Study of the trend pattern of COVID-19 using spline-based time series model: a Bayesian paradigm.

A vast majority of the countries are under economic and health crises due to the current epidemic of coronavirus disease 2019 (COVID-19). The present study analyzes the COVID-19 using time series, an essential gizmo for knowing the enlargement of infection and its changing behavior, especially the trending model. We consider an autoregressive model with a non-linear time trend component that approximately converts into the linear trend using the spline function.

A pairwise likelihood-based approach for changepoint detection in multivariate time series models.

This paper develops a composite likelihood-based approach for multiple changepoint estimation in multivariate time series. We derive a criterion based on pairwise likelihood and minimum description length for estimating the number and locations of changepoints and for performing model selection in each segment. The number and locations of the changepoints can be consistently estimated under mild conditions and the computation can be conducted efficiently with a pruned dynamic programming algorithm.

Concurrent epidemics of influenza A/H3N2 and A/H1N1pdm in Southern China: A serial cross-sectional study.

Objectives: This study aimed to elucidate the antibody response pattern of multiple influenza subtypes through a 4-year serological study of a general population in Shenzhen, Southern China.

Methods: A serial cross-sectional serological survey was conducted at eight time points between 2009 and 2012. A total number of 5876 subjects were recruited from all age groups.

Inequality in obesigenic environments: fast food density in New York City.

The high prevalence of obesity in African American populations may be due to the food environment in residential communities, and the density of fast food restaurants is an important aspect of the restaurant landscape in US cities. This study investigated racial and socioeconomic correlates of fast food density in New York City. We found that predominantly Black areas had higher densities of fast food than predominantly White areas; high-income Black areas had similar exposure as low-income Black areas; and national chains were most dense in commercial areas.