Spatial Epidemiology and Infectious Diseases in the Context of Changing Climate

A special issue of Tropical Medicine and Infectious Disease (ISSN 2414-6366). This special issue belongs to the section "Infectious Diseases".

Deadline for manuscript submissions: 15 June 2026 | Viewed by 1946

Special Issue Editors


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Guest Editor
UQ Centre for Clinical Research (UQCCR), Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Brisbane 4006, Australia
Interests: spatial analysis; infectious diseases; spatial modelling; medical informatics; geospatial health
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E-Mail Website
Guest Editor
Centre for Clinical Research (UQCCR), Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Brisbane 4006, Australia
Interests: health sciences; public health; global health; applied statistics; epidemiological modelling; spatial modelling; burden of disease; social determinants of health; climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue explores the application of spatial epidemiology methods for modelling the complex relationships between climate change, environmental factors, and the burden of infectious diseases. Climate change significantly affects infectious disease transmission patterns through mechanisms such as shifting temperature ranges, altered precipitation patterns, and changing habitats for vectors and pathogens. Socioeconomic vulnerability, including limited access to healthcare, poor infrastructure, and economic disparities, can further mediate or amplify these effects.

We invite original research articles, reviews, and methodological advances that address themes, including, but not limited to:

  • Spatial modelling of climate change impacts on infectious disease transmission;
  • Environmental determinants of climate-sensitive disease patterns;
  • Socioeconomic vulnerabilities as mediators in climate-related health risks;
  • Integration of climate, environmental, and socioeconomic data in spatial epidemiological models;
  • Case studies linking climate variability and disease burden;
  • Methods for assessing climate and health resilience in vulnerable populations;
  • Policy implications of climate change in infectious disease control.

By emphasizing the diverse pathways through which climate change influences infectious diseases, this Special Issue aims to foster a comprehensive understanding of disease vulnerability and contribute to the development of targeted interventions for climate-sensitive infectious diseases.

Dr. Behzad Kiani
Dr. Benn Sartorius
Guest Editors

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Keywords

  • climate change
  • spatial epidemiology
  • climate change
  • infectious diseases
  • disease transmission patterns
  • environmental factors
  • socioeconomic vulnerability
  • healthcare access
  • infrastructure
  • economic disparities
  • spatial and spatial-temporal modelling
  • climate-sensitive diseases
  • environmental determinants
  • health risks
  • climate variability
  • disease burden
  • health resilience
  • vulnerable populations
  • policy implications
  • disease control

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Published Papers (2 papers)

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Research

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20 pages, 2861 KB  
Article
High-Resolution Geospatial Analysis of Dengue Vulnerability in Urban and Rural Areas of San Luis Potosí, Mexico
by Darío Gaytán Hernández, Daniel Sánchez Hernández, Luis Eduardo Hernández Ibarra, Enrique Ibarra Zapata, Omar Parra Rodríguez, Verónica Gallegos García, Omar Medina de la Cruz and Marisol Gallegos García
Trop. Med. Infect. Dis. 2025, 10(11), 307; https://doi.org/10.3390/tropicalmed10110307 - 28 Oct 2025
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Abstract
Objective: The aim was to analyze the temporal evolution and spatial distribution of classic and hemorrhagic dengue in the Mexican state of San Luis Potosí at the basic geostatistical area (BGA) level and to develop multivariate models to estimate the population’s degree of [...] Read more.
Objective: The aim was to analyze the temporal evolution and spatial distribution of classic and hemorrhagic dengue in the Mexican state of San Luis Potosí at the basic geostatistical area (BGA) level and to develop multivariate models to estimate the population’s degree of vulnerability. Methodology: Classic and hemorrhagic dengue cases for 2015–2020 were obtained from the Mexican Ministry of Health, georeferenced at the pixel level, and subsequently grouped by BGA. Environmental, proximity, and social variables were obtained from official sites: IMTA, SMN, USGS, and INEGI. Multivariate logistic regression models were developed using PASW Statistics v. 18 software to estimate the degree of vulnerability, and the receiver operating characteristic curve was used to validate them. Results: A total of 125, 128, 109, 624, 1580, and 1817 dengue cases were identified for 2015, 2016, 2017, 2018, 2019, and 2020, respectively. The major factors contributing to the vulnerability of classic dengue fever included population, temperature, and distance to agricultural areas. For hemorrhagic dengue, the contributing factors were temperature, population, and mean annual rainfall. Vulnerability prediction was determined by taking the area under the curve values, which were 0.957 for classic dengue fever and 0.930 for hemorrhagic dengue, both indicating a “very good ability” to predict. Conclusions: These results can be used to design and implement targeted strategies, particularly for modifiable factors, such as prevention measures directed towards populated areas and the improvement of sewage systems, in addition to non-modifiable factors, such as temperature and rainfall. This method can be replicated as an additional tool to address this public health issue. Full article
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Review

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17 pages, 772 KB  
Review
Spatial Risk Factors of Vector-Borne Diseases in Pacific Island Countries and Territories: A Scoping Review
by Tathiana Nuñez Murillo, Angela Cadavid Restrepo, Helen J. Mayfield, Colleen L. Lau, Benn Sartorius and Behzad Kiani
Trop. Med. Infect. Dis. 2026, 11(1), 6; https://doi.org/10.3390/tropicalmed11010006 - 24 Dec 2025
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Abstract
This scoping review aimed to identify and synthesise spatially relevant environmental, demographic, and socio-economic factors associated with vector-borne diseases (VBDs) in Pacific Island Countries and Territories (PICTs), a region particularly vulnerable due to its ecological and climate diversity. A systematic search of PubMed, [...] Read more.
This scoping review aimed to identify and synthesise spatially relevant environmental, demographic, and socio-economic factors associated with vector-borne diseases (VBDs) in Pacific Island Countries and Territories (PICTs), a region particularly vulnerable due to its ecological and climate diversity. A systematic search of PubMed, Scopus, and Web of Science was conducted in March 2025 with no time restrictions, yielding 3008 records. After applying the inclusion criteria, 21 studies were selected for analysis. Environmental factors such as temperature, precipitation, and land cover were consistently associated with increased burden of malaria, dengue, and lymphatic filariasis, while associations with elevation and flooding were mixed or inconclusive. Demographic factors, including population density and household composition, were found to be associated with disease occurrence, although the direction and the strength of these associations varied. Three studies reported a negative association between population density and disease outcomes, including lymphatic filariasis in American Samoa and dengue in New Caledonia. Spatial socioeconomic factors such as low income, unemployment, and limited education were positively correlated with disease burden, particularly lymphatic filariasis and dengue. These findings underscore the importance of spatial determinants in shaping VBD transmission across PICTs and highlight the utility of spatial risk mapping to inform geographically targeted vector control strategies. Notably, infrastructure, health care access, and intra-island mobility remain underexplored in the literature, representing critical gaps for future research. Strengthening surveillance through spatially informed public health planning is essential to mitigate disease burden in this climate-sensitive and geographically dispersed region. Full article
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