scholarly journals Purely data-driven exploration of COVID-19 pandemic after three months of the outbreak

2020 ◽  
Author(s):  
Shirali Kadyrov ◽  
Hayot Berk Saydaliev
Keyword(s):  
Reproduction Number ◽  
Statistical Tests ◽  
Disease Outbreak ◽  
Data Driven ◽  
The Novel ◽  
Epidemic Modeling ◽  
Death Rates ◽  
Sir Epidemic ◽  
Novel Coronavirus ◽  
Epidemiological Characteristics

AbstractIt has been three months since the novel coronavirus (COVID-19) pandemic outbreak. Many research studies were carried to understand its epidemiological characteristics in the early phase of the disease outbreak. The current study is yet another contribution to better understand the disease properties by parameter estimation of mathematical SIR epidemic modeling. The authors use Johns Hopkins University’s dataset to estimate the basic reproduction number of COVID-19 for representative countries (Japan, Germany, Italy, France, and Netherlands) selected using cluster analysis. As a by-product, the authors estimate transmission, recovery, and death rates for each selected country and carry statistical tests to see if there are any significant differences.

scholarly journals Purely Data-driven Exploration of COVID-19 Pandemic After Three Months of the Outbreak

2021 ◽  
Vol 53 (3) ◽  
pp. 358-368
Author(s):  
Shirali Kadyrov ◽  
Alibek Orynbassar ◽  
Hayot Berk Saydaliev
Keyword(s):  
Cluster Analysis ◽  
Parameter Estimation ◽  
Reproduction Number ◽  
Statistical Tests ◽  
Data Driven ◽  
Epidemic Modeling ◽  
Death Rates ◽  
Sir Epidemic ◽  
Epidemiological Characteristics ◽  
The Basic Reproduction Number

Many research studies have been carried out to understand the epidemiological characteristics of the COVID-19 pandemic in its early phase. The current study is yet another contribution to better understand the disease properties by parameter estimation based on mathematical SIR epidemic modeling. The authors used Johns Hopkins University’s dataset to estimate the basic reproduction number of COVID-19 for five representative countries (Japan, Germany, Italy, France, and the Netherlands) that were selected using cluster analysis. As byproducts, the authors estimated the transmission, recovery, and death rates for each selected country and carried out statistical tests to see if there were any significant differences.

FEATURES OF THE COURSE AND TACTICS OF MANAGING CHILDREN WITH KIDNEYS AND URINARY TRACT DISEASES DURING THE PANDEMIC OF NEW CORONAVIRUS INFECTION COVID-19

2021 ◽  
Vol 100 (4) ◽  
pp. 74-79
Author(s):  
I.M. Kagantsov ◽  
◽  
V.V. Sizonov ◽  
V.G. Svarich ◽  
K.P. Piskunov ◽  
...  
Keyword(s):  
Age Groups ◽  
Clinical Manifestations ◽  
Routine Care ◽  
The Novel ◽  
Urinary System ◽  
Death Rates ◽  
Global Pandemic ◽  
Coronavirus Infection ◽  
Novel Coronavirus ◽  
Significant Health

The novel coronavirus infection (SARS-CoV-2), which first appeared in Wuhan, China in December 2019, has been declared a global pandemic by WHO. COVID-19 affects people of all age groups. The disease in children is usually asymptomatic or mild compared to adults, and with a significantly lower death rates. Data on kidney damage in children with COVID-19, as well as the effect of coronavirus infection on the course of diseases of the genitourinary system, are limited, the risks of contracting a new coronavirus infection in children with significant health problems, including those with chronic kidney disease, remain uncertain. The pandemic has affected the activities of surgeons treating diseases of the urinary system in children. Since the prospects for the end of the pandemic are vague, it is necessary to formulate criteria for selecting patients who can and should be provided with routine care in the pandemic. The purpose of this review is to highlight the features of the clinical manifestations and treatment of children with COVID-19, occurring against the background of previous renal pathology or complicating its course.

scholarly journals Early epidemiological assessment of the transmission potential and virulence of coronavirus disease 2019 (COVID-19) in Wuhan City: China, January-February, 2020

2020 ◽  
Author(s):  
Kenji Mizumoto ◽  
Katsushi Kagaya ◽  
Gerardo Chowell
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Public Health Intervention ◽  
Ecological Modelling ◽  
The Novel ◽  
Wuhan City ◽  
Transmission Potential ◽  
The World ◽  
Novel Coronavirus ◽  
Epidemiological Parameters

AbstractBackgroundSince the first cluster of cases was identified in Wuhan City, China, in December, 2019, coronavirus disease 2019 (COVID-19) rapidly spread around the world. Despite the scarcity of publicly available data, scientists around the world have made strides in estimating the magnitude of the epidemic, the basic reproduction number, and transmission patterns. Accumulating evidence suggests that a substantial fraction of the infected individuals with the novel coronavirus show little if any symptoms, which highlights the need to reassess the transmission potential of this emerging disease. In this study, we derive estimates of the transmissibility and virulence of COVID-19 in Wuhan City, China, by reconstructing the underlying transmission dynamics using multiple data sources.MethodsWe employ statistical methods and publicly available epidemiological datasets to jointly derive estimates of transmissibility and severity associated with the novel coronavirus. For this purpose, the daily series of laboratory–confirmed COVID-19 cases and deaths in Wuhan City together with epidemiological data of Japanese repatriated from Wuhan City on board government–chartered flights were integrated into our analysis.ResultsOur posterior estimates of basic reproduction number (R) in Wuhan City, China in 2019–2020 reached values at 3.49 (95%CrI: 3.39–3.62) with a mean serial interval of 6.0 days, and the enhanced public health intervention after January 23rd in 2020 was associated with a significantly reduced R at 0.84 (95%CrI: 0.81–0.88), with the total number of infections (i.e. cumulative infections) estimated at 1906634 (95%CrI: 1373500–2651124) in Wuhan City, elevating the overall proportion of infected individuals to 19.1% (95%CrI: 13.5–26.6%). We also estimated the most recent crude infection fatality ratio (IFR) and time–delay adjusted IFR at 0.04% (95% CrI: 0.03%–0.06%) and 0.12% (95%CrI: 0.08–0.17%), respectively, estimates that are several orders of magnitude smaller than the crude CFR estimated at 4.06%ConclusionsWe have estimated key epidemiological parameters of the transmissibility and virulence of COVID-19 in Wuhan, China during January-February, 2020 using an ecological modelling approach. The power of this approach lies in the ability to infer epidemiological parameters with quantified uncertainty from partial observations collected by surveillance systems.

scholarly journals Endocrine changes in SARS-CoV-2 patients and lessons from SARS-CoV

2020 ◽  
Vol 96 (1137) ◽  
pp. 412-416 ◽  
Author(s):  
Shubham Agarwal ◽  
Sanjeev Kumar Agarwal
Keyword(s):  
Disease Outbreak ◽  
The Novel ◽  
Endocrine Glands ◽  
Sars Coronavirus ◽  
Endocrine Disturbances ◽  
Clinical Presentations ◽  
Coronavirus Infection ◽  
Novel Coronavirus ◽  
Convalescence Phase ◽  
Significant Mortality

Coronavirus infection outbreaks have occurred frequently in the last two decades and have led to significant mortality. Despite the focus on reducing mortality by preventing the spread of the virus, patients have died due to several other complications of the illness. The understanding of pathological mechanisms and their implications is continuously evolving. A number of symptoms occur in these patients due to the involvement of various endocrine glands. These clinical presentations went largely unnoticed during the first outbreak of severe acute respiratory syndrome (SARS) in 2002–2003. A few of these derangements continued during the convalescence phase and sometimes occurred after recovery. Similar pathological and biochemical changes are being reported with the novel coronavirus disease outbreak in 2020. In this review, we focus on these endocrine changes that have been reported in both SARS coronavirus and SARS coronavirus-2. As we battle the pandemic, it becomes imperative to address these underlying endocrine disturbances that are contributing towards or predicting mortality of these patients.

scholarly journals The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran

2020 ◽  
Vol 148 ◽  
Author(s):  
A. Khosravi ◽  
R. Chaman ◽  
M. Rohani-Rasaf ◽  
F. Zare ◽  
S. Mehravaran ◽  
...  
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Early Stage ◽  
Screening Tests ◽  
The Novel ◽  
Epidemic Size ◽  
Serial Interval ◽  
Novel Coronavirus ◽  
Interval Distribution ◽  
The Basic Reproduction Number

Abstract The aim of this study was to estimate the basic reproduction number (R0) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud in Northeastern Iran. The R0 of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The 30-day probable incidence and cumulative incidence were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using ‘earlyR’ and ‘projections’ packages in R software. The maximum-likelihood value of R0 was 2.7 (95% confidence interval (CI): 2.1−3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI 1.03–1.25) by the end of day 42. The expected average number of new cases in Shahroud was 9.0 ± 3.8 cases/day, which means an estimated total of 271 (95% CI: 178–383) new cases for the period between 02 April to 03 May 2020. By day 67 (27 April), the effective reproduction number (Rt), which had a descending trend and was around 1, reduced to 0.70. Based on the Rt for the last 21 days (days 46–67 of the epidemic), the prediction for 27 April to 26 May is a mean daily cases of 2.9 ± 2.0 with 87 (48–136) new cases. In order to maintain R below 1, we strongly recommend enforcing and continuing the current preventive measures, restricting travel and providing screening tests for a larger proportion of the population.

scholarly journals SARS2020: an integrated platform for identification of novel coronavirus by a consensus sequence-function model

2020 ◽  
Author(s):  
Dachuan Zhang ◽  
Tong Zhang ◽  
Sheng Liu ◽  
Dandan Sun ◽  
Shaozhen Ding ◽  
...  
Keyword(s):  
Biological Function ◽  
Consensus Sequence ◽  
Rapid Identification ◽  
Data Driven ◽  
Supplementary Information ◽  
Respiratory Syndrome Virus ◽  
The Novel ◽  
Function Model ◽  
Catalytic Function ◽  
Novel Coronavirus

Abstract Motivation The 2019 novel coronavirus outbreak has significantly affected global health and society. Thus, predicting biological function from pathogen sequence is crucial and urgently needed. However, little work has been conducted to identify viruses by the enzymes that they encode, and which are key to pathogen propagation. Results We built a comprehensive scientific resource, SARS2020, which integrates coronavirus-related research, genomic sequences and results of anti-viral drug trials. In addition, we built a consensus sequence-catalytic function model from which we identified the novel coronavirus as encoding the same proteinase as the severe acute respiratory syndrome virus. This data-driven sequence-based strategy will enable rapid identification of agents responsible for future epidemics. Availabilityand implementation SARS2020 is available at http://design.rxnfinder.org/sars2020/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Hybrid Method for Simulation of a Fractional COVID-19 Model with Real Case Application

Axioms ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 290
Author(s):  
Anwarud Din ◽  
Amir Khan ◽  
Anwar Zeb ◽  
Moulay Rchid Sidi Ammi ◽  
Mouhcine Tilioua ◽  
...  
Keyword(s):  
Hybrid Method ◽  
Reproduction Number ◽  
Real Data ◽  
The Novel ◽  
Order Analysis ◽  
The Laplace Transform ◽  
Case Application ◽  
Novel Coronavirus ◽  
Available Information ◽  
Fractional Orders

In this research, we provide a mathematical analysis for the novel coronavirus responsible for COVID-19, which continues to be a big source of threat for humanity. Our fractional-order analysis is carried out using a non-singular kernel type operator known as the Atangana-Baleanu-Caputo (ABC) derivative. We parametrize the model adopting available information of the disease from Pakistan in the period 9 April to 2 June 2020. We obtain the required solution with the help of a hybrid method, which is a combination of the decomposition method and the Laplace transform. Furthermore, a sensitivity analysis is carried out to evaluate the parameters that are more sensitive to the basic reproduction number of the model. Our results are compared with the real data of Pakistan and numerical plots are presented at various fractional orders.

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