15
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Rapid implementation of mobile technology for real-time epidemiology of COVID-19

      research-article
      1 , 1 , 2 , 3 , 2 , 2 , 4 , 4 ,   4 , 4 , 5 , 2 , 5 , 1 , 6 , , COPE Consortium §
      (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab), (Collab)
      Science (New York, N.y.)
      American Association for the Advancement of Science

      Read this article at

      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

          The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic (COVID-19) presents challenges to the robust collection of population-scale data to address this global health crisis. We established the COronavirus Pandemic Epidemiology (COPE) consortium to bring together scientists with expertise in big data research and epidemiology to develop a COVID-19 Symptom Tracker mobile application that we launched in the UK on March 24, 2020 and the US on March 29, 2020 garnering more than 2.8 million users as of May 2, 2020. This mobile application offers data on risk factors, herald symptoms, clinical outcomes, and geographical hot spots. This initiative offers critical proof-of-concept for the repurposing of existing approaches to enable rapidly scalable epidemiologic data collection and analysis which is critical for a data-driven response to this public health challenge.

          Related collections

          Most cited references15

          • Record: found
          • Abstract: found
          • Article: not found

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            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.)
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

              Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p<0·0001), and d-dimer greater than 1 μg/mL (18·42, 2·64–128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0–24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days. Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.
                Bookmark

                Author and article information

                Journal
                Science
                Science
                SCIENCE
                Science (New York, N.y.)
                American Association for the Advancement of Science
                0036-8075
                1095-9203
                05 May 2020
                : eabc0473
                Affiliations
                [1 ]Clinical & Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, 55 Fruit St., Boston, MA 02114, USA.
                [2 ]Department of Twin Research and Genetic Epidemiology, King’s College London, Westminster Bridge Road, London SE17EH, UK.
                [3 ]Department of Ageing and Health, Guys and St. Thomas’s NHS Foundation Trust, Lambeth Palace Road, London SE17EHIL, UK.
                [4 ]School of Biomedical Engineering & Imaging Sciences, King’s College London, 1 Lambeth Palace Road, London SE1 7EU, UK.
                [5 ]Zoe Global Limited, 164 Westminster Bridge Road, London SE17RW, UK.
                [6 ]Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02114, USA.
                Author notes
                [*]

                These authors contributed equally to this work.

                [†]

                These authors contributed equally to this work.

                []Corresponding author. Email: achan@ 123456mgh.harvard.edu
                [§]

                COPE Consortium members and affiliations are listed in the supplementary materials.

                Author information
                https://orcid.org/0000-0002-8813-0816
                https://orcid.org/0000-0002-5436-4219
                https://orcid.org/0000-0002-4910-0489
                https://orcid.org/0000-0002-1439-6259
                https://orcid.org/0000-0001-5753-428X
                https://orcid.org/0000-0003-1284-2558
                https://orcid.org/0000-0002-0530-2257
                https://orcid.org/0000-0002-9795-0365
                https://orcid.org/0000-0001-7284-6767
                Article
                abc0473
                10.1126/science.abc0473
                7200009
                32371477
                90d3b89b-8bd8-48e8-a4f0-683a9b438ebd
                Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

                This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

                History
                : 02 April 2020
                : 30 April 2020
                Funding
                Funded by: doi http://dx.doi.org/10.13039/100005294, Massachusetts General Hospital;
                Award ID: Stuart and Suzanne Steele MGH Research Scholar Award
                Funded by: doi http://dx.doi.org/10.13039/501100013372, Wellcome Trust Centre for Mitochondrial Research;
                Funded by: Zoe Global Ltd.;
                Categories
                Report
                Reports
                Reports
                Epidemiology
                Techniques
                Custom metadata
                4
                4

                Uncategorized
                Uncategorized

                Comments

                Comment on this article