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. 2022 Mar 31;59(3):2101209. doi: 10.1183/13993003.01209-2021

Asthma and COVID-19 risk: a systematic review and meta-analysis

Anthony P Sunjaya 1,2, Sabine M Allida 1,2, Gian Luca Di Tanna 1,2, Christine R Jenkins 1,2,3,✉
PMCID: PMC8361304  PMID: 34385278

Abstract

Background

Individual case series and cohort studies have reported conflicting results in people with asthma on the vulnerability to and risk of mortality from coronavirus disease 2019 (COVID-19).

Research question

Are people with asthma at a higher risk of being infected or hospitalised or poorer clinical outcomes from COVID-19?

Methods

A systematic review and meta-analysis based on five main databases including the World Health Organization COVID-19 database between 1 December 2019 and 11 July 2021 on studies with a control (non-asthma) group was conducted. Prevalence and risk ratios were pooled using Sidik–Jonkman random-effects meta-analyses.

Findings

51 studies with an 8.08% (95% CI 6.87–9.30%) pooled prevalence of people with asthma among COVID-19 positive cases. The risk ratios were 0.83 (95% CI 0.73–0.95, p=0.01) for acquiring COVID-19; 1.18 (95% CI 0.98–1.42, p=0.08) for hospitalisation; 1.21 (95% CI 0.97–1.51, p=0.09) for intensive care unit (ICU) admission; 1.06 (95% CI 0.82–1.36, p=0.65) for ventilator use; and 0.94 (95% CI 0.76–1.17, p=0.58) for mortality for people with asthma. Subgroup analyses by continent revealed a significant difference in risk of acquiring COVID-19, ICU admission, ventilator use and death between the continents.

Interpretation

The risk of being infected with severe acute respiratory syndrome coronavirus 2 was reduced compared to the non-asthma group. No statistically significant differences in hospitalisation, ICU admission and ventilator use were found between groups. Subgroup analyses showed significant differences in outcomes from COVID-19 between America, Europe and Asia. Additional studies are required to confirm this risk profile, particularly in Africa and South America, where few studies originate.

Short abstract

The risk of being infected with SARS-CoV-2 was reduced in patients with asthma compared to the non-asthma group. No significant differences in hospitalisation, ICU admission, ventilator use and mortality were found between groups. https://bit.ly/3izKB9h

Introduction

Asthma is one of the most common chronic conditions with an estimated prevalence of >300 million people globally [1]. As coronavirus disease 2019 (COVID-19) continues to spread across the world with >4.05 million deaths as of 15 July 2021 [2], there are concerns that people with asthma are at a higher risk of acquiring the disease, or of poorer outcomes.

There are differing reports on the vulnerability of asthmatics to COVID-19 based on various local or national level case series and analyses [3]. Several meta-analyses have been conducted, but their conclusions suffer limitations from the inclusion of COVID-19 non-PCR-confirmed cases and inclusion of case series in their analyses which confer significant selection bias [4–6] (supplementary table S1). Most focus only on mortality, but not on other important considerations such as risk of being infected, hospitalised, admission to an intensive care unit (ICU) and importantly ventilator use when admitted [7–9].

A comprehensive understanding of COVID-19 risk among asthmatics globally is crucial as countries lift lockdown, and for prioritisation of vaccine allocation considering the limited supply of vaccines globally. Hence, we aimed to conduct a comprehensive systematic review and meta-analysis based only on controlled studies with reverse transcriptase (RT)-PCR-confirmed COVID-19 cases to ascertain the pooled prevalence and overall risk of infection, hospitalisation, ICU admission, ventilator use and mortality from COVID-19 among patients with asthma.

Methods

Search strategy and selection criteria

This systematic review and meta-analysis form part of a living systematic review on the risk of COVID-19 for people with asthma. Our first meta-analysis, which included studies up to 26 May 2020, has been published previously [5] and included pre-prints due to the early stage of the pandemic at that point. The protocol was prospectively registered and published in PROSPERO (www.crd.york.ac.uk/PROSPERO CRD42020222303) (appendix 1). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (www.prisma-statement.org) was used in reporting this study.

A comprehensive search of electronic databases including Cochrane Central Register of Controlled Trials (CENTRAL), Cochrane Database of Systematic Reviews, PubMed, MEDLINE and the World Health Organization COVID-19 database were conducted between 1 December 2019 and 11 July 2021. In addition, a hand search of references of relevant systematic reviews was conducted. In the case of missing information, we contacted the authors whenever possible. If the study identified patients with chronic respiratory conditions, we asked them to specify if this included asthma and requested these data.

We included all primary controlled studies reporting on adults with confirmed COVID-19 based on positive RT-PCR, with a pre-existing diagnosis of asthma, published in the English language. Asthma was defined according to definitions in the individual studies and included those sourced from medical records, physician-diagnosed and self-reported asthma. We excluded studies with ≤15 participants, pre-prints and those not published in English. The search strategy is available in appendix 2.

Data collection

Two reviewers (AS and SA) screened titles and abstracts and excluded irrelevant studies using Rayyan QCRI [10]. Full-text articles were subsequently reviewed independently, and disagreement resolved via consensus and referral to a third reviewer (CJ). Potential overlaps between studies were identified at full-text review to prevent double counting individual patients. A decision on inclusion was made by comparing the study country, location, setting (hospital/community), participant (adults/children), study period and sample size. Data extraction was conducted using a standard electronic form while quality assessment of included studies was performed using the Newcastle–Ottawa Scale [11]. Disagreements were resolved by discussion within the wider team (AS, SA, GL and CJ). No institutional review board approval was required as this study did not independently or prospectively collect patient data.

Outcomes

The outcomes were 1) the risk of acquiring COVID-19, expressed as the proportion of confirmed COVID-19 patients with a pre-existing diagnosis of asthma; 2) risk of hospitalisation from COVID-19 (proportion of confirmed COVID-19 patients hospitalised with asthma); 3) risk of being admitted to ICU (proportion of confirmed COVID-19 patients with asthma admitted to ICU); 4) risk of being ventilated (proportion of confirmed COVID-19 patients with asthma treated with mechanical ventilation once admitted to ICU); and 5) risk of death (proportion of confirmed COVID-19 patients with asthma who are dead or alive).

Data analysis

Descriptive statistics were utilised to summarise the details of the included studies in table 1. The Newcastle–Ottawa Scale [11] was used to assess the methodological quality of included studies based on the relevant study designs cohort or case–control. One star is allocated in the domains of selection and outcome or exposure and up to two stars are allocated to the comparability domain. A total of nine stars are allocated across all three domains. An overall score of 1–3 stars is categorised as low quality, 4–6 as medium quality and 7–9 as high quality.

TABLE 1.

Characteristics of included studies

First author [reference] Country Setting Design Study period COVID-19 positive Age (years) Male (n) Current smokers (n) COPD (n) Diabetes (n) Hypertension (n) NOS score (out of 9)
Asthma (n) Overall (n) Mean Median
Ahlström [ 17 ] Sweden Mixed Case–control study 6 March to 27 May 2020 133 1981 61 1465 75 522 982 9
Almazeedi [ 41 ] Kuwait Hospital Retrospective cohort study 24 February to 20 April 2020 43 1096 41 888 44 5 155 177 9
Arslan [ 46 ] Turkey Hospital Retrospective cohort study 18 March to 15 May 2020 58 767 51.99 374 80 43 137 220 8
Ashinyo [ 47 ] Ghana Hospital Retrospective cohort study 23 March to 29 June 2020 24 307 37.9 174 20 219 7
Aveyard [ 13 ] Mexico Hospital Retrospective cohort study 27 February to 21 June 2020 4942 178 306 44.1 88 083 8
Baumer [ 12 ] UK Hospital Prospective cohort study 9 March to 7 May 2020 12 52 54.82 29 8
Bergman [ 18 ] Sweden Mixed Case–control study To mid-September 2020 4493 68 575 46 26 808 2168 4897 16 416 9
Beurnier [ 48 ] France Hospital Prospective cohort study 15 March to 15 April 2020 37 112 60 49 17 32 9
Calmes [ 49 ] Belgium Hospital Retrospective cohort study 18 March to 17 April 2020 57 596 58.75# 294 9
Castilla [ 19 ] Spain Mixed Retrospective cohort study July to December 2020 2330 35 387 38.8 17 172 6119 1404 1893 4543 9
Chhiba [ 50 ] USA Hospital Retrospective cohort study 1 March to 15 April 2020 220 1526 53.3# 654 43 9
Choi [ 20 ] South Korea Mixed Retrospective cohort study To 15 May 2020 218 7372 44.5# 3000 9
Dennis [ 30 ] UK Hospital Retrospective cohort study 1 March to 27 July 2020 1557 17 606 67 10 560 231 421 9
Eggert [ 51 ] USA Hospital Retrospective cohort study 1 March to 30 September 2020 598 5596 38.4 2635 123 88 609 1021 9
Emami [ 52 ] Iran Hospital Retrospective cohort study 20 February to 1 March 2020 25 1239 51.48 692 27 176 7
Ferastraoaru [ 53 ] USA Hospital Retrospective cohort study 14 March to 27 April 2020 951 4558 60.5 9
Fong [ 54 ] UK Hospital Retrospective cohort study 1 March to 31 May 2020 102 617 65 9
Garcia-Pachon [ 14 ] Spain Community Retrospective cohort study 3 March to 12 April 2020 10 376 54 192 8
Green [ 21 ] Israel Mixed Retrospective cohort study February to June 2020 153 2266 33.31 1200 102 200 276 9
Guan [ 55 ] China Hospital Retrospective cohort study December 2019 to 6 May 2020 244 39 420 55.7 19 655 9
Gude-Sampedro [ 22 ] Spain Mixed Retrospective cohort study 6 March to 7 May 2020 288 10 454 58 4172 258 180 619 1457 9
Gupta [ 29 ] USA Hospital Retrospective cohort study To 4 March 2020 30 529 70 286 39 36 289 416 6
Hansen [ 23 ] Denmark Mixed Retrospective cohort study 1 February to 10 July 2020 354 5104 54.6 2399 432 598 9
Ho [ 38 ] USA Hospital Retrospective cohort study 7 March to 7 June 2020 468 10 523 58.35 5707 286 1679 2662 9
Je [ 56 ] Australia Hospital Retrospective cohort study March to April 2020 22 197 45 94 4 8 28 7
Kim [ 57 ] South Korea Hospital Case–control study February to May 2020 66 2200 56.71 785 92 30 378 645 9
Kipourou [ 58 ] Kuwait Hospital Prospective cohort study 24 February to 27 May 2020 235 3995 40.4 2814 140 17 730 778 9
Lee [ 15 ] South Korea Community Retrospective cohort study January to 27 May 2020 686 7272 45.3 2927 1041 1401 9
Lemus Calderon [ 59 ] Spain Hospital Retrospective cohort study To July 2020 577 6310 59 2983 873 1641 3239 9
Liao [ 60 ] USA Hospital Retrospective cohort study 11 March to 23 June 2020 41 113 50 53 2 57 11 18 9
Lieberman-Cribbin [ 61 ] USA Hospital Retrospective cohort study 29 February to 24 April 2020 272 6245 57 3060 8
Lombardi [ 62 ] Italy Hospital Retrospective cohort study 20 February to 20 April 2020 20 1043 52.5# 704 9
Louie [ 24 ] Australia Mixed Case series 19 March to 15 May 2020 10 99 54 51 2 8 14 8
Lovinsky-Desir [ 63 ] USA Mixed Prospective cohort study 11 February to 7 May 2020 163 1298 52 762 55 9
Martos-Benítez [ 25 ] Mexico Mixed Retrospective cohort study 1 January to 12 May 2020 1188 38 324 46.9 22 362 3277 889 7168 8340 9
Mash [64] South Africa Hospital Retrospective cohort study March to June 2020 67 1376 46.3 571 95 50 364 564 8
Mather [65] USA Hospital Case–control study February to November 2020 88 1045 64.6 352 18 221 307 8
Murillo-Zamora [66] Mexico Hospital Retrospective cohort study 4 March to 15 August 2020 1448 66 123 52.4 40 124 2619 21 840 26 728 9
Nystad [26] Norway Mixed Retrospective cohort study 1 March to 13 May 2020 515 7632 33.22# 161 468 977 7
Patone [27] UK Mixed Retrospective cohort study 1 November to 26 January 2021 29 792 198 420 37.7 93 765 22 134 1873 10 347 19 636 9
Robinson [67] USA Hospital Case–control study 4 March to 2 July 2020 562 3248 51 911 131 321 107 8
Rosenthal [68] USA Hospital Retrospective cohort study March to May 2020 105 727 49.46 165 278 8
Salacup [69] USA Hospital Retrospective cohort study 1 March to 24 April 2020 18 242 66 123 30 118 180 8
Schönfeld [28] Argentina Mixed Retrospective cohort study 3 March to 2 October 2020 12 580 207 079 41 103 487 4074 4405 20 058 39 833 9
Shah [70] USA Hospital Retrospective cohort study 3 February to 31 March 2020 4 33 63 22 0 1 9 16 8
Tutiya [71] Brazil Hospital Retrospective cohort study 13 March to 7 June 2020 7 114 32.4 0 12 13 7
Valverde-Monge [72] Spain Hospital Retrospective cohort study 31 January to 17 April 2020 113 2539 62.66 1275 154 89 403 1054 9
Wang [40] China Hospital Retrospective cohort study 28 January to 25 February 2020 68 562 47 265 8
Yang [37] South Korea Community Retrospective cohort study 1 January to 15 May 2020 725 7340 47.1 2970 350 951 1638 9
Yordanov [16] France Mixed Prospective cohort study March to August 2020 814 7320 43 2301 790 87 402 978 6
Zhang [31] China Hospital Retrospective cohort study 29 December 2019 to 16 February 2020 1 290 57 155 10 6 27 81 8
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COVID-19: coronavirus disease 2019; NOS: Newcastle–Ottawa Scale. #: imputed values based on weighted average.

Two main sets of meta analyses were performed. To pool the prevalence of asthmatics among those with COVID-19, we used the binomial distribution to model the within-study variability and calculated Wilson score 95% confidence intervals.

For all the binary outcomes, we performed Sidik–Jonkman random-effects meta-analysis (assuming that there is not only one true effect size, but a distribution of true effect sizes). We assessed the quantitative heterogeneity by conducting a formal test of homogeneity and evaluating the proportion of variability due to heterogeneity (I2). Pre-specified subgroup analyses were conducted by continent and by the quality of the studies (low, medium, high) and univariable meta-regressions using age and proportions of current and former smokers as covariates.

The assessment of small-study effects has been done by regression-based Egger test and eyeball evaluation of the contour-enhanced funnel plots.

Along with the pooled effect sizes and 95% confidence intervals, we also reported the prediction intervals. All pooled results are presented in the form of forest plots. All statistical analyses were performed using Stata 16 (StataCorp LLC, College Station, TX, USA).

Results

The searches resulted in 32 379 citations. After duplicates were removed, 20 559 titles and abstracts were screened, 19 559  articles were excluded. Of the remaining 1000 articles, 949 were excluded after full-text review. A total of 51 studies were included in the review. Studies with overlapping patient populations were excluded if they reported the same outcome (figure 1).

FIGURE 1.

FIGURE 1

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Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram [73]. CENTRAL: Cochrane Central Register of Controlled Trials; WHO: World Health Organization; COVID-19: coronavirus disease 2019.

Descriptive characteristics

This review is based on a pooled sample of 1 471 643 COVID-19-tested patients, of whom 965 551 were COVID-19 positive with reported information related to asthma. The sample sizes ranged from 52 [12] to 417 366 [13]. Most of the studies were hospital-based (34 studies) while three were studies [14–16] in the community and 14 had a mixed setting [16–28]. Studies originate from 21 countries spread on all five continents: Europe (n=17), North America (n=13), Asia (n=12), South America (n=5), Africa (n=2) and Australia (n=2). The summary of included studies is presented in table 1.

Among COVID-19 positive patients, based on RT-PCR assay results, the mean±sd age of participants was 52.0±12.9 years, 42.64% were male (n=459 640 from 47 out of 51 studies), 5.4% were current smokers (n=38 672 from 23 out of 51 studies) and 9.8% were former smokers (n=43 622 from 10 out of 51 studies). The prevalence of asthma among those infected with COVID-19 was 8.08% (95% CI 6.87–9.30%; test of homogeneity p<0.001). ∼25% had hypertension (n=135 274 from 35 out of 51 studies), 14.3% had diabetes (n=78 923 from 38 out of 51 studies) and 3% had COPD (n=15 636 from 29 out of 51 studies).

Risk-of-bias results

Scores on the Newcastle–Ottawa Scale ranged between 6 and 9 (maximum 9) [16, 29], with a higher score indicating a higher quality. All studies scored ≥7 and were of high quality. A full assessment is presented in supplementary table S3.

Meta-analysis of the risk of acquiring COVID-19

The pooled analysis of 10 studies (n=785 151) showed a risk ratio reduction in acquiring COVID-19 of 17% for people with asthma compared to those without asthma (risk ratio 0.83, 95% CI 0.73–0.95; p=0.01; figure 2). There was considerable heterogeneity (I2=98.46%) across the studies. Meta-regression by age revealed that older age was associated with increased risk of acquiring COVID-19 in individuals with asthma (meta-regression coefficient 0.014, 95% CI 0.004–0.025; p=0.006). Furthermore, R2 showed that 45.51% of the variance between studies can be explained by age. Heterogeneity remains high when age is included as a moderator in the meta-regression (I2=92.03%) meaning that it is not a main factor in the difference between studies. No statistically significant association for current smoker (five out of 10 studies; p=0.09) and former smoker were found (two out of 10 studies; p=0.94).

FIGURE 2.

FIGURE 2

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Risk of acquiring coronavirus disease 2019 (COVID-19) in individuals with asthma compared with no asthma.

Meta-analysis of the risk of hospitalisation

We observed a non-statistically significant different risk for hospitalisation from COVID-19 for people with asthma compared to no asthma (risk ratio 1.18, 95% CI 0.98–1.42; p=0.08), in the 18 studies (n=411 093) included in this analysis. There was considerable heterogeneity observed (I2=98.86%) across the studies (figure 3). Meta-regression by age, current smoker (only from nine out of 18 studies) and former smoker (only from six out of 18 studies) revealed no relevant association in risk of being hospitalised with COVID-19 in individuals with asthma.

FIGURE 3.

FIGURE 3

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Risk of hospitalisation when infected with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Meta-analysis of the risk of ICU admission

There was a non-statistically significant different risk of ICU admission (risk ratio 1.21, 95% CI 0.97–1.51; p=0.09) for people with asthma compared to those without asthma in a pooled analysis of 21 studies (n=192 694). Substantial heterogeneity was observed (I2=94.21%) across the studies (figure 4). Meta-regression with former smoker (four out of 21 studies) as moderator found a statistically significant decrease in risk of ICU admission (meta-regression coefficient −0.00009, 95% CI −0.0002– −2.65×106; p=0.043). Meta-regression with age and current smoker (nine out of 21 studies) as moderator did not reveal statistically significant results (p=0.15 and p=0.37, respectively).

FIGURE 4.

FIGURE 4

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Risk of intensive care unit (ICU) admission when infected with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Meta-analysis of the risk of ventilator use when admitted into the ICU

In relation to probability of mechanical ventilation, of the 11 studies (n=101 694) pooled for this analysis, there was no statistically significant difference in risk of being treated with ventilator once admitted to ICU for people with asthma compared to those without asthma (risk ratio 1.06, 95% 0.82–1.36; p=0.65). Considerable heterogeneity was observed (I2=87.91%) across the studies (figure 5). Meta-regression with age and current smoker (four out of 11 studies) did not reveal statistically significant results (p=0.276 and p=0.260, respectively). Whereas meta-regression with former smoker as a moderator (two out of 11 studies) found a reduction in risk of ventilator use (meta-regression coefficient −0.0022, 95% CI −0.0037– −0.0007; p=0.004).

FIGURE 5.

FIGURE 5

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Risk of mechanical ventilator (MV) use upon admission to intensive care unit with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Meta-analysis of the risk of death

There was a non-statistically significant different risk of death from COVID-19 for people with asthma compared to those without asthma in the 32 studies (n=379 381) pooled for this analysis (risk ratio 0.94, 95% CI 0.76–1.17; p= 0.58). Considerable heterogeneity was observed (I2=94.85%) across the studies (figure 6). When age was included as moderator for meta-regression, there was no statistically significant reduction in risk of death by age (p=0.219). No statistically significant association was also found for current smoker (14 out of 21 studies) and former smoker (seven out of 21 studies) as a moderator (p=0.458 and p=0.288, respectively).

FIGURE 6.

FIGURE 6

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Risk of death when infected with coronavirus disease 2019 in individuals with asthma compared with no asthma.

Subgroup analyses

Subgroup analyses by continent revealed substantial differences in risk of acquiring COVID-19 between the continents (statistically significant at p=0.001) during the period up to 11 July 2021. It showed the lowest risk in Asia (risk ratio 0.66, 95% CI 0.57–0.75) followed by North America (risk ratio 0.78, 95% CI 0.69–0.89), South America (risk ratio 0.84, 95% CI 0.82–0.85) and Europe (risk ratio 1.01, 95% CI 0.82–1.26). No major differences were found between continents in hospitalisation (p=0.128). However, relevant differences in ICU admission were found between continents (statistically significant at p=0.007). The highest risk was found to be in Asia (risk ratio 1.81, 95% CI 1.12–2.91) followed by Europe (risk ratio 1.04, 95% CI 0.86–1.27), North America (risk ratio 0.96, 95% CI 0.72–1.27) and lowest in South America (risk ratio 0.84, 95% CI 0.75–0.93).

In addition, risk of ventilator use was statistically significant different across the continents (p<0.001). The highest risk was found to be in Europe (risk ratio 1.59, 95% CI 1.26–2.00), followed by Asia (risk ratio 1.19, 95% CI 0.74–1.91), North America (risk ratio 1.02, 95% CI 0.74–1.42) and South America (risk ratio 0.50, 95% CI 0.82–1.36). Similarly, risk of death was quite different across the continents (p=0.011). The highest risk was found to be in Asia (risk ratio 2.01, 95% CI 1.19–3.39), followed by Europe (risk ratio 0.85, 95% CI 0.68–1.05), North America (risk ratio 0.79, 95% CI 0.58–1.06) and South America (risk ratio 0.72, 95% CI 0.47–1.12).

Subgroup analyses by study quality for risk for death showed significantly higher risk in the one study of medium quality compared to the 30 higher-quality ones (risk ratio 1.45, 95% CI 1.14–1.87 versus risk ratio 0.92, 95% CI 0.74–1.15; p=0.007).

Publication bias

Egger's test showed evidence of small-study effects for the pooled proportion of COVID-19-positive (RT-PCR) individuals (p<0.0001) and risk of hospitalisation (p=0.0199), but not for all other outcomes (supplementary table S3). Eyeball assessment of the contour enhanced funnel plots revealed asymmetry only for the risk of hospitalisation, but not other outcomes (supplementary figures S1–S6).

Discussion

This meta-analysis aimed to rigorously assess the vulnerability of patients with asthma to COVID-19 based on controlled studies. It revealed an 8.08% prevalence of asthma among those who tested COVID-19 positive based on RT-PCR. This pooled prevalence is higher than the 7.46% prevalence in our previous meta-analysis [30] which analysed studies including pre-prints until May 2020. Only one study [31] from the previous meta-analysis was included in this meta-analysis. This is due to the tighter inclusion criteria of including only published studies with a non-asthma control group, and excluding case series and single-arm cohort studies. Furthermore, both these prevalence rates were lower than the global prevalence of self-reported asthma symptoms of 8.6% [32].

While the proportion estimated in this meta-analysis is lower than in two recent studies in the UK [27] which reported a prevalence of ∼15% in those infected with the B.1.1.7 variant; lower prevalence rates have been reported in other studies in Italy [33] and in Turkey [34] (2.1% among 2000 patients and 3.7% among 565 patients, respectively).

In the studies that report them, we found a high pooled proportion of hypertension (25.7%) and diabetes (14.3%) as comorbidities. These were mostly contributed by hospital studies (22 of the 35 studies reporting hypertension and 24 of the 38 studies reporting diabetes).

This study found a statistically significant risk reduction of 17% (95% CI 5–27%) for acquiring COVID-19, similar to the 14% reduction reported in our previous study [5]. This result is similar to a study from Missouri, USA which reported lower COVID-19 test positivity rates in asthmatics versus non-asthmatics (69.2% versus 81.9%) [35]. Furthermore, a community study in Mexico showed a lower proportion of asthmatics in a COVID-19 positive group compared to a negative group (2.8% versus 3.7%; OR 0.74, 95% CI 0.71–0.77) [21, 36].

Subgroup analyses by continent revealed significant differences in risk of acquiring COVID-19 between the continents, the lowest risk being in Asia (risk ratio 0.66, 95% CI 0.57–0.75) followed by North America (risk ratio 0.78, 95% CI 0.69–0.89), South America (risk ratio 0.84, 95% CI 0.82–0.85) and Europe (risk ratio 1.01, 95% CI 0.82–1.26). Additionally, we noted the consistent nature of the risk reduction in three out of the four regions where data are available. The risk reduction in Asia was found to be consistent in the three studies pooled from China [31], Israel [21] and South Korea [37]; all countries with a high testing regime which might account for this variance between regions. However, analysis of community studies such as this could better reflect the true nature of the risk compared to analysis of hospital-based studies. In addition, it is important to note that this result may not reflect other countries in Asia such as India and Southeast Asia where testing regimes have not been as extensive.

Several possible mechanisms might contribute to a lower risk of acquiring COVID-19 in people with asthma compared to a non-asthmatic population. A retrospective study by Ho et al. [38] showed that not only is asthma associated with lower risk of poor outcomes, but the presence of eosinophilia (≥200 cells·μL−1) both in those with and without asthma was also reported to be associated with reduced mortality risk. While not statistically significant, a higher proportion of those with asthma in this study had eosinophilia compared to non-asthmatics (38.2% versus 32.3%) [38].

Furthermore, a lower risk of acquiring COVID-19 may be attributed to the expression of the angiotensin-converting enzyme (ACE)2 receptor, which is significantly lower in asthma patients compared to those with COPD and healthy controls, as reported in another study [6] which showed that ACE2 expression is increased with older age (at p=0.03). This supports the result of our analysis, which showed strong evidence of increasing age being associated with increased risk of acquiring COVID-19. Finally, people with asthma have been advised by health authorities to practise social distancing and be particularly careful to avoid contracting COVID-19. This was especially the case early in the pandemic when the added risks of having an underlying lung condition were assumed to be substantial. To the extent that these messages [39] were taken seriously by people with asthma, their risk of acquiring infection could have been commensurately reduced.

We also found similar risks for hospitalisation, ICU admission when hospitalised and ventilator use in this study. Even so, we note that for hospitalisation, while not statistically significant, the pooled point estimate suggests a possible 18% increased risk of hospitalisation from COVID-19 for people with asthma, with a wide confidence interval (95% CI −2–42%).

Similarly, for ICU admission, while not statistically significant, the pooled point estimate suggests a possible 21% increased risk of ICU admission from COVID-19 for people with asthma (95% CI −3–51%). One study from China [40] and another from Kuwait [41] reported risk ratios of 5.16 and 4.08, respectively, far greater than in other studies. These differences in risk may be linked to resource allocation and availability or difference in vulnerability due to ethnicity or other environmental factors.

An important finding of this current study and our previous meta-analysis is the similar risk of death between asthmatics and non-asthmatics from COVID-19. While this may be due to a variety of factors, two recent randomised controlled trials of budesonide (an inhaled corticosteroid frequently prescribed to patients with asthma) [42, 43] have raised the possibility that this is an effect of the inhaled corticosteroid. They reported that early administration of inhaled budesonide reduced the likelihood of urgent medical care and reduced time to recovery from COVID-19. One of these studies, the STOIC open-label trial in 146 participants showed a number needed to treat of eight with budesonide to reduce COVID-19 deterioration, and that clinical recovery occurred a day faster in the budesonide group compared to usual care (7 days, 95% CI 6–9 days versus 8 days, 7–11 days; log-rank test p=0.007) [42]. The other study is an interim analysis of the PRINCIPLE trial published as a pre-print, which randomised 751 participants to budesonide compared with 1028 usual care and 643 on other interventions showed a faster recovery in the budesonide group compared to usual care (hazard ratio 1.208, 95% Bayesian credible interval (BCI) 1.076–1.356; probability of superiority 0.999, estimated benefit of 3.011 days, 95% BCI 1.134–5.41 days) [43].

A limitation of this study is the inclusion of very few studies originating from Africa and South America. Additionally, most of the studies were hospital-based, which is likely to be a consequence of including only COVID-19 cases confirmed by RT-PCR. We chose RT-PCR positivity to give more certainty to our estimation of the association between asthma and several important COVID-19 outcomes. As PCR testing regimens show substantial variation between countries, our results might not be generalisable to regions which are poorer and marginalised or to groups that might be less likely to seek testing. In these regions, it is likely that due to under-testing the true proportion of asthmatics as well as the general public with COVID-19 is substantially higher than official reports, by a magnitude of multiple folds [44, 45].

Potential selection bias to those more unwell may also be present due to the large number of hospital-based studies included in this review. Even so, 10 of the studies found to calculate the risk of getting the infection were community based (n=726 269), which we hope provides a better representation of risk for the general community.

There was minimal information provided on smoking (only 23 out of 51 studies indicated the proportion of current smokers, and 10 out of 51 indicated the proportion of former smokers). Hence, based on the 10 studies, we found that being a former smoker was associated with a lower risk of ICU admission; however, this minimal information limits the generalisability of our assessment of the impact of smoking. Despite these limitations, the majority of studies we included were of high quality with minimal selection bias due to their large sample sizes, data sourcing through electronic health records or data linkages which resulted in minimal loss to follow-up. Additionally, we used hard outcome measures such as COVID-19 infection (PCR positivity), hospitalisation, ICU admission and death, which are generally well-defined globally, limiting the risk of classification bias. Funnel plots and Egger's test for small-study effects were also conducted to explore the presence of publication bias and we found that most outcomes do not show signs of publication bias.

Furthermore, our conclusions are based on studies which report details of both asthma and non-asthma patients where COVID-19 infection status was confirmed by RT-PCR results and not only by symptoms or suspected cases in the context of the pandemic. We did not have access to information that would enable us to determine if people with asthma were over-represented among mild or asymptomatic cases that did not receive testing.

In conclusion, the findings from this analysis indicate the prevalence of asthma was 8.08% among people who were RT-PCR-positive for COVID-19 in these controlled studies. The overall findings suggest that people with asthma are at lower risk of being infected with COVID-19 compared to those without asthma, but have a similar risk of hospitalisation, ICU admission, ventilator use and mortality when RT-PCR-positive. With the fast evolution of the severe acute respiratory syndrome coronavirus 2 virus and the emergence of variants globally, caution must be maintained for people with asthma. There remains a need for higher-quality community studies as well as regular risk assessments and review of new data throughout the pandemic. Furthermore, additional studies are required to confirm this risk profile, particularly in Africa and South America, where none of the eligible studies originated.

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Supplementary tables and figures ERJ-01209-2021.Supplement (662.1KB, pdf)

Appendix 1 ERJ-01209-2021.Appendix_1 (1.9MB, pdf)

Appendix 2 ERJ-01209-2021.Appendix_2 (38KB, pdf)

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Acknowledgements

This study was self-funded. A.P. Sunjaya is supported by a Scientia PhD scholarship from UNSW Sydney. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Footnotes

This article has supplementary material available from erj.ersjournals.com

Author contributions: A.P. Sunjaya and S.M. Allida completed the search of the literature, title/abstract screening and inclusion/exclusion review, data extraction and quality assessment and contributed to writing the review. G.L. Di Tanna performed the statistical analysis and contributed to writing the review. C.R. Jenkins initiated this review, engaged co-authors, was third independent reviewer, and oversaw the study from inception to completion. She contributed to writing and reviewing all draft manuscripts.

Conflict of interest: A.P. Sunjaya has nothing to disclose.

Conflict of interest: S.M. Allida has nothing to disclose.

Conflict of interest: G.L. Di Tanna has nothing to disclose.

Conflict of interest: C.R. Jenkins has nothing to disclose.

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