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Application of geo-spatial technology in schistosomiasis modelling in Africa: a review

Tawanda Manyangadze, Moses John Chimbari, Michael Gebreslasie, Samson Mukaratirwa

04-11-2015

https://doi.org/10.4081/gh.2015.326

4003

PDF: 2089

HTML: 2145
Assessing effects of structural zeros on models of canine cancer incidence: a case study of the Swiss Canine Cancer Registry

Gianluca Boo, Stefan Leyk, Sara Irina Fabrikant, Andreas Pospischil, Ramona Graf

11-05-2017

https://doi.org/10.4081/gh.2017.539

3252

PDF: 1049

HTML: 815
A review of spatial technologies with applications for malaria transmission modelling and control in Africa

Michael T. Gebreslasie

26-11-2015

https://doi.org/10.4081/gh.2015.328

5845

PDF: 2308

HTML: 3062
Modelling the presence of disease under spatial misalignment using Bayesian latent Gaussian models

Xavier Barber, David Conesa, Silvia Lladosa, Antonio Lòpez-Quílez

18-04-2016

https://doi.org/10.4081/gh.2016.415

3341

PDF: 1612

HTML: 2222
Comparison of single- and multi-scale models for the prediction of the Culicoides biting midge distribution in Germany

Renke Lühken, Jörn Martin Gethmann, Petra Kranz, Pia Steffenhagen, Christoph Staubach, Franz J. Conraths, Ellen Kiel

31-05-2016

https://doi.org/10.4081/gh.2016.405

3073

PDF: 955

HTML: 1457
Spatial air pollution modelling for a West-African town

Sirak Zenebe Gebreab, Danielle Vienneau, Christian Feigenwinter, HampÃ¢té BÃ¢, Guéladio Cissé, Ming-Yi Tsai

26-11-2015

https://doi.org/10.4081/gh.2015.321

3457

PDF: 1366

SUPPL. MATERIAL: 387

HTML: 1078
Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa

Thandi Kapwata, Michael T. Gebreslasie

16-11-2016

https://doi.org/10.4081/gh.2016.434

3809

PDF: 1470

APPENDIX 1: 405

APPENDIX 2: 392

HTML: 1637
Predicting the spatial distribution of Biomphalaria straminea, a potential intermediate host for Schistosoma mansoni, in China

Mohamed R. Habib, Yun-Hai Guo, Shan Lv, Wen-Biao Gu, Xiao-Heng Li, Xiao-Nong Zhou

29-11-2016

https://doi.org/10.4081/gh.2016.453

3685

PDF: 1249

HTML: 1130
Validation of a spatial liver fluke model under field conditions in Ireland

Amalia Naranjo Lucena, María Pía Munita Corbalán, Ana María Martínez-Ibeas, Guy McGrath, Riona Sayers, Grace Mulcahy, Annetta Zintl

07-05-2018

https://doi.org/10.4081/gh.2018.641

2136

PDF: 885

HTML: 127
Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling

Yvonne Walz, Martin Wegmann, Benjamin Leutner, Stefan Dech, Penelope Vounatsou, Eliézer K. N'Goran, Giovanna Raso, Jürg Utzinger

30-11-2015

https://doi.org/10.4081/gh.2015.398

4094

PDF: 1087

HTML: 1196
Assessing the effects of air temperature and rainfall on malaria incidence: an epidemiological study across Rwanda and Uganda

Felipe J. Colòn-González, Adrian M. Tompkins, Riccardo Biondi, Jean Pierre Bizimana, Didacus Bambaiha Namanya

31-03-2016

https://doi.org/10.4081/gh.2016.379

5891

PDF: 2077

Appendix: 539

HTML: 3235

Appendix: 189
Validation of an interactive map assessing the potential spread of Galba truncatula as intermediate host of Fasciola hepatica in Switzerland

Rhea Baggenstos, Tobias Dahinden, Paul R. Torgerson, Hansruedi Bär, Christina Rapsch, Gabriela Knubben-Schweizer

31-05-2016

https://doi.org/10.4081/gh.2016.418

2018

PDF: 918

HTML: 1002
Geostatistical modelling of the malaria risk in Mozambique: effect of the spatial resolution when using remotely-sensed imagery

Federica Giardina, Jonas Franke, Penelope Vounatsou

26-11-2015

https://doi.org/10.4081/gh.2015.333

3415

PDF: 1409

HTML: 1177
Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty

Joseph Leedale, Adrian M. Tompkins, Cyril Caminade, Anne E. Jones, Grigory Nikulin, Andrew P. Morse

31-03-2016

https://doi.org/10.4081/gh.2016.393

4006

PDF: 1599

HTML: 2541
A dynamic, climate-driven model of Rift Valley fever

Joseph Leedale, Anne E. Jones, Cyril Caminade, Andrew P. Morse

31-03-2016

https://doi.org/10.4081/gh.2016.394

4198

PDF: 1612

Appendix: 481

HTML: 1576
Comparison of the spatial patterns of schistosomiasis in Zimbabwe at two points in time, spaced twenty-nine years apart: is climate variability of importance?

Ulrik B. Pedersen, Dimitrios-Alexios Karagiannis-Voules, Nicholas Midzi, Tkafira Mduluza, Samson Mukaratirwa, Rasmus Fensholt, Birgitte J. Vennervald, Thomas K. Kristensen, Penelope Vounatsou, Anna-Sofie Stensgaard

08-05-2017

https://doi.org/10.4081/gh.2017.505

3070

PDF: 1337

HTML: 1025
Interpreting predictive maps of disease: highlighting the pitfalls of distribution models in epidemiology

Nicola A. Wardrop, Matthew Geary, Patrick E. Osborne, Peter M. Atkinson

237-246

01-11-2014

https://doi.org/10.4081/gh.2014.397

2084

PDF: 885
Geostatistical integration and uncertainty in pollutant concentration surface under preferential sampling

Laura Grisotto, Dario Consonni, Lorenzo Cecconi, Dolores Catelan, Corrado Lagazio, Pier Alberto Bertazzi, Michela Baccini, Annibale Biggeri

18-04-2016

https://doi.org/10.4081/gh.2016.426

2104

PDF: 1475

HTML: 1139
Climate change and species distribution: possible scenarios for thermophilic ticks in Romania

Cristian DomÈ™a, Attila D. Sándor, Andrei D. Mihalca

31-05-2016

https://doi.org/10.4081/gh.2016.421

2700

PDF: 1232

HTML: 1673
Zoning the territory of the Republic of Kazakhstan as to the risk of rabies among various categories of animals

Sarsenbay K. Abdrakhmanov, Akhmetzhan A. Sultanov, Kanatzhan K. Beisembayev, Fedor I. Korennoy, Dosym B. Ðšushubaev, Ablaikhan S. ÐšÐ°dyrov

31-05-2016

https://doi.org/10.4081/gh.2016.429

2534

PDF: 1111

APPENDIX: 578

HTML: 1441
Preferential sampling in veterinary parasitological surveillance

Lorenzo Cecconi, Annibale Biggeri, Laura Grisotto, Veronica Berrocal, Laura Rinaldi, Vincenzo Musella, Giuseppe Cringoli, Dolores Catelan

18-04-2016

https://doi.org/10.4081/gh.2016.412

1933

PDF: 1430

APPENDIX: 526

HTML: 1032
Ecological characterization of a cutaneous leishmaniasis outbreak through remotely sensed land cover changes

Verónica Andreo, Juan Rosa, Karina Ramos, O. Daniel Salomón

06-05-2022

https://doi.org/10.4081/gh.2022.1033

1473

PDF: 671

Appendix: 95

HTML: 30
Modelling of the distribution of Biomphalaria glabrata and Biomphalaria straminea in the metropolitan region of Recife, Pernambuco, Brazil

Verônica Santos Barbosa, Ricardo José de Paula Souza e Guimarães, Rodrigo Moraes Loyo, Constança SimÃµes Barbosa

25-11-2016

https://doi.org/10.4081/gh.2016.490

2696

PDF: 1077

HTML: 1598
Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution

Yazmin Alcala-Canto, Juan Antonio Figueroa-Castillo, Froylán Ibarra-Velarde, Yolanda Vera-Montenegro, María Eugenia Cervantes-Valencia, Abdelfattah Z.M. Salem, Jorge Alfredo Cuéllar-Ordaz

07-05-2018

https://doi.org/10.4081/gh.2018.624

4155

PDF: 1031

HTML: 251
Spatial pattern evolution of Aedes aegypti breeding sites in an Argentinean city without a dengue vector control programme

Manuel O. Espinosa, Francisco Polop, Camilo H. Rotela, Marcelo Abril, Carlos M. Scavuzzo

21-11-2016

https://doi.org/10.4081/gh.2016.471

3635

PDF: 1240

APPENDIX: 465

HTML: 1532
Understanding the spatial non-stationarity in the relationships between malaria incidence and environmental risk factors using Geographically Weighted Random Forest: A case study in Rwanda

Gilbert Nduwayezu, Pengxiang Zhao, Clarisse Kagoyire, Lina Eklund, Jean Pierre Bizimana, Petter Pilesjo, Ali Mansourian

25-05-2023

https://doi.org/10.4081/gh.2023.1184

2178

PDF: 1171

HTML: 133
Combining process-based and correlative models improves predictions of climate change effects on Schistosoma mansoni transmission in eastern Africa

Anna-Sofie Stensgaard, Mark Booth, Grigory Nikulin, Nicky McCreesh

31-03-2016

https://doi.org/10.4081/gh.2016.406

3746

PDF: 1284

HTML: 1054
Health, environmental change and adaptive capacity; mapping, examining and anticipating future risks of water-related vector-borne diseases in eastern Africa

David Taylor, Stefan Kienberger, Jack B. Malone, Adrian M. Tompkins

18-02-2016

https://doi.org/10.4081/gh.2016.464

3329

PDF: 1447

HTML: 1100
Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia

Hassan M. Khormi, Lalit Kumar

21-11-2016

https://doi.org/10.4081/gh.2016.416

5092

PDF: 2266

HTML: 1978
Environmental modelling of visceral leishmaniasis by susceptibility-mapping using neural networks: a case study in north-western Iran

Mohammadreza Rajabi, Ali Mansourian, Petter Pilesjö, Ahad Bazmani

179-191

01-11-2014

https://doi.org/10.4081/gh.2014.15

7063

PDF: 1382
From Snow’s map of cholera transmission to dynamic catchment boundary delineation: current front lines in spatial analysis

Behzad Kiani, Colleen Lau, Robert Bergquist

26-10-2023

https://doi.org/10.4081/gh.2023.1247

1353

PDF: 602

HTML: 22
Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate variables and impact machine learning

Alireza Mohammadi, Bardia Mashhoodi, Ali Shamsoddini, Elahe Pishgar, Robert Bergquist

26-03-2025

https://doi.org/10.4081/gh.2025.1319

1433

PDF: 265

HTML: 49
Spatial distribution and sociodemographic risk factors of malaria in Nigerian children less than 5 years old

Chigozie Louisa J. Ugwu, Temesgen Zewotir

29-12-2020

https://doi.org/10.4081/gh.2020.819

3228

PDF: 1502

HTML: 590
Does mobility restriction significantly control infectious disease transmission? Accounting for non-stationarity in the impact of COVID-19 based on Bayesian spatially varying coefficient models

I Gede Nyoman Mindra Jaya, Anna Chadidjah, Farah Kristiani, Gumgum Darmawan, Jane Christine Princidy

25-05-2023

https://doi.org/10.4081/gh.2023.1161

1032

PDF: 399

HTML: 10
Impacts of sample ratio and size on the performance of random forest model to predict the potential distribution of snail habitats

Yuanhua Liu, Jun Zhang, Michael P. Ward, Wei Tu, Lili Yu, Jin Shi, Yi Hu, Fenghua Gao, Zhiguo Cao, Zhijie Zhang

03-07-2023

https://doi.org/10.4081/gh.2023.1151

1730

PDF: 631

Supplementary Materials: 69

HTML: 35
The spatial distribution of Schistosoma mansoni infection in four regions of western Côte d'Ivoire

Rufin K. Assaré, Ying-Si Lai, Ahoua Yapi, Yves-Nathan T. Tian-Bi, Mamadou Ouattara, Patrick K. Yao, Stefanie Knopp, Penelope Vounatsou, Jürg Utzinger, Eliézer K. N'Goran

03-06-2015

https://doi.org/10.4081/gh.2015.345

3849

PDF: 1591

HTML: 1230
Geospatial Health: achievements, innovations, priorities

Sherif Amer, Ellen-Wien Augustijn, Carmen Anthonj, Nils Tjaden, Justine Blanford, Marc van den Homberg, Laura Rinaldi, Thomas van Rompay, Raúl Zurita Milla

25-10-2024

https://doi.org/10.4081/gh.2024.1355

1488

PDF: 464

HTML: 95
Prediction of dengue cases using the attention-based long short-term memory (LSTM) approach

Mokhalad A. Majeed, Helmi Z. M. Shafri, Aimrun Wayayok, Zed Zulkafli

25-05-2023

https://doi.org/10.4081/gh.2023.1176

1650

PDF: 792

Supplementary Materials: 99

HTML: 31
Environmental and socio-economic risk modelling for Chagas disease in Bolivia

Paula Mischler, Michael Kearney, Jennifer C. McCarroll, Ronaldo G.C. Scholte, Penelope Vounatsou, John B. Malone

S59-S66

01-09-2012

https://doi.org/10.4081/gh.2012.123

3376

PDF: 1132
Mapping and prediction of schistosomiasis in Nigeria using compiled survey data and Bayesian geospatial modelling

Uwem F. Ekpo, Eveline Hürlimann, Nadine Schur, Akinola. S. Oluwole, Eniola M. Abe, Margaret A. Mafe, Obiageli J. Nebe, Sunday Isiyaku, Francisca Olamiju, Mukaila Kadiri, Temitope O.S. Poopola, Eka I. Braide, Yisa Saka, Chiedu F. Mafiana, Thomas K. Kristensen, Jürg Utzinger, Penelope Vounatsou

355-366

01-05-2013

https://doi.org/10.4081/gh.2013.92

5020

PDF: 1803
FleaTickRisk: a meteorological model developed to monitor and predict the activity and density of three tick species and the cat flea in Europe

Frédéric Beugnet, Karine Chalvet-Monfray, Harilaos Loukos

97-113

01-11-2009

https://doi.org/10.4081/gh.2009.213

2558

PDF: 961
Post-pandemic COVID-19 estimated and forecasted hotspots in the Association of Southeast Asian Nations (ASEAN) countries in connection to vaccination rate

I Gede Nyoman Mindra Jaya, Yudhie Andriyana, Bertho Tantular

22-03-2022

https://doi.org/10.4081/gh.2022.1070

1197

PDF: 340

HTML: 31
Application of decision tree for prediction of cutaneous leishmaniasis incidence based on environmental and topographic factors in Isfahan Province, Iran

Roghieh Ramezankhani, Nooshin Sajjadi, Roya Nezakati Esmaeilzadeh, Seyed Ali Jozi, Mohammad Reza Shirzadi

08-05-2018

https://doi.org/10.4081/gh.2018.664

1601

PDF: 753

HTML: 157
Using object-based image analysis to map commercial poultry operations from high resolution imagery to support animal health outbreaks and events

Susan Maroney, MaryJane McCool-Eye, Andrew Fox, Christopher Burdett

10-12-2020

https://doi.org/10.4081/gh.2020.919

2302

PDF: 719

HTML: 94
Prehistoric human migrations: a prospective subject for modelling using geographical information systems

Robert Bergquist

25-05-2023

https://doi.org/10.4081/gh.2023.1210

1160

PDF: 375

HTML: 25
Spatial and temporal dynamic analysis of rabies: A review of current methodologies

Shuaicheng Chen

30-11-2022

https://doi.org/10.4081/gh.2022.1139

2056

PDF: 1291

HTML: 233
Climate impact on malaria in northern Burkina Faso

Yves M. Tourre, Cécile Vignolles, Christian Viel, Flore Mounier

27-11-2017

https://doi.org/10.4081/gh.2017.600

2420

PDF: 766

HTML: 725
Assessing the relationship between environmental factors and malaria vector breeding sites in Swaziland using multi-scale remotely sensed data

Sabelo Nick Dlamini, Jonas Franke, Penelope Vounatsou

03-06-2015

https://doi.org/10.4081/gh.2015.302

3900

PDF: 1564

HTML: 1739
A breeding site model for regional, dynamical malaria simulations evaluated using in situ temporary ponds observations

Ernest O. Asare, Adrian M. Tompkins, Leonard K. Amekudzi, Volker Ermert

31-03-2016

https://doi.org/10.4081/gh.2016.390

2511

PDF: 986

HTML: 1096
Estimating malaria burden in Nigeria: a geostatistical modelling approach

Nnadozie Onyiri

04-11-2015

https://doi.org/10.4081/gh.2015.306

6993

PDF: 2834

HTML: 3245
Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models

Ronaldo G. C. Scholte, Nadine Schur, Maria E. Bavia, Edgar M. Carvalho, Frédérique Chammartin, Jürg Utzinger, Penelope Vounatsou

97-110

01-11-2013

https://doi.org/10.4081/gh.2013.58

3461

PDF: 1801
Analytical report of the 2016 dengue outbreak in CÃ³rdoba city, Argentina

Camilo Rotela, Laura Lopez, María Frías Céspedes, Gabriela Barbas, Andrés Lighezzolo, Ximena Porcasi, Mario A. Lanfri, Carlos M. Scavuzzo, David E. Gorla

06-11-2017

https://doi.org/10.4081/gh.2017.564

3112

PDF: 1160

HTML: 850
Mapping and modelling the geographical distribution of soil-transmitted helminthiases in Peninsular Malaysia: implications for control approaches

Romano Ngui, Aziz Shafie, Kek H. Chua, Mohd S. Mistam, Hesham M. Al-Mekhlafi, Wan W. W. Sulaiman, Rohela Mahmud, Yvonne A. L. Lim

365-376

01-05-2014

https://doi.org/10.4081/gh.2014.26

4142

PDF: 1150
Satellite imaging and vector-borne diseases: the approach of the French National Space Agency (CNES)

Fabienne Marechal, Nathalie Ribeiro, Murielle Lafaye, Antonio Güell

1-5

01-11-2008

https://doi.org/10.4081/gh.2008.226

2279

PDF: 989
Climate and the distribution of vector-borne diseases: what's in store?

Robert Bergquist

08-05-2017

https://doi.org/10.4081/gh.2017.549

3106

PDF: 1162

HTML: 841
Impact of the COVID-19 pandemic on the number of births in Pernambuco Brazil

Heitor Victor Veiga da Costa, Cristine Vieira do Bonfim, Wilson Fusco, Morvan de Melo Moreira, Fernando Maciano de Paula Neto

15-06-2022

https://doi.org/10.4081/gh.2022.1069

870

PDF: 363

HTML: 48
Spatial prediction of the risk of exposure to Echinococcus spp. among schoolchildren and dogs in Ningxia Hui Autonomous Region, People's Republic of China

Angela M. Cadavid Restrepo, Yu Rong Yang, Donald P. McManus, Darren J. Gray, Tamsin S. Barnes, Gail M. Williams, Ricardo J. Soares Magalhães, Archie C.A. Clements

07-05-2018

https://doi.org/10.4081/gh.2018.644

1912

PDF: 755

HTML: 79
Effects of geographical factors on reference values of the thyroid stimulating hormone in healthy adults in China and its clinical significance

Xinrui Pang, Miao Ge, Congxia Wang, Jinwei He

06-05-2022

https://doi.org/10.4081/gh.2022.1030

1013

PDF: 421

HTML: 203
Vector-borne diseases in a warmer world: Will they stay or will they go?

Robert Bergquist, Anna-Sofie Stensgaard, Laura Rinaldi

07-05-2018

https://doi.org/10.4081/gh.2018.699

2465

PDF: 1100

HTML: 210
Bayesian modelling of geostatistical malaria risk data

L. Gosoniu, P. Vounatsou, N. Sogoba, T. Smith

127-139

01-11-2006

https://doi.org/10.4081/gh.2006.287

8510

PDF: 1529
Study of the variation of schistosomiasis risk in Lake Poyang in the People's Republic of China using multiple space-borne sensors for monitoring and modelling

Kuo-Hsin Tseng, Song Liang, Motomu Ibaraki, Hyongki Lee, C. K. Shum

353-364

01-05-2014

https://doi.org/10.4081/gh.2014.25

1499

PDF: 905
Comparison of data-fitting models for schistosomiasis: a case study in Xingzi, China

Yi Hu, Cheng-Long Xiong, Zhi-Jie Zhang, Robert Bergquist, Zeng-Liang Wang, Jie Gao, Rui Li, Bo Tao, Qiu-Lin Jiang, Qingwu Jiang

125-132

01-11-2013

https://doi.org/10.4081/gh.2013.60

2484

PDF: 851
Climate-based risk models for Fasciola hepatica in Colombia

Natalia Valencia-Lòpez, John B. Malone, Catalina Gòmez Carmona, Luz E. Velásquez

S75-S85

01-09-2012

https://doi.org/10.4081/gh.2012.125

2717

PDF: 1287
Systematic errors in temperature estimates from MODIS data covering the western Palearctic and their impact on a parasite development model

Jorge Alonso-Carné, Alberto García-Martín, Agustin Estrada-Peña

1-12

01-11-2013

https://doi.org/10.4081/gh.2013.49

1213

PDF: 676
Use of soil moisture active passive satellite data and WorldClim 2.0 data to predict the potential distribution of visceral leishmaniasis and its vector Lutzomyia longipalpis in Sao Paulo and Bahia states, Brazil

Moara de Santana Martins Rodgers, Elivelton Fonseca, Prixia del Mar Nieto, John B. Malone, Jeffery C. Luvall, Jennifer C. McCarroll, Ryan Harry Avery, Maria Emilia Bavia, Raul Guimaraes, Xue Wen, Marta Mariana Nascimento Silva, Deborah D.M.T. Carneiro, Luciana Lobato Cardim

08-06-2022

https://doi.org/10.4081/gh.2022.1095

1322

PDF: 734

HTML: 43
Spatial association between COVID-19 incidence rate and nighttime light index

Amornrat Luenam, Nattapong Puttanapong

18-03-2022

https://doi.org/10.4081/gh.2022.1066

1592

PDF: 460

HTML: 80
Role of malnutrition and parasite infections in the spatial variation in children's anaemia risk in northern Angola

Ricardo J. Soares Magalhães, Antonio Langa, João Mário Pedro, José Carlos Sousa-Figueiredo, Archie C.A. Clements, Susana Vaz Nery

341-354

01-05-2013

https://doi.org/10.4081/gh.2013.91

3746

PDF: 1717
A conceptional model integrating geographic information systems (GIS) and social media data for disease exposure assessment

Jerry Enoe , Michael Sutherland, Dexter Davis, Bheshem Ramlal, Charisse Griffith-Charles , Keston H. Bhola, Elsai Mati Asefa

28-03-2024

https://doi.org/10.4081/gh.2024.1264

2420

PDF: 573

HTML: 62
Spatial analysis of the AIDS mortality rate among young people in a province of the Brazilian Amazon: An ecological study

Sara Melissa Lago Sousa, Andrey Oeiras Pedroso , Iaron Leal Seabra , Glenda Roberta Oliveira Naiff Ferreira, Aline Maria Pereira Cruz Ramos , Sandra Helena Isse Polaro, Eliã Pinheiro Botelho

29-11-2022

https://doi.org/10.4081/gh.2022.1102

763

PDF: 647

HTML: 14
Understanding COVID-19: comparison of spatio-temporal analysis methods used to study epidemic spread patterns in the United States

Chunhui Liu, Xiaodi Su, Zhaoxuan Dong, Xingyu Liu, Chunxia Qiu

25-05-2023

https://doi.org/10.4081/gh.2023.1200

979

PDF: 499

HTML: 49
A geographical information system model to define COVID-19 problem areas with an analysis in the socio-economic context at the regional scale in the North of Spain

Olga De Cos, Valentín Castillo-Salcines, David Cantarero-Prieto

18-03-2022

https://doi.org/10.4081/gh.2022.1067

1417

PDF: 399

HTML: 34
Dynamic risk model for Rift Valley fever outbreaks in Kenya based on climate and disease outbreak data

David Gikungu, Jacob Wakhungu, Donald Siamba, Edward Neyole, Richard Muita, Bernard Bett

31-05-2016

https://doi.org/10.4081/gh.2016.377

2933

PDF: 1247

HTML: 1421
Spatial analysis for the epidemiological study of cardiovascular diseases: A systematic literature search

Carlos Mena, Cesar Sepúlveda, Eduardo Fuentes, Yony Ormazábal, Iván Palomo

07-05-2018

https://doi.org/10.4081/gh.2018.587

4810

PDF: 2188

HTML: 731
How much incident lung cancer was missed globally in 2012? An ecological country-level study

Benn Sartorius, Kurt Sartorius

31-05-2016

https://doi.org/10.4081/gh.2016.396

2382

PDF: 1167

HTML: 1025
Vulnerability to COVID-19 in Pernambuco, Brazil: A geospatial evaluation supported by multiple-criteria decision aid methodology

Ciro José Jardim de Figueiredo, Caroline Maria de Miranda Mota, Amanda Gadelha Ferreira Rosa, Arthur Pimentel Gomes de Souza, Simone Maria da Silva Lima

14-01-2022

https://doi.org/10.4081/gh.2022.1000

2304

PDF: 355

HTML: 43
Dynamic effect of economic growth on the persistence of suicide rates

Tzu-Yi Yang, Yu-Tai Yang, Ssu-Han Chen, Yu-Ting Lan, Chia-Jui Peng

25-05-2023

https://doi.org/10.4081/gh.2023.1201

662

PDF: 407

HTML: 12
Measuring neighborhood deprivation for childhood health and development - scale implications in rural and urban context

Alexandra Ursache, Seann Regan, Allison De Marco, Dustin T. Duncan, The Family Life Project Key Investigators

11-03-2021

https://doi.org/10.4081/gh.2021.926

2423

PDF: 822

HTML: 50
The future of spatial epidemiology in the AI era: enhancing machine learning approaches with explicit spatial structure

Nima Kianfar, Benn Sartorius, Colleen L. Lau, Robert Bergquist, Behzad Kiani

04-06-2025

https://doi.org/10.4081/gh.2025.1386

298

PDF: 64
The use of geographic information system as a tool for schistosomiasis surveillance in the province of Davao del Norte, the Philippines

Vicente Y. Belizario, John Paul Caesar R. delos Trinos, Berne Silawan, Chiqui M. De Veyra, Agapito Hornido, Hansel Amoguis, Dominic Basalo, Cherry Dema-ala, Irenn Mantilla, Rosele Layan

06-11-2017

https://doi.org/10.4081/gh.2017.540

6908

PDF: 1717

HTML: 2081
Spatial analysis of the prevalence of schistosomiasis in an endemic coastal area in north-eastern Brazil

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