scholarly journals Measuring the accuracy of gridded human population density surfaces: A case study in Bioko Island, Equatorial Guinea

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0248646
Author(s):  
Brendan Fries ◽  
Carlos A. Guerra ◽  
Guillermo A. García ◽  
Sean L. Wu ◽  
Jordan M. Smith ◽  
...  
Keyword(s):  
Rural Areas ◽  
Gold Standard ◽  
Urban Areas ◽  
Human Population ◽  
Census Data ◽  
Equatorial Guinea ◽  
Population Densities ◽  
Bioko Island ◽  
Statistical Measures ◽  
Malaria Model

Background Geospatial datasets of population are becoming more common in models used for health policy. Publicly-available maps of human population make a consistent picture from inconsistent census data, and the techniques they use to impute data makes each population map unique. Each mapping model explains its methods, but it can be difficult to know which map is appropriate for which policy work. High quality census datasets, where available, are a unique opportunity to characterize maps by comparing them with truth. Methods We use census data from a bed-net mass-distribution campaign on Bioko Island, Equatorial Guinea, conducted by the Bioko Island Malaria Elimination Program as a gold standard to evaluate LandScan (LS), WorldPop Constrained (WP-C) and WorldPop Unconstrained (WP-U), Gridded Population of the World (GPW), and the High-Resolution Settlement Layer (HRSL). Each layer is compared to the gold-standard using statistical measures to evaluate distribution, error, and bias. We investigated how map choice affects burden estimates from a malaria prevalence model. Results Specific population layers were able to match the gold-standard distribution at different population densities. LandScan was able to most accurately capture highly urban distribution, HRSL and WP-C matched best at all other lower population densities. GPW and WP-U performed poorly everywhere. Correctly capturing empty pixels is key, and smaller pixel sizes (100 m vs 1 km) improve this. Normalizing areas based on known district populations increased performance. The use of differing population layers in a malaria model showed a disparity in results around transition points between endemicity levels. Discussion The metrics in this paper, some of them novel in this context, characterize how these population maps differ from the gold standard census and from each other. We show that the metrics help understand the performance of a population map within a malaria model. The closest match to the census data would combine LandScan within urban areas and the HRSL for rural areas. Researchers should prefer particular maps if health calculations have a strong dependency on knowing where people are not, or if it is important to categorize variation in density within a city.

scholarly journals Measuring the accuracy of gridded human population density surfaces: a case study in Bioko Island, Equatorial Guinea

2020 ◽  
Author(s):  
Brendan F Fries ◽  
Carlos A Guerra ◽  
Guillermo A García ◽  
Sean L Wu ◽  
Jordan M Smith ◽  
...  
Keyword(s):  
Gold Standard ◽  
Urban Areas ◽  
Human Population ◽  
Census Data ◽  
Sub Saharan Africa ◽  
Equatorial Guinea ◽  
Population Densities ◽  
Bioko Island ◽  
Statistical Measures ◽  
Malaria Model

Geospatial datasets of population are becoming more common in models used for health policy. Publicly-available maps of human population in sub-Saharan Africa make a consistent picture from inconsistent census data, and the techniques they use to impute data makes each population map unique. Each mapping model explains its methods, but it can be difficult to know which map is appropriate for which policy work. Gold-standard census datasets, where available, are a unique opportunity to characterize maps by comparing them with truth. We use census data from Bioko Island, in Equatorial Guinea, to evaluate LandScan (LS), WorldPop (WP), and the High-Resolution Settlement Layer (HRSL). Each layer is compared to the gold-standard using statistical measures to evaluate distribution, error, and bias. We investigated how map choice affects burden estimates from a malaria prevalence model. Specific population layers were able to match the gold-standard distribution at different population densities. LandScan was able to most accurately capture highly urban distribution, HRSL matched best at all other lower population densities and WorldPop performed poorly everywhere. Correctly capturing empty pixels is key, and smaller pixel sizes (100 m vs 1 km) improve this. Normalizing areas based on known district populations increased performance. The use of differing population layers in a malaria model showed a disparity in results around transition points between endemicity levels. The metrics in this paper, some of them novel in this context, characterize how these population maps differ from the gold standard census and from each other. We show that the metrics help understand the performance of a population map within a malaria model. The closest match to the census data would combine LandScan within urban areas and the HRSL for rural areas. Researchers should prefer particular maps if health calculations have a strong dependency on knowing where people are not, or if it is important to categorize variation in density within a city.

Using a Rural Index to Assess Crime Risk and Crime Prevention Behavior Across the Urban–Rural Continuum: A Japanese Case Study

2021 ◽  
pp. 105756772110399
Author(s):  
Takahito Shimada ◽  
Ai Suzuki
Keyword(s):  
Crime Prevention ◽  
Rural Areas ◽  
Urban Areas ◽  
Census Data ◽  
Motor Vehicle ◽  
Linear Pattern ◽  
Combining Data ◽  
Prevention Behavior ◽  
Urban Rural ◽  
Municipal Level

The study proposes a new method of crime analysis combining data from multiple secondary data sources (census, open crime data, and social survey) to assess the risk of victimization and crime prevention behavior in resource-limited settings. Principal component analysis was performed on municipal-level census data ( n = 1,883) to generate a rural index that represents the ecological characteristics of each municipality across the urban–rural continuum. Multilevel logistic analyses were then applied to crime incident data ( n = 207,771) to assess the municipal-level effects on victims’ use of locks in motor vehicle and bicycle thefts. A linear pattern of victimization was found for bicycle theft (the risk was about one-thirtieth in the most rural municipalities than that in the most urban municipalities), while the pattern found was nonlinear for motor vehicle thefts. The analysis also revealed that victims in rural areas were less likely to have locked their vehicles before they were stolen than those living in urban areas. Using the rural index developed in this study, police forces can have a better understanding of crime problems in their jurisdiction across the urban–rural continuum. The study discusses the implications of the results for crime prevention and problem-solving policymaking in the urban–rural continuum.

scholarly journals Mapping poverty using mobile phone and satellite data

2017 ◽  
Vol 14 (127) ◽  
pp. 20160690 ◽  
Author(s):  
Jessica E. Steele ◽  
Pål Roe Sundsøy ◽  
Carla Pezzulo ◽  
Victor A. Alegana ◽  
Tomas J. Bird ◽  
...  
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Census Data ◽  
Data Sources ◽  
Human Potential ◽  
Public And Private ◽  
Middle Income ◽  
Mobile Data ◽  
Poverty Measures ◽  
Urban And Rural Areas

Poverty is one of the most important determinants of adverse health outcomes globally, a major cause of societal instability and one of the largest causes of lost human potential. Traditional approaches to measuring and targeting poverty rely heavily on census data, which in most low- and middle-income countries (LMICs) are unavailable or out-of-date. Alternate measures are needed to complement and update estimates between censuses. This study demonstrates how public and private data sources that are commonly available for LMICs can be used to provide novel insight into the spatial distribution of poverty. We evaluate the relative value of modelling three traditional poverty measures using aggregate data from mobile operators and widely available geospatial data. Taken together, models combining these data sources provide the best predictive power (highest r 2 = 0.78) and lowest error, but generally models employing mobile data only yield comparable results, offering the potential to measure poverty more frequently and at finer granularity. Stratifying models into urban and rural areas highlights the advantage of using mobile data in urban areas and different data in different contexts. The findings indicate the possibility to estimate and continually monitor poverty rates at high spatial resolution in countries with limited capacity to support traditional methods of data collection.

scholarly journals Diet Quality and Neighborhood Environment in the Atlantic Partnership for Tomorrow’s Health Project

Nutrients ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 3217
Author(s):  
Kaitlyn Gilham ◽  
Qianqian Gu ◽  
Trevor J. B. Dummer ◽  
John J. Spinelli ◽  
Rachel A. Murphy
Keyword(s):  
Population Density ◽  
Diet Quality ◽  
Rural Areas ◽  
Urban Areas ◽  
Census Data ◽  
Social Deprivation ◽  
Neighborhood Environment ◽  
Neighbourhood Environment ◽  
Deprived Neighbourhoods ◽  
Intermediate Density

An understanding of relationships between different constructs of the neighbourhood environment and diet quality is needed to inform public health interventions. This study investigated associations between material deprivation, social deprivation and population density with diet quality in a cohort of 19,973 Canadian adults aged 35 to 69 years within the Atlantic PATH cohort study. Diet quality, a metric of how well diet conforms to recommendations was determined from a 24-item food frequency questionnaire. Neighbourhood environment data were derived from dissemination area level Census data. Two deprivation indices were evaluated: material and social deprivation, which reflect access to goods and amenities and social relationships. Multi-level models were used to estimate relationships (mean differences and 95% CI) between neighbourhood environment and diet quality, adjusting for covariates. Mean diet quality was lower in the most socially deprived neighbourhoods compared to the least socially deprived: −0.56, 95% CI (−0.88, −0.25). Relationships between diet quality and population density differed between urban and rural areas (p-interaction < 0.0001). In rural areas, diet quality was higher in intermediate-density neighbourhoods: 0.54, 95% CI (0.05, 1.03). In urban areas, diet quality was lower in intermediate-density and the most-dense neighbourhoods: −0.84, 95% CI (−1.28, −0.40) and −0.72, 95% CI (−1.20, −0.25). Our findings suggest socially deprived and high-density neighbourhoods are associated with lower diet quality and possible urban-rural differences in neighbourhood environment-diet quality relationships. Additional studies are needed to determine the temporal nature of relationships and whether differences in diet quality are meaningful.

scholarly journals Model simulations of cooking organic aerosol (COA) over the UK using estimates of emissions based on measurements at two sites in London

2016 ◽  
Vol 16 (21) ◽  
pp. 13773-13789 ◽  
Author(s):  
Riinu Ots ◽  
Massimo Vieno ◽  
James D. Allan ◽  
Stefan Reis ◽  
Eiko Nemitz ◽  
...  
Keyword(s):  
Population Density ◽  
Atmospheric Chemistry ◽  
Rural Areas ◽  
Urban Areas ◽  
Census Data ◽  
Organic Aerosol ◽  
Balance Model ◽  
Rural Site ◽  
Annual Average ◽  
The Uk

Abstract. Cooking organic aerosol (COA) is currently not included in European emission inventories. However, recent positive matrix factorization (PMF) analyses of aerosol mass spectrometer (AMS) measurements have suggested important contributions of COA in several European cities. In this study, emissions of COA were estimated for the UK, based on hourly AMS measurements of COA made at two sites in London (a kerbside site in central London and an urban background site in a residential area close to central London) for the full calendar year of 2012 during the Clean Air for London (ClearfLo) campaign. Iteration of COA emissions estimates and subsequent evaluation and sensitivity experiments were conducted with the EMEP4UK atmospheric chemistry transport modelling system with a horizontal resolution of 5 km  ×  5 km. The spatial distribution of these emissions was based on workday population density derived from the 2011 census data. The estimated UK annual COA emission was 7.4 Gg per year, which is an almost 10 % addition to the officially reported UK national total anthropogenic emissions of PM2.5 (82 Gg in 2012), corresponding to 320 mg person−1 day−1 on average. Weekday and weekend diurnal variation in COA emissions were also based on the AMS measurements. Modelled concentrations of COA were then independently evaluated against AMS-derived COA measurements from another city and time period (Manchester, January–February 2007), as well as with COA estimated by a chemical mass balance model of measurements for a 2-week period at the Harwell rural site (∼ 80 km west of central London). The modelled annual average contribution of COA to ambient particulate matter (PM) in central London was between 1 and 2 µg m−3 (∼ 20 % of total measured OA1) and between 0.5 and 0.7 µg m−3 in other major cities in England (Manchester, Birmingham, Leeds). It was also shown that cities smaller than London can have a central hotspot of population density of smaller area than the computational grid cell, in which case higher localized COA concentrations than modelled here may be expected. Modelled COA concentrations dropped rapidly outside of major urban areas (annual average of 0.12 µg m−3 for the Harwell location), indicating that although COA can be a notable component in urban air, it does not have a significant effect on PM concentrations on rural areas. The possibility that the AMS-PMF apportionment measurements overestimate COA concentrations by up to a factor of 2 is discussed. Since COA is a primary emission, any downward adjustments in COA emissions would lead to a proportional linear downward scaling in the absolute magnitudes of COA concentrations simulated in the model.

scholarly journals Household food security access, and amidst Covid-19: a study case in Equatorial Guinea

2021 ◽  
Vol 8 (10) ◽  
pp. 131-145
Author(s):  
Emilio Edu Nguema Osea ◽  
Wang Jian
Keyword(s):  
Food Security ◽  
Urban Areas ◽  
Equatorial Guinea ◽  
Living Standard ◽  
Household Food Security ◽  
Hunger Level ◽  
Bioko Island ◽  
Rural And Urban Areas ◽  
Household Food ◽  
Rural And Urban

Food is of primary importance for households. Equatorial Guinea (EG) has progressed much in income growth but less in living standard, which includes food security. To situating food–insecurity prevalence in EG, this paper researches household food security-access, and its link-cause to agriculture–considering the Covid-19– using the Household Hunger Scale (HHS). On the data, we surveyed 400 households, imparted in EG rural and urban areas of Bioko Island and the mainland. The results reveal a 2.4 mean for both rural and urban Bioko, placing households at moderate hunger level. On the mainland, rural scores 3.21 (the area most affected), yet falling in moderate hunger level; while the urban scores best 0.64 and stands in the food-safe zone. It derives that diet is rather monotonous and embrace–mainly– carbohydrates rice, bread, cassava, and plantain. A focus on boosting the productivity of staples is paramount for Food security and even national security.

scholarly journals The urban heat island effect is closely related to cicada density in metropolitan Seoul

2017 ◽  
Author(s):  
Hoa Q. Nguyen ◽  
Yuseob Kim ◽  
Yikweon Jang
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Urban Areas ◽  
Underlying Mechanism ◽  
Heat Island ◽  
Population Densities ◽  
Island Effect ◽  
Significant Difference ◽  
Order Of Magnitude ◽  
Urban Heat

Background. Cryptotympana atrata and Hyalessa fuscata are the most abundant cicada species in the Korean Peninsula, where their population densities are higher in urban areas than in rural ones. The urban heat island (UHI) effect, wherein human activities cause urban areas to be significantly warmer than surrounding rural areas, may underlie this difference. We predicted a positive relationship between the degrees of UHI in urban areas and population densities of C. atrata and H. fuscata. Methods. To test this prediction, we examined cicada population densities in three groups: those of high and low UHI areas within metropolitan Seoul, and suburban areas. Enumeration surveys of cicada exuviae were conducted from July to August, 2015. Results. C. atrata and H. fuscata constituted almost 30% and 70% of the cicada populations, respectively, collected across all sampling localities. No significant difference in species composition was observed, regardless of groups, but the densities of the two species were significantly higher in urban areas with high UHI than in other groups. Specifically, densities of C. atrata in high UHI areas were approximately seven and four times higher compared to those in low UHI and in suburban groups, respectively. The order of magnitude was greater in H. fuscata, where densities in high UHI group were respectively 22 and six times higher than those in low UHI and in suburban groups. Discussion. These results suggest that the UHI effect may be closely linked to high cicada densities in metropolitan Seoul, although the underlying mechanism for this remains unclear.

scholarly journals PREDICTION OF THE NUMBER OF AND CARE COSTS FOR DISABLED OLDER ADULTS FROM 2020 TO 2050 IN URBAN AND RURAL AREAS IN CHINA

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S847-S847
Author(s):  
liangwen zhang ◽  
Ya Fang
Keyword(s):  
Older Adults ◽  
Rural Areas ◽  
Urban Areas ◽  
Census Data ◽  
The Elderly ◽  
Severe Disabilities ◽  
Term Care ◽  
Total Care ◽  
Urban And Rural Areas ◽  
Care Costs

Abstract Disability for the elderly has become a crucial policy concerns in rapidly aging Asia counties, especially in China. This study aimed to predict the trend of the number of and care costs for disabled older adults from 2020 to 2050 in urban and rural areas in China. Population Administration Decision Information System was used to predict the population of China by urban and rural areas and age group from 2020 to 2050. Monte Carlo simulation and Policy Simulation Model were used to estimate the number and care costs of disabled elderly between urban and rural areas, based on the Chinese latest census data, statistical yearbook, and national survey database. The total disabled population rises rapidly from 43.75 million in 2020 to 91.4 million in 2050, of which 69.7% were urban adults. Compared with the values in 2020, the growth rates of the adults with mild, moderate and severe disabilities were 108%, 104% and 120% in 2050, respectively. The value were 167% and 39% in urban and rural areas, respectively. By 2050, the total care costs increase from 538.0 billion yuan in 2020 to 8530.8 billion yuan, of which 80.2% occurs in urban areas. The predicted results indicate that the numbers and care costs for disabled older adults increase sharply from 2020 to 2050, especially in urban areas of China. It provided a series of evidence for the establishment of the long-term care insurance system in China.

scholarly journals Climate hazards in small and medium cities in the Amazon Delta and Estuary: challenges for resilience

2019 ◽  
Vol 32 (1) ◽  
pp. 195-212
Author(s):  
Ana C B De Lima ◽  
Oriana Almeida ◽  
Miguel Pinedo-Vasquez ◽  
Tien Ming Lee ◽  
Sergio Rivero ◽  
...  
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Local Governments ◽  
Census Data ◽  
High Mobility ◽  
Small Cities ◽  
Climate Vulnerability ◽  
Climate Hazards ◽  
Urban And Rural Areas ◽  
Adaptive Actions

Recent research on climate vulnerability in cities in the Amazon Delta and Estuary (ADE) shows that about 1.2 million people are at risk of flooding due to the rapid unplanned occupation of lowlands and the absence of investment in infrastructure and services. In this study, we use secondary climate and census data, interviews and focus groups in four small cities in the Amazon Delta and Estuary (SCADEs), to discuss how residents and local governments perceive and respond to climate hazards and their implications. These SCADEs may be better equipped than other urban areas to deal with challenges brought by climate change, due partially to residents’ high mobility between urban and rural areas and a tradition of adaptive actions in a dynamic social and environmental context. However, persistent flooding and sinkholes demonstrate the limited capacity of local governments to cope with the dynamics of accelerated occupation of floodplain areas in SCADEs.

scholarly journals The urban heat island effect is closely related to cicada density in metropolitan Seoul

2017 ◽  
Author(s):  
Hoa Q. Nguyen ◽  
Yuseob Kim ◽  
Yikweon Jang
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Urban Areas ◽  
Underlying Mechanism ◽  
Heat Island ◽  
Population Densities ◽  
Island Effect ◽  
Significant Difference ◽  
Order Of Magnitude ◽  
Urban Heat

Background. Cryptotympana atrata and Hyalessa fuscata are the most abundant cicada species in the Korean Peninsula, where their population densities are higher in urban areas than in rural ones. The urban heat island (UHI) effect, wherein human activities cause urban areas to be significantly warmer than surrounding rural areas, may underlie this difference. We predicted a positive relationship between the degrees of UHI in urban areas and population densities of C. atrata and H. fuscata. Methods. To test this prediction, we examined cicada population densities in three groups: those of high and low UHI areas within metropolitan Seoul, and suburban areas. Enumeration surveys of cicada exuviae were conducted from July to August, 2015. Results. C. atrata and H. fuscata constituted almost 30% and 70% of the cicada populations, respectively, collected across all sampling localities. No significant difference in species composition was observed, regardless of groups, but the densities of the two species were significantly higher in urban areas with high UHI than in other groups. Specifically, densities of C. atrata in high UHI areas were approximately seven and four times higher compared to those in low UHI and in suburban groups, respectively. The order of magnitude was greater in H. fuscata, where densities in high UHI group were respectively 22 and six times higher than those in low UHI and in suburban groups. Discussion. These results suggest that the UHI effect may be closely linked to high cicada densities in metropolitan Seoul, although the underlying mechanism for this remains unclear.

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