Drill-down analysis from National to Sub-national (Regional) data of both surveillance and case management data. Some of this analysis include test positivity over-time, symptomatic versus asymptomatic proportions, case fatality with different demographical representions, case severity and proportion of critical cases from reported active cases. Moreover, a projection module to forecast clinical, severe (hospitalized), critical (ICU) cases and deaths by considering various intensity and efficacy of Non Pharmaceutical Interventions (NPI)

Modelling the progression and the impact of Covid-19 on health care services such as ICU requirements and Hospitalization needs depending on various intervention scenarios and different demographic characterstics.

Reported number of Covid-19 cases, deaths, case positivity rate, and case fatality rate for few Sub-sahara countries such as Ethiopia, Kenya, Rwanda, Mozambique, Malawi, and Zambia are also studied to provide comprehensive understanding of epidemiological progression of the virus in these countries.

Rate of Change in Covid-19 Test Positivity Over-time at National and Sub-nationals.

Positivity Rate is an informative representation of the outbreak size in relation to the number of tests. In addition, it provides useful information in identifying risk areas.

DPR = Daily Postivity Rate
\[DPR = {Number of confirmed(Nc) \over Number of tests(Nt)}\]

This representation is only useful for regions with relatively large number of tests.

Covid-19 Case Fatality Different Demographic Groups at National and Sub-nationals.

Case fatality of COVID-19 was calculated as the number of total deaths due to COVID-19 divided by the number of total confirmed COVID-19 cases.

CFR = Case Fatality Rate
\[CFR = {Number of deaths(Nd) \over Number of cases(Nc)}\]

Under this module general Covid-19 case fatality at National and Sub-national levels; age disagregatted Covid-19 case fatality study; comorbidities versus the fatality rate; sex or gender versus the fatality rate are provided.

This representation is only useful for regions with relatively large number of reported cases and deaths.

How to account for case underestimations in Ethiopia?

Sero-prevalence refers to the frequency of individuals with antibody to a particular virus in a population, and as neutralizing antibodies often last for many years, or even for life, sero prevalence rates usually represent the cumulative experience within a studied population. The first sero-prevalence study was conducted in June/July, 2020 for Ethiopia's major cities. Using results from combat testing movement, sero prevalence for Addis Ababa was adjusted to be 3.55% in month of August, 2020. This prevalence value was later used to account for case under-reporting, and the under-reporting factor was found to be 5.2.

The under-reporting factor was only estimated for the month of the sero-prevalance study.

How COVID 19 Intervention Compliance and Efficacy Changed Over-time in Ethiopia?

This study has been conducted by Addis Ababa University. The study involves weekly monitoring of individual behaviors towards the preventive practice of Covid-19 (Proper Social Distancing Practice, Proper Hand Hygiene Practice and Proper Respiratory Hygiene Practice ) in 15 major cities of Ethiopia, which are, Addis Ababa, Adama, Jimma, Bahir-Dar, Gondar, Hawassa, Wolaita Sodo, Hosaena, Mekelle, Dire-Dawa, Harar, Jigjiga, Gambella, Asossa, and Semera, which can be used to represent the situation at national level. Eight service sectors (hot-spot sites for mobility) are selected based on level of crowding that implies the presence of high risk for the transmission of COVID-19. The eight sector-facilities are: religious places, banks, market places, transport services, food and drinking establishments, health facilities, workplaces, and selected streets.

We have used proper respiratory hygiene practices as proxiy estimation for Facemask complience.

Covid-19 Modeling and Forecasting at National and Sub-national Levels

We have implemented a Curve Fitting method to drive the infection rate or transmission rate of the virus at the national level. Then used this transmission rate to calculate force of infection of Differentail Deterministcs Model. Three scenarios were built to look at the progression in accordance to the Non Pharmaceutical Interventions, which are, Current applied NPI, Mandate easing and Mandate tightening. The considered NPI interventions are compliance and efficacy of Facemask and Social Distancing.

Since the model is deterministics in nature, careful reading/interpretation is required.

Epidemiology of COVID-19 in the Sub-saharan Africa and Ethiopia

In this visualization module, the reported number of Covid-19 cases, deaths, case positivity rate, and case fatality rate for few Sub-saharan countries such as Ethiopia, Kenya, Rwanda, Mozambique, Malawi, and Zambia are presented in simple and interactive manner. In addition, the visualization module provides a brief information on the relationship between case fatality rate of Covid-19 and common comorbidity prevalence in these six countries.

The Analyses in this module are only useful for countries with relatively complete and consistent number of reported cases and deaths.