10
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Factors determining different death rates because of the COVID-19 outbreak among countries

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          During the coronavirus disease 2019 (COVID-19) pandemic, all European countries were hit, but mortality rates were heterogenous. The aim of the current paper was to identify factors responsible for this heterogeneity.

          Methods

          Data concerning 40 countries were gathered, concerning demographics, vulnerability factors and characteristics of the national response. These variables were tested against the rate of deaths per million in each country. The statistical analysis included Person correlation coefficient and Forward Stepwise Linear Regression Analysis (FSLRA).

          Results

          The FSLRA results suggested that ‘days since first national death for the implementation of ban of all public events’ was the only variable significantly contributing to the final model, explaining 44% of observed variability.

          Discussion

          The current study suggests that the crucial factor for the different death rates because of COVID-19 outbreak was the fast implementation of public events ban. This does not necessarily mean that the other measures were useless, especially since most countries implemented all of them as a ‘package’. However, it does imply that this is a possibility and focused research is needed to clarify it, and is in accord with a model of spreading where only a few superspreaders infect large numbers through prolonged exposure.

          Related collections

          Most cited references7

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          COVID-19 and smoking: A systematic review of the evidence

          COVID-19 is a coronavirus outbreak that initially appeared in Wuhan, Hubei Province, China, in December 2019, but it has already evolved into a pandemic spreading rapidly worldwide 1,2 . As of 18 March 2020, a total number of 194909 cases of COVID-19 have been reported, including 7876 deaths, the majority of which have been reported in China (3242) and Italy (2505) 3 . However, as the pandemic is still unfortunately under progression, there are limited data with regard to the clinical characteristics of the patients as well as to their prognostic factors 4 . Smoking, to date, has been assumed to be possibly associated with adverse disease prognosis, as extensive evidence has highlighted the negative impact of tobacco use on lung health and its causal association with a plethora of respiratory diseases 5 . Smoking is also detrimental to the immune system and its responsiveness to infections, making smokers more vulnerable to infectious diseases 6 . Previous studies have shown that smokers are twice more likely than non-smokers to contract influenza and have more severe symptoms, while smokers were also noted to have higher mortality in the previous MERS-CoV outbreak 7,8 . Given the gap in the evidence, we conducted a systematic review of studies on COVID-19 that included information on patients’ smoking status to evaluate the association between smoking and COVID-19 outcomes including the severity of the disease, the need for mechanical ventilation, the need for intensive care unit (ICU) hospitalization and death. The literature search was conducted on 17 March 2020, using two databases (PubMed, ScienceDirect), with the search terms: [‘smoking’ OR ‘tobacco’ OR ‘risk factors’ OR ‘smoker*’] AND [‘COVID-19’ OR ‘COVID 19’ OR ‘novel coronavirus’ OR ‘sars cov-2’ OR ‘sars cov 2’] and included studies published in 2019 and 2020. Further inclusion criteria were that the studies were in English and referred to humans. We also searched the reference lists of the studies included. A total of 71 studies were retrieved through the search, of which 66 were excluded after full-text screening, leaving five studies that were included. All of the studies were conducted in China, four in Wuhan and one across provinces in mainland China. The populations in all studies were patients with COVID-19, and the sample size ranged from 41 to 1099 patients. With regard to the study design, retrospective and prospective methods were used, and the timeframe of all five studies covered the first two months of the COVID-19 pandemic (December 2019, January 2020). Specifically, Zhou et al. 9 studied the epidemiological characteristics of 191 individuals infected with COVID-19, without, however, reporting in more detail the mortality risk factors and the clinical outcomes of the disease. Among the 191 patients, there were 54 deaths, while 137 survived. Among those that died, 9% were current smokers compared to 4% among those that survived, with no statistically significant difference between the smoking rates of survivors and non-survivors (p=0.21) with regard to mortality from COVID-19. Similarly, Zhang et al. 10 presented clinical characteristics of 140 patients with COVID-19. The results showed that among severe patients (n=58), 3.4% were current smokers and 6.9% were former smokers, in contrast to non-severe patients (n=82) among which 0% were current smokers and 3.7% were former smokers , leading to an OR of 2.23; (95% CI: 0.65–7.63; p=0.2). Huang et al. 11 studied the epidemiological characteristics of COVID-19 among 41 patients. In this study, none of those who needed to be admitted to an ICU (n=13) was a current smoker. In contrast, three patients from the non-ICU group were current smokers, with no statistically significant difference between the two groups of patients (p=0.31), albeit the small sample size of the study. The largest study population of 1099 patients with COVID-19 was provided by Guan et al. 12 from multiple regions of mainland China. Descriptive results on the smoking status of patients were provided for the 1099 patients, of which 173 had severe symptoms, and 926 had non-severe symptoms. Among the patients with severe symptoms, 16.9% were current smokers and 5.2% were former smokers, in contrast to patients with non-severe symptoms where 11.8% were current smokers and 1.3% were former smokers. Additionally, in the group of patients that either needed mechanical ventilation, admission to an ICU or died, 25.5% were current smokers and 7.6% were former smokers. In contrast, in the group of patients that did not have these adverse outcomes, only 11.8% were current smokers and 1.6% were former smokers. No statistical analysis for evaluating the association between the severity of the disease outcome and smoking status was conducted in that study. Finally, Liu et al. 13 found among their population of 78 patients with COVID-19 that the adverse outcome group had a significantly higher proportion of patients with a history of smoking (27.3%) than the group that showed improvement or stabilization (3.0%), with this difference statistically significant at the p=0.018 level. In their multivariate logistic regression analysis, the history of smoking was a risk factor of disease progression (OR=14.28; 95% CI: 1.58–25.00; p= 0.018). We identified five studies that reported data on the smoking status of patients infected with COVID-19. Notably, in the largest study that assessed severity, there were higher percentages of current and former smokers among patients that needed ICU support, mechanical ventilation or who had died, and a higher percentage of smokers among the severe cases 12 . However, from their published data we can calculate that the smokers were 1.4 times more likely (RR=1.4, 95% CI: 0.98–2.00) to have severe symptoms of COVID-19 and approximately 2.4 times more likely to be admitted to an ICU, need mechanical ventilation or die compared to non-smokers (RR=2.4, 95% CI: 1.43–4.04). In conclusion, although further research is warranted as the weight of the evidence increases, with the limited available data, and although the above results are unadjusted for other factors that may impact disease progression, smoking is most likely associated with the negative progression and adverse outcomes of COVID-19. Table 1 Overview of the five studies included in the systematic review Title Setting Population Study design and time horizon Outcomes Smoking rates by outcome Zhou et al. 9 (2020)Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study Jinyintan Hospital and Wuhan Pulmonary Hospital, Wuhan, China All adult inpatients (aged ≥18 years) with laboratory confirmed COVID-19 (191 patients) Retrospective multicenter cohort study until 31 January 2020 Mortality 54 patients died during hospitalisation and 137 were discharged Current smokers: n=11 (6%)Non-survivors: n=5 (9%)Survivors: n=6 (4%)(p=0.20) Current smoker vs non-smokerUnivariate logistic regression(OR=2.23; 95% CI: 0.65–7.63; p=0.2) Zhang et al. 10 (2020)Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China No. 7 Hospital of Wuhan, China All hospitalised patients clinically diagnosed as ‘viral pneumonia’ based on their clinical symptoms with typical changes in chest radiology (140 patients) Retrospective 16 January to 3 February 2020 Disease Severity Non-severepatients: n=82Severe patients:n=58 Disease Severity Former smokers: n=7Severe: n=4 (6.9%)Non-severe: n=3 (3.7%) (p= 0.448) Current smokers: n=2Severe: n=2 (3.4%)Non-severe: n=0 (0%) Guan et al. 12 (2019)Clinical Characteristics of Coronavirus Disease 2019 in China 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China Patients with laboratory-confirmed COVID-19 (1099 patients) Retrospective until 29 January 2020 Severity and admission to an ICU, the use of mechanical ventilation, or death Non-severe patients: n=926 Severe patients: n=173 By severity Severe cases16.9% current smokers5.2% former smokers77.9% never smokers Non-severe cases11.8% current smokers1.3% former smokers86.9% never smokers By mechanical ventilation, ICU or death Needed mechanical ventilation, ICU or died25.8% current smokers7.6% former smokers66.7% non-smokers No mechanical ventilation, ICU or death11.8% current smokers1.6% former smokers86.7% never smokers Huang et al. 11 (2020)Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China A hospital in Wuhan, China Laboratory-confirmed 2019-nCoV patients in Wuhan (41 patients) Prospective from 16 December 2019 to 2 January 2020 Mortality As of 22 January 2020, 28 (68%) of 41 patients were discharged and 6 (15%) patients died Current smokers: n=3ICU care: n=0Non-ICU care: n=3 (11%) Current smokers in ICU care vs non-ICU care patients (p=0.31) Liu et al. 13 (2019)Analysis of factors associated with disease outcomes in hospitalised patients with 2019 novel coronavirus disease Three tertiary hospitals in Wuhan, China Patients tested positive for COVID-19 (78 patients) Retrospective multicentre cohort study from 30 December 2019 to 15 January 2020 Disease progression 11 patients (14.1%) in the progression group 67 patients (85.9%) in the improvement/stabilization group 2 deaths Negative progression group: 27.3% smokersIn the improvement group: 3% smokers The negative progression group had a significantly higher proportion of patients with a history of smoking than the improvement/stabilisation group (27.3% vs 3.0%)Multivariate logistic regression analysis indicated that the history of smoking was a risk factor of disease progression (OR=14.28; 95% CI: 1.58–25.00; p= 0.018)
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Why inequality could spread COVID-19

            Pandemics rarely affect all people in a uniform way. The Black Death in the 14th century reduced the global population by a third, with the highest number of deaths observed among the poorest populations. 1 Densely populated with malnourished and overworked peasants, medieval Europe was a fertile breeding ground for the bubonic plague. Seven centuries on—with a global gross domestic product of almost US$100 trillion—is our world adequately resourced to prevent another pandemic? 2 Current evidence from the coronavirus disease 2019 (COVID-19) pandemic would suggest otherwise. Estimates indicate that COVID-19 could cost the world more than $10 trillion, 3 although considerable uncertainty exists with regard to the reach of the virus and the efficacy of the policy response. For each percentage point reduction in the global economy, more than 10 million people are plunged into poverty worldwide. 3 Considering that the poorest populations are more likely to have chronic conditions, this puts them at higher risk of COVID-19-associated mortality. Since the pandemic has perpetuated an economic crisis, unemployment rates will rise substantially and weakened welfare safety nets further threaten health and social insecurity. Working should never come at the expense of an individual's health nor to public health. In the USA, instances of unexpected medical billings for uninsured patients treated for COVID-19 and carriers continuing to work for fear of redundancy have already been documented. 4 Despite employment safeguards recently being passed into law in some high-income countries, such as the UK and the USA, low-income groups are wary of these assurances since they have experience of long-standing difficulties navigating complex benefits systems, 4 and many workers (including the self-employed) can be omitted from such contingency plans. The implications of inadequate financial protections for low-wage workers are more evident in countries with higher levels of extreme poverty, such as India. In recent pandemics, such as the Middle East respiratory syndrome, doctors were vectors of disease transmission due to inadequate testing and personal protective equipment. 5 History seems to be repeating itself, with clinicians comprising more than a tenth of all COVID-19 cases in Spain and Italy. With a projected global shortage of 15 million health-care workers by 2030, governments have left essential personnel exposed in this time of need. Poor populations lacking access to health services in normal circumstances are left most vulnerable during times of crisis. Misinformation and miscommunication disproportionally affect individuals with less access to information channels, who are thus more likely to ignore government health warnings. 6 With the introduction of physical distancing measures, household internet coverage should be made ubiquitous. The inequitable response to COVID-19 is already evident. Healthy life expectancy and mortality rates have historically been markedly disproportionate between the richest and poorest populations. The full effects of COVID-19 are yet to be seen, while the disease begins to spread across the most fragile settings, including conflict zones, prisons, and refugee camps. As the global economy plunges deeper into an economic crisis and government bailout programmes continue to prioritise industry, scarce resources and funding allocation decisions must aim to reduce inequities rather than exacerbate them.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              COVID-19 and the impact of social determinants of health

              The novel coronavirus disease 2019 (COVID-19), caused by the pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), originated in Wuhan, China, and has now spread internationally with over 4·3 million individuals infected and over 297 000 deaths as of May 14, 2020, according to the Johns Hopkins Coronavirus Resource Center. While COVID-19 has been termed a great equaliser, necessitating physical distancing measures across the globe, it is increasingly demonstrable that social inequalities in health are profoundly, and unevenly, impacting COVID-19 morbidity and mortality. Many social determinants of health—including poverty, physical environment (eg, smoke exposure, homelessness), and race or ethnicity—can have a considerable effect on COVID-19 outcomes. Homeless families are at higher risk of viral transmission because of crowded living spaces and scarce access to COVID-19 screening and testing facilities. 1 In a Boston study of 408 individuals residing in a shelter, 147 (36%) had a positive SARS-CoV-2 PCR test. 2 Smoke exposure and smoking has been linked to adverse outcomes in COVID-19. 3 A systematic review found that current or former smokers were more likely to have severe COVID-19 symptoms than non-smokers (relative risk [RR] 1·4 [95% CI 0·98–2·00]) as well as an increased risk of intensive care unit (ICU) admission, mechanical ventilation, or COVID-19-related mortality (RR 2·4, 1·43–4·04). 3 In the USA, the COVID-19 infection rate is three times higher in predominantly black counties than in predominantly white counties, and the mortality rate is six times higher. 4 In Chicago alone, over 50% of COVID-19 cases and almost 70% of COVID-19 fatalities are disproportionately within the black population, who make up only 30% of the overall Chicago population. 4 It is also poignant that physical distancing measures, which are necessary to prevent the spread of COVID-19, are substantially more difficult for those with adverse social determinants and might contribute to both short-term and long-term morbidity. School closures increase food insecurity for children living in poverty who participate in school lunch programmes. Malnutrition causes substantial risk to both the physical and mental health of these children, including lowering immune response, which has the potential to increase the risk of infectious disease transmission. 5 People or families who are homeless are at higher risk of infection during physical lockdowns especially if public spaces are closed, resulting in physical crowding that is thought to increase viral transmission and reduce access to care. 1 Being able to physically distance has been dubbed an issue of privilege that is simply not accessible in some communities. 4 The association of social inequalities and COVID-19 morbidity is further compounded in the context of underlying chronic respiratory conditions, such as asthma, where there is a possible additive, or even multiplicative, effect on COVID-19 morbidity. Several adverse social determinants that impact the risk of COVID-19 morbidity also increase asthma morbidity, including poverty, smoke exposure, and race or ethnicity. 6 Consistent associations have been noted between poverty, smoke exposure, and non-Hispanic black race and measures of asthma morbidity, including poorer asthma control and increased emergency department visits for asthma. 6 The interplay of social determinants, asthma, and COVID-19 might help explain the risk of COVID-19 morbidity imposed by asthma, such as the disproportionate hospitalisations for COVID-19 among adults with asthma living in the USA. 7 The CDC note asthma to be a risk factor for COVID-19 morbidity. 8 Data released from the CDC on hospitalisations in the USA in the month of March, 2020, notes that 12 (27%) of 44 patients aged 18–49 years who were hospitalised with COVID-19 had a history of asthma, 8 in those aged 50–64 years, asthma was present in 7 (13%) of 53 cases, and in those 65 years or older asthma was present in 8 (13%) of 62 cases. 8 The effect of social determinants of health and COVID-19 morbidity is perhaps underappreciated. 6 Yet, the great public health lesson is that for centuries pandemics disproportionately affect the poor and disadvantaged. 9 Additionally, mitigating social determinants—such as improved housing, reduced overcrowding, and improved nutrition—reduces the effect of infectious diseases, such as tuberculosis, even before the advent of effective medications. 10 It is projected that recurrent wintertime outbreaks of SARS-CoV-2 will likely occur after this initial wave, necessitating ongoing planning over the next few years. Studies are required to measure the effect of COVID-19 on individuals with adverse social determinants and innovative approaches to management are required, and might be different from those of the broader population. The effect of physical distancing measures, particularly among individuals with chronic conditions facing adverse social circumstances, needs to be studied because adverse determinants and physical distancing measures could compound issues, such as asthma medication access and broader access to care. The long-term effect of school closures, among those facing adverse social circumstances, is also in need of study. Moving forward, as the lessons of COVID-19 are considered, social determinants of health must be included as part of pandemic research priorities, public health goals, and policy implementation. While the relationships between these variables needs elucidating, measures that affect adverse determinants, such as reducing smoke exposure, regular income support to low-income households, access to testing and shelter among the homeless, and improving health-care access in low-income neighbourhoods have the potential to dramatically reduce future pandemic morbidity and mortality, perhaps even more so among individuals with respiratory conditions such as asthma. 7 More broadly, the effects of COVID-19 have shed light on the broad disparities within our society and provides an opportunity to address those disparities moving forward. 6 © 2020 Jim West/Science Photo Library 2020 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
                Bookmark

                Author and article information

                Journal
                J Public Health (Oxf)
                J Public Health (Oxf)
                pubmed
                Journal of Public Health (Oxford, England)
                Oxford University Press
                1741-3842
                1741-3850
                30 July 2020
                : fdaa119
                Affiliations
                [1 ]Third Department of Psychiatry, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki , Thessaloniki, Greece
                [2 ] Faculty of Medicine , Medical University of Sofia , Sofia, Bulgaria
                [3 ] Social Cooperative (KoiSPE) “Athina Elpis” , 8th Athens Mental Health Sector, Panhellenic Federation of Social Cooperatives (POKoiSPE), Athens, Greece
                [4 ] Department of Nursing , University of Peloponnese , Laboratory of Integrated Health Care, Tripoli, Greece
                Author notes
                Address correspondence to Konstantinos N. Fountoulakis, E-mail: kfount@ 123456med.auth.gr , Kostasfountoulakis@ 123456gmail.com
                Article
                fdaa119
                10.1093/pubmed/fdaa119
                7454744
                32728758
                dfd70f5b-99cd-4b2d-aa8e-39ca2a8848d9
                © The Author(s) 2020. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

                This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

                This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.

                History
                : 23 June 2020
                : 25 June 2020
                : 27 June 2020
                Page count
                Pages: 7
                Categories
                AcademicSubjects/MED00860
                Original Article
                Custom metadata
                PAP

                Public health
                covid-19,death rate,measures,public events ban
                Public health
                covid-19, death rate, measures, public events ban

                Comments

                Comment on this article