A GIS based multi criteria analysis for determining COVID-19 vulnerability in Lagos state Nigeria

The COVID-19 pandemic possesses intricate spatial dimensions that, when comprehensively examined, offer profound insights into various aspects of the crisis. Spatial analysis can unravel the multifaceted characteristics of the pandemic, shedding light on its distribution, dynamics, and impact. This research is driven by the imperative need to merge diverse variables, thereby gaining a nuanced understanding of the COVID-19 phenomenon, conducting spatial and spatiotemporal analyses, deciphering its geographical implications for decision-making and daily life, and crafting predictive models to anticipate its evolution. Consequently, this study has a primary objective: determining the COVID-19 vulnerability in Lagos State, Nigeria. The research aims to elucidate the pandemic's spread and distribution patterns, identify its hotspots within Lagos State, and assess COVID-19 vulnerability using the analytical hierarchy process (AHP). The methodology employed in this research encompasses several key steps. Initially, a comprehensive analysis of the spatial distribution of COVID-19 cases between 2020 and 2022 was conducted, allowing for an examination of how the pandemic evolved over this period. Subsequently, a COVID-19 prevalence analysis was performed to delineate the areas most affected by the virus, offering a detailed view of the pandemic's reach. Lastly, a vulnerability index analysis was executed to identify zones with varying levels of vulnerability to COVID-19 within Lagos State. The vulnerability index analysis unveiled diverse vulnerability levels across local government areas (LGAs) within Lagos State. Notably, LGAs such as Ikorodu, Badagary, Eti-Osa, Alimosho, and Epe exhibited relatively larger areas characterized by high vulnerability, signifying the elevated risk of COVID-19 transmission and impact in these regions. In contrast, LGAs like Agege, Ajeromi, Ifako, Ikeja, Mainland, Mushin, Oshodi, Shomolu, and Surulere displayed smaller areas characterized by low vulnerability, indicating a lower risk within these locales. These findings bear significant implications for public health management and decision-making. LGAs with the highest number of confirmed cases, particularly Alimosho and Eti-Osa, demand targeted interventions to curtail the spread of COVID-19 and ensure that resources are channeled where they are most urgently needed. This research underlines the utility of geospatial analysis in pandemic response, offering a valuable tool for governments, healthcare authorities, and policymakers to address the dynamic challenges posed by COVID-19 and protect public health effectively.