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      Covid-19 deaths in Africa: prospective systematic postmortem surveillance study

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          Abstract

          Objective

          To directly measure the fatal impact of coronavirus disease 2019 (covid-19) in an urban African population.

          Design

          Prospective systematic postmortem surveillance study.

          Setting

          Zambia’s largest tertiary care referral hospital.

          Participants

          Deceased people of all ages at the University Teaching Hospital morgue in Lusaka, Zambia, enrolled within 48 hours of death.

          Main outcome measure

          Postmortem nasopharyngeal swabs were tested via reverse transcriptase quantitative polymerase chain reaction (PCR) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Deaths were stratified by covis-19 status, location, age, sex, and underlying risk factors.

          Results

          372 participants were enrolled between June and September 2020; PCR results were available for 364 (97.8%). SARS-CoV-2 was detected in 58/364 (15.9%) according to the recommended cycle threshold value of <40 and in 70/364 (19.2%) when expanded to any level of PCR detection. The median age at death among people with a positive test for SARS-CoV-2 was 48 (interquartile range 36-72) years, and 69% (n=48) were male. Most deaths in people with covid-19 (51/70; 73%) occurred in the community; none had been tested for SARS-CoV-2 before death. Among the 19/70 people who died in hospital, six were tested before death. Among the 52/70 people with data on symptoms, 44/52 had typical symptoms of covid-19 (cough, fever, shortness of breath), of whom only five were tested before death. Covid-19 was identified in seven children, only one of whom had been tested before death. The proportion of deaths with covid-19 increased with age, but 76% (n=53) of people who died were aged under 60 years. The five most common comorbidities among people who died with covid-19 were tuberculosis (22; 31%), hypertension (19; 27%), HIV/AIDS (16; 23%), alcohol misuse (12; 17%), and diabetes (9; 13%).

          Conclusions

          Contrary to expectations, deaths with covid-19 were common in Lusaka. Most occurred in the community, where testing capacity is lacking. However, few people who died at facilities were tested, despite presenting with typical symptoms of covid-19. Therefore, cases of covid-19 were under-reported because testing was rarely done not because covid-19 was rare. If these data are generalizable, the impact of covid-19 in Africa has been vastly underestimated.

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          Most cited references31

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          Covid-19 in Critically Ill Patients in the Seattle Region — Case Series

          Abstract Background Community transmission of coronavirus 2019 (Covid-19) was detected in the state of Washington in February 2020. Methods We identified patients from nine Seattle-area hospitals who were admitted to the intensive care unit (ICU) with confirmed infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Clinical data were obtained through review of medical records. The data reported here are those available through March 23, 2020. Each patient had at least 14 days of follow-up. Results We identified 24 patients with confirmed Covid-19. The mean (±SD) age of the patients was 64±18 years, 63% were men, and symptoms began 7±4 days before admission. The most common symptoms were cough and shortness of breath; 50% of patients had fever on admission, and 58% had diabetes mellitus. All the patients were admitted for hypoxemic respiratory failure; 75% (18 patients) needed mechanical ventilation. Most of the patients (17) also had hypotension and needed vasopressors. No patient tested positive for influenza A, influenza B, or other respiratory viruses. Half the patients (12) died between ICU day 1 and day 18, including 4 patients who had a do-not-resuscitate order on admission. Of the 12 surviving patients, 5 were discharged home, 4 were discharged from the ICU but remained in the hospital, and 3 continued to receive mechanical ventilation in the ICU. Conclusions During the first 3 weeks of the Covid-19 outbreak in the Seattle area, the most common reasons for admission to the ICU were hypoxemic respiratory failure leading to mechanical ventilation, hypotension requiring vasopressor treatment, or both. Mortality among these critically ill patients was high. (Funded by the National Institutes of Health.)
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            Is Open Access

            Viral epitope profiling of COVID-19 patients reveals cross-reactivity and correlates of severity

            Profiling coronaviruses Among the coronaviruses that infect humans, four cause mild common colds, whereas three others, including the currently circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), result in severe infections. Shrock et al. used a technology known as VirScan to probe the antibody repertoires of hundreds of coronavirus disease 2019 (COVID-19) patients and pre–COVID-19 era controls. They identified hundreds of antibody targets, including several antibody epitopes shared by the mild and severe coronaviruses and many specific to SARS-CoV-2. A machine-learning model accurately classified patients infected with SARS-CoV-2 and guided the design of an assay for rapid SARS-CoV-2 antibody detection. The study also looked at how the antibody response and viral exposure history differ in patients with diverging outcomes, which could inform the production of improved vaccine and antibody therapies. Science, this issue p. eabd4250
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              Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study

              Summary Background The coronavirus disease 2019 (COVID-19) epidemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in Wuhan city, Hubei province, in December, 2019, and has spread throughout China. Understanding the evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy. Methods We collected individual information from official public sources on laboratory-confirmed cases reported outside Hubei in mainland China for the period of Jan 19 to Feb 17, 2020. We used the date of the fourth revision of the case definition (Jan 27) to divide the epidemic into two time periods (Dec 24 to Jan 27, and Jan 28 to Feb 17) as the date of symptom onset. We estimated trends in the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (R t) at the provincial level. Findings We collected data on 8579 cases from 30 provinces. The median age of cases was 44 years (33–56), with an increasing proportion of cases in younger age groups and in elderly people (ie, aged >64 years) as the epidemic progressed. The mean time from symptom onset to hospital admission decreased from 4·4 days (95% CI 0·0–14·0) for the period of Dec 24 to Jan 27, to 2·6 days (0·0–9·0) for the period of Jan 28 to Feb 17. The mean incubation period for the entire period was estimated at 5·2 days (1·8–12·4) and the mean serial interval at 5·1 days (1·3–11·6). The epidemic dynamics in provinces outside Hubei were highly variable but consistently included a mixture of case importations and local transmission. We estimated that the epidemic was self-sustained for less than 3 weeks, with mean Rt reaching peaks between 1·08 (95% CI 0·74–1·54) in Shenzhen city of Guangdong province and 1·71 (1·32–2·17) in Shandong province. In all the locations for which we had sufficient data coverage of Rt, Rt was estimated to be below the epidemic threshold (ie, <1) after Jan 30. Interpretation Our estimates of the incubation period and serial interval were similar, suggesting an early peak of infectiousness, with possible transmission before the onset of symptoms. Our results also indicate that, as the epidemic progressed, infectious individuals were isolated more quickly, thus shortening the window of transmission in the community. Overall, our findings indicate that strict containment measures, movement restrictions, and increased awareness of the population might have contributed to interrupt local transmission of SARS-CoV-2 outside Hubei province. Funding National Science Fund for Distinguished Young Scholars, National Institute of General Medical Sciences, and European Commission Horizon 2020.
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                Author and article information

                Contributors
                Role: adjunct research professorRole: chief medical officer
                Role: associate professor
                Role: associate professor
                Role: professor
                Role: research fellow
                Role: head of ZPRIME Molecular Laboratory
                Role: assistant professor
                Role: clinical professor
                Role: statistician
                Role: registrar
                Role: research fellow
                Role: professor
                Journal
                BMJ
                BMJ
                BMJ-US
                bmj
                The BMJ
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2021
                17 February 2021
                : 372
                : n334
                Affiliations
                [1 ]Department of Global Health, Boston University School of Public Health, Boston, MA 02118, USA
                [2 ]Right To Care – Zambia
                [3 ]Department of Biomedical Sciences, University of Zambia, Lusaka, Zambia
                [4 ]ZPRIME Molecular Laboratory, University Teaching Hospital, Lusaka, Zambia
                [5 ]Department of Global Health, Boston University School of Public Health, Boston, MA, USA
                [6 ]Division of Internal Medicine, Infectious Diseases Section, University Teaching Hospital, Lusaka, Zambia
                [7 ]Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA
                [* ]Contributed equally
                Author notes
                Correspondence to: Christopher J Gill cgill@ 123456bu.edu (or @iddocgill on Twitter)
                Author information
                https://orcid.org/0000-0003-3353-0617
                Article
                mwal063837
                10.1136/bmj.n334
                7887952
                33597166
                9814a922-1268-4ecb-ae31-49cd1f0ddf9b
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions
                History
                : 03 February 2021
                Categories
                Research
                2474

                Medicine
                Medicine

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