Abstract
Abstract
Background
A viral disease due to a virus called SARS-Cov-2 spreads globally with a total of 34,627,141 infected people and 1,029,815 deaths. Algeria is an African country where 51,690, 1,741 and 36,282 are currently reported as infected, dead and recovered. A multivariate time series model has been used to model these variables and forecast their future scenarios for the next 20 days.
Results
The results show that there will be a minimum of 63 and a maximum of 147 new infections in the next 20 days with their corresponding 95% confidence intervals of − 89 to 214 and 108–186, respectively. Deaths’ forecast shows that there will be 8 and 12 minimum and maximum numbers of deaths in the upcoming 20 days with their 95% confidence intervals of 1–17 and 4–20, respectively. Minimum and maximum numbers of recovered cases will be 40 and 142 with their corresponding 95% confidence intervals of − 106 to 185 and 44–239, respectively. The total number of infections, fatalities and recoveries in the next 20 days will be 1850, 186 and 1680, respectively.
Conclusion
The results of this study suggest that the new infections are higher in number than recover cases, and therefore, the number of infected people may increase in future. This study can provide valuable information for policy makers including health and education departments.
Publisher
Springer Science and Business Media LLC
Subject
Pharmaceutical Science,Agricultural and Biological Sciences (miscellaneous),Medicine (miscellaneous)
Reference28 articles.
1. Issanov A, Amanbek Y, Abbay A, Adambekov S, Aljofan M, Kashkynbayev A, Gaipov A (2020) COVID-19 outbreak in post-soviet states: modeling the best and worst possible scenarios. Electron J Gen Med 17(6):em256. https://doi.org/10.29333/ejgm/8346
2. https://www.who.int/news/item/29-06-2020-covidtimeline. Accessed 1 Aug 2021
3. Johns Hopkins University of Medicine, Coronavirus resource center: https://coronavirus.jhu.edu/map.html. Accessed 31 Aug 2020.
4. Peng L, Yang W, Zhang D, Zhuge C, Hong L. Epidemic analysis of COVID-19 in China by dynamical modeling. arXiv preprint arXiv: 2002.06563, 2020.
5. Alsayed A, Sadir H, Kamil R, Sari H (2020) prediction of epidemic peak and infected cases for COVID-19 disease in Malaysia, 2020. Int J Environ Res Public Health 17:4076. https://doi.org/10.3390/ijerph17114076
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