Kulldorff's scan statistical analysis was used to analyze the spatial, temporal, and spatiotemporal clusters of COVID 19 in Ethiopia from 2021/11/23 to 2021/12/29.
To our knowledge, no other study of this nature has been conducted in Ethiopia.
Our research found that the distribution of COVID 19 cases in Addis Ababa was highly space-time clustered.
Addis Ababa was the epicenter of the COVID 19 outbreak.
Multiple testing problems are taken into consideration in Kulldorff's retrospective scan statistics, which is known as the most powerful method for evaluating geographical and temporal distribution utilizing routinely obtained data (27).
This approach has been used to detect disease clusters all over the world (28-31)
The results of our temporal scanning revealed that COVID 19 had a low-risk phase between November 23, 2021, and December 29, 2021.
The spatiotemporal model utilized in this work examined both time and space distributions at the same time.
The time-space scanning model, as opposed to the distinct spatial and temporal scanning models, produces a conclusion that is closer to the real-world situation.
We discovered that COVID 19 instances were concentrated in Addis Ababa from 2021/11/23-2021/12/29 when we used this model to determine the Spatio-temporal distribution of COVID 19 in Ethiopia.
COVID 19 was more prevalent in Addis Ababa during this time than in other Ethiopian districts.
The causes for the great magnitude of COVID 19 in Addis Ababa are as follows:
Addis Ababa is Ethiopia's capital city, and it has a higher level of testing and quarantine coverage than the rest of the country.
Many people, including Ethiopian long-distance vehicle drivers, traders, and others, have been traveling from Djibouti to Ethiopia via the route that connects the Amhara area, Addis Ababa, and Oromia region since the commencement of the COVID-19 pandemic, mostly owing to geographical proximity (32)
SARS-CoV 2 infection is very dangerous for certain populations.
Sentinel monitoring attempts to detect the early introduction and spread of COVID-19 are especially well-suited for such populations, especially in areas with low vaccination coverage or where layered preventative techniques are not used.
Due to their high risk of exposure or severe illness, the CDC deems the ability to monitor COVID-19 incidence in the following populations to be particularly useful:
Health care workers, residents and staff members of long-term care facilities, incarcerated people, homeless people, and workers in high-density work sites, students and staff members of kindergarten–grade 12 schools and institutions of higher education, incarcerated people, homeless people, and workers in high-density work sites (33-38)
Rising case detection rates can act as an early warning indicator that prevention methods in the facility and the larger community need to be reinforced or introduced.
Furthermore, strategic serial testing can aid in the prevention of SARS-CoV-2 transmission by quickly detecting asymptomatic cases, which are thought to account for at least 50% of SARS-CoV-2 transmission (39-40)
Further prevention and particular COVID 19 control methods should be addressed regarding the vaccine, testing, and prevention practices in other Ethiopian regions, according to our findings.
Our research also confirmed the use of spatial and temporal clustering analysis with ArcGIS and SaTScan in identifying significant COVID 19 space-time clusters in Ethiopia.
This could be utilized to develop COVID19 preventive initiatives at the county level.
However, the study's analysis was limited.
First and foremost, the data were studied at the county level, which is not the smallest administrative regionalization unit.
As a result, we can rule out several important elements.
Second, meteorological and socio-economic aspects were not taken into account in this study.