Three models were used to estimate deaths and cases in the Amhara region. Each of them has their strength and limitations. The result obtained from each modeling technique was presented and discussed as follows:
Susceptible-Exposed-Infected-Recovered (SEIR) Model
For this model, parameters mentioned above: clinical parameters, the transmission rate parameters, and simulation values by considering the context of the Amhara region.
Our projection shows that with no intervention, the peak day will be at the beginning of August (150thday after a case with coronavirus is confirmed); the region will experience about 4,222,172cases. On the 100th day, the day will be 21st June; the cases will reach 21, 917,130. In terms of the population exposed, the peak day will be on July 29thwith 3,013,605 cases. After putting the different parameters in the model, findings indicate mild infection will be high in the region at 140 days, 31st July with 3, 167,679 cases. It is estimated that people to be infected severely and critically in July will be the highest in experiencing 3,310,069 cases and 142,548cases, respectively. After 125 days, the region will start having people recovered from the pandemic, on that day (16thJuly) with 1,694,316. The worst side of this pandemic is its fatality rate; the number of deaths that will be experienced high in the region estimated will be on the 160thday on August 20thwith 273,458 deaths (Figure 1).
Even though the model predicts the peak number of severe, critical, and recovered cases could be occurred in July, what observed in the region in July was among 33, 166 individuals tested for Covid-19, about 642 and 478 were found test positive, and recovered from Covid-19 respectively. In addition, contrary to the predicted high number of deaths in August, the observed total death in August was 25 in the region. These contradicting findings might be due to mainly two possible reasons: first, the testing capacity of the region was so limited, particularly during the start of the pandemic, this, in turn, might miss infections and deaths from Covid-19; second, took the clinical and transmission parameters used in the model from other countries study estimates, which might not represent the developing countries’ including Ethiopia’s context.
To help the evaluation, we generated different scenarios. We tested the potential effects of
intervention strategies to control or reduce social contacts. As literature shows, some public
health interventions could curb the transmission of the pandemic in different degrees (8). For this study, we used an assumption of the region’s implementing of intervention strategies, if able to reduce 30% of the virus's transmission; we estimated the following situations that the region might experience.
The results of the scenario with a 30% reduction in transmission describe the peak day will be at
222 days, on 21st October with 2,407,042 cases (Figure 2). A drastic decrease in the number of
cases compared to no intervention model if we increase the days of peak case burden by more than two months. A reduction in the reproduction rate will help in slowing the community transmission.
The result of the scenario with a 40% reduction in transmission was a decrease of about 2 million
cases and able to increase the actual daily protection rate around 12 times. The peak day (December 15th) will be pushed by beyond four months, compared to the model with no intervention. It can be achieved by reducing both infection and death if strict public health intervention measures are implemented in the region (Figure 3).
Susceptible-Infected-Recovered (SIR) Model
Number of Susceptible, Infected and Recovered Cases for COVID-19 if no Non-Pharmacologic intervention is implemented
With and without non-pharmacologic intervention (NPI) the susceptible-Infected-Recovered
(SIR) model was the most commonly used modeling technique for infectious diseases. Based on the SIR model the expected number of cases by date is shown in Figure 4 below. Without NPI that was designed in Excel as SIR modeling template and taking the parameters shown in Table 2 above as well as the total population of the Amhara region (22, 189, 999) to be susceptible the predicted number of peak COVID-19 cases in the region was estimated to be 5, 947, 685.
This finding emphasizes the peak date of occurrences of cumulative cases, need for hospitalization, and ICU care and death; accordingly, the above peak figures all were expected to be occurring on the same date on July 2, 2020. This prediction is without any non-pharmacologic interventions targeting in minimizing the daily contact rate such as school closure, physical distancing, self-isolation, quarantine, and lockdown.
Number of cases in need of Hospitalization and ICU care and Death from COVID-19 if no Non-Pharmacologic Intervention is implemented
Assuming that there are no interventions made in the region, the peak number of cases in need of hospitalization was expected to be 820,781occurring on the date July 2, 2020. Regarding the maximum number of cases in need of ICU care, it was expected to be 279,541 the same date of peak hospitalization, July 2, 2020, and on the same date, the maximum number of death (53,529) is expected (Figure 5).
Number of Susceptible, Infected and Recovered Cases for COVID-19 when a Non-Pharmacologic intervention (NPI) is implemented
If community interventions mainly focusing on the reduction of contact rate are applied, such as
school closure and stay at home lockdown with an assumption of 80% reduction in contact rate (3.35) for at least six weeks from 4/15 to 5/30, the peak expected number of infected cases would be shifted from July 2, 2020, to August 27, 2020 (Figure 6).
Number of cases in need of Hospitalization and ICU care and Death from COVID-19 with a Non-Pharmacologic Intervention (NIP)
When a community intervention of school closure and lockdown are applied with an assumption
of an 80% reduction in contact rate (3.35) from 4/15 to 5/30; the peak expected number of cases
needing hospitalization and ICU care, and the peak number of deaths would be shifted from July 2, 2020, to August 27, 2020 (Figure 7).
Number of Susceptible, Infected and Recovered Cases for COVID-19 with a Non-Pharmacologic intervention (NPI and reactive approach)
If a non-pharmacologic intervention with a reactive approach is applied, targeting an 80% reduction of the contact rate during the first ten weeks (from April 15/2020 to June 30/2020) followed by a 20% reduction of the contact rate during the next 8 months (from July 1/2020 to March 12/2021) one can expect the following results. The peak number of infected cases would be 4,051,875 on November 10/2020 (Figure 8).
With the same consideration of the NPI mentioned above, the peak number of cases needing hospitalization would be 559,159, while those needing ICU care are 190,438. The estimated death is 36,467 on November10, 2020 (Figure 9).
If the NPIs are implemented successfully one can see how the date for the peak number of cases, needing hospitalization and ICU care as well as, death could be shifted from being early to late occurrences. This mechanism of delaying the outbreak in turn assists to develop the health institutions’ capacity and to have preparedness for emergency response. However, such kinds of NPI couldn’t be implemented sustainably due to their socio-economic impact hence releasing the restrictions and reopening schools is mandatory. The questions such as when and how the restrictions to be released depend on the levels of healthcare capacity and the preparedness for emergency response. Therefore, another alternative approach such as NPI of some duration taking the capacity developing time in to consideration with a reactive reduction is required.
If NPIs and a reactive reduction in the contact rate is implemented, keeping all other parameters
constant and assuming an 80% reduction in Contact Rate (3.35) for ten weeks (from April 15 to
June 30, 2020) and then a reactive reduction of 20% (10.72) for the rest of six months, two
important results were observed. The first was the epidemic curve could be flattened as a result
the peak number of infected cases reduced from 5, 947, 685 cases to 4,051,875, those in need of
Hospitalization decreased from 820,781 to 559,159, needing ICU care from 279,541 to 190,438
and death from 53,529 to 36, 467. The second observation was a pronounced dalliance in the
epidemic from July 2 to November 10, 2020. These observations are essential findings that may inform us if this approach is used. It is possible to minimize the risk of acquiring the diseases and dying from it in one hand and get enough time to build capacity and prepare for the emergency response. Despite the important role of NPI in flattening the epidemic curve, low testing coverage and detection rate in the region could result in the hidden epidemic because onward transmission from asymptomatic and undetected infections accounts for 65%infectiousness (9).The peak day determines the duration of the epidemic, which is also dependent on our testing capacity. Testing campaigns can reduce the infection peak because the diagnosed population enters quarantine or treatment center and is less likely to affect the susceptible people(10). Moreover, on the month November, the observed data showed that among 165, 498 individuals who tested for Covid-19, about 6,125 were found test positive, 3,226 recovered, and 89 died.
DisMod epidemiological diseases model
We used this model by considering the worst-case scenario to estimate the expected number ofCOVID-19 cases and deaths. Using the USA COVID-19 infected cases and deaths data by age and sex, it was tried to estimate the regional incidence, case fatality, and recovery rate in DisMod-II software with an indirect standardization method to the region’s population size by age and sex. Accordingly, the expected number of infected cases and deaths were calculated by age and sex and presented as follows. Below is the male population graph on COVID-19 cumulative incidence rate, case fatality rate, and remission rate. In the graph, one can observe how the case fatality rate increases as age increases and the remission rate decreases as age increases, whereas the incidence rate remains more or less constant, except it is very low at an early age and low at an older age. Moreover, during an epidemic for an emerging disease not occurred previously, can observe that the cumulative incidence rate is more or less equal to the prevalence rate. This pattern is the same for both males and females though females have lower incidence and case-fatality rates compared to males at similar age while females have a higher remission rate compared to males (Figure 10 and Figure 11).
One can also estimate the expected number of COVID-19 cases, deaths, and recoveries overall or a specific age group by sex in the region using Table 3 and Table 4. The total annual cumulative incident cases in the region were estimated to be 837,348(474, 809 male and 362, 540 female cases). The expected number of total deaths in the region were also estimated at 44,247 (30, 176 male and 14, 071 female deaths).
The Covid-19 data observed in the region so far showed that among 243, 638 total tested peoples, about 6760 were positive for Covid-19 and 3, 552 recovered while 125 deaths were registered. This observation is completely contradicting what was forecasted using the DisMod-II. It might be due to both the region's capacity for testing and the unrepresentative initial rates of the variables taken and used for the model.
The annual cumulative incidence rate and case fatality rate in Table below one can estimate the expected number of COVID-19 cases among the Amhara region's male population, and it is 4.2896% of 11,068,826 male population that is estimated to be 474, 809.In addition, the expected number of COVID-19 deaths among the male population of the Amhara region is 6.3553% of the expected male COVID-19 cases (474, 809) is estimated to be 30, 176 cases.
Table 3 COVID-19 expected rates of new cases, deaths and remission among males by 5 years age group in Amhara Region, Ethiopia, 2020.
DisMod II input and output, database COVID-19
Males, Disease: COVID-19U (Rates * 100), sex: Males
Written 5/25/2020, 1:03:52 AM
|
Age
|
Incidence (rates * 100)
|
Prevalence (rates * 100)
|
Remission (rates * 100)
|
Case fatality (rates * 100)
|
Mortality (rates * 100)
|
0-4
|
0.0044
|
0.0041
|
99.34
|
0.0303
|
0
|
5-9
|
0
|
0.0003
|
99.34
|
0.0389
|
0
|
10-15
|
0.8692
|
0.5259
|
99.34
|
0
|
0
|
15-19
|
3.9207
|
3.2261
|
99.34
|
0.0086
|
0.0003
|
20-24
|
6.7598
|
6.2527
|
99.34
|
0.3143
|
0.0198
|
25-29
|
7.8523
|
7.7006
|
99.34
|
1.2365
|
0.0953
|
30-34
|
7.7227
|
7.6525
|
99.3365
|
3.0425
|
0.2326
|
35-39
|
7.5197
|
7.2371
|
99.2863
|
5.8019
|
0.4196
|
40-44
|
7.9559
|
7.3171
|
99.0899
|
8.9852
|
0.6582
|
45-49
|
9.1516
|
8.1105
|
98.8643
|
11.8817
|
0.9663
|
50-54
|
10.3517
|
9.1862
|
98.2221
|
13.7892
|
1.2689
|
55-59
|
10.0143
|
9.2429
|
97.3381
|
14.1489
|
1.3056
|
60-64
|
8.1336
|
7.9319
|
94.7431
|
13.5075
|
1.0671
|
65-69
|
6.6564
|
6.5326
|
91.7705
|
13.8079
|
0.8999
|
70-74
|
6.4137
|
6.3709
|
83.9362
|
17.1405
|
1.0926
|
75-79
|
6.528
|
6.4765
|
78.8656
|
23.1684
|
1.5008
|
80+
|
6.498
|
6.7235
|
65.67
|
26.9479
|
1.8199
|
All ages
|
4.2896
|
3.9548
|
97.5812
|
6.3553
|
0.2514
|
Focusing on the annual cumulative incidence rate and case fatality rate, it is estimated that the expected number of COVID-19 cases among the Amhara region's female population is 3.2599% of 11,121,173, which is 362, 540 (Table 4). Also, the expected number of COVID-19 deaths among the region's female population is 3.881% of expected female COVID-19 cases (362,540), which are 14,071.
Table 4 COVID-19 expected rates of new cases, deaths and remission among Females by 5 years age group in Amhara Region, Ethiopia,2020.
|
DisMod II input and output, database COVID-19
|
|
Females, Disease: COVID-19U (Rates * 100), sex: Females
|
|
Written 5/25/2020, 1:08:07 AM
|
|
|
Age
|
Incidence
(rates * 100)
|
Prevalence
(rates * 100)
|
Remission (rates * 100)
|
Case fatality (rates * 100)
|
Mortality (rates * 100)
|
0-4
|
0.003
|
0.0028
|
99.76
|
0.0188
|
0
|
5-9
|
0
|
0.0002
|
99.76
|
0.0241
|
0
|
10-14
|
0.6309
|
0.3806
|
99.76
|
0
|
0
|
15-19
|
2.8667
|
2.348
|
99.76
|
0.0054
|
0.0001
|
20-24
|
4.9826
|
4.5889
|
99.76
|
0.1945
|
0.009
|
25-29
|
5.8098
|
5.691
|
99.7551
|
0.7647
|
0.0436
|
30-34
|
5.7111
|
5.688
|
99.7225
|
1.8813
|
0.1069
|
35-39
|
5.552
|
5.4168
|
99.6905
|
3.5875
|
0.1942
|
40-44
|
5.8725
|
5.5221
|
99.6056
|
5.5553
|
0.3072
|
45-49
|
6.7667
|
6.1735
|
99.533
|
7.3453
|
0.4547
|
50-54
|
7.6743
|
7.0244
|
99.3477
|
8.5236
|
0.5997
|
55-59
|
7.4254
|
7.0686
|
98.8287
|
8.7458
|
0.6172
|
60-64
|
6.0132
|
6.0072
|
97.1273
|
8.3496
|
0.4995
|
65-69
|
4.9049
|
4.8886
|
95.3137
|
8.5339
|
0.4161
|
70-74
|
4.7284
|
4.6734
|
90.7169
|
10.591
|
0.4951
|
75-79
|
4.8154
|
4.7272
|
88.1846
|
14.3183
|
0.6769
|
80+
|
4.8035
|
4.7768
|
82.56
|
16.6571
|
0.797
|
All ages
|
3.2599
|
3.0378
|
98.9243
|
3.881
|
0.1179
|
With the application of DisMod-II considering the United States of American’s (USA) data by
age and sex, the annual cumulative incidence rate of COVID-19 was estimated at 837,348. This result is based on the age-sex specific rates observed in the USA after a community transmission started on May 13, 2020Worldometer’s report. As clearly described it in the result part, one can look at the age-sex pattern of COVID-19 cumulative incidence, Case fatality and recovery rates.
Unlike the above two models (SIR and SEIR), this model result emphasizes indicating the most
affected group of peoples than the peak of several expected cases by date. Moreover, it could not detect the impact of NPI on the magnitude and in delaying peak date of occurrences of COVID-19 with this model. However, contrary to the other models, it indicates the high-risk groups (at least by age and sex) with their number expected to be infected, recovered, and dead; this, in turn, aid deciding about preventing and controlling the pandemic in the region. Accordingly, it showed that cumulative incidence is very low at lower age groups (less than 15 years old) and low at higher age group (greater than 65 years old); however, it is highest among the working-age groups (from 15 to 65 years old). It might be due to their contact rate per day. Since they are mostly unemployed young and old dependents having limited movements, peoples at the lowest and highest age groups have lower average contact rates per day compared to the middle working age groups. It might pronounce if measures like school closure were made. Even though the acquiring probability is higher in the middle age group, the fatality rate is very high among those sixty and above age group people with the lowest recovery rates. This idea is supported by the CDC report that most USA deaths are above 75s (11). Similarly, the WHO’s 11th- 14thweekly reports indicated that 60 and above age group peoples are at high risk of death from COVID-19 than the younger age groups(12).In this modeling, it was tried to explore the age-adjusted gender variation through an indirect method of adjustment. As a result, males' cumulative incidence rate is 1.32 times higher than females at 4,290 per 100, 000 and 3,260 per 100, 000 respectively. Similarly, the overall male death rate is 1.6 times higher than females at 6,355 per 100, 000 and 3,881 per 100, 000 respectively. This gender variation in the death rate from COVID-19 is in line with the CDC’s report of COVID-19 much more fatal for men, especially taking age into account, it indicated that in New York, the overall male death rate is 1.7 times higher than the female death rate at 228 per 100, 000 and 134 per 100, 000, respectively.