scholarly journals Epidemiology study of SARS-CoV-2 pandemic in India, the first and second wave

2021 ◽  
Author(s):  
Dwaipayan Chaudhuri ◽  
Joyeeta Datta ◽  
Satyabrata Majumder ◽  
Kalyan Giri
Keyword(s):  
Statistical Analysis ◽  
Epidemic Model ◽  
Age Distribution ◽  
Age Groups ◽  
Salient Feature ◽  
Age Group ◽  
Sir Epidemic Model ◽  
Sir Epidemic ◽  
And Gender ◽  
Second Wave

Background and objectives: SARS-CoV-2 has wrecked the world for the past 17 months. India has been hit by the second wave of the virus which has been characterized by new symptoms. This study focuses on the pattern of infection over the last 13 months utilizing epidemic model to predict course of the pandemic. Material and methods: The data was collected from covid19india.org to perform analysis based on age and gender distribution. Statistical analysis was performed to determine the relation between confirmed and recovered cases while SIR epidemic model was used to determine the course of the pandemic in the country and the changes that have occurred from the first to the second wave. Results and discussions: Results show infectivity rate to be higher in ages 20-50 while mortality is higher in 50-80 age group while 60-70% of the infected population are males. Each of the 9 states have their own salient feature curves of infection. It was seen that the confirmed and recovered cases are more correlated at present than previous wave. The curves for both waves show a polynomial distribution while the reproduction number data shows an almost U-shaped curve indicating decrease of infection spread in the middle phase when the first wave was on a decline before picking up again owing to the second wave. Interpretations and conclusion: The gender and age distribution shows that although lower age group is more infected, mortality is high for higher age groups, on the other hand males are more prone to the infection. The statistical analysis shows the nature of spread of the disease, the data of which is quantified by the SIR model based study.

scholarly journals Estimating effective infection fatality rates during the course of the COVID-19 pandemic in Germany

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Christian Staerk ◽  
Tobias Wistuba ◽  
Andreas Mayr
Keyword(s):  
Age Distribution ◽  
Age Groups ◽  
Case Fatality ◽  
Time Dependent ◽  
Temporary Increase ◽  
International Studies ◽  
Age Group ◽  
Fatality Rate ◽  
Substantial Fraction ◽  
Second Wave

Abstract Background The infection fatality rate (IFR) of the Coronavirus Disease 2019 (COVID-19) is one of the most discussed figures in the context of this pandemic. In contrast to the case fatality rate (CFR), the IFR depends on the total number of infected individuals – not just on the number of confirmed cases. In order to estimate the IFR, several seroprevalence studies have been or are currently conducted. Methods Using German COVID-19 surveillance data and age-group specific IFR estimates from multiple international studies, this work investigates time-dependent variations in effective IFR over the course of the pandemic. Three different methods for estimating (effective) IFRs are presented: (a) population-averaged IFRs based on the assumption that the infection risk is independent of age and time, (b) effective IFRs based on the assumption that the age distribution of confirmed cases approximately reflects the age distribution of infected individuals, and (c) effective IFRs accounting for age- and time-dependent dark figures of infections. Results Effective IFRs in Germany are estimated to vary over time, as the age distributions of confirmed cases and estimated infections are changing during the course of the pandemic. In particular during the first and second waves of infections in spring and autumn/winter 2020, there has been a pronounced shift in the age distribution of confirmed cases towards older age groups, resulting in larger effective IFR estimates. The temporary increase in effective IFR during the first wave is estimated to be smaller but still remains when adjusting for age- and time-dependent dark figures. A comparison of effective IFRs with observed CFRs indicates that a substantial fraction of the time-dependent variability in observed mortality can be explained by changes in the age distribution of infections. Furthermore, a vanishing gap between effective IFRs and observed CFRs is apparent after the first infection wave, while an increasing gap can be observed during the second wave. Conclusions The development of estimated effective IFR and observed CFR reflects the changing age distribution of infections over the course of the COVID-19 pandemic in Germany. Further research is warranted to obtain timely age-stratified IFR estimates, particularly in light of new variants of the virus.

scholarly journals Survival in a cohort of patients with lung cancer: the role of age and gender in prognosis

2017 ◽  
Vol 43 (6) ◽  
pp. 431-436 ◽  
Author(s):  
Juliana Pereira Franceschini ◽  
Sérgio Jamnik ◽  
Ilka Lopes Santoro
Keyword(s):  
Lung Cancer ◽  
Age Distribution ◽  
Age Groups ◽  
Rank Test ◽  
Age Group ◽  
Tertiary Referral Hospital ◽  
Kaplan Meier ◽  
Stage Disease ◽  
And Gender ◽  
Disease Stages

ABSTRACT Objective: To determine the demographic and clinical characteristics of patients with non-small cell lung cancer (NSCLC), as well as their disease course, by age group and gender. Methods: This was a retrospective cohort study of patients diagnosed with NSCLC from 2000 to 2012 and followed until July 2015 in a tertiary referral hospital in the city of São Paulo, Brazil. Based on the 25th and 75th percentiles of the age distribution, patients were stratified into three age groups: < 55 years; ≥ 55 and < 72 years; and ≥ 72 years. Survival time was evaluated during the follow-up period of the study. Functions of overall and gender-specific survival stratified by age groups (event: all-cause mortality) were calculated using the Kaplan-Meier method. Differences among survival curves were assessed via the log-rank test. Results: We included 790 patients with the following age distribution: < 55 years, 165 patients; ≥ 55 and < 72 years, 423; and ≥ 72 years, 202. In the entire sample, there were 493 men (62.4%). Adenocarcinoma was the most common histological pattern in the < 72-year age groups; 575 patients (73%) presented with advanced disease (stages IIIB-IV). The median 5-year survival was 12 months (95% CI: 4-46 months), with no significant differences among the age groups studied. Conclusions: NSCLC remains more common in men, although we found an increase in the proportion of the disease in women in the < 55-year age group. Adenocarcinoma predominated in women. In men, squamous cell carcinoma predominated in the ≥ 72-year age group. Most patients presented with advanced-stage disease at diagnosis. There were no statistical differences in survival between genders or among age groups.

Analisis Titik Kesetimbangan Dan Kestabilan Penyebaran Penyakit Malaria di Distrik Manokwari Barat Berdasarkan Model Epidemik SIR

2012 ◽  
Vol 8 (2) ◽  
Author(s):  
Fandy Fandy ◽  
Andi Fajeriani Wyrasti ◽  
Tri Widjajanti
Keyword(s):  
Epidemic Model ◽  
Sir Epidemic Model ◽  
Endemic Diseases ◽  
Sir Epidemic

<em>Stability and equilibrium of malaria&rsquo;s epidemics in Manokwari Barat district based on SIR epidemic model will be discussed in this paper. The SIR epidemic model can be applied to make a model of endemic diseases like malaria. Based on this research, there are 2 types of the equilibrium of malaria&rsquo;s epidemics in Manokwari Barat District, endemic and non endemic point.</em>

scholarly journals Global dynamics of a novel deterministic and stochastic SIR epidemic model with vertical transmission and media coverage

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Xiaodong Wang ◽  
Chunxia Wang ◽  
Kai Wang
Keyword(s):  
Vertical Transmission ◽  
Epidemic Model ◽  
Media Coverage ◽  
Existence And Uniqueness ◽  
Deterministic Model ◽  
Reproduction Number ◽  
Global Dynamics ◽  
Sir Epidemic Model ◽  
Sir Epidemic ◽  
Stochastic Sir

AbstractIn this paper, we study a novel deterministic and stochastic SIR epidemic model with vertical transmission and media coverage. For the deterministic model, we give the basic reproduction number $R_{0}$ R 0 which determines the extinction or prevalence of the disease. In addition, for the stochastic model, we prove existence and uniqueness of the positive solution, and extinction and persistence in mean. Furthermore, we give numerical simulations to verify our results.

scholarly journals Stability and Hopf Bifurcation for a Delayed SIR Epidemic Model with Logistic Growth

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Yakui Xue ◽  
Tiantian Li
Keyword(s):  
Incidence Rate ◽  
Epidemic Model ◽  
Threshold Value ◽  
Endemic Equilibrium ◽  
Logistic Growth ◽  
Global Dynamics ◽  
Asymptotically Stable ◽  
Sir Epidemic Model ◽  
Globally Asymptotically Stable ◽  
Sir Epidemic

We study a delayed SIR epidemic model and get the threshold value which determines the global dynamics and outcome of the disease. First of all, for anyτ, we show that the disease-free equilibrium is globally asymptotically stable; whenR0<1, the disease will die out. Directly afterwards, we prove that the endemic equilibrium is locally asymptotically stable for anyτ=0; whenR0>1, the disease will persist. However, for anyτ≠0, the existence conditions for Hopf bifurcations at the endemic equilibrium are obtained. Besides, we compare the delayed SIR epidemic model with nonlinear incidence rate to the one with bilinear incidence rate. At last, numerical simulations are performed to illustrate and verify the conclusions.

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