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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

4023

PDF: 2111

HTML: 2152
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

3825

PDF: 1504

APPENDIX 1: 414

APPENDIX 2: 401

HTML: 1638
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

3706

PDF: 1272

HTML: 1132
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

3260

PDF: 1055

HTML: 816
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

5925

PDF: 2093

Appendix: 546

HTML: 3239

Appendix: 196
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

579

PDF: 141

HTML: 0
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

3661

PDF: 1263

APPENDIX: 477

HTML: 1533
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

2503

PDF: 870
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

4174

PDF: 1049

HTML: 253
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

3094

PDF: 963

HTML: 1457
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

1227

PDF: 355

HTML: 31
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

1486

PDF: 688

Appendix: 102

HTML: 30
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

3357

PDF: 1629

HTML: 2222
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

2560

PDF: 1125

APPENDIX: 583

HTML: 1441
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

1581

PDF: 303

HTML: 72
Environmental and geographical factors influence malaria transmission in KwaZulu-Natal province, South Africa

Osadolor Ebhuoma, Michael Gebreslasie, Oswaldo Villena, Ali Arab

09-06-2025

https://doi.org/10.4081/gh.2025.1370

404

PDF: 91

HTML: 4
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

2208

PDF: 1190

HTML: 136
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

1744

PDF: 667

Supplementary Materials: 78

HTML: 37
Modeling the distribution of Culex tritaeniorhynchus to predict Japanese encephalitis distribution in the Republic of Korea

Penny Masuoka, Terry A. Klein, Heung-Chul Kim, David M. Claborn, Nicole Achee, Richard Andre, Judith Chamberlin, Jennifer Small, Assaf Anyamba, Dong-Kyu Lee, Suk H. Yi, Michael Sardelis, Young-Ran Ju, John Grieco

45-57

01-11-2010

https://doi.org/10.4081/gh.2010.186

2912

PDF: 1239
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

3254

PDF: 1533

HTML: 608
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

4233

PDF: 1636

Appendix: 487

HTML: 1576
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

2725

PDF: 1094

HTML: 1599
Geographic distribution of canine heartworm (Dirofilaria immitis) infection in stray dogs of eastern Romania

Lavinia CiucÄƒ, Vincenzo Musella, Liviu D. Miron, Maria Paola Maurelli, Giuseppe Cringoli, Antonio Bosco, Laura Rinaldi

21-11-2016

https://doi.org/10.4081/gh.2016.499

4150

PDF: 1474

HTML: 2238
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

1617

PDF: 768

HTML: 158
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

3780

PDF: 1301

HTML: 1054
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

1345

PDF: 754

HTML: 44
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

2732

PDF: 1250

HTML: 1673
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

3086

PDF: 1361

HTML: 1025
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

3488

PDF: 1401

SUPPL. MATERIAL: 395

HTML: 1078
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

4033

PDF: 1610

HTML: 2541
Spatial patterns of intestinal parasite infections among children and adolescents in some indigenous communities in Argentina

Carlos Matías Scavuzzo, Micaela Natalia Campero, Rosana Elizabeth Maidana, María Georgina Oberto, María Victoria Periago, Ximena Porcasi

28-05-2024

https://doi.org/10.4081/gh.2024.1279

2310

PDF: 493

HTML: 76
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

2541

PDF: 1012

HTML: 1096
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

1008

PDF: 523

HTML: 49
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

3136

PDF: 1179

HTML: 850
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

1052

PDF: 410

HTML: 10
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

5117

PDF: 2288

HTML: 1979
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

2126

PDF: 1499

HTML: 1139
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

2443

PDF: 590

HTML: 62
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

1615

PDF: 482

HTML: 82
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

2093

PDF: 1316

HTML: 240
Estimating malaria burden in Nigeria: a geostatistical modelling approach

Nnadozie Onyiri

04-11-2015

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

7018

PDF: 2859

HTML: 3246
Ecological niche modeling for visceral leishmaniasis in the state of Bahia, Brazil, using genetic algorithm for rule-set prediction and growing degree day-water budget analysis

Prixia Nieto, John B. Malone, Maria E. Bavia

115-126

01-11-2006

https://doi.org/10.4081/gh.2006.286

1786

PDF: 795
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

2954

PDF: 1268

HTML: 1423
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

4128

PDF: 1110

HTML: 1196
The effects of vegetation density and habitat disturbance on the spatial distribution of ixodid ticks (Acari: Ixodidae)

Kenneth J. Stein, Megan Waterman, Jefferson L. Waldon

241-252

01-05-2008

https://doi.org/10.4081/gh.2008.247

2068

PDF: 1245
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

3883

PDF: 1608

HTML: 1231
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

1929

PDF: 770

HTML: 80
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

1971

PDF: 1444

APPENDIX: 532

HTML: 1032
Spatio-temporal trends and distribution patterns of typhoid disease in Uganda from 2012 to 2017

Kamukama Ismail, Gilbert Maiga, Denis Ssebuggwawo, Peter Nabende, Ali Mansourian

07-01-2021

https://doi.org/10.4081/gh.2020.860

2908

PDF: 916

HTML: 23
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

4837

PDF: 2225

HTML: 734
Dengue risk-mapping in an Amazonian locality in Colombia based on regression and multi-criteria analysis

Maria Camila Lesmes , Alvaro Ávila-Díaz, Erika Santamaría, Carlos Andrés Morales , Horacio Cadena, Patricia Fuya, Nicolas Frutos, Ximena Porcasi, Catalina Marceló-Díaz

04-06-2025

https://doi.org/10.4081/gh.2025.1292

509

PDF: 169

HTML: 3
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

5882

PDF: 2346

HTML: 3065
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

892

PDF: 388

HTML: 48
Spatial-temporal risk factors in the occurrence of rabies in Mexico

Reyna Ortega-Sánchez, Isabel Bárcenas-Reyes, Jesús Luna-Cozar, Edith Rojas-Anaya, José Quintín Cuador-Gil, Germinal Jorge Cantó-Alarcón, Nerina Veyna-Salazar, Sara González-Ruiz, Feliciano Milián-Suazo

30-01-2024

https://doi.org/10.4081/gh.2024.1245

3788

PDF: 1025

HTML: 755
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

1381

PDF: 623

HTML: 22
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

2452

PDF: 782

HTML: 726
Geographical distribution and spatio-temporal patterns of hospitalization due to dengue infection at a leading specialist hospital in Malaysia

Gary K.K. Low, Panayoti Papapreponis, Ridzuan M. Isa, Seng Chiew Gan, Hui Yee Chee, Kian Keong Te, Nadia M. Hatta

07-05-2018

https://doi.org/10.4081/gh.2018.642

2215

PDF: 876

APPENDIX: 387

HTML: 103
Associations between seasonal influenza and meteorological parameters in Costa Rica, Honduras and Nicaragua

Radina P. Soebiyanto, Wilfrido A. Clara, Jorge Jara, Angel Balmaseda, Jenny Lara, Mariel Lopez Moya, Rakhee Palekar, Marc-Alain Widdowson, Eduardo Azziz-Baumgartner, Richard K. Kiang

04-11-2015

https://doi.org/10.4081/gh.2015.372

4212

PDF: 1362

HTML: 1161
Haemodialysis services in the northeastern region of Iran

Behzad Kiani, Nasser Bagheri, Ahmad Tara, Benyamin Hoseini, Mahmoud Tara

11-05-2017

https://doi.org/10.4081/gh.2017.561

3935

PDF: 1045

HTML: 901
Spatial distribution and identifying biochemical factors affecting haemoglobin levels among women of reproductive age for each province in Indonesia: A geospatial analysis

Muhammad Nur Aidi, Fitrah Ernawati, Efriwati Efriwati, Nunung Nurjanah, Rika Rachmawati, Elisa Diana Julianti, Dian Sundari, Fifi Retiaty, Anwar Fitrianto, Khalilah Nurfadilah, Aya Yuriestia Arifin

30-11-2022

https://doi.org/10.4081/gh.2022.1118

1820

PDF: 825

HTML: 56
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

2328

PDF: 373

HTML: 43

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