Frequency of occurrence of COVID-19 cases across Nigeria

[This article was first published on R-Blog on Data modelling to develop ..., and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

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. Now that the world is consolidating on the management and final defeat of the spread of the virus, it is good to have knowledge of states that still frequently report cases so that efforts can be geared towards effective confinement.

The data for this visuals which were scrapped from Ngerian Centre for Disease Control, have undergone some cleaning and wrangling.

Load library and data

library(tidyverse)
Fre_days <- readRDS("data/Fre_days.RDS")

Frequency of recorded cases in states

ggplot(Fre_days) +
aes(x = date, y = N_days, colour = Province.State) +
geom_line(size = 0.5) +
scale_color_hue(direction = 1) +
labs(x = "Date", y = "Number of days") +
theme_minimal() +
theme(legend.position = "none") +
facet_wrap(vars(Province.State), ncol = 4, scales = "free_y") +
labs(caption = "Graphics: Job Nmadu | @JobNmadu \n Source: https://covid19.ncdc.gov.ng/")

As can be observed, there were only six days in 933 days when no case was reported in Lagos State. Similarly, 10 days in Abuja, the Federal capital and Rivers State; 15 days in Ondo State; 25 days in Oyo, Kaduna and Kano States respectively and 30 days in Ogun, Plateau and Delta States respectively. Lagos, Ogun, Oyo, Ondo, Delta and Rivers States share boundaries. Also, Abuja, Kaduna, Kano and Plateau states share boundaries. So it can be seen that the virus is moving within among contiguous states. Therefore in terms of attention, these states still pose some risks to the spread of the virus and should be well-policed.

Frequency of occurence of cases in the zones

ggplot(Fre_days) +
aes(x = date, y = N_days, colour = County) +
geom_line(size = 0.5) +
scale_color_hue(direction = 1) +
labs(x = "Date", y = "Number of days") +
theme_minimal() +
theme(legend.position = "none") +
facet_wrap(vars(County), ncol = 2, scales = "free_y") +
labs(caption = "Graphics: Job Nmadu | @JobNmadu \n Source: https://covid19.ncdc.gov.ng/")

Just as in the case of States, South West, South South, Federal Capital, North Central and North West zones are of interest in the final defeat of COVID-19.

To leave a comment for the author, please follow the link and comment on their blog: R-Blog on Data modelling to develop ....

R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)