Vitiligo is an autoimmune disease that results in patches of depigmented skin and hair. Previous genome-wide association studies (GWASs) of vitiligo have identified 50 susceptibility loci. Variants at the associated loci are generally common and have individually small effects on risk. Most vitiligo cases are ''simplex,'' where there is no family history of vitiligo, though occasional family clustering of vitiligo occurs, and some ''multiplex'' families report numerous close affected relatives. Here, we investigate whether simplex and multiplex vitiligo comprise different disease subtypes with different underlying genetic etiologies. We developed and compared the performance of several different vitiligo polygenic risk scores derived from GWAS data. By using the best-performing risk score, we find increased polygenic burden of risk alleles identified by GWAS in multiplex vitiligo cases relative to simplex cases. We additionally find evidence of polygenic transmission of common, low-effect-size risk alleles within multiplex-vitiligo-affected families. Our findings strongly suggest that family clustering of vitiligo involves a high burden of the same common, low-effect-size variants that are relevant in simplex cases. We furthermore find that a variant within the major histocompatibility complex (MHC) class II region contributes disproportionately more to risk in multiplex vitiligo cases than in simplex cases, supporting a special role for adaptive immune triggering in the etiology of multiplex cases. We suggest that genetic risk scores can be a useful tool in analyzing the genetic architecture of clinical disease subtypes and identifying subjects with unusual etiologies for further investigation.

In recent times, the Coronavirus disease (caused by COVID-19) is evidently observed to be the extremely contagious one with high fatality rate worldwide. In March 2020, the disease was declared a “global pandemic” by the World Health Organization (WHO). So far, there is no known/effective vaccine or medicine. In this paper, we propose and analyze an SEIR compartment model. We also compare and analyze the case study of India and Brazil. The model system is discussed by using MATLAB (2018a) software and the numerical results are verified graphically.

The dynamics of COVID-19 (Coronavirus Disease-2019) transmission are described using a fractional order SIQR model. The stability analysis of the model is performed. To obtain semi-analytic solutions to the model, the Iterative Laplace Transform Method [ILTM] is implemented. Real-time data from COVID-19 cases in India and Brazil is employed to estimate the parameters of the fractional order SIQR model. Numerical solutions obtained using Adam-Bashforth-Moulton predictor–corrector technique is compared with those obtained by ILTM. It is observed that the fractional order of the derivatives is more effective in studying the dynamics of the spread of COVID-19 in comparison to integral order of the SIQR model.

Infectious diseases have been a constant cause of disaster in human population. Simultaneously, it provides motivation for math and biology professionals to research and analyze the systems that drive such illnesses in order to predict their long-term spread and management. During the spread of such diseases several kinds of delay come into play, owing to changes in their dynamics. Here, we have studied a fractional order dynamical system of susceptible, exposed, infected, recovered and vaccinated population with a single delay incorporated in the infectious population accounting for the time period required by the said population to recover. We have employed Adam-Bashforth-Moulton technique for deriving numerical solutions to the model system. The stability of all equilibrium points has been analyzed with respect to the delay parameter. Utilizing actual data from India COVID-19 instances, the parameters of the fractional order SEIRV model were calculated. Graphical demonstration and numerical simulations have been done with the help of MATLAB (2018a). Threshold values of the time delay parameter have been found beyond which the system exhibits Hopf bifurcation and the solutions are no longer periodic.

In mid-March 2020, the World Health Organization declared COVID-19, a worldwide public health emergency. This paper presents a study of an SEIRV epidemic model with optimal control in the context of the Caputo fractional derivative of order . The stability analysis of the model is performed. We also present an optimum control scheme for an SEIRV model. The real time data for India COVID-19 cases have been used to determine the parameters of the fractional order SEIRV model. The Adam-Bashforth-Moulton predictor–corrector method is implemented to solve the SEIRV model numerically. For analyzing COVID-19 transmission dynamics, the fractional order of the SEIRV model is found to be better than the integral order. Graphical demonstration and numerical simulations are presented using MATLAB (2018a) software.

Introduction-While avalanche fatalities have remained relatively steady per year, data suggest a possible increase in sidecountry use and snowmobile fatalities. Limited information is known regarding the accident details and preparedness among different groups of backcountry users including snowmobiles, sidecountry, and backcountry skiers, and what specific factors could contribute to their fatalities.Methods-Avalanche fatality reports covering all US states posted by the Colorado Avalanche Information Center available online for 10 seasons (2009-2010 through 2018-2019 seasons) were analyzed for group size, specific equipment carried, burial depth, burial time, and other details. Only reports in the 3 following categories were included in the analysis: backcountry ski/snowboard, sidecountry ski/snowboard, and snowmobile/snowbike. These aspects were compared among the 3 tourer types using statistical analyses (ANOVA).Results-Two hundred and five fatalities were analyzed (n=32 sidecountry, n=91 skier/snowboard, n=82 snowmobile/snowbike). Using 2 preparedness scores, the ski/snowboard group had the greatest distribution of high scores when evaluated by equipment carried and group size, with significant differences per group (P<0.01). Of the fatalities that were buried, burial time was related to the tourer group (P=0.04), with the ski/snowboard group having the highest proportion of burials <15 min. Burial depth was significantly different among the 3 tourer groups, with snowmobiles buried the deepest on average (P<0.01).Conclusions-Despite limited data available on fatalities, an analysis of preparedness suggests that backcountry skiers and snowboarders are more prepared for avalanche accidents compared to snowmobiles and sidecountry users when evaluated by equipment carried and group size.

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In this manuscript, a fractional order SEIR model with vaccination has been proposed. The positivity and boundedness of the solutions have been verified. The stability analysis of the model shows that the system is locally as well as globally asymptotically stable at diseasefree equilibrium point E 0 when R 0 < 1 and at epidemic equilibrium E 1 when R 0 > 1. It has been found that introduction of the vaccination parameter η reduces the reproduction number R 0 . The parameters are identified using real-time data from COVID-19 cases in India. To numerically solve the SEIR model with vaccination, the Adam-Bashforth-Moulton technique is used. We employed MATLAB Software (Version 2018a) for graphical presentations and numerical simulations.. It has been observed that the SEIR model with fractional order derivatives of the dynamical variables is much more effective in studying the effect of vaccination than the integral model.