The Plight of COVID-19 in Ethiopia: Describing Pattern, Predicting Infections, Recoveries and Deaths Using Initial Values from Different Sources
Background: On 31rd December 2019, China reported a cluster of cases of pneumonia of unknown etiology in Wuhan city, Hubei province. Eventually, a coronavirus was identified which was called “COVID-19” by World Health Organization (WHO) and was declared as a Public Health Emergency Concern globally.
Experts suggested a country context evidence to reduce the impact of COVID-19 in Africa region. To this end, this study aimed to model the course of the outbreak towards understanding the spread of the disease and the effect of integrated intervention.
Methods: The SEIR and other relevant models were fitted to determine the effect of integrated intervention towards prevention and control of the virus. Comparative visualization of data was conducted to show the pattern and progress of the disease in Ethiopia in relation with other countries.
Results: The overall trend of the virus in Ethiopia showed linear increase since the first case on March 13, 2020, and exponential increase after May 24, 2020. The confirmed cases in Ethiopia reached 5034 within 67 days, while South Africa and Italy reached 22,556 and 205,425 respectively within 67 days after passing 100 cases. The SEIR model considered integrated intervention measures (social distancing, facemask, and hand hygiene) with rho values of 0.7 and 0.5. Without intervention, about 9% of the population can be infected, while the proportion reduced to 5.5% and 2.5% with implementation of 30% and 50% integrated intervention measures, respectively.
The Prophet model showed prediction accuracy of 78.3% (95%CI = 74.2% – 82.3%) for confirmed cases.
Conclusion: Ethiopia showed the slow progress of COVID-19 compared with South Africa and Italy. The implementation of integrated measures could reduce the proportion of infection significantly. The integrated intervention measures could also extend the peak time to a longer period. The Prophet model showed promising prediction accuracy as it increases when the data increase. [Ethiop. J. Health Dev. 2021; 35(SI-1):82-89]
Key Words: COVID-19, patterns, predicting, infections, recovery and death