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Spatiotemporal analysis of the relationship between socioeconomic factors and stroke in the Portuguese mainland population under 65 years old

André Oliveira, Antònio J.R. Cabral, Jorge M. Mendes, Maria R.O. Martins, Pedro Cabral

04-11-2015

https://doi.org/10.4081/gh.2015.365

3414

PDF: 1527

HTML: 1231
Understanding the relationship between land use and land cover and malaria in Nepal

Shreejana Bhattarai, Korine N. Kolivras, Kabita Ghimire, Yang Shao

29-12-2020

https://doi.org/10.4081/gh.2020.855

2339

PDF: 977

HTML: 45
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

1611

PDF: 1028

HTML: 167
Performance of a negative binomial-GLM in spatial scan statistic: a case study of low-birth weights in Pakistan

Sami Ullah, Mushtaq Ahmad Khan Barakzai, Tianfa Xie

03-09-2024

https://doi.org/10.4081/gh.2024.1313

1799

PDF: 707

HTML: 181
Spatial analysis and modelling of depression relative to social vulnerability index across the United States

Kiara M. Rivera, Abolfazl Mollalo

01-09-2022

https://doi.org/10.4081/gh.2022.1132

5541

PDF: 2524

HTML: 619
Associations between rocky mountain spotted fever and veterinary care access, climatic factors and landscape in the State of Arizona, USA

Yan Lin, Al Ekram Elahee Hridoy , Meifang Li, Zhe Wang, Li Luo, Xiaogang Ma, Zhuoming Liu, Murphy John, Chao Fan, Irene Ruberto, Xi Gong, Xun Shi

17-07-2025

https://doi.org/10.4081/gh.2025.1390

1194

PDF: 1001

Supplementary Materials: 134

HTML: 124
Bayesian modelling of dengue incidence with climatic drivers: comparing fixed-effects, nonlinear and dynamic approaches

Farah Kristiani, I Gede Nyoman Mindra Jaya, Robyn Irawan, Inanta Maria Priscilia

02-02-2026

https://doi.org/10.4081/gh.2026.1461

799

PDF: 498

Supplementary materials: 80

HTML: 19
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

3536

PDF: 1171

HTML: 1468
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

4549

PDF: 2393

HTML: 2225
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

3733

PDF: 1242

HTML: 831
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

1882

PDF: 611

HTML: 77
A Bayesian spatial ecological analysis of social conditions, infection burden and COVID-19 mortality across mainland Scottish councils 2020-2021

Zhiyuan Luo, Yancheng Liu, Wenqi Xu

10-06-2026

https://doi.org/10.4081/gh.2026.1477

370

PDF: 207

Supplementary Materials: 45

HTML: 8
Perceived spatial stigma, body mass index and blood pressure: a global positioning system study among low-income housing residents in New York City

Dustin T. Duncan, Ryan R. Ruff, Basile Chaix, Seann D. Regan, James H. Williams, Joseph Ravenell, Marie A. Bragg, Gbenga Ogedegbe, Brian Elbel

31-05-2016

https://doi.org/10.4081/gh.2016.399

4330

PDF: 2064

HTML: 1510
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

2402

PDF: 1032

HTML: 103
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

1712

PDF: 737

HTML: 44
Comparing conditional autoregressive models for Bayesian spatial mapping of dengue cases in Indonesia

Ferra Yanuar, Yudiantri Asdi, Aidinil Zetra, Sofiana Wudlu, Fenni Kurnia Mutiya, Rahmawita Rahmawita

18-06-2026

https://doi.org/10.4081/gh.2026.1443

272

PDF: 354

HTML: 3
Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space

Benjamin G. Jacob, Fiorella Krapp, Mario Ponce, Eduardo Gotuzzo, Daniel A. Griffith, Robert J. Novak

201-217

01-05-2010

https://doi.org/10.4081/gh.2010.201

1862

PDF: 1127
A Bayesian spatiotemporal Poisson conditional autoregressive model for dengue haemorrhagic fever in Indonesia integrating satellite-generated environmental data

Sukarna Sukarna, Hari Wijayanto, Yenni Angraini, Anang Kurnia

18-07-2025

https://doi.org/10.4081/gh.2025.1379

1410

PDF: 696

HTML: 64
Spatial multilevel modelling male partners’ influence on women’s modern contraceptive use: a study in Angola and Zambia

Kabeya Clement Mulamba

12-05-2025

https://doi.org/10.4081/gh.2025.1340

1577

PDF: 351

HTML: 61
Estimating malaria burden in Nigeria: a geostatistical modelling approach

Nnadozie Onyiri

04-11-2015

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

7958

PDF: 3333

HTML: 3291
Diagnostic approaches to malaria in Zambia, 2009-2014

Victor M. Mukonka, Emmanuel Chanda, Mulakwa Kamuliwo, Maha A. Elbadry, Pauline K. Wamulume, Mercy Mwanza-Ingwe, Jailos Lubinda, Lindsey A. Laytner, Wenyi Zhang, Gabriel Mushinge, Ubydul Haque

03-06-2015

https://doi.org/10.4081/gh.2015.330

3792

PDF: 1529

HTML: 1177
Spatial distribution and predictive risk of perpetuation of non-typhoidal salmonellosis in poultry farms and human communities: meta-analysis of data from Nigeria

Abdullahi O. Sanni , Annelize Jonker, Olatunji O. Johnson , Ezra Gayawan , Aminu Shittu , Olubunmi G. Fasanmi , Oluwawemimo A. Adebowale , Folorunso O. Fasina

12-02-2026

https://doi.org/10.4081/gh.2026.1316

1382

PDF: 650

Supplementary Materials: 153

HTML: 24
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

3878

PDF: 2015

HTML: 2265
Modelling count data with an excess of zero values applied to childhood bone tumour incidence in Iraq

Muzahem Mohammed Al-Hashimi, Hasmek Antranik Warttan

12-03-2021

https://doi.org/10.4081/gh.2021.873

2242

PDF: 812

HTML: 145
The influence of socioeconomic deprivation, access to healthcare and physical environment on old-age survival in Portugal

Ana Isabel Ribeiro, Elias Teixeira Krainski, Marilia Sá Carvalho, Maria de Fátima de Pina

07-11-2017

https://doi.org/10.4081/gh.2017.581

3854

PDF: 1491

HTML: 881

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