Prof Sujit Sahu recently co-edited the special issue (SI)

Prof Sujit Sahu recently co-edited the special issue (SI), “ Spatio-temporal dynamics of Covid ” of the journal Spatial Statistics jointly with Prof P. D’Urso  (University of Rome, Sapienza) and Prof Stein (University of Twente).  The issue presents a large variety of methodological and applied research papers all discussing different aspects of spatio-temporal spread of Covid-19. For example, an article by Sahu and Prof Böhning (S3RI)  develops an adaptive model for the weekly Covid-19 death rates in England as part of a joint bivariate model for number of cases and deaths. The joint model is used to evaluate the effects of several socioeconomic and environmental covariates.

The SI contains nineteen articles which were accepted out of more than fifty submitted manuscripts after peer review. Published applications and case studies include Covid-19 clustering structure in Italian regions, small-area spatio-temporal dynamics of Covid-19 in Scotland, mortality data in Toronto, spread in USA, and infection rate in Romania.

The SI also presents state of the art in methodological research on topics such as Bayesian spatio-temporal modelling, Bayesian non-parametric methods, small area estimation, and adaptive cluster sampling. The editors hope that the articles in the special issue will inspire a generation of researchers to develop new methods and applications related to the ongoing pandemic as nature generates new data and dynamics.