Abstract
Background: Despite specific vaccination campaigns, many outbreaks of seasonal influenza like ilness (ILI) in long term care (LTC) facilities are occasionally reported. We explored the dynamics of influenza starting from real data collected from a nursing home located in Italy and a mathematical model. Our aim was to identify the best vaccination strategy to minimize cases among the guests. Materials and
Methods: The model consists of a classical SEIR part describing the spreading of the influenza in the general population and a stochastic agent based model that formalizes the dynamics of the disease inside the institution. After a model fit of a baseline scenario, we explored the impact of varying the HCW and guests parameters (vaccine uptake and vaccine efficacy) on the guest attack rates (AR) of the nursing home.
Results: The aggregate AR of ILI in the nursing home was 36.4% (ward1 = 56%, ward2 = 33.3%, ward3 = 31.7%, ward4 = 34.5%). The model fit to data returned a probability of infection of the causal contact of 0.3 and of the shift change contact of 0.2. We noticed no decreasing or increasing AR trend when varying the HCW vaccine uptake and efficacy parameters, whereas the increase in both guest vaccine efficacy and uptake parameter was accompanied by a slight decrease in AR of all the wards of the LTC facility. Conclusions: We can conclude that a nursing home is still an environment at high risk of influenza transmission but the handover situation carry no higher relative risk. Therefore, additional preventive measures in this circumstance may be unnecessary. Finally, in a closed environment such as a LTC facility, the vaccination of guests, rather than HCWs, may still represent the cornerstone of an effective preventive strategy.
Lingua originale | Inglese |
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Pagine | 112-112 |
Numero di pagine | 1 |
DOI | |
Stato di pubblicazione | Pubblicato - 2023 |
Evento | 17th World Congress on Public Health - Rome, Italy Durata: 1 gen 2023 → … |
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???event.eventtypes.event.conference??? | 17th World Congress on Public Health |
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Città | Rome, Italy |
Periodo | 1/01/23 → … |