Related Experiment Video

Updated: Dec 22, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
03:53

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses

Published on: November 10, 2023

1.7K

Modelling spatial variations of coronavirus disease (COVID-19) in Africa

Ibrahim Ayoade Adekunle1, Abayomi Toyin Onanuga1, Olanrewaju Olugbenga Akinola1

  • 1Department of Economics, Olabisi Onabanjo University, Ago-Iwoye, Nigeria; Department of Mass Communication, Olabisi Onabanjo University, Ago-Iwoye, Nigeria.

The Science of the Total Environment
|May 4, 2020
PubMed

Insights

This study analyzed COVID-19 deaths and confirmed cases in Africa, finding approximately 0.045 deaths per confirmed case. Understanding these spatial variations is crucial for public health strategies against the novel coronavirus.

Area of Science:

  • Epidemiology
  • Spatial analysis
  • Public Health

Background:

  • Human-to-human transmission of the novel coronavirus (COVID-19) has been established globally since late 2019.
  • Exploration of transmission outliers and spatial patterns remains critical for understanding disease spread.
  • Publicly available data on COVID-19 confirmed cases and deaths across Africa provide a basis for epidemiological investigation.

Purpose of the Study:

  • To examine the spatial density and statistical credence of COVID-19 transmission dynamics in Africa.
  • To investigate the nexus between COVID-19 attributable deaths and confirmed cases.
  • To identify unobserved factors influencing the spread of COVID-19 within the African continent.

Main Methods:

  • Construction of spatial variations and clusters to analyze COVID-19 data.
  • Application of the dynamic system generalized method of moment estimation procedure.
  • Accounting for cross-sectional dependence in statistical analysis.

Main Results:

  • A statistically significant finding of approximately 0.045 COVID-19 deaths per confirmed case in Africa.
  • Identification of a strict orthogonal relationship between confirmed cases and deaths, after accounting for cross-sectional dependence.
  • Spatial analysis revealed variations in disease burden across different regions.

Conclusions:

  • The study provides statistical evidence on the relationship between COVID-19 deaths and cases in Africa.
  • Findings underscore the importance of spatial analysis in understanding disease transmission patterns.
  • Discussion of policy measures informed by the epidemiological and spatial findings is essential for pandemic control.

Keywords:
AfricaCOVID-19 attributable deathsCOVID-19 confirmed casesSpatial variationSystem GMM

More Related Videos

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples09:26

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Published on: June 30, 2023

1.5K
Comprehensive & Cost Effective Laboratory Monitoring of HIV/AIDS: an African Role Model23:56

Comprehensive & Cost Effective Laboratory Monitoring of HIV/AIDS: an African Role Model

Published on: October 31, 2010

17.0K

Related Concept Videos

Principles of Disease Surveillance01:26

Principles of Disease Surveillance

Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
397
Pareto Chart00:52

Pareto Chart

A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the lines represent the cumulative total values. In this chart, the longest bars are arranged on the left and the shortest bars on the right, which makes it easier to read and interpret the data. It can also be called a Pareto diagram or Pareto analysis.
The Pareto chart is named after the Italian economist Vilfredo Pareto, who described the Pareto...
7.5K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
817
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
420
Causality in Epidemiology01:21

Causality in Epidemiology

Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
1.4K
Pie Chart01:04

Pie Chart

A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each indicating numerical proportions. It is also used to show the relative sizes of data in a single chart.
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
15.6K