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  • 1. Dambach, Peter
    et al.
    Machault, Vanessa
    Lacaux, Jean-Pierre
    Vignolles, Cecile
    Sie, Ali
    Sauerborn, Rainer
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
    Utilization of combined remote sensing techniques to detect environmental variables influencing malaria vector densities in rural West Africa2012In: International Journal of Health Geographics, E-ISSN 1476-072X, Vol. 11, p. 8-Article in journal (Refereed)
    Abstract [en]

    Introduction: The use of remote sensing has found its way into the field of epidemiology within the last decades. With the increased sensor resolution of recent and future satellites new possibilities emerge for high resolution risk modeling and risk mapping. Methods: A SPOT 5 satellite image, taken during the rainy season 2009 was used for calculating indices by combining the image's spectral bands. Besides the widely used Normalized Difference Vegetation Index (NDVI) other indices were tested for significant correlation against field observations. Multiple steps, including the detection of surface water, its breeding appropriateness for Anopheles and modeling of vector imagines abundance, were performed. Data collection on larvae, adult vectors and geographic parameters in the field, was amended by using remote sensing techniques to gather data on altitude (Digital Elevation Model = DEM), precipitation (Tropical Rainfall Measurement Mission = TRMM), land surface temperatures (LST). Results: The DEM derived altitude as well as indices calculations combining the satellite's spectral bands (NDTI = Normalized Difference Turbidity Index, NDWI Mac Feeters = Normalized Difference Water Index) turned out to be reliable indicators for surface water in the local geographic setting. While Anopheles larvae abundance in habitats is driven by multiple, interconnected factors - amongst which the NDVI - and precipitation events, the presence of vector imagines was found to be correlated negatively to remotely sensed LST and positively to the cumulated amount of rainfall in the preceding 15 days and to the Normalized Difference Pond Index (NDPI) within the 500 m buffer zone around capture points. Conclusions: Remotely sensed geographical and meteorological factors, including precipitations, temperature, as well as vegetation, humidity and land cover indicators could be used as explanatory variables for surface water presence, larval development and imagines densities. This modeling approach based on remotely sensed information is potentially useful for counter measures that are putting on at the environmental side, namely vector larvae control via larviciding and water body reforming.

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  • 2.
    Grodzinsky, Ewa
    et al.
    Linköping University, Department of Medical and Health Sciences, General Practice. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Local Health Care Services in West Östergötland, Research & Development Unit in Local Health Care.
    Hallert, Claes
    Linköping University, Department of Social and Welfare Studies, Division of Health, Activity and Care. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Local Health Care Services in East Östergötland, Department of Internal Medicine in Norrköping.
    Faresjö, Tomas
    Linköping University, Department of Medical and Health Sciences, General Practice. Linköping University, Faculty of Health Sciences.
    Bergfors, Elisabet
    Linköping University, Department of Medical and Health Sciences, General Practice. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Local Health Care Services in West Östergötland, Research & Development Unit in Local Health Care.
    Olsen Faresjö, Åshild
    Linköping University, Department of Medical and Health Sciences, Social Medicine and Public Health Science. Linköping University, Faculty of Health Sciences.
    Could gastrointestinal disorders differ in two close but divergent social environments?2012In: International Journal of Health Geographics, E-ISSN 1476-072X, Vol. 11, no 5Article in journal (Refereed)
    Abstract [en]

    Background: Many public health problems in modern society affect the gastrointestinal area. Knowledge of the disease occurrence in populations is better understood if viewed in a psychosocial context including indicators of the social environment where people spend their lives. The general aim of this study was to estimate the occurrence in the population and between sexes of common gastrointestinal conditions in two neighborhood cities representing two different social environments defined as a "white-collar" and a "blue-collar" city. less thanbrgreater than less thanbrgreater thanMethods: We conducted a retrospective register study using data of diagnosed gastrointestinal disorders (cumulative incidence rates) derived from an administrative health care register based on medical records assigned by the physicians at hospitals and primary care. less thanbrgreater than less thanbrgreater thanResults: Functional gastrointestinal diseases and peptic ulcers were more frequent in the white-collar city, while diagnoses in the gallbladder area were significantly more frequent in the blue-collar city. Functional dyspepsia, irritable bowel syndrome, and unspecified functional bowel diseases, and celiac disease, were more frequent among women while esophageal reflux, peptic ulcers, gastric and rectal cancers were more frequent among men regardless of social environment. less thanbrgreater than less thanbrgreater thanConclusions: Knowledge of the occurrence of gastrointestinal problems in populations is better understood if viewed in a context were the social environment is included. Indicators of the social environment should therefore also be considered in future studies of the occurrence of gastrointestinal problems.

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  • 3.
    Hassler, Jacob
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment.
    Andersson Granberg, Tobias
    Department of Science and Technology, Linköping University/ITN, 60174 Norrköping, Sweden.
    Steins, Krisjanis
    Department of Science and Technology, Linköping University/ITN, 60174 Norrköping, Sweden.
    Ceccato, Vania
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment.
    Towards more realistic measures of accessibility to emergency departments in Sweden2024In: International Journal of Health Geographics, E-ISSN 1476-072X, Vol. 23, no 1, article id 6Article in journal (Other academic)
    Abstract [en]

    Background Assuring that emergency health care (EHC) is accessible is a key objective for health care planners.Conventional accessibility analysis commonly relies on resident population data. However, the allocation of resourcesbased on stationary population data may lead to erroneous assumptions of population accessibility to EHC.Method Therefore, in this paper, we calculate population accessibility to emergency departments in Swedenwith a geographical information system based network analysis. Utilizing static population data and dynamic populationdata, we investigate spatiotemporal patterns of how static population data over- or underestimates populationsizes derived from temporally dynamic population data.Results Our findings show that conventional measures of population accessibility tend to underestimate populationsizes particularly in rural areas and in smaller ED’s catchment areas compared to urban, larger ED’s—especially duringvacation time in the summer.Conclusions Planning based on static population data may thus lead to inequitable distributions of resources. Thisstudy is motivated in light of the ongoing centralization of ED’s in Sweden, which largely depends on population sizesin ED’s catchment areas.Keywords Accessibility, Emergency health care, Dynamic population data, Spatiotemporal analysis

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  • 4.
    Huerta Munoz, Ulises
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health, International Maternal and Child Health (IMCH).
    Källestål, Carina
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health, International Maternal and Child Health (IMCH).
    Geographical accessibility and spatial coverage modeling of the primary health care network in the Western Province of Rwanda2012In: International Journal of Health Geographics, E-ISSN 1476-072X, Vol. 11, no 1, p. 40-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND:

    Primary health care is essential in improving and maintaining the health of populations. It has the potential to accelerate achievement of the Millennium Development Goals and fulfill the "Health for All" doctrine of the Alma-Ata Declaration. Understanding the performance of the health system from a geographic perspective is important for improved health planning and evidence-based policy development. The aims of this study were to measure geographical accessibility, model spatial coverage of the existing primary health facility network, estimate the number of primary health facilities working under capacity and the population underserved in the Western Province of Rwanda.

    METHODS:

    This study uses health facility, population and ancillary data for the Western Province of Rwanda. Three different travel scenarios utilized by the population to attend the nearest primary health facility were defined with a maximum travelling time of 60 minutes: Scenario 1 - waking; Scenario 2 - walking and cycling; and Scenario 3 - walking and public transportation. Considering these scenarios, a raster surface of travel time between primary health facilities and population was developed. To model spatial coverage and estimate the number of primary health facilities working under capacity, the catchment area of each facility was calculated by taking into account population coverage capacity, the population distribution, the terrain topography and the travelling modes through the different land categories.

    RESULTS:

    Scenario 2 (walking and cycling) has the highest degree of geographical accessibility followed by Scenario 3 (walking and public transportation). The lowest level of accessibility can be observed in Scenario 1 (walking). The total population covered differs depending on the type of travel scenario. The existing primary health facility network covers only 26.6 % of the population in Scenario 1. In Scenario 2, the use of a bicycle greatly increases the population being served to 58 % of inhabitants. When considering Scenario 3, the total population served is 34.3 %.

    CONCLUSIONS:

    Significant spatial variations in geographical accessibility and spatial coverage were observed across the three travel scenarios. The analysis demonstrates that regardless of which travel scenario is used, the majority of the population in the Western Province does not have access to the existing primary health facility network. Our findings also demonstrate the usefulness of GIS methods to leverage multiple datasets from different sources in a spatial framework to provide support to evidence-based planning and resource allocation decision-making in developing countries.

  • 5.
    Koppner, Jenny
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Society and Health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Primary Care Center, Primary Health Care Center Vikbolandet.
    Chatziarzenis, Marios
    Thriasson Gen Hosp Elefsina, Greece.
    Faresjö, Tomas
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Theodorsson, Elvar
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Clinical Chemistry. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Clinical Chemistry.
    Thorsell, Annika
    Linköping University, Department of Biomedical and Clinical Sciences, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences.
    Nilsson, Staffan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Primary Care Center, Primary Health Care Center Vikbolandet.
    Olsen, Ole
    Univ Tromso, Norway.
    Olsen Faresjö, Åshild
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Society and Health. Linköping University, Faculty of Medicine and Health Sciences.
    Stress and perceived health among primary care visitors in two corners of Europe: Scandinavia and Greece2020In: International Journal of Health Geographics, E-ISSN 1476-072X, Vol. 19, no 1, article id 55Article in journal (Refereed)
    Abstract [en]

    Background The global financial crisis emerging in 2008 struck Greece especially hard, whereas Scandinavian countries were less affected. This has created a unique opportunity to study the long-term effect of community stress on populations. Increasing frequencies of mental health issues and poorer perceived health among the Greek population have been reported. The physiological marker of long-term stress, cortisol in hair, is applied in this study together with measures of perceived health and stress, depression and anxiety. Our aim was to study self-reported and physiological stress, perceived health, including mental health, in the general population of Greece compared to Scandinavia, in order to assess long-term effects of the economic crisis on these parameters. Methods A cross-sectional comparative study of adult (18-65 years) Primary Health Care visitors from semi-rural areas in Greece (n = 84) and Scandinavia (n = 140). Data collection was performed in 2012, and encompassed a questionnaire with a variety of health and stress indicators as well as hair samples for analyzes of cortisol levels. Results The Greek sample reported significantly poorer overall health (p < 0.0001) than the Scandinavians and a significantly higher perceived stress (p < 0.0001). The Greeks were also less hopeful of the future (p < 0.0001), and to a larger extent fulfilled the HAD criteria for depression (p < 0.0001) and anxiety (p = 0.002). The strongest predictors explaining ill health in logistic regressions were being Greek (p = 0.001) and feeling hopeless about the future p = 0.001, OR = 6.00 (CI 2.10-14.88). Strong predictors in logistic regressions for high perceived stress were anxiety: high (p < 0.0001) and medium (p = 0.0001), as well as medium depression (p = 0.02). Conclusions Greek adult Primary Health Care visitors perceived their health more negatively than the Scandinavians, including a higher presence of depression, anxiety, and a lower hope for the future. The Greeks also reported higher perceived stress, but this was not reflected in higher cortisol levels. The findings presented here, identify possible adverse long-term effects of the economic crisis in the examined Greek population that are not seen in the Scandinavian cohort. These differences may also be interpreted against the background of socio-cultural differences in the northern and south-eastern corners of Europe.

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  • 6. Louis, Valérie R
    et al.
    Phalkey, Revati
    Horstick, Olaf
    Ratanawong, Pitcha
    Wilder-Smith, Annelies
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health. Institute of Public Health, Heidelberg University Medical School, Heidelberg, Germany.
    Tozan, Yesim
    Dambach, Peter
    Modeling tools for dengue risk mapping - a systematic review2014In: International Journal of Health Geographics, E-ISSN 1476-072X, Vol. 13, article id 50Article, review/survey (Refereed)
    Abstract [en]

    INTRODUCTION: The global spread and the increased frequency and magnitude of epidemic dengue in the last 50 years underscore the urgent need for effective tools for surveillance, prevention, and control. This review aims at providing a systematic overview of what predictors are critical and which spatial and spatio-temporal modeling approaches are useful in generating risk maps for dengue.

    METHODS: A systematic search was undertaken, using the PubMed, Web of Science, WHOLIS, Center for Disease Control (CDC) and OvidSP databases for published citations, without language or time restrictions. A manual search of the titles and abstracts was carried out using predefined criteria, notably the inclusion of dengue cases. Data were extracted for pre-identified variables, including the type of predictors and the type of modeling approach used for risk mapping.

    RESULTS: A wide variety of both predictors and modeling approaches was used to create dengue risk maps. No specific patterns could be identified in the combination of predictors or models across studies. The most important and commonly used predictors for the category of demographic and socio-economic variables were age, gender, education, housing conditions and level of income. Among environmental variables, precipitation and air temperature were often significant predictors. Remote sensing provided a source of varied land cover data that could act as a proxy for other predictor categories. Descriptive maps showing dengue case hotspots were useful for identifying high-risk areas. Predictive maps based on more complex methodology facilitated advanced data analysis and visualization, but their applicability in public health contexts remains to be established.

    CONCLUSIONS: The majority of available dengue risk maps was descriptive and based on retrospective data. Availability of resources, feasibility of acquisition, quality of data, alongside available technical expertise, determines the accuracy of dengue risk maps and their applicability to the field of public health. A large number of unknowns, including effective entomological predictors, genetic diversity of circulating viruses, population serological profile, and human mobility, continue to pose challenges and to limit the ability to produce accurate and effective risk maps, and fail to support the development of early warning systems.

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  • 7.
    Sohel, Nazmul
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health.
    Vahter, Marie
    Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
    Ali, Mohammad
    International Vaccine Institute, Seoul, Korea.
    Rahman, Mahfuzar
    ICDDR,B, Dhaka, Bangladesh.
    Rahman, Anisur
    ICDDR,B, Dhaka, Bangladesh.
    Kim Streatfield, Peter
    ICDDR,B, Dhaka, Bangladesh.
    Kanaroglou, Pavlos
    School of Geography and Earth Science, McMaster University, Hamilton, ON, Canada.
    Persson, Lars-Åke
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Women's and Children's Health.
    Spatial patterns of fetal loss and infant death in an arsenic-affected area in Bangladesh2010In: International Journal of Health Geographics, E-ISSN 1476-072X, Vol. 9, p. 53-Article in journal (Refereed)
    Abstract [en]

    Background: Arsenic exposure in pregnancy is associated with adverse pregnancy outcome and infant mortality. Knowledge of the spatial characteristics of the outcomes and their possible link to arsenic exposure are important for planning effective mitigation activities. The aim of this study was to identify spatial and spatiotemporal clustering of fetal loss and infant death, and spatial relationships between high and low clusters of fetal loss and infant death rates and high and low clusters of arsenic concentrations in tube-well water used for drinking.Methods: Pregnant women from Matlab, Bangladesh, who used tube-well water for drinking while pregnant between 1991 and 2000, were included in this study. In total 29,134 pregnancies were identified. A spatial scan test was used to identify unique non-random spatial and spatiotemporal clusters of fetal loss and infant death using a retrospective spatial and spatiotemporal permutation and Poisson probability models.Results: Two significant clusters of fetal loss and infant death were identified and these clusters remained stable after adjustment for covariates. One cluster of higher rates of fetal loss and infant death was in the vicinity of the Meghna River, and the other cluster of lower rates was in the center of Matlab. The average concentration of arsenic in the water differed between these clusters (319 μg/L for the high cluster and 174 μg/L for the low cluster). The spatial patterns of arsenic concentrations in tube-well water were found to be linked with the adverse pregnancy outcome clusters. In the spatiotemporal analysis, only one high fetal loss and infant death cluster was identified in the same high cluster area obtained from purely spatial analysis. However, the cluster was no longer significant after adjustment for the covariates.Conclusion: The finding of this study suggests that given the geographical variation in tube-well water contamination, higher fetal loss and infant deaths were observed in the areas of higher arsenic concentrations in groundwater. This illustrates a possible link between arsenic contamination in tube-well water and adverse pregnancy outcome. Thus, these areas should be considered a priority in arsenic mitigation programs.

  • 8.
    Van Haute, Tom
    et al.
    Ghent University, Belgium.
    De Poorter, Eli
    Ghent University, Belgium.
    Crombez, Pieter
    Televic NV, Belgium.
    Lemic, Filip
    Technical University of Berlin, Germany.
    Handziski, Vlado
    Technical University of Berlin, Germany.
    Wirström, Niklas
    RISE, Swedish ICT, SICS.
    Wolisz, Adam
    Technical University of Berlin, Germany.
    Voigt, Thiemo
    RISE, Swedish ICT, SICS, Computer Systems Laboratory.
    Moerman, Ingrid
    Ghent University, Belgium.
    Performance Analysis of Multiple Indoor Positioning Systems in a Healthcare Environment2016In: International Journal of Health Geographics, E-ISSN 1476-072X, Vol. 15, no 7Article in journal (Refereed)
    Abstract [en]

    Background: The combination of an aging population and nursing staff shortages implies the need for more advanced systems in the healthcare industry. Many key enablers for the optimization of healthcare systems require provisioning of location awareness for patients (e.g. with dementia), nurses, doctors, assets, etc. Therefore, many Indoor Positioning Systems(IPSs) will be indispensable in healthcare systems. However, although many IPSs have been proposed in literature, most of these have been evaluated in non-representative environments such as office buildings rather than in a hospital. Methods: To remedy this, the paper evaluates the performance of existing IPSs in an operational modern healthcare environment: the “Sint-Jozefs kliniek Izegem” hospital in Belgium. The evaluation (data-collecting & data-processing) is executed using a standardized methodology and evaluates the point accuracy, room accuracy and latency of multiple IPSs. To evaluate the solutions, the position of a stationary device was requested at 73 evaluation locations. By using the same evaluation locations for all IPSs the performance of all systems could objectively be compared. Results: Several trends can be identified such as the fact that Wi-Fi based fingerprinting solutions have the best accuracy result (point accuracy of 1.21 m and room accuracy of 98 %) however it requires calibration before use and needs 5.43 s to estimate the location. On the other hand, proximity based solutions (based on sensor nodes) are significantly cheaper to install, do not require calibration and still obtain acceptable room accuracy results. Conclusion: As a conclusion of this paper, Wi-Fi based solutions have the most potential for an indoor positioning service in case when accuracy is the most important metric. Applying the fingerprinting approach with an anchor installed in every two rooms is the preferred solution for a hospital environment.

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  • 9.
    Wennerholm, Carina
    et al.
    Linköping University, Department of Medical and Health Sciences, Nursing Science. Linköping University, Faculty of Health Sciences.
    Grip, Björn
    Linköping University, Department for Studies of Social Change and Culture. Linköping University, Faculty of Arts and Sciences.
    Johansson, AnnaKarin
    Linköping University, Department of Medical and Health Sciences, Nursing Science. Linköping University, Faculty of Health Sciences.
    Nilsson, Hans
    Linköping University, Department for Studies of Social Change and Culture, Centre for Local History. Linköping University, Faculty of Arts and Sciences.
    Honkasalo, Marja-Liisa
    Linköping University, Department of Medical and Health Sciences, Health and Society. Linköping University, Faculty of Health Sciences.
    Faresjö, Tomas
    Linköping University, Department of Medical and Health Sciences, General Practice. Linköping University, Faculty of Health Sciences.
    Cardiovascular disease occurrence in two close but different social environments2011In: International Journal of Health Geographics, E-ISSN 1476-072X, Vol. 10, no 5Article in journal (Refereed)
    Abstract [en]

    Background: Cardiovascular diseases estimate to be the leading cause of death and loss of disability-adjusted life years globally. Conventional risk factors for cardiovascular diseases only partly account for the social gradient. The purpose of this study was to compare the occurrence of the most frequent cardiovascular diseases and cardiovascular mortality in two close cities, the Twin cities. Methods: We focused on the total population in two neighbour and equally sized cities with a population of around 135 000 inhabitants each. These twin cities represent two different social environments in the same Swedish county. According to their social history they could be labelled a "blue-collar" and a "white-collar" city. Morbidity data for the two cities was derived from an administrative health care register based on medical records assigned by the physicians at both hospitals and primary care. The morbidity data presented are cumulative incidence rates and the data on mortality for ischemic heart diseases is based on official Swedish statistics. Results: The cumulative incidence of different cardiovascular diagnoses for younger and also elderly men and women revealed significantly differences for studied cardiovascular diagnoses. The occurrence rates were in all aspects highest in the population of the "blue-collar" twin city for both sexes. Conclusions: This study revealed that there are significant differences in risk for cardiovascular morbidity and mortality between the populations in the studied different social environments. These differences seem to be profound and stable over time and thereby give implication for public health policy to initiate a community intervention program in the "blue-collar" twin city.

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  • 10. Zeimes, Caroline B.
    et al.
    Olsson, Gert E.
    Ahlm, Clas
    Umeå University, Faculty of Medicine, Department of Clinical Microbiology, Infectious Diseases.
    Vanwambeke, Sophie O.
    Modelling zoonotic diseases in humans: comparison of methods for hantavirus in Sweden2012In: International Journal of Health Geographics, E-ISSN 1476-072X, no 11, p. 39-Article in journal (Refereed)
    Abstract [en]

    Because their distribution usually depends on the presence of more than one species, modelling zoonotic diseases in humans differs from modelling individual species distribution even though the data are similar in nature. Three approaches can be used to model spatial distributions recorded by points: based on presence/absence, presence/available or presence data. Here, we compared one or two of several existing methods for each of these approaches. Human cases of hantavirus infection reported by place of infection between 1991 and 1998 in Sweden were used as a case study. Puumala virus (PUUV), the most common hantavirus in Europe, circulates among bank voles (Myodes glareolus). In northern Sweden, it causes nephropathia epidemica (NE) in humans, a mild form of hemorrhagic fever with renal syndrome. Logistic binomial regression and boosted regression trees were used to model presence and absence data. Presence and available sites (where the disease may occur) were modelled using cross-validated logistic regression. Finally, the ecological niche model MaxEnt, based on presence-only data, was used. In our study, logistic regression had the best predictive power, followed by boosted regression trees, MaxEnt and cross-validated logistic regression. It is also the most statistically reliable but requires absence data. The cross-validated method partly avoids the issue of absence data but requires fastidious calculations. MaxEnt accounts for non-linear responses but the estimators can be complex. The advantages and disadvantages of each method are reviewed.

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