Evaluation of the impact of COVID-19 pandemic on hospital admission related to common infections: Risk prediction models to tackle antimicrobial resistance in primary care

PLoS One. 2024 Dec 31;19(12):e0311515. doi: 10.1371/journal.pone.0311515. eCollection 2024.

Abstract

Background: Antimicrobial resistance (AMR) is a multifaceted global challenge, partly driven by inappropriate antibiotic prescribing. The objectives of this study were to evaluate the impact of the COVID-19 pandemic on treatment of common infections, develop risk prediction models and examine the effects of antibiotics on infection-related hospital admissions.

Methods: With the approval of NHS England, we accessed electronic health records from The Phoenix Partnership (TPP) through OpenSAFELY platform. We included adult patients with primary care diagnosis of common infections, including lower respiratory tract infection (LRTI), upper respiratory tract infections (URTI), and lower urinary tract infection (UTI), from 1 January 2019 to 31 August 2022. We excluded patients with a COVID-19 record in the 90 days before to 30 days after the infection diagnosis. Risk prediction models using Cox proportional-hazard regression were developed for infection-related hospital admission in the 30 days after the common infection diagnosis.

Results: We found 12,745,165 infection diagnoses from 1 January 2019 to 31 August 2022. Of them, 80,395 (2.05%) cases were admitted to the hospital during follow-up. Counts of hospital admission for infections dropped during COVID-19, for example LRTI from 3,950 in December 2019 to 520 in April 2020. Comparing those prescribed an antibiotic to those without, reduction in risk of hospital admission were largest with LRTI (adjusted hazard ratio (aHR) of 0.35; 95% confidence interval (CI), 0.35-0.36) and UTI (aHR 0.45; 95% CI, 0.44-0.46), compared to URTI (aHR 1.04; 95% CI, 1.03-1.06).

Conclusions: A substantial variation in hospital admission risks between infections and patient groups was found. Antibiotics appeared more effective in preventing infection-related complications with LRTI and UTI, but not URTI. While this study has several limitations, the results indicate that a focus on risk-based antibiotic prescribing could help tackle AMR in primary care.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Anti-Bacterial Agents* / therapeutic use
  • COVID-19* / epidemiology
  • England / epidemiology
  • Female
  • Hospitalization*
  • Humans
  • Male
  • Middle Aged
  • Pandemics
  • Primary Health Care*
  • Proportional Hazards Models
  • Respiratory Tract Infections / drug therapy
  • Respiratory Tract Infections / epidemiology
  • SARS-CoV-2 / isolation & purification
  • Urinary Tract Infections / drug therapy
  • Urinary Tract Infections / epidemiology

Substances

  • Anti-Bacterial Agents

Grants and funding

This work was supported by Health Data Research UK (Better prescribing in frail elderly people with polypharmacy: learning from practice and nudging prescribers into better practice -BetterRx) and by National Institute for Health and Care Research (NIHR130581 - Cluster randomised trial to improve antibiotic prescribing in primary care: individualised knowledge support during consultation for general practitioners and patients – BRIT2). DMA is funded by the NIHR Greater Manchester Patient Safety Translational Research Centre (PSTRC-2016-003). The views expressed are those of the authors and not necessarily those of Health Data Research UK, the NHS, the NIHR, the Department of Health and Social Care or Public Health England. AF is funded by the National Institute for Health and Care Research (DSE Award; NIHR303781). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.