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Rural-urban migration often triggers additional demand for housing and infrastructural development to cater for the growing population in urban areas. Consequently, town planners and urban development authorities need to understand the urban development trend to make sustainable urban planning decisions. Yet, methods to analyse changes and trends in urban spatial development are often complex and require costly data collection. This article thus presents a simplified method to analyse the urban development trend in an area. The method integrates Google Earth (GE) historical imagery (baseline data) and unmanned aerial vehicle (UAV) photogrammetry (recent data) to quantify the changes over time. This approach can be applied to study the urban development trends in low-income countries with budget constraints. The method is discussed under four main headings: (1) background, (2) method details, (3) limitations, and (4) conclusion.â¢Google Earth historical image can be extracted with its associated world file.â¢The population of an area can be estimated by using average household size data and the number of residential buildings in the area.â¢The building height ratio can be used to ascertain if the land is being used parsimoniously.
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Urban development will likely continue to increase in suburban areas to cater for the growing human population. In Nigeria, the relevant analysis of these urban developments is not well documented. This article presents spatiotemporal datasets for analysing urban developments in a suburb of Kuje, an Area Council within the Federal Capital Territory of Nigeria. Data from Google Earth (GE) historical imagery of 2005 was used as a baseline for analysis and was compared with a UAV digital orthomosaic of 2019 to quantify urban developments. This data provides useful information on the status of urban development that has taken place in the Kuje suburb over 14 years. The data will be of great importance to town planners and urban development authorities for future planning, and for making informed decisions about urban development issues in the area.
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The interrelationships between air quality, land cover change, and road networks in the Lagos megacity have not been explored. Globally, there are knowledge gaps in understanding these dynamics, especially using remote sensing data. This study used multi-temporal and multi-spectral Landsat imageries at four epochs (2002, 2013, 2015, and 2020) to evaluate the aerosol optical thickness (AOT) levels in relation to land cover and road networks in the Lagos megacity. A look-up table (LUT) was generated using Py6S, a python-based 6S module, to simulate the AOT using land surface reflectance and top of atmosphere reflectance. A comparative assessment of the method against in situ measurements of particulate matter (PM) at different locations shows a strong positive correlation between the imagery-derived AOT values and the PMs. The AOT concentration across the land cover and road networks showed an increasing trend from 2002 to 2020, which could be explained by urbanization in the megacity. The higher concentration of AOT along the major roads is attributed to the high air pollutants released from vehicles, including home/office generators and industries along the road corridors. The continuous rise in pollutant values requires urgent intervention and mitigation efforts. Remote sensing-based AOT monitoring is a possible solution.
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Poluentes Atmosféricos , Monitoramento Ambiental , Monitoramento Ambiental/métodos , Nigéria , Poluentes Atmosféricos/análise , Material Particulado/análise , Aerossóis/análiseRESUMO
Introduction: Vaccines alone do not control pandemics, but vaccinations. The hope of COVID-19 pandemic control is hinged on vaccinations and other public health measures. This systematic review/meta-analysis (SR/MA) investigated the factors that inform coronavirus vaccine uptake globally in an attempt to improve COVID-19 immunization. Method: The PRISMA 2020 methodology was used for this review. A total of 2902 articles were identified from electronic databases and other sources. After screening, 33 articles were included in the review and quantitative meta-analysis. Comprehensive meta-analysis software version 3 was used for the meta-analysis. Results: We observed that vaccine effectiveness, side effects and the proportion of acquaintances vaccinated significantly influenced respondents' COVID-19 immunization decision. Also, associations of vaccine effectiveness, smaller risks to serious side effects, free and voluntary vaccinations and fewer vaccine doses, and longer duration to wanning were observed. We also observed variations in vaccine hesitancy trends in studies carried out in Asia, Europe, America, and Africa. Conclusion: Wanning and acquaintance's vaccination status as factors to vaccination are insights the present paper is bringing to the limelight. Health promotion and COVID-19 vaccination planning are crucial for enhancing vaccine uptake.
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COVID-19 , Coronavirus , Humanos , Vacinas contra COVID-19 , Pandemias , COVID-19/prevenção & controle , VacinaçãoRESUMO
INTRODUCTION: the spread and diffusion of COVID-19 undoubtedly shows strong spatial connotations and alignment with the physical indices of civilization and globalization. Several spatial risk factors have possible influence on its dispersal trajectory. Understanding their influence is critical for mobilization, sensitization and managing non-pharmaceutical interventions at the appropriate spatial-administrative units. METHODS: on 01 April 2020, we constructed a rapid spatial diagnostics and generated vulnerability map for COVID-19 infection spread at state level using 12 core spatial drivers. The risk factors used include established COVID-19 cases (as at 01 April 2020), population, proximity to the airports, inter-state road traffic, intra-state road traffic, intra city traffic, international road traffic, possible influx of elites from abroad, preponderance of high risk political elite, likelihood of religious gathering, likelihood of other social gatherings, and proximity to existing COVID-19 test centers. These were also tested as predictors of COVID-19 spread using multiple regression analysis. RESULTS: the results show that 6 States - Lagos, Kano, Katsina, Kaduna, Oyo and Rivers - and the Federal Capital Territory have very high vulnerability, 17 states have high vulnerability and 13 states have medium vulnerability to COVID-19 transmission. Several drivers show a strong association with COVID-19 with the coefficient of correlation ranging from 0.983 - 0.995. The regression analysis indicates that between 96.6 and 99.0 percent of the total variation in the COVID-19 infections across Nigeria can be explained by the predictors. CONCLUSION: the spatial pattern of infection across the states are substantially consistent with the predicted pattern of vulnerability.
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COVID-19/epidemiologia , Análise Espacial , Populações Vulneráveis , COVID-19/transmissão , Humanos , Nigéria/epidemiologia , Fatores de RiscoRESUMO
BACKGROUND: Plasmodium falciparum-resistance to sulphadoxine-pyrimethamine (SP) has been largely reported among pregnant women. However, the profile of resistance markers to SP dihydrofolate reductase (dhfr) and dihydropteroate synthase (dhps) in the general population are varied and not frequently monitored. Currently, SP is used as partner drug for artemisinin combination therapy (SP-artesunate) in some sub-Saharan African countries or as a prophylactic drug in intermittent preventive treatment of malaria during pregnancy and infants and in seasonal malaria chemoprevention (SMC). Profiling of P. falciparum-resistant genotypes to SP is dynamic and critical in providing data that would be useful for malaria control programmes. This study assessed the profile of dhfr and dhps genes genotypes among individuals with malaria in Lagos, Nigeria. METHODS: Molecular markers of SP resistance were identified by nested PCR and sequenced among malaria positive dried blood spots (DBS) that were collected from individuals attending health facilities from January 2013 to February 2014 and during community surveys from October 2010 to September 2011 across different Local Government Areas of Lagos State, Nigeria. RESULTS: A total of 242 and 167 samples were sequenced for dhfr and dhps, respectively. Sequence analysis of dhfr showed that 95.5% (231/242), 96.3% (233/242) and 96.7% (234/242) of the samples had N51I, C59R and S108N mutant alleles, respectively. The prevalence of dhps mutation at codons A437G, A613S, S436A, A581G, I431V and K540E were 95.8% (160/167), 41.9% (70/167), 41.3% (69/167), 31.1% (52/167), 25.1% (42/167), and 1.2% (2/167) respectively. The prevalence of triple mutations (CIRNI) in dhfr was 93.8% and 44.3% for the single dhps haplotype mutation (SGKAA). Partial SP-resistance due to quadruple dhfr-dhps haplotype mutations (CIRNI-SGKAA) and octuple haplotype mutations (CIRNI-VAGKGS) with rate of 42.6% and 22.0%, respectively has been reported. CONCLUSIONS: There was increased prevalence in dhfr triple haplotype mutations when compared with previous reports in the same environment but aligned with high prevalence in other locations in Nigeria and other countries in Africa. Also, high prevalence of dhfr and dhps mutant alleles occurred in the study areas in Lagos, Nigeria five to eight years after the introduction of artemisinin combination therapy underscores the need for continuous monitoring.