Spatial Dynamics of Infectious Diseases in a Changing World: Navigating Population, Mobility, Climate, and Environmental Change

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: closed (31 May 2024) | Viewed by 2093

Special Issue Editors


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Guest Editor
UQ Centre for Clinical Research (UQCCR), Faculty of Medicine, The University of Queensland, Brisbane 4006, Australia
Interests: medical (health) geography; medical informatics; spatial epidemiology; public health; digital health
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
UQ Centre for Clinical Research (UQCCR), Faculty of Medicine, The University of Queensland, Brisbane 4006, Australia
Interests: spatial epidemiology; infectious disease epidemiology; global health; burden of disease; risk factors

Special Issue Information

Dear Colleagues,

We are excited to announce a forthcoming Special Issue on Spatial Epidemiology in Infectious Diseases, dedicated to exploring the dynamic interplay between infectious diseases and their spatial context. This Issue aims to shed light on the critical aspects of infectious disease transmission within the broader framework of population mobility, climate change, environmental factors, and more.

  1. Population Mobility: Understanding how human movement influences the spread of infectious diseases is paramount for devising effective containment and mitigation strategies. We invite contributions that explore the impact of population mobility on disease dynamics and transmission patterns.
  2. Climate Change: As climate patterns evolve, so do the landscapes for infectious disease transmission. We seek research that delves into the nexus between climate change and infectious diseases, addressing how shifts in temperature, precipitation, and ecological systems influence the infectious disease prevalence and distribution.
  3. Spatial Sampling: Rigorous and well-designed sampling strategies are crucial for capturing accurate representations of disease seroprevalence. We welcome studies that employ innovative spatial sampling techniques, contributing to the advancement of spatial epidemiological research methodologies.
  4. Spatiotemporal Modeling: Cutting-edge models that integrate spatial and temporal dimensions play a pivotal role in uncovering the complex dynamics of infectious diseases. We encourage submissions that employ advanced spatiotemporal modeling techniques to enhance our understanding of disease spread.
  5. Spatial Decision Support System: Contributions focused on the development and application of spatial decision support systems for infectious disease management and control are highly sought. We aim to showcase practical tools that aid in informed decision-making.
  6. Spatial Predictive Risk Mapping: Predicting areas at higher risk for disease outbreaks is instrumental in preparedness and response efforts. We invite studies that employ spatial predictive risk mapping techniques to identify vulnerable regions and inform targeted interventions.
  7. Interactive Spatiotemporal Dashboards: The integration of dynamic visualization tools enhances accessibility and comprehension of complex spatial epidemiological data. We encourage submissions that showcase interactive dashboards as an effective means of disseminating critical information.
  8. Environmental Factors: Environmental variables play a crucial role in influencing infectious disease dynamics. We invite research that examines the relationship between environmental factors, such as land use, habitat changes, water quality, and disease transmission patterns.

Dr. Behzad Kiani
Dr. Benn Sartorius
Guest Editors

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Keywords

  • population mobility
  • climate change
  • spatial sampling
  • spatiotemporal modeling
  • spatial decision support system
  • infectious disease
  • spatial predictive risk mapping
  • interactive spatiotemporal dashboards
  • environmental factors
  • spatial analysis

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Published Papers (1 paper)

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Research

14 pages, 1797 KiB  
Article
International Migration, Refugees, and Spread of Tuberculosis in Brazil: Analysis of Clusters, Trends, and Associated Factors (2010–2021)
by Yan Mathias Alves, Thaís Zamboni Berra, Reginaldo Bazon Vaz Tavares, Marcela Antunes Paschoal Popolin, Fernanda Bruzadelli Paulino da Costa, Sonia Vivian de Jezus, Letícia Perticarrara Ferezin, Ariela Fehr Tártaro, Maria Del Pilar Serrano-Gallardo, Ione Carvalho Pinto, Ethel Leonor Noia Maciel and Ricardo Alexandre Arcêncio
Trop. Med. Infect. Dis. 2024, 9(4), 82; https://doi.org/10.3390/tropicalmed9040082 - 11 Apr 2024
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Abstract
Background: International migration is a global phenomenon with significant implications on the health–disease process due to exposures along transit routes and local/destination epidemiological indicators. We aimed to analyze the transmission and spread of tuberculosis among international migrants and refugees from a spatiotemporal perspective [...] Read more.
Background: International migration is a global phenomenon with significant implications on the health–disease process due to exposures along transit routes and local/destination epidemiological indicators. We aimed to analyze the transmission and spread of tuberculosis among international migrants and refugees from a spatiotemporal perspective and the associated factors. Method: This was an ecological study of cases of tuberculosis in international migrants in Brazil, between 2010 and 2021. Annual incidence rates were calculated and spatiotemporal scan techniques were used to identify municipalities at risk. Multiple logistic regression was used to identify factors associated with tuberculosis in international migrants. Results: A total of 4037 cases of tuberculosis were reported in Brazil in international migrants. Municipalities at risk for this event were identified using the spatiotemporal scan technique, and a cluster was identified with ITT: +52.01% and ETT: +25.60%. A higher probability of TB infection was identified in municipalities with a TB incidence rate >14.40 cases/100 inhabitants, population >11,042 inhabitants, Gini index >0.49, and illiteracy rate >13.12%. A lower probability was found in municipalities with average per capita household income >BRL 456.43. Conclusions: It is recommended that health authorities implement monitoring and rigorous follow-up in affected areas to ensure proper diagnosis and treatment completion for international migrants, preventing disease spread to other communities. Full article
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