In this paper, we propose a multivariate-count time series model for epidemics. We also propose a statistical method for estimating the transmission of infections across multiple communities and the time-varying reproduction numbers of each community simultaneously from a multivariate time series...
Modeling multivariate time series of counts using the integer-valued generalized autoregressive conditional heteroscedastic (INGARCH) scheme is proposed. The key idea is to model each component of the time series with a univariate INGARCH model, where the conditional distribution is modeled with a one...
Finally, the daily hospital referral average in the pre-COVID-19 period was higher than in the ascending phase of the epidemic and even higher than in the post-COVID-19 period (Fig. 3c; Table 3). Univariate time series analyses of changes, vis-à-vis the enactment of the triage protoco...
In this paper, vectors of the deviance residuals (after fitting a STARMA model) are used to build MCUSUM and MEWMA control charts to monitor multivariate space–time count series. Chart parameters are estimated by simulation to meet a desired in-control average run length and to minimize out-...
Some studies propose the structural vector autoregression model and allege that the introduction of this multivariate time series tool can effectively deal with the problem of exogenous conditions (Sims, 1980). In this context, White, Kim and Manganelli (2015) proposed the multivariate multiquantile ...
Some other models that are utilized to characterize epidemic pervasion are based on time series models. For instance, seasonal autoregressive integrated moving average (SARIMA) models were employed for modeling infectious disease count data in Helfenstein [8] and Trottier et al. [9]. Recently, ...