Ricardo Cao, Editor, and José Chacón, Guest Editor

The COVID-19 pandemic is affecting the lives of people all around the world. Mathematicians, statisticians, and data scientists can play a prominent role by contributing their analytical and modeling skills to describe possible scenarios; make inferences; and design strategies to control the disease spread, avoid health system breakdowns, and save lives.

With these goals in mind, the Journal of Nonparametric Statistics is calling for papers on subjects including prediction of pandemic evolution, case tracking and forecasting techniques, risk analysis, data quality and under-reporting effects, spatiotemporal disease dynamics, peak and length estimation, analysis of transmission reduction covariates, data-supported efficacy of isolation and lockdown strategies, and any other problem related to COVID-19 that has been addressed with a data science approach.

All papers will be refereed and subject to the same high-quality standards as regular submissions to the Journal of Nonparametric Statistics. This special issue will be published upon completion of the required number of papers, following a fast-track process and avoiding a publication queue.

Submissions will be accepted until October 31.