Yun Niu

Bio: Yun Niu is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

Modeling the effects of the contaminated environments on COVID-19 transmission in India.

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.

Dynamic analysis and optimal control of a class of SISP respiratory diseases

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.

Study on the Associations between Meteorological Factors and the Incidence of Pulmonary Tuberculosis in Xinjiang, China

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.

Modelling the effects of the vaccination on seasonal influenza in gansu, china

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 R₀ is derived, and formulate that R₀ 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 R₀ 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.