Introduction In the 933 days since the first COVID-19 case was reported on February 29, 2020 in Nigeria, about 267,511 cases have been recorded with 1.18% fatalities. Except for Kogi State which Government refused monitoring laboratories to be setup in her health facilities for confirming and managing COVID-19, cases have been recorded on regular basis in the other 35 states and Abuja, the Federal Capital. However, the frequency of cases vary from state to state.
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 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.
The African Continental Free Trade Area (AfCFTA) is a platform created to increase intra-trade and ease movement of persons and goods across borders within Africa as well as promote economic welfare and wellbeing of member states. Nigeria being a …
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This study investigated the relationship between the share of agriculture in GDP and some socio-economic and climate variables using ARMA, ARDL and structural change estimation in R. The data, covering the period 1960-2016, were obtained from various …