Seeing the Patterns in Space and TimeSeptember 28, 2017
The METRIC project has been accepted to the NIH-CAP (NIH Commercialization Accelerator Program). This highly competitive program was established and administered by the NIH. The program is described here. It is run by Larta, an organization focused on innovation, entrepreneurship, and commercialization.
Our kick-off meeting in Los Angeles is October 24-25.
Check out the NIH-CAP program timeline.
Geospatial Cryptography: enabling researchers to access private, spatially referenced, human subjects data for cancer control and preventionSeptember 5, 2017
Protecting confidentiality is mission-critical across the health care continuum, yet poses obstacles for the sharing and analysis of health data. Recent advances in cryptography support the analysis of confidential data in the encrypted space (e.g. make it homomorphic) – meaning analyses can be conducted on encrypted data with little if any risk of revealing confidential information. Prof. Jacquez’s research is developing geospatial cryptographic techniques for accelerating sharing of confidential data from our nation’s cancer registries.
- Jacquez, GM, A Essex, A Curtis, B Kohler, R Sherman, K Emam, C Shi, A Kaufmann, L Beale, T Cusick, D Goldberg, P Goovaerts. 2017. Geospatial cryptography: Enabling researchers to access private, spatially-referenced, human subjects data for cancer control and prevention. Journal of Geographical Systems 19(3), 197-220. DOI 10.1007/s10109-017-0252-3.
June 4, 2017
Recently my colleague Huang Yi, PhD, Nantong University, and I published a paper that used SpaceStat to find Blue Zones in China.
The data came from the Chinese and local governments. After loading and validating the data we used spatial time series methods to identify statistically significant Blue Zones. We explored several indices that have been proposed for blue zone identification and report the following results (refer to abstract, below). You can use the methods described in this paper to identify Blue Zones, and how their spatial distribution changes through time.
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 used to analyze the longevity phenomenon in 88 towns between 2011 and 2015. Our research findings show that longevity is more important than birth rate and migration in shaping the degree of deep aging in the research region.
Fluctuations in the proportion of centenarians are much higher than for nonagenarians, both in relation to towns and to years. This is because there are so few centenarians that data collected over a short time period cannot accurately represent the overall degree of longevity in a small region; data and statistics must be collected over a longer time period to achieve this. GIS analysis revealed a stable longevity zone located in the center of the research region. This area seems to help people live more easily to 90–99 years old; however, its ability to help nonagenarians live to 100 is a weaker effect.
Identification of a Blue Zone in a Typical Chinese Longevity Region. Available from: https://www.researchgate.net/publication/317179284_Identification_of_a_Blue_Zone_in_a_Typical_Chinese_Longevity_Region [accessed May 28, 2017].March 13, 2015
Save the dates April 13 and 14: Oakland, California
April 13: Pre-Workshop Short-course: Space Time Analysis for Health and the Environment
This 1-day class will provide instruction on the space-time analysis of data relating health events to potential sources of environmental exposures. Examples of data will include the time and place of residence of individuals with a given diagnosis, space-time paths of cases and controls over the life course, and cancer rates in local areas through time. We will focus on chronic diseases, such as cancer.
Instructor: Geoffrey Jacquez, PhD
Suitable for: Students, environmental and health faculty, researchers and community activists (a basic understanding of data and statistics would be useful).
April 14: Workshop on how to use geographic data to look at breast and other cancer risk factors in our physical and social environments and to inform prevention efforts.
(Supported by the California Breast Cancer Research Program award 21MB-0001 with space donated by The California Endowment.)
For additional information and registration details: www.zerobreastcancer.org/eventsMarch 9, 2015
“To examine the association of major types of comorbidity with late-stage prostate cancer, a random sample of 11,083 men diagnosed with prostate cancer during 2002-2007 was taken from the Florida Cancer Data System. Individual-level covariates included demographics, primary insurance payer, and comorbidity following the Elixhauser Index. Socioeconomic variables were extracted from Census 2000 data and merged to the individual level data. Provider-to-case ratio at county level was also computed.”
SpaceStat software was utilized for multilevel logistic regression to assess associations between these factors and late-stage diagnosis of prostate cancer.
Read more >> hereJanuary 12, 2015
Two proposal tips
We write a fair number of research proposals, with most of them going to the National Institutes of Health, and the Centers for Disease Control and surveillance. We also submit proposals to the National Science Foundation and NASA. For those researchers who are new to a proposal writing role here are a couple tips.
One of the first things to do after identifying the next “Big Idea” is to assess its potential viability and impact. Two items top the list. The first is the priority in terms of disease targeted; it is much easier to obtain funding for a disease with a large human and economic impact. One resource that may be of use is the global burden of disease, and of years of life lost (YYL). This article, published recently in The Lancet provides estimates from around the globe for both chronic and infectious disease burdens.
Second, if you are looking for funding in the U.S. it is important to consider what the funding organization’s budget and plan are for the near term. Remember the reviewers may not even be aware of the funding organizations research priorities. For NIH, the reviewers are external, and it is good proposal practice to remind them of the relevant NIH research priorities. A good portion of BioMedware’s research portfolio has been funded by the National Cancer Institute. Our 2015 proposals likely will incorporate information from NCI’s 2016 budget proposal and plan, which may be found here.
In summary, the message is to (1) seek to address important diseases, where importance is defined by human and economic costs; and (2) go after those proposal ideas that are highly relevant to the funding organization’s mission and budget plan.
Save the Date: April 13-14, 2015
Organized by The Cancer Prevention Institute of California and Zero Breast Cancer
Location: The California Endowment, 1111 Broadway, Oakland, CA
Geoffrey Jacquez, PhD, President of BioMedware, and Keynote speaker is conducting the preconference workshop on April 13th, titled “Space Time Analysis Using SpaceStat”.
In the news: SpaceStat for spatial analysis
Recently published articles demonstrating how SpaceStat’s rigorous, statistical analysis methods are being utilized by researchers.
Timothy S. Hare, Chad Wells, Nicole Johnson; Morehead State University, Morehead, KY, USA
International Journal of Applied Geospatial Research, 5(4), 35-53, October-December 2014 35
“…We use ESRI’s ArcGIS for data processing and visualization and BioMedware’s SpaceStat for EDA, ESDA, OLS regression, spatial regression, and GWR. SpaceStat is a set of software tools for conducting a variety of spatial statisti¬cal analysis techniques (BioMedware, 2012). It supports dynamic and interactive analysis of linked tables, charts, and maps. SpaceStat calculates probability values (p-values) for observed test statistics by comparing them to their null distributions, which estimates the likelihood of the observed values in comparison with the null distribution. The spatial weights matrix used is queen’s case contiguity.”
Download a 14-day Free Trial of SpaceStat
Alessandro Zini, Sergio Grauso, Vladimiro Verrubbi, Luca Falconi, Gabriele Leoni, Claudio Puglisi
Landslides, DOI 10.1007/s10346-014-0515-8
Received: 25 September 2013; Accepted: 14 August 2014
Background. Debris flows represent dangerous occurrences in many parts of the world. Several disasters are documented due to this type of fast-moving landslides, therefore, natural-hazard assessment of debris flows is crucial for safety of life and property. In this paper we investigated the effectiveness of the soil erosion index as debris flows susceptibility indicator. The relation between the erosion index, which was assessed by means of the Revised Universal Soil Loss Equation (RUSLE) model, and the inventory of debris flows that have occurred in an area in Sicily was investigated.
Method. To this aim, a geographically weighted logistic regression analysis (GWR) was carried out making use of SpaceStat. While traditional logistic regression aims to obtain an average parameter estimate over the whole territory under observation, the GWR attempts to gain point-to-point estimates. Moreover, the GWR technique may provide a better fit with experimental data.
Results. The results of the statistical analysis prove the existence of a significant connection between the observed debris flows and the RUSLE erosion index. Secondly, the complexity of the GWR model, based on non-fixed regression coefficients, points out that the same value of RUSLE index can have different effects in different locations. This result highlights the behavior of complex land systems in the real world, where different forces are acting (rain, running waters, internal water pressures, internal strains, gravity, etc.) and determine different point-to-point degrees of susceptibility to debris flows. On the basis of GWR parameters a scenario analysis regarding the area was conducted.
Download a 14-day Free Trial of SpaceStat
Follow Geoffrey Jacquez, PhD, on Twitter @GeoffJacquez.
Best wishes for your research efforts in 2015 and thank you for your interest in BioMedware.November 9, 2014
Due to an interrupted flight, Dr. Jacquez’s presentation was delivered via video at the CRCSI annual conference in Perth, Australia in November, 2014. The vision addresses opportunities at the forefront of wearable sensors and the genome+, exposome and behavome.October 22, 2014
There is a certain amount of false information regarding how infectious the Ebola virus is, see, for example, some of the statements by certain Congressman. Mathematical epidemiologists use something called “R naught”, the basic reproductive number, to quantify how many new cases arise, on average, from a given case. These can be thought of as new cases caused by infection between a sick individual and those who have had contact with that sick person.
The World Health Organization recently completed a study that found R naught to be around 1.7 (e.g. so a case on average gives rise to about 1.7 other cases). The challenge for infection control is to get R naught below the replacement rate, less than 1.0. In contrast, R naught for the flu is greater than 10. The Ebola virus is about 10 times less infectious than the flu.
Statistics Views – article “Arsenic Exposure, Bladder Cancer, and You: The Geostatistical Story You’ve Got to Read”October 8, 2014
Published in Statistics Views
Author: Lillian Pierson, P.E.
Since the dawn of time there’s been the haves and the have nots. Their stories precede them. While the moral and ethical viewpoints about economic disparity clash and rage, quietly in the backdrop, scientists are uncovering deeper truths about the extent to which we’re all affected.
Last year, researchers at the University of Exeter in the UK published a study that revealed a significant correlation between socio-economic status, body chemistry, and environmental exposure to harmful toxins. What they found is that the body of the average poor person has higher concentrations of lead, cadmium, and plastics, thought to be due to poor diet and a greater tendency for cigarette smoking among the poor. In contrast, rich people tend to have higher body chemistry concentrations of mercury, arsenic, and benzophenone-3, thought due to their greater consumption of shellfish and seafood, and the prevalent use of sunscreen among the middle-upper class. The study also confirmed what we’ve all known for quite some time, that chronic long-term exposure to chemical toxins usually causes adverse health effects.
But how, exactly, is our health affected? This question is central to the work of spatio-temporal epidemiologist, Dr. Pierre Goovaerts. Dr. Goovaerts is an established and long-respected leader in the fields of geostatistics and soil science, but he’s recently made a debut in the spatio-temporal epidemiology arena as well. Behind this recent career transition Goovaerts explains, “After 15 years devoted to the application of geostatistics to the characterization of contaminated sites, it seemed logical to wonder about the impact of this contamination on human health. After all, concern about human health should be one of the main drivers guiding the characterization and remediation of these sites.”September 21, 2014
The 43pl consortium operates a unit trust which facilitates participation in the CRCSI by a large number of small to medium sized enterprises. Founded in 2003, the CRC for Spatial Information (CRCSI) is a research organisation funded by Australia’s Cooperative Research Centre Program and by participant contributions.
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