Upheaval in cancer care during the COVID-19 outbreak

On Monday, 23 March 2020, Nigeria recorded its first mortality from the novel global COVID-19 outbreak. Before this, the country reported 36 confirmed cases (at the time of writing) and has discharged home two cases after weeks of care at a government-approved isolation center in Lagos State. This first mortality was that of a 67-year-old man with a history of multiple myeloma, a type of blood cancer. He was undergoing chemotherapy and had just returned to Nigeria following medical treatment in the United Kingdom. The novel COVID-19 pandemic has grounded several global activities including the provision of health care serves to people with chronic conditions such as cancer. Evidence from China suggests that cancer patients with COVID-19 infection are a vulnerable group, with a higher risk of severe illness resulting in intensive care unit admissions or death particularly if they received chemotherapy or surgery. This letter is an attempt to suggests practicable interventions such as the use of existing digital health platforms to limit patients' and oncology professionals’ physical interaction as a way of reducing the risk of COVID-19 infection transmission amongst cancer patients and oncologists, as well as outlining effective strategies to ensure that cancer care is not completely disrupted during the outbreak

Kumaraswamy log-logistic Weibull distribution: model, theory and application to lifetime and survival data

We develop the new Kumaraswamy Log-Logistic Weibull (KLLoGW) distribution by combining the Kumaraswamy and Log-logistic Weibull distributions. This new model is flexible for modelling lifetime data. Some statistical properties including quantile function, hazard rate function, moments and conditional moments are presented. Model parameters are estimated via the method of maximum likelihood and a Monte Carlo simulation study conducted to assess the accuracy of the estimates. Finally, the model is applied to a real dataset

On the new modified Dagum distribution: Properties and applications

In this paper, a new five parameter extended Dagum model called new modified Dagum (NMD) distribution is proposed. The proposed distribution is flexible as its density contains important sub-models such as modified Dagum, new Dagum, new modified Burr III, modified Burr III, Frechet, modified Frechet and many other distributions. The NMD density function is symmetrical, left-skewed, right-skewed, J, reverse-J and arc. The NMD distribution can produce all types of failure rates such as modified bathtub, bathtub, inverted bathtub, increasing and decreasing. To show the importance of the proposed distribution, we derive mathematical properties such as random number generator, sub-models, ordinary moments, moment generating function, characteristic function, incomplete moments, inequality measures, residual life functions and reliability measures. We characterize the NMD distribution via innovative techniques. We address the maximum likelihood estimation technique for the model parameters. We evaluate the precision of the maximum likelihood estimators via simulation study on the basis of the graphical results. We consider an application to a real data set to clarify the potentiality and utility of the NMD model. We establish empirically that the proposed model is suitable for survival times of patient's application. We apply goodness of fit statistics and graphical tools to examine the adequacy of the NMD distribution