Load library and the data The data is scrapped from the website of the Nigerian Centre for Disease Control (NCDC) i.e (NCDC 2020). The scrapping was done with some bits of tricks. Please see my post on that. The BREAKS were established from the visual inspection of the data (see (Nmadu, Yisa, and Mohammed 2009))
library(tidyverse) library(splines) library(Metrics) library(scales) library(readxl) library(patchwork) library(Dyn4cast) BREAKS <- c(70, 131, 173, 228, 274, 326) z.
Introduction The advent of the COVID-19 pandemic really put everyone in confusion and as the days, weeks went-by, everyone was trying to understand the trend and the direction of the incidence. While the medicals were in their labs trying to understand the anatomy of the various, various statisticians and data scientists were trying to model the trend so as to guide future actions and preparations. One of the early models was done for Australia by (Krispin and Byrnes 2020).
Introduction On the advent of COVID-19 globally and since February 29, 2020 in Nigeria, motivations to provide visuals of the trends and to provide guide to Nigerians on how to conduct themselves responsibly was boosted by the publication of the first coronavirus package and the awesome animation of the province level by Krispin and Byrnes 2020. That immediately sent me working on how to animate the cases for Nigeria. However, this desire was met with short comings because the data publish at the Johns Hopkins University Center for Systems Science and Engineering (JHU-CCSE) by the Nigerian Centre for Disease Control is agrregated nationally, whereas the animations that motivated me were regional for Australia.