scholarly journals Assessment of Vaccination and Underreporting on COVID-19 Infections in Turkey Based On Effective Reproduction Number

Author(s):  
Tuğba Akman Yıldız ◽  
Emek Köse ◽  
Necibe Tuncer

AbstractIn this paper, we introduce a SEIR type COVID-19 model where the infected class is further divided into individuals in intensive care (ICUs) and ventilation units. The model is validated with the COVID-19 cases, deaths, and the number of patients in ICUs and ventilation units as reported by Turkey Department of Health for the period March 11 through May 30 when the nationwide lockdown is in order. COVID-19 interventions in Turkey are incorporated into the model to detect the future trend of the outbreak accurately. The lockdown is lifted on June 1, and the model is modified to include a time dependent transmission rate which is linked to the effective reproduction number ℛt through basic reproduction number ℛ0. The modified model captures the changing dynamics and peaks of the outbreak successfully. With the onset of vaccination on 13 January 2021, we augment the model with the vaccination class to investigate the impact of vaccination rate and efficacy. We observe that vaccination rate is a more critical parameter than the vaccine efficacy to eliminate the disease successfully.

2020 ◽  
Author(s):  
Eduardo Atem De Carvalho ◽  
Rogerio Atem De Carvalho

BACKGROUND Since the beginning of the COVID-19 pandemic, researchers and health authorities have sought to identify the different parameters that govern their infection and death cycles, in order to be able to make better decisions. In particular, a series of reproduction number estimation models have been presented, with different practical results. OBJECTIVE This article aims to present an effective and efficient model for estimating the Reproduction Number and to discuss the impacts of sub-notification on these calculations. METHODS The concept of Moving Average Method with Initial value (MAMI) is used, as well as a model for Rt, the Reproduction Number, is derived from experimental data. The models are applied to real data and their performance is presented. RESULTS Analyses on Rt and sub-notification effects for Germany, Italy, Sweden, United Kingdom, South Korea, and the State of New York are presented to show the performance of the methods here introduced. CONCLUSIONS We show that, with relatively simple mathematical tools, it is possible to obtain reliable values for time-dependent, incubation period-independent Reproduction Numbers (Rt). We also demonstrate that the impact of sub-notification is relatively low, after the initial phase of the epidemic cycle has passed.


J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 86-100
Author(s):  
Nita H. Shah ◽  
Ankush H. Suthar ◽  
Ekta N. Jayswal ◽  
Ankit Sikarwar

In this article, a time-dependent susceptible-infected-recovered (SIR) model is constructed to investigate the transmission rate of COVID-19 in various regions of India. The model included the fundamental parameters on which the transmission rate of the infection is dependent, like the population density, contact rate, recovery rate, and intensity of the infection in the respective region. Looking at the great diversity in different geographic locations in India, we determined to calculate the basic reproduction number for all Indian districts based on the COVID-19 data till 7 July 2020. By preparing district-wise spatial distribution maps with the help of ArcGIS 10.2, the model was employed to show the effect of complete lockdown on the transmission rate of the COVID-19 infection in Indian districts. Moreover, with the model's transformation to the fractional ordered dynamical system, we found that the nature of the proposed SIR model is different for the different order of the systems. The sensitivity analysis of the basic reproduction number is done graphically which forecasts the change in the transmission rate of COVID-19 infection with change in different parameters. In the numerical simulation section, oscillations and variations in the model compartments are shown for two different situations, with and without lockdown.


BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
James D. Munday ◽  
Christopher I. Jarvis ◽  
Amy Gimma ◽  
Kerry L. M. Wong ◽  
Kevin van Zandvoort ◽  
...  

Abstract Background Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear. Methods We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. Results Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone. Conclusion Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening.


2019 ◽  
Vol 12 (07) ◽  
pp. 1950073 ◽  
Author(s):  
A. O. Egonmwan ◽  
D. Okuonghae

Since 1921, the Bacille Calmette–Guerin (BCG) vaccine continues to be the most widely used vaccine for the prevention of Tuberculosis (TB). However, the immunity induced by BCG wanes out after some time making the vaccinated individual susceptible to TB infection. In this work, we formulate a mathematical model that incorporates the vaccination of newly born children and older susceptible individuals in the transmission dynamics of TB in a population, with a vaccine that can confer protection on older susceptible individuals. In the absence of disease-induced deaths, the model is shown to undergo the phenomenon of backward bifurcation where a stable disease-free equilibrium (DFE) co-exists with a stable positive (endemic) equilibrium when the associated reproduction number is less than unity. It is shown that this phenomenon does not exist in the absence of imperfect vaccine, exogenous reinfection, and reinfection of previously treated individuals. It is further shown that a special case of the model has a unique endemic equilibrium point (EEP), which is globally asymptotically stable when the associated reproduction number exceeds unity. Uncertainty and sensitivity analysis are carried out to identify key parameters that have the greatest influence on the transmission dynamics of TB in the population using the total population of latently infected individuals, total number of actively infected individuals, disease incidence, and the effective reproduction number as output responses. The analysis shows that the top five parameters of the model that have the greatest influence on the effective reproduction number of the model are the transmission rate, the fraction of fast disease progression, modification parameter which accounts for reduced likelihood to infection by vaccinated individuals due to imperfect vaccine, rate of progression from latent to active TB, and the treatment rate of actively infected individuals, with other key parameters influencing the outcomes of the other output responses. Numerical simulations suggest that with higher vaccination rate of older susceptible individuals, fewer new born children need to be vaccinated, in order to achieve disease eradication.


2016 ◽  
Vol 10 (01) ◽  
pp. 1750003
Author(s):  
Maoxing Liu ◽  
Lixia Zuo

A three-dimensional compartmental model with media coverage is proposed to describe the real characteristics of its impact in the spread of infectious diseases in a given region. A piecewise continuous transmission rate is introduced to describe that media coverage exhibits its effect only when the number of the infected exceeds a certain critical level. Further, it is assumed that the impact of media coverage on the contact transmission is described by an exponential decreasing factor. Stability analysis of the model shows that the disease-free equilibrium is globally asymptotically stable if the basic reproduction number is less than unity. On the other hand, when the basic reproduction number is greater than unity and media coverage impact is sufficiently small, a unique endemic equilibrium exists, which is globally asymptotically stable.


2020 ◽  
Author(s):  
Jie Zhu ◽  
Blanca Gallego

Abstract To date, many studies have argued the potential impact of public health interventions on flattening the epidemic curve of SARS-CoV-2. Most of them have focused on simulating the impact of interventions in a region of interest by manipulating contact patterns and key transmission parameters to reflect different scenarios. Our study looks into the evolution of the daily effective reproduction number during the epidemic via a stochastic transmission model. We found this measure (although model-dependent) provides an early signal of the efficacy of containment measures. This epidemiological parameter when updated in real-time can also provide better predictions of future outbreaks. Our results found a substantial variation in the effect of public health interventions on the dynamic of SARS-CoV-2 transmission over time and across countries, that could not be explained solely by the timing and number of the adopted interventions. This suggests that further knowledge about the idiosyncrasy of their implementation and effectiveness is required. Although sustained containment measures have successfully lowered growth in disease transmission, more than half of the 101 studied countries failed to maintain the effective reproduction number close to or below 1. This resulted in continued growth in reported cases. Finally, we were able to predict with reasonable accuracy which countries would experience outbreaks in the next 30 days.


2021 ◽  
Author(s):  
quentin Griette ◽  
Jacques Demongeot ◽  
pierre magal

Background: The COVID-19 epidemic, which started in late December 2019 and rapidly spread throughout the world, was accompanied by an unprecedented release of reported case data. Our objective is to propose a fresh look at this data by coupling a phenomenological description to the epidemiological dynamics. Methods: We use a phenomenological model to describe and regularize the data. This model can be matched by a single mathematical model reproducing the epidemiological dynamics with a time-dependent transmission rate. We provide a method to compute this transmission rate and reconstruct the changes in the social interactions between people as well as changes in host-pathogen interactions. This method is applied to the cumulative case data of 8 different geographic areas. Findings: We reconstruct the transmission rate from the data, therefore we are in position to understand the contribution of the dynamical effects of social interactions (contacts between individuals) and the contribution of the dynamics of the epidemic. We deduce from the comparison of several instantaneous reproduction numbers that the social effects are the most important in the dynamic of COVID-19. We obtain an instantaneous reproduction number that stays below $3.5$ from early beginning of the epidemic. Conclusion: The instantaneous reproduction number staying below $3.5$ implies that it is sufficient to vaccinate $71\%$ of the population in each state or country considered in our study. Therefore assuming the vaccines will remain efficient against the new variants, and to be more confident it is sufficient to vaccinate $75-80\%$ to get rid of COVID-19 in each state or country. Funding: This research was funded by the Agence Nationale de la Recherche in France (Project name: MPCUII (PM) and (QG))


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 2014-2014
Author(s):  
Asad Bashey ◽  
Xu Zhang ◽  
Lawrence E Morris ◽  
H. Kent Holland ◽  
Scott R. Solomon ◽  
...  

Relapse of leukemia (RL) is the most common cause of treatment failure following allogeneic hematopoietic cell transplantation (alloHCT) in patients with AML. Historically, patients who suffer RL following alloHCT have had a dismal prognosis. A number of therapeutic options have recently become available for relapsed/refractory AML, including some that are associated with limited toxicity and may be well tolerated in the post-alloHCT setting. These therapies, and advances in supportive care have the potential to prolong survival of recently transplanted patients who suffer RL post post-alloHCT compared to prior cohorts. We hypothesized that patients suffering RL post-alloHCT within the last 5 years will have improved post-relapse survival compared to patients experiencing RL before this period. In order to test this hypothesis, we analyzed 309 patients who underwent a first allo-HCT for AML between Jan 2002 and Dec 2016 at our center and identified 112 patients (36%) who suffered RL post-alloHCT. Data were extracted from our institutional BMT database where they had been prospectively entered. Patient characteristics of those who experienced RL were: median age 53 (19-74); male - 51%; race- white-86%, black 12%, Asian -2%; donor-MRD 33%, MUD 41%, Haplo 26%; graft source - PBSC 86%, BM 11%, CBU 2%, PBSC+BM 1%; regimen intensity - MAC 61%, NST/RIC 39%%; DRI - intermediate 46%, high 50%, v. high 5%; HCT-CI 0-2 (58%), >3 (42%); KPS > 90 (39%) <90 (61%), CMV - pos 70%, neg 29%, year of relapse -2003-2013 (68%), 2014-2018 (32%). Median time from alloHCT to relapse was 170 days (25-1106). Median follow-up of surviving patients was 50 months (15-143). DLI: A first DLI was administered to 19 patients at a median of 41 days post relapse. The corresponding number of patients receiving 2nd, 3rd and 4th DLI were 12, 6 and 2 patients given at a median of 62, 48 and 38 days following the prior DLI. A second alloHCT post RL was performed in 33 patients (29%) at a median of 85 days (22-772d) post relapse using the same donor as the first allo-HCT in 45% and a different donor in 55%. The second transplant was from a MRD, MUD and Haplo donor in 10, 11 and 12 patients respectively. Estimates of post-relapse survival at 1, 2 and 3 years following relapse for all patients are 39%, 23% and 15% (Fig 1). For patients whose AML relapsed between 2003-2013, and 2014-2018 estimated 1, 2, and 3 year survival rates following relapse were 34%, 18% and 9% vs 50%, 32% and 28% respectively (p=0.017, Fig 2). A multivariable Cox model was developed for post-relapse survival considering the following variables: at relapse, gender, race, time from transplant to relapse, donor type, graft source, regimen intensity DRI, HCT-CI, KPS, CMV status, DLI post relapse , second alloHCT post relapse, year of relapse. Second alloHCT post-relapse was tested as a time-dependent covariate. Variables were selected if the p value was less than 0.05. Proportionality was tested for selected variables and all variables passed the test. On multivariable analysis, survival was significantly better for patients who relapsed in 2014-2018 vs patients relapsing in prior years (2003-2013) - HR 0.55. p=0.018. Other variables associated with post-relapse survival were time from BMT to relapse >250 d vs <100 d - HR 0.55, p=0.025 and haplo donor vs MRD for first alloHCT- HR 2.41, p=0.002. The use of DLI or the occurrence of a second alloHCT post-relapse tested as a time-dependent co-variate were not significantly associated with survival in this analysis. These data suggest that survival for AML patients who suffer relapse of malignancy following alloHCT has improved in recent cohorts when compared to historic controls. Approximately one-half and one-third of the patients are now estimated to live 1 and 2 years following relapse and prolonged survival is possible in some cases. The impact of specific interventions that help promote survival following relapse should be further studied Disclosures Solh: ADC Therapeutics: Research Funding; Celgene: Speakers Bureau; Amgen: Speakers Bureau.


2021 ◽  
Author(s):  
MUSA RABIU ◽  
Sarafa A. Iyaniwura

Abstract We developed an endemic model of COVID-19 to assess the impact of vaccination and immunity waning on the dynamics of the disease. Our model exhibits the phenomenon of backward bifurcation and bi-stability, where a stable disease-free equilibrium co-exists with a stable endemic equilibrium. The epidemiological implication of this is that the control reproduction number being less than unity is no longer sufficient to guarantee disease eradication. We showed that this phenomenon could be eliminated by either increasing the vaccine efficacy or by reducing the disease transmission rate (adhering to non-pharmaceutical interventions). Furthermore, we numerically investigated the impacts of vaccination and waning of both vaccine-induced immunity and post-recovery immunity on the disease dynamics. Our simulation results show that the waning of vaccine-induced immunity has more effect on the disease dynamics relative to post-recovery immunity waning, and suggests that more emphasis should be on reducing the waning of vaccine-induced immunity to eradicate COVID-19.


Author(s):  
Tanvi ◽  
Mohammad Sajid ◽  
Rajiv Aggarwal ◽  
Ashutosh Rajput

In this paper, we have proposed a nonlinear mathematical model of different classes of individuals for coronavirus (COVID-19). The model incorporates the effect of transmission and treatment on the occurrence of new infections. For the model, the basic reproduction number [Formula: see text] has been computed. Corresponding to the threshold quantity [Formula: see text], the stability of endemic and disease-free equilibrium (DFE) points are determined. For [Formula: see text], if the endemic equilibrium point exists, then it is locally asymptotically stable, whereas the DFE point is globally asymptotically stable for [Formula: see text] which implies the eradication of the disease. The effects of various parameters on the spread of COVID-19 are discussed in the segment of sensitivity analysis. The model is numerically simulated to understand the effect of reproduction number on the transmission dynamics of the disease COVID-19. From the numerical simulations, it is concluded that if the reproduction number for the coronavirus disease is reduced below unity by decreasing the transmission rate and detecting more number of infectives, then the epidemic can be eradicated from the population.


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