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Automation in the practice of infection prevention and control: From automated surveillance of healthcare-associated infections to automated cluster detection and beyond

Thematic Series

Submission Status: Open | Submission Deadline: 30 April 2024

Edited by: 
Maaike van Mourik:
University Medical Center, Netherlands
Seven Aghdassi: Charité, Universitätsmedizin Berlin, Germany

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Description:

The aim of the thematic series is to collect works focusing on various aspects of automation in the field of surveillance of healthcare-associated infections (HAI) and infection prevention and control (IPC). The main focus of the edition will be placed on automated surveillance of HAI. However, a variety of other topics will be of interest to the journal as well. The following provides an orientation what will be considered in scope of the thematic series:

Automation of HAI surveillance

• Manuscripts may focus on any kind of HAI and may pertain to both institutional level (e.g. hospital) and beyond (e.g. national reference center)

• Manuscripts may focus of any degree of automation (e.g. fully automated versus semi-automated)

• Manuscripts on systems that are already implemented and routinely used or in an experimental phase will be preferred, merely conceptual descriptions will only be selected if they describe a vision that goes beyond implementation in individual hospitals

• Manuscripts delineating important prerequisites for automation or inventorising implementation of automated surveillance on a regional/national/international level will be considered

• Manuscripts focusing on validation of previously developed methods in new settings will be considered

• Manuscripts describing systems incorporating patient-reported measures are in scope (e.g. reporting through apps)


Automation of the detection of healthcare-associated clusters of microorganisms

• Manuscripts may pertain to both institutional level and beyond (e.g. national reference centre)

• Manuscripts may focus of any degree of automation (e.g. fully automated versus semi-automated)

• Manuscripts on systems that are already implemented and routinely used or in an experimental phase will be preferred, merely conceptual descriptions will only be selected if they describe a vision that goes beyond implementation in individual hospitals

• Manuscripts delineating important prerequisites for automation or inventorising implementation of automated cluster detection on a regional/national/international level will be considered

• Manuscripts focusing on validation of previously developed methods in new settings will be considered

Automation of other IPC activities 

• The use of intelligent software or machine learning methods in field of IPC, when the focus of the system is to replace human decision making or improve processes 

• The intersection of information technology and IPC: lessons learnt, pitfalls and future goals

Not in scope are manuscripts that present automated solutions (e.g. wearable devices) to monitor process measures (e.g. patient movement, hand hygiene).

Before submitting your manuscript, please ensure you have read the submission guidelines of Antimicrobial Resistance & Infection Control. Articles can be submitted via the online submission system.  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 Guest 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 Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests.


  1. In patients who underwent colorectal surgery, an existing semi-automated surveillance algorithm based on structured data achieves high sensitivity in detecting deep surgical site infections (SSI), however, gen...

    Authors: Janneke D.M. Verberk, Suzanne D. van der Werff, Rebecka Weegar, Aron Henriksson, Milan C. Richir, Christian Buchli, Maaike S.M. van Mourik and Pontus Nauclér
    Citation: Antimicrobial Resistance & Infection Control 2023 12:117
  2. Automated surveillance methods that re-use electronic health record data are considered an attractive alternative to traditional manual surveillance. However, surveillance algorithms need to be thoroughly vali...

    Authors: Suzanne D. van der Werff, Janneke D.M. Verberk, Christian Buchli, Maaike S.M. van Mourik and Pontus Nauclér
    Citation: Antimicrobial Resistance & Infection Control 2023 12:96
  3. Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep inc...

    Authors: Guosong Wu, Cheligeer Cheligeer, Danielle A. Southern, Elliot A. Martin, Yuan Xu, Jenine Leal, Jennifer Ellison, Kathryn Bush, Tyler Williamson, Hude Quan and Cathy A. Eastwood
    Citation: Antimicrobial Resistance & Infection Control 2023 12:88
  4. Intravascular catheter infections are associated with adverse clinical outcomes. However, a significant proportion of these infections are preventable. Evaluations of the performance of automated surveillance ...

    Authors: Jean-Marie Januel, Nasim Lotfinejad, Rebecca Grant, Sarah Tschudin-Sutter, Peter W. Schreiber, Bruno Grandbastien, Philipp Jent, Elia Lo Priore, Alexandra Scherrer, Stephan Harbarth, Gaud Catho and Niccolò Buetti
    Citation: Antimicrobial Resistance & Infection Control 2023 12:87
  5. Surveillance of surgical site infections (SSI) relies on access to data from various sources. Insights into the practices of German hospitals conducting SSI surveillance and their information technology (IT) i...

    Authors: Seven Johannes Sam Aghdassi, Hengameh Goodarzi, Alexander Gropmann, Jörg Clausmeyer, Christine Geffers, Brar Piening, Petra Gastmeier and Michael Behnke
    Citation: Antimicrobial Resistance & Infection Control 2023 12:49