Epidemiological spaces: the use of multidimensional scaling to identify cholera diffusion processes in wake of the Philippines insurrection, 1899–1902

Between 1902 and 1904 an epidemic of cholera, fuelled initially by the operations of the Philippine-American War (1899–1902), swept through the Philippine Islands in two waves. In earlier papers, the authors showed that spatially contagious spread dominated the waves at the geographical levels of province, island and nation (Smallman-Raynor and Cliff 1998a, b). To explore the visualization and analysis of epidemic transmission in an alternative metric, the present paper uses multidimensional scaling (MDS) to translate the spread corridors followed by the waves from conventional geographical space into non-Euclidean cholera spaces. The re-mapping confirms the importance of contagious diffusion in the spread of the epidemic, but also picks out the moments in time in which spread driven through the population hierarchy switched in. In addition, the analysis illustrates the utility of constructing non-Euclidean spaces to identify disease diffusion processes.     

分析SARS:在我国的地理扩散和地理障碍

SARS疫情在我国的迅速传播已经对我国的社会和经济生活造成了重大的影响,也为我们观察和分析地理扩散提供了难得的机会。SARS的扩散显然是一种地理过程,这个过程的第一个特征是以等级扩散为发展方式的,第二个特征是必然在扩散中遇到障碍。第一个特征的存在使疫情在一段时间里在我国得以迅速的蔓延,但是当采取各种医疗、隔离和防护措施后,SARS的扩散在出现障碍的条件下受到抑制。文章描述了疫情扩散的方式,在我国形成的地理格局(以广东和北京为源地),认为这个地理格局的形成与我国流动人口的分布、人口流动的条件有关。同时指出,在疫情扩散的地理格局中,在中心城市形成的高度集中是一种令人担忧的现象。因为这样的集中已经对这些中心城市的包括"医疗中心"在内的行政、经济、交通等核心地的功能产生严重影响。为此,文章注意到我国一些没有发现疫情的地区的地理条件,认为存在着如地理距离(距离衰减)、地理环境、产业特征等地理障碍。通过对这些障碍的分析,文章最后提出了防治疫情及其继续扩散的措施。     

民国时期江南地区疫灾地理研究

疫灾自古以来就是人类健康和生命安全的巨大威胁。本文通过编制疫灾序列,采用历史文献分析、数理统计分析和GIS空间分析等方法,对民国时期江南地区的疫灾时空变迁进行研究,结果发现: 一、 民国时期江南地区无年不疫,疫灾季发率高达94.70%,秋、夏、春三季疫灾多发,集中了全年近九成的疫灾县数,秋、夏季尤甚,集中了全年四分之三的疫灾县数;逐年的疫灾广度总体呈上升趋势,但波动特征明显;在明初至民国末年的582年间,江南地区疫灾的波动周期越来越短,年均发生疫灾的县数越来越多,说明随着时间的推移,疫灾越来越频繁,民国时期是江南地区历史上疫灾最频繁最严重的时期。二、 民国时期江南地区的疫灾主要分布于大运河、宁沪杭铁路沿线及其以东的地区,苏州—无锡一带和环上海地区为疫灾热点区,江苏溧阳地区和浙西山丘地区为疫灾冷点区;疫灾分布重心始终位于苏州境内。三、 民国时期江南地区疫灾分布的一般规律是: 交通沿线城市都是疫灾高发点,人口稠密区多为疫灾频发区,水旱灾害严重区也是疫灾严重区,平原地区的疫灾多于山丘地区的疫灾。     

The spatial anatomy of an epidemic: influenza in London and the county boroughs of England and Wales, 1918–1919

From uncertain origins in the spring of 1918, an apparently new variant of influenza A virus spread around the world as three distinct diffusion waves, infecting half a billion and probably killing around 40 million people. This paper examines the spatial structure of influenza transmission during the ten–month course of the epidemic in England and Wales, June 1918–April 1919, using the weekly counts of influenza deaths in London and the county boroughs as collated by the General Register Office, London. In addition, a particular case study of the borough of Cambridge is presented. From mid–1916, Cambridge contained, as well as its undergraduate population, a large naval contingent billeted in both the colleges and the town. It therefore affords the opportunity of studying the effect of the epidemic in contiguous groups with widely differing demographic characteristics. Through the application of a range of statistical methods (average lags, correlations and regressions), it is shown that the three waves that comprised the pandemic had fundamentally different spatial and temporal characteristics. The first, moving through a population that was a virgin soil to the new virus strain, was explosive in its north to south progress across the country. The second wave was somewhat slower in its rate of diffusion and displayed a south to north drift. Finally, the third wave reverted more closely to the form of the first. The spread of all three waves, however, was underpinned by a clearly defined process of spatial contagion. The Cambridge study showed the special characteristics of this pandemic in terms of the ages of those attacked: high rates were experienced across the age spectrum, a feature also seen internationally.     

基于街道尺度的南京市老年人口空间分布演变研究

基于南京市第五次和第六次人口普查分乡镇、街道数据,通过街道和圈层双尺度分析了人口老龄化的程度差异、空间差异以及空间相关性,探讨南京市街道老年人口的空间分布格局,采用热点区演化分析了街道老年人口的时空演变特征。结果显示:①近10年南京市街道老龄化系数总体上呈现"跨越式"圈层蔓延扩散的空间分布特征,处于老年人口成长阶段的街道由分布在中心城区和主城区的交界地带转变为向主城区蔓延的趋势,轻度老龄化的街道分布在中心城区,中度老龄化阶段的街道集中分布在主城区和郊区,重度老龄化阶段的街道以郊区为主。②街道老年人口密度类型为密集区,密度最高的区域位于中心城区,郊区次之,主城区内密度最低。③南京市街道人口老龄化率呈现显著的空间正相关,随着时间的推移,街道人口老龄化在空间上的差异增大,集聚效应减弱,空间上的发展渐趋不均衡。热点区分布呈现"冷-次冷-次热-热"的圈层式空间分布格局。④从历史因素、人口生命周期、城市变迁三个角度分析了影响南京市老年人口分布和演变的主要因素。     

THE KNIGHTS OF LABOR DATA-BANK

Several countries have made large investments in building historical Geographical Information Systems (GIS) databases containing census and other quantitative statistics over long periods of time. Making good use of these databases requires approaches that explore spatial and temporal change. The authors use a variety of visualization and spatial analysis techniques to explore population change in Ireland during and after the Great Famine of the late 1840s. Importantly, the techniques allow differences over space and time to be explored, thus stressing the diversity between places, rather than making all places appear the same, a common criticism of many statistical approaches. The authors demonstrate the potential of these techniques to explore geographical and temporal variations in large quantitative GIS datasets.     

Closed‐Form Maximum Likelihood Estimates of Nearest Neighbor Spatial Dependence

Models of n² potential spatial dependencies among n observations spread irregularly over space seem unlikely to yield simple structure. However, the use of the nearest neighbor leads to a very parsimonious eigenstructure of the associated adjacency matrix which results in an extremely simple closed form for the log determinant. In turn, this leads to a closed‐form solution for the maximum likelihood estimates of the spatially autoregressive and mixed regressive spatially autoregressive models. With the closed‐form solution, one can find the neighbors and compute maximum likelihood estimates for 100,000 observations in under one minute. The model has theoretical, pedagogical, diagnostic, modeling, and methodological applications. For example, the model could serve as a more enlightened null hypothesis for geographic data than spatial independence.     

新冠肺炎疫情和公众焦虑情绪的时空分异研究——基于微博数据的分析

采集河南省17个地市在COVID-19疫情期间的微博数据,利用微博数据分析疫情期间公众焦虑情绪及其时空分异.研究结果发现:公众的焦虑情绪波动幅度与疫情态势基本成正相关,疫情初期,公众对疫情数据的变化敏感,新增确诊人数的小幅增加和下降均能引起公众焦虑情绪的大幅攀升和下跌,疫情态势稳定向好时,焦虑情绪波动幅度逐渐趋稳;在疫...     

Latent trajectory models for space‐time analysis: An application in deciphering spatial panel data

This article introduces latent trajectory models (LTMs), an approach often employed in social sciences to handle longitudinal data, to the arena of GIScience, particularly space‐time analysis. Using the space‐time data collected at county level for the whole United States through webpage search on the keyword “climate change,” we show that LTMs, when combined with eigenvector filtering of spatial dependence in data, are very useful in unveiling temporal trends hidden in such data: the webpage‐data derived popularity measure for climate change has been increasing from December 2011 to March 2013, but the increase rate has been slowing down. In addition, LTMs help reveal potential mechanisms behind observed space‐time trajectories through linking the webpage‐data derived popularity measure about climate change to a set of socio‐demographic covariates. Our analysis shows that controlling for population density, greater drought exposure, higher percent of people who are 16 years old or above, and higher household income are positively predictive of the trajectory slopes. Higher percentages of Republicans and number of hot days in summer are negatively related to the trajectory slopes. Implications of these results are examined, concluding with consideration of the potential utility of LTMs in space‐time analysis and more generally in GIScience.     

西部大学城对未来西安市城市空间扩散的影响

本文在简单介绍了西部大学城及西安市城市空间扩散基本情况的基础上,具体分析了西部大学城对未来西安市中心城区用地面积,教育空间,人口空间,产业空间等方面的城市空间扩散的影响,并提出了在此过程中需要注意的问题及对策,为促进西安市城市空间有序扩散提供一种理论支撑。     

Spatial-Temporal Spread of the AIDS Epidemic, 1982–1990: A Correlogram Analysis of Four Regions of the United States

We applied correlogram analysis to county-level AIDS data of four regions—the Northeast (Delaware, the District of Columbia, Maryland, New Jersey, New York, and Pennsylvania), California, Florida, and Louisiana—for the period 1982–1990 to characterize the spatial-temporal spread of the AIDS epidemic. Correlograms computed from yearly incidence rates differ substantially among these four regions, revealing regional differences in the spatial patterns and intensity of AIDS spread. A general trend of increasing spread to rural America, however, can still be detected. Contagious spread was predominant in the Northeast throughout the nine-year period, whereas California was dominated by hierarchical spread through time. The spatial-temporal changes of AIDS incidence patterns were most drastic in Florida, where the correlograms show hierarchical spread in the early years and then contagious spread in the later years. As a representative region for most other states in the United States, Louisiana has low spatial autocorrelation and no definite spatial pattern of spread. Grouping data into three-year periods for states with low yearly incidence rates such as Louisiana should help identify the dominant trends for these states. The correlogram results could provide useful insights into the specification of spatial models for AIDS forecasting.     

Spatiotemporal Modeling of Correlated Small‐Area Outcomes: Analyzing the Shared and Type‐Specific Patterns of Crime and Disorder

This research applies a Bayesian multivariate modeling approach to analyze the spatiotemporal patterns of physical disorder, social disorder, property crime, and violent crime at the small‐area scale. Despite crime and disorder exhibiting similar spatiotemporal patterns, as hypothesized by broken windows and collective efficacy theories, past studies often analyze a single outcome and overlook the correlation structures between multiple crime and disorder types. Accounting for five covariates, the best‐fitting model partitions the residual risk of each crime and disorder type into one spatial shared component, one temporal shared component, and type‐specific spatial, temporal, and space–time components. The shared components capture the underlying spatial pattern and time trend common to all types of crime and disorder. Results show that population size, residential mobility, and the central business district are positively associated with all outcomes. The spatial shared component is found to explain the largest proportion of residual variability for all types of crime and disorder. Spatiotemporal hotspots of crime and disorder are examined to contextualize broken windows theory. Applications of multivariate spatiotemporal modeling with shared components to ecological crime theories and crime prevention policy are discussed.     

SPACE–TIME MEASURES OF DEMAND FOR SERVICE: BRIDGING LOCATION MODELLING AND ACCESSIBILITY STUDIES THROUGH A TIME‐GEOGRAPHIC FRAMEWORK

Demand for service in location modelling is often evaluated based on the spatial proximity of fixed and static reference locations of demand (e.g. home) to a facility, which ignores person‐specific activity–travel patterns and the temporal changes in demand for service throughout the day. To address these limitations, this study draws upon recent developments in space–time measures of individual accessibility to explore the spatial and temporal structures of demand by considering individuals' space–time constraints and impact of existing urban structures. Based on a time‐geographic framework, eight space–time demand measures were developed and compared with three conventional location‐based demand measures for 12 hospitals through an empirical study conducted in Columbus, Ohio. The results show that geographic proximity between clients' home and facilities may not be an effective indicator for service demand, and conventional demand measures tend to underestimate potential demand for service in most situations. The study concludes that space–time demand measures that take into account people's activity‐travel patterns in space–time would lead to better estimation of demand for service in most cases.     

发展型城市政体主导的城市游憩商业区空间生产研究——以西安大唐不夜城为例

基于列斐伏尔空间三元论的理论视角,以西安大唐不夜城城市游憩商业区为例,采用城市政体理论的分析方法,深入探讨城市游憩商业区空间的生产机制和利益相关者之间的相互作用关系。研究发现：空间三元论可以用来解析城市游憩商业区的空间生产过程。空间的表征是政—商增长联盟主导构建符号化空间的过程。表征的空间中的社会关系,表现为发展型城市政体三方参与者的互动关系：一是公众在实体和虚拟空间中同步建构起来的空间想象和身份认同;二是政—商增长联盟对公众空间想象的积极回应,促使符号化空间的进一步情景化,以及空间的重塑。其中,网络时代的社交媒体已经成为公众参与城市政体议价的新路径。空间的实践表现在地域生产关系的转变和城市游憩商业区影响力的尺度跃迁。空间生产的上述三个方面是三位一体的辩证统一关系。研究还发现,在城市游憩商业区这种空间类型中,发展型城市政体导致公众对符号化空间规训的反应以悦纳为主,而非抵抗。     

The Spatial Association of Demographic and Population Health Characteristics with COVID-19 Prevalence Across Districts in India

In less-developed countries, the lack of granular data limits the researcher's ability to study the spatial interaction of different factors on the COVID-19 pandemic. This study designs a novel database to examine the spatial effects of demographic and population health factors on COVID-19 prevalence across 640 districts in India. The goal is to provide a robust understanding of how spatial associations and the interconnections between places influence disease spread. In addition to the linear Ordinary Least Square regression model, three spatial regression models—Spatial Lag Model, Spatial Error Model, and Geographically Weighted Regression are employed to study and compare the variables explanatory power in shaping geographic variations in the COVID-19 prevalence. We found that the local GWR model is more robust and effective at predicting spatial relationships. The findings indicate that among the demographic factors, a high share of the population living in slums is positively associated with a higher incidence of COVID-19 across districts. The spatial variations in COVID-19 deaths were explained by obesity and high blood sugar, indicating a strong association between pre-existing health conditions and COVID-19 fatalities. The study brings forth the critical factors that expose the poor and vulnerable populations to severe public health risks and highlight the application of geographical analysis vis-a-vis spatial regression models to help explain those associations.     

Quantifying Animal Trajectories Using Spatial Aggregation and Sequence Analysis: A Case Study of Differentiating Trajectories of Multiple Species

The increasing availability of telemetry data with high spatial and temporal resolution promises to greatly advance scientific understandings of the movement patterns of individual organisms across space and time. The amount of data provided by such methods, however, can be challenging to analyze and interpret. In this study, we present a new approach for analyzing animal movements that aggregates telemetry locations into spatial clusters and extracts the information from sequences formed by individuals passing through these spatial clusters. We applied this integrated approach of spatial aggregation and sequence analysis to quantify and compare trajectories of cattle (Bos taurus), mule deer (Odocoileus hemionus), and elk (Cervus elaphus) tracked by automated telemetry at the Starkey Experimental Forest and Range in northeastern Oregon, USA. Our approach effectively differentiated movement patterns of the three species. It provides a useful mean of quantifying movement patterns of species in a landscape.     

大数据时代的精细化城市模拟:方法、数据和案例

以地块作为基本空间单元并以城市活动主体作为模拟对象的精细化模拟是未来城市模型研究的重要方向,大数据(big data)时代的到来也为其提供了重要发展机遇。本文重点对精细化城市模型的主流建模方法进行了介绍,包括元胞自动机(Cellular Automata,CA)、基于主体建模(Agent-based Modelling,ABM)和传统的微观模拟(Microsimulation,MSM)这三种自下而上的微观模拟方法。之后结合精细化城市模型的高标准数据需求问题,对国际上通行的用于精细化模拟数据合成(population synthesis)的方法进行了综述,并给出笔者近年来在精细化城市模拟方面的多项实践案例,最后提出了以GIS为平台,结合CA/ABM/MSM方法,构建我国精细化城市模型的框架体系和关键技术,以期支持我国大城市地区空间政策的制定和评估。     

Wealth alone does not buy health: Political capacity,democracy, and the spread of AIDS

Although there have been have numerous studies on AIDS documenting its mortality, its epidemiological features, and its relationship to poverty and development, few studies have systematically analyzed how political factors and policies may help curtail the spread of AIDS. In this paper I consider how a variety of domestic factors influence HIV infection rates across countries. I argue that states with higher state capacity are better able to reduce the spread of the HIV/AIDS epidemic. Moreover, I argue that while strong autocracies can implement efficient policies with fewer constraints, democracies tend to be more responsive to the needs of the population and can be more efficient in curtailing the spread of HIV/AIDS. I empirically evaluate the hypotheses using a cross-sectional time-series sample of 117 countries. The empirical results indicate that greater state capacity indeed appears to help curtail HIV/AIDS infection rates.     

2000—2009年广东省入境游客时空分布格局及其变化研究

依据2000—2009年广东省入境旅游的相关数据,从时间序列和空间尺度两个方面对广东省入境游客的年际变化、时间分布、空间集聚性和空间格局演变进行分析。结果表明:(1)除个别地级市外,广东省大部分地级市入境游客到访率年际变化稳定,年际集中指数较小,时间分布均匀;(2)入境游客空间分布地区差异,呈明显的集中型格局,主要集中于珠三角地区,且有进一步向其集中的态势;(3)入境游客空间分布市域差异,呈现从以广州、深圳为双中心,向四周辐散的"中心双核辐射式结构"到以深圳、广州、珠海、东莞以及惠州为多中心,向四周辐散的"中心多核辐射式结构"过度趋势,空间集聚性指数下降,入境游客空间分布趋于分散均匀,市域差异有缩小的趋势。