Regional variability in relationships between climate and dengue/DHF in Indonesia

Since 1970, the worldwide distribution, frequency and intensity of epidemics of dengue and dengue haemorrhagic fever (DHF) have increased dramatically. In Indonesia, as elsewhere, the geographic distribution and behaviour of the two main vectors – Aedes aegypti and Aedes albopictus – and the consequent transmission dynamics of the disease are strongly influenced by climate. Monthly incidence data were examined in relation to monthly data for temperature, rainfall, rainfall anomalies, humidity and the Southern Oscillation Index for 1992–2001. Focusing on eight provinces, significant Pearson correlations were observed between dengue/DHF incidence and at least one climate variable ( r  = ±0.2 to ±0.43; P  < 0.05). Multiple regression analyses showed that 12.9–24.5 per cent of variance in incidence was explained by two or three climate variables in each province ( P  < 0.1–0.01). Rainfall appears to be the principal climatic agent affecting the geographic distribution and temporal pattern of incidence while temperature appears to play a critical role in outbreak intensity. Wide regional and temporal variations in the strength and nature of the observed associations led to the identification of three groups of provinces where increases in dengue/DHF incidence were variously associated with increased rainfall, decreased rainfall and/or high susceptibility to climate variability. Although climatic factors play an important role in explaining the timing and intensity of dengue/DHF outbreaks, a wide range of other factors specific to local environments also appear to be involved – information that may assist in the prediction and mitigation of regional dengue/DHF outbreaks.     

Supporting local health decision making with spatial video: Dengue,Chikungunya and Zika risks in a data poor,informal community in Nicaragua

One challenge facing spatial scientists trying to support public health outreach and intervention in challenging environments is the lack of fine scale spatial data. These data are required to gain a better understanding of both physical and social systems; why disease occurs where it does, and how to disrupt it. While data options exist, including high resolution aerial imagery, remotely sensed data, and even online mapping products like Google Street View, these all come with limitations. One option that has previously been utilized to assess cholera risk is spatial video. Here it is used to map potential mosquito breeding sites in an endemic Dengue and Chikungunya, and emerging Zika impacted community. We show how this method can provide mapping support in the hands of non-specialist public health workers who, working in collaboration with out-of-area geographic information systems (GIS) teams, can identify where to target limited intervention resources. We use a case study of an impoverished informal style Nicaraguan community suffering from a high disease burden to show spatial variation in potential mosquito breeding habitats. A field team collected street-by-street spatial video data to produce fine scale risk maps of standing water and trash locations, which, when interpreted with the associated spatial video imagery, were used to suggest where intervention strategies should be targeted. We also discuss how these same data layers can be used to address other health concerns traditionally found in informal settlements.     

Site-specific prediction of West Nile virus mosquito abundance in Greater Toronto Area using generalized linear mixed models

Mosquito surveillance programs provide a primary means of understanding mosquito vector population dynamics for the risk assessment of human exposure to West Nile virus (WNv). The lack of spatial coverage and missing observations in mosquito surveillance data often challenge our efforts to predict this vector-borne disease and implement control measures. We developed a WNv mosquito abundance prediction model in which local meteorological and environmental data were synthesized with entomological data in a generalized linear mixed modeling framework. The discrete nature of mosquito surveillance data is accommodated by a Poisson distributional assumption, and the site-specific random effects of the generalized linear mixed model (GLMM) capture any fluctuation unexplained by a general trend. The proposed Poisson GLMMs efficiently account for the nested structure of mosquito surveillance data and incorporate the temporal correlation between observations obtained at each trap by a first-order autoregressive model. In the case study, Bayesian inference of the proposed models is illustrated using a subset of mosquito surveillance data in the Greater Toronto Area. The relevance of the proposed GLMM tailored to WNv mosquito surveillance data is highlighted by the comparison of model performance in the presence of inevitable but quantifiable uncertainties.     

A Systems Perspective on World-Systems Theory

Abstract

This article presents a conceptual framework that embeds ideas from world-systems theory within the larger systemic context known as the theory of dissipative structures. This article creates a theoretical perspective on global capitalism, both geographic and historical, that offers a sufficiently general and flexible model for this particular complex system in human geography. The goal is to provide a perspective that reflects the interconnectedness of individual and separate places into a larger global system that is a single functioning spatial entity. In this view, the modern world-system becomes a culmination of its past and a prologue to its future.     

A Cartographic Analysis Using Spatial Filter Logistic Model Specifications for Implementing Mosquito Control in Kenya

Negative spatial autocorrelation (NSA), the tendency for dissimilar neighboring values to cluster on a map, may go undetected in statistical analyses of immature Anopheles gambiae s.l., a leading malaria mosquito vector in Sub-Saharan Africa. Unquantified NSA generated from an inverse variance-covariance matrix may generate misspecifications in an An. gambiae s.l. habitat model. In this research, we used an eigenfunction decomposition algorithm based on a modified geographic connectivity matrix to compute the Moran's I statistic, to uncover hidden NSA in a dataset of georeferenced An. gambiae s.l. habitat explanatory predictor variables spatiotemporally sampled in Malindi and Kisumu, Kenya. The Moran's I statistic was decomposed into orthogonal synthetic map patterns. Global tests revealed that |z_MC|s generated were less than 1.11 for the presence of latent autocorrelation. The algorithm captured NSA in the An. gambiae s.l. habitat data by quantifying all non-normal random variables, space-time heterogeneity, and distributional properties of the spatial filters.     

Spatial patterns of adolescent drug use

Adolescent drug use is individually and socially harmful in terms of disrupting adolescent development and social cohesion. Prior research has identified populations at risk and risk factors for adolescent drug use. This research sought to contextualize adolescent drug use by examining this behavior from a geographic perspective. The specific objectives were to identify patterns, local clusters and excess spatial risk for 5-digit zip codes within the 5-county Cincinnati, Ohio region. Adolescents (n = 57,241) were recruited within local schools by the Coalition for a Drug-free Greater Cincinnati. Results of this research show spatial clusters for perceived safety of marijuana; peer approval of alcohol, tobacco and marijuana; and age of onset for other drugs. The location and nature of these clusters are discussed and displayed in-text. Further, zip codes that were in excess risk compared to the 5-county region were identified. The utility of this research is two-fold: (1) It identifies the geographic variability in adolescent drug use and correlated factors of use, and (2) It provides a methodological framework for future research in spatial epidemiology of drug use.     

Constructed wetland technology and mosquito populations in Arizona

Constructed wetlands and other aquatic habitat creation or restoration efforts offer both potential benefits and problems for arid areas. An unintentional consequence of these efforts has been the potential for an increase in local adult mosquito populations. Shallow water-emergent plant zones may provide ideal conditions for mosquito larval growth, and areas of high humidity, dense vegetation, and abundant birds and other wildlife may provide ideal conditions for adult mosquitoes. Three constructed wetlands in southern Arizona were studied over a period of years before and after they were constructed and operational. Mosquito populations were sampled using a variety of methods, primarily trapping of adults with CO₂-baited traps. Populations apparently increased, sometimes by several orders of magnitude, after wetlands became operational. Several methods of mosquito abatement were initiated and their results are discussed. However, no definitive conclusions can be drawn because no untreated areas were available for comparison and many factors that may have affected mosquito populations also changed. Based on the experience gained at these three sites, mosquito control is an especially important design and management component for constructed wetlands in arid environments with low background populations of mosquitoes.     

A Spatial Variant of the Basic Reproduction Number for the New Orleans Yellow Fever Epidemic of 1878

A spatial variant of the basic reproduction number (R₀), here defined as the number of subsequent deaths attributed to an initial mortality, can be used to identify geographic variation within an epidemic. A spatial R₀ was calculated at the neighborhood level, here defined by a 50‐m buffer surrounding an index case, for mortality data from the 1878 yellow fever epidemic of New Orleans. The highest number of secondary mortalities linked to a neighborhood index case was twelve, with a further eighty‐seven extrapolated morbidity cases. Results also highlight the importance of multideath residences and cultural contacts in neighborhood‐level disease spread.     

A GIS-based risk rating of forest insect outbreaks using aerial overview surveys and the local Moran's I statistic

The objective of this study is to provide an approach for assessing the short-term risk of mountain pine beetle Dendroctonus ponderosae Hopkins (Coleoptera: Scolytidae) attack over large forested areas based on the spatial-temporal behavior of beetle spread. This is accomplished by integrating GIS, aerial overview surveys, and local indicators of spatial association (LISA) in order to measure the spatial relationships of mountain pine beetle impacts from one year to the next. Specifically, we implement a LISA method called the bivariate local Moran's I_i to estimate the risk of mountain pine beetle attack across the pine distribution of British Columbia, Canada. The bivariate local Moran's I_i provides a means for classifying locations into separate qualitative risk categories that describe insect population dynamics from one year to the next, revealing where mountain pine beetle populations are most likely to increase, stay constant, or decline. The accuracy of the model's prediction of qualitative risk was higher in initial years and lower in later years of the study, ranging from 91% in 2002 to 72% in 2006. The risk rating can be continually updated by utilizing annual overview surveys, thus ensuring that risk prediction remains relatively high in the short-term. Such information can equip forest managers with the ability to allocate mitigation resources for responding to insect epidemics over very large areas.     

Lesson Plans in Geography

Abstract

This article advocates that geography teachers undertake field studies of human systems with their students. A field trip process is described that helps teachers to guide students to explore and analyze a real human system with the expressed goal of building skills that can transfer to and complement a wide range of geographic learning tasks identified in Geography for Life: National Geography Standards 1994. Students are taken to a human system, such as a supermarket or a hotel. In groups, students interview as well as tour with a representative of a key department of the human system. Using teacher-supplied materials, groups create models or visual schematics of the whole human system they studied. The model must show the complex as a collection of interdependent elements with distinct functions. The learning outcomes achieved by students are a collection of geographic skills ideal for transfer to subsequent geographic investigations of urban places and or regions.     

A comprehensive framework for studying diffusion patterns of imported dengue with individual-based movement data

ABSTRACT

International communication and global cooperation have greatly accelerated the worldwide spread of dengue fever, increasing the impact of imported cases on dengue outbreaks in non-naturally endemic areas. Existing studies mostly focus on describing the quantitative relationship between imported cases and local transmission but ignore the space-time diffusion mode of imported cases under the influence of individual mobility. In this paper, we propose a comprehensive framework at a fine scale to establish the disease transmission network and a mathematical model, which constructs ‘source-sink’ links between the imported and indigenous cases on a regular grid with a spatial resolution of 1 km to explore the diffusion pattern and spatiotemporal heterogeneity of imported cases. An application to Guangzhou, China, reveals the main flow and transmission path of imported cases under the influence of human movement and identifies the spatiotemporal distribution of transmission speed according to the time lag of each source-sink link. In addition, we demonstrate that using individual-based movement data and socio-economic factors to study human mobility and imported cases can help to understand the driving forces of dengue spread. Our research provides a comprehensive framework for the analysis of early dengue transmission patterns with benefits to similar urban applications.     

三江平原湿地区域生态风险评价研究

采用“点轴体系”及“中心地理论”来描述和表征区域人类活动的空间集聚特征,以此反映湿地区域人类活动直接风险来源,通过土壤侵蚀与非点源污染途径,区域非湿地部分(森林、水田、旱地等)通过物质联系(泥沙、氮磷、水等的输出与输入)方式也会对湿地健康造成影响,反映湿地区域人类活动间接风险来源。基于对人类活动影响湿地直接途径和间接途径的区分以及相应部分风险指标的选择,论文最终完成三江平原湿地区域生态风险评价研究工作。结果表明：DMSP/OLS(Defense Meteorological Program Operational Line-Scan System)夜间灯光及多等级道路数据可以用于区域点轴体系描述,从而表征出湿地区域人类活动直接风险来源的空间分布特征,其中高和极高风险源强度等级与区域高等级中心地和高等级道路拟合程度较好;由于较高的生态资产及脆弱性水平,湿地有最高的生态风险水平;三江平原低、中、高和很高风险等级所占比例分别为64.00%、24.28%、10.38%、1.34%,大部分为低和中等风险水平,但有关风险防范任务仍不可掉以轻心,特别是在相应的高等级风险分布区域;南部地区有较高的风险水平,因此需要着重加以保护。从生态系统服务功能来看,一般认为水田、旱地为生产功能区,森林、湿地为生态功能区。过分关注水田、旱地的生产服务功能会造成下游湿地过量的物质输入从而加剧其风险水平;相反,注重森林保育能够减少泥沙、氮磷等大量输出风险,增加流域产流,从而可为下游湿地健康维持作出贡献。因此,水田、旱地与湿地间是一种生态服务权衡关系,森林与湿地间是一种生态服务协同关系,因此,风险管理方面,应强调区域”点轴体系“与湿地间的空间邻接关系,注重湿地重点生态风险来源（地点与方位）的防范以及湿地与非湿地类型间基于生态系统服务功能的权衡及协同管理问题。可为从区域整体水平上削减湿地健康风险水平提供指导和帮助。     

Same space – different perspectives: comparative analysis of geographic context through sketch maps and spatial video geonarratives

ABSTRACT

The importance of including a contextual underpinning to the spatial analysis of social data is gaining traction in the spatial science community. The challenge, though, is how to capture these data in a rigorous manner that is translational. One method that has shown promise in achieving this aim is the spatial video geonarrative (SVG), and in this paper we pose questions that advance the science of geonarratives through a case study of criminal ex-offenders. Eleven ex-offenders provided sketch maps and SVGs identifying high-crime areas of their community. Wordmapper software was used to map and classify the SVG content; its spatial filter extension was used for hot spot mapping with statistical significance tested using Monte Carlo simulations. Then, each subject’s sketch map and SVG were compared. Results reveal that SVGs consistently produce finer spatial-scale data and more locations of relevance than the sketch maps. SVGs also provide explanation of spatial-temporal processes and causal mechanisms linked to specific places, which are not evident in the sketch maps. SVG can be a rigorous translational method for collecting data on the geographic context of many phenomena. Therefore, this paper makes an important advance in understanding how environmentally immersive methods contribute to the understanding of geographic context.     

Making Space for the Citizen in Geographic Education

Abstract

This article argues that we need to reconsider the connection between citizenship and geography. Although geographic education purports to prepare citizens, the possibilities for this relationship have been addressed by few scholars. The study shows that citizenship is situated in places and students’ actions as citizens reinscribe the meaning of these places. Because of this intersection, educators must be attentive to how they teach about places, particularly the ongoing interconnection between place and identity. One of the identities common in the teaching of places is citizenship. Geography instructors need to be thoughtful about their role as citizenship educators.     

互联网对城市人居活动的影响研究——以大连市为例

随着互联网的快速发展及其普及,人类生存的地理空间环境也受到了网络化影响,形成一种虚拟空间环境。论文基于问卷调查法,以大连市为例,借助SPSS统计软件对不同调查区虚拟空间环境下的城市人居活动进行比较分析,并研究其空间特征。研究结果表明:虚拟空间环境对城市人居活动的影响日益突出,并与现实地理空间下人居活动存在一定的补充与替代性;在各区层面上,居民的网购频率、网购花费、远程工作和学习频率、以及通过网络获取信息和联系等人居活动的空间差异明显。     

松嫩平原湖泊底泥重金属空间变异特征及其风险评价

利用地理信息系统和地统计分析技术分析了松嫩平原湖泊群湖泊底泥重金属的空间变异特征,并绘制了6种重金属的空间分异图,利用地累积指数法和潜在生态危害指数法对湖泊底泥重金属的污染现状和潜在生态风险进行了评价。结果表明,松嫩平原湖泊群底泥重金属含量除Mn低于土壤背景值外,其他元素均高于背景值2～4倍,并且重金属含量在空间上呈东北向西南方向逐渐降低,表现出较强的相关性;污染现状评价表明,Zn已处于中等以上的污染程度,其他重金属污染程度较低,而Mn无污染,污染程度的顺序为Zn>Cu>Ni>Pb>Sr>Mn;潜在生态风险评价表明,评价的重金属均处于低生态风险程度,单项重金属的风险程度顺序为Pb>Cu>Ni>Zn;综合污染评价与风险评价,Zn的污染程度虽然较大,但仍处于低风险程度。     

Exploratory Spatiotemporal Analysis in Risk Communication during the MERS Outbreak in South Korea

The 2015 Middle East respiratory syndrome (MERS) outbreak in South Korea gave rise to chaos caused by psychological anxiety, and it has been assumed that people shared rumors about hospital lists through social media. Sharing rumors is a common form of public perception and risk communication among individuals during an outbreak. Social media analysis offers an important window into the spatiotemporal patterns of public perception and risk communication about disease outbreaks. Such processes of socially mediated risk communication are a process of meme diffusion. This article aims to investigate the role of social media meme diffusion and its spatiotemporal patterns in public perception and risk communication. To do so, we applied analytical methods including the daily number of tweets for metropolitan cities and geovisualization with the weighted mean centers. The spatiotemporal patterns shown by Twitter users' interests in specific places, triggered by real space events, demonstrate the spatial interactions among places in public perception and risk communication. Public perception and risk communication about places are relevant to both social networks and spatial proximity to where Twitter users live and are interpreted in reference to both Zipf's law and Tobler's law.     

Measuring the attractiveness of Dutch landscapes: Identifying national hotspots of highly valued places using Google Maps

In a Cost-Benefit Analysis (CBA) or an Environmental Impact Assessment (EIA), determining the value that the general public attaches to a landscape is often problematic. To aid the inclusion of this social value in such analyses, a Google Maps-based tool, called the HotSpotMonitor (HSM), was developed. The HSM determines which natural places are highly attractive by having people mark such places on a map. The definition of attractiveness remains open to avoid having marker placement being influenced by preconceived thoughts. The number of markers an area receives is considered to indicate its social value. Six regions were selected, and from these, stratified samples were drawn (total n = 3293). Participants placed markers at three spatial levels: local, regional and national. This paper focuses on the markers at the national level. The first research question is whether the HSM can produce an accurate map of highly attractive places at a national level. The results indicated that while in principle HSM can produce such a map, the spatial representativeness of the sample is important. The region of origin of the participants influenced where they placed their markers, an effect previously termed spatial discounting. The second research question considers which qualities the participants associate with the marked places. These qualities were very similar at all three spatial levels: green, natural, presence of water and quiet were often selected out of the fourteen suggested qualities. The third, and more exploratory, research question concerns which characteristics of an area predict its attractiveness. Natural and forest areas had higher marker densities than water surfaces or all other types of land use combined. The discussion evaluates the potential of the HSM to generate input on social landscape values for CBAs and EIAs.     

广州市登革热时空传播特征及影响因素

以广州市主城区为研究区,着眼于街道等微观尺度,首先通过实地调查分析法、核密度分析法、标准差椭圆法,探究登革热时空传播特征;其次结合交叉相关性分析法与地理探测器,分析温度、湿度、气压、用地类型对登革热传播的影响,讨论了不同用地类型交互作用与登革热扩散的关系。研究表明：1）登革热时空传播具明显的阶段性特征,多发生于居住环境较差、人口密度较高的区域,并快速向外扩散;2)登革热发展初期,以输入型病例为主;3）环境较差、老年人口众多、人员构成复杂、交通便捷的老城区是登革热高爆发风险区域;4）温度、湿度、气压对登革热传播存在显著滞后性影响关系,温度、湿度与登革热传播呈正相关关系,气压与登革热传播呈负相关关系;5）居民人口分布与登革热传播关系最为密切,池塘、农田、草地、公共绿地交互地区会增加登革热传播风险。