Infant Mortality in South Africa – Distribution, Associations and Policy Implications, 2007: An Ecological Spatial Analysis

International Journal of Health GeographicsInternational Journal of Health Geographics, 10:61, Published 18 November 2011

Benn KD Sartorius, Kurt Sartorius, Tobias F Chirwa, and Sharon Fonn

“Background: Many sub-Saharan countries are confronted with persistently high levels of infant mortality because of the impact of a range of biological and social determinants. In particular, infant mortality has increased in sub-Saharan Africa in recent decades due to the HIV/AIDS epidemic. The geographic distribution of health problems and their relationship to potential risk factors can be invaluable for cost effective intervention planning. The objective of this paper is to determine and map the spatial nature of infant mortality in South Africa at a sub district level in order to inform policy intervention. In particular, the paper identifies and maps high risk clusters of infant mortality, as well as examines the impact of a range of determinants on infant mortality. A Bayesian approach is used to quantify the spatial risk of infant mortality, as well as significant associations (given spatial correlation between neighbouring areas) between infant mortality and a range of determinants. The most attributable determinants in each sub-district are calculated based on a combination of prevalence and model risk factor coefficient estimates. This integrated small area approach can be adapted and applied in other high burden settings to assist intervention planning and targeting.

Risk indicators with highest attributable fractions (impact) in significantly high risk infant mortality sub-districts, South Africa, 2007

Risk indicators with highest attributable fractions (impact) in significantly high risk infant mortality sub-districts, South Africa, 2007

“Results: Infant mortality remains high in South Africa with seemingly little reduction since previous estimates in the early 2000’s. Results showed marked geographical differences in infant mortality risk between provinces as well as within provinces as well as significantly higher risk in specific sub-districts and provinces. A number of determinants were found to have a significant adverse influence on infant mortality at the sub-district level. Following multivariable adjustment increasing maternal mortality, antenatal HIV prevalence, previous sibling mortality and male infant gender remained significantly associated with increased infant mortality risk. Of these antenatal HIV sero-prevalence, previous sibling mortality and maternal mortality were found to be the most attributable respectively.

“Conclusions: This study demonstrates the usefulness of advanced spatial analysis to both quantify excess infant mortality risk at the lowest administrative unit, as well as the use of Bayesian modelling to quantify determinant significance given spatial correlation. The “novel” integration of determinant prevalence at the sub-district and coefficient estimates to estimate attributable fractions further elucidates the “high impact” factors in particular areas and has considerable potential to be applied in other locations. The usefulness of the paper, therefore, not only suggests where to intervene geographically, but also what specific interventions policy makers should prioritize in order to reduce the infant mortality burden in specific administration areas.”

URISA Publishes 2011 Salary Survey for GIS Professionals

URISAURISA is pleased to announce the results of its latest salary survey for GIS professionals. The 2011 publication has been further expanded and includes a much wider-range of detailed information. Additions include more job titles and information pertaining to the increase/decrease of department size, professional certification, specific technical skills and soft skills and salary information. This is an ideal resource for both job seekers and also for those who are hiring GIS staff in 2012.

For a limited time, those who purchase the 2011 salary survey will also receive a copy of the 2007 salary survey (while quantities last). The publication is available on CD to URISA International members for $99 and Nonmembers for $199.

The 2011 Salary Survey addresses the following questions:

  • How have salary levels changed since 2007?
  • Have GIS departments increased in size?
  • Are more non-technical skills required?
  • What GIS software proficiencies are necessary?
  • What benefits do employers typically offer?
  • How long is the average workweek?
  • How has GIS certification impacted salaries?
  • Are GIS professionals actively pursuing continuing education?

Here’s a preview of information included in this year’s Salary Survey:

  • GISPs, on average, earned $10,000 more than non-GISPs
  • The average salary of survey respondents was $61,540 – an increase of 2.5%
  • GIS Managers saw a 3.8% increase in salary in 2010-2011 – from $67,302 to $69,842
  • Over 65% of respondents are employed within some level of government, from local to federal agencies
  • Most respondents to this survey hold GIS-related titles, with many possessing management responsibilities

The URISA Salary Survey debuted in 1998 to keep GIS and IT Professionals informed of the latest information related to salary, required skills, job advancement and professional certification. To purchase the URISA 2011 Salary Survey for GIS Professionals, or for additional information, please visit .

[Source: URISA press release]

GIS and Paleoanthropology: Incorporating New Approaches from the Geospatial Sciences in the Analysis of Primate and Human Evolution

Yearbook of Physical AnthropologyYearbook of Physical Anthropology, 2011, published online 19 November 2011

R.L. Anemone, G.C. Conroy, and C.W. Emerson

“The incorporation of research tools and analytical approaches from the geospatial sciences is a welcome trend for the study of primate and human evolution. The use of remote sensing (RS) imagery and geographic information systems (GIS) allows vertebrate paleontologists, paleoanthropologists, and functional morphologists to study fossil localities, landscapes, and individual specimens in new and innovative ways that recognize and analyze the spatial nature of much paleoanthropological data. Whether one is interested in locating and mapping fossiliferous rock units in the field, creating a searchable and georeferenced database to catalog fossil localities and specimens, or studying the functional morphology of fossil teeth, bones, or artifacts, the new geospatial sciences provide an essential element in modern paleoanthropological inquiry. In this article we review recent successful applications of RS and GIS within paleoanthropology and related fields and argue for the importance of these methods for the study of human evolution in the twenty first century. We argue that the time has come for inclusion of geospatial specialists in all interdisciplinary field research in paleoanthropology, and suggest some promising areas of development and application of the methods of geospatial science to the science of human evolution.”

Spatio-Temporal Analysis of Topic Popularity in Twitter

Cornell University LibraryCornell University Library,16 November 2011

Sebastien Ardon, Amitabha Bagchi, Anirban Mahanti, Amit Ruhela, Aaditeshwar Seth, Rudra Mohan Tripathy, and Sipat Triukose

“We present the first comprehensive characterization of the diffusion of ideas on Twitter, studying more than 4,000 topics that include both popular and less popular topics. On a data set containing approximately 10 million users and a comprehensive scraping of all the tweets posted by these users between June 2009 and August 2009 (approximately 200 million tweets), we perform a rigorous temporal and spatial analysis, investigating the time-evolving properties of the subgraphs formed by the users discussing each topic. We focus on two different notions of the spatial: the network topology formed by follower-following links on Twitter, and the geospatial location of the users.

Evolving graph conductance

Evolving graph conductance.

“We investigate the effect of initiators on the popularity of topics and find that users with a high number of followers have a strong impact on popularity. We deduce that topics become popular when disjoint clusters of users discussing them begin to merge and form one giant component that grows to cover a significant fraction of the network. Our geospatial analysis shows that highly popular topics are those that cross regional boundaries aggressively.”

Spatial Giants Form Landmark Industry Partnership

Esri AustraliaTwo heavyweights of Australia’s $2.1 billion geospatial industry have joined forces in an industry-first partnership designed to expand spatial technology into new, ‘untapped’ markets.

Leading Geographic Information System (GIS) specialists Esri Australia and the nation’s peak spatial industry body the Surveying and Spatial Sciences Institute (SSSI) announced the alliance today at the International Surveying and Spatial Sciences Conference (SSSC) in New Zealand.

The move follows a record year of growth for the spatial industry, which saw GIS technology play a vital role in emergency response during the Queensland flood and cyclone disasters; underpin think tank forums for the Committee for Economic Development (CEDA); and expand its footprint in sectors such as insurance, utilities, mining and resources.

Esri Australia Managing Director Brett Bundock said together the spatial industry mainstays would facilitate a series of strategic round table discussions with business leaders from sectors where GIS is not yet established.

“Our goal here is to pave the way for an expansion and use of the science into non-traditional markets,” Mr Bundock said.

“Following the public role of GIS during this year’s flood crisis in Queensland, a number of sectors are now looking with great interest to how the technology can strengthen their decision-making.

“Esri Australia has been a member of the spatial industry for over 34 years – this partnership with SSSI gives us the opportunity to drive the sector forward, taking with us a membership base that has also contributed significantly to the industry’s success.

“We are bringing together the Australian spatial industry’s chief thought leaders to not only determine ways we can foster growth in traditional markets – but also how we can continue to forge a strong position for the technology in emerging sectors, like agribusiness, health and engineering.

“GIS is a game-changing technology – in any industry – and through research, round-table discussions and promotional forums, we intend to build a deeper understanding of that potential across the broader Australian business community.”

The alliance is expected to drive new training and educational opportunities in the local market, andsee the production of joint industry reports and in-depth analysis of challenges facing the spatial industry.

SSSI CEO Roger Buckley said the partnership was the first of its kind entered into by the peak industry body, whose membership includes hundreds of Australia’s leading spatial technology professionals.

“This is a unique case of two market leaders sharing data, expertise and market intel to champion geospatial technology,” Mr Buckley said.

“It’s a natural pairing – Esri Australia has the country’s premier spatial technology and know-how, while we represent hundreds of Australia’s most highly regarded cartographers, remote sensors, land surveyors, photogrammetrists and other spatial professionals.

“Together, we have an unmatched ability to drive growth in the spatial sector – and support organisations around the country in their use of location intelligence.

“There are many businesses who don’t yet understand where spatial technology can fit within their organisation and through this partnership, we’re here to say ‘let us show you’.”

[Source: Esri Australia press release]

A Comparison of Multisensor Integration Methods for Land Cover Classification in the Brazilian Amazon

GIScience & Remote SensingGIScience & Remote Sensing, Volume 48, Number 3 / July-September 2011

Dengsheng Lu, Guiying Li, Emilio Moran, Luciano Dutra, and Mateus Batistella

“Many data fusion methods are available, but it is poorly understood which fusion method is suitable for integrating Landsat Thematic Mapper (TM) and radar data for land cover classification. This research explores the integration of Landsat TM and radar images (i.e., ALOS PALSAR L-band and RADARSAT-2 C-band) for land cover classification in a moist tropical region of the Brazilian Amazon. Different data fusion methods—principal component analysis (PCA), wavelet-merging technique (Wavelet), high-pass filter resolution-merging (HPF), and normalized multiplication (NMM)—were explored. Land cover classification was conducted with maximum likelihood classification based on different scenarios. This research indicates that individual radar data yield much poorer land cover classifications than TM data, and PALSAR L-band data perform relatively better than RADARSAT-2 C-band data. Compared to the TM data, the Wavelet multisensor fusion improved overall classification by 3.3%-5.7%, HPF performed similarly, but PCA and NMM reduced overall classification accuracy by 5.1%-6.1% and 7.6%-12.7%, respectively. Different polarization options, such as HH and HV, work similarly when used in data fusion. This research underscores the importance of selecting a suitable data fusion method that can preserve spectral fidelity while improving spatial resolution.”

Multiscale Analyses of Mammal Species Composition – Environment Relationship in the Contiguous USA

PLoS ONEPLoS ONE 6(9): e25440, Published 27 September 2011

Rafi Kent, Avi Bar-Massada, and Yohay Carmel

“Relationships between species composition and its environmental determinants are a basic objective of ecology. Such relationships are scale dependent, and predictors of species composition typically include variables such as climate, topographic, historical legacies, land uses, human population levels, and random processes. Our objective was to quantify the effect of environmental determinants on U.S. mammal composition at various spatial scales.

 Explained variance rates of individual environmental variables in mammal species composition: a) climatic variables; b) topographic variables and c) LULC variables.

Explained variance rates of individual environmental variables in mammal species composition: a) climatic variables; b) topographic variables and c) LULC variables.

“We found that climate was the predominant factor affecting species composition, and its relative impact increased in correlation with the increase of the spatial scale. Another factor affecting species composition is land-use–land-cover. Our findings showed that its impact decreased as the spatial scale increased. We provide quantitative indication of highly significant effect of climate and land-use–land-cover variables on mammal composition at multiple scales.”

Targeting Pediatric Pedestrian Injury Prevention Efforts: Teasing the Information Through Spatial Analysis

The Journal of Trauma Journal of Trauma-Injury Infection & Critical Care, 71(5):S511-S516, November 2011

Statter, Mindy; Schuble, Todd; Harris-Rosado, Michele; Liu, Donald; and Quinlan, Kyran

“Background: Pediatric pedestrian injuries remain a major cause of childhood death, hospitalization, and disability. To target injury prevention efforts, it is imperative to identify those children at risk. Racial disparities have been noted in the rates of pediatric pedestrian injury and death. Children from low-income families living in dense, urban residential neighborhoods have a higher risk of sustaining pedestrian injury. Geographic information systems (GIS) analysis of associated community factors such as child population density and median income may offer insights into prevention.

“Methods: Using trauma registry E-codes for pedestrian motor vehicle crashes, children younger than 16 years were identified, who received acute care and were hospitalized at the University of Chicago Medical Center, a Level I pediatric trauma center, after being struck by a motor vehicle from 2002 to 2009. By retrospective chart review and review of the Emergency Medical Services run sheets, demographic data and details of the crash site were collected. Crash sites were aggregated on a block by block basis. A “hot spot” analysis was performed to localize clusters of injury events. Using Gi* statistical method, spatial clusters were identified at different confidence intervals using a fixed distance band of 400 m (∼¼ mile). Maps were generated using GIS with 2000 census data to evaluate race, employment, income, density of public and private schools, and density of children living in the neighborhoods surrounding our medical center where crash sites were identified. Spatial correlation is used to identify statistically significant locations.

All crashes, 2002-2009.

All crashes, 2002-2009.

“Results: There were 3,521 children admitted to the University of Chicago Medical Center for traumatic injuries from 2002 to 2009; 27.7% (974) of these children sustained injuries in pedestrian motor vehicle injuries. From 2002 to 2009, there were a total of 106 traumatic deaths, of which 29 (27.4%) were due to pedestrian motor vehicle crashes. Pediatric pedestrian motor vehicle crash sites occurred predominantly within low-income, predominantly African-American neighborhoods. A lower prevalence of crash sites was observed in the predominantly higher income, non–African-American neighborhoods.

“Conclusions: Spatial analysis using GIS identified associations between pediatric pedestrian motor vehicle crash sites and the neighborhoods served by our pediatric trauma center. Pediatric pedestrian motor vehicle crash sites occurred predominantly within low-income, African-American neighborhoods. The disparity in prevalence of crash sites is somewhat attributable to the lower density of children living in the predominantly higher income, non-African-American neighborhoods, including the community immediately around our hospital. Traffic volume patterns, as a denominator of these injury events, remain to be studied.”

Maternity Ward Closures in Philadelphia: Using GIS to Measure Disruptions in Essential Health Services

Journal of Map & Geography LibrariesJournal of Map & Geography Libraries, Volume 7, Issue 3, 2011

Sarah Cordivano

“GIS is a robust analysis tool capable of contributing to a more comprehensive study of public health issues than was possible using traditional methods. By analyzing the issue of maternity ward closures in Philadelphia, this paper explores the proper methods for utilizing, processing, and analyzing sensitive public health data.

Evolution of density of Philadelphia residential births during the period of closures including open and closed facilities.

Evolution of density of Philadelphia residential births during the period of closures including open and closed facilities.

“These analytical methods are underutilized in public health research due to widespread unfamiliarity with GIS technology as well as difficulty in accessing accurate data. Understanding and adopting GIS technology is valuable to the assessment, allocation, and delivery of health care services.”

Spatial and Temporal Relationships among NDVI, Climate Factors, and Land Cover Changes in Northeast Asia from 1982 to 2009

GIScience & Remote Sensing

GIScience & Remote Sensing, Volume 48, Number 3 / July-September 2011

Yang Liu, Xiufeng Wang, Meng Guo, Hiroshi Tani, Nobuhiro Matsuoka and Shinji Matsumura

“This study uses a multiple linear regression method to composite standard Normalized Difference Vegetation Index (NDVI) time series (1982-2009) consisting of three kinds of satellite NDVI data (AVHRR, SPOT, and MODIS). This dataset was combined with climate data and land cover maps to analyze growing season (June to September) NDVI trends in northeast Asia. In combination with climate zones, NDVI changes that are influenced by climate factors and land cover changes were also evaluated. This study revealed that the vegetation cover in the arid, western regions of northeast Asia is strongly influenced by precipitation, and with increasing precipitation, NDVI values become less influenced by precipitation. Spatial changes in the NDVI as influenced by temperature in this region are less obvious. Land cover dynamics also influence NDVI changes in different climate zones, especially for bare ground, cropland, and grassland. Future research should also incorporate higher-spatial-resolution data as well as other data types (such as greenhouse gas data) to further evaluate the mechanisms through which these factors interact.”