Modeling Methods:
A Hybrid model was used to forecast the total number of cases, hospitalization and ICU requirements, and the total number of deaths at national level.
Hybrid Model:
1: Mathematical and statistical models were used to rapidly characterize and estimate the key parameters of the compartmental model from surveillance and case management data.
2: A compartmental S
u-E
u-I
cu-I
hu-I
(icu)u-R-D for the non-vaccinated portion of the population. This structure is connected to
V-E-I
c-I
h-I
(icu)-R for the vaccinated portion of the population.
Vaccination Intervention (VI):
The rate of vaccination is calculated from currently administered vaccines. Apparently, the impact of the vaccines is quantified in the model, in the following three areas.
1. Prevention of infection
2. Prevention of symptomatic diseases
3. Prevention of severe or critical cases (Hospitalization and ICU)
| Types |
Efficacy |
| Prevention of infection |
52% |
| Prevention of symptomatic diseases |
85%, for 65+ age groups; 74% for others |
| Prevention of severe or critical cases |
100% |
Vaccine type: AstraZeneca. The above efficacy values only work for D614G and B.1.1.7 variants, and the efficacy is critically low for South African variant.
Non-pharmaceutical Interventions (NPIs):
Weekly observed facemask and social distancing compliances at a national level were used in the model. Moreover, NPIs are seen to be useful in preventing and reducing the transmission rate.
Clinical Interventions:
These are useful for assuming the efficacy and availability, of treatment for severe and critical cases.
| Parametric values |
Descriptions |
| Intermediate Clinical Intervention |
With current clinical interventions which are helpful in reducing case severity and fatality. |
| Lowest Clinical Intervention |
If clinical interventions are not effective enough in reducing case severity and fatality, due to resource overwhelming or other reasons. |
| Highest Clinical Intervention |
If clinical interventions are effective in reducing the continuously increasing case severity and fatality. |
These values can be affected by many factors, but availability of hospitalization, ICU beds, oxygen cylinders and mechanical ventilators are the most common ones.
Re-infection:
Available scientific data suggests that in most people immune responses remain robust and protective against reinfection for at least 6-8 months after the first infection. In this regard, in our model, we have assumed there will be a rare probability of re-infection after 180 days (6 months). However, the rate of re-infection is highly impacted by the types of variants. In the case of Ethiopia, before July 2021 we have assumed D614G and B.1.1.7 variants to be more dominant, making the re-infection percentage of those who are already recovered to be 0.2%. The existence of the Delta variant in Ethiopia was confirmed by MoH (Ministry of Health) in July 2021. Different studies and surveillance data for other countries suggest that the Delta variant will increase the risk of re-infection. Accordingly, after July 2021, we have introduced a 1% of re-infection dynamically into our simulation.
Increase in transmission rate:
The Delta variant causes more infections and spreads faster than earlier forms of the virus that causes COVID-19. Thus, the Delta variant is highly contagious, more than 2x as contagious as previous variants. Therefore, after July 2021, we have doubled the fitted transmission rate to account for this change.
Simulation Method:
The simulation started on May 10, 2020. This is the time when community transmission was assumed to start. The model assumes vaccines doses were being administered as of March 25, 2021
targeting older age groups (55+). In that regard, intervention easing and tightening scenarios were introduced starting from July 01, 2021.
