Management of zoonoses in research institutions – lessons learned from a <i>Coxiella burnetii</i> outbreak case

When biomedical research investigates the human surgical situation in the need of a chronic course, it is more often possible to do so using large animal models. The use of farm animals always poses special challenges for the institution conducting the research in terms of infection prevention and occupational safety. Especially for the zoonotic disease coxiellosis it is important to be aware of the constant risk of pathogen introduction by small ruminants and to take appropriate precautions. In this way, personal injury should be avoided or at least be kept to a minimum in the event of infection since then sustainable zoonosis control can be immediately initiated. Using the example of a Q fever outbreak at a research facility, we want to share with this extended case report the importance of central emergency structures, provisions and the inclusion of relevant experts and disciplines in a crisis team. Its primary purpose is to support the affected facility and coordinate the implementation of necessary cleaning, disinfection and decontamination measures in close contact with the responsible local authorities. The aim is to inactivate the pathogen in a systematic and controlled manner in few steps of action only and to keep the interruption of the facility's operations as short as possible.

Authors

Institutions

Publication Details

Journal
Laboratory Animals
Published
2024-11-19
DOI
https://doi.org/10.1177/00236772241271028
Citations
1
Primary Topic
Vector-borne infectious diseases
Type
article
Field-Weighted Citation Impact
0.52
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Management of zoonoses in research institutions – lessons learned from a Coxiella burnetii outbreak case

Anne Keil, André Dülsner, Stefan Nagel-Riedasch, Pia KS Ostach
1 citations
Laboratory Animals
Vector-borne infectious diseases
0.52
article

Management of zoonoses in research institutions – lessons learned from a Coxiella burnetii outbreak case

Anne Keil, André Dülsner, Stefan Nagel-Riedasch, Pia KS Ostach
article en
1 citations

Abstract

When biomedical research investigates the human surgical situation in the need of a chronic course, it is more often possible to do so using large animal models. The use of farm animals always poses special challenges for the institution conducting the research in terms of infection prevention and occupational safety. Especially for the zoonotic disease coxiellosis it is important to be aware of the constant risk of pathogen introduction by small ruminants and to take appropriate precautions. In this way, personal injury should be avoided or at least be kept to a minimum in the event of infection since then sustainable zoonosis control can be immediately initiated. Using the example of a Q fever outbreak at a research facility, we want to share with this extended case report the importance of central emergency structures, provisions and the inclusion of relevant experts and disciplines in a crisis team. Its primary purpose is to support the affected facility and coordinate the implementation of necessary cleaning, disinfection and decontamination measures in close contact with the responsible local authorities. The aim is to inactivate the pathogen in a systematic and controlled manner in few steps of action only and to keep the interruption of the facility's operations as short as possible.

Laboratory AnimalsVol. 59(1)
Charité - Universitätsmedizin Berlin (DE)
Openalex Percentile: Top 32%
Vector-borne infectious diseases
0.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.