Seasonality and community interventions in a mathematical model of Clostridium difficile transmission

A McLure; L Furuya-Kanamori; A C A Clements; M Kirk; K Glass

doi:10.1016/j.jhin.2019.03.001

Seasonality and community interventions in a mathematical model of Clostridium difficile transmission

J Hosp Infect. 2019 Jun;102(2):157-164. doi: 10.1016/j.jhin.2019.03.001. Epub 2019 Mar 15.

Authors

A McLure¹, L Furuya-Kanamori², A C A Clements³, M Kirk⁴, K Glass⁴

Affiliations

¹ Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia. Electronic address: angus.mclure@anu.edu.au.
² Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia; Department of Population Medicine, College of Medicine, Qatar University, Doha, Qatar.
³ Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia.
⁴ Research School of Population Health, Australian National University, Canberra, Australian Capital Territory, Australia.

PMID: 30880267
DOI: 10.1016/j.jhin.2019.03.001

Abstract

Background: Clostridium difficile infection (CDI) is the leading cause of antibiotic-associated diarrhoea with peak incidence in late winter or early autumn. Although CDI is commonly associated with hospitals, community transmission is important.

Aim: To explore potential drivers of CDI seasonality and the effect of community-based interventions to reduce transmission.

Methods: A mechanistic compartmental model of C. difficile transmission in a hospital and surrounding community was used to determine the effect of reducing transmission or antibiotic prescriptions in these settings. The model was extended to allow for seasonal antibiotic prescriptions and seasonal transmission.

Findings: Modelling antibiotic seasonality reproduced the seasonality of CDI, including approximate magnitude (13.9-15.1% above annual mean) and timing of peaks (0.7-1.0 months after peak antibiotics). Halving seasonal excess prescriptions reduced the incidence of CDI by 6-18%. Seasonal transmission produced larger seasonal peaks in the prevalence of community colonization (14.8-22.1% above mean) than seasonal antibiotic prescriptions (0.2-1.7% above mean). Reducing transmission from symptomatic or hospitalized patients had little effect on community-acquired CDI, but reducing transmission in the community by ≥7% or transmission from infants by ≥30% eliminated the pathogen. Reducing antibiotic prescription rates led to approximately proportional reductions in infections, but limited reductions in the prevalence of colonization.

Conclusion: Seasonal variation in antibiotic prescription rates can account for the observed magnitude and timing of C. difficile seasonality. Even complete prevention of transmission from hospitalized patients or symptomatic patients cannot eliminate the pathogen, but interventions to reduce transmission from community residents or infants could have a large impact on both hospital- and community-acquired infections.

Keywords: Clostridium difficile; Community-acquired infections; Hospital-acquired infections; Mathematical model; Seasonal infections.

MeSH terms

Adult
Aged
Anti-Bacterial Agents / therapeutic use*
Clostridium Infections / prevention & control*
Clostridium Infections / transmission*
Disease Transmission, Infectious / prevention & control*
Drug Utilization*
Humans
Infant
Infection Control / methods*
Models, Theoretical*
Prescriptions / statistics & numerical data
Prevalence
Seasons

Substances

Anti-Bacterial Agents