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Call for papers - Digitalization in infectious disease control measures

Guest Editors

Fardad Haghpanah, PhD, One Health Trust, USA
Gary Lin, PhD, Johns Hopkins University Applied Physics Laboratory, USA

Submission Status: Open   |   Submission Deadline: 28 February 2025

BMC Microbiology welcomes submissions to the collection, Digitalization in infectious disease control measures. This collection aims to explore the innovative use of digital technologies in infectious disease surveillance, control, and diagnosis to strengthen disease control strategies. We invite researchers to submit articles with a clear focus on infectious diseases, addressing topics such as infectious disease digital surveillance, the integration of big data and digital platforms, computational modeling, AI and ML applications, digital diagnostic tools, real-time monitoring, cloud computing or digital technologies for One Health, among others.

New Content ItemThis Collection supports and amplifies research related to SDG 3: Good Health & Well-Being.

Meet the Guest Editors

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Fardad Haghpanah, PhD, One Health Trust, USA

Dr Haghpanah is a computational modeler with expertise in computational epidemiology, systems engineering, and community resilience. He applies complex systems principles to address healthcare challenges. Currently, through the CDC's Modeling Infectious Diseases in Healthcare Network (MInD – Healthcare) program, his research focuses on the transmission of healthcare-associated infections in hospitals. Additionally, Dr Haghpanah has contributed to COVID-19 and influenza research with the Scenario Modeling Hub. He has developed models for various public health issues, including increasing smoking cessation rates, improving dental care access for the working poor, and informing diabetes control policies.

Gary Lin, PhD, Johns Hopkins University Applied Physics Laboratory, USA

Dr Lin is a senior computational epidemiologist at the Johns Hopkins University Applied Physics Laboratory. His research focuses on utilizing modeling and computational simulation to understand complex systems, particularly in infectious disease surveillance, community resilience, and public health response. Other research contribution includes biomedical research innovation, international development, environmental sustainability, and healthcare decision support. He was previously a Postdoctoral Research Fellow at an international non-profit called One Health Trust (formerly Center for Disease Dynamics, Economics & Policy), and Johns Hopkins University School of Medicine. Dr Lin earned his PhD in Civil and Systems Engineering at the Johns Hopkins University and holds a M.S.E. in Geography and Environmental Engineering. 

About the Collection

Outbreaks of infectious diseases are unpredictable and can have major detrimental impacts and long-lasting effects on human society and public health. The digitalization and digital surveillance systems applied to develop infectious disease control measures have emerged as a transformative approach in public health, potentially capable to improve the way we monitor, diagnose, control and communicate about infectious diseases. From digital epidemiology and real-time monitoring to the use of computational modeling and machine learning for predicting disease spread and prevention strategies, the integration of technology and laboratory research represents a powerful tool to understand the epidemiology of infectious diseases.

Emerging technological developments in laboratory and epidemiologic methods, combined with the use of big data, increasing computational power and applications of machine learning/artificial intelligence can significantly improve how we study and control the spreading of infectious diseases and zoonoses. In support of the UN Sustainable Development Goal 3 (SDG 3), ‘Good health and well-being’, BMC Microbiology  welcomes submissions to the collection, Digitalization in infectious disease control measures. The collection aims to explore the innovative use of digital technologies in infectious disease surveillance and control, as well as diagnosis. Research must focus on infectious diseases and be in scope for the journal. Manuscripts focusing exclusively on digital technologies and tools, as well as on digital communication, will not be considered. We invite researchers to submit research articles that cover, but are not limited to, the following topics:

  • Infectious disease digital surveillance to prevent and control outbreaks
  • Development and use of digital data and technology for epidemiological research and infectious disease tracking
  • Big data and digital platforms for infectious disease surveillance and modeling
  • Computational modeling to study the complex behavior of infectious diseases
  • Machine learning and artificial intelligence applications/tools for predicting and preventing the spreading of infectious diseases
  • Development and applications of digital tools for the diagnosing of infectious diseases
  • Advances in real-time monitoring of infectious diseases for early detection and response
  • Development and use of cloud computing for infectious disease surveillance and control, including data security and federated data governance
  • Digital technologies applied to One Health approach
  • Potential barriers and solutions for the adaptation of digital technologies applied to infectious disease surveillance and control by decision-makers
  • Applications of digital twin technology towards infectious diseases
  • Incorporating socio-behavioral mechanisms to study transmission and disease risks

Image credit: © [M] denisismagilov /

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Digitalization in infectious disease control measures" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.