#Data-based #analysis, #modelling and #forecasting of the #COVID19 #outbreak (PLOS One, abstract)

[Source: PLOS One, full page: (LINK). Abstract, edited.]

OPEN ACCESS |  PEER-REVIEWED | RESEARCH ARTICLE

Data-based analysis, modelling and forecasting of the COVID-19 outbreak

Cleo Anastassopoulou , Lucia Russo, Athanasios Tsakris, Constantinos Siettos

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Published: March 31, 2020 | DOI: https://doi.org/10.1371/journal.pone.0230405

 

Abstract

Since the first suspected case of coronavirus disease-2019 (COVID-19) on December 1st, 2019, in Wuhan, Hubei Province, China, a total of 40,235 confirmed cases and 909 deaths have been reported in China up to February 10, 2020, evoking fear locally and internationally. Here, based on the publicly available epidemiological data for Hubei, China from January 11 to February 10, 2020, we provide estimates of the main epidemiological parameters. In particular, we provide an estimation of the case fatality and case recovery ratios, along with their 90% confidence intervals as the outbreak evolves. On the basis of a Susceptible-Infectious-Recovered-Dead (SIDR) model, we provide estimations of the basic reproduction number (R0), and the per day infection mortality and recovery rates. By calibrating the parameters of the SIRD model to the reported data, we also attempt to forecast the evolution of the outbreak at the epicenter three weeks ahead, i.e. until February 29. As the number of infected individuals, especially of those with asymptomatic or mild courses, is suspected to be much higher than the official numbers, which can be considered only as a subset of the actual numbers of infected and recovered cases in the total population, we have repeated the calculations under a second scenario that considers twenty times the number of confirmed infected cases and forty times the number of recovered, leaving the number of deaths unchanged. Based on the reported data, the expected value of R0 as computed considering the period from the 11th of January until the 18th of January, using the official counts of confirmed cases was found to be ∼4.6, while the one computed under the second scenario was found to be ∼3.2. Thus, based on the SIRD simulations, the estimated average value of R0 was found to be ∼2.6 based on confirmed cases and ∼2 based on the second scenario. Our forecasting flashes a note of caution for the presently unfolding outbreak in China. Based on the official counts for confirmed cases, the simulations suggest that the cumulative number of infected could reach 180,000 (with a lower bound of 45,000) by February 29. Regarding the number of deaths, simulations forecast that on the basis of the up to the 10th of February reported data, the death toll might exceed 2,700 (as a lower bound) by February 29. Our analysis further reveals a significant decline of the case fatality ratio from January 26 to which various factors may have contributed, such as the severe control measures taken in Hubei, China (e.g. quarantine and hospitalization of infected individuals), but mainly because of the fact that the actual cumulative numbers of infected and recovered cases in the population most likely are much higher than the reported ones. Thus, in a scenario where we have taken twenty times the confirmed number of infected and forty times the confirmed number of recovered cases, the case fatality ratio is around ∼0.15% in the total population. Importantly, based on this scenario, simulations suggest a slow down of the outbreak in Hubei at the end of February.

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Citation: Anastassopoulou C, Russo L, Tsakris A, Siettos C (2020) Data-based analysis, modelling and forecasting of the COVID-19 outbreak. PLoS ONE 15(3): e0230405. https://doi.org/10.1371/journal.pone.0230405

Editor: Sreekumar Othumpangat, Center for Disease control and Prevention, UNITED STATES

Received: February 11, 2020; Accepted: March 1, 2020; Published: March 31, 2020

Copyright: © 2020 Anastassopoulou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data used in this paper were acquired from https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6. In S1 Table we provide the data that we have used for this study, i.e. the cumulative confirmed cases of infected recovered and deaths from January 11 to February 10.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Keywords: SARS-CoV-2; COVID-19.

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#Forecasting the novel #coronavirus #COVID19 (PLOS One, abstract)

[Source: PLOS One, full page: (LINK). Abstract, edited.]

OPEN ACCESS |  PEER-REVIEWED | RESEARCH ARTICLE

Forecasting the novel coronavirus COVID-19

Fotios Petropoulos , Spyros Makridakis

Published: March 31, 2020 | DOI: https://doi.org/10.1371/journal.pone.0231236

 

Abstract

What will be the global impact of the novel coronavirus (COVID-19)? Answering this question requires accurate forecasting the spread of confirmed cases as well as analysis of the number of deaths and recoveries. Forecasting, however, requires ample historical data. At the same time, no prediction is certain as the future rarely repeats itself in the same way as the past. Moreover, forecasts are influenced by the reliability of the data, vested interests, and what variables are being predicted. Also, psychological factors play a significant role in how people perceive and react to the danger from the disease and the fear that it may affect them personally. This paper introduces an objective approach to predicting the continuation of the COVID-19 using a simple, but powerful method to do so. Assuming that the data used is reliable and that the future will continue to follow the past pattern of the disease, our forecasts suggest a continuing increase in the confirmed COVID-19 cases with sizable associated uncertainty. The risks are far from symmetric as underestimating its spread like a pandemic and not doing enough to contain it is much more severe than overspending and being over careful when it will not be needed. This paper describes the timeline of a live forecasting exercise with massive potential implications for planning and decision making and provides objective forecasts for the confirmed cases of COVID-19.

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Citation: Petropoulos F, Makridakis S (2020) Forecasting the novel coronavirus COVID-19. PLoS ONE 15(3): e0231236. https://doi.org/10.1371/journal.pone.0231236

Editor: Lidia Adriana Braunstein, Universidad Nacional de Mar del Plata, ARGENTINA

Received: February 24, 2020; Accepted: March 17, 2020; Published: March 31, 2020

Copyright: © 2020 Petropoulos, Makridakis. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data were retrieved by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University: https://github.com/CSSEGISandData/COVID-19 [accessed on 12/03/2020].

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Keywords: SARS-CoV-2; COVID-19.

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#Humans, #Viruses, and the #Eye—An Early #Report From the #COVID19 Front Line (JAMA Ophthalmol., summary)

[Source: JAMA Ophthalmology, full page: (LINK). Summary, edited.]

Humans, Viruses, and the Eye—An Early Report From the COVID-19 Front Line

Alfred Sommer, MD, MHS1

Author Affiliations: 1 Johns Hopkins Bloomberg School of Public Health and the Wilmer Eye Institute at the Johns Hopkins University School of Medicine, Baltimore, Maryland

JAMA Ophthalmol. Published online March 31, 2020. doi:10.1001/jamaophthalmol.2020.1294

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Viruses have always been part of the human experience, most often in a delicate balance, otherwise the virus and its human host would become extinct. But this relationship is not particularly stable. Like all living substances, viruses mutate, sometimes in ways that cause explosive, severe disease. Viral outbreaks have killed off virtually entire populations, as happened when measles was first introduced into the previously naive population of the Faroe Islands, or when Europeans brought smallpox to North America. Humankind, as a whole, has survived evolving viral threats by evolving with them; prior exposure to related viruses produces varying degrees of resistance (immunity) to new strains. Humans with less resistance die, often despite modern medical intervention, while others remain entirely asymptomatic. Medical interventions (principally vaccines) and stringent public health measures have often altered the outcome, but not necessarily in predictable ways.

(…)

Keywords: SARS-CoV-2; COVID-19; Ophthalmology.

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Characteristics of #Ocular #Findings of Patients With #Coronavirus Disease 2019 (#COVID19) in #Hubei Province, #China (JAMA Ophthalmol., abstract)

[Source: JAMA Ophthalmology, full page: (LINK). Abstract, edited.]

Characteristics of Ocular Findings of Patients With Coronavirus Disease 2019 (COVID-19) in Hubei Province, China

Ping Wu, MD1; Fang Duan, MD2; Chunhua Luo, MD1; et al. Qiang Liu, MD1; Xingguang Qu, MD1; Liang Liang, MD1; Kaili Wu, MD2

Author Affiliations: 1 Department of Ophthalmology, The First College of Clinical Medical Science, Yichang Central People’s Hospital, China Three Gorges University, Yichang, China; 2 Zhongshan Ophthalmic Center, State Key Laboratory of Ophthalmology, Sun Yat-Sen University, Guangzhou, China

JAMA Ophthalmol. Published online March 31, 2020. doi:10.1001/jamaophthalmol.2020.1291

 

Key Points

  • Question  – What are the ocular manifestations and conjunctival viral prevalence in patients from Hubei province, China, with coronavirus disease 2019 (COVID-19)?
  • Findings  – In this case series including 38 patients with COVID-19, 12 patients had ocular manifestations, such as epiphora, conjunctival congestion, or chemosis, and these commonly occurred in patients with more severe systemic manifestations. Reverse transcriptase–polymerase chain reaction results were positive for severe acute respiratory syndrome coronavirus 2 in 28 nasopharyngeal swabs and 2 conjunctival swabs, and more significant changes in blood test values appeared in patients with ocular abnormalities.
  • Meaning  – These data may assist ophthalmologists and others to understand the ocular manifestations of COVID-19, thus enhancing the diagnosis and prevention of the transmission of the disease.

 

Abstract

Importance  

While the outbreak of coronavirus disease 2019 (COVID-19) has resulted in more than 100 000 infected individuals in China and worldwide, there are few reports on the association of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with ocular abnormalities. Understanding ocular manifestations of patients with COVID-19 by ophthalmologists and others may facilitate the diagnosis and prevention of transmission of the disease.

Objective  

To investigate ocular manifestations and viral prevalence in the conjunctiva of patients with COVID-19.

Design, Setting, and Participants  

In this case series, patients with COVID-19 treated from February 9 to 15, 2020, at a hospital center in Hubei province, China, were retrospectively reviewed for ocular manifestations. During the period of treatment, the ocular signs and symptoms as well as results of blood tests and reverse transcriptase–polymerase chain reaction (RT-PCR) from nasopharyngeal and conjunctival swabs for SARS-CoV-2 were noted and analyzed.

Main Outcomes and Measures  

Ocular signs and symptoms as well as results of blood tests and RT-PCR for SARS-CoV-2.

Results  

Of the 38 included patients with clinically confirmed COVID-19, 25 (65.8%) were male, and the mean (SD) age was 65.8 (16.6) years. Among them, 28 patients (73.7%) had positive findings for COVID-19 on RT-PCR from nasopharyngeal swabs, and of these, 2 patients (5.2%) yielded positive findings for SARS-CoV-2 in their conjunctival as well as nasopharyngeal specimens. A total of 12 of 38 patients (31.6%; 95% CI, 17.5-48.7) had ocular manifestations consistent with conjunctivitis, including conjunctival hyperemia, chemosis, epiphora, or increased secretions. By univariate analysis, patients with ocular symptoms were more likely to have higher white blood cell and neutrophil counts and higher levels of procalcitonin, C-reactive protein, and lactate dehydrogenase than patients without ocular symptoms. In addition, 11 of 12 patients with ocular abnormalities (91.7%; 95% CI, 61.5-99.8) had positive results for SARS-CoV-2 on RT-PCR from nasopharyngeal swabs. Of these, 2 (16.7%) had positive results for SARS-CoV-2 on RT-PCR from both conjunctival and nasopharyngeal swabs.

Conclusions and Relevance  

In this study, one-third of patients with COVID-19 had ocular abnormalities, which frequently occurred in patients with more severe COVID-19. Although there is a low prevalence of SARS-CoV-2 in tears, it is possible to transmit via the eyes.

Keywords: SARS-CoV-2; COVID-19; Ophthalmology.

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#CT #Imaging of 3 Patients With #COVID19 #Pneumonia With Negative Virus Real-time Reverse-Transcription #PCR #Test (Clin Infect Dis., abstract)

[Source: Clinical Infectious Diseases, full page: (LINK). Abstract, edited.]

Computed Tomographic Imaging of 3 Patients With Coronavirus Disease 2019 Pneumonia With Negative Virus Real-time Reverse-Transcription Polymerase Chain Reaction Test

Junqing Xu, Ruodai Wu, Hua Huang, Weidong Zheng, Xinling Ren, Nashan Wu, Bin Ji, Yungang Lv, Yumeng Liu, Rui Mi

Clinical Infectious Diseases, ciaa207, https://doi.org/10.1093/cid/ciaa207

Published: 31 March 2020

 

Abstract

We reported computed tomographic (CT) imaging findings of 3 patients with coronavirus disease 2019 (COVID-19) pneumonia with initially negative results before CT examination and finally confirmed positive for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by real-time reverse-transcription polymerase chain reaction assay.

chest CT, covid-19 pneumonia, rt-PCR

Issue Section: Brief Report

Keywords: SARS-CoV-2; COVID-19; Radiology; Diagnostic tests.

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Preliminary #Estimates of #Prevalence of Selected Underlying Health #Conditions Among Patients with #COVID19 — #USA, Feb. 12–Mar. 28 ’20 (MMWR Morb Mortal Wkly Rep., abstract)

[Source: US Centers for Disease Control and Prevention (CDC), MMWR Morbidity and Mortality Weekly Report, full page: (LINK). Abstract, edited.]

Preliminary Estimates of the Prevalence of Selected Underlying Health Conditions Among Patients with Coronavirus Disease 2019 — United States, February 12–March 28, 2020

Early Release / March 31, 2020 / 69

CDC COVID-19 Response Team

CDC COVID-19 Response Team: Nancy Chow, CDC; Katherine Fleming-Dutra, CDC; Ryan Gierke, CDC; Aron Hall, CDC; Michelle Hughes, CDC; Tamara Pilishvili, CDC; Matthew Ritchey, CDC; Katherine Roguski, CDC; Tami Skoff, CDC; Emily Ussery, CDC.

Corresponding author: Katherine Fleming-Dutra, for the CDC COVID-19 Response Team, eocevent294@cdc.gov, 770-488-7100.

All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.

Suggested citation for this article: Preliminary Estimates of the Prevalence of Selected Underlying Health Conditions Among Patients with Coronavirus Disease 2019 — United States, February 12–March 28, 2020. MMWR Morb Mortal Wkly Rep. ePub: 31 March 2020. DOI: http://dx.doi.org/10.15585/mmwr.mm6913e2external icon.

 

Summary

  • What is already known about this topic?
    • Published reports from China and Italy suggest that risk factors for severe COVID-19 disease include underlying health conditions, but data describing underlying health conditions among U.S. COVID-19 patients have not yet been reported.
  • What is added by this report?
    • Based on preliminary U.S. data, persons with underlying health conditions such as diabetes mellitus, chronic lung disease, and cardiovascular disease, appear to be at higher risk for severe COVID-19–associated disease than persons without these conditions.
  • What are the implications for public health practice?
    • Strategies to protect all persons and especially those with underlying health conditions, including social distancing and handwashing, should be implemented by all communities and all persons to help slow the spread of COVID-19.

 

Abstract

On March 11, 2020, the World Health Organization declared Coronavirus Disease 2019 (COVID-19) a pandemic (1). As of March 28, 2020, a total of 571,678 confirmed COVID-19 cases and 26,494 deaths have been reported worldwide (2). Reports from China and Italy suggest that risk factors for severe disease include older age and the presence of at least one of several underlying health conditions (3,4). U.S. older adults, including those aged ≥65 years and particularly those aged ≥85 years, also appear to be at higher risk for severe COVID-19–associated outcomes; however, data describing underlying health conditions among U.S. COVID-19 patients have not yet been reported (5). As of March 28, 2020, U.S. states and territories have reported 122,653 U.S. COVID-19 cases to CDC, including 7,162 (5.8%) for whom data on underlying health conditions and other known risk factors for severe outcomes from respiratory infections were reported. Among these 7,162 cases, 2,692 (37.6%) patients had one or more underlying health condition or risk factor, and 4,470 (62.4%) had none of these conditions reported. The percentage of COVID-19 patients with at least one underlying health condition or risk factor was higher among those requiring intensive care unit (ICU) admission (358 of 457, 78%) and those requiring hospitalization without ICU admission (732 of 1,037, 71%) than that among those who were not hospitalized (1,388 of 5,143, 27%). The most commonly reported conditions were diabetes mellitus, chronic lung disease, and cardiovascular disease. These preliminary findings suggest that in the United States, persons with underlying health conditions or other recognized risk factors for severe outcomes from respiratory infections appear to be at a higher risk for severe disease from COVID-19 than are persons without these conditions.

Keywords: SARS-CoV-2; COVID-19; USA; Intensive Care.

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Angel, I will follow you, Jacek Malczewski (1901)

Annotazione 2020-03-31 185812

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Angel, I will follow you
Jacek Malczewski
Date: 1901
Style: Art Nouveau (Modern)
Genre: religious painting
Media: oil, panel
Dimensions: 34.5 x 28 cm

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Permissions: Public Domain.

Source: WikiArt, full page: https://www.wikiart.org/en/jacek-malczewski/angel-i-will-follow-you-1901

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