%0 Journal Article %1 joel_izuchukwu_igbokwe_2024_10674976 %A Igbokwe, Joel. Izuchukwu %A Akinpelu, Akinwumi Abodunrin %A Oliha, Andrew. Osagie %A Anyadiegwu, Princecharles Chukwuemeka %A Ojanikele, Wille Augustine %D 2024 %J Global Journal of Engineering and Technology Advances %K COVID-19 %N 2 %P 070–088 %R 10.30574/gjeta.2023.17.2.0225 %T Geospatial modeling and analysis of COVID-19 prevalence in Lagos state Nigeria %U https://gjeta.com/content/geospatial-modeling-and-analysis-covid-19-prevalence-lagos-state-nigeria %V 17 %X The impact of COVID-19 pandemic has spatial dimensions which when properly interpreted could lead to better understanding of different characteristics of the pandemic. Thus, the impact of COVID-19 can be mapped for spatial analysis of its attributes. From health science, the research needs include the ability to cross variables of different kinds to interpret the COVID-19 phenomenon, its spatial analysis and spatiotemporal dimensions, its geographical impact on decision-making and everyday life, and predictive modelling of the evolution of the disease. For these reasons, this research aimed at geospatial modelling and analysis of COVID-19 prevalence in Lagos State Nigeria with a view to determine the spread and distribution pattern of COVID-19 as well as its hotspots in Lagos State Nigeria. Its objectives are to: identify and model the spatial distribution of COVID-19 in Lagos State and map the prevalence of COVID-19 in Lagos State. The methodology involved the analysis of the spatial distribution of COVID-19 between 2020 and 2022 and COVID-19 prevalence analysis. Results indicate a substantial surge in confirmed COVID-19 cases, rising from 21,717 to 56,596 during the study period. Alimosho and Eti-Osa LGAs emerged as the most affected regions, reporting the highest total confirmed cases. Additionally, confirmed deaths increased from 4,090 in 2020 to 9,874 in 2022, with Eti-Osa consistently reporting the highest number of fatalities, followed by Ikorodu and Surulere. Assessing the prevalence of confirmed cases and deaths across different LGAs, Eti-Osa consistently exhibited the highest prevalence, indicating a significant proportion of cases and deaths relative to its population.

@article{joel_izuchukwu_igbokwe_2024_10674976, abstract = {The impact of COVID-19 pandemic has spatial dimensions which when properly interpreted could lead to better understanding of different characteristics of the pandemic. Thus, the impact of COVID-19 can be mapped for spatial analysis of its attributes. From health science, the research needs include the ability to cross variables of different kinds to interpret the COVID-19 phenomenon, its spatial analysis and spatiotemporal dimensions, its geographical impact on decision-making and everyday life, and predictive modelling of the evolution of the disease. For these reasons, this research aimed at geospatial modelling and analysis of COVID-19 prevalence in Lagos State Nigeria with a view to determine the spread and distribution pattern of COVID-19 as well as its hotspots in Lagos State Nigeria. Its objectives are to: identify and model the spatial distribution of COVID-19 in Lagos State and map the prevalence of COVID-19 in Lagos State. The methodology involved the analysis of the spatial distribution of COVID-19 between 2020 and 2022 and COVID-19 prevalence analysis. Results indicate a substantial surge in confirmed COVID-19 cases, rising from 21,717 to 56,596 during the study period. Alimosho and Eti-Osa LGAs emerged as the most affected regions, reporting the highest total confirmed cases. Additionally, confirmed deaths increased from 4,090 in 2020 to 9,874 in 2022, with Eti-Osa consistently reporting the highest number of fatalities, followed by Ikorodu and Surulere. Assessing the prevalence of confirmed cases and deaths across different LGAs, Eti-Osa consistently exhibited the highest prevalence, indicating a significant proportion of cases and deaths relative to its population.}, added-at = {2024-03-17T02:41:42.000+0100}, author = {Igbokwe, Joel. Izuchukwu and Akinpelu, Akinwumi Abodunrin and Oliha, Andrew. Osagie and Anyadiegwu, Princecharles Chukwuemeka and Ojanikele, Wille Augustine}, biburl = {https://www.bibsonomy.org/bibtex/2da6fe8acb20e5652d329b5eaaf833887/gjetajournal}, doi = {10.30574/gjeta.2023.17.2.0225}, interhash = {316b4dee6f246bf6541138461dd25e51}, intrahash = {da6fe8acb20e5652d329b5eaaf833887}, issn = {2582-5003}, journal = {{Global Journal of Engineering and Technology Advances}}, keywords = {COVID-19}, month = feb, number = 2, pages = {070–088}, timestamp = {2024-03-17T02:41:42.000+0100}, title = {Geospatial modeling and analysis of COVID-19 prevalence in Lagos state Nigeria}, url = {https://gjeta.com/content/geospatial-modeling-and-analysis-covid-19-prevalence-lagos-state-nigeria}, volume = 17, year = 2024 }