Spatio-Temporal Modelling of COVID-19 Dynamics in Africa

Spatio-Temporal Modelling of COVID-19 Dynamics in Africa

Iddrisu Wahab Abdul

Since the outbreak of COVID-19 in China, in December 2019, almost no country in the world has been spared the devastation caused by the pandemic. In this paper, I model and analyze the trend of COVID-19 in Africa along space and time, in order to provide accurate and reliable predictions of the dynamics of the disease in Africa. Data on daily confirmed cases of COVID-19 for fiftytwo countries in Africa from February 14, 2020 to December 04, 2020 were obtained from “Our World in Data”(OWID). A model that captures space-time dependence was fitted to the data and used for analysis. The results indicate that the second wave of the pandemic in Africa is yet to reach its peak. The results also indicate that countries in Africa have been affected by the disease to a very heterogeneous extent during this period. It was also observed that the average reproduction of the disease within countries in Africa, which is known as the autoregressive effect was about 0.46 while the neighbourhood effect, which is the transmission of the disease from adjacent countries, was quite negligible. The seasonality-adjusted factor which indicates how the basic endemic incidence increases per day was observed to be about 1.23 while the epidemic proportion of the disease incidence in Africa was found to be 46%. These findings, indicating where and when the incidence of the disease will be high may be useful for public health decisionmaking, as they provide time to intervene on the local public health systems.

2020

https://scholar.google.com/citations?view_op=view_citation&hl=en&user=ECTxVnYAAAAJ&cstart=20&pagesize=80&citation_for_view=ECTxVnYAAAAJ:UeHWp8X0CEIC

English