Geoffrey Mark Jacquez

• MS, PhD
• CEO at BioMedware

As the volume, accuracy and precision of digital geographic informationhave increased, concerns regarding individual privacy and confidentiality havecome to the forefront. Not only do these challenge a basic tenet underlying theadvancement of science by posing substantial obst acles to the sharing of data tovalidate research results, but they are ob...

The exposome, defined as the totality of an individual's exposures over the life course, is a seminal concept in the environmental health sciences. Although inherently geographic, the exposome as yet is unfamiliar to many geographers. This article proposes a place-based synthesis, genetic geographic information science (genetic 10 GIScience), that...

The representation of geographies (e.g. census units), demographics and populations as unchanging rather than dynamic is due in part to the static world-view of GIS software, which has been criticized as not fully capable of representing temporal change and better suited to ‘snapshots’ of static systems (Goodchild 2000; Hornsby and Egenhofer 2002;...

Until recently, little attention has been paid to geocoding positional accuracy and its impacts on accessibility measures; estimates of disease rates; findings of disease clustering; spatial prediction and modeling of health outcomes; and estimates of individual exposures based on geographic proximity to pollutant and pathogen sources. It is now cl...

This chapter introduces concepts central to the space-time analysis of cancer and breast cancer in space and time. By "space" we mean geographic location; by time we mean when specific events occurred. We deal with cancer at both the individual-and population-level, and are concerned with quantifying individual exposures through space and time, and...

Abstract: To what extent should cancer registries be integrated with individual-level data on the human exposome and genome? This presentation will explore this question within the framework of an ongoing contract from the National Cancer Institute’s “METRIC Software to Measure Cancer Health Environments” and a research proposal (in development)—“H...

Influenced by a special local environment, the proportion of centenarians is particularly high in some places, known as “blue zones”. Blue zones are mysterious regions that continue to attract research. This paper explores the spatial distribution of the longevity population in a typical Chinese longevity region. Longevity evaluation indexes are us...

Non-Hodgkin lymphoma (NHL) is an enigmatic disease with few known risk factors. Spatio-temporal epidemiologic analyses have the potential to reveal patterns that may give clues to new risk factors worthy of investigation. We sought to investigate clusters of NHL through space and time based on life course residential histories. We used residential...

In case control studies disease risk not explained by the significant risk factors is the unexplained risk. Considering unexplained risk for specific populations, places and times can reveal the signature of unidentified risk factors and risk factors not fully accounted for in the case-control study. This potentially can lead to new hypotheses rega...

Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of test...

Here, we focus on alternative significance tests for ecological data that often have skewed distributions, which impair the use of most parametric significance tests based on the normal distribution. Randomization tests have been proposed as an alternative to those classical significance tests where the observed data are repetitively reshuffled to...

Projected increases in global mean temperature of 2 – 4 °F (Kirtman et al. 2013) are anticipated to be accompanied with more severe and longer periods of extreme heat, particularly in the United States (Meehl and Tebaldi 2004). Adverse health effects of heat have been extensively researched and documented (Anderson and Bell 2011, Michelozzi et al....

Observed and expected changes in global and regional climates pose significant challenges to local decision makers tasked with identifying, preparing for, and responding to impacts on human populations. In particular, extreme heat is expected to increase in duration and intensity in Midwestern U.S. cities in this century. Because of the increased a...

Global mean temperatures are projected to rise 2– 4°F by the mid twenty-first cen-tury (Kirtman et al. 2013) and are expected to be accompanied by more severe and longer periods of extreme heat in particular geographic locations, including regions in the United States. (Meehl and Tebaldi 2004). Extensive research on the adverse health effects of ex...

This User Manual for SpaceStat Version 4.0 provides a comprehensive description of the software and how to use it. Check here for current pdf http://www.biomedware.com/files/SpaceStat_4.0_Documentation.pdf and here for software http://www.biomedware.com/?module=Page&sID=spacestat.

A large proportion of breast cancer cases are thought related to environmental factors. Identification of specific geographical areas with high risk (clusters) may give clues to potential environmental risk factors. The aim of this study was to investigate whether clusters of breast cancer existed in space and time in Denmark, using 33 years of res...

Generally, according to the definition by International Programme for Chemical Safety, part of World Health Organization (WHO 2004) an exposure event is an interaction between " an agent and a target ". In the field of human and environment interaction, an exposure refers to a human being impacted by different physical and psychological elements in...

In recent decades, digitally georeferenced data and geographic information systems (GIS) have played a growing role in human exposure assessment. Despite this, spatiotemporally varying datasets, such as daily activity spaces, residential histories, and time-varying maps of environmental contaminants, are poorly characterized in the GIS environment....

Marin County (California, USA) has among the highest incidences of breast cancer in the U.S. A previously conducted case-control study found eight significant risk factors in participants enrolled from 1997-1999. These included being premenopausal, never using birth control pills, lower highest lifetime body mass index, having four or more mammogra...

This report on the Vespucci Institute on health geography in 2013 emphasizes the importance of research that connects population, health, and place from a holistic perspective. We review important trends related to Health GIS and highlight directions for future research in this area that were identified at the Institute.

In this position paper, we describe a vision for the future of a so-called "Spatial-Health CyberGIS Marketplace". We first situate this proposed new computing ecosystem within the set of currently-available enabling technologies and techniques. We next provide a detailed vision of the capabilities and features of an ecosystem that will benefit indi...

This chapter explores the geocoding process in the context of health science research from both the theoretical and applied viewpoints. First, the many roles that geocoding plays in health science research are illustrated to show the breadth of scenarios where geocoding technologies have an impact. Secondly, technical details of the geocoding proce...

This project runs in BioMedware's SpaceStat software. I used it when I created the book chapter in the Handbook of Applied Spatial Analysis titled "Space-Time Intelligence System Software for the Analysis of Complex Systems." The data come from the Dominik's store chain in the Chicago area. Daily sales in several categories were recorded for each...

Spatial autocorrelation in health events may be the signature of underlying causal factors of direct scientific and practical interest but may also be due to pedestrian or nuisance factors that obscure meaningful spatial patterns. The problem is to discern spatial patterns that inform our understanding of the health events themselves from those tha...

The “Evaluation of Homomorphic Cryptography for Geospatial Studies with Human Subjects Workshop, sponsored by Biomedware and the North American Association of Central Cancer Registries, Inc., (NAACCR), was held on June 8-9, 2013, in Austin, TX. The purpose of the workshop was to: • Learn of the current status of the National Library of Medicine (NL...

Understanding latency – the delay between a cause and its effect – is critical when modeling dynamic geographic systems in general and in particular for human health outcomes such as cancer. This paper uses compartmental models to estimate residence times in states defining the progression of pancreatic cancer. Two models are developed. The first m...

Non-Hodgkin lymphoma (NHL) is a frequent cancer and incidence rates have increased markedly during the second half of the 20(th) century; however, the few established risk factors cannot explain this rise and still little is known about the aetiology of NHL. Spatial analyses have been applied in an attempt to identify environmental risk factors, bu...

In recent decades, digitally georeferenced data and Geographic Information Systems (GIS) have played a growing role in human exposure assessment for environmental epidemiologic studies. Despite the increased use of GIS in exposure assessment research, spatio-temporally varying datasets, such as daily activity spaces, residential histories, and time...

Few investigations of health event clustering have evaluated residential mobility, though causative exposures for chronic diseases such as cancer often occur long before diagnosis. Recently developed Q-statistics incorporate human mobility into disease cluster investigations by quantifying space- and time-dependent nearest neighbor relationships. U...

The First International Geocoding Conference took place in December at the Esri campus in Redlands, CA. Participants Daniel Goldberg from the University of Southern California and Geoffrey Jacquez of BioMedware, Inc. offer this report.

This chapter explores the complex, and sometimes frustrating, world of data discovery, access, delivery and use by reference to the US National Aeronautics & Space Administration’s (NASA’s) public health applications portfolio in 2011. It also provides examples of global information system applications in health.

A number of college presidents have endorsed the Amethyst Initiative, a call to consider lowering the minimum legal drinking age (MLDA). Our objective is to forecast the effect of the Amethyst Initiative on college drinking. A system model of college drinking simulates MLDA changes through (i) a decrease in heavy episodic drinking (HED) because of...

Few cancer clustering investigations have evaluated residential mobility even though exposure to environmental carcinogens may occur decades before a cancer diagnosis. Recently developed Q-statistics can be used to investigate disease clusters based on mobility histories by quantifying space- and time-dependent nearest neighbor relationships. Qik i...

It has been proposed that type 1 diabetes (T1D) and leukemia in children may cluster in space and time due to common spatially mediated etiologies. We investigated this hypothesis and clustering of both diseases separately in Danish children aged 0-14 years, using 1,168 leukemia cases diagnosed in the period 1980-2006, 2,443 T1D cases diagnosed 199...

Geographic boundary analysis is a relatively new approach that is just beginning to be applied in spatial and spatio-temporal epidemiology to quantify spatial variation in health outcomes, predictors and correlates; generate and test epidemiologic hypotheses; to evaluate health-environment relationships; and to guide sampling design. Geographic bou...

A key component of environmental epidemiologic research is the assessment of historic exposure to environmental contaminants. The continual expansion of space-time databases, coupled with the recognized need to incorporate mobility histories in environmental epidemiology, has highlighted the deficiencies of current software to visualize and process...

A key problem facing epidemiologists who wish to account for residential mobility in their analyses is the cost and difficulty of obtaining residential histories. Commercial residential history data of acceptable accuracy, cost, and coverage would be of great value. The present research evaluated the accuracy of residential histories from LexisNexi...

Epidemiologic analyses traditionally rely on point estimates of exposure for assessing risk despite exposure error. We present a strategy that produces a range of risk estimates reflecting distributions of individual-level exposure. Quantitative estimates of exposure and its associated error are used to create for each individual a normal distribut...

Objective Arsenic in drinking water has been linked with the risk of urinary bladder cancer, but the dose–response relationships for arsenic exposures below 100 μg/L remain equivocal. We conducted a population-based case–control study in southeastern Michigan, USA, where approximately 230,000 people were exposed to arsenic concentrations between 10...

Exposure to the risk of neighbourhood infection was estimated for the H7N1 Highly Pathogenic Avian Influenza (HPAI) epidemic that affected Northern Italy between 1999 and 2000. The two most affected regions (Lombardy and Veneto) were analyzed and the epidemic was divided into three phases. Q statistics were used to evaluate exposure to the risk of...

This article extends the compartmental model previously developed by Scribner et al. in the context of college drinking to a mathematical model of the consequences of lowering the legal drinking age. Using data available from 32 U.S. campuses, the analyses separate underage and legal age drinking groups into an eight-compartment model with differen...

Epidemiologic analyses traditionally rely on point estimates of exposure for assessing risk. In reality, however, exposure is characterized with uncertainty that can vary across individuals. Methods which incorporate uncertainty in exposure into epidemiologic analyses will yield a greater degree of confidence in estimates of risk. In this report we...

Although sources of positional error in geographic locations (e.g. geocoding error) used for describing and modeling spatial patterns are widely acknowledged, research on how such error impacts the statistical results has been limited. In this paper we explore techniques for quantifying the perturbability of spatial weights to different specificati...

The misuse and abuse of alcohol among college students remain persistent problems. Using a systems approach to understand the dynamics of student drinking behavior and thus forecasting the impact of campus policy to address the problem represents a novel approach. Toward this end, the successful development of a predictive mathematical model of col...

The objective of this study was to detect statistically significant racial disparities in lung cancer mortality at the U.S. congressional district level. We applied absolute disparity statistics to mortality data from the National Center for Health Statistics (NCHS) for 1990-2001, mapped significant lung cancer mortality disparities by race and gen...

Most disease clustering methods assume specific shapes and do not evaluate statistical power using the applicable geography, at-risk population, and covariates. Cluster Morphology Analysis (CMA) conducts power analyses of alternative techniques assuming clusters of different relative risks and shapes. Results are ranked by statistical power and fal...

Racial disparities in survival from breast and prostate cancer are well established; however, the roles of societal/socioeconomic factors and innate/genetic factors in explaining the disparities remain unclear. One approach for evaluating the relative importance of societal and innate factors is to quantify how the magnitude of racial disparities c...

Cancer registries are increasingly mapping residences of patients at time of diagnosis, however, an accepted protocol for spatial analysis of these data is lacking. We undertook a public health practice-research partnership to develop a strategy for detecting spatial clusters of early stage breast cancer using registry data. Spatial patterns of ear...

This paper develops and applies new techniques for the simultaneous detection of boundaries and clusters within a probabilistic framework. The new statistic “little b” (written b ij) evaluates boundaries between adjacent areas with different values, as well as links between adjacent areas with similar values. Clusters of high values (hotspots) and...

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Exposure misclassification is a major concern in epidemiologic studies. The potential for misclassification becomes even more problematic when participants are asked to recall historical information. Yet, historical information is important in cancer studies, where latency is long and causative exposures may have occurred years or even decades prio...

Spatial autocorrelation in health events may be the signature of underlying causal factors of direct scientific and practical interest but may also be due to pedestrian or nuisance factors that obscure meaningful spatial patterns. The problem is to discern spatial patterns that inform our understanding of the health events themselves from those tha...

Objective: Arsenic is a pervasive contaminant in underground aquifers worldwide, yet documentation of health effects associated with low-to-moderate concentrations (<100microg/L) has been stymied by uncertainties in assessing long-term exposure. A critical component of assessing exposure to arsenic in drinking water is the development of models fo...

Real-world systems are dynamic, complex and geographic, yet many mathematical modeling tools do n ot evaluate sensitivity of results to underlying assumptions, and GIS do not adequately represent time. This presentation describes two new approaches: Space-Time Information Systems (STIS), and Model Transition Sensitivity Analysis (MTSA). Current GIS...

Our research group recently developed Q-statistics for evaluating space-time clustering in case-control studies with residential histories. This technique relies on time-dependent nearest-neighbor relationships to examine clustering at any moment in the life-course of the residential histories of cases relative to that of controls. In addition, in...

Methods for analyzing geographic clusters of disease typically ignore the space-time variability inherent in epidemiologic datasets, do not adequately account for known risk factors (e.g., smoking and education) or covariates (e.g., age, gender, and race), and do not permit investigation of the latency window between exposure and disease. Our resea...

Space-time interaction arises when nearby cases occur at about the same time, and may be attributable to an infectious etiology or from exposures that cause a geographically localized increase in risk. But available techniques for detecting interaction do not account for residential mobility, nor do they evaluate sensitivity to induction and latenc...

Our progress towards the goal of eliminating racial health disparities requires methods for assessing the existence, magnitude, and statistical significance of health disparities. In comparing disease rates, we must account for the unreliability of rates computed for small minority populations and within sparsely populated areas. Furthermore, as th...

A space-time information system (STIS) based method is introduced for calculating individual-level estimates of inorganic arsenic exposure over the adult life-course. STIS enables visualization and analysis of space-time data, overcoming some of the constraints inherent to spatial-only Geographic Information System software. The power of this new m...

Our research group recently developed Q-statistics for evaluating space–time clustering in case–control studies with residential histories. This technique relies on time-dependent nearest-neighbor relationships to examine clustering at any moment in the life-course of the residential histories of cases relative to that of controls. In addition, in...

With recent advances in the power of personal computers, reference distributions of statistics are now often generated using computer-intensive methods. Several terms are erroneously used interchangeably when referring to such computer-intensive statistical methods, including ‘resampling techniques’, ‘Monte Carlo’, ‘permutation’, ‘randomization’ an...

Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn - w...

During the last decade one has witnessed an increasing interest in assessing health risks caused by exposure to contaminants present in the soil, air, and water. A key component of any exposure study is a reliable model for the space-time distribution of pollutants. This paper compares the performances of multi-Gaussian and indicator kriging for mo...

This article describes the Cancer Atlas Viewer: free, downloadable software for the exploration of United States cancer mortality data. We demonstrate the software by exploring spatio-temporal patterns in colon cancer mortality rates for African-American and white females and males in the southeastern United States over the period 1970-1995. We com...

This paper presents the first application of spatially correlated neutral models to the detection of changes in mortality rates across space and time using the local Moran's I statistic. Sequential Gaussian simulation is used to generate realizations of the spatial distribution of mortality rates under increasingly stringent conditions: 1) reproduc...

Geographic Information System (GIS) software is constrained, to a greater or lesser extent, by a static world view that is not well-suited to the representation of time (Goodchild 2000). Space Time Intelligence System (STIS) software holds the promise of relaxing some of the technological constraints of spatial only GIS, making possible visualizati...

A thorough assessment of human exposure to environmental agents should incorporate mobility patterns and temporal changes in human behaviors and concentrations of contaminants; yet the temporal dimension is often under-emphasized in exposure assessment endeavors, due in part to insufficient tools for visualizing and examining temporal datasets. Spa...

Modeling chronic and infectious diseases entails tracking and describing individuals and their attributes (such as disease status, date of diagnosis, risk factors and so on) as they move and change through space and time. Using Geographic Information Systems, researchers can model, visualize and query spatial data, but their ability to address time...

This paper presents a geostatistical methodology which accounts for spatially varying population size in the processing of cancer mortality data. The approach proceeds in two steps: (1) spatial patterns are first described and modeled using population-weighted semivariogram estimators, (2) spatial components corresponding to nested structures ident...

This paper describes a new methodology to detect small anomalies in high resolution hyperspectral imagery, which involves successively: (1) a multivariate statistical analysis (principal component analysis, PCA) of all spectral bands; (2) a geostatistical filtering of noise and regional background in the first principal components using factorial k...

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This paper introduces a new approach for evaluating clustering in case-control data that accounts for residential histories. Although many statistics have been proposed for assessing local, focused and global clustering in health outcomes, few, if any, exist for evaluating clusters when individuals are mobile. Local, global and focused tests for re...

Background Complete Spatial Randomness (CSR) is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial...

Background Recent years have seen an expansion in the use of Geographic Information Systems (GIS) in environmental health research. In this field GIS can be used to detect disease clustering, to analyze access to hospital emergency care, to predict environmental outbreaks, and to estimate exposure to toxic compounds. Despite these advances the inab...

While many lessons have been learned from the spatial analysis of cancer, there are several caveats that apply to many, if not all such analyses. As "flies in the ointment", these can substantially detract from a spatial analysis, and if not accounted for, can lead to weakened and erroneous conclusions. This paper discusses several assumptions and...