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COVID-19: Potential Implications for Individuals with Substance Use Disorders

March 23, 2020

As people across the U.S. and the rest of the world contend with coronavirus disease 2019 (COVID-19), the research community should be alert to the possibility that it could hit some populations with substance use disorders (SUDs) particularly hard. Because it attacks the lungs, the coronavirus that causes COVID-19 could be an especially serious threat to those who smoke tobacco or marijuana or who vape. People with opioid use disorder (OUD) and methamphetamine use disorder may also be vulnerable due to those drugs’ effects on respiratory and pulmonary health. Additionally, individuals with a substance use disorder are more likely to experience homelessness or incarceration than those in the general population, and these circumstances pose unique challenges regarding transmission of the virus that causes COVID-19. All these possibilities should be a focus of active surveillance as we work to understand this emerging health threat.

Coronavirus Disease 2019 (COVID-19)

Image by CDC/ Alissa Eckert, MS; Dan Higgins, MAMS

This illustration, created at the Centers for Disease Control and Prevention (CDC), reveals ultrastructural morphology exhibited by coronaviruses. Note the spikes that adorn the outer surface of the virus, which impart the look of a corona surrounding the virion, when viewed electron microscopically. A novel coronavirus, named Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), was identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China in 2019. The illness caused by this virus has been named coronavirus disease 2019 (COVID-19).

 

NIH has posted a compilation of updates for applicants and grantees, including a Guide Notice on administrative flexibilities and accompanying FAQs.

 

SARS-CoV-2, the virus that causes COVID-19 is believed to have jumped species from other mammals (likely bats) to first infect humans in Wuhan, capital of China’s Hubei province, in late 2019. It attacks the respiratory tract and appears to have a higher fatality rate than seasonal influenza. The exact fatality rate is still unknown, since it depends on the number of undiagnosed and asymptomatic cases, and further analyses are needed to determine those figures. Thus far, deaths and serious illness from COVID-19 seem concentrated among those who are older and who have underlying health issues, such as diabetes, cancer, and respiratory conditions. It is therefore reasonable to be concerned that compromised lung function or lung disease related to smoking history, such as chronic obstructive pulmonary disease (COPD), could put people at risk for serious complications of COVID-19.

Co-occurring conditions including COPD, cardiovascular disease, and other respiratory diseases have been found to worsen prognosis in patients with other coronaviruses that affect the respiratory system, such as those that cause SARS and MERS. According to a case series published in JAMA based on data from the Chinese Center for Disease Control and Prevention (China CDC), the case fatality rate (CFR) for COVID-19 was 6.3 percent for those with chronic respiratory disease, compared to a CFR of 2.3 percent overall. In China, 52.9 percent of men smoke, in contrast to just 2.4 percent of women; further analysis of the emerging COVID-19 data from China could help determine if this disparity is contributing to the higher mortality observed in men compared to women, as reported by China CDC. While data thus far are preliminary, they do highlight the need for further research to clarify the role of underlying illness and other factors in susceptibility to COVID-19 and its clinical course.

Vaping, like smoking, may also harm lung health. Whether it can lead to COPD is still unknown, but emerging evidence suggests that exposure to aerosols from e-cigarettes harms the cells of the lung and diminishes the ability to respond to infection. In one NIH-supported study, for instance, influenza virus-infected mice exposed to these aerosols had enhanced tissue damage and inflammation.

People who use opioids at high doses medically or who have OUD face separate challenges to their respiratory health. Since opioids act in the brainstem to slow breathing, their use not only puts the user at risk of life-threatening or fatal overdose, it may also cause a harmful decrease in oxygen in the blood (hypoxemia). Lack of oxygen can be especially damaging to the brain; while brain cells can withstand short periods of low oxygen, they can suffer damage when this state persists. Chronic respiratory disease is already known to increase overdose mortality risk among people taking opioids, and thus diminished lung capacity from COVID-19 could similarly endanger this population.

A history of methamphetamine use may also put people at risk. Methamphetamine constricts the blood vessels, which is one of the properties that contributes to pulmonary damage and pulmonary hypertension in people who use it. Clinicians should be prepared to monitor the possible adverse effects of methamphetamine use, the prevalence of which is increasing in our country, when treating those with COVID-19.

Other risks for people with substance use disorders include decreased access to health care, housing insecurity, and greater likelihood for incarceration. Limited access to health care places people with addiction at greater risk for many illnesses, but if hospitals and clinics are pushed to their capacity, it could be that people with addiction—who are already stigmatized and underserved by the healthcare system—will experience even greater barriers to treatment for COVID-19.  Homelessness or incarceration can expose people to environments where they are in close contact with others who might also be at higher risk for infections. The prospect of self-quarantine and other public health measures may also disrupt access to syringe services, medications, and other support needed by people with OUD.

We know very little right now about COVID-19 and even less about its intersection with substance use disorders. But we can make educated guesses based on past experience that people with compromised health due to smoking or vaping and people with opioid, methamphetamine, cannabis, and other substance use disorders could find themselves at increased risk of COVID-19 and its more serious complications—for multiple physiological and social/environmental reasons. The research community should thus be alert to associations between COVID-19 case severity/mortality and substance use, smoking or vaping history, and smoking- or vaping-related lung disease. We must also ensure that patients with substance use disorders are not discriminated against if a rise in COVID-19 cases places added burden on our healthcare system.

As we strive to confront the major health challenges of opioid and other drug overdoses—and now the rising infections with COVID-19—NIDA encourages researchers to request supplements that will allow them to obtain data on the risks for COVID-19 in individuals experiencing substance use disorders.

This content is also available in Spanish – COVID-19: Las posibles implicaciones para las personas con trastornos por consumo de drogas.

 

Additional Links

Latest Information from the CDC on Coronavirus Disease 2019 (COVID-19)

For those with questions about how their state justice systems are adjusting operating procedures in response to COVID-19, The Marshall Project is tracking changes as they occur. Also, the Vera Institute of Justice has developed guidance for justice system adjustments to COVID-19.

 

This page was last updated March 2020

Analysis of Factors Associated with Disease Outcomes in Hospitalized Patients with 2019 Novel Coronavirus Disease

Liu, Wei1; Tao, Zhao-Wu2; Lei, Wang1; Ming-Li, Yuan1; Kui, Liu3; Ling, Zhou3; Shuang, Wei3; Yan, Deng3; Jing, Liu4; Liu, Hui-Guo3; Ming, Yang5; Yi, Hu1

Section Editor(s): Wei, Pei-Fang

Author Information

doi: 10.1097/CM9.0000000000000775

Abstract

Background:

Since early December 2019, the 2019 novel coronavirus disease (COVID-19) has caused pneumonia epidemic in Wuhan, Hubei province of China. This study aims to investigate the factors affecting the progression of pneumonia in COVID-19 patients. Associated results will be used to evaluate the prognosis and to find the optimal treatment regimens for COVID-19 pneumonia.

Methods:

Patients tested positive for the COVID-19 based on nucleic acid detection were included in this study. Patients were admitted to 3 tertiary hospitals in Wuhan between December 30, 2019, and January 15, 2020. Individual data, laboratory indices, imaging characteristics, and clinical data were collected, and statistical analysis was performed. Based on clinical typing results, the patients were divided into a progression group or an improvement/stabilization group. Continuous variables were analyzed using independent samples t-test or Mann-Whitney U test. Categorical variables were analyzed using Chi-squared test or Fisher exact test. Logistic regression analysis was performed to explore the risk factors for disease progression.

Results:

Seventy-eight patients with COVID-19-induced pneumonia met the inclusion criteria and were included in this study. Efficacy evaluation at 2 weeks after hospitalization indicated that 11 patients (14.1%) had deteriorated, and 67 patients (85.9%) had improved/stabilized. The patients in the progression group were significantly older than those in the disease improvement/stabilization group (66 [51, 70] vs. 37 [32, 41] years, U = 4.932, P = 0.001). The progression group had a significantly higher proportion of patients with a history of smoking than the improvement/stabilization group (27.3% vs. 3.0%, χ2 = 9.291, P = 0.018). For all the 78 patients, fever was the most common initial symptom, and the maximum body temperature at admission was significantly higher in the progression group than in the improvement/stabilization group (38.2 [37.8, 38.6] vs. 37.5 [37.0, 38.4]°C, U = 2.057, P = 0.027). Moreover, the proportion of patients with respiratory failure (54.5% vs. 20.9%, χ2 = 5.611, P = 0.028) and respiratory rate (34 [18, 48] vs. 24 [16, 60] breaths/min, U = 4.030, P = 0.004) were significantly higher in the progression group than in the improvement/stabilization group. C-reactive protein was significantly elevated in the progression group compared to the improvement/stabilization group (38.9 [14.3, 64.8] vs. 10.6 [1.9, 33.1] mg/L, U = 1.315, P = 0.024). Albumin was significantly lower in the progression group than in the improvement/stabilization group (36.62 ± 6.60 vs. 41.27 ± 4.55 g/L, U = 2.843, P = 0.006). Patients in the progression group were more likely to receive high-level respiratory support than in the improvement/stabilization group (χ2 = 16.01, P = 0.001). Multivariate logistic analysis indicated that age (odds ratio [OR], 8.546; 95% confidence interval [CI]: 1.628–44.864; P = 0.011), history of smoking (OR, 14.285; 95% CI: 1.577–25.000; P = 0.018), maximum body temperature at admission (OR, 8.999; 95% CI: 1.036–78.147, P = 0.046), respiratory failure (OR, 8.772, 95% CI: 1.942–40.000; P = 0.016), albumin (OR, 7.353, 95% CI: 1.098–50.000; P = 0.003), and C-reactive protein (OR, 10.530; 95% CI: 1.224−34.701, P = 0.028) were risk factors for disease progression.

Conclusions:

Several factors that led to the progression of COVID-19 pneumonia were identified, including age, history of smoking, maximum body temperature on admission, respiratory failure, albumin, C-reactive protein. These results can be used to further enhance the ability of management of COVID-19 pneumonia.

 

© 2020 by Lippincott Williams & Wilkins, Inc.

Call for a Ban on the Sale of All Tobacco/Vaping Products During Pandemic Period

New York State Academy of Family Physicians

For Immediate Release

March 22, 2020

Contact: Vito F. Grasso, MPA

Executive Vice President

(518) 489-8945/ vito@nysafp.org

 

Statement by NYSAFP on Link Between Tobacco Use and COVID-19 Call for a Ban on the Sale of All Tobacco/Vaping Products During Pandemic Period

 

Barbara Keber, MD President

“As our State and Country struggle to respond to the rapidly evolving and escalating COVID-19 pandemic affecting our residents and straining our healthcare system, mounting evidence demonstrates the link between tobacco use and increased risk for progressive COVID-19. NYSAFP calls for an immediate ban on the sale of all tobacco and vaping/e-cigarette products by Executive Order to protect New Yorkers and lessen the impact and progression of this serious virus on those who contract it.”

“A recently published study (https://pubmed.ncbi.nlm.nih.gov/32118640/ compared COVID-19 patients with disease progression to those who’s health improved or were stabilized. The study found that the progression group had a significantly higher proportion of patients with a history of smoking/tobacco use than the improvement/stabilization group, suggesting patients who use tobacco are 14 times as likely to have COVID-19 progression requiring more extensive treatment and hospitalization than those who do not. Additionally, people with COVID-19 are highly contagious and with sustained progression continue to infect others. The increased risk is an alarming finding which must be immediately addressed in our COVID-19 response.”

“The American Academy of Family Physicians recently developed guidance stating that people who smoke or use vapes or e-cigarettes have a significantly higher risk of contracting respiratory infections like coronavirus. People with decreased lung function caused by smoking or vaping are more likely to develop serious complications caused by infections.”

“Now more than ever, it is critical for the State and medical community to take actions to prevent our youth from ever using these highly addictive, deadly products and to help our patients to reduce their risks through FDA-approved cessation and telehealth during this pandemic.”

“NYSAFP has been an active supporter of legislation to end the sale of all flavored tobacco including flavored e-cigarettes given that nearly one in three high schoolers are now using a flavored vape product in New York. This proposal must be enacted immediately in the final budget being negotiated. Further, given the clear evidence of elevated risk of COVID-19 and tobacco use, NYSAFP calls for a ban on the sale of all tobacco/vaping products during the pandemic period. Bold, swift actions must be taken to protect our residents and we must follow the science which supports our call for a ban.”

 

The NYSAFP is the New York chapter of the American Academy of Family Physicians. NYSAFP represents more than 6,000 family physicians and medical students throughout the state and provides advocacy, education and information for its members. For more information, please visit www.nysafp.org.

Clinical Characteristics of Coronavirus Disease 2019 in China

Abstract

BACKGROUND

Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients.

METHODS

We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death.

RESULTS

The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission.

CONCLUSIONS

During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)


In early December 2019, the first pneumonia cases of unknown origin were identified in Wuhan, the capital city of Hubei province.1 The pathogen has been identified as a novel enveloped RNA betacoronavirus2 that has currently been named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has a phylogenetic similarity to SARS-CoV.3 Patients with the infection have been documented both in hospitals and in family settings.4-8

The World Health Organization (WHO) has recently declared coronavirus disease 2019 (Covid-19) a public health emergency of international concern.9 As of February 25, 2020, a total of 81,109 laboratory-confirmed cases had been documented globally.5,6,9-11 In recent studies, the severity of some cases of Covid-19 mimicked that of SARS-CoV.1,12,13 Given the rapid spread of Covid-19, we determined that an updated analysis of cases throughout mainland China might help identify the defining clinical characteristics and severity of the disease. Here, we describe the results of our analysis of the clinical characteristics of Covid-19 in a selected cohort of patients throughout China.

Methods

STUDY OVERSIGHT

The study was supported by National Health Commission of China and designed by the investigators. The study was approved by the institutional review board of the National Health Commission. Written informed consent was waived in light of the urgent need to collect data. Data were analyzed and interpreted by the authors. All the authors reviewed the manuscript and vouch for the accuracy and completeness of the data and for the adherence of the study to the protocol, available with the full text of this article at NEJM.org.

DATA SOURCES

We obtained the medical records and compiled data for hospitalized patients and outpatients with laboratory-confirmed Covid-19, as reported to the National Health Commission between December 11, 2019, and January 29, 2020; the data cutoff for the study was January 31, 2020. Covid-19 was diagnosed on the basis of the WHO interim guidance.14 A confirmed case of Covid-19 was defined as a positive result on high-throughput sequencing or real-time reverse-transcriptase–polymerase-chain-reaction (RT-PCR) assay of nasal and pharyngeal swab specimens.1 Only laboratory-confirmed cases were included in the analysis.

We obtained data regarding cases outside Hubei province from the National Health Commission. Because of the high workload of clinicians, three outside experts from Guangzhou performed raw data extraction at Wuhan Jinyintan Hospital, where many of the patients with Covid-19 in Wuhan were being treated.

We extracted the recent exposure history, clinical symptoms or signs, and laboratory findings on admission from electronic medical records. Radiologic assessments included chest radiography or computed tomography (CT), and all laboratory testing was performed according to the clinical care needs of the patient. We determined the presence of a radiologic abnormality on the basis of the documentation or description in medical charts; if imaging scans were available, they were reviewed by attending physicians in respiratory medicine who extracted the data. Major disagreement between two reviewers was resolved by consultation with a third reviewer. Laboratory assessments consisted of a complete blood count, blood chemical analysis, coagulation testing, assessment of liver and renal function, and measures of electrolytes, C-reactive protein, procalcitonin, lactate dehydrogenase, and creatine kinase. We defined the degree of severity of Covid-19 (severe vs. nonsevere) at the time of admission using the American Thoracic Society guidelines for community-acquired pneumonia.15

All medical records were copied and sent to the data-processing center in Guangzhou, under the coordination of the National Health Commission. A team of experienced respiratory clinicians reviewed and abstracted the data. Data were entered into a computerized database and cross-checked. If the core data were missing, requests for clarification were sent to the coordinators, who subsequently contacted the attending clinicians.

STUDY OUTCOMES

The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. These outcomes were used in a previous study to assess the severity of other serious infectious diseases, such as H7N9 infection.16 Secondary end points were the rate of death and the time from symptom onset until the composite end point and until each component of the composite end point.

STUDY DEFINITIONS

The incubation period was defined as the interval between the potential earliest date of contact of the transmission source (wildlife or person with suspected or confirmed case) and the potential earliest date of symptom onset (i.e., cough, fever, fatigue, or myalgia). We excluded incubation periods of less than 1 day because some patients had continuous exposure to contamination sources; in these cases, the latest date of exposure was recorded. The summary statistics of incubation periods were calculated on the basis of 291 patients who had clear information regarding the specific date of exposure.

Fever was defined as an axillary temperature of 37.5°C or higher. Lymphocytopenia was defined as a lymphocyte count of less than 1500 cells per cubic millimeter. Thrombocytopenia was defined as a platelet count of less than 150,000 per cubic millimeter. Additional definitions — including exposure to wildlife, acute respiratory distress syndrome (ARDS), pneumonia, acute kidney failure, acute heart failure, and rhabdomyolysis — are provided in the Supplementary Appendix, available at NEJM.org.

LABORATORY CONFIRMATION

Laboratory confirmation of SARS-CoV-2 was performed at the Chinese Center for Disease Prevention and Control before January 23, 2020, and subsequently in certified tertiary care hospitals. RT-PCR assays were performed in accordance with the protocol established by the WHO.17 Details regarding laboratory confirmation processes are provided in the Supplementary Appendix.

STATISTICAL ANALYSIS

Continuous variables were expressed as medians and interquartile ranges or simple ranges, as appropriate. Categorical variables were summarized as counts and percentages. No imputation was made for missing data. Because the cohort of patients in our study was not derived from random selection, all statistics are deemed to be descriptive only. We used ArcGIS, version 10.2.2, to plot the numbers of patients with reportedly confirmed cases on a map. All the analyses were performed with the use of R software, version 3.6.2 (R Foundation for Statistical Computing).

Results

DEMOGRAPHIC AND CLINICAL CHARACTERISTICS

Of the 7736 patients with Covid-19 who had been hospitalized at 552 sites as of January 29, 2020, we obtained data regarding clinical symptoms and outcomes for 1099 patients (14.2%). The largest number of patients (132) had been admitted to Wuhan Jinyintan Hospital. The hospitals that were included in this study accounted for 29.7% of the 1856 designated hospitals where patients with Covid-19 could be admitted in 30 provinces, autonomous regions, or municipalities across China (Figure 1).

Figure 1. Distribution of Patients with Covid-19 across Mainland China.

Shown are the official statistics of all documented, laboratory-confirmed cases of coronavirus disease 2019 (Covid-19) throughout China, according to the National Health Commission as of February 4, 2020. The numerator denotes the number of patients who were included in the study cohort and the denominator denotes the number of laboratory-confirmed cases for each province, autonomous region, or provincial municipality, as reported by the National Health Commission.

Table 1. Clinical Characteristics of the Study Patients, According to Disease Severity and the Presence or Absence of the Primary Composite End Point.

The demographic and clinical characteristics of the patients are shown in Table 1. A total of 3.5% were health care workers, and a history of contact with wildlife was documented in 1.9%; 483 patients (43.9%) were residents of Wuhan. Among the patients who lived outside Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city; 25.9% of nonresidents had neither visited the city nor had contact with Wuhan residents.

The median incubation period was 4 days (interquartile range, 2 to 7). The median age of the patients was 47 years (interquartile range, 35 to 58); 0.9% of the patients were younger than 15 years of age. A total of 41.9% were female. Fever was present in 43.8% of the patients on admission but developed in 88.7% during hospitalization. The second most common symptom was cough (67.8%); nausea or vomiting (5.0%) and diarrhea (3.8%) were uncommon. Among the overall population, 23.7% had at least one coexisting illness (e.g., hypertension and chronic obstructive pulmonary disease).

On admission, the degree of severity of Covid-19 was categorized as nonsevere in 926 patients and severe in 173 patients. Patients with severe disease were older than those with nonsevere disease by a median of 7 years. Moreover, the presence of any coexisting illness was more common among patients with severe disease than among those with nonsevere disease (38.7% vs. 21.0%). However, the exposure history between the two groups of disease severity was similar.

RADIOLOGIC AND LABORATORY FINDINGS

Table 2. Radiographic and Laboratory Findings.

Table 2 shows the radiologic and laboratory findings on admission. Of 975 CT scans that were performed at the time of admission, 86.2% revealed abnormal results. The most common patterns on chest CT were ground-glass opacity (56.4%) and bilateral patchy shadowing (51.8%). Representative radiologic findings in two patients with nonsevere Covid-19 and in another two patients with severe Covid-19 are provided in Figure S1 in the Supplementary Appendix. No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease.

On admission, lymphocytopenia was present in 83.2% of the patients, thrombocytopenia in 36.2%, and leukopenia in 33.7%. Most of the patients had elevated levels of C-reactive protein; less common were elevated levels of alanine aminotransferase, aspartate aminotransferase, creatine kinase, and d-dimer. Patients with severe disease had more prominent laboratory abnormalities (including lymphocytopenia and leukopenia) than those with nonsevere disease.

CLINICAL OUTCOMES

None of the 1099 patients were lost to follow-up during the study. A primary composite end-point event occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died (Table 3). Among the 173 patients with severe disease, a primary composite end-point event occurred in 43 patients (24.9%). Among all the patients, the cumulative risk of the composite end point was 3.6%; among those with severe disease, the cumulative risk was 20.6%.

TREATMENT AND COMPLICATIONS

A majority of the patients (58.0%) received intravenous antibiotic therapy, and 35.8% received oseltamivir therapy; oxygen therapy was administered in 41.3% and mechanical ventilation in 6.1%; higher percentages of patients with severe disease received these therapies (Table 3). Mechanical ventilation was initiated in more patients with severe disease than in those with nonsevere disease (noninvasive ventilation, 32.4% vs. 0%; invasive ventilation, 14.5% vs. 0%). Systemic glucocorticoids were given to 204 patients (18.6%), with a higher percentage among those with severe disease than nonsevere disease (44.5% vs. 13.7%). Of these 204 patients, 33 (16.2%) were admitted to the ICU, 17 (8.3%) underwent invasive ventilation, and 5 (2.5%) died. Extracorporeal membrane oxygenation was performed in 5 patients (0.5%) with severe disease.

Table 3. Complications, Treatments, and Clinical Outcomes.

The median duration of hospitalization was 12.0 days (mean, 12.8). During hospital admission, most of the patients received a diagnosis of pneumonia from a physician (91.1%), followed by ARDS (3.4%) and shock (1.1%). Patients with severe disease had a higher incidence of physician-diagnosed pneumonia than those with nonsevere disease (99.4% vs. 89.5%).

Discussion

During the initial phase of the Covid-19 outbreak, the diagnosis of the disease was complicated by the diversity in symptoms and imaging findings and in the severity of disease at the time of presentation. Fever was identified in 43.8% of the patients on presentation but developed in 88.7% after hospitalization. Severe illness occurred in 15.7% of the patients after admission to a hospital. No radiologic abnormalities were noted on initial presentation in 2.9% of the patients with severe disease and in 17.9% of those with nonsevere disease. Despite the number of deaths associated with Covid-19, SARS-CoV-2 appears to have a lower case fatality rate than either SARS-CoV or Middle East respiratory syndrome–related coronavirus (MERS-CoV). Compromised respiratory status on admission (the primary driver of disease severity) was associated with worse outcomes.

Approximately 2% of the patients had a history of direct contact with wildlife, whereas more than three quarters were either residents of Wuhan, had visited the city, or had contact with city residents. These findings echo the latest reports, including the outbreak of a family cluster,4 transmission from an asymptomatic patient,6 and the three-phase outbreak patterns.8 Our study cannot preclude the presence of patients who have been termed “super-spreaders.”

Conventional routes of transmission of SARS-CoV, MERS-CoV, and highly pathogenic influenza consist of respiratory droplets and direct contact,18-20 mechanisms that probably occur with SARS-CoV-2 as well. Because SARS-CoV-2 can be detected in the gastrointestinal tract, saliva, and urine, these routes of potential transmission need to be investigated21 (Tables S1 and S2).

The term Covid-19 has been applied to patients who have laboratory-confirmed symptomatic cases without apparent radiologic manifestations. A better understanding of the spectrum of the disease is needed, since in 8.9% of the patients, SARS-CoV-2 infection was detected before the development of viral pneumonia or viral pneumonia did not develop.

In concert with recent studies,1,8,12 we found that the clinical characteristics of Covid-19 mimic those of SARS-CoV. Fever and cough were the dominant symptoms and gastrointestinal symptoms were uncommon, which suggests a difference in viral tropism as compared with SARS-CoV, MERS-CoV, and seasonal influenza.22,23 The absence of fever in Covid-19 is more frequent than in SARS-CoV (1%) and MERS-CoV infection (2%),20 so afebrile patients may be missed if the surveillance case definition focuses on fever detection.14 Lymphocytopenia was common and, in some cases, severe, a finding that was consistent with the results of two recent reports.1,12 We found a lower case fatality rate (1.4%) than the rate that was recently reportedly,1,12 probably because of the difference in sample sizes and case inclusion criteria. Our findings were more similar to the national official statistics, which showed a rate of death of 3.2% among 51,857 cases of Covid-19 as of February 16, 2020.11,24 Since patients who were mildly ill and who did not seek medical attention were not included in our study, the case fatality rate in a real-world scenario might be even lower. Early isolation, early diagnosis, and early management might have collectively contributed to the reduction in mortality in Guangdong.

Despite the phylogenetic homogeneity between SARS-CoV-2 and SARS-CoV, there are some clinical characteristics that differentiate Covid-19 from SARS-CoV, MERS-CoV, and seasonal influenza infections. (For example, seasonal influenza has been more common in respiratory outpatient clinics and wards.) Some additional characteristics that are unique to Covid-19 are detailed in Table S3.

Our study has some notable limitations. First, some cases had incomplete documentation of the exposure history and laboratory testing, given the variation in the structure of electronic databases among different participating sites and the urgent timeline for data extraction. Some cases were diagnosed in outpatient settings where medical information was briefly documented and incomplete laboratory testing was performed, along with a shortage of infrastructure and training of medical staff in nonspecialty hospitals. Second, we could estimate the incubation period in only 291 of the study patients who had documented information. The uncertainty of the exact dates (recall bias) might have inevitably affected our assessment. Third, because many patients remained in the hospital and the outcomes were unknown at the time of data cutoff, we censored the data regarding their clinical outcomes as of the time of our analysis. Fourth, we no doubt missed patients who were asymptomatic or had mild cases and who were treated at home, so our study cohort may represent the more severe end of Covid-19. Fifth, many patients did not undergo sputum bacteriologic or fungal assessment on admission because, in some hospitals, medical resources were overwhelmed. Sixth, data generation was clinically driven and not systematic.

Covid-19 has spread rapidly since it was first identified in Wuhan and has been shown to have a wide spectrum of severity. Some patients with Covid-19 do not have fever or radiologic abnormalities on initial presentation, which has complicated the diagnosis.


Supported by the National Health Commission of China, the National Natural Science Foundation, and the Department of Science and Technology of Guangdong Province.

Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.

Drs. Guan, Ni, Yu Hu, W. Liang, Ou, He, L. Liu, Shan, Lei, Hui, Du, L. Li, Zeng, and Yuen contributed equally to this article.

This article was published on February 28, 2020, and last updated on March 6, 2020, at NEJM.org.

We thank all the hospital staff members (see Supplementary Appendix for a full list of the staff) for their efforts in collecting the information that was used in this study; Zong-jiu Zhang, Ya-hui Jiao, Xin-qiang Gao, and Tao Wei (National Health Commission), Yu-fei Duan and Zhi-ling Zhao (Health Commission of Guangdong Province), and Yi-min Li, Nuo-fu Zhang, Qing-hui Huang, Wen-xi Huang, and Ming Li (Guangzhou Institute of Respiratory Health) for facilitating the collection of patients’ data; the statistical team members Zheng Chen, Dong Han, Li Li, Zhi-ying Zhan, Jin-jian Chen, Li-jun Xu, and Xiao-han Xu (State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, and Southern Medical University, respectively); Li-qiang Wang, Wei-peng Cai, Zi-sheng Chen (the Sixth Affiliated Hospital of Guangzhou Medical University) and Chang-xing Ou, Xiao-min Peng, Si-ni Cui, Yuan Wang, Mou Zeng, Xin Hao, Qi-hua He, Jing-pei Li, Xu-kai Li, Wei Wang, Li-min Ou, Ya-lei Zhang, Jing-wei Liu, Xin-guo Xiong, Wei-juna Shi, San-mei Yu, Run-dong Qin, Si-yang Yao, Bo-meng Zhang, Xiao-hong Xie, Zhan-hong Xie, Wan-di Wang, Xiao-xian Zhang, Hui-yin Xu, Zi-qing Zhou, Ying Jiang, Ni Liu, Jing-jing Yuan, Zheng Zhu, Jie-xia Zhang, Hong-hao Li, Wei-hua Huang, Lu-lin Wang, Jie-ying Li, Li-fen Gao, Cai-chen Li, Xue-wei Chen, Jia-bo Gao, Ming-shan Xue, Shou-xie Huang, Jia-man Tang, and Wei-li Gu (Guangzhou Institute of Respiratory Health) for their dedication to data entry and verification; Tencent (Internet-services company) for providing the number of hospitals certified to admit patients with Covid-19 throughout China; and all the patients who consented to donate their data for analysis and the medical staff members who are on the front line of caring for patients.

Author Affiliations

From the State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University (W.G., W.L., J.H., R.C., C.T., T.W., S.L., Jin-lin Wang, N.Z., J.H., W.L.), the Departments of Thoracic Oncology (W.L.), Thoracic Surgery and Oncology (J.H.), and Emergency Medicine (Z.L.), First Affiliated Hospital of Guangzhou Medical University, and Guangzhou Eighth People’s Hospital, Guangzhou Medical University (C.L.), and the State Key Laboratory of Organ Failure Research, Department of Biostatistics, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University (C.O., P.C.), Guangzhou, Wuhan Jinyintan Hospital (Z.N., J.X.), Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (Yu Hu), the Central Hospital of Wuhan (Y.P.), Wuhan No. 1 Hospital, Wuhan Hospital of Traditional Chinese and Western Medicine (L.W.), Wuhan Pulmonary Hospital (P.P.), Tianyou Hospital Affiliated to Wuhan University of Science and Technology (Jian-ming Wang), and the People’s Hospital of Huangpi District (S.Z.), Wuhan, Shenzhen Third People’s Hospital and the Second Affiliated Hospital of Southern University of Science and Technology, National Clinical Research Center for Infectious Diseases (L. Liu), and the Department of Clinical Microbiology and Infection Control, University of Hong Kong–Shenzhen Hospital (K.-Y.Y.), Shenzhen, the Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai (H.S.), the Department of Medicine and Therapeutics, Chinese University of Hong Kong, Shatin (D.S.C.H.), and the Department of Microbiology and the Carol Yu Center for Infection, Li Ka Shing Faculty of Medicine, University of Hong Kong, Pok Fu Lam (K.-Y.Y.), Hong Kong, Medical ICU, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences (B.D.), and the Chinese Center for Disease Control and Prevention (G.Z.), Beijing, the State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou (L. Li), Chengdu Public Health Clinical Medical Center, Chengdu (Y.L.), Huangshi Central Hospital of Edong Healthcare Group, Affiliated Hospital of Hubei Polytechnic University, Huangshi (Ya-hua Hu), the First Hospital of Changsha, Changsha (J. Liu), the Third People’s Hospital of Hainan Province, Sanya (Z.C.), Huanggang Central Hospital, Huanggang (G.L.), Wenling First People’s Hospital, Wenling (Z.Z.), the Third People’s Hospital of Yichang, Yichang (S.Q.), Affiliated Taihe Hospital of Hubei University of Medicine, Shiyan (J. Luo), and Xiantao First People’s Hospital, Xiantao (C.Y.) — all in China.

Address reprint requests to Dr. Zhong at the State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, 151 Yanjiang Rd., Guangzhou, Guangdong, China, or at .

A list of investigators in the China Medical Treatment Expert Group for Covid-19 study is provided in the Supplementary Appendix, available at NEJM.org.

Smoking Upregulates Angiotensin-Converting Enzyme-2 Receptor: A Potential Adhesion Site for Novel Coronavirus SARS-CoV-2 (Covid-19)

Samuel James Brake (1), Kathryn Barnsley (2), Wenying Lu (1) , Kielan Darcy McAlinden (1), Mathew Suji Eapen (1) and Sukhwinder Singh Sohal (1),*

(1) Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, University of Tasmania, Launceston, Tasmania 7248, Australia; sjbrake@utas.edu.au (S.J.B.); Wenying.Lu@utas.edu.au (W.L.); kielan.mcalinden@utas.edu.au (K.D.M.); mathew.eapen@utas.edu.au (M.S.E.)
(2) School of Medicine, University of Tasmania, Hobart, Tasmania 7001, Australia;
kathryn.barnsley@utas.edu.au
* Correspondence: sssohal@utas.edu.au; Tel.: +61-424-753-373

J. Clin. Med. 20209(3), 841; https://doi.org/10.3390/jcm9030841

Received: 17 March 2020; Accepted: 18 March 2020; Published: 20 March 2020

(This article belongs to the Section Pulmonology)

Abstract

The epicenter of the original outbreak in China has high male smoking rates of around 50%, and early reported death rates have an emphasis on older males, therefore the likelihood of smokers being overrepresented in fatalities is high. In Iran, China, Italy, and South Korea, female smoking rates are much lower than males. Fewer females have contracted the virus. If this analysis is correct, then Indonesia would be expected to begin experiencing high rates of Covid-19 because its male smoking rate is over 60% (Tobacco Atlas). Smokers are vulnerable to respiratory viruses. Smoking can upregulate angiotensin-converting enzyme-2 (ACE2) receptor, the known receptor for both the severe acute respiratory syndrome (SARS)-coronavirus (SARS-CoV) and the human respiratory coronavirus NL638. This could also be true for new electronic smoking devices such as electronic cigarettes and “heat-not-burn” IQOS devices. ACE2 could be a novel adhesion molecule for SARS-CoV-2 causing Covid-19 and a potential therapeutic target for the prevention of fatal microbial infections, and therefore it should be fast tracked and prioritized for research and investigation. Data on smoking status should be collected on all identified cases of Covid-19.
Little attention has been given to the role of smoking in either the transmission of the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, actual virus) or mortality rate of Covid-19 (name of the disease caused). Smokers contract more respiratory ailments, including colds (commonly rhinoviruses, but also coronaviruses) than non-smokers. Smokers also show double the influenza rate and increased rates of bacterial pneumonia and tuberculosis [1,2,3,4,5]. The damage caused to the lungs by smoking makes patients more susceptible to pulmonary infections, both bacterial and viral [6]. Smokers are 34% more likely than non-smokers to contract the flu [6]. Han and colleagues conclude that literature evidence showed that smoking was consistently associated with a higher risk of hospital admissions after influenza infection [7]. Smoking is the primary etiological factor behind chronic obstructive pulmonary disease (COPD) in the developed world, but environmental pollution and degrading air quality are also responsible in developing countries. It is now the fourth leading cause of death in the world [8]. Vaccination against influenza is strongly recommended for patients with COPD, as the frequency and progression of exacerbations are strongly linked to respiratory viruses in 30% of cases [1]. Rubin et al. found that COPD patients who were prone to viral infections had higher exacerbation rates, more inflammation, and loss of lung function compared to those with existing exacerbating disease conditions [9]. Symptomatology and mortality in influenza-infected smokers were also enhanced [9]. According to the WHO, comorbidities are associated with a high percentage of Covid-19 related deaths [10,11]. In conjunction with the complications arising from comorbidities in patients who smoke [12], we put forth the question of whether smoking, smoking-induced health conditions, and comorbidities, in combination, is culminating in a high risk demographic for both contraction of the virus and the severe presentation of Covid-19.
China has a high male smoking rate at around 50% in rural areas and is estimated to be about 44.8% overall [13]. Most of the deaths identified from the epicenter of the Covid-19 outbreak were in men from older age groups and those with underlying conditions such as chronic respiratory disease, cancer, hypertension, diabetes, or cardiovascular disease. The initial age distribution of Covid-19 cases was skewed towards older age groups with a median age of 45 years (IQR 33–56) for patients who were alive or who had an unknown outcome at the time of reporting. The median age of patients who had died at the time of reporting was 70 years (IQR 65–81) as reported by Sun and colleagues [14]. This data was also supported by an early epidemiological study of 99 Covid-19 cases from Wuhan, China [14].
Fatality rates are given as the percentage of the defined group with confirmed Covid-19 that died, and therefore will not add up to 100%. The Table 1 was adapted from Coronavirus Disease (Covid-19) Research and Statistics [15].
Table 1. Risk factor-based fatality rates of Covid-19 from early data in China.
Age group Fatality rates
0–9 years 0%
10–19 years 0.2%
20–29 years 0.2%
30–39 years 0.2%
40 – 49 years 0.4%
50–59 years 1.3%
60–69 years 3.6%
70–79 years 8%
80 years and above 14.8%
Underlying health conditions
Cardiovascular disease 10.5%
Diabetes 7.3%
Chronic respiratory disease 6.3%
Hypertension 6%
Cancer 5.6%
No underlying health conditions 0.9%

 

The term “coronaviruses” arose from their crown-like appearance when imaged, the Latin for crown being corona. The distinguishing crown-like feature of coronaviruses is attributed to the presence of large type 1 transmembrane spike (S) glycoproteins. This heavily glycosylated cell surface protein contains two distinct functional domains (S1 and S2) which are thought to mediate host cell entry by the virus. The S1 domain contains the angiotensin-converting enzyme-2 (ACE2) receptor-binding domain and is responsible for first stage host cell entry [16]. The S2 domain facilitates fusion between cell and virus membrane, required for cellular infiltration [17]. S proteins are enzymatically modified, exposing the fusion site for cellular adhesion. This is achieved through cleavage by cellular proteases, mediated by protein convertase called “furin” [17,18]. Furin is expressed significantly in the lungs, and respiratory viruses also utilize this system to convert their surface proteins [17]. Although the S protein cleavage site is less observed in coronavirus with similar genomic sequence [17], it is essential to note that more pathogenic influenza viruses share similar cleavage sites [19].
The ACE2 receptor provides a human cell-binding site for the S protein for the SARS-coronavirus (SARS-CoV) [20,21,22] (a virus that was first identified in 2003 in a southern province of China [23,24,25]), the coronavirus NL63 [20,26], and now SARS-CoV-2 [27]. Recent studies have found that the modified S protein of SARS-CoV-2 has a significantly higher affinity for ACE2 and is 10- to 20-fold more likely to bind to ACE2 in human cells than the S protein of the previous SARS-CoV [28,29]. This increase in affinity may enable easier person-to-person spread of the virus and thus contribute to a higher estimated R0 for SARS-CoV-2 than the previous SARS virus. The ACE2 protein is expressed on the surface of lung type-2 pneumocytes [30]. It could thus act as a novel adhesion molecule for Covid-19 and be a potential therapeutic target for the prevention of fatal microbial infections in the community.
An early suggestion is that ACE2 is upregulated on the airway epithelium of smokers. Guoshuai Cai recently reported higher ACE2 gene expression in smoker samples compared to never-smokers. Zhao et al. observed that ACE2 is expressed explicitly in type-2 pneumocytes, in which genes regulating viral reproduction and transmission are highly expressed [31]. This indicates that smokers may be more susceptible to infection by SARS-CoV-2, and possibly Covid-19. We recently identified enhanced ACE2 expression in resected lung tissue from patients with COPD and healthy lung function smokers, albeit comparably less in the latter, while entirely absent in heathy non-smoking individuals (Figure 1). ACE2 expression was quite evident in the type-2 pneumocytes, alveolar macrophages, and the apical end of the small airway epithelium. COPD patients showed significantly higher levels of ACE2, suggesting that COPD further exaggerates ACE2 and potential SARS-CoV-2 adhesion site. ACE2 expression could also be true for patients with another chronic lung disease such as idiopathic pulmonary fibrosis [32]. The attachment of the virus to cell surface ACE2 protects them from immune surveillance mechanisms, leaving them tagged to the host for relatively longer periods, thus making them an efficient carrier and vulnerable host for future infections and spread. The eventual engulfment of ACE2 further provides the virus access to the host cells system, thus providing a flourishing environment, not just to sustain and proliferate but also to mutate and modify host evasion mechanisms. Previous observations using in vivo knockout mice models suggest that SARS-CoV-2 adhesion on ACE2 could also downmodulate the expression of ACE2 itself. This, in turn, increases the production and activation of other related ACE enzymes. This differential modulation and the drastic reduction in ACE2 results in severe acute respiratory failure [33,34].
Jcm 09 00841 g001 550
Figure 1. Surgically resected lung tissue stained for the angiotensin-converting enzyme-2 (ACE2) receptor. Current smoker with chronic obstructive pulmonary disease (COPD-CS), (A) showing positive staining in the small airway epithelium but also apical including cilia (B) red arrows indicating positive staining in type-2 pneumocytes and black arrows showing alveolar macrophages positive for the ACE2 receptor. Normal lung function smoker (NLFS), (C) and (D) showing similar pattern for COPD-CS although a little less staining is observed. Normal controls (NC), (E) and (F) no staining observed in any of the areas. This is the first immunohistochemical human lung evidence for ACE2 receptor expression in smokers and patients with COPD.
Wang et al. also noted an ACE2 connection to smoking and Covid-19 [35]. The increases seen in smokers further raises the question of whether this is also true for people engaged in waterpipe smoking [36] and those switching over to the more recent alternatives such as electronic cigarettes and “heat-not-burn” IQOS devices. It is essential to recognize that these devices are not “safer”, they are still a tobacco product that produces vapor or smoke and similarly could cause infectious lung damage as we see with traditional cigarettes [37,38,39].
Further research on these products and their influence on the virulence of coronaviruses is urgently needed. Following the outbreak in New York City, Mayor Bill de Blasio announced that “If you are a smoker or a vaper that does make you more vulnerable,” urging that now is the perfect time to quit [40]. Smokers, as a vulnerable group, must be supported to quit and should be advised to avoid areas where they may be liable to be exposed to Covid-19, especially smokers with pre-existing respiratory health concerns. Smokers should be prioritized for vaccination when a vaccine is developed, particularly if it is found they are a key transmission source.
Research on smoking and potential exacerbations of Covid-19 transmission and mortality should include waterpipes, electronic smoking devices, and “heat-not-burn” devices, such as IQOS devices. Further compounding this link between smoking and Covid-19 vulnerability are the comorbidities that have been identified as a significant increased risk factor for severe and fatal Covid-19. The link between smoking and comorbidities, such as diabetes and cardiovascular disease, have long been established [12]. As a research community, we must ask the questions:
(1) Are COPD and other smoking-related illnesses associated with fatal Covid-19 cases?
(2) Are smokers more likely to contract and transmit SARS-CoV-2 than non-smokers?
(3) Are demographics with high smoking rates more vulnerable to Covid-19 outbreaks?
WHO and all countries should ensure that the smoking status of patients identified with Covid-19, including deaths, is recorded and incorporated in data sets, so the smoker’s relationship to Covid-19 can be determined.
Status data collection could be simple in four categories,
1. active smoker,
2. passive smoker (those living in households with smokers or working in smoky environments),
3. former smoker (12 months or longer abstinence),
4. non-smoker.
Governments should act to reduce smoking rates in all countries in accordance with the WHO Framework Convention on Tobacco Control (FCTC), and initiate a stimulus package for health, as they have done for business, at the time of this outbreak/pandemic including all communicable pulmonary diseases and Covid-19, as it is possible that smoking exacerbates contraction, transmission, and mortality. It appears that smoking has the potential to upregulate the ACE2 receptor, making smokers and COPD patients more vulnerable to Covid-19. The new electronic smoking devices also do not seem to be safer options. ACE2 thus could be a potential therapeutic target for SARS-CoV-2 and should be prioritized for further research.

Author Contributions

All authors contributed towards the writing of the manuscript. All authors have read and agreed to the published version of the manuscript.

Acknowledgments

Clifford Craig Foundation Launceston General Hospital, Rebecca L. Cooper Medical Research Foundation, Cancer Council Tasmania.

Conflicts of Interest

The authors declare no conflict of interest.

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