{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T07:07:55Z","timestamp":1760425675637,"version":"build-2065373602"},"reference-count":80,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,1,9]],"date-time":"2019-01-09T00:00:00Z","timestamp":1546992000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Uncertainties in spatial modeling studies of schistosomiasis (SCH) are relevant for the reliable identification of at-risk populations. Ecological fallacy occurs when ecological or group-level analyses, such as spatial aggregations at a specific administrative level, are carried out for an individual-level inference. This could lead to the unreliable identification of at-risk populations, and consequently to fallacies in the drugs\u2019 allocation strategies and their cost-effectiveness. A specific form of ecological fallacy is pure specification bias. The present research aims to quantify its effect on the parameter estimates of various environmental covariates used as drivers for SCH infection. This is done by (i) using a spatial convolution model that removes pure specification bias, (ii) estimating group and individual-level covariate regression parameters, and (iii) quantifying the difference between the parameter estimates and the predicted disease outcomes from the convolution and ecological models. We modeled the prevalence of Schistosoma japonicum using group-level health outcome data, and city-level environmental data as a proxy for individual-level exposure. We included environmental data such as water and vegetation indexes, distance to water bodies, day and night land surface temperature, and elevation. We estimated and compared the convolution and ecological model parameter estimates using Bayesian statistics. Covariate parameter estimates from the convolution and ecological models differed between 0.03 for the nearest distance to water bodies (NDWB), and 0.28 for the normalized difference water index (NDWI). The convolution model presented lower uncertainties in most of the parameter estimates, except for NDWB. High differences in uncertainty were found in night land surface temperature (0.23) and elevation (0.13). No significant differences were found between the predicted values and their uncertainties from both models. The proposed convolution model is able to correct for a pure specification bias by presenting less uncertain parameter estimates. It shows a good predictive performance for the mean prevalence values and for a positive number of infected people. Further research is needed to better understand the spatial extent and support of analysis to reliably explore the role of environmental variables.<\/jats:p>","DOI":"10.3390\/ijerph16020176","type":"journal-article","created":{"date-parts":[[2019,1,10]],"date-time":"2019-01-10T03:22:31Z","timestamp":1547090551000},"page":"176","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Modeling Schistosoma japonicum Infection under Pure Specification Bias: Impact of Environmental Drivers of Infection"],"prefix":"10.3390","volume":"16","author":[{"given":"Andrea L.","family":"Araujo Navas","sequence":"first","affiliation":[{"name":"Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2206-3662","authenticated-orcid":false,"given":"Frank","family":"Osei","sequence":"additional","affiliation":[{"name":"Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lydia R.","family":"Leonardo","sequence":"additional","affiliation":[{"name":"Institute of Biology, College of Science, University of the Philippines Diliman, UP Diliman 1101 Quezon City, Philippines"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9157-8470","authenticated-orcid":false,"given":"Ricardo J.","family":"Soares Magalh\u00e3es","sequence":"additional","affiliation":[{"name":"UQ Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, Gatton 4343 QLD, Australia"},{"name":"Child Health and Environment Program, Child Health Research Centre, The University of Queensland, South Brisbane 4101 QLD, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9456-1233","authenticated-orcid":false,"given":"Alfred","family":"Stein","sequence":"additional","affiliation":[{"name":"Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"458","DOI":"10.2471\/BLT.06.033035","article-title":"Assessment of the age-specific disability weight of chronic schistosomiasis japonica","volume":"85","author":"Jia","year":"2007","journal-title":"Bull. World Health Organ."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Tarafder, M.R., Balolong, E., Carabin, H., Belisle, P., Tallo, V., Joseph, L., Alday, P., Gonzales, R.O., Riley, S., and Olveda, R. (2006). A cross-sectional study of the prevalence of intensity of infection with Schistosoma japonicum in 50 irrigated and rain-fed villages in Samar Province, the Philippines. BMC Public Health, 6.","DOI":"10.1186\/1471-2458-6-61"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1016\/j.ijpara.2007.12.007","article-title":"An integrated approach to identify distribution of Oncomelania hupensis, the intermediate host of Schistosoma japonicum, in a mountainous region in China","volume":"38","author":"Yang","year":"2008","journal-title":"Int. J. Parasitol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1016\/S0140-6736(05)66457-4","article-title":"Reassessment of the cost of chronic helmintic infection: A meta-analysis of disability-related outcomes in endemic schistosomiasis","volume":"365","author":"King","year":"2005","journal-title":"Lancet"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Walz, Y., Wegmann, M., Dech, S., Vounatsou, P., Poda, J.-N., N\u2019Goran, E.K., Utzinger, J., and Raso, G. (2015). Modeling and Validation of Environmental Suitability for Schistosomiasis Transmission Using Remote Sensing. PLoS Negl. Trop. Dis., 9.","DOI":"10.1371\/journal.pntd.0004217"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Hotez, P.J., Alvarado, M., Basanez, M.G., Bolliger, I., Bourne, R., Boussinesq, M., Brooker, S.J., Brown, A.S., Buckle, G., and Budke, C.M. (2014). The Global Burden of Disease Study 2010: Interpretation and Implications for the Neglected Tropical Diseases. PLoS Negl. Trop. Dis., 8.","DOI":"10.1371\/journal.pntd.0002865"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1093\/ajcn\/83.2.371","article-title":"Schistosomiasis japonica, anemia, and iron status in children, adolescents, and young adults in Leyte, Philippines","volume":"83","author":"Leenstra","year":"2006","journal-title":"Am. J. Clin. Nutr."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1086\/430929","article-title":"Nutritional status and serum cytokine profiles in children, adolescents, and young adults with Schistosoma japonicum-associated hepatic fibrosis, in Leyte, Philippines","volume":"192","author":"Coutinho","year":"2005","journal-title":"J. Infect. Dis."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1016\/j.ijpara.2014.06.010","article-title":"Geographical distribution of human Schistosoma japonicum infection in The Philippines: Tools to support disease control and further elimination","volume":"44","author":"Salamat","year":"2014","journal-title":"Int. J. Parasitol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.healthplace.2006.03.003","article-title":"Thirty years of use and improvement of remote sensing, applied to epidemiology: From early promises to lasting frustration","volume":"13","author":"Herbreteau","year":"2007","journal-title":"Health Place"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2899","DOI":"10.1080\/014311697217125","article-title":"Review article The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors for disease","volume":"18","author":"Hay","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kalluri, S., Gilruth, P., Rogers, D., and Szczur, M. (2007). Surveillance of arthropod vector-borne infectious diseases using remote sensing techniques: A review. PLoS Pathog., 3.","DOI":"10.1371\/journal.ppat.0030116"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Hamm, N.A.S., Soares Magalh\u00e3es, R.J., and Clements, A.C.A. (2015). Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases. PLoS Negl. Trop. Dis., 9.","DOI":"10.1371\/journal.pntd.0004164"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1186\/s12942-016-0049-5","article-title":"Spatial measurement errors in the field of spatial epidemiology","volume":"15","author":"Zhang","year":"2016","journal-title":"Int. J. Health Geogr."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Araujo Navas, A.L., Hamm, N.A.S., Soares Magalh\u00e3es, R.J., and Stein, A. (2016). Mapping Soil Transmitted Helminths and Schistosomiasis under Uncertainty: A Systematic Review and Critical Appraisal of Evidence. PLoS Negl. Trop. Dis., 10.","DOI":"10.1371\/journal.pntd.0005208"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zhang, J., and Goodchild, M.F. (2002). Uncertainty in Geographical Information, Taylor & Francis Group.","DOI":"10.1201\/b12624"},{"key":"ref_17","unstructured":"Elliot, P.W., Wakefield, J.C., Best, N.G., and Briggs, D.J. (2000). Ecological Correlation Studies. Spatial Epidemiology: Methods and Applications, Oxford University Press."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1093\/biostatistics\/kxj017","article-title":"Health-exposure modeling and the ecological fallacy","volume":"7","author":"Wakefield","year":"2006","journal-title":"Biostatistics"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"King, G. (2013). A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data, Princeton University Press.","DOI":"10.1515\/9781400849208"},{"key":"ref_20","unstructured":"Hall\/CRC, C. (2010). Spatial Aggregation and the Ecological Fallacy. Handbook of Modern Statisticcal Methods, CRC Press."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Gelfand, A.E., Diggle, P., Guttorp, P., and Fuentes, M. (2010). Handbook of Spatial Statistics, Taylor & Francis Group.","DOI":"10.1201\/9781420072884"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1093\/biomet\/82.1.113","article-title":"Aggregate data studies of disease risk factors","volume":"82","author":"Prentice","year":"1995","journal-title":"Biometrika"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1093\/ije\/16.1.111","article-title":"Comparison of relative risks obtained in ecological and individual studies: Some methodological considerations","volume":"16","author":"Richardson","year":"1987","journal-title":"Int. J. Epidemiol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4930","DOI":"10.1002\/sim.7494","article-title":"Accommodating the ecological fallacy in disease mapping in the absence of individual exposures","volume":"36","author":"Wang","year":"2017","journal-title":"Stat. Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1017\/S0031182005007432","article-title":"Spatial risk prediction and mapping of Schistosoma mansoni infections among schoolchildren living in western C\u00f4te d\u2019Ivoire","volume":"131","author":"Raso","year":"2005","journal-title":"Parasitology"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Chammartin, F., Houngbedji, C.A., Huerlimann, E., Yapi, R.B., Silue, K.D., Soro, G., Kouame, F.N., N\u2019Goran, E.K., Utzinger, J., and Raso, G. (2014). Bayesian Risk Mapping and Model-Based Estimation of Schistosoma haematobium-Schistosoma mansoni Co-distribution in Cote d\u2019Ivoire. PLoS Negl. Trop. Dis., 8.","DOI":"10.1371\/journal.pntd.0003407"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Woodhall, D.M., Wiegand, R.E., Wellman, M., Matey, E., Abudho, B., Karanja, D.M.S., Mwinzi, P.M.N., Montgomery, S.P., and Secor, W.E. (2013). Use of Geospatial Modeling to Predict Schistosoma mansoni Prevalence in Nyanza Province, Kenya. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0071635"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Sturrock, H.J.W., Pullan, R.L., Kihara, J.H., Mwandawiro, C., and Brooker, S.J. (2013). The Use of Bivariate Spatial Modeling of Questionnaire and Parasitology Data to Predict the Distribution of Schistosoma haematobium in Coastal Kenya. PLoS Negl. Trop. Dis., 7.","DOI":"10.1371\/journal.pntd.0002016"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"111","DOI":"10.4081\/gh.2015.324","article-title":"Sandwich mapping of schistosomiasis risk in Anhui Province, China","volume":"10","author":"Hu","year":"2015","journal-title":"Geospat. Health"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1590\/S0074-02762010000400030","article-title":"A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil","volume":"105","author":"Freitas","year":"2010","journal-title":"Mem. Inst. Oswaldo Cruz"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.actatropica.2013.12.007","article-title":"Predictive risk mapping of schistosomiasis in Brazil using Bayesian geostatistical models","volume":"132","author":"Scholte","year":"2014","journal-title":"Acta Trop."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Soares Magalh\u00e3es, R.J., Salamat, M.S., Leonardo, L., Gray, D.J., Carabin, H., Halton, K., McManus, D.P., Williams, G.M., Rivera, P., and Saniel, O. (2015). Mapping the Risk of Soil-Transmitted Helminthic Infections in the Philippines. PLoS Negl. Trop. Dis., 9.","DOI":"10.1371\/journal.pntd.0003915"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1016\/j.ijpara.2007.08.001","article-title":"Bayesian spatial analysis of a national urinary schistosomiasis questionnaire to assist geographic targeting of schistosomiasis control in Tanzania, East Africa","volume":"38","author":"Clements","year":"2008","journal-title":"Int. J. Parasitol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1155\/2012\/936128","article-title":"A national baseline prevalence survey of schistosomiasis in the Philippines using stratified two-step systematic cluster sampling design","volume":"2012","author":"Leonardo","year":"2012","journal-title":"J. Trop. Med."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1016\/j.actatropica.2013.03.015","article-title":"New endemic foci of schistosomiasis infections in the Philippines","volume":"141","author":"Leonardo","year":"2015","journal-title":"Acta Trop."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/S0001-706X(02)00022-0","article-title":"Difficulties and strategies in the control of schistosomiasis in the Philippines","volume":"82","author":"Leonardo","year":"2002","journal-title":"Acta Trop."},{"key":"ref_37","first-page":"145","article-title":"Schistosomiasis Japonica: Control and Research Needs","volume":"Volume 72","author":"Zhou","year":"2010","journal-title":"Important Helminth Infections in Southeast Asia: Diversity and Potential for Control and Elimination, Peart A"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.parint.2008.04.006","article-title":"Prevalence survey of schistosomiasis in Mindanao and the Visayas, The Philippines","volume":"57","author":"Leonardo","year":"2008","journal-title":"Parasitol. Int."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1590\/S0037-86822005000200016","article-title":"Comparison of the thick smear and Kato-Katz techniques for diagnosis of intestinal helminth infections","volume":"38","author":"Santos","year":"2005","journal-title":"Rev. Soc. Bras. Med. Trop."},{"key":"ref_40","unstructured":"ESRI (2011). ArcGIS Desktop, 10, Environmental Systems Research Institute."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/1756-3305-5-275","article-title":"Factors impacting on progress towards elimination of transmission of schistosomiasis japonica in China","volume":"5","author":"Zhou","year":"2012","journal-title":"Parasit. Vectors"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1186\/s13071-015-0732-6","article-title":"Risk profiling of schistosomiasis using remote sensing: Approaches, challenges and outlook","volume":"8","author":"Walz","year":"2015","journal-title":"Parasit. Vectors"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery","volume":"27","author":"Xu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1017\/S0022149X00007288","article-title":"The influence of physical factors on the survival and infectivity of miracidia of Schistosoma mansoni and S. haematobium I. Effect of temperature and ultra-violet light","volume":"51","author":"Prah","year":"1977","journal-title":"J. Helminthol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/0001-706X(90)90021-Q","article-title":"Population dynamics model for Bulinus globosus, intermediate host for Schistosoma haematobium, in river habitats","volume":"47","author":"Woolhouse","year":"1990","journal-title":"Acta Trop."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/S1471-4922(03)00117-X","article-title":"Free-living endohelminth stages: At the mercy of environmental conditions","volume":"19","author":"Pietrock","year":"2003","journal-title":"Trends Parasitol."},{"key":"ref_47","unstructured":"Geological Survey, U.S. (2017, August 15). Global Data Explorer, Available online: https:\/\/gdex.cr.usgs.gov\/gdex\/."},{"key":"ref_48","first-page":"481","article-title":"Studies on Schistosoma japonicum infection in the Philippines 2. The molluscan host","volume":"18","author":"Pesigan","year":"1958","journal-title":"Bull. World Health Organ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"93","DOI":"10.4081\/gh.2006.284","article-title":"Modeling freshwater snail habitat suitability and areas of potential snail-borne disease transmission in Uganda","volume":"1","author":"Stensgaard","year":"2006","journal-title":"Geospat. Health"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1016\/j.actatropica.2011.11.010","article-title":"Large-scale determinants of intestinal schistosomiasis and intermediate host snail distribution across Africa: Does climate matter?","volume":"128","author":"Stensgaard","year":"2013","journal-title":"Acta Trop."},{"key":"ref_51","unstructured":"(2018, February 15). National Mapping and Resource Information Authority, Available online: http:\/\/www.namria.gov.ph\/."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1214\/06-BA117A","article-title":"Prior distributions for variance parameters in hierarchical models (Comment on an Article by Browne and Draper)","volume":"1","author":"Gelman","year":"2006","journal-title":"Bayesian Anal."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Gelman, A., Carlin, J.B., Stern, H.S., and Rubin, D.B. (1995). Bayesian Data Analysis, Chapman and Hall\/CRC.","DOI":"10.1201\/9780429258411"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1111\/1467-9876.00113","article-title":"Model-based geostatistics","volume":"47","author":"Diggle","year":"2002","journal-title":"J. R. Stat. Soc. Ser. C Appl. Stat."},{"key":"ref_55","unstructured":"Thomas, A., Best, N., Lunn, D., Arnold, R., and Spiegelhalter, D. (2004). GeoBugs User Manual, MRC Biostatistics Unit."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Lunn, D., Jackson, C., Best, N., Thomas, A., and Spiegelhalter, D. (2012). The BUGS Book: A Practical Introduction to Bayesian Analysis, CRC Press.","DOI":"10.1201\/b13613"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1080\/10618600.1998.10474787","article-title":"General methods for monitoring convergence of iterative simulations","volume":"7","author":"Brooks","year":"1998","journal-title":"J. Comput. Graph. Stat."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1214\/ss\/1177011136","article-title":"Inference from iterative simulation using multiple sequences","volume":"7","author":"Gelman","year":"1992","journal-title":"Stat. Sci."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/S1471-4922(01)02223-1","article-title":"Tools from ecology: Useful for evaluating infection risk models?","volume":"18","author":"Brooker","year":"2002","journal-title":"Trends Parasitol."},{"key":"ref_60","unstructured":"Hijmans, R., Rojas, E., Cruz, M., O\u2019Brien, R., and Barrantes, I. (2018, April 08). DIVA-GIS free, simple and effective. Available online: http:\/\/www.diva-gis.org\/Data."},{"key":"ref_61","unstructured":"Project, O.S.M. (2017). Planet OSM, Open Street Map Project."},{"key":"ref_62","unstructured":"(2018, April 10). OCHA Humanitarian Data Exchange v1.25.3. Available online: https:\/\/data.humdata.org\/search?groups=phl&q=&ext_page_size=25."},{"key":"ref_63","unstructured":"Spiegelhalter, D., Thomas, A., Best, N., and Lunn, D. (2007). OpenBUGS User Manual, MRC Biostatistics Unit. Version 3.0.2."},{"key":"ref_64","unstructured":"Spiegelhalter, D., Thomas, A., Best, N., and Lunn, D. (2003). WinBUGS User Manual, MRC Biostatistics Unit."},{"key":"ref_65","unstructured":"Lunn, D., Spiegelhalter, D., Thomas, A., and Best, N. (2018, June 25). OpenBUGS license. Available online: http:\/\/www.openbugs.net\/w\/Downloads."},{"key":"ref_66","unstructured":"Sturtz, S., Ligges, U., and Gelman, A. (2010). R2OpenBUGS: A Package for Running OpenBUGS from R., Journal of Statistical Software."},{"key":"ref_67","unstructured":"Team, R.D.C. (2013). R: A Language and Environment for Statistical Computing, The R Foundation for Statistical Computing."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"998","DOI":"10.1046\/j.1365-3156.2001.00798.x","article-title":"Predicting the distribution of urinary schistosomiasis in Tanzania using satellite sensor data","volume":"6","author":"Brooker","year":"2001","journal-title":"Trop. Med. Int. Health"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/S0001-706X(01)00104-8","article-title":"Use of satellite remote sensing and geographic information systems to model the distribution and abundance of snail intermediate hosts in Africa: A preliminary model for Biomphalaria pfeifferi in Ethiopia","volume":"79","author":"Kristensen","year":"2001","journal-title":"Acta Trop."},{"key":"ref_70","first-page":"175","article-title":"Using NOAA-AVHRR data to model human helminth distributions in planning disease control in Cameroon, West Africa","volume":"68","author":"Brooker","year":"2002","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/S0001-706X(01)00103-6","article-title":"Satellite climatology and the environmental risk of Schistosoma mansoni in Ethiopia and east Africa","volume":"79","author":"Malone","year":"2001","journal-title":"Acta Trop."},{"key":"ref_72","unstructured":"(2018, October 18). Rice Science for a Better World. Available online: http:\/\/irri.org\/our-work\/research\/policy-and-markets\/mapping-rice-in-the-philippines-where."},{"key":"ref_73","first-page":"115","article-title":"Modeling the distribution of Schistosoma mansoni and host snails in Uganda using satellite sensor data and Geographical Information Systems","volume":"47","author":"Stensgaard","year":"2005","journal-title":"Parassitologia"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1160","DOI":"10.1289\/ehp.1308062","article-title":"Evaluating Uncertainty to Strengthen Epidemiologic Data for Use in Human Health Risk Assessments","volume":"122","author":"Burns","year":"2014","journal-title":"Environ. Health Perspect."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"e1194","DOI":"10.1371\/journal.pntd.0001194","article-title":"Geostatistical Model-Based Estimates of Schistosomiasis Prevalence among Individuals Aged <= 20 Years in West Africa","volume":"5","author":"Schur","year":"2011","journal-title":"PLoS Negl. Trop. Dis."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1016\/j.actatropica.2011.10.006","article-title":"Spatially explicit Schistosoma infection risk in eastern Africa using Bayesian geostatistical modelling","volume":"128","author":"Schur","year":"2013","journal-title":"Acta Trop."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"1683","DOI":"10.1017\/S0031182009006222","article-title":"Remote sensing, geographical information system and spatial analysis for schistosomiasis epidemiology and ecology in Africa","volume":"136","author":"Simoonga","year":"2009","journal-title":"Parasitology"},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 817\u2013838.","DOI":"10.2307\/1912934"},{"key":"ref_79","unstructured":"Fox, J. (1997). Applied Regression Analysis, Linear Models, and Related Methods, Sage Publications, Inc."},{"key":"ref_80","first-page":"1645","article-title":"A Quick Refresher Course in Macroeconomics","volume":"28","author":"Mankiw","year":"1990","journal-title":"J. Econ. Lit."}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/16\/2\/176\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:24:43Z","timestamp":1760185483000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/16\/2\/176"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,9]]},"references-count":80,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2019,1]]}},"alternative-id":["ijerph16020176"],"URL":"https:\/\/doi.org\/10.3390\/ijerph16020176","relation":{},"ISSN":["1660-4601"],"issn-type":[{"type":"electronic","value":"1660-4601"}],"subject":[],"published":{"date-parts":[[2019,1,9]]}}}