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

View ORCID ProfileAleksandra Kovacevic, David R M Smith, Eve Rahbé, View ORCID ProfileSophie Novelli, Paul Henriot, Laura Temime, Lulla Opatowski
doi: https://doi.org/10.1101/2022.08.08.503267
Aleksandra Kovacevic
1Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE), Paris, France
2Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, Inserm U1018, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France
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  • For correspondence: aleksandra.kovacevic@pasteur.fr
David R M Smith
1Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE), Paris, France
2Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, Inserm U1018, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France
3Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire national des arts et métiers, Paris, France
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Eve Rahbé
1Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE), Paris, France
2Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, Inserm U1018, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France
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Sophie Novelli
2Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, Inserm U1018, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France
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Paul Henriot
3Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire national des arts et métiers, Paris, France
4PACRI unit, Institut Pasteur, Conservatoire national des arts et métiers, Paris, France
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Laura Temime
3Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire national des arts et métiers, Paris, France
4PACRI unit, Institut Pasteur, Conservatoire national des arts et métiers, Paris, France
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Lulla Opatowski
1Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE), Paris, France
2Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, Inserm U1018, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France
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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.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Data included in the analyses (Figure 1).

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 23, 2023.
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A modeling study on the impact of COVID-19 pandemic responses on the community transmission of antibiotic-resistant bacteria
Aleksandra Kovacevic, David R M Smith, Eve Rahbé, Sophie Novelli, Paul Henriot, Laura Temime, Lulla Opatowski
bioRxiv 2022.08.08.503267; doi: https://doi.org/10.1101/2022.08.08.503267
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A modeling study on the impact of COVID-19 pandemic responses on the community transmission of antibiotic-resistant bacteria
Aleksandra Kovacevic, David R M Smith, Eve Rahbé, Sophie Novelli, Paul Henriot, Laura Temime, Lulla Opatowski
bioRxiv 2022.08.08.503267; doi: https://doi.org/10.1101/2022.08.08.503267

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