Hospital vulnerability to spread of respiratory infections: close contact data collection and mathematical modelling
Abstract The transmission risk of SARS-CoV-2 within hospitals can exceed that in the general community because of more frequent close proximity interactions. However, epidemic risk across wards is still poorly described. We measured CPIs directly using wearable sensors given to all those present in a clinical ward over a 36-hour period, across 15 wards in three hospitals in spring 2020. Data were collected from 2114 participants. These data were combined with a simple transmission model describing the arrival of a single index case to the ward to estimate the risk of an outbreak. Estimated epidemic risk ranged four-fold, from 0.12 secondary infections per day in an adult emergency to 0.49 per day in general paediatrics. The risk presented by an index case in a patient varied twenty-fold across wards. Using simulation, we assessed the potential impact on outbreak risk of targeting the most connected individuals for prevention. We found that targeting those with the highest cumulative contact hours was most impactful (20% reduction for 5% of the population targeted), and on average resources were better spent targeting patients. This study reveals patterns of interactions between individuals in hospital during a pandemic and opens new routes for research into airborne nosocomial risk..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
ResearchSquare.com - (2024) vom: 19. Feb. Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Shirreff, George [VerfasserIn] |
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| doi: |
10.21203/rs.3.rs-2884334/v1 |
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XRA039881784 |
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| 520 | |a Abstract The transmission risk of SARS-CoV-2 within hospitals can exceed that in the general community because of more frequent close proximity interactions. However, epidemic risk across wards is still poorly described. We measured CPIs directly using wearable sensors given to all those present in a clinical ward over a 36-hour period, across 15 wards in three hospitals in spring 2020. Data were collected from 2114 participants. These data were combined with a simple transmission model describing the arrival of a single index case to the ward to estimate the risk of an outbreak. Estimated epidemic risk ranged four-fold, from 0.12 secondary infections per day in an adult emergency to 0.49 per day in general paediatrics. The risk presented by an index case in a patient varied twenty-fold across wards. Using simulation, we assessed the potential impact on outbreak risk of targeting the most connected individuals for prevention. We found that targeting those with the highest cumulative contact hours was most impactful (20% reduction for 5% of the population targeted), and on average resources were better spent targeting patients. This study reveals patterns of interactions between individuals in hospital during a pandemic and opens new routes for research into airborne nosocomial risk. | ||
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