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Consider a fixed number of clustered areas identified by their geographical coordinates that are monitored for the occurrences of an event such as a pandemic, epidemic, or migration. Data collected on units at all areas include covariates and environmental factors. We apply a probit transformation to the time to event and embed an isotropic spatial correlation function into our models for better modeling as compared to existing methodologies that use frailty or copula. Composite likelihood technique is employed for the construction of a multivariate Gaussian random field that preserves the spatial correlation function. The data are analyzed using counting process and geostatistical formulation that led to a class of weighted pairwise semiparametric estimating functions. The estimators of model parameters are shown to be consistent and asymptotically normally distributed under infill-type asymptotic spatial statistics. Detailed small sample numerical studies that are in agreement with theoretical results are provided. The foregoing procedures are applied to the leukemia survival data in Northeast England. A comparison to existing methodologies provides improvement.

This study analyses the research publications data about Coronavirus before and after the Covid-19 outbreak, to answer vital questions relevant to the Coronavirus research. The objectives of this study are to compare the Coronavirus research publications and tries to distinguish the pre and post Covid-19 outbreak trend in Coronavirus research, in the context of research areas, publications growth pattern, country and institutional contributions, funding agencies, language distribution, publishers and journal preferences, etc. It also tries to visualise the institutional and country-wide collaboration patterns in the Coronavirus research using the VOSviewer visualisation software. This study is based on the data retrieved from the Web of Science database for two time-frames, such as 1965 to 31st December 2019, and 1st January 2020 to 30th June 2021. This study reveals that, 89 per cent of the Coronavirus research publications were brought out after the Covid-19 outbreak, and research on Coronavirus has been undertaken in diversified areas in contrast to the prior period where it was mainly on virology, veterinary science, infectious diseases, microbiology, immunology, etc. It shows that USA and China continued to stand on top of the Coronavirus publications share, and the research collaboration between various countries and institutions has improved during 2020-21. It shows that over 97 per cent of the Coronavirus publications are in the English and the majority of the publications are in the journals published by Elsevier in both periods. During 2020-21 the Journal of Virology lost its upper hand in publishing the Coronavirus research publications.