Special Issue: Statistical modeling of pandemics and coronavirus

This special MASA issue is intended for the problems of statistical modeling of pandemics in general, and the Coronavirus COVID-19 one particularly. A recent analysis in Nature1 shows that the number of papers on coronavirus skyrocketed in the first 4 months of 2020 and then stabilized, more or less in accordance with behavior of the pandemic itself. The statistical modeling of the coronavirus pandemic is also flattened – yet the number of monthly publications is huge, exceeding the “normal pre-pandemic” level in 25–30 times.

Volume 16, Issue 1

Statistical modeling of pandemics and coronavirus – Openly Available
Mandel, Igor | Zaslavsky, Boris | Lipovetsky, Stan

RESEARCH ARTICLES
Using the Weibull distribution to model COVID-19 epidemic data
Moreau, Vitor Hugo

A probabilistic epidemiological model
Switkay, Hal M.

A hybrid of artificial neural network, exponential smoothing, and ARIMA models for COVID-19 time series forecasting
Safi, Samir K. | Sanusi, Olajide Idris

Social network analysis and community detection on spread of COVID-19
Wickramasinghe, Ashani Nuwanthika | Muthukumarana, Saman

Modeling COVID-19 positivity rates and hospitalizations in Texas
Kafle, Ram C. | Kim, Doo Young | Malandro, Martin E. | Holt, Melinda Miller

Statistical methods for estimating cure fraction of COVID-19 patients in India
Sreedevi, E.P. | Sankaran, P.G.

Spatial identification of component-based relative risks
Kadhem, Safaa K.

Inconsistencies in countries COVID-19 data revealed by Benford’s law
Moreau, Vitor Hugo

Comment on the paper “The science of statistics in victimhood culture: Dignity and dishonor”
Lipkovich, Ilya

OTHER
Acknowledgment – Openly Available

Call for Papers

As a member of our research community, we would like to invite you to contribute your own work for publication in the journal. Model Assisted Statistics and Applications offers contributing authors many benefits, including:

· First class Editorial Board

· Rigorous peer review and speedy manuscript processing

View the detailed Instructions to Authors.