https://geospatialhealth.net/index.php/gh/issue/feed Geospatial Health 2018-08-17T16:56:23+02:00 Francesca Baccino francesca.baccino@pagepress.org Open Journal Systems <p><strong>Geospatial Health</strong> is the official journal of the International Society of Geospatial Health (<a href="http://www.gnosisgis.org/">www.GnosisGIS.org</a>).</p> <p>The journal was founded in 2006 at the University of Naples Federico II by Giuseppe Cringoli, John B. Malone, Robert Bergquist and Laura Rinaldi. The focus of the journal is on all aspects of the application of geographical information systems, remote sensing, global positioning systems, spatial statistics and other geospatial tools in human and veterinary health. The journal publishes two issues per year.</p> https://geospatialhealth.net/index.php/gh/article/view/699 Vector-borne diseases in a warmer world: Will they stay or will they go? 2018-08-17T16:56:21+02:00 Robert Bergquist editor@geospatialhealth.net Anna-Sofie Stensgaard asstensgaard@snm.ku.dk Laura Rinaldi lrinaldi@unina.it Not available. 2018-05-07T17:15:37+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/577 Access to dialysis services: A systematic mapping review based on geographical information systems 2018-08-17T16:56:23+02:00 Benyamin Hoseini binyamin.hoseini@gmail.com Nasser Bagheri nasser.bagheri@anu.edu.au Behzad Kiani kiani.behzad@gmail.com Amirabbas Azizi AziziAA@mums.ac.ir Hamed Tabesh TabeshH@mums.ac.ir Mahmood Tara smtara@gmail.com Equitable access to healthcare services constitutes one of the leading priorities of healthcare provision and access to dialysis services (ADS) has an essential impact on patients depending on renal dialysis. The many existing GIS-based ADS evaluations include various spatial and non-spatial factors affecting ADS. We systematically mapped and reviewed the available literature with reference to this area identifying gaps in current GIS-based ADS measurements and developing recommendations for future studies. A threestep, systematic mapping review of the available GIS-related evidence in PubMed, Embase, Web of science, Scopus, Science Direct and IEEE Xplore was performed in May 2016 and the information collected updated October 2017 by two independent selection processes. The quality of the studies was assessed using an informal, mixed-approach scoring system. Out of 1119 literature references identified, 36 were identified and used for final review after removal of duplicates, study screenings and applying inclusion/exclusion criteria. Given the contents of the selected studies, three study groups were identified and 41 factors with potential effects on ADS determined. These studies mainly addressed the potential and/or spatial aspects of ADS. Our systematic mapping review of the evidence revealed that current GIS-based measures of ADS tend to calculate potential ADS instead of a realized one. It was also noted that listed factors affecting ADS were mainly nonspatial bringing forth the hypothesis that designing an integrated ADS index could possibly produce better ADS score than those currently advocated. Some primary and secondary research suggestions are made and a list of recommendations offered. 2018-05-07T17:15:37+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/587 Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search 2018-08-17T16:56:22+02:00 Carlos Mena cmena@utalca.cl Cesar Sepúlveda csepulveda10@alumnos.utalca.cl Eduardo Fuentes edfuentes@utalca.cl Yony Ormazábal yormazabal@utalca.cl Iván Palomo ipalomo@utalca.cl Cardiovascular diseases (CVDs) are the primary cause of death and disability in de world, and the detection of populations at risk as well as localization of vulnerable areas is essential for adequate epidemiological management. Techniques developed for spatial analysis, among them geographical information systems and spatial statistics, such as cluster detection and spatial correlation, are useful for the study of the distribution of the CVDs. These techniques, enabling recognition of events at different geographical levels of study (<em>e.g.</em>, rural, deprived neighbourhoods, <em>etc.</em>), make it possible to relate CVDs to factors present in the immediate environment. The systemic literature presented here shows that this group of diseases is clustered with regard to incidence, mortality and hospitalization as well as obesity, smoking, increased glycated haemoglobin levels, hypertension physical activity and age. In addition, acquired variables such as income, residency (rural or urban) and education, contribute to CVD clustering. Both local cluster detection and spatial regression techniques give statistical weight to the findings providing valuable information that can influence response mechanisms in the health services by indicating locations in need of intervention and assignment of available resources. 2018-05-07T17:15:37+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/608 Prevalence of hypertension in Thailand: Hotspot clustering detected by spatial analysis 2018-08-17T16:56:18+02:00 Wongsa Laohasiriwong drwongsa@gmail.com Nattapong Puttanapong nattapong@econ.tu.ac.th Atthawit Singsalasang atthawit.s@kkumail.com Spatial pattern detection can be a useful tool for understanding the geographical distribution of hypertension (HT). The aim of this study was to apply the technique of local indicators of spatial association statistics to examine the spatial patterns of HT in the 76 provinces of Thailand. Previous studies have demonstrated that socioeconomic status (SES), economic growth, population density and urbanization have effects on the occurrence of disease. Research has suggested that night-time light (NTL) can be used as a proxy for a number of variables, including urbanization, density, economic growth and SES. To date, there has not been any study on spatial patterns of HT and there is no information on how NTL might correlate with HT. Therefore, this study has investigated NTL as a parameter for detection of hotspots of HT in Thailand. It was found that HT clusters occurred in Bangkok and in metropolitan areas. In addition, significantly low-rate clusters were seen in some provinces in the Northeast and also in southern provinces. These findings should facilitate control and prevention of HT and, therefore, serve as support for researchers, decision-makers, academics and public health officials to propose more sound and effective strategies for the control of HT in Thailand and elsewhere. 2018-05-07T17:15:38+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/527 Spatial electromagnetic field intensity modelling of global system for mobile communication base stations in the Istanbul Technical University Ayazaga campus area 2018-08-17T16:56:20+02:00 Kubra Boz k.bilginol@gmail.com Hayri Hakan Denli denli@itu.edu.tr The rapid development of the global system for mobile communication services and the consequent increased electromagnetic field (EMF) exposure to the human body have generated debate on the potential danger with respect to human health. The many research studies focused on this subject have, however, not provided any certain evidence about harmful consequences due to mobile communication systems. On the other hand, there are still views suggesting such exposure might affect the human body in different ways. To reduce such effects to a minimum, the International Commission on Non-Ionizing Radiation Protection (ICNIRP) has declared boundary values for the energy released by the base stations, which are the main source of the electromagnetic fields. These values are accepted by many countries in various parts of the world. The aim of this study was to create EMF intensity maps for the area covered by Istanbul Technical University (ITU) and find areas of potential risk with regard to health considering the current situation and future trends. In this study, the field intensities of electromagnetic signals issued at the frequencies of 900 and 1800 MHz were measured in V/m at 29 pre-specified survey points using a spectrum analyzer (Spectran HF-6065). Geographic information systems and spatial interpolation techniques were used to produce EMF intensity maps. Three different spatial interpolation methods, minimum mean square error, Radial Basis and Empirical Bayesian Kriging, were compared. The results were geographically analyzed and the measurements expressed as <em>heat maps</em> covering the study area. Using these maps, the values measured were compared with the EMF intensity standards issued by ICNIRP. The results showed that the exposure levels to the EMF intensities were all within the ICNIRP limits at the ITU study area. However, since the EMF intensity level with respect to human health is not known, it is not possible to confirm if these levels are safe or not. 2018-05-07T17:15:38+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/653 Measuring high-density built environment for public health research: Uncertainty with respect to data, indicator design and spatial scale 2018-08-17T16:56:16+02:00 Guibo Sun gbsun@hku.hk Chris Webster xiaohu@smart.mit.edu Michael Y. Ni xiaohu@smart.mit.edu Xiaohu Zhang xiaohu@smart.mit.edu Uncertainty with respect to built environment (BE) data collection, measure conceptualization and spatial scales is evident in urban health research, but most findings are from relatively lowdensity contexts. We selected Hong Kong, an iconic high-density city, as the study area as limited research has been conducted on uncertainty in such areas. We used geocoded home addresses (n=5732) from a large population-based cohort in Hong Kong to extract BE measures for the participants’ place of residence based on an internationally recognized BE framework. Variability of the measures was mapped and Spearman’s rank correlation calculated to assess how well the relationships among indicators are preserved across variables and spatial scales. We found extreme variations and uncertainties for the 180 measures collected using comprehensive data and advanced geographic information systems modelling techniques. We highlight the implications of methodological selection and spatial scales of the measures. The results suggest that more robust information regarding urban health research in high-density city would emerge if greater consideration were given to BE data, design methods and spatial scales of the BE measures. 2018-05-07T17:15:38+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/542 Spatial association of public sports facilities with body mass index in Korea 2018-08-17T16:56:15+02:00 Eun Jin Han sohns@yonsei.ac.kr Kiyeon Kang kkyrldus@hanmail.net So Young Sohn sohns@yonsei.ac.kr Governments and also local councils create and enforce their own regional public health care plans for the problem of overweight and obesity in the population. Public sports facilities can help these plans. In this paper, we investigated the contribution of public sports facilities to the reduction of the obesity of local residents. We used the data obtained from the Fifth Korea National Health and Nutrition Examination Surveys; and measured the degree of obesity using body mass index (BMI). We conducted various spatial regression analyses including the global Moran’s <em>I</em> test and local indicators of spatial autocorrelation analysis finding that there exists spatial dependence in the error term of spatial regression model for BMI. However, we also observed that the number of local public sports facilities is not significantly related to local BMI. This result can be caused by the low utilization ratio and an unbalanced spatial distribution of local public sports facilities. Based on our findings, we suggest that local councils need to improve the quality of public sports facilities encouraging the establishment of preferred types of pubic sports facilities. 2018-05-07T17:15:39+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/629 Report-back for geo-referenced environmental data: A case study on personal monitoring of temperature in outdoor workers 2018-08-17T16:56:14+02:00 Laura Thompson thompsonlk1@appstate.edu Maggie Sugg kovachmm@appstate.edu Jennifer Runkle jrrunkle@ncsu.edu Few studies have evaluated the benefits of reporting back participatory environmental monitoring results, particularly regarding participant motivation toward behavioural modification concerning workplace heat exposure. This study evaluated the individual data report-back for geo-located environmental temperature and time activity patterns in grounds maintenance crews in three geographic regions across the South-eastern United States. Surveys collected information on worker interpretation of their results and intended action(s) to reduce heat exposure. Worker response was highly positive, especially among more experienced workers who expressed a greater willingness to modify personal behaviour to reduce heat stress. Individual-level report-back of environmental data is a powerful tool for individuals to understand and act on their personal exposure to heat. 2018-05-07T17:15:39+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/655 Spatial heterogeneity of quality, use and spending on medicare for the elderly 2018-08-17T16:56:14+02:00 Felipa de Mello-Sampayo fdmso@iscte.pt The spatial variation of the relations between Medicare spending (MS), use and quality in the United States was investigated employing spatial regression. A focus of the study was whether, and to what extent, MS and use vary by service type. Employing different spatial regression designs based on Medicare regional data, the impact of the heterogeneous spatial effects of hospital readmissions on MS for the elderly at the aggregate level was examined. The results were followed up by investigation whether the effects of hospital readmissions are heterogeneous with regard to service type. It was found that poor quality indicators lead to increased MS at the aggregate level and thus higher costs per beneficiary, and that the quality effects are heterogeneous with variable impacts, both spatially and by type of medical service. The results shed new light on the relationship between quality and MS highlighting the pitfalls of global averaging models that hide the reality of a highly diversified and spatially stratified country. Reducing payments to high-spending areas and increasing payments to low-spending areas should reduce spending variability but the quality indicators of care become ambiguous and not easy to interpret. 2018-05-07T17:15:39+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/594 Understanding needs and barriers to using geospatial tools for public health policymaking in China 2018-08-17T16:56:13+02:00 Dohyeong Kim dohyeong.kim@utdallas.edu Yingyuan Zhang yxz094920@utdallas.edu Chang Kil Lee changkillee@incheon.ac.kr Despite growing popularity of using geographical information systems and geospatial tools in public health fields, these tools are only rarely implemented in health policy management in China. This study examines the barriers that could prevent policy-makers from applying such tools to actual managerial processes related to public health problems that could be assisted by such approaches, <em>e.g.</em> evidence-based policy-making. A questionnaire-based survey of 127 health-related experts and other stakeholders in China revealed that there is a consensus on the needs and demands for the use of geospatial tools, which shows that there is a more unified opinion on the matter than so far reported. Respondents pointed to lack of communication and collaboration among stakeholders as the most significant barrier to the implementation of geospatial tools. Comparison of survey results to those emanating from a similar study in Bangladesh revealed different priorities concerning the use of geospatial tools between the two countries. In addition, the follow-up in-depth interviews highlighted the political culture specific to China as a critical barrier to adopting new tools in policy development. Other barriers included concerns over the limited awareness of the availability of advanced geospatial tools. Taken together, these findings can facilitate a better understanding among policy-makers and practitioners of the challenges and opportunities for widespread adoption and implementation of a geospatial approach to public health policy-making in China. 2018-05-07T17:15:40+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/616 Detection of spatial aggregation of cases of cancer from data on patients and health centres contained in the Minimum Basic Data Set 2018-08-17T16:56:12+02:00 Pablo Fernández-Navarro pfernandezn@isciii.es Jose-Miguel Sanz-Anquela jmsanz.uah@gmail.com Angel Sánchez Pinilla angel.sanchez@madrid.org Rosario Arenas Mayorga charo.arenas@madrid.org Carmen Salido-Campos carmen.salido@salud.madrid.org Gonzalo López-Abente glabente@isciii.es The feasibility of the Minimum Basic Data Set (MBDS) as a tool in cancer research was explored monitoring its incidence through the detection of spatial clusters. Case-control studies based on MBDS and marked point process were carried out with the focus on the residence of patients from the Prince of Asturias University Hospital in Alcalá de Henares (Madrid, Spain). Patients older than 39 years with diagnoses of stomach, colorectal, lung, breast, prostate, bladder and kidney cancer, melanoma and haematological tumours were selected. Geocoding of the residence address of the cases was done by locating them in the continuous population roll provided by the Madrid Statistical Institute and extracting the coordinates. The geocoded control group was a random sample of 10 controls per case matched by frequency of age and sex. To assess case clusters, differences in Ripley K functions between cases and controls were calculated. The spatial location of clusters was explored by investigating <em>spatial intensity</em> and its ratio between cases and controls. Results suggest the existence of an aggregation of cancers with a common risk factor such as tobacco smoking (lung, bladder and kidney cancers). These clusters were located in an urban area with high socioeconomic deprivation. The feasibility of designing and carrying out case-control studies from the MBDS is shown and we conclude that MBDS can be a useful epidemiological tool for cancer surveillance and identification of risk factors through case-control spatial point process studies. 2018-05-07T17:15:40+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/622 Geographic access to radiation therapy facilities and disparities of early-stage breast cancer treatment 2018-08-17T16:56:11+02:00 Yan Lin yanlin@unm.edu Michael C. Wimberly Michael.Wimberly@sdstate.edu Patricia Da Rosa Patricia.DaRosa@sdstate.edu Joseph Hoover JoHoover@salud.unm.edu William F. Athas WAthas@salud.unm.edu Few studies of breast cancer treatment have focused on the Northern Plains of the United States, an area with a high mastectomy rate. This study examined the association between geographic access to radiation therapy facilities and receipt of breast cancer treatments among early-stage breast cancer patients in South Dakota. Based on 4,209 early-stage breast cancer patients diagnosed between 2001 and 2012 in South Dakota, the study measured geographic proximity to radiation therapy facilities using the shortest travel time for patients to the closest radiation therapy facility. Two-level logistic regression models were used to estimate for early stage cases i) the odds of mastectomy versus breast conserving surgery (BCS); ii) the odds of not receiving radiation therapy after BCS versus receiving follow-up radiation therapy. Covariates included race/ethnicity, age at diagnosis, tumour grade, tumour sequence, year of diagnosis, census tract-level poverty rate and urban/rural residence. The spatial scan statistic method was used to identify geographic areas with significantly higher likelihood of experiencing mastectomy. The study found that geographic accessibility to radiation therapy facilities was negatively associated with the likelihood of receiving mastectomy after adjustment for other covariates, but not associated with radiation therapy use among patients receiving BCS. Compared with patients travelling less than 30 minutes to a radiation therapy facility, patients travelling more than 90 minutes were about 1.5 times more likely to receive mastectomy (odds ratio, 1.51; 95% confidence interval, 1.08-2.11) and patients travelling more than 120 minutes were 1.7 times more likely to receive mastectomy (odds ratio, 1.70; 95% confidence interval, 1.19-2.42). The study also identified a statistically significant cluster of patients receiving mastectomy who were located in south-eastern South Dakota, after adjustment for other factors. Because geographic proximity to treatment facilities plays an important role on the treatment for early-stage breast cancer patients, this study has important implications for developing targeted intervention to reduce disparities in breast cancer treatment in South Dakota. 2018-05-07T17:15:41+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/613 Correlation analysis of air pollutant index levels and dengue cases across five different zones in Selangor, Malaysia 2018-08-17T16:56:12+02:00 Loshini Thiruchelvam losht_88@yahoo.com Sarat C. Dass saratcdass@gmail.com Rafdzah Zaki saratcdass@gmail.com Abqariyah Yahya saratcdass@gmail.com Vijanth S. Asirvadam saratcdass@gmail.com This study investigated the potential relationship between dengue cases and air quality – as measured by the Air Pollution Index (API) for five zones in the state of Selangor, Malaysia. Dengue case patterns can be learned using prediction models based on feedback (lagged terms). However, the question whether air quality affects dengue cases is still not thoroughly investigated based on such feedback models. This work developed dengue prediction models using the autoregressive integrated moving average (ARIMA) and ARIMA with an exogeneous variable (ARIMAX) time series methodologies with API as the exogeneous variable. The Box Jenkins approach based on maximum likelihood was used for analysis as it gives effective model estimates and prediction. Three stages of model comparison were carried out for each zone: first with ARIMA models without API, then ARIMAX models with API data from the API station for that zone and finally, ARIMAX models with API data from the zone and spatially neighbouring zones. Bayesian Information Criterion (BIC) gives goodness-of-fit versus parsimony comparisons between all elicited models. Our study found that ARIMA models, with the lowest BIC value, outperformed the rest in all five zones. The BIC values for the zone of Kuala Selangor were –800.66, –796.22, and –790.5229, respectively, for ARIMA only, ARIMAX with single API component and ARIMAX with API components from its zone and spatially neighbouring zones. Therefore, we concluded that API levels, either temporally for each zone or spatio- temporally based on neighbouring zones, do not have a significant effect on dengue cases. 2018-05-07T17:15:41+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/624 Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution 2018-08-17T16:56:09+02:00 Yazmin Alcala-Canto yazmin@unam.mx Juan Antonio Figueroa-Castillo yazmin@unam.mx Froylán Ibarra-Velarde yazmin@unam.mx Yolanda Vera-Montenegro yazmin@unam.mx María Eugenia Cervantes-Valencia yazmin@unam.mx Abdelfattah Z.M. Salem yazmin@unam.mx Jorge Alfredo Cuéllar-Ordaz yazmin@unam.mx The tick genus <em>Ripicephalus (Boophilus)</em>, particularly <em>R. microplus</em>, is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of <em>Rhipicephalus </em>spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks’ distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of <em>Rhipicephalus</em> spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that <em>Rhipicephalus</em> has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using <em>Rhipicephalus</em> records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies. 2018-05-07T17:15:42+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/641 Validation of a spatial liver fluke model under field conditions in Ireland 2018-08-17T16:56:08+02:00 Amalia Naranjo Lucena amalia.naranjo-lucena@ucdconnect.ie María Pía Munita Corbalán Maria.MunitaCorbalan@teagasc.ie Ana María Martínez-Ibeas anamaria_mi@hotmail.com Guy McGrath guy.mcgrath@ucd.ie Riona Sayers Riona.Sayers@teagasc.ie Grace Mulcahy grace.mulcahy@ucd.ie Annetta Zintl annetta.zintl@ucd.ie <em>Fasciola hepatica</em> is the causative agent of fasciolosis, a global disease of a wide range of mammals, particularly sheep and cattle. Liver fluke infection causes annual losses estimated at around €2.5 billion to livestock and food industries worldwide. Various models have been developed to define risk factors and predict exposure to this liver fluke in ruminants in European countries, most of them based exclusively on data from dairy herds. The aim of this study was to validate a published theoretical baseline risk map of liver fluke exposure and cluster maps in Ireland, by including further explanatory variables and additional herd types that are spatially more widespread. Three approaches were employed: i) comparison of predicted and actual exposure; ii) comparison of cluster distribution of hotspots and coldspots; and iii) development of a new model to compare predicted spatial distribution and risk factors. Based on new survey data, the published baseline predictive map was found to have a sensitivity of 94.7%, a specificity of 5%, a positive predictive value of 60% and a negative predictive value of 38.2%. In agreement with the original model, our validation highlighted temperature and rainfall among the main risk factors. In addition, we identified vegetation indices as important risk factors. Both the previously published and our new model predict that exposure to <em>Fasciola</em> is higher in the western parts of Ireland. However, foci of high probability do not match completely, nor do the location of clusters of hotspots and coldspots. 2018-05-07T17:15:43+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/642 Geographical distribution and spatio-temporal patterns of hospitalization due to dengue infection at a leading specialist hospital in Malaysia 2018-08-17T16:56:07+02:00 Gary K.K. Low garylowkk@utar.edu.my Panayoti Papapreponis garylowkk@utar.edu.my Ridzuan M. Isa garylowkk@utar.edu.my Seng Chiew Gan garylowkk@utar.edu.my Hui Yee Chee garylowkk@utar.edu.my Kian Keong Te garylowkk@utar.edu.my Nadia M. Hatta garylowkk@utar.edu.my Increasing numbers of dengue infection worldwide have led to a rise in deaths due to complications caused by this disease. We present here a cross-sectional study of dengue patients who attended the Emergency and Trauma Department of Ampang Hospital, one of Malaysia’s leading specialist hospitals. The objective was to search for potential clustering of severe dengue, in space and/or time, among the annual admissions with the secondary objective to describe the spatio-temporal pattern of all dengue cases admitted to this hospital. The dengue status of the patients was confirmed serologically with the geographic location of the patients determined by residency, but not more specific than the street level. A total of 1165 dengue patients were included in the analysis using SaTScan software. The mean age of these patients was 27.8 years, with a standard deviation of 14.2 years and an age range from 1 to 77 years, among whom 54 (4.6%) were cases of severe dengue. A cluster of general dengue cases was identified occurring from October to December in the study year of 2015 but the inclusion of severe dengue in that cluster was not statistically significant (P=0.862). The standardized incidence ratio was 1.51. General presence of dengue cases was, however, detected to be concentrated at the end of the year, which should be useful for hospital planning and management if this pattern holds. 2018-05-07T17:15:44+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/654 Urban environmental clustering to assess the spatial dynamics of Aedes aegypti breeding sites 2018-08-17T16:56:06+02:00 Guillermo Albrieu-Llinás guillermoalbrieu@gmail.com Manuel O. Espinosa mespinosa@mundosano.org Agustín Quaglia quaglia.agu@gmail.com Marcelo Abril mabril@mundosano.org Carlos Marcelo Scavuzzo scavuzzo@conae.gov.ar The identification of <em>Aedes aegypti</em> breeding hotspots in urban areas is crucial for the rational design of control strategies against this disease vector. Remote sensing and geographic information systems offer valuable tools for mapping habitat suitability of a given area. However, predicting species occurrences by means of probability distribution maps based on transversal entomological surveys has limited utility for local authorities. The aim of the present study was to carefully examine the temporal evolution of the number of houses infested with immature stages of <em>Ae. aegypti</em> in each individual neighbourhood and to explore the value of producing environmental clusters generated with information provided by remotely sensed variables to explain the observed differential temporal behaviour. Entomological surveys were conducted between 2011 and 2013 throughout a small town in Argentina registering the number of houses with containers harbouring immature stages of <em>Ae. aegypti</em>. A SPOT 5 satellite image was used to obtain land cover variables, which were subsequently submitted to k-means partitioning for grouping neighbourhoods into four environmental clusters. Finally, a generalized linear model was fitted showing that the number of houses found to be positive for <em>Ae. aegypti</em> was jointly affected by the interaction between environmental clusters and the year of sampling. Moreover, the number of positive houses in one of the clusters was 9.5 times higher (P&lt;0.005, SE=0.37) in 2013 than in 2012, but we did not observe any other statistically significant increases. 2018-05-07T17:15:44+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/644 Spatial prediction of the risk of exposure to Echinococcus spp. among schoolchildren and dogs in Ningxia Hui Autonomous Region, People’s Republic of China 2018-08-17T16:56:06+02:00 Angela M. Cadavid Restrepo angela.cadavid@anu.edu.au Yu Rong Yang Yurong.Yang@qimrberghofer.edu.au Donald P. McManus Don.McManus@qimrberghofer.edu.au Darren J. Gray u5624503@uds.anu.edu.au Tamsin S. Barnes t.barnes@uq.edu.au Gail M. Williams g.williams@sph.uq.edu.au Ricardo J. Soares Magalhães r.magalhaes@uq.edu.au Archie C.A. Clements director.rsph@anu.edu.au The geographical distribution of <em>Echinococcus</em> spp. infections in Ningxia Hui Autonomous Region (NHAR) has been reported to be expanding in response to environmental change. The aim of the present study was to predict and compare the spatial distribution of human seropositivity for <em>Echinococcus granulosus</em> and <em>Echinococcus multilocularis</em> and infections with these parasites in dogs in four counties in the south of NHAR to identify communities where targeted prevention and control efforts are required. Predicted seroprevalence of <em>E. granulosus</em> in schoolchildren and <em>E. granulosus</em> infections in dogs concurred spatially, whereas predicted seroprevalence of <em>E. multilocularis</em> in schoolchildren and<em> E. multilocularis</em> infections in dogs differed spatially. Enhanced vegetation index was significantly associated with <em>E. multilocularis</em> seropositivity among schoolchildren, and infections with <em>E. granulosus</em> and <em>E. multilocularis</em> in dogs. A positive association was also found between dog infection with <em>E. granulosus</em> and cultivated land, and a negative association between human seropositivity for <em>E. granulosus</em> and bare-land/artificial surfaces. The findings of this study support the importance of land cover and climatic variables in determining habitat suitability for <em>Echinococcus</em> spp. infections, and suggest that definitive hosts other than dogs (<em>e.g</em>. foxes) are important in defining the geographical risk of human seropositivity for <em>E. multilocularis</em> in NHAR. 2018-05-07T17:15:44+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/660 Mapping malaria risk using geographic information systems and remote sensing: The case of Bahir Dar City, Ethiopia 2018-08-17T16:56:05+02:00 Amare Sewnet Minale amare1974@gmail.com Kalkidan Alemu amare1974@gmail.com The main objective of this study was to develop a malaria risk map for Bahir Dar City, Amhara, which is situated south of Lake Tana on the Ethiopian plateau. Rainfall, temperature, altitude, slope and land use/land cover (LULC), as well as proximity measures to lake, river and health facilities, were investigated using remote sensing and geographical information systems. The LULC variable was derived from a 2012 SPOT satellite image by supervised classification, while 30-m spatial resolution measurements of altitude and slope came from the Shuttle Radar Topography Mission. Metrological data were collected from the National Meteorological Agency, Bahir Dar branch. These separate datasets, represented as layers in the computer, were combined using weighted, multi-criteria evaluations. The outcome shows that rainfall, temperature, slope, elevation, distance from the lake and distance from the river influenced the malaria hazard the study area by 35%, 15%, 10%, 7%, 5% and 3%, respectively, resulting in a map showing five areas with different levels of malaria hazard: very high (11.2%); high (14.5%); moderate (63.3%); low (6%); and none (5%). The malaria risk map, based on this hazard map plus additional information on proximity to health facilities and current LULC conditions, shows that Bahir Dar City has areas with very high (15%); high (65%); moderate (8%); and low (5%) levels of malaria risk, with only 2% of the land completely riskfree. Such risk maps are essential for planning, implementing, monitoring and evaluating disease control as well as for contemplating prevention and elimination of epidemiological hazards from endemic areas. 2018-05-07T17:15:45+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/645 Bivariate spatiotemporal disease mapping of cancer of the breast and cervix uteri among Iranian women 2018-08-17T16:56:04+02:00 Mehdi Raei mehdi_r_d@yahoo.com Volker Johann Schmid volker.schmid@lmu.de Behzad Mahaki behzad.mahaki@gmail.com Cervical cancer in women is one of the most common cancers and breast cancer has grown dramatically in recent years. The purpose of this study was to map the incidence of breast and cervix uteri cancer among Iranian women over a 6-year period (2004-2009) searching for trend changes and risk factors. Cancer incidence data were extracted from the annual reports of the National Cancer Registry in Iran. Hierarchical Bayesian models, including random spatial and temporal effects was utilized together with bivariate, spatio-temporal shared component modelling. The provinces Tehran, Isfahan, Mazandaran and Gilan were found to have the highest relative risk (RR) of breast cancer, while the highest RR of cervix uteri cancer was observed in Tehran, Golestan, Khuzestan and Khorasan Razavi. Shared risk factors (smoking component) between the two cancers were seen to have the highest influence in Tehran, Khorasan Razavi, Yazd, Isfahan, Golestan, Khuzestan, Fars and Mazandaran, while the least were observed in Kohgiluyeh Boyerahmad. Apparent differences and distinctions between high-risk and low-risk provinces reveal a pattern of obvious dispersion for these cancers in Iran that should be considered when allocating healthcare resources and services in different areas. 2018-05-08T10:52:40+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/664 Application of decision tree for prediction of cutaneous leishmaniasis incidence based on environmental and topographic factors in Isfahan Province, Iran 2018-08-17T16:56:03+02:00 Roghieh Ramezankhani minoo.ramezani@gmail.com Nooshin Sajjadi nooshinsadjadi@yahoo.com Roya Nezakati Esmaeilzadeh royanezakati@gmail.com Seyed Ali Jozi sajozi@yahoo.com Mohammad Reza Shirzadi shirzadim@gmail.com Cutaneous Leishmaniasis (CL) is a neglected tropical disease that continues to be a health problem in Iran. Nearly 350 million people are thought to be at risk. We investigated the impact of the environmental factors on CL incidence during the period 2007- 2015 in a known endemic area for this disease in Isfahan Province, Iran. After collecting data with regard to the climatic, topographic, vegetation coverage and CL cases in the study area, a decision tree model was built using the classification and regression tree algorithm. CL data for the years 2007 until 2012 were used for model construction and the data for the years 2013 until 2015 were used for testing the model. The Root Mean Square error and the correlation factor were used to evaluate the predictive performance of the decision tree model. We found that wind speeds less than 14 m/s, altitudes between 1234 and 1810 m above the mean sea level, vegetation coverage according to the normalized difference vegetation index (NDVI) less than 0.12, rainfall less than 1.6 mm and air temperatures higher than 30°C would correspond to a seasonal incidence of 163.28 per 100,000 persons, while if wind speed is less than 14 m/s, altitude less than 1,810 m and NDVI higher than 0.12, then the mean seasonal incidence of the disease would be 2.27 per 100,000 persons. Environmental factors were found to be important predictive variables for CL incidence and should be considered in surveillance and prevention programmes for CL control. 2018-05-08T11:00:37+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/623 The influence of urban heat islands and socioeconomic factors on the spatial distribution of Aedes aegypti larval habitats 2018-08-17T16:56:03+02:00 Thiago S. de Azevedo azevedots@gmail.com Brian Patrick Bourke azevedots@gmail.com Rafael Piovezan piovezan.rafael@gmail.com Maria Anice M. Sallum masallum@usp.br We addressed the potential associations among the temporal and spatial distribution of larval habitats of<em> Aedes (Stegomyia) aegypti</em>, the presence of urban heat islands and socioeconomic factors. Data on larval habitats were collected in Santa Bárbara d’Oeste, São Paulo, Brazil, from 2004 to 2006, and spatial and temporal variations were analysed using a wavelet-based approach. We quantified urban heat islands by calculating surface temperatures using the results of wavelet analyses and grey level transformation from Thematic Mapper images (Landsat 5). <em>Ae. aegypti</em> larval habitats were geo-referenced corresponding to the wavelet analyses to test the potential association between geographical distribution of habitats and surface temperature. In an inhomogeneous spatial point process, we estimated the frequency of occurrence of larval habitats in relation to temperature. The São Paulo State Social Vulnerability Index in the municipality of Santa Barbára d’Oeste was used to test the potential association between presence of larval habitats and social vulnerability. We found abundant <em>Ae. aegypti</em> larval habitats in areas of higher surface temperature and social vulnerability and fewer larval habitats in areas with lower surface temperature and social vulnerability. 2018-05-08T11:08:28+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/607 Risk areas for hepatitis A, B and C in the municipality of Maringá, Paraná State, Brazil 2007-2010 2018-08-17T16:56:02+02:00 Valéria Miranda Avanzi valeriaavanzi@hotmail.com Udelysses Janete Veltrini Fonzar janetefonzar@hotmail.com Eraldo Schunk Silva eraldoschunk@gmail.com Jorge Juarez Vieira Teixeira jjvteixeira@uem.br Dennis Armando Bertolini dabertolini@uem.br Viral hepatitis is a major public health problem in Brazil and worldwide. We retrospectively analyzed 338 cases of hepatitis A, B and C in Maringá, Paraná State from 2007 through 2010. The hepatitis A virus was present in 5.6% of the cases, hepatitis B in 44.7% and hepatitis C in 49.7%. Most of the patients affected were male (55.3%), white (79.6%) and had some primary education (42.9%). Of the 338 cases analyzed, 13.0% had comorbidities. The cases were concentrated in large-population census zones, but it was concluded that the spatial distribution of viral hepatitis in Maringá occurred randomly rather than show any regular pattern. 2018-05-08T11:15:50+02:00 ##submission.copyrightStatement## https://geospatialhealth.net/index.php/gh/article/view/631 Quantifying human-environment interactions using videography in the context of infectious disease transmission 2018-08-17T16:56:01+02:00 Timothy R. Julian tim.julian@eawag.ch Carla Bustos cbustos@email.arizona.edu Laura H. Kwong kwong.laura@gmail.com Alejandro D. Badilla axb611@med.miami.edu Julia Lee julialee2012@gmail.com Heather N. Bischel hbischel@ucdavis.edu Robert A. Canales rcanales@email.arizona.edu Quantitative data on human-environment interactions are needed to fully understand infectious disease transmission processes and conduct accurate risk assessments. Interaction events occur during an individual’s movement through, and contact with, the environment, and can be quantified using diverse methodologies. Methods that utilize videography, coupled with specialized software, can provide a permanent record of events, collect detailed interactions in high resolution, be reviewed for accuracy, capture events difficult to observe in real-time, and gather multiple concurrent phenomena. In the accompanying video, the use of specialized software to capture humanenvironment interactions for human exposure and disease transmission is highlighted. Use of videography, combined with specialized software, allows for the collection of accurate quantitative representations of human-environment interactions in high resolution. Two specialized programs include the Virtual Timing Device for the Personal Computer, which collects sequential microlevel activity time series of contact events and interactions, and LiveTrak, which is optimized to facilitate annotation of events in real-time. Opportunities to annotate behaviors at high resolution using these tools are promising, permitting detailed records that can be summarized to gain information on infectious disease transmission and incorporated into more complex models of human exposure and risk. 2018-05-08T11:33:46+02:00 ##submission.copyrightStatement##