Forecasting of Indian tourism industry using modeling approach.

Currently, India has become one of the largest economies of the world in which tourism and hospitality have significantly contributed; however, the growth rate of tourism industry has been greatly affected during the COVID-19 pandemic. In this study, we have used the modeling approach to analyze and understand the growth pattern of Indian tourism industry. To achieve this, we consider the data of international tourist arrivals before and after the lockdown. The Dickey-Fuller test, AIC and BIC methods are used to obtain the best fitted model and further, the accuracy of obtained model is also analyzed. Data and forecasting indicate that the weather and public holidays significantly affect the tourism industry.

Analysing an epidemic-economic model in the presence of novel corona virus infection: capital stabilization, media effect, and the role of vaccine.

The pandemic being a health issue at its core is a multifaceted crisis encompassing both economic and epidemic factors in a twisted tale of challenges. In counteraction, we have proposed a combined epidemic-economic model that analyses system dynamics arising in the presence of an infectious disease (SARS-2-COVID-19 in our case). Dynamical analysis of the system has been performed in context to the equilibria along with local and global stability analysis of the system simultaneously visualizing the effect on capital stabilization. The global stability analysis has been performed using graph-theoretic method. Curve-Fit has been performed for the system using optimization algorithm. The relation between all the parameters and variables involved in the model has been explored by calculating sensitivity indices which gives us the proportion that a relative change in a parameter brings to the relative change in a variable. Our findings reveal that (1) Vaccination instigates economic growth (with evidence of data obtained for 24 countries). (2) Complete vaccination leads to a considerable reduction in all infections (reduction up to 90%, as per current CDC study). (3) Excessive exposure to media can facilitate spike in infections. (4) Parameter sensitivity analysis can be of immense help in policy formation.

Dynamics of a stage-structured SI model for food adulteration with media-induced response function.

In this work, an eco-epidemic predator-prey model with media-induced response function for the interaction of humans with adulterated food is developed and studied. The human population is divided into two main compartments, namely, susceptible and infected. This system has three equilibria; trivial, disease-free and endemic. The trivial equilibrium is forever an unstable saddle position, while the disease-free state is locally asymptotically stable under a threshold of delay parameter τ as well as R 0 < 1 . The sufficient conditions for the local stability of the endemic equilibrium point are further explored when min { R 0 , R 0 ∗ } > 1 . The conditions for the occurrence of the stability switching are also determined by taking infection delay time as a critical parameter, which concludes that the delay can produce instability and small amplitude oscillations of population masses via Hopf bifurcations. Further, we study the stability and direction of the Hopf bifurcations using the center manifold argument. Furthermore, some numerical simulations are conducted to validate our analytical findings and discuss their biological inferences. Finally, the normalized forward sensitivity index is used to perform the sensitivity analysis of R 0 and R 0 ∗ .

Optical Flow Methods for Lung Nodule Segmentation on LIDC-IDRI Images.

Lung nodule segmentation is an essential step in any CAD system for lung cancer detection and diagnosis. Traditional approaches for image segmentation are mainly morphology based or intensity based. Motion-based segmentation techniques tend to use the temporal information along with the morphology and intensity information to perform segmentation of regions of interest in videos. CT scans comprise of a sequence of dicom 2-D image slices similar to videos which also comprise of a sequence of image frames ordered on a timeline. In this work, Farneback, Horn-Schunck and Lucas-Kanade optical flow methods have been used for processing the dicom slices. The novelty of this work lies in the usage of optical flow methods, generally used in motion-based segmentation tasks, for the segmentation of nodules from CT images. Since thin-sliced CT scans are the imaging modality considered, they closely approximate the motion videos and are the primary motivation for using optical flow for lung nodule segmentation. This paper also provides a detailed comparative analysis and validates the effectiveness of using optical flow methods for segmentation. Finally, we propose methods to further improve the efficiency of segmentation using optical flow methods on CT scans.

Dynamics of cholera epidemics with impulsive vaccination and disinfection.

Waterborne diseases have a tremendous influence on human life. The contaminated drinking water causes water-borne disease like cholera. Pulse vaccination is an important and effective strategy for the elimination of infectious diseases. A waterborne disease like cholera can also be controlled by using impulse technique. In this paper, we have proposed a delayed SEIRB epidemic model with impulsive vaccination and disinfection. We have studied the pulse vaccination strategy and sanitation to control the cholera disease. The existence and stability of the disease-free and endemic periodic solution are investigated both analytically and numerically. It is shown that there exists an infection-free periodic solution, using the impulsive dynamical system defined by the stroboscopic map. It is observed that the infection-free periodic solution is globally attractive when the impulse period is less than some critical value. From the analysis of the model, we have obtained a sufficient condition for the permanence of the epidemic with pulse vaccination. The main highlight of this paper is to introduce impulse technique along with latent period into the SEIRB epidemic model to investigate the role of pulse vaccination and disinfection on the dynamics of the cholera epidemics.

Dynamics of an SEQIHRS epidemic model with media coverage, quarantine and isolation in a community with pre-existing immunity.

An autonomous deterministic non-linear epidemic model SEQIHRS is proposed for the transmission dynamics of an infectious disease with quarantine and isolation control strategies in a community with pre-existing immunity. The model exhibits two equilibria, namely, the disease-free and a unique endemic equilibrium. The existence and local stability of the disease free and endemic equilibria are explored in terms of the effective reproduction number R C . It is observed that media coverage does not affect the effective reproduction number, but it helps to mitigate disease burden by lowering the number of infectious individuals at the endemic steady state and also lowering the infection peak. A new approach is proposed to estimate the coefficient of media coverage. Using the results of central manifold theory, it is established that as R C passes through unity, transcritical bifurcation occurs in the system and the unique endemic equilibrium is asymptotically stable. It is observed that the population level impact of quarantine and isolation depend on the level of transmission by the isolated individuals. Moreover, the higher level of pre-existing immunity in the population decreases the infection peak and causes its early arrival. Theoretical findings are supported by numerical simulation. Sensitivity analysis is performed for R C and state variables at endemic steady state with respect to model parameters.