.; Liao, T.-C. (2017). "A Survey of Blockchain Security Issues and Challenges". International Journal of Network Security 19 (5): 653–659. doi:10.6633/IJNS.201709.19(5).01. 
  10. Vazirani, A.A.; O'Donoghue, O.; Brindley, D. et al. (2019). "Implementing Blockchains for Efficient Health Care: Systematic Review". Journal of Medical Internet Research 21 (2): e12439. doi:10.2196/12439. PMC PMC6390185. PMID 30747714. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6390185. 
  11. Beck, R.; Avital, M.; Rossi, M. et al. (2017). "Blockchain Technology in Business and Information Systems Research". Business & Information Systems Engineering 59: 381–84. doi:10.1007/s12599-017-0505-1. 
  12. 12.0 12.1 Peterson, K. (September 2016). "A Blockchain-Based Approach to Health Information Exchange Networks". Use of Blockchain in Healthcare and Research Workshop. https://oncprojectracking.healthit.gov/wiki/display/TechLabI/Use+of+Blockchain+in+Healthcare+and+Research+Workshop. 
  13. Sharma, A.; Kumar, R. (2017). "An optimal routing scheme for critical healthcare HTH services — An IOT perspective". Proceedings from the Fourth International Conference on Image Information Processing: 1–5. doi:10.1109/ICIIP.2017.8313784. 
  14. 14.0 14.1 Roman-Belmonte, J.M.; De la Corte-Rodriguez, H.; Rodriguez-Merchan, E.C. (2018). "How blockchain technology can change medicine". Postgraduate Medicine 130 (4): 420-427. doi:10.1080/00325481.2018.1472996. PMID 29727247. 
  15. Ekblaw, A.; Azaria, A.; Halamka, J.D. et al. (August 2016). "A Case Study for Blockchain in Healthcare: “MedRec” prototype for electronic health records and medical research data". 2nd International Conference on Open & Big Data 2016. pp. 1–13. https://dci.mit.edu/research/blockchain-medical-records. 
  16. Tseng, J.H.; Liao, Y.C.; Chong, B. et al. (2018). "Governance on the Drug Supply Chain via Gcoin Blockchain". International Journal of Environmental Research and Public Health 15 (6): E1055. doi:10.3390/ijerph15061055. PMC PMC6025275. PMID 29882861. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6025275. 
  17. Engelhardt, M.A. (2017). "Hitching Healthcare to the Chain: An Introduction to Blockchain Technology in the Healthcare Sector". Technology Innovation Management Review 7 (10): 22–34. doi:10.22215/timreview/1111. 
  18. Saravanan, M.; Shubha, R.; Marks, A.M. et al. (2017). "SMEAD: A secured mobile enabled assisting device for diabetics monitoring". Proceedings of the 2017 IEEE International Conference on Advanced Networks and Telecommunications Systems: 1–6. doi:10.1109/ANTS.2017.8384099. 
  19. Last, J.M., ed. (2001). "A Dictionary of Epidemiology". Oxford University Press. ISBN 9780195141696. https://books.google.com/books?id=RPaQY8cG4N4C. 
  20. Fan, V.Y.; Jamison, D.T.; Summers, L.H. (2018). "Pandemic risk: how large are the expected losses?". Bulletin of the World Health Organization 96 (2): 129–34. doi:10.2471/BLT.17.199588. 
  21. Islam, N.; Faheem, Y.; Din, I.U. et al. (2019). "A blockchain-based fog computing framework for activity recognition as an application to e-Healthcare services". Future Generation Computer Systems 100: 569–78. doi:10.1016/j.future.2019.05.059. 
  22. Khan, S.U.; Islam, N.; Jan, Z. et al. (2019). "An e-Health care services framework for the detection and classification of breast cancer in breast cytology images as an IoMT application". Future Generation Computer Systems 98: 286–96. doi:10.1016/j.future.2019.01.033. 
  23. 23.0 23.1 Chattu, V.K.; Nanda, A.; Chattu, S.K. et al. (2019). "The Emerging Role of Blockchain Technology Applications in Routine Disease Surveillance Systems to Strengthen Global Health Security". Big Data and Cognitive Computing 3 (2): 25. doi:10.3390/bdcc3020025. 
  24. Katuwal, G.J.; Pandey, S.; Hennessey, M. et al. (2018). "Applications of Blockchain in Healthcare: Current Landscape & Challenges". arXiv: 1–17. https://arxiv.org/abs/1812.02776. 
  25. Jervelund, S.S. (2018). "How social media is transforming the spreading of knowledge: Implications for our perceptions concerning vaccinations and migrant health". Scandanavian Journal of Public Health 46 (2): 167-169. doi:10.1177/1403494818760139. 
  26. Huckle, S.; White, M. (2017). "Fake News: A Technological Approach to Proving the Origins of Content, Using Blockchains". Big Data 5 (4): 356–71. doi:10.1089/big.2017.0071. 
  27. Rahouti, M.; Xiong, K.; Ghani, N. (2018). "Bitcoin Concepts, Threats, and Machine-Learning Security Solutions". IEEE Access 6: 67189-67205. doi:10.1109/ACCESS.2018.2874539. 
  28. Mamoshina, P.; Ojomoko, L.; Yanovich, Y. et al. (2017). "Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare". Oncotarget 9 (5): 5665-5690. doi:10.18632/oncotarget.22345. PMC PMC5814166. PMID 29464026. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5814166. 
  29. Global Health Security Agenda (2019). "About the GHSA". https://ghsagenda.org/home/about-the-ghsa/. 
  30. Kostova, D.; Husain, M.J.; Sugerman, D. et al. (2017). "Synergies between Communicable and Noncommunicable Disease Programs to Enhance Global Health Security". Emerging Infectious Diseases 23 (13): S40–S46. doi:10.3201/eid2313.170581. PMC PMC5711304. PMID 29155655. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711304. 
  31. Boulos, M.N.K.; Wilson, J.T.; Clauson, K.A. (2018). "Geospatial blockchain: Promises, challenges, and scenarios in health and healthcare". International Journal of Health Geographics 17: 25. doi:10.1186/s12942-018-0144-x. 
  32. Jian, S.W.; Chen, C.M.; Lee, C.Y. et al. (2017). "Real-Time Surveillance of Infectious Diseases: Taiwan's Experience". Health Security 15 (2): 144–53. doi:10.1089/hs.2016.0107. PMC 28418738. PMID PMC5404256. https://www.ncbi.nlm.nih.gov/pmc/articles/28418738. 
  33. Mettler, M. (2016). "Blockchain technology in healthcare: The revolution starts here". Proceedings of the 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services: 1–3. doi:10.1109/HealthCom.2016.7749510. 
  34. Abat, C.; Chaudet, H.; Colson, P. et al. (2015). "Real-Time Microbiology Laboratory Surveillance System to Detect Abnormal Events and Emerging Infections, Marseille, France". Emergency Infectious Diseases 21 (8): 1302-10. doi:10.3201/eid2108.141419. PMC 26196165. PMID PMC4517727. https://www.ncbi.nlm.nih.gov/pmc/articles/26196165. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. A reference was added for the GHSA in this version.