Modelling the effects of the contaminated environments on tuberculosis in Jiangsu, China.
TL;DR: This study formulate a novel TB epidemic model accounting for the effects of the contaminated environments on the TB transmission dynamics, and proves that the annual average of TB cases in Jiangsu province, China can be used to govern the threshold dynamics of the model.
About: This article is published in Journal of Theoretical Biology.The article was published on 2021-01-07 and is currently open access. It has received 21 citations till now.
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TL;DR: In this paper, a nonlinear mathematical model of the COVID-19 epidemic is proposed and analyzed under the effects of the environmental virus on the transmission patterns, and the sensitivity analysis is performed for the proposed model that determines the relative importance of the disease transmission parameters.
Abstract: COVID-19 is an infectious disease caused by the SARS-CoV-2 virus that caused an outbreak of typical pneumonia first in Wuhan and then globally. Although researchers focus on the human-to-human transmission of this virus but not much research is done on the dynamics of the virus in the environment and the role humans play by releasing the virus into the environment. In this paper, a novel nonlinear mathematical model of the COVID-19 epidemic is proposed and analyzed under the effects of the environmental virus on the transmission patterns. The model consists of seven population compartments with the inclusion of contaminated environments means there is a chance to get infected by the virus in the environment. We also calculated the threshold quantity R 0 to know the disease status and provide conditions that guarantee the local and global asymptotic stability of the equilibria using Volterra-type Lyapunov functions, LaSalle’s invariance principle, and the Routh–Hurwitz criterion. Furthermore, the sensitivity analysis is performed for the proposed model that determines the relative importance of the disease transmission parameters. Numerical experiments are performed to illustrate the effectiveness of the obtained theoretical results.
18 citations
TL;DR: Qualitative theoretical analysis proves that the existence, local stability and global stability of the equilibria are all related to the daily emission P0 of PM2.5 and the SISP respiratory disease model.
Abstract: In this paper, the actual background of the susceptible population being directly patients after inhaling a certain amount of PM is taken into account. The concentration response function of PM is introduced, and the SISP respiratory disease model is proposed. Qualitative theoretical analysis proves that the existence, local stability and global stability of the equilibria are all related to the daily emission of PM and PM pathogenic threshold K. Based on the sensitivity factor analysis and time-varying sensitivity analysis of parameters on the number of patients, it is found that the conversion rate β and the inhalation rate η has the largest positive correlation. The cure rate γ of infected persons has the greatest negative correlation on the number of patients. The control strategy formulated by the analysis results of optimal control theory is as follows: The first step is to improve the clearance rate of PM by reducing the PM emissions and increasing the intensity of dust removal. Moreover, such removal work must be maintained for a long time. The second step is to improve the cure rate of patients by being treated in time. After that, people should be reminded to wear masks and go out less so as to reduce the conversion rate of susceptible people becoming patients.
4 citations
TL;DR: In this article , an SVEITR dynamical model with vaccination, fast and slow progression, incomplete treatment, and relapse was proposed and a Markov chain Monte-Carlo method was used to acquire the model's optimal parameters.
4 citations
TL;DR: In this article , a penalized distributed lag nonlinear model was applied to explore the influence of meteorological factors (such as air temperature, relative humidity and wind speed) on the PTB incidence in Xinjiang from 2004 to 2019.
Abstract: Pulmonary tuberculosis (PTB) has been a major threat to global public health. The association between meteorological factors and the incidence of PTB has been widely investigated by the generalized additive model, auto-regressive integrated moving average model and the distributed lag model, etc. However, these models could not address a non-linear or lag correlation between them. In this paper, a penalized distributed lag non-linear model, as a generalized and improved one, was applied to explore the influence of meteorological factors (such as air temperature, relative humidity and wind speed) on the PTB incidence in Xinjiang from 2004 to 2019. Moreover, we firstly use a comprehensive index (apparent temperature, AT) to access the impact of multiple meteorological factors on the incidence of PTB. It was found that the relationships between air temperature, relative humidity, wind speed, AT and PTB incidence were nonlinear (showed “wave-type “, “invested U-type”, “U-type” and “wave-type”, respectively). When air temperature at the lowest value (−16.1 °C) could increase the risk of PTB incidence with the highest relative risk (RR = 1.63, 95% CI: 1.21–2.20). An assessment of relative humidity demonstrated an increased risk of PTB incidence between 44.5% and 71.8% with the largest relative risk (RR = 1.49, 95% CI: 1.32–1.67) occurring at 59.2%. Both high and low wind speeds increased the risk of PTB incidence, especially at the lowest wind speed 1.4 m/s (RR = 2.20, 95% CI: 1.95–2.51). In particular, the lag effects of low and high AT on PTB incidence were nonlinear. The lag effects of extreme cold AT (−18.5 °C, 1st percentile) on PTB incidence reached a relative risk peak (RR = 2.18, 95% CI: 2.06–2.31) at lag 1 month. Overall, it was indicated that the environment with low air temperature, suitable relative humidity and wind speed is more conducive to the transmission of PTB, and low AT is associated significantly with increased risk of PTB in Xinjiang.
4 citations
01 Jan 2022
TL;DR: In this article , a new influenza model with vaccination and periodic transmission rate is introduced, and the basic reproduction number R 0 is derived, and formulate that R., sub> 0, is an important indicator to measure whether seasonal influenza can spread in the population.
Abstract: Seasonal influenza is still prevalent and poses a huge health burden, which is the most worth considerable issue that causes economic pressure on the government. Investigating the essential characteristics of seasonal influenza can assist to improve people's vigilance. A new influenza model with vaccination and periodic transmission rate is introduced in this essay. The basic reproduction number R 0 is derived, and formulate that R 0 is an important indicator to measure whether seasonal influenza can spread in the population. Furthermore, the explicit consequences for the implementation of optimal control and the corresponding optimal solutions to alleviate the spread of influenza virus are explored and derived. The best fitting parameters in our model are determined from the seasonal influenza case data reported in Gansu Province via MCMC procedure. The value of R 0 is 1.2266(95%CI : (1.2230, 1.2302)) by estimating unknown parameters. The different vigorous control strategies for controlling the transmission of seasonal influenza are also studied and simulated. Finally, the uncertainty and sensitivity of some parameters are shown to determine which critical control strategy is effective. Our numerical results imply that raising the vaccination rate can availably reduce the spread of seasonal influenza in Gansu Province, and vaccination is a more effective method than treatment.
2 citations
References
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TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Abstract: Copyright (©) 1999–2012 R Foundation for Statistical Computing. Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions, except that this permission notice may be stated in a translation approved by the R Core Team.
272,030 citations
"Modelling the effects of the contam..." refers methods in this paper
...The model simulations are conducted by using the software R (version 3.6.3) (Team, 2013)....
[...]
[...]
01 Jan 2012
139,059 citations
"Modelling the effects of the contam..." refers methods in this paper
...This Q appears to be a simplified version of quantifying the time-varying 213 (effective) reproduction number by the serial interval approach as studied and implemented in 214 [33, 34, 35]....
[...]
TL;DR: The epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of patients with laboratory-confirmed 2019-nCoV infection in Wuhan, China, were reported.
36,578 citations
TL;DR: There is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019 and considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere.
Abstract: Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the...
13,101 citations
TL;DR: A precise definition of the basic reproduction number, R0, is presented for a general compartmental disease transmission model based on a system of ordinary differential equations and it is shown that, if R0<1, then the disease free equilibrium is locally asymptotically stable; whereas if R 0>1,Then it is unstable.
Abstract: A precise definition of the basic reproduction number, Ro, is presented for a general compartmental disease transmission model based on a system of ordinary dierential equations. It is shown that, if Ro 1, then it is unstable. Thus,Ro is a threshold parameter for the model. An analysis of the local centre manifold yields a simple criterion for the existence and stability of super- and sub-threshold endemic equilibria for Ro near one. This criterion, together with the definition of Ro, is illustrated by treatment, multigroup, staged progression, multistrain and vectorhost models and can be applied to more complex models. The results are significant for disease control.
7,106 citations