An investigation of Infection Prevention and Control professionals’ experiences during the COVID-19 pandemic: A global perspective
Bibliographic record
Abstract
BACKGROUND: Infection prevention and control (IPC) professionals played a vital role during COVID-19, yet their experiences remain largely unexplored. Understanding these experiences is crucial for strengthening health system preparedness for future outbreaks/pandemic. This study investigates IPC professionals' preparedness, response capacity, knowledge base, and barriers/enablers during COVID-19 to inform future pandemic planning. METHODS: A cross-sectional online survey was conducted in 2024 among IPC professionals worldwide through WHO's Global Outbreak Alert and Response Network partners and professional IPC organisations. The survey was translated into five languages, comprising 30 questions that covered demographics, professional preparedness, response capacity, and pandemic experiences. Quantitative data were analysed descriptively using SPSS, while qualitative responses underwent thematic analysis. RESULTS: Eighty-six responses from 19 countries were analysed, with participants mainly from Australia (48.8 %), Canada (17.4 %), and the United Kingdom (8.1 %). Most worked in government hospitals (54.7 %) with dedicated IPC roles (57.0 %) and over five years of experience (73.2 %). Four interconnected themes emerged: establishing IPC as vital expertise, confronting the psychological toll of IPC work, navigating shifting guidance and policy, and managing resource scarcity and workforce strain. Participants reported a lack of recognition as "front-line" staff, significant psychological burdens including post-traumatic stress, challenges with rapidly changing guidance undermining staff trust, and overwhelming workloads without additional resources. CONCLUSIONS: IPC professionals showed remarkable dedication despite facing structural neglect and emotional difficulties. Findings highlight the urgent need to formalise IPC leadership roles within health systems, ensure proper recognition and resources, and incorporate psychosocial support measures to enhance pandemic preparedness and response capacity worldwide.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".