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      A population-based study on mortality among Belgian immigrants during the first COVID-19 wave in Belgium. Can demographic and socioeconomic indicators explain differential mortality?

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          Abstract

          Introduction

          Belgium has noted a significant excess mortality during the first COVID-19 wave. Research in other countries has shown that people with migrant origin are disproportionally affected. Belgium has an ethnically diverse and increasingly ageing population and is therefore particularly apt to study differential mortality by migrant group during this first wave of COVID-19.

          Data and methods

          We used nationwide individually-linked data from the Belgian National Register providing sociodemographic indicators and mortality; and the administrative census of 2011 providing indicators of socioeconomic position. Age-standardized all-cause mortality rates (ASMRs) were calculated during the first COVID-19 wave (weeks 11–20 in 2020) and compared with ASMRs during weeks 11–20 in 2019 to calculate excess mortality by migrant origin, age and gender. For both years, relative inequalities were calculated by migrant group using Poisson regression, with and without adjustment for sociodemographic and socioeconomic indicators.

          Results

          Among the middle-aged, ASMRs revealed increased mortality in all origin groups, with significant excess mortality for Belgians and Sub-Saharan African men. At old age, excess mortality up to 60% was observed for all groups. In relative terms, most male elderly migrant groups showed higher mortality than natives, as opposed to 2019 and to women. Adding the control variables decreased this excess mortality.

          Discussion

          This study underlined important inequalities in overall and excess mortality in specific migrant communities, especially in men. Tailor-made policy measures and communication strategies should be set-up taking into account the particular risks to which groups are exposed.

          Highlights

          • We observed significant excess mortality during the first COVID-19 wave for middle-aged Belgians and Sub-Saharan African men.

          • At old age, excess mortality up to 60% was consistently observed across all origin groups.

          • In relative terms, especially migrant men were worse off during the first COVID-19 wave as in comparison with 2019.

          • Sociodemographic and socioeconomic factors explained some of the mortality disadvantage among migrants.

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          Most cited references33

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            OpenSAFELY: factors associated with COVID-19 death in 17 million patients

            COVID-19 has rapidly impacted on mortality worldwide. 1 There is unprecedented urgency to understand who is most at risk of severe outcomes, requiring new approaches for timely analysis of large datasets. Working on behalf of NHS England we created OpenSAFELY: a secure health analytics platform covering 40% of all patients in England, holding patient data within the existing data centre of a major primary care electronic health records vendor. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19 related deaths. COVID-19 related death was associated with: being male (hazard ratio 1.59, 95%CI 1.53-1.65); older age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared to people with white ethnicity, black and South Asian people were at higher risk even after adjustment for other factors (HR 1.48, 1.29-1.69 and 1.45, 1.32-1.58 respectively). We have quantified a range of clinical risk factors for COVID-19 related death in the largest cohort study conducted by any country to date. OpenSAFELY is rapidly adding further patients’ records; we will update and extend results regularly.
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              COVID-19 and Racial/Ethnic Disparities

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                Author and article information

                Contributors
                Journal
                SSM Popul Health
                SSM Popul Health
                SSM - Population Health
                Elsevier
                2352-8273
                16 April 2021
                June 2021
                16 April 2021
                : 14
                : 100797
                Affiliations
                [a ]Sociology Department, Interface Demography, Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussels, Belgium
                [b ]Statbel, Directorate General Statistics - Statistics Belgium, North Gate - Boulevard du Roi Albert II, 16 - 1000, Brussels, Belgium
                Author notes
                []Corresponding author. Katrien.Vanthomme@ 123456vub.be
                Article
                S2352-8273(21)00072-0 100797
                10.1016/j.ssmph.2021.100797
                8093459
                33997246
                5c54fdcc-f71b-41fd-b550-4e6184fabe23
                © 2021 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 13 January 2021
                : 6 April 2021
                : 7 April 2021
                Categories
                Article

                belgium,immigrants,covid-19,mortality,inequalities
                belgium, immigrants, covid-19, mortality, inequalities

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