Applied Geography (Sevenoaks, England)[JOURNAL]
Sun
108 papers
Socioeconomic inequalities in food outlet access through an online food delivery service in England: A cross-sectional descriptive analysis.
Keeble M, Adams J, Bishop TRP … +1 more , Burgoine T
Appl Geogr · 2021 Aug · PMID 34345056 · Full text
Online food delivery services facilitate 'online' access to food outlets selling food prepared away-from-home. Online food outlet access has not previously been investigated in England or across an entire country. System...
Online food delivery services facilitate 'online' access to food outlets selling food prepared away-from-home. Online food outlet access has not previously been investigated in England or across an entire country. Systematic differences in online food outlet access could exacerbate existing health inequalities, which is a public health concern. However, this is not known. Across postcode districts in England (n = 2118), we identified and described the number of food outlets and unique cuisine types accessible online from the market leader (Just Eat). We investigated associations with area-level deprivation using adjusted negative binomial regression models. We also compared the number of food outlets accessible online with the number physically accessible in the neighbourhood (1600m Euclidean buffers of postcode district geographic centroids) and investigated associations with deprivation using an adjusted general linear model. For each outcome, we predicted means and 95% confidence intervals. In November 2019, 29,232 food outlets were registered to accept orders online. Overall, the median number of food outlets accessible online per postcode district was 63.5 (IQR; 16.0-156.0). For the number of food outlets accessible online as a percentage of the number accessible within the neighbourhood, the median was 63.4% (IQR; 35.6-96.5). Analysis using negative binomial regression showed that online food outlet access was highest in the most deprived postcode districts (n = 106.1; 95% CI: 91.9, 120.3). The number of food outlets accessible online as a percentage of those accessible within the neighbourhood was highest in the least deprived postcode districts (n = 86.2%; 95% CI: 78.6, 93.7). In England, online food outlet access is socioeconomically patterned. Further research is required to understand how online food outlet access is related to using online food delivery services.
The main factors influencing COVID-19 spread and deaths in Mexico: A comparison between phases I and II.
Benita F, Gasca-Sanchez F
Appl Geogr · 2021 Sep · PMID 34334843 · Full text
This article investigates the geographical spread of confirmed COVID-19 cases and deaths across municipalities in Mexico. It focuses on the spread dynamics and containment of the virus between Phase I (from March 23 to M...
This article investigates the geographical spread of confirmed COVID-19 cases and deaths across municipalities in Mexico. It focuses on the spread dynamics and containment of the virus between Phase I (from March 23 to May 31, 2020) and Phase II (from June 1 to August 22, 2020) of the social distancing measures. It also examines municipal-level factors associated with cumulative COVID-19 cases and deaths to understand the spatial determinants of the pandemic. The analysis of the geographic pattern of the pandemic via spatial scan statistics revealed a fast spread among municipalities. During Phase I, clusters of infections and deaths were mainly located at the country's center, whereas in Phase II, these clusters dispersed to the rest of the country. The regression results from the zero-inflated negative binomial regression analysis suggested that income inequality, the prevalence of obesity and diabetes, and concentration of fine particulate matter (PM 2.5) are strongly positively associated with confirmed cases and deaths regardless of lockdown.
Downscaling a Human Well-Being Index for Environmental Management and Environmental Justice Applications in Puerto Rico.
Yee SH, Paulukonis E, Buck KD
Appl Geogr · 2020 Jul · PMID 34326563 · Full text
Human well-being is often an overarching goal in environmental decision-making, yet assessments are often limited to economic, health, or ecological endpoints that are more tangible to measure. Composite indices provide...
Human well-being is often an overarching goal in environmental decision-making, yet assessments are often limited to economic, health, or ecological endpoints that are more tangible to measure. Composite indices provide a comprehensive approach to measuring well-being in terms of multi-dimensional components, such as living standards, health, education, safety, and culture. For example, the Human Well-Being Index (HWBI) framework, initially developed for the U.S. fifty states, was recently applied to quantify human well-being for Puerto Rico. However, the paucity of data at spatial scales finer than state or county levels, particularly for social metrics, poses a major limitation to quantifying well-being at neighborhood-scales relevant to decision-making. Here we demonstrate a spatial interpolation method to fill in missing fine-scale data where coarser-scale data is available. Downscaling from municipio (i.e., county-equivalent) to census-tract revealed a greater range of variability in well-being scores across Puerto Rico, in particular, a larger proportion of low well-being scores. Furthermore, while some components of wellbeing (e.g., Education, Health, Leisure Time, Safety and Security, Social Cohesion) showed consistent improvement over time from 2000-2017 across Puerto Rico, others (e.g., Connection to Nature, Cultural Fulfillment, Living Standards) were variable among census tracts, increasing for some but declining for others. We use a case study in the San Juan Bay estuary watershed to illustrate how approaches to quantify baseline levels of well-being can be used to explore potential impacts of management actions on communities, including to identify environmental justice inequalities among neighborhoods. Spatial clustering analysis was used to identify statistically significant cold or hot spots in well-being. This study demonstrates how indicators of well-being, coupled with interpolation methods to overcome limitations of data availability, can help to monitor long-term changes over time and to better communicate the potential value of ecosystem restoration or resource management.
Improving Estimates of Neighborhood Change with Constant Tract Boundaries.
Logan JR, Zhang W, Stults BJ … +1 more , Gardner T
Appl Geogr · 2021 Jul · PMID 34121782 · Full text
Social scientists routinely rely on methods of interpolation to adjust available data to their research needs. Spatial data from different sources often are based on different geographies that need to be reconciled, and...
Social scientists routinely rely on methods of interpolation to adjust available data to their research needs. Spatial data from different sources often are based on different geographies that need to be reconciled, and some boundaries (e.g., administrative or political boundaries) change frequently. This study calls attention to the potential for substantial error in efforts to harmonize data to constant boundaries using standard approaches to areal and population interpolation. The case in point is census tract boundaries in the United States, which are redefined before every decennial census. Research on neighborhood effects and neighborhood change rely heavily on estimates of local area characteristics for a consistent area of time, for which they now routinely use estimates based on interpolation offered by sources such as the Neighborhood Change Data Base (NCDB) and Longitudinal Tract Data Base (LTDB). We identify a fundamental problem with how these estimates are created, and we reveal an alarming level of error in estimates of population characteristics in 2000 within 2010 boundaries. We do this by comparing estimates from one of these sources (the LTDB) to true values calculated by re-aggregating original 2000 census microdata to 2010 tract areas. We then demonstrate an alternative approach that allows the re-aggregated values to be publicly disclosed, using "differential privacy" (DP) methods to inject random noise that meets Census Bureau standards for protecting confidentiality of the raw data. We show that the DP estimates are considerably more accurate than the LTDB estimates based on interpolation, and we examine conditions under which interpolation is more susceptible to error. This study reveals cause for greater caution in the use of interpolated estimates from any source. Until and unless DP estimates can be publicly disclosed for a wide range of variables and years, research on neighborhood change should routinely examine data for signs of estimation error that may be substantial in a large share of tracts that experienced complex boundary changes.
Geospatial analysis of misinformation in COVID-19 related tweets.
Forati AM, Ghose R
Appl Geogr · 2021 Aug · PMID 34103772 · Full text
COVID-19 has emerged as a global pandemic caused by its highly transmissible nature during the incubation period. In the absence of vaccination, containment is seen as the best strategy to stop virus diffusion. However,...
COVID-19 has emerged as a global pandemic caused by its highly transmissible nature during the incubation period. In the absence of vaccination, containment is seen as the best strategy to stop virus diffusion. However, public awareness has been adversely affected by discourses in social media that have downplayed the severity of the virus and disseminated false information. This article investigates COVID-19 related Twitter activity in May and June 2020 to examine the origin and nature of misinformation and its relationship with the COVID-19 incidence rate at the state and county level. A geodatabase of all geotagged COVID-19 related tweets was compiled. Multiscale Geographically Weighted Regression was employed to examine the association between social media activity and the spatial variability of disease incidence. Findings suggest that MGWR could explain 80% of the COVID-19 incidence rate variations indicating a strong spatial relationship between social media activity and spread of the Covid-19 virus. Discourse analysis was conducted on tweets to index tweets downplaying the pandemic or disseminating misinformation. Findings indicate that sites of Twitter misinformation showed more resistance to pandemic management measures in May and June 2020 later experienced a rise in the number of cases in July.
Impact of the COVID-19 lockdown on air quality in the Delhi Metropolitan Region.
Roy SS, Balling RC
Appl Geogr · 2021 Mar · PMID 36536956 · Full text
With the rapid spread of COVID-19 related cases globally, national governments took different lockdown approaches to limit the spread of the virus. Among them, the Government of India imposed a complete nationwide lockdo...
With the rapid spread of COVID-19 related cases globally, national governments took different lockdown approaches to limit the spread of the virus. Among them, the Government of India imposed a complete nationwide lockdown starting on March 25, 2020. This presented a unique opportunity to explore how a complete standstill in regular daily activities might impact the local environment. In this study, we have analyzed the change in the air quality levels stemming from the reduced anthropogenic activities in one of the most polluted cities in the world, the Delhi Metropolitan Region (DMR). We analyzed station-level changes in particulate matter, PM and PM, across the DMR between April 2019 and 2020. The results of our study showed widespread reduction in the levels of both pollutants, with substantial spatial variations. The largest decreases in particulate matter were associated with industrial and commercial areas. Highest levels of PM and PM were observed near sunrise with little change in the time of maximum between 2019 and 2020. The results of our study highlight the role of anthropogenic activities on the air quality at the local level.
Regionalization for infection control: An algorithm for delineating containment zones considering the regularity of human mobility.
Kuo FY, Wen TH
Appl Geogr · 2021 Jan · PMID 33318717 · Full text
Restricting human movement to decrease contact probability and frequency helps mitigate large-scale epidemics. Movement-based zoning can be implemented to delineate the boundaries for movement restrictions. Previous stud...
Restricting human movement to decrease contact probability and frequency helps mitigate large-scale epidemics. Movement-based zoning can be implemented to delineate the boundaries for movement restrictions. Previous studies used network community detection methods, which capture cohesive within-region movements, to delineate containment zones. However, most people usually travel and spend most of their time in several fixed locations, which implies that an infected person could transmit the pathogens to only a specific group of people with whom s/he usually has a contact in frequently-visited locations. Existing network community detection methods cannot reflect the regularity of the flow of people; thus, this study aims to use land-use patterns to reflect trip purposes to measure the regularity of human mobility. We propose a novel network community detection method, the Human Mobility Regularity-based Zoning (HuMoRZ) algorithm, to delineate containment zones incorporating mobility regularity. The Taipei metropolitan area in Taiwan is used to demonstrate the feasibility of the proposed algorithm. The spatial diffusion of an emerging respiratory disease, novel influenza A/H1N1, is simulated for comparing three different quarantine zoning systems: (1) a minimum zoning unit, (2) optimal zoning without considering mobility regularity, and (3) optimal zoning considering mobility regularity. Two epidemiological performance indicators are used to compare simulation results: namely, the accumulated infected number (AN) on the 30th day, reflecting the severity of an epidemic, and the critical time (CT), the moment at which half of the population becomes infected, measuring the diffusion speed of an epidemic. To measure the variety of different facility types within a containment zone, we further use Shannon's entropy scores, representing a self-contained zone, and the boxplot of all zones' entropy scores, reflecting geospatial homogeneity of life functions across zones. Our results suggest that containment zones that incorporate mobility regularity could significantly delay the epidemic peak and critical time and decrease the severity of an epidemic. The zoning patterns proposed in our algorithm could also allow for more life functions in a zone and more evenly distributed life resources across zones than those of zones generated by other methods. These findings could provide insightful implications for fighting the COVID-19 pandemic.
A country comparison of place-based activity response to COVID-19 policies.
McKenzie G, Adams B
Appl Geogr · 2020 Dec · PMID 33162624 · Full text
The emergence of the novel Coronavirus Disease in late 2019 (COVID-19) and subsequent pandemic led to an immense disruption in the daily lives of almost everyone on the planet. Faced with the consequences of inaction, mo...
The emergence of the novel Coronavirus Disease in late 2019 (COVID-19) and subsequent pandemic led to an immense disruption in the daily lives of almost everyone on the planet. Faced with the consequences of inaction, most national governments responded with policies that restricted the activities conducted by their inhabitants. As schools and businesses shuttered, the mobility of these people decreased. This reduction in mobility, and related activities, was recorded through ubiquitous location-enabled personal mobile devices. Patterns emerged that varied by place-based activity. In this work the differences in these place-based activity patterns are investigated across nations, specifically by focusing on the relationship between government enacted policies and changes in community activity patterns. By addressing five research questions, we show that people's activity response to government action varies widely both across nations as well as regionally within them. Three assessment measures, namely cosine similarity, lag response, and subregional variation, are devised and the results correlate with a number of global indices. We discuss these findings and the relationship between government action and residents' response.
Spatial risk assessment of an emerging pandemic under data scarcity: A case of COVID-19 in Eswatini.
Dlamini WM, Dlamini SN, Mabaso SD … +1 more , Simelane SP
Appl Geogr · 2020 Dec · PMID 33132463 · Full text
Coronavirus (COVID-19) has rapidly spread across many countries in pandemic proportions since the first case was reported in Hubei, China in December 2019. Understanding transmission, susceptibility and exposure risks is...
Coronavirus (COVID-19) has rapidly spread across many countries in pandemic proportions since the first case was reported in Hubei, China in December 2019. Understanding transmission, susceptibility and exposure risks is crucial for surveillance, control and response to the disease. Knowing the geographic distribution of health resource scarcity areas is necessary if a country is to adequately anticipate and prepare for the full impact of infections. We explored the potential to undertake a spatial risk assessment of an emerging pandemic under data scarcity in Eswatini. We used a set of socio-economic and demographic variables to identify epidemic risk prone areas in the country. Three risk zone levels for COVID-19 were identified in the country. The analysis showed that about 29% (320 818) of the population were located in the high risk zone and these were people who could potentially be infected with COVID-19 in the absence of mitigation measures. A majority of cases and deaths attributed to COVID-19 would likely remain unknown but our estimate could be used to gauge the full burden of the disease. Approximating and quantifying the number of people who may be potentially infected with COVID-19 remains impossible under data scarcity and limited healthcare capacity especially in sub-Saharan Africa. We provided an estimation method that could support the pandemic risk forecasting, preparedness and response measures in the midst of data scarcity. The resultant map products could be used to guide on-the-ground surveillance and response efforts.
Identifying county-level factors for female breast cancer incidence rate through a large-scale population study.
Zhao T, Cui Z, McClellan MG … +3 more , Yu D, Sang QA, Zhang J
Appl Geogr · 2020 Dec · PMID 33041393 · Full text
Female breast cancer (FBC) incidence rate (IR) varies greatly across counties in the United States (U.S.). Factors contributing to these geographic disparities have not been fully understood at the population level. In t...
Female breast cancer (FBC) incidence rate (IR) varies greatly across counties in the United States (U.S.). Factors contributing to these geographic disparities have not been fully understood at the population level. In this study, we investigated the relationships between the county-level FBC IR and a diverse set of variables in demographics, socioeconomics, life style, health care accessibility, and environment. Our study included 1,277 counties in the U.S. where the female population was 10,000 or above for at least one race/ethnicity. After controlling for the racial/ethnic and other significant factors, percent of husband-wife family households (pHWFH) for a racial/ethnic group in a county is negatively associated with FBC IR (p < 0.001). A 10% increase in married family households may lower a county's IR by 5.2 cases per 100,000 females per year. We also found that PM (fine inhalable particles with a diameter of 2.5 micrometers or less) is positively associated with FBC IR (p < 0.001). Counties with the highest level of PM have approximately 4 additional FBC new cases per 100,000 females per year than counties with the lowest level of PM. Furthermore, we found that the county-level factors contributing to FBC IR vary significantly for different racial groups using race-specific models. While confirming most of the previously known patient- and neighborhood-level risk factors (such as race/ethnicity, income, and health care accessibility), our study identified two significant county-level factors contributing to the spatial disparity of FBC IR across the U.S. The newly-identified beneficial factor (marriage) and risk factor (PM), together with the verified known factors, may help provide insights to officials of health departments/organizations for them to make decisions on cancer intervention strategies.
Spaces of market politics: Retailscapes and modernist planning imaginaries in African cities.
Frimpong Boamah E, Amoako C, Asenso BK
Appl Geogr · 2020 Oct · PMID 32834206 · Full text
This article interrogates the spatial, economic, and cultural underpinnings of traditional retailscapes in sub-Saharan Africa to understand how they intersect with contemporary urban planning policies. It does so by depl...
This article interrogates the spatial, economic, and cultural underpinnings of traditional retailscapes in sub-Saharan Africa to understand how they intersect with contemporary urban planning policies. It does so by deploying a multi-step investigation of the issues from four perspectives: transportation corridors, spheres of influence, centrality, and observed spatial patterns - each leading us to connections between retail spaces and planning of African cities. Our analyses of 22 traditional satellite markets in Kumasi are distilled into four key findings. First, these markets emerge along, and at the intersection of, intra- and inter-urban road networks as a means of granting local access to indigenous goods and services. Second, the spatial distribution and spheres of influence of the markets partly support Christaller's hypothesis regarding the willingness of people to travel far distances to access higher-order goods and services. The hypothesis fails, however, to recognize that some traditional markets can still have high spheres of influence without providing higher-order goods and services because they constitute vital nodes in the rural-urban food networks. Third, we find a spatial clustering of these markets, suggesting agglomerative tendencies among the markets. Finally, we argue that the observed spatio-social patterns of Kumasi's retailscape only make sense if they are situated within the city's modernist urban planning imaginaries. Specifically, the city's retailscape embodies ongoing placemaking strategies, which involve the expropriation of urban spaces from traders to modernize the cityscape.
Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters.
Desjardins MR, Hohl A, Delmelle EM
Appl Geogr · 2020 May · PMID 32287518 · Full text
Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China in December 2019, and is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 is a pandemic with an estimated death rat...
Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China in December 2019, and is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 is a pandemic with an estimated death rate between 1% and 5%; and an estimated between 2.2 and 6.7 according to various sources. As of March 28th, 2020, there were over 649,000 confirmed cases and 30,249 total deaths, globally. In the United States, there were over 115,500 cases and 1891 deaths and this number is likely to increase rapidly. It is critical to detect clusters of COVID-19 to better allocate resources and improve decision-making as the outbreaks continue to grow. Using daily case data at the county level provided by Johns Hopkins University, we conducted a prospective spatial-temporal analysis with SaTScan. We detect statistically significant space-time clusters of COVID-19 at the county level in the U.S. between January 22nd-March 9th, 2020, and January 22nd-March 27th, 2020. The space-time prospective scan statistic detected "active" and emerging clusters that are present at the end of our study periods - notably, 18 more clusters were detected when adding the updated case data. These timely results can inform public health officials and decision makers about where to improve the allocation of resources, testing sites; also, where to implement stricter quarantines and travel bans. As more data becomes available, the statistic can be rerun to support timely surveillance of COVID-19, demonstrated here. Our research is the first geographic study that utilizes space-time statistics to monitor COVID-19 in the U.S.
Urban inequalities in the 21st century economy.
Nijman J, Wei YD
Appl Geogr · 2020 Apr · PMID 32287517 · Full text
In the last decade or so, inequality studies have assumed renewed prominence across the social sciences. In this introduction to a special issue of , we set out to articulate the importance of urban spatial context in br...
In the last decade or so, inequality studies have assumed renewed prominence across the social sciences. In this introduction to a special issue of , we set out to articulate the importance of urban spatial context in broader present-day inequality debates. We argue that the information-based economy is emphatically urban-based and that it has forged new spatial inequalities in and between cities and among urban populations. Income gaps have widened, inter-city disparities have grown, suburbs have been re-sorted into a wide array on the basis of class and race or ethnicity, and many central cities have assumed a renewed importance within metropolitan areas. We argue that attention to urban spatial dimensions at various scales is critical to understanding current inequality trends, from intra-urban to regional and global scales. Contributions to this special issue from North America, Europe, South America, and China suggest that deepening urban inequalities are pervasive across the globe.
Spatiotemporal analysis of regional socio-economic vulnerability change associated with heat risks in Canada.
Ho HC, Knudby A, Chi G … +2 more , Aminipouri M, Yuk-FoLai D
Appl Geogr · 2018 Jun · PMID 31031454 · Full text
Excess mortality can be caused by extreme hot weather events, which are increasing in severity and frequency in Canada due to climate change. Individual and social vulnerability factors influence the mortality risk assoc...
Excess mortality can be caused by extreme hot weather events, which are increasing in severity and frequency in Canada due to climate change. Individual and social vulnerability factors influence the mortality risk associated with a given heat exposure. We constructed heat vulnerability indices using census data from 2006 and 2011 in Canada, developed a novel design to compare spatiotemporal changes of heat vulnerability, and identified locations that may be increasingly vulnerable to heat. The results suggest that 1) urban areas in Canada are particularly vulnerable to heat, 2) suburban areas and satellite cities around major metropolitan areas show the greatest increases in vulnerability, and 3) heat vulnerability changes are driven primarily by changes in the density of older ages and infants. Our approach is applicable to heat vulnerability analyses in other countries.
A user-generated data based approach to enhancing location prediction of financial services in sub-Saharan Africa.
McKenzie G, Slind RT
Appl Geogr · 2019 Apr · PMID 31007312 · Full text
The recent increase in user-generated content and social media adoption in developing countries offers an unprecedented opportunity to better understand the accessibility and spatial distribution of financial services in...
The recent increase in user-generated content and social media adoption in developing countries offers an unprecedented opportunity to better understand the accessibility and spatial distribution of financial services in sub-Saharan Africa. Financial inclusion has been identified as a priority by multiple agencies in the region and on-the-ground efforts are currently underway to identify previously unknown financial access points in numerous developing African countries. Existing techniques for estimating the location of these access points rely on spatial analysis of often outdated or unsuitable publicly available datasets such as population density, road networks, etc., as well as expensive and time consuming surveys of locals in the region. In this work we propose an approach to augment existing spatial data analysis techniques through the inclusion of user-generated geo-content and geo-social media data. Through a comparison of standard regression models and machine learning techniques, this work proposes the use of alternative data sources to build prediction models for identifying financial access locations in countries where current estimation models are insufficient. With a better understanding of geospatial distribution patterns this work aims at reducing data acquisition costs and providing decision makers with critical data more quickly and efficiently. Finally, we present a mobile application built on the outcomes of this analysis that is currently being used to better inform on-the-ground data collection efforts.
Spatial clustering patterns of child weight status in a southeastern US county.
Hughey SM, Kaczynski AT, Porter DE … +3 more , Hibbert J, Turner-McGrievy G, Liu J
Appl Geogr · 2018 Oct · PMID 34924644 · Full text
Youth obesity is a major public health concern due to associated physical, social, and psychological health consequences. While rates and disparities of youth obesity levels are known, less research has explored spatial...
Youth obesity is a major public health concern due to associated physical, social, and psychological health consequences. While rates and disparities of youth obesity levels are known, less research has explored spatial clustering patterns, associated correlates of spatial clustering, comparing patterns in urban and rural areas. Therefore, this study 1) examined spatial clustering of youth weight status, 2) investigated sociodemographic correlates of spatial clustering patterns, and 3) explored spatial patterns by level of urbanization. This study occurred in a southeastern US county (pop:474,266) in 2013. Trained physical education teachers collected height and weight for all 3-5th grade youth (n = 13,469) and schools provided youth demographic attributes. BMI z-scores were calculated using standard procedures. Global Moran's Index and Anselin's Local Moran's I (LISA) were used detect global and local spatial clustering, respectively. To examine correlates of spatial clustering, BMI z-score residuals from a series of four linear regression models were spatially analyzed, mapped, and compared. SAS 9.4 and GeoDA were used for analyses; ArcGIS was used for mapping. Significant, positive global clustering (Index = 0.04,p < 0.001) was detected. LISA results showed that about 4.7% (n = 635) and 7.9% (n = 1058) of the sample were identified as high and low obesity localized spatial clusters (p < 0.01), respectively. Individual and neighborhood sociodemographic characteristics accounted for the majority of spatial clustering and differential patterns were observed by level of urbanization. Identifying geographic areas that contain significant spatial clusters is a powerful tool for understanding the location of and exploring contributing factors to youth obesity.
An Exploration of the Spatiotemporal and Demographic Patterns of Ebola Virus Disease Epidemic in West Africa Using Open Access Data Sources.
Suchar VA, Aziz N, Bowe A … +2 more , Burke A, Wiest MM
Appl Geogr · 2018 Jan · PMID 30224832 · Full text
The purpose of this study was to investigate the utility of exploratory analytical techniques using publically available data in informing interventions in case of infectious diseases outbreaks. More exactly spatiotempor...
The purpose of this study was to investigate the utility of exploratory analytical techniques using publically available data in informing interventions in case of infectious diseases outbreaks. More exactly spatiotemporal and multivariate methods were used to characterize the dynamics of the Ebola Virus Disease (EVD) epidemic in West Africa, and propose plausible relationships with demographic/social risk factors. The analysis showed that there was significant spatial, temporal, and spatiotemporal dependence in the evolution of the disease. For the first part of the epidemic, the cases were highly clustered in a few administrative units, in the proximity of the point of origin of the outbreak, possibly offering the opportunity to stop the spread of the disease. Later in the epidemic, high clusters were observed, but only in Liberia and Sierra Leone. Although not definitely factors of risk, in the setting in which the epidemic arose, our analysis suggests infrastructure, access to and use of health services, and connectivity possibly accelerated and magnified the spread of EVD. Also, the spatial, temporal, and spatiotemporal patterns of epidemic can be clearly shown - with evident application in the early stages of management of epidemics. In particular, we found that the spatial-temporal analytic tool SaTScan may be used effectively during the evolution of an epidemic to identify areas for targeted intervention. In the case of EVD epidemic in West Africa, better data and integration local knowledge and customs may have been more useful to recognize the proper response.
The implications of high-speed railways on air passenger flows in China.
Yang H, Burghouwt G, Wang J … +2 more , Boonekamp T, Dijst M
Appl Geogr · 2018 Aug · PMID 32287520 · Full text
The High-speed Railway (HSR) network in China is the largest in the world, competing intensively with airlines for inter-city travel. Panel data from 2007 to 2013 for 138 routes with HSR-air competition were used to iden...
The High-speed Railway (HSR) network in China is the largest in the world, competing intensively with airlines for inter-city travel. Panel data from 2007 to 2013 for 138 routes with HSR-air competition were used to identify the ex-post impacts of the entry of HSR services, the duration of operating HSR services since entry, and the specific impacts of HSR transportation variables such as travel time, frequency, and ticket fares on air passenger flows in China. The findings show that the entry of new HSR services in general leads to a 27% reduction in air travel demand. After two years of operating HSR services, however, the negative impact of HSR services on air passenger flows tends to further increase. The variations of the frequency in the temporal dimension and the travel time in the spatial dimension significantly affect air passenger flows. Neither in the temporal nor spatial dimensions are HSR fares strongly related to air passenger flows in China, due to the government regulation of HSR ticket prices during the period of analysis. The impacts of different transportation variables found in this paper are valuable to consider by operational HSR companies in terms of scheduling and planning of new routes to increase their competitiveness relative to airlines.
Modeling the Influence of Social Ties and Transportation Choice on Access to Oral Healthcare for Older Adults.
Jin Z, Northridge ME, Metcalf SS
Appl Geogr · 2018 Jul · PMID 30008491 · Full text
The current U.S. demographic shift toward an older population and the importance of intervening before conditions become severe warrant a concerted effort to ease the burden of access to healthcare for older adults. With...
The current U.S. demographic shift toward an older population and the importance of intervening before conditions become severe warrant a concerted effort to ease the burden of access to healthcare for older adults. With regard to oral healthcare, more integrated services for older adults are needed to effectively serve their complex medical and dental needs. Using an agent-based simulation model, this paper examines the influence of social ties and transportation mode choices on opportunities for older adults to participate in community-based preventive screening events and access needed oral healthcare. This approach accounts for the heterogeneity of behavior that arises for a population exhibiting diversity in terms of social factors, including socioeconomic means and social support. In the context of older adults living in urban environments, the availability of different transportation modes ought to be taken into consideration. To explore alternative scenarios for the accessibility of preventive screening events offered at senior centers in northern Manhattan, an agent-based model (ABM) was created with a geographic information system (GIS) to simulate the influence of social ties and transportation choices on older adults seeking preventive screening services and oral healthcare. Results of simulation experiments indicate preferences for public transportation and inequities in accessibility that may be mitigated with social support. This simulation model offers a way to explore social support as an important factor in making transportation mode choices that mediate oral healthcare accessibility and thus oral health outcomes for older adults.
Identifying populations and areas at greatest risk of household food insecurity in England.
Smith D, Thompson C, Harland K … +2 more , Parker S, Shelton N
Appl Geogr · 2018 Feb · PMID 29915447 · Full text
Despite the increasing recognition of household food insecurity as a policy issue, there is currently no routine measurement of food insecurity in the UK. There is nothing to suggest that Government will address this in...
Despite the increasing recognition of household food insecurity as a policy issue, there is currently no routine measurement of food insecurity in the UK. There is nothing to suggest that Government will address this in the near future for all parts of the UK. In which case, policy makers and campaigners might instead seek out consistent and robust measures of the population-level factors which are known to contribute to food insecurity. However, no systematic measures exist, meaning that resources may not be targeted at those areas most in need. This paper presents the first objective estimate of high population-level risk of household food insecurity in English neighbourhoods (4.09% of the population, 95%CI 4.08-4.10) using public data. Estimated geographic distribution of factors contributing to household food insecurity is customisable to local pressures and is adaptable to settings outside of England.
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