Background: Patient transfers between hospital departments and wards frequently occur and bring with them the risk of inter-department transmission of antibiotic-resistant bacteria (ARB). These bacteria form a risk to the patients already susceptible to colonisation and infection. Aim: Goal of this study is to assess the impact of the SARS-CoV-2 pandemic on the intra-hospital network of a German and an Italian hospital. Methods: Using data collected from the hospital between 2019 and 2023 we developed a model to represent an intra-hospital transfer network with all patient movements among all the wards, by creating a time-sliced temporal network for each month. We described the network and assessed its robustness against ARB spread by simulating outbreaks among wards. Findings: Over the years studied, in the German hospital we found that in April 2020, when many elective surgeries were cancelled due to the SARS-CoV-2 pandemic, the robustness of the network strongly increased in comparison to all other months. Despite the network being relatively stable over the study period, it was affected by an internal change of hospital structure due to a hospital merging event. In the Italian hospital the robustness in April 2020 was stable but was lower in October 2020. This network analysis shows that network robustness tends to increase with higher levels of modularity, while it decreases as the number of transfers and links grows. Conclusion: The intra-hospital transfer network in the German Hospital was affected by external influences due to the pandemic, slowing down the potential spread of the nosocomial pathogens; the network was generally stable and quickly recovered, although an internal force affected the structure of the network. The simulation conducted among the Italian network helped underline that network’s structure influences robustness independently from number of transfers. This study advances our understanding of how antimicrobial resistance can spread through hospital networks, highlighting the importance of both structural and operational variables. A better understanding of the influence of patient transfers will help to design intervention strategies against the spread of antimicrobial resistance within hospitals.
Introduzione: I trasferimenti di pazienti tra reparti e unità ospedaliere sono eventi frequenti, ma comportano un rischio significativo di trasmissione inter-reparto di batteri resistenti agli antibiotici (ARB). Tali batteri rappresentano una minaccia per i pazienti già suscettibili alla colonizzazione e all’infezione. Obiettivi: Lo scopo del presente studio è valutare l’impatto della pandemia da SARS-CoV-2 sulla rete intraospedaliera di un grande ospedale universitario tedesco e di un ospedale italiano. Materiali e metodi: Utilizzando i dati raccolti tra il 2019 e il 2023, è stato sviluppato un modello per rappresentare la rete di trasferimenti intraospedalieri, includendo tutti gli spostamenti dei pazienti tra le unità operative. È stata costruita una rete temporale suddivisa per mese e analizzata in termini di struttura; si è poi analizzata la sua robustezza rispetto alla diffusione di ARB, simulando focolai tra i reparti. Risultati: Nel corso del periodo analizzato, nell’ospedale tedesco si è osservato che nel mese di aprile 2020, quando molti interventi chirurgici elettivi furono cancellati a causa della pandemia, la robustezza della rete aumentò significativamente rispetto a tutti gli altri mesi. Sebbene la rete si sia mantenuta relativamente stabile nel tempo, essa ha subito un’alterazione strutturale dovuta a un processo di fusione ospedaliera. Nell’ospedale italiano, la robustezza della rete ad aprile 2020 si è mantenuta stabile, mentre è risultata inferiore nel mese di ottobre 2020. Questa analisi della rete mostra che la robustezza tende ad aumentare al crescere della modularità della rete e a diminuire con l’aumento del numero di trasferimenti e di collegamenti. Conclusioni: La rete intraospedaliera dell’ospedale tedesco è stata influenzata da fattori esterni legati alla pandemia, che hanno temporaneamente rallentato la potenziale diffusione di patogeni nosocomiali; la rete ha comunque mostrato un’elevata stabilità e un rapido ritorno alla configurazione originaria, nonostante un cambiamento interno ne abbia modificato la struttura. La simulazione effettuata sulla rete dell’ospedale italiano ha evidenziato che la struttura della rete influenza la robustezza in modo indipendente rispetto al solo numero di trasferimenti. Il presente studio contribuisce a migliorare la comprensione delle dinamiche di diffusione della resistenza antimicrobica all’interno delle reti ospedaliere, mettendo in luce l’importanza delle variabili sia strutturali sia operative. Una comprensione più approfondita dell’impatto dei trasferimenti di pazienti potrà supportare la progettazione di strategie di intervento più efficaci contro la diffusione della resistenza antimicrobica in ambito ospedaliero.
Donvito, G (2026). A network analysis of the impact of the SARS-CoV-2 pandemic on hospital robustness to antibiotic-resistant bacteria. (Tesi di dottorato, , 2026).
A network analysis of the impact of the SARS-CoV-2 pandemic on hospital robustness to antibiotic-resistant bacteria
DONVITO, GIOVANNA
2026
Abstract
Background: Patient transfers between hospital departments and wards frequently occur and bring with them the risk of inter-department transmission of antibiotic-resistant bacteria (ARB). These bacteria form a risk to the patients already susceptible to colonisation and infection. Aim: Goal of this study is to assess the impact of the SARS-CoV-2 pandemic on the intra-hospital network of a German and an Italian hospital. Methods: Using data collected from the hospital between 2019 and 2023 we developed a model to represent an intra-hospital transfer network with all patient movements among all the wards, by creating a time-sliced temporal network for each month. We described the network and assessed its robustness against ARB spread by simulating outbreaks among wards. Findings: Over the years studied, in the German hospital we found that in April 2020, when many elective surgeries were cancelled due to the SARS-CoV-2 pandemic, the robustness of the network strongly increased in comparison to all other months. Despite the network being relatively stable over the study period, it was affected by an internal change of hospital structure due to a hospital merging event. In the Italian hospital the robustness in April 2020 was stable but was lower in October 2020. This network analysis shows that network robustness tends to increase with higher levels of modularity, while it decreases as the number of transfers and links grows. Conclusion: The intra-hospital transfer network in the German Hospital was affected by external influences due to the pandemic, slowing down the potential spread of the nosocomial pathogens; the network was generally stable and quickly recovered, although an internal force affected the structure of the network. The simulation conducted among the Italian network helped underline that network’s structure influences robustness independently from number of transfers. This study advances our understanding of how antimicrobial resistance can spread through hospital networks, highlighting the importance of both structural and operational variables. A better understanding of the influence of patient transfers will help to design intervention strategies against the spread of antimicrobial resistance within hospitals.| File | Dimensione | Formato | |
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phd_unimib_896554.pdf
accesso aperto
Descrizione: A network analysis of the impact of the SARS-CoV-2 pandemic on hospital robustness to antibiotic-resistant bacteria
Tipologia di allegato:
Doctoral thesis
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6.6 MB
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Adobe PDF
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