The association of smoking status with SARS-CoV-2 infection, hospitalisation and mortality from COVID-19: A living rapid evidence review with Bayesian meta-analyses (version 8)

Aims: To estimate the association of smoking status with rates of i) infection, ii) hospitalisation, iii) disease severity, and iv) mortality from SARS-CoV-2/COVID-19 disease. Design: Living rapid review of observational and experimental studies with random-effects hierarchical Bayesian metaanalyses. Published articles and pre-prints were identified via MEDLINE and medRxiv. Setting: Community or hospital. No restrictions on location. Participants: Adults who received a SARS-CoV-2 test or a COVID-19 diagnosis. Measurements: Outcomes were SARS-CoV-2 infection, hospitalisation, disease severity and mortality stratified by smoking status. Study quality was assessed (i.e. ‘good’, ‘fair’ and ‘poor’). Findings: Version 8 (searches up to 22 September 2020) included 256 studies with 36 ‘good’ and ‘fair’ quality studies included in meta-analyses. Sixty-seven studies (26.2%) reported current, former and never smoking status with the remainder using broader categories. Recorded smoking prevalence among people with COVID-19 was generally lower than national prevalence. Current compared with never smokers were at reduced risk of SARS-CoV-2 infection (RR=0.72, 95% Credible Interval (CrI) = 0.57-0.89, τ = 0.40). Data for former smokers were inconclusive (RR=1.02, 95% CrI = 0.92-1.13, τ = 0.18) but favoured there being no important association (7% probability of RR ≥1.1). Former compared with never smokers were at somewhat increased risk of hospitalisation (RR=1.19, CrI = 1.03-1.43, τ = 0.17), greater disease severity (RR=1.52, CrI = 1.12-2.05, τ = 0.29) and mortality (RR=1.35, 95% CrI = 1.09-1.73, τ = 0.26). Data for current smokers on hospitalisation, disease severity and mortality were inconclusive (RR=1.06, CrI = 0.82-1.35, Qeios, CC-BY 4.0 · Article, October 7, 2020 Qeios ID: UJR2AW.9 · https://doi.org/10.32388/UJR2AW.9 1/56 τ = 0.27; RR=1.26, CrI = 0.85-1.96, τ = 0.34; RR=1.10, 95% CrI = 0.69-1.67, τ = 0.50, respectively) but favoured there being no important associations with hospitalisation and mortality (35% and 51% probability of RR ≥1.1, respectively) and a small but important association with disease severity (79% probability of RR ≥1.1). Conclusions: Compared with never smokers, current smokers appear to be at reduced risk of SARS-CoV-2 infection while former smokers appear to be at increased risk of hospitalisation, greater disease severity and mortality from COVID-19. However, it is uncertain whether these associations are causal.


Introduction
COVID-19 is a respiratory disease caused by the SARS-CoV-2 virus. Large age and gender differences in case severity and mortality have been observed in the ongoing COVID-19 pandemic 1 ; however, these differences are currently unexplained. SARS-CoV-2 enters epithelial cells through the angiotensin-converting enzyme 2 (ACE-2) receptor 2 . Some evidence suggests that gene expression and subsequent receptor levels are elevated in the airway and oral epithelium of current smokers 3,4 , which could put smokers at higher risk of contracting SARS-CoV-2. Other studies, however, suggest that nicotine downregulates the ACE-2 receptor 5 . These uncertainties notwithstanding, both former and current smoking is known to increase the risk of respiratory viral 6,7 and bacterial 8,9 infections and is associated with worse outcomes once infected. Cigarette smoke reduces the respiratory immune defence through peri-bronchiolar inflammation and fibrosis, impaired mucociliary clearance and disruption of the respiratory epithelium 10 . There is also reason to believe that behavioural factors (e.g. regular hand-to-mouth movements) involved in smoking may increase SARS-CoV-2 infection and transmission in current smokers. However, early data from the COVID-19 pandemic have not provided clear evidence for a negative impact of current or former smoking on SARS-CoV-2 infection or COVID-19 disease outcomes, such as hospitalisation or mortality 11 . It has also been hypothesised that nicotine might protect against a hyper-inflammatory response to SARS-CoV-2 infection, which may lead to adverse outcomes in patients with COVID-19 disease 12 .
There are several reviews that fall within the scope of smoking and COVID-19 11,[13][14][15][16][17][18] . We aimed to produce a rapid synthesis of available evidence pertaining to the rates of infection, hospitalisation, disease severity and mortality from SARS-CoV-2/COVID-19 stratified by smoking status. Given the increasing availability of data on this topic, this is a living review with regular updates. As evidence accumulates, the review will be expanded to include studies reporting COVID-19 outcomes by alternative nicotine use (e.g., nicotine replacement therapy or e-cigarettes).

Study design
This is a living evidence review which is updated as new evidence becomes available 19 . We adopted recommended best practice for rapid evidence reviews, which involved limiting the search to main databases and having one reviewer extract series of random-effects hierarchical Bayesian meta-analyses were performed with the brms 24 package to estimate the relative risk for each comparison with accompanying 95% credible intervals (CrIs). We first defined prior distributions for the true pooled effect size (µ) and the between-study heterogeneity (τ), with µ specified as a normal distribution with a mean equal to the derived point estimate from each comparison of interest in the immediately preceding version of this living review 25 , and τ specified as a half-Cauchy distribution with a mean of 0 and standard deviation of 1. The half-Cauchy distribution was selected to reflect prior knowledge that high levels of between-study heterogeneity are more likely than lower levels. Markov Chain Monte Carlo methods (20,000 burn-ins followed by 80,000 iterations) were then used to generate a risk distribution for each study, in addition to a pooled effect for the posterior risk distribution. We report forest plots with the pooled effect for the posterior risk distribution displayed as the median relative risk with an accompanying 95% CrIs. We used the empirical cumulative distribution function (ECDF) to estimate the probability of there being a 10% reduction or 10% increase in relative risk (RR) (i.e. RR ≥1.1 or RR ≤0.9). Due to a lack of indication as to what constitutes a clinically or epidemiologically meaningful effect (e.g. with regards to onward disease transmission or requirements for intensive care beds), we deemed a 10% change in risk as small but important. Where data were inconclusive (as indicated by CrIs crossing RR = 1.0), to disambiguate whether data favoured no effect or there being a small but important association, we estimated whether there was ≥75% probability of RR ≥1.1 or RR ≤0.9.
Two sensitivity analyses were performed. First, a minimally informative prior for µ was specified as a normal distribution with a mean of 0 and standard deviation of 1 and τ as described above. Second, an informative prior as described above for µ was used with τ specified as a half-Cauchy distribution with a mean of 0.3 and standard deviation of 1 to reflect greater between-study heterogeneity.
To aid in the visualisation of smoking prevalence in the included studies, the weighted mean prevalence of current and former smoking was calculated for countries in which ≥3 studies were conducted and plotted for comparison with national prevalence estimates. It should be noted that prevalence estimates in the included studies were not adjusted for age, sex, socioeconomic position, or region within countries.

Results
In the current review version (v8) with searches up to 22 September 2020, a total of 593 new records were identified, with 256 studies included in a narrative synthesis and 36 studies included in meta-analyses (see Figure 1).

Study characteristics
Characteristics of included studies are presented in Table 1. Studies were conducted across 34 countries. Sixty-eight studies were conducted in the US, 56 in China, 30 in the UK, 15 in Spain, 14 in Mexico, 12 in France, seven in Italy, seven across multiple international sites, five in Iran, four in Brazil, three in Israel and Turkey, two in Australia, Bangladesh, Chile, Denmark, Finland, India, Japan and Qatar and one from 15 further countries (see Supplementary figure S1). The majority of studies used observational designs (see Supplementary table S1). One-hundred-and-sixty-five studies (64.5%) were conducted in hospital settings, 73 studies (28.5%) included a community component in addition to hospitalised patients and 16 studies (6.2%) were conducted exclusively in the community, one in a quarantine centre and one did not state the study setting. Studies had a median of 428 (interquartile range = 129-1,765) participants. The majority of studies (92.6%) used reverse transcriptase polymerase chain reaction (RT-PCR) for confirmation of SARS-CoV-2 infection, 3.5% used an antibody test to confirm prior infection, and 3.9% further studies relied on a combination of RT-PCR and clinical diagnosis (see Supplementary table S1).

Smoking status
Categorisation of smoking status was heterogeneous (see Table 1). One-hundred-and-fifty-five studies collected data on smoking status through routine electronic health records (EHRs), 72 studies used a bespoke case report form for COVID- 19  remaining 171 studies reported current, current/former or current and former smoking status but did not explicitly state whether remaining participants were never smokers or if data were missing on smoking status (see Supplementary table   S2c). Eighty-three studies explicitly reported the proportion with missing data on smoking status, which ranged from 0% to 96.4%.

Use of alternative nicotine products
Five studies recorded the use of alternative nicotine products in current and/or former smokers but did not report COVID-19 outcomes stratified by nicotine use [26][27][28][29][30] .

Quality appraisal
Two studies were performed in random, representative population samples and were rated as 'good' quality. Fifty-two studies were rated as 'fair' quality, of which 36 studies reported results stratified by smoking status for the outcomes of interest and could be included in meta-analyses. The remaining 202 studies were rated as 'poor' quality (see Table 1).

Smoking prevalence by country
Unadjusted smoking prevalence compared with overall estimates for national adult smoking prevalence split by country and study setting is presented in Figure 2a and 2b. Lower than expected current smoking prevalence was generally observed. Former smoking prevalence was more similar to expected prevalence when reported. National smoking prevalence estimates used for comparison are presented in Supplementary table 3.

SARS-CoV-2 testing by smoking status
Three studies provided data on access to SARS-CoV-2 diagnostic testing for those meeting local testing criteria by smoking status. In a cohort study of US military veterans aged 54-75 31

SARS-CoV-2 infection by smoking status
Fifty studies provided data on SARS-CoV-2 infection for people meeting local testing criteria by smoking status (see Table   2). Meta-analyses were performed for two 'good' and 17 'fair' quality studies (see Figure 4

Hospitalisation for COVID-19 by smoking status
Thirty-one studies examined hospitalisation for COVID-19 disease, stratified by smoking status (see Table 3). Metaanalyses were performed for eight 'fair' quality studies (see Figure 6

Disease severity by smoking status
Sixty-three studies reported disease severity in hospitalised patients stratified by smoking status (see Table 4). Severe (as opposed to non-severe) disease was broadly defined as requiring intensive treatment unit (ITU) admission, requiring oxygen as a hospital inpatient or in-hospital death. Meta-analyses were performed for eight 'fair' quality studies (see Figure   8 and 9). Current (RR = 1.26, CrI = 0.85-1.96, τ = 0.34, 95% CI = 0.01-0.86) and former (RR = 1.52, CrI = 1.12-2.05, τ = 0.29, 95% CI = 0.47-0.66) compared with never smokers were at increased risk of greater disease severity; data for current smokers were inconclusive but favoured there being a small but important association. The probability of current and former smokers having increased risk of greater disease severity (RR ≥1.1) compared with never smokers was 79% and 98%, respectively. Results were materially unchanged in two sensitivity analyses (see Supplementary figure S4).

Discussion
This living rapid review found uncertainty in the majority of 256 studies arising from the recording of smoking status.
Notwithstanding these uncertainties, compared with overall adult national prevalence estimates, recorded current smoking rates in most studies were lower than expected. In a subset of better-quality studies (n = 19), current but not former smokers had a reduced risk of testing positive for SARS-CoV-2 but current smokers appeared somewhat more likely to present for testing and/or receive a test. Data for current smokers on the risk of hospitalisation, disease severity and mortality were inconclusive, and favoured there being no important associations with hospitalisation and mortality and a small but important increase in the risk of severe disease. Former smokers were at increased risk of hospitalisation, disease severity and mortality compared with never smokers.

Issues complicating interpretation
Interpretation of results from studies conducted during the first phase of the SARS-CoV-2 pandemic is complicated by several factors (see Figure 11): 1) Exposure to SARS-CoV-2 is heterogeneous with different subgroups at heightened risk of infection at different stages of the pandemic. This will likely introduce bias in studies assessing the rate of infection by smoking status conducted early on.
2) Current and former smokers may be more likely to meet local criteria for community testing due to increased prevalence of symptoms consistent with SARS-CoV-2 infection, such as cough, increased sputum production or altered sense of smell or taste 35 47 , where conditioning on a collider (e.g. testing or hospitalisation) by design or analysis may introduce a spurious association between current or former smoking (a potential cause of testing or hospitalisation) and SARS-CoV-2 infection/adverse outcomes from COVID-19 (potentially exacerbated by smoking) 48 .
13) The majority of included studies were conducted in hospital settings. It is plausible that a non-trivial proportion of patients were infected with SARS-CoV-2 while being an inpatient for a different medical reason. If so, this may have biased the hospitalised populations towards older and more frail groups, who are less likely to be smokers 49 . Figure 11. A schematic of some of the interpretation issues for the association of smoking and SARS-CoV-2/COVID-19. * Indicates potential confounding with smoking status.

Limitations
This living rapid evidence review was limited by having a single reviewer extracting data with a second independently verifying the data extracted to minimise errors, restricting the search to one electronic database and one pre-print server and by not including at least three large population surveys due to their reliance on self-reported suspected or confirmed SARS-CoV-2 infection (which means they do not meet our eligibility criteria) 35,50,51 . We also did not include a large, UKbased, representative seroprevalence study 52 in our meta-analyses as the odds of testing positive in former smokers was not reported. However, the odds of infection for current smokers (OR = 0.64, 95% CI = 0.58-0.71) was in concordance with the pooled estimate in our meta-analysis. Population surveys -particularly with linked data on confirmed infection or antibodies -will be included in future review versions to help mitigate some of the limitations of healthcare based observational studies. The comparisons of current and former smoking prevalence in the included studies with national prevalence estimates did not adjust observed prevalence for the demographic profile of those tested/admitted to hospital.
Other reviews focused on this comparison have applied adjustments for sex and age, and continue to find lower than expected prevalence -notwithstanding the issues complicating interpretation described above 17 .

Implications for research, policy and practice
Further scientific research is needed to resolve the mixed findings summarised in our review. First, clinical trials of the posited therapeutic effect of nicotine could have important implications both for smokers and for improved understanding of how the SARS-CoV-2 virus causes disease in humans. Such trials should focus on medicinal nicotine (as smoked tobacco is a dirty delivery mechanism that could mask beneficial effects) and potentially differentiate between different modes of delivery (i.e. inhaled vs. ingested) since this can affect pharmacokinetics 53 and potential therapeutic effects. A second research priority would be a large, representative (randomly sampled) population survey with a validated assessment of smoking status which distinguishes between recent and long-term ex-smokers -ideally biochemically verified -and assesses seroprevalence and links to health records.
In the meantime, public-facing messages about the possible protective effect of smoking or nicotine are premature. In our view, until there is further research, the quality of the evidence does not justify the huge risk associated with a message likely to reach millions of people that a lethal activity, such as smoking, may protect against COVID-19. It continues to be appropriate to recommend smoking cessation and emphasise the role of alternative nicotine products to support smokers to stop as part of public health efforts during COVID-19. At the very least, smoking cessation reduces acute risks from cardiovascular disease and could reduce demands on the healthcare system 54 . GPs and other healthcare providers can play a crucial role -brief, high-quality and free online training is available at National Centre for Smoking Cessation and Training.

Conclusion
Across 256 studies, recorded smoking prevalence was generally lower than national prevalence estimates. Current smokers were at reduced risk of testing positive for SARS-CoV-2 and former smokers were at increased risk of hospitalisation, disease severity and mortality compared with never smokers.
by Martin Dockrell, Tobacco Control Lead, Public Health England. All scientific decisions were made by the authors independently of funders and external organisations. The authors would like to thank Rosemary Koper for her assistance in running the electronic searches and data extraction.