Forecasts of the mortality risk of COVID-19 using the Markov-switching autoregressive model: a case study of Nigeria (2020–2022)

The global pandemic due to SARS-Cov-2 ravaged the world and killed more than 6 million people globally within two years. Studies predicting future occurrences are essential to effectively combat the virus. This study modeled daily fatality rate in Nigeria from March 23, 2020 to March 19, 2022 and forecast future occurrences using Markov switching model (MSM). MSM estimates segmented fatality rates into three states of low-, medium- and high-risks. Further, estimates revealed that as at 19th March, 2022, Nigeria remained at the low-risk regime in which 1 (95%CI: 0, 1) person, on the average, died of coronavirus daily; however, the most probable scenario in the nearest future was the medium-risk state in which an average of 4 (95%CI: 2, 5) persons would die daily with 48.7% probability. The study concluded that Nigerian COVID mortality risks followed a switching pattern which fluctuated within low-, medium- and high-risks; however, the medium-risk state was most likely in the future. Our results indicated that the quarantine measures adopted by the governments yielded positive results. It also underscored the need for governments and individuals to intensify efforts to ensure that the country remained at the low-risk zone till the virus would be eventually eradicated.

Authors

Publication Details

Journal
Statistics in Transition New Series
Published
2024-09-04
DOI
https://doi.org/10.59170/stattrans-2024-031
Citations
1
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.40
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article

Forecasts of the mortality risk of COVID-19 using the Markov-switching autoregressive model: a case study of Nigeria (2020–2022)

Idowu Oluwasayo Ayodeji
1 citations
Statistics in Transition New Series
COVID-19 epidemiological studies
0.40
article

Forecasts of the mortality risk of COVID-19 using the Markov-switching autoregressive model: a case study of Nigeria (2020–2022)

Idowu Oluwasayo Ayodeji
article en
1 citations

Abstract

The global pandemic due to SARS-Cov-2 ravaged the world and killed more than 6 million people globally within two years. Studies predicting future occurrences are essential to effectively combat the virus. This study modeled daily fatality rate in Nigeria from March 23, 2020 to March 19, 2022 and forecast future occurrences using Markov switching model (MSM). MSM estimates segmented fatality rates into three states of low-, medium- and high-risks. Further, estimates revealed that as at 19th March, 2022, Nigeria remained at the low-risk regime in which 1 (95%CI: 0, 1) person, on the average, died of coronavirus daily; however, the most probable scenario in the nearest future was the medium-risk state in which an average of 4 (95%CI: 2, 5) persons would die daily with 48.7% probability. The study concluded that Nigerian COVID mortality risks followed a switching pattern which fluctuated within low-, medium- and high-risks; however, the medium-risk state was most likely in the future. Our results indicated that the quarantine measures adopted by the governments yielded positive results. It also underscored the need for governments and individuals to intensify efforts to ensure that the country remained at the low-risk zone till the virus would be eventually eradicated.

Statistics in Transition New SeriesVol. 25(3)
Openalex Percentile: Top 41%
COVID-19 epidemiological studies
0.40
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Forecasts of the mortality risk of COVID-19 using the Markov-switching autoregressive model: a case study of Nigeria (2020–2022) — Idowu Oluwasayo Ayodeji · Statistics in Transition New Series (2024) | TGRS Research Map | TGRS