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Risk map for cutaneous leishmaniasis in Ethiopia based on environmental factors as revealed by geographical information systems and statistics

Ahmed Seid, Endalamaw Gadisa, Teshome Tsegaw, Adugna Abera, Aklilu Teshome, Abate Mulugeta, Merce Herrero, Daniel Argaw, Alvar Jorge, Asnakew Kebede, Abraham Aseffa

377-387

01-05-2014

https://doi.org/10.4081/gh.2014.27

6718

PDF: 2804
Spatial distribution of soil-transmitted helminths, including Strongyloides stercoralis, among children in Zanzibar

Stefanie Knopp, Khalfan A. Mohammed, I. Simba Khamis, Ali F. Mgeni, J. Russell Stothard, David Rollinson, Hanspeter Marti, Jürg Utzinger

47-56

01-11-2008

https://doi.org/10.4081/gh.2008.231

3517

PDF: 1377
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

3417

PDF: 1604

HTML: 1040
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

2313

PDF: 643

HTML: 79
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

1551

PDF: 730

HTML: 70
Immunity to poliovirus in Afghanistan: A household sampling method for serological assessment based on geographical information systems

Amalia Mendes, Ari Whiteman, Benjamin Nygren, Brian Kaplan, Imtiaz Hussain, Sajid Soofi, Maureen Martinez, Noha H. Farag

29-11-2022

https://doi.org/10.4081/gh.2022.1107

1241

PDF: 746

HTML: 45
One health review of recent Salmonella dynamics and human health outcomes in the United States

Geoffrey Kangogo, Lavanya Sankaran, Mitesh Rajpurohit, Kate E. Trout

11-12-2025

https://doi.org/10.4081/gh.2025.1416

652

PDF: 425

HTML: 43
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

1151

PDF: 744

HTML: 115
The impact of COVID-19 on healthcare coverage and access in racial and ethnic minority populations in the United States

Lauren Freelander, David S. Rickless, Corey Anderson, Frank Curriero, Sarah Rockhill, Amir Mirsajedin, Caleb J. Colón, Jasmine Lusane, Alexander Vigo-Valentín, David Wong

27-12-2023

https://doi.org/10.4081/gh.2023.1222

3671

PDF: 1115

HTML: 81
Prevalence of hypertension in Thailand: Hotspot clustering detected by spatial analysis

Wongsa Laohasiriwong, Nattapong Puttanapong, Atthawit Singsalasang

07-05-2018

https://doi.org/10.4081/gh.2018.608

4223

PDF: 2017

HTML: 581
Mapping the risk for transmission of urban schistosomiasis in the Brazilian Northeast

Emília Carolle Azevedo de Oliveira, Iris Edna Pereira da Silva, Ricardo José Ferreira, Ricardo José de Paula Souza e Guimarães, Elainne Christine de Souza Gomes, Constança SimÃµes Barbosa

29-12-2020

https://doi.org/10.4081/gh.2020.861

2644

PDF: 1024

HTML: 62
Impact of walkability with regard to physical activity in the prevention of diabetes

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

03-11-2017

https://doi.org/10.4081/gh.2017.595

3693

PDF: 1193

HTML: 1080
Spatial analysis of the regional variation of hypertensive disease mortality and its socio-economic correlates in South Korea

Seong-Yong Park, Jin-Mi Kwak, Eun-Won Seo, Kwang-Soo Lee

31-05-2016

https://doi.org/10.4081/gh.2016.420

3057

PDF: 1747

HTML: 1379
The food environment and adult obesity in US metropolitan areas

Akihiko Michimi, Michael C. Wimberly

26-11-2015

https://doi.org/10.4081/gh.2015.368

6192

PDF: 2836

HTML: 1224
Epidemiological aspects and spatial distribution of human and canine visceral leishmaniasis in an endemic area in northeastern Brazil

Roseane Campos, Márcio Santos, Gabriel Tunon, Luana Cunha, Lucas Magalhães, Juliana Moraes, Danielle Ramalho, Sanmy Lima, José Antônio Pacheco, Michael Lipscomb, Amélia Ribeiro de Jesus, Roque Pacheco de Almeida

11-05-2017

https://doi.org/10.4081/gh.2017.503

5561

PDF: 2154

HTML: 1152
Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand

Worrayot Darasawang, Wongsa Laohasiriwong, Kittipong Sornlorm , Warangkana Sungsitthisawad, Roshan Kumar Mahato

27-01-2025

https://doi.org/10.4081/gh.2025.1329

3252

PDF: 1035

Supplementary Materials: 567

HTML: 254
Flexible scan statistic with a restricted likelihood ratio for optimized COVID-19 surveillance

Ernest Akyereko, Frank B. Osei, Kofi M. Nyarko, Alfred Stein

26-11-2024

https://doi.org/10.4081/gh.2024.1265

885

PDF: 285

Supplementary Materials: 132

HTML: 26
Methodological framework for assessing malaria risk associated with climate change in Côte d’Ivoire

Yao Etienne Kouakou, Iba Dieudonné Dely, Madina Doumbia, Aziza Ouattara, Effah Jemima N’da, Koffi Evrard Brou, Yao Anicet Zouzou, Guéladio Cissé, Brama Koné

28-08-2024

https://doi.org/10.4081/gh.2024.1285

1676

PDF: 776

HTML: 101
Spatial distribution of triatomines (Reduviidae: Triatominae) in urban areas of the city of Salvador, Bahia, Brazil

Karine de Souza O. Santana, Maria Emília Bavia, Artur Dias Lima, Isabel Cristina S. Guimarães, Ênio Silva Soares, Marta Mariana Nascimento Silva, Jorge Mendonça, Moara de Santana Martin

199-203

01-05-2011

https://doi.org/10.4081/gh.2011.172

2289

PDF: 1004
Application of spatio-temporal scan statistics for the detection of areas with increased risk for American visceral leishmaniasis in the state of Bahia, Brazil

Deborah D.M.T. Carneiro, Maria E. Bavia, Washington J.S.F. Rocha, Antônio C.Q. Tavares, Luciana L. Cardim, Biruk Alemayehu

113-126

01-11-2007

https://doi.org/10.4081/gh.2007.260

1517

PDF: 1017
Spatio-temporal patterns of dengue in Malaysia: combining address and sub-district level

Cheong Y. Ling, Oliver Gruebner, Alexander Krämer, Tobia Lakes

131-140

01-11-2014

https://doi.org/10.4081/gh.2014.11

3856

PDF: 2119
Influence of topography on the endemicity of Kala-azar: a study based on remote sensing and geographical information system

Gouri S. Bhunia, Shreekant Kesari, Algarsamy Jeyaram, Vijay Kumar, Pradeep Das

155-165

01-05-2010

https://doi.org/10.4081/gh.2010.197

2461

PDF: 932
Spatio-temporal analysis of fox rabies cases in Germany 2005-2006

Matthias Eckardt, Conrad Freuling, Thomas Müller, Thomas Selhorst

03-06-2015

https://doi.org/10.4081/gh.2015.313

2853

PDF: 1247

HTML: 1211
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

4044

PDF: 2092
A post-pandemic analysis of air pollution over small-sized urban areas in southern Thailand following the COVID-19 lockdown

Dimitris Stratoulias, Beomgeun Jang, Narissara Nuthammachot

07-07-2025

https://doi.org/10.4081/gh.2025.1354

979

PDF: 391

Supplementary Materials: 85

HTML: 51
The effects of the Health Insurance Portability and Accountability Act privacy rule on influenza research using geographical information systems

Norisse Tellman, Eric R. Litt, Caprice Knapp, Aaron Eagan, Jing Cheng, Lewis J. Jr Radonovich

3-9

01-11-2010

https://doi.org/10.4081/gh.2010.182

2385

PDF: 971
Spatial autocorrelation pattern of COVID-19 vaccine coverage in Thailand 2021 and 2022

Sarayu Muntaphan, Kittipong Sornlorm

13-05-2025

https://doi.org/10.4081/gh.2025.1368

1468

PDF: 334

HTML: 67
Localization of kala-azar in the endemic region of Bihar, India based on land use/land cover assessment at different scales

Gouri S. Bhunia, Shreekant Kesari, Nandini Chatterjee, Vijay Kumar, Pradeep Das

177-193

01-05-2012

https://doi.org/10.4081/gh.2012.136

1503

PDF: 1060
The spatial distribution of Anopheles gambiae sensu stricto and An. arabiensis (Diptera: Culicidae) in Mali

N. Sogoba, P. Vounatsou, M.M. Bagayoko, S. Doumbia, G. Dolo, L. Gosoniu, S.F. Traore, Y.T. Toure, T. Smith

213-222

01-05-2007

https://doi.org/10.4081/gh.2007.269

2753

PDF: 1018
Rivers and flooded areas identified by medium-resolution remote sensing improve risk prediction of the highly pathogenic avian influenza H5N1 in Thailand

Weerapong Thanapongtharm, Thomas P. Van Boeckel, Chandrashekhar Biradar, Xiangming Xiao, Marius Gilbert

193-201

01-11-2013

https://doi.org/10.4081/gh.2013.66

1899

PDF: 1172
Impact of climate change on dengue fever: a bibliometric analysis

Mai Liu, Yin Zhang

19-02-2025

https://doi.org/10.4081/gh.2025.1301

2710

PDF: 897

Supplementary Materials: 362

HTML: 125
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

2231

PDF: 684

HTML: 89
Use of geocoding techniques for epidemiological surveillance in the Federal District, Brazil: a case study using dengue

Lucas Sanglard, Klauss K. S. Garcia, Walter Massa Ramalho

02-09-2025

https://doi.org/10.4081/gh.2025.1403

801

PDF: 276

HTML: 46
Migration statistics relevant for malaria transmission in Senegal derived from mobile phone data and used in an agent-based migration model

Adrian M. Tompkins, Nicky McCreesh

31-03-2016

https://doi.org/10.4081/gh.2016.408

3559

PDF: 1450

HTML: 999
Vaccine hesitancy in East Malaysia (Sabah): A survey of the national COVID-19 immunisation programme

Adi Jafar, Mohammad Tahir Mapa, Nordin Sakke, Ramli Dollah, Eko Prayitno Joko, Colonius Atang, Syahruddin Awang Ahmad, Chong Vun Hung, Fionna Geogre

14-01-2022

https://doi.org/10.4081/gh.2022.1037

6136

PDF: 1186

HTML: 279
Spatio-temporal analysis of foot traffic dynamics in Charleston County, South Carolina: before, during, and after COVID-19

Wish Shao, Abolfazl Mollalo, Navid Hashemi Tonekaboni

23-06-2025

https://doi.org/10.4081/gh.2025.1363

708

PDF: 379

HTML: 29
Global Mpox spread due to increased air travel

Huijie Qiao, Paanwaris Paansri, Luis E. Escobar

11-06-2024

https://doi.org/10.4081/gh.2024.1261

2380

PDF: 788

HTML: 256
Urban gentrification and infectious diseases: an interdisciplinary narrative review

Behzad Kiani, Gabriel Parker, Senobar Naderian, Colleen L. Lau, Benn Sartorius

07-07-2025

https://doi.org/10.4081/gh.2025.1388

1282

PDF: 534

HTML: 86
Application of modern spatio-temporal analysis technologies to identify and visualize patterns of rabies emergence among different animal species in Kazakhstan

Aizada A. Mukhanbetkaliyeva, Anar M. Kabzhanova, Ablaikhan S. Kadyrov, Yersyn Y. Mukhanbetkaliyev, Temirlan G. Bakishev, Aslan A. Bainiyazov, Rakhimtay B. Tleulessov, Fedor I. Korennoy, Andres M. Perez, Sarsenbay K. Abdrakhmanov

31-07-2024

https://doi.org/10.4081/gh.2024.1290

1682

PDF: 717

HTML: 114
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

1778

PDF: 906

Appendix: 158

HTML: 37
Balancing geo-privacy and spatial patterns in epidemiological studies

Chien-Chou Chen, Jen-Hsiang Chuang, Da-Wei Wang, Chien-Min Wang, Bo-Cheng Lin, Ta-Chien Chan

08-11-2017

https://doi.org/10.4081/gh.2017.573

4027

PDF: 1271

APPENDIX: 541

HTML: 955
Risk areas for hepatitis A, B and C in the municipality of MaringÃ¡, ParanÃ¡ State, Brazil 2007-2010

Valéria Miranda Avanzi, Udelysses Janete Veltrini Fonzar, Eraldo Schunk Silva, Jorge Juarez Vieira Teixeira, Dennis Armando Bertolini

08-05-2018

https://doi.org/10.4081/gh.2018.607

1978

PDF: 801

HTML: 133
Nigeria’s malaria prevalence in 2015: a geospatial, exploratory district-level approach

Mina Whyte, Kennedy Mwai Wambui, Eustasius Musenge

25-11-2024

https://doi.org/10.4081/gh.2024.1243

1487

PDF: 604

HTML: 114
A 24-year exploratory spatial data analysis of Lyme disease incidence rate in Connecticut, USA

Abolfazl Mollalo, Jason K. Blackburn, Lillian R. Morris, Gregory E. Glass

08-11-2017

https://doi.org/10.4081/gh.2017.588

3124

PDF: 1338

HTML: 1024
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

1390

PDF: 576

HTML: 17
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

3157

PDF: 1352

HTML: 1621
American cutaneous leishmaniasis cases in the metropolitan region of Manaus, Brazil: association with climate variables over time

Rodrigo Augusto Ferreira de Souza, Rita Valéria Andreoli, Mary Toshie Kayano, AfrÃ¢nio Lima Carvalho

18-05-2015

https://doi.org/10.4081/gh.2015.314

3011

PDF: 1505

HTML: 816
Typhoid fever in Jakarta, Indonesia 2017-2023: spatial clustering and seasonality of hospitalization data to inform better intervention

Mujiyanto Mujiyanto, Basuki Rachmat, Aris Yulianto, Made Agus Nurjana, Wawan Ridwan, Endang Puji Astuti, Doni Lasut, Pandji Wibawa Dhewantara

15-05-2025

https://doi.org/10.4081/gh.2025.1372

2437

PDF: 1076

HTML: 665
Bayesian spatial modelling of contraception effects on fertility in Mexican municipalities in 2020

Gerardo Núñez Medina

17-05-2022

https://doi.org/10.4081/gh.2022.1080

1199

PDF: 635

HTML: 142
Modelling the domestic poultry population in the United States: A novel approach leveraging remote sensing and synthetic data methods

Kelly A. Patyk, Mary J. McCool-Eye, David D. South, Christopher L. Burdett, Susan A. Maroney, Andrew Fox, Grace Kuiper, Sheryl Magzamen

10-12-2020

https://doi.org/10.4081/gh.2020.913

3860

PDF: 1464

HTML: 184
Identification and mapping of objects targeted for surveillance and their role as risk factors for brucellosis in livestock farms in Kazakhstan

Aizada A. Mukhanbetkaliyeva, Ablaikhan S. Kadyrov, Yersyn Y. Mukhanbetkaliyev, Zhanat S. Adilbekov, Assylbek A. Zhanabayev, Assem Z. Abenova, Fedor I. Korennoy, Sarsenbay K. Abdrakhmanov

08-11-2024

https://doi.org/10.4081/gh.2024.1335

1574

PDF: 482

HTML: 63
The effects of population mobility on Chinese HIV epidemics in spill-over and influx risks perspectives: a spatial epidemiology analysis

Yazhen Zhang, Hui Jin

08-09-2025

https://doi.org/10.4081/gh.2025.1384

757

PDF: 366

Supplementary materials: 63

HTML: 25
Making the most of spatial information in health: a tutorial in Bayesian disease mapping for areal data

Su Yun Kang, Susanna M. Cramb, Nicole M. White, Stephen J. Ball, Kerrie L. Mengersen

31-05-2016

https://doi.org/10.4081/gh.2016.428

7237

PDF: 2515

APPENDIX: 1174

HTML: 5392
Neurological disability in leprosy: incidence and gender association in Sergipe, Brazil

Daniela Teles de Oliveira, Marília Matos Bezerra, José Antônio Pacheco de Almeida, Malcolm Duthie, Steven Reed, Amelia Ribeiro de Jesus

S125-S129

01-09-2012

https://doi.org/10.4081/gh.2012.130

1567

PDF: 863
Taming the beast: rabies control in the cradle of mankind

Gianluca D'Amico, Andrei D. Mihalca, Cristian DomÅŸa, KateÅ™ina Albrechtová, Attila D. Sándor, David ModryÌ

409-411

01-05-2013

https://doi.org/10.4081/gh.2013.98

1584

PDF: 954

Video: 0
Spatiotemporal distribution and geostatistically interpolated mapping of the melioidosis risk in an endemic zone in Thailand

Jaruwan Wongbutdee, Jutharat Jittimanee, Wacharapong Saengnill

05-07-2023

https://doi.org/10.4081/gh.2023.1189

1746

PDF: 924

HTML: 64
Multiple testing in disease mapping and descriptive epidemiology

Dolores Catelan, Annibale Biggeri

219-229

01-05-2010

https://doi.org/10.4081/gh.2010.202

1613

PDF: 1024
Mapping livestock systems, bovine and caprine diseases in Mayo-Kebbi Ouest Province, Chad

Kella Douzouné, Joseph Oloukoi, Ismaila Toko Imorou, Toure Gorgui Ba, Derrick Chefor Ymele Demeveng

03-02-2025

https://doi.org/10.4081/gh.2025.1365

3691

PDF: 1241

Supplementary Materials: 603

HTML: 195
Geospatial (s)tools: integration of advanced epidemiological sampling and novel diagnostics

Giuseppe Cringoli, Laura Rinaldi, Marco Albonico, Robert Bergquist, Jürg Utzinger

399-404

01-05-2013

https://doi.org/10.4081/gh.2013.97

4425

PDF: 1659
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

2793

PDF: 1348

APPENDIX: 685

HTML: 1501
Spatio-temporal evaluation of cattle trade in Sweden: description of a grid network visualization technique

Stefan Widgren, Jenny Frössling

119-130

01-11-2010

https://doi.org/10.4081/gh.2010.192

1502

PDF: 1107
Mapping of the environmental contamination of Toxoplasma gondii by georeferencing isolates from chickens in an endemic area in Southeast Rio de Janeiro State, Brazil

Luciana Casartelli-Alves, Maria Regina Reis Amendoeira, Viviane Cardoso Boechat, Luiz Cláudio Ferreira, João Carlos Araujo Carreira, José Leonardo Nicolau, Eloiza Paula de Freitas Trindade, Julia Novaes de Barros Peixoto, Mônica de Avelar Figueiredo Mafra Magalhães, Raquel de Vasconcellos Carvalhaes de Oliveira, TÃ¢nia Maria Pacheco Schubach, Rodrigo Caldas Menezes

18-05-2015

https://doi.org/10.4081/gh.2015.311

3400

PDF: 1466

HTML: 1508
Spatial dynamic patterns of hand-foot-mouth disease in the People's Republic of China

Jin-Feng Wang, Cheng-Dong Xu, Shi-Lu Tong, Hong-Yan Chen, Wei-Zhong Yang

381-390

01-05-2013

https://doi.org/10.4081/gh.2013.95

3069

PDF: 1574
The impact of geographic mobility on the spread of COVID-19 in Hong Kong

Paulina Pui Yun Wong, Chien-Tat Low, Poh-Chin Lai

14-02-2022

https://doi.org/10.4081/gh.2022.1022

3264

PDF: 577

HTML: 141
Mapping brucellosis risk in communities in the Republic of Armenia

Thibaud Porphyre, Ronald Jackson, Carola Sauter-Louis, David Ward, Grigor Baghyan, Edik Stepanyan

103-118

01-11-2010

https://doi.org/10.4081/gh.2010.191

2039

PDF: 1123
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

2781

PDF: 1071
Urban agriculture and Anopheles habitats in Dar es Salaam, Tanzania

Stefan Dongus, Dickson Nyika, Khadija Kannady, Deo Mtasiwa, Hassan Mshinda, Laura Gosoniu, Axel W. Drescher, Ulrike Fillinger, Marcel Tanner, Gerry F. Killeen, Marcia C. Castro

189-210

01-05-2009

https://doi.org/10.4081/gh.2009.220

4435

PDF: 1467
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

1995

PDF: 855

HTML: 29
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

5955

PDF: 2049
Detection of high risk campylobacteriosis clusters at three geographic levels

Jennifer Weisent, Barton Rohrbach, John R. Dunn, Agricola Odoi

65-76

01-11-2011

https://doi.org/10.4081/gh.2011.158

1830

PDF: 858
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

2153

PDF: 1080

HTML: 66
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

4168

PDF: 1978
The epidemiology and small-scale spatial heterogeneity of urinary schistosomiasis in Lusaka province, Zambia

Christopher Simoonga, Lawrence N. Kazembe, Thomas K. Kristensen, Annette Olsen, Chris C. Appleton, Patricia Mubita, Likezo Mubila

57-67

01-11-2008

https://doi.org/10.4081/gh.2008.232

3108

PDF: 1115
Transmissibility of the highly pathogenic avian influenza virus, subtype H5N1 in domestic poultry: a spatio-temporal estimation at the global scale

Zhijie Zhang, Dongmei Chen, Michael P. Ward, Qingwu Jiang

135-143

01-11-2012

https://doi.org/10.4081/gh.2012.112

1642

PDF: 975
Bayesian risk maps for Schistosoma mansoni and hookworm mono-infections in a setting where both parasites co-exist

Giovanna Raso, Penelope Vounatsou, Donald P. McManus, Jürg Utzinger

85-96

01-11-2007

https://doi.org/10.4081/gh.2007.257

2612

PDF: 894
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

3191

PDF: 1454

HTML: 1464
Spatial-temporal analysis of prostate cancer incidence from the Pennsylvania Cancer Registry, 2000-2011

Ming Wang, Stephen A. Matthews, Khaled Iskandarani, Yimei Li, Zheng Li, Vernon M. Chinchilli, Lijun Zhang

28-11-2017

https://doi.org/10.4081/gh.2017.611

3721

PDF: 931

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Environmental change and Rift Valley fever in eastern Africa: projecting beyond HEALTHY FUTURES

David Taylor, Michael Hagenlocher, Anne E. Jones, Stefan Kienberger, Joseph Leedale, Andrew P. Morse

31-03-2016

https://doi.org/10.4081/gh.2016.387

6465

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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

3748

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A determination of the spatial concordance between Lyme disease incidence and habitat probability of its primary vector Ixodes scapularis (black-legged tick)

Samuel F. Atkinson, Sahotra Sarkar, Aldo Aviña, Jim A. Schuermann, Phillip Williamson

203-212

01-11-2014

https://doi.org/10.4081/gh.2014.17

15292

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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

2938

PDF: 852

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Healthcare-seeking behavior and spatial variation of internal migrants with chronic diseases: a nationwide empirical study in China

Dan Li, Dawei Gao, Masaaki Yamada, Chuangbin Chen, Liuchun Xiang, Haisong Nie

28-05-2024

https://doi.org/10.4081/gh.2024.1255

2626

PDF: 761

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Evaluation and planning of Chagas control activities using geospatial tools

Diego Weinberg, Mario Lanfri, Carlos M. Scavuzzo, Marcelo Abril, Sofía Lanfri

06-11-2019

https://doi.org/10.4081/gh.2019.786

1632

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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

1748

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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

4148

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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

3792

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Modelling geographical heterogeneity of diabetes prevalence and socio-economic and built environment determinants in Saudi City - Jeddah

Abdulkader Murad, Fazlay Faruque, Ammar Naji, Alok Tiwari, Mansour Helmi, Ammar Dahlan

16-05-2022

https://doi.org/10.4081/gh.2022.1072

2013

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Province clustering based on the percentage of communicable disease using the BCBimax biclustering algorithm

Muhammad Nur Aidi, Cynthia Wulandari, Sachnaz Desta Oktarina, Taufiqur Rakhim Aditra, Fitrah Ernawati, Efriwati Efriwati, Nunung Nurjanah, Rika Rachmawati, Elisa Diana Julianti, Dian Sundari, Fifi Retiaty, Aya Yuriestia Arifin, Rita Marleta Dewi, Nazarina Nazaruddin, Salimar Salimar, Noviati Fuada, Yekti Widodo, Budi Setyawati, Nuzuliyati Nurhidayati, Sudikno Sudikno, Irlina Raswanti Irawan, Widoretno Widoretno

12-09-2023

https://doi.org/10.4081/gh.2023.1202

1763

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Habitat suitability map of Ixodes ricinus tick in France using multi-criteria analysis

Isabelle Lebert, Séverine Bord, Christine Saint-Andrieux, Eva Cassar, Patrick Gasqui, Frédéric Beugnet, Karine Chalvet-Monfray, Sophie O. Vanwambeke, Gwenaël Vourc’h, Magalie René-Martellet

17-05-2022

https://doi.org/10.4081/gh.2022.1058

6647

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Appendix: 368

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Predicting malaria cases using remotely sensed environmental variables in Nkomazi, South Africa

Abiodun Morakinyo Adeola, Joel Ondego Botai, Jane Mukarugwiza Olwoch, Hannes C.J. de W. Rautenbach, Omolola Mayowa Adisa, Christiaan de Jager, Christina M. Botai, Mabuza Aaron

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https://doi.org/10.4081/gh.2019.676

3070

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Spatial heterogeneity in relationship between district patterns of HIV incidence and covariates in Zimbabwe: a multi-scale geographically weighted regression analysis

Rutendo Birri Makota, Eustasius Musenge

27-11-2023

https://doi.org/10.4081/gh.2023.1207

1547

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Epidemiological characteristics and determination of spatio-temporal clusters during the 2013 dengue outbreak in Chiang Mai, Thailand

Veerasak Punyapornwithaya, Chalutwan Sansamur, Arisara Charoenpanyanet

29-12-2020

https://doi.org/10.4081/gh.2020.857

1701

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Geospatial analysis in the United States reveals the changing roles of temperature on COVID-19 transmission

Ruiwen Xiong, Xiaolong Li

20-07-2023

https://doi.org/10.4081/gh.2023.1213

1434

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Spatial analysis of cutaneous leishmaniasis in an endemic area of Iran based on environmental factors

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

08-11-2017

https://doi.org/10.4081/gh.2017.578

2848

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Socio-economic and environmental factors are related to acute exacerbation of chronic obstructive pulmonary disease incidence in Thailand

Phuricha Phacharathonphakul, Kittipong Sornlorm

29-11-2024

https://doi.org/10.4081/gh.2024.1300

1996

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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

2437

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Comments on Socio-geographical factors in vulnerability to dengue in Thai villages: a spatial regression analysis by Tipayamongkholgul and Lisakulruk

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3

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https://doi.org/10.4081/gh.2011.150

1100

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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

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Diabetes prevalence in the state of Alabama: identifying the risk factors

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https://doi.org/10.4081/gh.2026.1465

148

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Assessing the risk for dengue fever based on socioeconomic and environmental variables in a geographical information system environment

Hassan M. Khormi, Lalit Kumar

171-176

01-05-2012

https://doi.org/10.4081/gh.2012.135

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