Skip to main navigation
Skip to search
Skip to main content
University of Johannesburg Home
Search content at University of Johannesburg
Home
Scholars
Research entities
Research output
Press/Media
Equipment & facilities
Bayesian inference of COVID-19 spreading rates in South Africa
Rendani Mbuvha
,
Tshilidzi Marwala
University of the Witwatersrand
University of Johannesburg
Research output
:
Contribution to journal
›
Article
›
peer-review
52
Citations (Scopus)
Overview
Fingerprint
Press/Media
(1)
Fingerprint
Dive into the research topics of 'Bayesian inference of COVID-19 spreading rates in South Africa'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
South Africa
100%
COVID-19
100%
Bayesian Inference
100%
Rate of Spread
100%
Community Level
66%
Epidemiological Model
66%
Disease Spread
33%
Containment
33%
State-led
33%
Markov Chain Monte Carlo Methods
33%
State Response
33%
Testing Data
33%
Travellers
33%
National Lockdown
33%
Imported Case
33%
Mass Testing
33%
Travel Ban
33%
Mass Screening
33%
Confirmed Cases
33%
Private Laboratory
33%
Screening Program
33%
Imported Infections
33%
Parameter Inference
33%
Case-driven
33%
Trajectory Prediction
33%
Testing Program
33%
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)
33%
Bayesian Parameter Inference
33%
Accurate Inference
33%
Medicine and Dentistry
COVID-19
100%
Republic of South Africa
100%
Diseases
66%
Infection
33%
Severe Acute Respiratory Syndrome Coronavirus 2
33%
Mass Screening
33%
Monte Carlo Method
33%
Mathematics
Bayesian
100%
Markov Chain Monte Carlo Method
100%
Bayesian Inference
100%