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Meta-Analysis
. 2020 Aug;81(2):266-275.
doi: 10.1016/j.jinf.2020.05.046. Epub 2020 May 27.

Co-infections in people with COVID-19: a systematic review and meta-analysis

Louise Lansbury  1 , Benjamin Lim  2 , Vadsala Baskaran  3 , Wei Shen Lim  4
Affiliations
Meta-Analysis

Co-infections in people with COVID-19: a systematic review and meta-analysis

Louise Lansbury et al. J Infect. 2020 Aug.

Abstract

Objectives: In previous influenza pandemics, bacterial co-infections have been a major cause of mortality. We aimed to evaluate the burden of co-infections in patients with COVID-19.

Methods: We systematically searched Embase, Medline, Cochrane Library, LILACS and CINAHL for eligible studies published from 1 January 2020 to 17 April 2020. We included patients of all ages, in all settings. The main outcome was the proportion of patients with a bacterial, fungal or viral co-infection. .

Results: Thirty studies including 3834 patients were included. Overall, 7% of hospitalised COVID-19 patients had a bacterial co-infection (95% CI 3-12%, n=2183, I2=92·2%). A higher proportion of ICU patients had bacterial co-infections than patients in mixed ward/ICU settings (14%, 95% CI 5-26, I2=74·7% versus 4%, 95% CI 1-9, I2= 91·7%). The commonest bacteria were Mycoplasma pneumonia, Pseudomonas aeruginosa and Haemophilus influenzae. The pooled proportion with a viral co-infection was 3% (95% CI 1-6, n=1014, I2=62·3%), with Respiratory Syncytial Virus and influenza A the commonest. Three studies reported fungal co-infections.

Conclusions: A low proportion of COVID-19 patients have a bacterial co-infection; less than in previous influenza pandemics. These findings do not support the routine use of antibiotics in the management of confirmed COVID-19 infection.

Keywords: COVID-19; Coinfection; Coronavirus; Meta-Analysis.

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Conflict of interest statement

Declaration of Competing Interest LL, BL and VB declare no competing interests. WSL's institution has received unrestricted investigated-initiated research funding from Pfizer for an unrelated pneumonia cohort study in which he is the Chief Investigator.

Figures

Figure 1
Figure 1
PRISMA flow diagram for study selection
Figure 2
Figure 2
Forest plot of proportion of COVID-19 patients with bacterial co-infections. Subgroup analysis for ICU versus mixed ward/ICU settings.
Figure 3
Figure 3
Forest plot of proportion of hospitalised COVID-19 patients with viral co-infections. Subgroup analysis for ICU versus mixed ward/ICU settings
Figure 4
Figure 4
Bacterial pathogens detected in COVID-19 patients, as a proportion (%) of the total number of detections (n=27) Key: M pneumoniae - Mycoplasma pneumoniae; P aeruginosa – Pseudomonas aeruginosa; H influenzae – Haemophilus influenzae; K pneumoniae – Klebsiella pneumoniae, A baumannii – Acinetobacter baumannii, S marcescens - Serratia marcescens, MRSA – Methicillin-resistant Staphylococcus aureus; E faecium – Enterococcus faecium.
Figure 5
Figure 5
Viral pathogens as a proportion (%) of the total number of viral detections (n=71). Key: RSV – Respiratory Syncytial Virus, hMPV – human Metapneumovirus, EBV – Epstein-Barr Virus, CMV - Cytomegalovirus.
See this image and copyright information in PMC

Comment in

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