Effects of Vaccination and the Spatio-Temporal Diffusion of Covid-19 Incidence in Turkey

This study assesses the spatio-temporal impact of vaccination efforts on Covid-19 incidence growth in Turkey. Incorporating geographical features of SARS-CoV-2 transmission, we adopt a spatial Susceptible–Infected–Recovered (SIR) model that serves as a guide of our empirical specification. Using provincial weekly panel data, we estimate a dynamic spatial autoregressive (SAR) model to elucidate the short- and the long-run impact of vaccination on Covid-19 incidence growth after controlling for temporal and spatio-temporal diffusion, testing capacity, social distancing behavior and unobserved space-varying confounders. Results show that vaccination growth reduces Covid-19 incidence growth rate directly and indirectly by creating a positive externality over space. The significant association between vaccination and Covid-19 incidence is robust to a host of spatial weight matrix specifications. Conspicuous spatial and temporal diffusion effects of Covid-19 incidence growth were found across all specifications: the former being a severer threat to the containment of the pandemic than the latter.     

Differences in cancer incidence between men and women in the province of Québec, Canada, 1984–1993

This research concerns variation in incidence rates of cancer for males and females aged 35 to 69 in Québec for the period 1984 to 1993. In analysing the data, the Island of Montréal (health region 06) was distinguished from the rest of the province of Québec (excluding Nunavik and the James Bay regions). Relative rate index and the ratio of standardised incidence rates of cancer for males and females showed similar tendencies in all regions studied, with the risk of non–sex‐specific cancer higher in men than in women (excess ranged from 5 or 20 to 240 percent according to the study region). However, this higher risk was not consistent across lifespan and cancer site in the Montréal area. We suggest some general points that could explain the differences in cancer incidence between males and females.     

Waiting during disasters: Negotiating the spatio-temporalities of resilience and recovery

Always spatial, waiting time is the observation of past-present-future, and temporality is the condition of being bounded by time. Both are mechanisms of state governance that control how and when families recover from rapid-onset humanitarian disasters. Analysing these spatio-temporalities reveals how families leverage resources to engage in acts of resilience that challenge the state’s spatio-temporal control of recovery. A case study focuses on the aftermath of Hurricane Maria, which devastated Puerto Rico in 2017. We draw on qualitative longitudinal research to explore politicised spatio-temporal experiences of waiting for the state to fix public infrastructures; approve financial support; and provide access to affordable consumables—which all shape families’ recovery rates and pathways. Disaster-affected families do not passively wait for the state and often leverage their incomes and social networks to engage in resilience-based strategies that ease their everyday lives and enable recovery while waiting for the state. Waiting feels more arduous for families with fewer resources and when there is uncertainty about access to the state and how and when to begin certain recovery activities. Waiting in disasters can also provide space for collective socio-political practices such as community gardening to emerge in neighbourhoods. For researchers of disasters, this article highlights the spatio-temporal dimensions of grassroots resilience and the ways in which state power and citizen agency interact in ways that subvert state control of families’ recovery rates in heterogeneous ways. Research on waiting during disasters has great potential to inform and reform governance for resilience and recovery.     

Identifying Areas with Elevated Disease Incidence Rates Using Empirical Bayes Estimators

Using maps of observed disease incidence rates to identify regions with potentially elevated risk may be misleading due to the instability of the observed rates in regions with small populations. We use a simulation study to examine the use of maps based on observed incidence rates in identifying such high-risk areas as compared to maps based on empirical Bayes and constrained empirical Bayes rate estimates. In addition, because the existence of clusters of areas with elevated risk violates the usual distributional assumptions underlying the empirical Bayes approach, we also examine the robustness of the estimates and the impact of incorrect assumptions on identification of high-risk regions. The simulation results indicate that the observed incidence rates were quite sensitive in terms of identifying areas with truly elevated rates. However, due to the instability of the observed rates, maps based on observed incidence incorrectly identified areas as high risk more frequently than did maps based on the estimators. The standard and constrained empirical Bayes estimates were more stable than the observed rates even when based on incorrect distributional assumptions. The standard empirical Bayes estimates, however, were oversmoothed in that too few areas were identified as having elevated risk. The constrained empirical Bayes approach provided sensitivity closer to that of the observed rates yet with the percentage of areas incorrectly identified as high risk equal to that of the standard empirical Bayes estimates. We illustrate an application of these results with an analysis of the geographic distribution of brain cancer mortality among counties in Ohio.     

A Potential Case of Social Bankruptcy: States' AFDC Payments and Their Teen Birth Rates

Based on a pooled time series analysis that covers a 30-year period at five different time points—1960, 1970, 1980, 1985, and 1990—this research examines the relationship between states' Aid to Families with Dependent Children (AFDC) payments and teen birth rates. Drawing on rational choice theories, we expected the effects of states' AFDC payments on their teen birth rates to be positive, taking into account states' divorce rates, population change rates, unemployment rates, racial composition, and poverty rates. The effects of states'AFDC payments were significant in a negative direction in Model 1, a random effects model; they also were significant in a negative direction in Model 2 when we controlled for the effects of year; however, when we controlled for the effects of year and state in Model 3, they were not significant. The findings do not support assumptions regarding the incentive effects of welfare that underlie rational choice theories in states where teen birth rates are higher. If anything, teen birth rates are higher in states where AFDC payments are lower. Implications for policy and further research are discussed in relation to the positive effects of states' poverty and population change rates on the state teen birth rate problem.     

Aggregation of Regional Economic Time Series with Different Spatial Correlation Structures. 具有不同空间相关结构的区域经济时间序列集成

In this article, we compare the relative efficiency of different forecasting methods of space‐time series when variables are spatially and temporally correlated. We consider two cases: (1) univariate forecasting (i.e., a space‐time series aggregated into a single time series) and (2) the more general instance of multivariate forecasting (i.e., a space‐time series aggregated into a coarser spatial partition). We extend the results in the literature by including the consideration of larger datasets and the treatment of edge effects and of negative spatial correlation. We first introduce a statistical framework based on the space‐time autoregressive class of random field models, which constitutes the basis of our simulation study, and we present the various alternative forecasting methods considered in the simulation. We then present the results of a Monte Carlo study related to univariate forecasting. In order to allow a comparison with the findings of Giacomini and Granger (2004), we consider the same forecasting strategies and the same combinations of the parameter values used there, but with a larger parametric set. Finally, we extend our analysis to the case of multivariate forecasting. The outcomes obtained provide operational suggestions about how to choose between alternative forecasting methods in empirical circumstances.     

Ceramic diversity,random copying,and tests for selectivity in ceramic production

This paper examines the evidence for selective reproduction of ceramic types based on their evolving frequency distribution, and on correlations of the abundance of types with underlying functional characteristics. How can we tell if a variant has been preferentially selected or discriminated against, and become more or less frequent than would be expected under pure drift (i.e. random copying, with the compounding over time of proportionate sampling error)? We examined a database of Hittite ceramic bowl types from two successive Phases of occupation of the Upper City of Bo?azköy–Hattusa, capital of the Hittite empire and the largest Bronze Age settlement in Turkey. We applied two tests used in genetics to assess departures from neutrality, to assess selectivity in rates of reproduction of ceramic bowl types (the Ewens-Watterson and Slatkin's Exact tests). We also examined the effects of ceramic fabric and vessel dimensions on changes in vessel abundance between the two Phases, using regression analysis. We found that while the frequency distribution of rim sherds did not in itself enable us to reject the null hypothesis of random copying, closer examination of the characteristics of these types enabled us to recognize latent dimensions of functional variability (including ware type and bowl diameter) that had demonstrably been the subject of selective decision-making by the potters. The present case study suggests that we should be wary of applying the neutral model from genetics uncritically in archaeology, because it is much harder to prove that the cultural traits whose frequencies are being modelled are genuinely functionally equivalent (as that model requires).     

南京市居民日常消费时空行为的代际差异

在我国居民消费趋于个性化和多元化的情形下,基于代群特征与差异的研究显得尤为缺乏。本研究结合代际差异理论和行为地理学、社会学的研究方法,研究居民消费时空行为特征及影响因素的代际差异。通过对南京市50后—90后的5代居民抽样调查,利用ArcGIS平台、SPSS23.0中多独立样本非参数检验和相关性分析方法,刻画并分析5个代群之间及两两代群之间的差异。研究发现：①不同代际群体在消费空间类型、消费出行距离和消费频率上存在显著代际差异,消费时长和消费出行时耗没有显著代际差异,这种差异性与代群之间的年龄差距并非呈线性相关;②居民日常消费时空行为所受影响因素的类型存在代际差异,不同代群尤其是年龄相近的代群之间所受主要影响因素的显著差异,进一步说明代群所内涵的社会文化特征以及习惯和观念等方面的差异,构成其消费时空行为的内在驱动机制;③消费的代沟是局部存在的。研究发现消费时空行为的代际差异与代际差异理论内涵之间具有联系,并表明代际差异是一个重要的视角,有助于我们揭示社会群体消费时空行为的多样性和差异性。     

Dental Wear and Pathology in the Precolonial Caribbean: Evidence for Dietary Change in the Ceramic Age

This study investigates temporal changes in dietary practices in the Caribbean archipelago during the Ceramic Age (400 BC–AD 1500), through analyses of dental wear and pathology. Some previous studies in the region have suggested that diet and subsistence practices changed over time due to increasing sociopolitical complexity, climate change, or adaptation to island environments rich in marine resources. Both horticultural/agricultural intensification and increased marine focus of the diet over time have been posited, based among other things on faunal and botanical remains, and early ethnohistorical accounts. Local and micro‐regional stable isotope studies of temporal dietary variation have found few indications for change over time, and large regional isotope studies are still lacking. Dentitions from sites throughout the region dating to the Early Ceramic Age (400 BC–AD 600/800) and the Late Ceramic Age (AD 600/800–1500) were analysed in order to assess temporal differences. Intra‐individual rates of wear were calculated using the difference in degree of wear between the adjacent molars and the two groups were compared with principal axis analysis. Caries, antemortem tooth loss, abscesses and dental calculus were recorded per individual and per tooth/socket, and population caries and antemortem tooth loss rates were assessed and compared by age group, tooth class and sex. Comparisons between the two occupation periods revealed significant differences in the rate of dental wear and pathology, indicating a shift in dietary practices over time, coinciding with known social changes. The increase in pathology rates suggests a rise in the consumption of cariogenic foods or preparation techniques that increase cariogenicity. The decrease in rate of wear over time indicates a reduction in abrasivity of the diet. Together these data suggest that there was a growing focus on refined, cariogenic foods, likely horticultural/agricultural produce. Copyright © 2014 John Wiley & Sons, Ltd.     

Hispanic Pregnancy Outcomes: Differentials Over Time and Current Risk Factor Effects

In light of major changes over the past decade or two in the structure of infant mortality in the United States, the primary objectives of this article are to document recent variation in pregnancy outcomes in specific Hispanic populations compared with non-Hispanic Whites and to estimate the contemporaneous association of ethnicity with risk of preterm birth, low birth weight, and infant mortality. The primary data employed are the 1995–1997 NCHS Linked Birth/Infant Death Files. Changes over time are examined through comparisons with the 1989–1991 counterpart files. Logistic regression models provide estimates of ethnic disparities in birth weight, gestational age, and infant mortality. Every ethnic population followed the national pattern of increasing rates of adverse birth outcomes coupled with declining rates of infant mortality. Net of the effects of a wide range of risk factors, every Hispanic group was at greater risk of short gestation and low-weight births, but at lower risk of infant death. The findings are consistent with the view that Hispanics, as well as the White, non-Hispanic majority, have benefited from advances in neonatal health services and technology at the time of delivery and postpartum. The epidemiologic paradox appears to be applicable to some, but not all, Hispanic groups.     

Representing Structural Change in U.S. Migration Patterns

This paper focuses on the identification of three sets of relationships exhibited by a time series of age-specific national migration rates and multiregional transition probability matrices: the relationship across time for the same age group, as defined by period (temporal) transformation coefficients or matrices; the relationships across age at a particular moment in time, as defined by age transformation coefficients or matrices; and the relationships across time and age, as defined by cohort transformation coefficients or matrices. Given any two of these relationships one can solve for the third. This feature of age-period-cohort relationships has a practical application in the development of improved methods for representing structural change in migration patterns over time and for indirectly estimating migration patterns using inadequate data.     

多情境下城市时空间行为的社会分异——以北京不同住房来源居民为例

近年来,居民时空间行为的社会分异已成为学者们广泛关注的话题。然而,已有关于居民时空间行为的社会分异研究中,缺少对于居民活动情境的社会分异的研究。因此,本研究基于时间地理学中对人类活动的情境嵌入性与情境的不同维度的相关理论,以北京清河街道为例,分析不同住房来源居民在日常情境、地理情境和社会情境下的时空间行为的社会分异,尝试从多个情境维度拓展对时空间行为社会分异的理解。研究发现,市场性住房居民“朝九晚五”的活动特征明显,活动同伴选择外向性突出;单位性住房居民职住相对接近,在社区空间内分配时间最长且活动目的多样;安置性住房居民活动较为分散,地理情境与社会情境都呈现出“家庭内向性”特征;保障性住房居民非工作活动的“滞后性”明显,对社区空间的时间分配总体较低。除住房来源因素与个人社会经济因素外,建成环境因素对于居民对社区空间的使用有显著影响。     

THE STUDY OF POLITICAL FEEDBACK USING NONRECURSIVE CAUSAL MODELS: THE CASE OF STATE DIVORCE POLICIES

Researchers interested in policy feedback effects can use the nonrecursive modeling strategies proposed here when time series data are not available for assessing feedback dynamics. This strategy is illustrated in a study of the impacts of American state divorce policies on divorce behavior and the responsiveness of policies to divorce rates. The findings show appreciable impact and feedback effects. In states where divorces are easier to obtain, the incidence of divorce is higher; and where divorce is more widespread, states are likely to implement more permissive divorce policies.     

Geographically Weighted Cox Regression for Prostate Cancer Survival Data in Louisiana

The Cox proportional hazard model is one of the most popular tools in analyzing time-to-event data in public health studies. When outcomes observed in clinical data from different regions yield a varying pattern correlated with location, it is often of great interest to investigate spatially varying effects of covariates. In this paper, we propose a geographically weighted Cox regression model for sparse spatial survival data. In addition, a stochastic neighborhood weighting scheme is introduced at the county level. Theoretical properties of the proposed geographically weighted estimators are examined in detail. A model selection scheme based on the Takeuchi’s model robust information criteria is discussed. Extensive simulation studies are carried out to examine the empirical performance of the proposed methods. We further apply the proposed methodology to analyze real data on prostate cancer from the Surveillance, Epidemiology, and End Results cancer registry for the state of Louisiana.     

An English approach to the American frontier

Studies of frontier migration in the American west are hampered by lack of data because few records contain evidence of reasons for migrating or evidence of decisions taken by individual migrants or groups of migrants. An extensive collection of letters from two English brothers who, in 1882, migrated to an English farm colony in north-west Iowa, then moved into horse-raising in Wyoming, then returned to Iowa, and later went back to Wyoming, provides an unusually illuminating case study in frontier migration. The letters reveal reasons for the frequent moves in the west over a seventeen-year period ending with the brothers' successful establishment as sheep ranchers in Wyoming. They show how each shift was conditioned by their previous experience of economic difficulties and by their persistent reliance upon contacts in England.     

A Correlation Between Radiation and Health Problems in Belarus'?

An international authority on the effects of the Chernobyl' nuclear power station accident surveys the emerging controversy over the severity of its impact upon the health of the population of Belarus', the republic most seriously affected by the radiation release. A broad spectrum of assessments is analyzed, ranging from those which are inclined to attribute negligible health impacts to the disaster to those citing dramatic increases in the incidence of thyroid cancer among children in the most severely impacted oblasts as a possible precursor of significant long-term health risks to the population at large. 1 map, 1 table, 17 references.     

Hierarchical Bayesian Spatiotemporal Analysis of Childhood Cancer Trends

In this article, generalized additive mixed models are constructed for the analysis of geographical and temporal variability of cancer ratios. In this class of models, spatially correlated random effects and temporal components are adopted. Spatio‐temporal models that use intrinsic conditionally autoregressive smoothing across the spatial dimension and B‐spline smoothing over the temporal dimension are considered. We study the patterns of incidence ratios over time and identify areas with consistently high ratio estimates as areas for further investigation. A hierarchical Bayesian approach using Markov chain Monte Carlo techniques is employed for the analysis of the childhood cancer diagnoses in the province of Alberta, Canada during 1995–2004. We also evaluate the sensitivity of such analyses to prior assumptions in the Poisson context. En este artículo los autores construyen modelos aditivos generalizados mixtos (generalized additive mixed models) con el fin de analizar la variabilidad geográfica y temporal en las tasas de incidencia de cáncer. Este tipo de modelos emplean efectos aleatorios correlacionados espacialmente y componentes temporales. Los modelos espacio‐temporales emplean un suavizado condicional intrínseco autorregresivo (conditionally autoregressive smoothing) a través de la dimensión espacial y un suavizado de tipo B‐spline sobre la dimensión temporal. Los autores examinan los patrones de las tasas de incidencia a través del tiempo e identifican las áreas con valores consistentemente altos con el fin de sugerir áreas de investigación para el futuro. El estudio utiliza un enfoque jerárquico bayesiano (hierarchical bayesian) que usa una cadena de Markov Monte Carlo para evaluar los diagnósticos de cáncer infantil en la provincia de Alberta, Canadá durante el periodo 1995–2004. Asimismo, también se evalúa la sensibilidad de este tipo de análisis con respecto a los supuestos a‐priori, en el contexto de los modelos tipo Poisson. 本文提出了广义可加和混合模型进行癌症比率的地理和时间变化分析。在这类模型中引入了空间相关的随机效应和时间组分。时空模型在空间维度上采用本征自回归条件平滑,而在时间维度上则使用了B样条平滑。本文研究了疾病发生率模式,并识别出一直具有高比率估计的地区作为进一步调查区。在1995–2004年加拿大亚伯达省儿童癌症的诊断中,采用了基于马尔科夫链‐蒙特卡罗模型的分层贝叶斯方法,并且在泊松先验假设条件下评估了该类分析的敏感性。     

Loglinear Residual Tests of Moran's I Autocorrelation and their Applications to Kentucky Breast Cancer Data

This article bridges the permutation test of Moran's I to the residuals of a loglinear model under the asymptotic normality assumption. It provides the versions of Moran's I based on Pearson residuals ( I _PR) and deviance residuals ( I _DR) so that they can be used to test for spatial clustering while at the same time account for potential covariates and heterogeneous population sizes. Our simulations showed that both I _PR and I _DR are effective to account for heterogeneous population sizes. The tests based on I _PR and I _DR are applied to a set of log-rate models for early-stage and late-stage breast cancer with socioeconomic and access-to-care data in Kentucky. The results showed that socioeconomic and access-to-care variables can sufficiently explain spatial clustering of early-stage breast carcinomas, but these factors cannot explain that for the late stage. For this reason, we used local spatial association terms and located four late-stage breast cancer clusters that could not be explained. The results also confirmed our expectation that a high screening level would be associated with a high incidence rate of early-stage disease, which in turn would reduce late-stage incidence rates.     

北京市休闲型乡村时空修复与潜在风险——以莲花池村为例

城市化进程的加快和城市消费文化的兴起,促使乡村成为资本青睐和占用的空间,其实质是资本为缓解过度积累危机而进行的“时空修复”。基于此,本文在引介时空修复理论基础上,探讨了北京市莲花池村时间修复和空间修复过程,剖析了其背后隐含的潜在风险。研究发现,莲花池村经由资本三级循环实现了空间转型,乡村空间本身成为资本增值元素,内外资本的流动在实现地理空间拓展的同时,造成聚落空间形态的重构和地方组织模式的调整,并孕育了村民内部分层、空间生产同化、空间正义缺失、传统文化消融等多重风险。