Nigeria’s Urbanisation History, Trends, Drivers and Implications

Ojo, Adegbola; Ojewale, Oluwole

doi:10.1007/978-3-030-19765-0_2

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…In Nigeria, there is a divide in terms of WASH and development between the northern and southern regions of the country (S6 Fig) [42]. Northern states are generally more rural, which has potentially resulted in less development.…”

Section: Evidence From the Historical Datamentioning

confidence: 99%

Cholera past and future in Nigeria: are the Global Task Force on Cholera Control’s 2030 targets achievable?

Charnley

Yennan

Ochu

et al. 2022

Preprint

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Background Understanding and continually assessing the achievability of global health targets is key to reducing disease burden and mortality. The Global Task Force on Cholera Control (GTFCC) Roadmap aims to reduce cholera deaths by 90% and eliminate the disease in twenty countries by 2030. The Roadmap has three axes focusing on reporting, response and coordination. Here, we assess the achievability of the GTFCC targets in Nigeria and identify where the three axes could be strengthened to reach and exceed these goals. Methodology/Principal Findings First, historical data were analysed for cholera death rates and a range of well-established cholera risk factors (particularly those included in the best fit models), using correlation, regression, autocorrelation function and AutoRegressive Integrated Moving Averages. Next, future scenario datasets were created (based on varying degrees of socioeconomic development and emission reductions) and used to project future cholera outbreak occurrence and transmission to 2070. The two models used were a generalised linear model and a random forest model. The historical data highlighted the significant cholera burden in Nigeria and its correlation with sanitation access. The projections suggest that significant reductions in cholera cases could be achieved by 2030, particularly in the more developed southern states, but increases in cases remain a possibility. Meeting the 2030 target, nationally, currently looks unachievable and we propose a new 2050 target focusing on reducing regional inequities. Conclusion/Significance The 2030 targets could potentially be reached by 2030 in some parts of Nigeria, but more effort is needed to reach these targets at a national level, particularly through access and incentives to cholera testing, sanitation expansion, poverty alleviation and urban planning. The results highlight the importance of and how modelling studies can be used to inform cholera policy and the potential for this to be applied in other contexts.

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Section: Evidence From the Historical Datamentioning

confidence: 99%

Cholera past and future in Nigeria: are the Global Task Force on Cholera Control’s 2030 targets achievable?

Charnley

Yennan

Ochu

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…higher fertility and low mortality rates), migration and the city's regional economic and industrial strategic influences. The magnitude of these individual factors' contributions is debatable; however, among researchers, there is a preponderance of views in favor of natural population as the dominant driver of urban spatial evolution (Bloch et al, 2015;Ojo and Ojewale, 2019). As Nigeria began the early accelerated phase of urban transition, natural population and urban migration accounting for 48 and 37% respectively, are the major contributors to the evolutionary phase of urban demographic statistics while 15% of rural areas are reclassified into towns and urban centers (Fox et al, 2018).…”

Section: Classified Lulc Imageriesmentioning

confidence: 99%

Monitoring Spatial-Temporal Transition Dynamics of Transport Infrastructure Space in Urban Growth Phenomena: A Case Study of Lagos—Nigeria

Otuoze

Hunt

Jefferson

2021

Front. Future Transp.

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Lagos is one of the fastest growing world mega-cities with a huge urban mobility crisis, the traditional aggregate city’s development model could not provide reliable scientific solutions to monitor the competing demands of various land-use components and the urbanization’s effects on transport infrastructure space. This study uses a disaggregated predictive spatial modeling approach to investigate the evolutionary dynamics of transportation infrastructure space to address the fragmented urban chain process. The methodology involves analysis and modeling of the land-use spatial transition changes that have occurred over the past three decades using three Landsat imagery epochs (1984, 2013, and 2019) in remote sensing ARC-GIS 10.7. Furthermore, the prediction of the two-temporal milestones (2030 and 2050) using hybrid cellular automata-Markov (CA-Markov) implemented in IDIRISI SELVA 17.0 software when the tides of social-demographic factors were expected to bring about significant urban spatial transformation. The forecast results are expected to increase the area for transport infrastructure spaces by 93 km2 (7.3%) in 2030 and 157 km2 (12.4%) in 2050. The model’s kappa reliability coefficient estimates for the three temporal scales (k1984 = 85%; k2013 = 88% and k2019 = 89%) are higher than the 80% minimum adjudged strong agreement between the ground truth and prediction classified images in literature. The model provides efficient tool in urban development planning and sustainable transport decisions.

show abstract

Cholera past and future in Nigeria: Are the Global Task Force on Cholera Control’s 2030 targets achievable?

et al. 2023

View full text Add to dashboard Cite

Background Understanding and continually assessing the achievability of global health targets is key to reducing disease burden and mortality. The Global Task Force on Cholera Control (GTFCC) Roadmap aims to reduce cholera deaths by 90% and eliminate the disease in twenty countries by 2030. The Roadmap has three axes focusing on reporting, response and coordination. Here, we assess the achievability of the GTFCC targets in Nigeria and identify where the three axes could be strengthened to reach and exceed these goals. Methodology/Principal findings Using cholera surveillance data from Nigeria, cholera incidence was calculated and used to model time-varying reproduction number (R). A best fit random forest model was identified using R as the outcome variable and several environmental and social covariates were considered in the model, using random forest variable importance and correlation clustering. Future scenarios were created (based on varying degrees of socioeconomic development and emission reductions) and used to project future cholera transmission, nationally and sub-nationally to 2070. The projections suggest that significant reductions in cholera cases could be achieved by 2030, particularly in the more developed southern states, but increases in cases remain a possibility. Meeting the 2030 target, nationally, currently looks unlikely and we propose a new 2050 target focusing on reducing regional inequities, while still advocating for cholera elimination being achieved as soon as possible. Conclusion/Significance The 2030 targets could potentially be reached by 2030 in some parts of Nigeria, but more effort is needed to reach these targets at a national level, particularly through access and incentives to cholera testing, sanitation expansion, poverty alleviation and urban planning. The results highlight the importance of and how modelling studies can be used to inform cholera policy and the potential for this to be applied in other contexts.

show abstract

Nigeria’s Urbanisation History, Trends, Drivers and Implications

Cited by 3 publications

References 42 publications

Cholera past and future in Nigeria: are the Global Task Force on Cholera Control’s 2030 targets achievable?

Cholera past and future in Nigeria: are the Global Task Force on Cholera Control’s 2030 targets achievable?

Monitoring Spatial-Temporal Transition Dynamics of Transport Infrastructure Space in Urban Growth Phenomena: A Case Study of Lagos—Nigeria

Cholera past and future in Nigeria: Are the Global Task Force on Cholera Control’s 2030 targets achievable?

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