A new automated national register-based surveillance system for outbreaks in long-term care facilities in Norway detected three times more severe acute respiratory coronavirus virus 2 (SARS-CoV-2) clusters than traditional methods

Integrated Management Systems (IMS) to Support and Sustain Quality One Health Services: International Lessons from the COVID-19 Pandemic by the IMIA Primary Care Working Group

OBJECTIVES

One Health considers human, animal and environment health as a continuum. The COVID-19 pandemic started with the leap of a virus from animals to humans. Integrated management systems (IMS) should provide a coherent management framework, to meet reporting requirements and support care delivery. We report IMS deployment during, and retention post the COVID-19 pandemic, and exemplar One Health use cases.

METHODS

Six volunteer members of the International Medical Association's (IMIA) Primary Care Working Group provided data about any IMS and One Health use to support the COVID-19 pandemic initiatives. We explored how IMS were: (1) Integrated with organisational strategy; (2) Utilised standardised processes, and (3) Met reporting requirements, including public health. Selected contributors provided Unified Modelling Language (UML) use case diagram for a One Health exemplar.

RESULTS

There was weak evidence of synergy between IMS and health system strategy to the COVID-19 pandemic. However, there were rapid pragmatic responses to COVID-19, not citing IMS. All health systems implemented IMS to link COVID test results, vaccine uptake and outcomes, particularly mortality and to provide patients access to test results and vaccination certification. Neither proportion of gross domestic product alone, nor vaccine uptake determined outcome. One Health exemplars demonstrated that animal, human and environmental specialists could collaborate.

CONCLUSIONS

IMS use improved the pandemic response. However, IMS use was pragmatic rather than utilising an international standard, with some of their benefits lost post-pandemic. Health systems should incorporate IMS that enables One Health approaches as part of their post COVID-19 pandemic preparedness.

Clusters of healthcare-associated SARS-CoV-2 infections in Norwegian hospitals detected by a fully automatic register-based surveillance system

BACKGROUND

Notifications to the Norwegian Institute of Public Health of outbreaks in Norwegian healthcare institutions are mandatory by law, but underreporting is suspected due to failure to identify clusters, or because of human or system-based factors. This study aimed to establish and describe a fully automatic, register-based surveillance system to identify clusters of healthcare-associated infections (HAIs) of SARS-CoV-2 in hospitals and compare these with outbreaks notified through the mandated outbreak system Vesuv.

METHODS

We used linked data from the emergency preparedness register Beredt C19, based on the Norwegian Patient Registry and the Norwegian Surveillance System for Communicable Diseases. We tested two different algorithms for HAI clusters, described their size and compared them to outbreaks notified through Vesuv.

RESULTS

5033 patients were registered with an indeterminate, probable, or definite HAI. Depending on the algorithm, our system detected 44 or 36 of the 56 officially notified outbreaks. Both algorithms detected more clusters then officially reported (301 and 206, respectively).

CONCLUSIONS

It was possible to use existing data sources to establish a fully automatic surveillance system identifying clusters of SARS-CoV-2 s. Automatic surveillance can improve preparedness through earlier identification of clusters of HAIs, and by lowering the workloads of infection control specialists in hospitals.