A Visualization and Analysis of the Effect of Population Density on the Mutation Rate of SARS- CoV-2 - Kim, Juno (International Journal of Sciences: Basic and Applied Research (IJSBAR), 2021)
The SARS-CoV-2 genome is prone to mutations during replication, similar to other viruses. Mutations are caused by random errors in the process of viruses replicating themselves via a host cell. With these mutations, SARS-CoV-2 changes into several different strains, often categorized by their geographical location, such as the UK variant(B.1.1.7) or the Brazilian variant(P.1). Population density is a metric detailing the number of citizens in km^2 and is used as an approximation for social interaction in this study. By comparing the two factors in a country, the relationship can be observed for SARS-CoV-2 viral mutation rate against population density. (The GISAID SARS-CoV-2 dataset was downloaded and analyzed for this study, along with population density data provided by the UN. After preprocessing the data, the number of distinct viral mutations in a country was analyzed by finding the unique mutations in the cases of a country. After calculating the viral mutation rate, a heatmap was assembled with several Python libraries which highlights areas of interest. Additionally, a scatter plot graph comparing the two factors was created using the Seaborn library. After taking into account the population densities of multiple countries, the results show that population density has no observable correlation with mutation rate from this dataset After analyzing the graph and the map, there is no clear correlation between population density and the mutation rate of SARS-CoV-2. However, the procedures used for this study can be applied to other factors as well, such as temperature, which may result in trends that forecast future areas of viral mutation.