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      Increase in COVID‐19 cases and case‐fatality and case‐recovery rates in Europe: A cross‐temporal meta‐analysis

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          Abstract

          The new coronavirus (COVID‐19) infection reported in China in December 2019 has become a pandemic in a few weeks, affecting the entire world. In this respect, it is crucial to determine the case‐increase, case‐fatality, and case‐recovery rates to control COVID‐19. In this study, the case‐increase, case‐fatality, and case‐recovery rates of COVID‐19 in 36 European countries were analyzed with the meta‐analysis method using data released by the health organizations and WHO. The data were obtained from the website of health organizations of 36 European countries and the website of WHO until 11 May 2020. The analyses were carried out on 1 744 704 COVID‐19‐diagnosed cases in 36 European countries. The case‐increase, case‐fatality and case‐recovery rates of COVID‐19 were calculated using 95% confidence intervals (95% CI), single‐arm meta‐analysis, cross‐temporal meta‐analysis, and meta‐regression random‐effects model. The standardized case‐increase rate of COVID‐19 is 5% (95% CI [0.040, 0.063]) and the average case‐increase rate in European countries has started to decline by around 3% (95% CI [0.047, 0.083]) weekly. The countries with the highest rate of case increase are Belgium, Sweden, Russia, the Netherlands and the United Kingdom. Although the case‐fatality rate of COVID‐19 patients was 4.5% as of May 11 (95% CI [0.037‐0.055]), this rate is 6.3% (95% CI [0.047, 0.083]) in standardized time (6th week). The case‐recovery rates of patients are 46% (95% CI [0.376‐0.547]). This study presents important results regarding the COVID‐19 pandemic in Europe. Although the rate of increase in new COVID‐19 cases has dropped, there is not much decline in the case‐fatality rates and no increase in case‐recovery rates. The case‐fatality rate of COVID‐19 in Europe was estimated to be in the range of 4% to 4.5% and a minimum of 4 weeks (as of 11 May) is expected to have the figure below 1% in a country with an average case‐increase rate. Monitoring case fatalities in Belgium, the Netherlands and Sweden, and treatment successes in Germany and Austria play a role of utmost importance.

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

          Chaolin Huang, Yeming Wang, Xingwang Li … (2020)
          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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            Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy

            Graziano Onder, Giovanni Rezza, Silvio Brusaferro (2020)
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              Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study

              Joseph Wu, Kathy Leung, Gabriel Leung (2020)
              Summary Background Since Dec 31, 2019, the Chinese city of Wuhan has reported an outbreak of atypical pneumonia caused by the 2019 novel coronavirus (2019-nCoV). Cases have been exported to other Chinese cities, as well as internationally, threatening to trigger a global outbreak. Here, we provide an estimate of the size of the epidemic in Wuhan on the basis of the number of cases exported from Wuhan to cities outside mainland China and forecast the extent of the domestic and global public health risks of epidemics, accounting for social and non-pharmaceutical prevention interventions. Methods We used data from Dec 31, 2019, to Jan 28, 2020, on the number of cases exported from Wuhan internationally (known days of symptom onset from Dec 25, 2019, to Jan 19, 2020) to infer the number of infections in Wuhan from Dec 1, 2019, to Jan 25, 2020. Cases exported domestically were then estimated. We forecasted the national and global spread of 2019-nCoV, accounting for the effect of the metropolitan-wide quarantine of Wuhan and surrounding cities, which began Jan 23–24, 2020. We used data on monthly flight bookings from the Official Aviation Guide and data on human mobility across more than 300 prefecture-level cities in mainland China from the Tencent database. Data on confirmed cases were obtained from the reports published by the Chinese Center for Disease Control and Prevention. Serial interval estimates were based on previous studies of severe acute respiratory syndrome coronavirus (SARS-CoV). A susceptible-exposed-infectious-recovered metapopulation model was used to simulate the epidemics across all major cities in China. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credibile interval (CrI). Findings In our baseline scenario, we estimated that the basic reproductive number for 2019-nCoV was 2·68 (95% CrI 2·47–2·86) and that 75 815 individuals (95% CrI 37 304–130 330) have been infected in Wuhan as of Jan 25, 2020. The epidemic doubling time was 6·4 days (95% CrI 5·8–7·1). We estimated that in the baseline scenario, Chongqing, Beijing, Shanghai, Guangzhou, and Shenzhen had imported 461 (95% CrI 227–805), 113 (57–193), 98 (49–168), 111 (56–191), and 80 (40–139) infections from Wuhan, respectively. If the transmissibility of 2019-nCoV were similar everywhere domestically and over time, we inferred that epidemics are already growing exponentially in multiple major cities of China with a lag time behind the Wuhan outbreak of about 1–2 weeks. Interpretation Given that 2019-nCoV is no longer contained within Wuhan, other major Chinese cities are probably sustaining localised outbreaks. Large cities overseas with close transport links to China could also become outbreak epicentres, unless substantial public health interventions at both the population and personal levels are implemented immediately. Independent self-sustaining outbreaks in major cities globally could become inevitable because of substantial exportation of presymptomatic cases and in the absence of large-scale public health interventions. Preparedness plans and mitigation interventions should be readied for quick deployment globally. Funding Health and Medical Research Fund (Hong Kong, China).
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                Author and article information

                Contributors
                Engin Karadag:
                ORCID: http://orcid.org/0000-0002-9723-3833
                enginkaradag@akdeniz.edu.tr , engin.karadag@hotmail.com
                Journal
                Journal ID (nlm-ta): J Med Virol
                Journal ID (iso-abbrev): J. Med. Virol
                Journal ID (doi): 10.1002/(ISSN)1096-9071
                Journal ID (publisher-id): JMV
                Title: Journal of Medical Virology
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Print): 0146-6615
                ISSN (Electronic): 1096-9071
                Publication date (Electronic): 02 June 2020
                Electronic Location Identifier: 10.1002/jmv.26035
                Affiliations
                [ 1 ] Akdeniz University Kampus Antalya 07070 Turkey
                Author notes
                [*] [* ] Correspondence Engin Karadag, Akdeniz University, Kampus, Antalya 07070, Turkey.

                Email: enginkaradag@ 123456akdeniz.edu.tr and engin.karadag@ 123456hotmail.com

                Author information
                http://orcid.org/0000-0002-9723-3833
                Article
                Publisher ID: JMV26035
                DOI: 10.1002/jmv.26035
                PMC ID: 7280723
                PubMed ID: 32437052
                SO-VID: 04db494a-2f0f-43ff-b77c-5e106480fc16
                Copyright © © 2020 Wiley Periodicals LLC
                License:

                This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.

                History
                Date received : 30 April 2020
                Date accepted : 18 May 2020
                Page count
                Figures: 1, Tables: 6, Pages: 7, Words: 4855
                Categories
                Subject: Review
                Subject: Reviews
                Custom metadata
                source-schema-version-number 2.0
                edited-state corrected-proof
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:5.8.4 mode:remove_FC converted:09.06.2020

                ScienceOpen disciplines: Microbiology & Virology
                Keywords: case‐fatality rate,case‐increase rate,case‐recovery rate,covid‐19,europe
                Data availability:
                ScienceOpen disciplines: Microbiology & Virology
                Keywords: case‐fatality rate, case‐increase rate, case‐recovery rate, covid‐19, europe

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