A modeling study on the impact of COVID-19 pandemic responses on the community transmission of antibiotic-resistant bacteria - Cnam - Conservatoire national des arts et métiers Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2022

A modeling study on the impact of COVID-19 pandemic responses on the community transmission of antibiotic-resistant bacteria

Résumé

Abstract Non-pharmaceutical COVID-19 interventions have dramatically modified the transmission dynamics of pathogens other than SARS-CoV-2. In many countries, reports have shown that implementation of population-wide lockdowns led to substantial reductions in invasive bacterial disease caused by respiratory bacteria such as Streptococcus pneumoniae . By contrast, most European countries reported increased antibiotic resistance among S. pneumoniae isolates from 2019 to 2020. To disentangle impacts of the COVID-19 pandemic responses on bacterial epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae . The impacts of population-wide lockdowns, isolation of COVID-19 cases, changes in antibiotic consumption due to altered healthcare-seeking behavior and prophylactic use in the early pandemic were explored across six pandemic scenarios. Our model was able to reproduce the observed trends, showing how lockdowns substantially reduce invasive pneumococcal disease incidence, while surges in prophylactic antibiotic prescribing favor disease caused by resistant strains. Surges in COVID-19 cases were associated with increased antibiotic resistance rates across all pandemic scenarios. Introducing synergistic within-host SARS-CoV-2-pneumococcus interactions further exacerbates increasing incidence of resistant disease. When data availability is limited, mathematical modeling can help improve our understanding of the complex interactions between COVID-19 and antibiotic resistance.
Fichier principal
Vignette du fichier
2022.08.08.503267v3.full.pdf (3.37 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Licence : CC BY - Paternité

Dates et versions

hal-04252911 , version 1 (24-10-2023)

Licence

Paternité

Identifiants

Citer

Aleksandra Kovacevic, David Smith, Eve Rahbé, Sophie Novelli, Paul Henriot, et al.. A modeling study on the impact of COVID-19 pandemic responses on the community transmission of antibiotic-resistant bacteria. 2023. ⟨hal-04252911⟩
81 Consultations
9 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More