posted by organizer: dPHE || 60 views || tracked by 1 users: [display]

DPH 2027 : 12th International Digital Public Health Conference 2027

FacebookTwitterLinkedInGoogle

Link: https://dphconf.org/
 
When Jun 15, 2027 - Jun 17, 2027
Where London, United Kingdom
Submission Deadline Nov 18, 2026
Notification Due Jan 28, 2027
Categories    artificial intelligence   public health   computer science   data science
 

Call For Papers

The International Digital Public Health Conference (DPH) is a leading annual interdisciplinary forum bringing together research, technology and innovation to address real-world public health challenges.

Since 2008, DPH has connected researchers, practitioners, innovators and stakeholders across Public Health, AI, Data Science, MedTech and beyond, creating opportunities to share emerging research, exchange ideas and build new collaborations. Following the success of DPH2026 in Barcelona, DPH2027 comes to London on 15-17 June 2027, continuing the conference’s tradition of connecting disciplines, ideas and people shaping the future of digital public health.

DPH is hosted by the UCL Centre for Digital Public Health in Emergencies (dPHE), a newly designated WHO Collaborating Centre for Digital Public Health and Pandemic Preparedness.

SUBMISSION GUIDELINES

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

- Fast Track – An optional early submission route for Early Career Researchers (ECRs) and researchers from low- or middle-income countries (LMICs) seeking an early pre-acceptance decision to support applications for travel grants, bursaries, studentships and other funding opportunities with deadlines before the standard DPH2027 notification date. Fast Track pre-acceptance is not final conference acceptance and does not replace the standard submission and peer-review process.

https://dphconf.org/calls-for-papers-and-prizes-2/fast-track-pre-acceptance-opportunity/

- Workshops, Tutorials, Panels Track – Invites proposals for interactive workshops, practical tutorials, and expert-led panels addressing focused topics, emerging methods, technologies, or timely issues in digital public health. Proposals should clearly describe the format, objectives, intended audience, and planned activities or speakers.

https://dphconf.org/calls-for-papers-and-prizes-2/call-for-workshops-tutorials-and-panels/

- Main Track – Accepts Full Papers (4-8 pages) and Extended Abstracts (up to 1000 words) presenting mature, original research and innovation in digital public health.

https://dphconf.org/calls-for-papers-and-prizes-2/call-for-main-track-papers-and-abstracts/

- PhD/MSc Student Track – A dedicated forum for postgraduate students to share ongoing research, including progress reports, as well as long or short research papers.

https://dphconf.org/calls-for-papers-and-prizes-2/call-for-phd-msc-student-abstracts/

- Posters & Demos Track – Designed for visual presentations of current projects, preliminary results, or innovative concepts, showcasing ongoing or planned work.

https://dphconf.org/calls-for-papers-and-prizes-2/call-for-posters-demos-2/

Authors are strongly encouraged to register early on the EasyChair submission system and begin preparing their submissions well in advance of the deadline.

IMPORTANT DATES & DEADLINES

- 30 September 2026: Fast Track Submission
- 07 October 2026: Workshop/ Tutorial/ Panel Submission
- 18 November 2026: Main Track Submission
- 09 December 2026: Posters & Demos Track Submission
- 09 December 2026: PhD/MSc Student Track Submission
- 31 March 2027: Early Bird Registration deadline
- 07 April 2027: Camera-Ready Deadline (All Tracks)
- 14 June 2027: Pre-Conference Student Day (Day 0)
- 15-17 June 2027: Main Conference

LIST OF TOPICS

The themes include but are not restricted to:

- Digital One Health
- Disease Surveillance, Early Warning and Pandemic Preparedness
- Artificial Intelligence in Public Health
- Digital Technology for Training and Behaviour Change
- Emerging Technology and Public Health
- Digital Systems and Public Health Data Governance
- Public Health Challenges

Click here for the full list of topics: https://dphconf.org/calls-for-papers-and-prizes-2/

PUBLICATION & ACCREDITATION

DPH2027 contributions are expected to be published through two separate publication routes, currently in negotiation. Accepted Full Papers that are presented at the conference will be submitted for possible inclusion in the IEEE Xplore DPH2027 Proceedings, while accepted Extended Abstracts presented at the conference will be included in the DPH2027 Abstract Book, published in Frontiers in Digital Public Health.

DPH is also APHEA-accredited as a Continuing Training and Educational Event (CTEE), providing 15 CPD points for Public Health professionals. Publication arrangements and inclusion in the respective proceedings are subject to confirmation of the relevant agreements for DPH2027.

CONTACT

All questions about submissions should be emailed to support@dphconf.org.

Related Resources

Ei/Scopus-AI2A 2026   2026 IEEE 6th International Conference on Artificial Intelligence, Automation and Algorithms (AI2A 2026)
Public Health 2026   9th International Symposium on Public Health
Ei/Scopus-ACEPE 2026   2026 3rd IEEE Asia Conference on Advances in Electrical and Power Engineering (ACEPE 2026)
GLOBAL HEALTH 2026   The Fifteenth International Conference on Global Health Challenges
IEEE-MLNLP 2026   2026 IEEE 9th International Conference on Machine Learning and Natural Language Processing (MLNLP 2026)
Cyberfare State and Digital Governance 2026   Cyberfare State and Digital Governance: Security, Control and Resilience in the Digital Age
AMLDS 2027   IEEE--2027 3rd International Conference on Advanced Machine Learning and Data Science
ACM ICIMH 2026   ACM--2026 The 7th International Conference on Intelligent Medicine and Health (ICIMH 2026)
ICMHI 2027   2027 11th International Conference on Medical and Health Informatics (ICMHI 2027)
AAIML 2027   IEEE--2027 2nd International Conference on Advances in Artificial Intelligence and Machine Learning