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      Telemedicine in Peru as a Result of the COVID-19 Pandemic: Perspective from a Country with Limited Internet Access

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          Abstract.

          The COVID-19 pandemic contributed to the worldwide implementation of telemedicine because of the need for medical care for patients, especially those with chronic diseases. This perspective paper presents the current situation of telemedicine in Peru, showing advances in regulation, cases of successful implementation, and the current challenges. Access to health should be available to all, and more efforts need to be implemented to offer access to the internet to achieve high-quality telemedicine to all the vulnerable groups in Peru.

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          Most cited references75

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          An interactive web-based dashboard to track COVID-19 in real time

          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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            Virtually Perfect? Telemedicine for Covid-19

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              Diabetes mellitus is associated with increased mortality and severity of disease in COVID-19 pneumonia – A systematic review, meta-analysis, and meta-regression ☆

              Background and aims Diabetes Mellitus (DM) is chronic conditions with devastating multi-systemic complication and may be associated with severe form of Coronavirus Disease 2019 (COVID-19). We conducted a systematic review and meta-analysis in order to investigate the association between DM and poor outcome in patients with COVID-19 pneumonia. Methods Systematic literature search was performed from several electronic databases on subjects that assess DM and outcome in COVID-19 pneumonia. The outcome of interest was composite poor outcome, including mortality, severe COVID-19, acute respiratory distress syndrome (ARDS), need for intensive care unit (ICU) care, and disease progression. Results There were a total of 6452 patients from 30 studies. Meta-analysis showed that DM was associated with composite poor outcome (RR 2.38 [1.88, 3.03], p < 0.001; I2: 62%) and its subgroup which comprised of mortality (RR 2.12 [1.44, 3.11], p < 0.001; I2: 72%), severe COVID-19 (RR 2.45 [1.79, 3.35], p < 0.001; I2: 45%), ARDS (RR 4.64 [1.86, 11.58], p = 0.001; I2: 9%), and disease progression (RR 3.31 [1.08, 10.14], p = 0.04; I2: 0%). Meta-regression showed that the association with composite poor outcome was influenced by age (p = 0.003) and hypertension (p < 0.001). Subgroup analysis showed that the association was weaker in studies with median age ≥55 years-old (RR 1.92) compared to <55 years-old (RR 3.48), and in prevalence of hypertension ≥25% (RR 1.93) compared to <25% (RR 3.06). Subgroup analysis on median age <55 years-old and prevalence of hypertension <25% showed strong association (RR 3.33) Conclusion DM was associated with mortality, severe COVID-19, ARDS, and disease progression in patients with COVID-19.

                Author and article information

                Journal
                Am J Trop Med Hyg
                Am J Trop Med Hyg
                tpmd
                tropmed
                The American Journal of Tropical Medicine and Hygiene
                The American Society of Tropical Medicine and Hygiene
                0002-9637
                1476-1645
                July 2021
                17 May 2021
                17 May 2021
                : 105
                : 1
                : 6-11
                Affiliations
                [1 ]Universidad de Lima, Facultad de Ciencias Empresariales y Económicas, Carrera de Negocios Internacionales, Lima, Perú;
                [2 ]Escuela Nacional de Marina Mercante “Almirante Miguel Grau,” Callao, Peru;
                [3 ]Universidad Peruana de Ciencias Aplicadas, Facultad de Educación, Carrera de Educación y Gestión del Aprendizaje;
                [4 ]Teoma Global, Gerencia Corporativa de Asuntos Científicos y Regulatorios, Lima, Peru
                Author notes
                *Address correspondence to Aldo Alvarez-Risco, Universidad de Lima, Facultad de Ciencias Empresariales y Económicas, Carrera de Negocios Internacionales. Lima, Perú, Av. Javier Prado Este 4600 Santiago de Surco, Lima, Peru. E-mail: aralvare@ 123456ulima.edu.pe

                Authors’ addresses: Aldo Alvarez-Risco, Universidad de Lima, Facultad de Ciencias Empresariales y Economicas, Carrera de Negocios Internacionales, Lima, Peru, E-mail: aralvare@ 123456ulima.edu.pe . Shyla Del-Aguila-Arcentales, Escuela Nacional de Marina Mercante “Almirante Miguel Grau,” Callao, Peru, E-mail: shyladel01@ 123456gmail.com . Jaime A. Yáñez, Universidad Peruana de Ciencias Aplicadas, Facultad de Educacion, Carrera de Educacion y Gestion del Aprendizaje, Lima, Peru, E-mail: jaimeayanez@ 123456gmail.com .

                Article
                tpmd210255
                10.4269/ajtmh.21-0255
                8274764
                33999847
                eb5768df-22d7-48e9-bd58-135be92d9598
                © The American Society of Tropical Medicine and Hygiene

                This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 02 March 2021
                : 17 April 2021
                Page count
                Pages: 6
                Categories
                Perspective Piece

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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