How the COVID-19 pandemic altered antibiotic prescribing for common bacterial infections

In a study posted to the medRxiv* preprint server, investigators evaluated the impact of the coronavirus disease 2019 (COVID-19) pandemic on the use of antibiotics in primary care for common infections. 

Study: Evaluation of the impact of COVID-19 pandemic on hospital admission related to common infections. Image Credit: nokwalai/Shutterstock.com

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Background

Antimicrobial resistance (AMR), a significant challenge worldwide, is managed via antimicrobial stewardship interventions. Although antibiotics are prescribed to combat infections, they could contribute to AMR if prescribed excessively or inappropriately. 

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic altered prescribing antibiotics for common bacterial infections. As a result of the SARS-CoV-2 pandemic, antibiotic prescribing dropped between the final months of 2019 and 2021 relative to prior years, primarily because of decreased social contact and infection spread.

This emphasizes the necessity to investigate the likelihood of hospital admissions associated with common infections other than SARS-CoV-2 infections during the COVID-19 pandemic. 

Limited studies have examined the probability of hospital admissions linked to common infections and antibiotic use across the COVID-19 pandemic. According to a previous study, the prescribing of antibiotics in the community plummeted during the SARS-CoV-2 pandemic in northwest London.

While the available studies on this topic are enlightening, it is important to comprehend how the pandemic may affect outcomes following typical infections. 

About the study

In the present study, the researchers assessed the impact of the SARS-CoV-2 pandemic on antibiotic-based primary care therapy for common infections in England. They aimed to design and validate risk prediction models for infection-linked consequences.

In addition, the work used Cox proportional hazards regression models to calculate the likelihood of hospital admission due to common infections. The team developed and validated risk prediction models for infection-associated complications employing pre-pandemic information.

Another goal of the research was to analyze the efficacy of antibiotics in preventing infection-associated hospitalizations and determine common antibiotic types that could reduce the chance of infection-linked hospitalization.

The current cohort study used information from January 2019 to August 2020 from the OpenSAFELY platform, which securely pseudonymizes, stores, links, and evaluates electronic health records (EHR) for the National Health Service (NHS) during the SARS-CoV-2 pandemic.

The study population included patients with common infections such as sinusitis, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), otitis media, lower urinary tract infection (UTI), and otitis externa.

The research employed various predictor variables that may be associated with the likelihood of hospital admission for common infections.

These variables include sex, ethnicity, age, smoking status, socioeconomic class, region in England, body mass index (BMI), comorbidities, flu vaccination in the prior year, season of infection diagnosis, and history of antibiotic use.

Results

The study found a drop in patients diagnosed with common infections and given antibiotic prescriptions during the COVID-19 pandemic relative to the pre-pandemic phase. Antibiotics were more efficient in preventing hospitalizations associated with infections such as LRTI and UTI than URTI.  

The authors discovered that the most frequently prescribed antibiotics for UTI, LRTI, and URTI were linked to a lower likelihood of infection-associated hospital admission. Further, the second-most commonly prescribed antibiotic types for UTI and LRTI were linked to a lower probability of infection-linked hospital admission, whereas this was not the case for URTI. 

The researchers developed and validated risk prediction models for infection-associated complications, demonstrating good discrimination and calibration.

Individuals who were male, older, had a history of antibiotics administration, and had comorbid conditions were more likely to be hospitalized due to common infections.

Moreover, subjects diagnosed with infections throughout the winter season and those who did not receive a flu vaccination the year before had a higher chance of hospital admission linked to common infections. 

Conclusions

According to the current cohort study, the primary care management of common infections in England was significantly impacted by the SARS-CoV-2 pandemic. The pandemic indirectly affected antibiotic therapy for common diseases, especially infections like LRTI.

Age, past antibiotic usage, and comorbidities were discovered to be the primary predictors of hospital admission associated with common infections in risk models. In contrast to URTI, prescribed antibiotics were linked to a decreased risk of complications for UTI and LRTI.

The study emphasizes the necessity for general practitioners and patients to be given tailored risks on the prognosis of a common infection to enhance risk-based antibiotic prescribing in primary care.

The study’s findings have significant implications for managing common infections in primary care during and after the SARS-CoV-2 pandemic.

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.