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Special Issue "Spatio-Temporal Analysis of Infectious Diseases"

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Global Health".

Deadline for manuscript submissions: 31 October 2018

Special Issue Editor

Guest Editor
Prof. Dr. Antonio López-Quílez

Department of Statistics and Operations Research, University of Valencia, Dr. Moliner, 50, 46100 Burjassot, Spain
Website | E-Mail

Special Issue Information

Dear Colleagues,

A Special Issue on spatio-temporal analysis of infectious diseases is being organized in the International Journal of Environmental Research and Public Health. For detailed information on the journal, I refer you to http://www.mdpi.com/journal/ijerph.

Epidemiological research on the pathogenesis, diagnosis, and treatment of infectious diseases is a broad field of work with renewed validity in the face of social changes and new threats. The spatiotemporal distribution is central in the knowledge of the development, transmission, spread and dynamics of these diseases.

New technologies and GIS methods together with highly structured mathematical and statistical techniques have a special utility in describing and analyzing infectious disease incidence. Specifically, Bayesian inference methods allow the analysis of models with complex and flexible structures suitable to represent the diverse characteristics present in each geographical environment and disease.

Tuberculosis, hepatitis, HIV, influenza, malaria, dengue, zika and other vector-borne diseases are a constant concern for health authorities, practitioners and patients. A variety of environmental, climatic and socio-economic factors underlie their spatiotemporal patterns. In addition, factors such as changes in climate, habits or land use intervene and complicate the understanding of these processes.

This Special Issue invites contributions on spatio-temporal analysis of infectious diseases and related themes. The keywords listed below provide an outline of some of the possible areas of interest.

Prof. Dr. Antonio López-Quílez
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • spatio-temporal modeling
  • infectious disease epidemiology
  • geographical pattern
  • spatial heterogeneity
  • transmission dynamics
  • emerging infectious diseases
  • neglected tropical diseases
  • environmental factors
  • climate change

Published Papers (5 papers)

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Research

Open AccessArticle Risk Assessment and Mapping of Hand, Foot, and Mouth Disease at the County Level in Mainland China Using Spatiotemporal Zero-Inflated Bayesian Hierarchical Models
Int. J. Environ. Res. Public Health 2018, 15(7), 1476; https://doi.org/10.3390/ijerph15071476
Received: 16 June 2018 / Revised: 7 July 2018 / Accepted: 10 July 2018 / Published: 12 July 2018
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Abstract
Hand, foot, and mouth disease (HFMD) is a worldwide infectious disease, prominent in China. China’s HFMD data are sparse with a large number of observed zeros across locations and over time. However, no previous studies have considered such a zero-inflated problem on HFMD’s
[...] Read more.
Hand, foot, and mouth disease (HFMD) is a worldwide infectious disease, prominent in China. China’s HFMD data are sparse with a large number of observed zeros across locations and over time. However, no previous studies have considered such a zero-inflated problem on HFMD’s spatiotemporal risk analysis and mapping, not to mention for the entire Mainland China at county level. Monthly county-level HFMD cases data combined with related climate and socioeconomic variables were collected. We developed four models, including spatiotemporal Poisson, negative binomial, zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) models under the Bayesian hierarchical modeling framework to explore disease spatiotemporal patterns. The results showed that the spatiotemporal ZINB model performed best. Both climate and socioeconomic variables were identified as significant risk factors for increasing HFMD incidence. The relative risk (RR) of HFMD at the local scale showed nonlinear temporal trends and was considerably spatially clustered in Mainland China. The first complete county-level spatiotemporal relative risk maps of HFMD were generated by this study. The new findings provide great potential for national county-level HFMD prevention and control, and the improved spatiotemporal zero-inflated model offers new insights for epidemic data with the zero-inflated problem in environmental epidemiology and public health. Full article
(This article belongs to the Special Issue Spatio-Temporal Analysis of Infectious Diseases)
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Open AccessArticle Spatio-Temporal Modeling of Zika and Dengue Infections within Colombia
Int. J. Environ. Res. Public Health 2018, 15(7), 1376; https://doi.org/10.3390/ijerph15071376
Received: 24 May 2018 / Revised: 23 June 2018 / Accepted: 26 June 2018 / Published: 30 June 2018
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Abstract
The aim of this study is to estimate the parallel relative risk of Zika virus disease (ZVD) and dengue using spatio-temporal interaction effects models for one department and one city of Colombia during the 2015–2016 ZVD outbreak. We apply the integrated nested Laplace
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The aim of this study is to estimate the parallel relative risk of Zika virus disease (ZVD) and dengue using spatio-temporal interaction effects models for one department and one city of Colombia during the 2015–2016 ZVD outbreak. We apply the integrated nested Laplace approximation (INLA) for parameter estimation, using the epidemiological week (EW) as a time measure. At the departmental level, the best model showed that the dengue or ZVD risk in one municipality was highly associated with risk in the same municipality during the preceding EWs, while at the city level, the final model selected established that the high risk of dengue or ZVD in one census sector was highly associated not only with its neighboring census sectors in the same EW, but also with its neighboring sectors in the preceding EW. The spatio-temporal models provided smoothed risk estimates, credible risk intervals, and estimation of the probability of high risk of dengue and ZVD by area and time period. We explore the intricacies of the modeling process and interpretation of the results, advocating for the use of spatio-temporal models of the relative risk of dengue and ZVD in order to generate highly valuable epidemiological information for public health decision making. Full article
(This article belongs to the Special Issue Spatio-Temporal Analysis of Infectious Diseases)
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Open AccessArticle The Social and Spatial Ecology of Dengue Presence and Burden during an Outbreak in Guayaquil, Ecuador, 2012
Int. J. Environ. Res. Public Health 2018, 15(4), 827; https://doi.org/10.3390/ijerph15040827
Received: 22 March 2018 / Revised: 9 April 2018 / Accepted: 14 April 2018 / Published: 23 April 2018
Cited by 1 | PDF Full-text (3785 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Dengue fever, a mosquito-borne arbovirus, is a major public health concern in Ecuador. In this study, we aimed to describe the spatial distribution of dengue risk and identify local social-ecological factors associated with an outbreak of dengue fever in the city of Guayaquil,
[...] Read more.
Dengue fever, a mosquito-borne arbovirus, is a major public health concern in Ecuador. In this study, we aimed to describe the spatial distribution of dengue risk and identify local social-ecological factors associated with an outbreak of dengue fever in the city of Guayaquil, Ecuador. We examined georeferenced dengue cases (n = 4248) and block-level census data variables to identify social-ecological risk factors associated with the presence/absence and burden of dengue in Guayaquil in 2012. Local Indicators of Spatial Association (LISA), specifically Anselin’s Local Moran’s I, and Moran’s I tests were used to locate hotspots of dengue transmission, and multimodel selection was used to identify covariates associated with dengue presence and burden at the census block level. We identified significant dengue transmission hotspots near the North Central and Southern portions of Guayaquil. Significant risk factors for presence of dengue included poor housing conditions, access to paved roads, and receipt of remittances. Counterintuitive positive correlations with dengue presence were observed with several municipal services such as garbage collection and access to piped water. Risk factors for increased burden of dengue included poor housing conditions, garbage collection, receipt of remittances, and sharing a property with more than one household. Social factors such as education and household demographics were negatively correlated with increased dengue burden. These findings elucidate underlying differences with dengue presence versus burden, and suggest that vulnerability and risk maps could be developed to inform dengue prevention and control; this is information that is also relevant for emerging epidemics of chikungunya and Zika viruses. Full article
(This article belongs to the Special Issue Spatio-Temporal Analysis of Infectious Diseases)
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Open AccessArticle Spatio-Temporal Epidemiology of Viral Hepatitis in China (2003–2015): Implications for Prevention and Control Policies
Int. J. Environ. Res. Public Health 2018, 15(4), 661; https://doi.org/10.3390/ijerph15040661
Received: 13 February 2018 / Revised: 19 March 2018 / Accepted: 30 March 2018 / Published: 2 April 2018
Cited by 1 | PDF Full-text (21923 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Viral hepatitis, as one of the most serious notifiable infectious diseases in China, takes heavy tolls from the infected and causes a severe economic burden to society, yet few studies have systematically explored the spatio-temporal epidemiology of viral hepatitis in China. This study
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Viral hepatitis, as one of the most serious notifiable infectious diseases in China, takes heavy tolls from the infected and causes a severe economic burden to society, yet few studies have systematically explored the spatio-temporal epidemiology of viral hepatitis in China. This study aims to explore, visualize and compare the epidemiologic trends and spatial changing patterns of different types of viral hepatitis (A, B, C, E and unspecified, based on the classification of CDC) at the provincial level in China. The growth rates of incidence are used and converted to box plots to visualize the epidemiologic trends, with the linear trend being tested by chi-square linear by linear association test. Two complementary spatial cluster methods are used to explore the overall agglomeration level and identify spatial clusters: spatial autocorrelation analysis (measured by global and local Moran’s I) and space-time scan analysis. Based on the spatial autocorrelation analysis, the hotspots of hepatitis A remain relatively stable and gradually shrunk, with Yunnan and Sichuan successively moving out the high-high (HH) cluster area. The HH clustering feature of hepatitis B in China gradually disappeared with time. However, the HH cluster area of hepatitis C has gradually moved towards the west, while for hepatitis E, the provincial units around the Yangtze River Delta region have been revealing HH cluster features since 2005. The space-time scan analysis also indicates the distinct spatial changing patterns of different types of viral hepatitis in China. It is easy to conclude that there is no one-size-fits-all plan for the prevention and control of viral hepatitis in all the provincial units. An effective response requires a package of coordinated actions, which should vary across localities regarding the spatial-temporal epidemic dynamics of each type of virus and the specific conditions of each provincial unit. Full article
(This article belongs to the Special Issue Spatio-Temporal Analysis of Infectious Diseases)
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Open AccessArticle Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan
Int. J. Environ. Res. Public Health 2018, 15(3), 396; https://doi.org/10.3390/ijerph15030396
Received: 9 February 2018 / Revised: 23 February 2018 / Accepted: 23 February 2018 / Published: 26 February 2018
PDF Full-text (4098 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found
[...] Read more.
The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found that, independently of gender, dengue incidence rate increased with age, and proportionally affected more males below the age of 40 years but females above the age of 40 years. A spatial scan statistic was applied to detect clusters of disease transmission. The scan statistic found that dengue spread in a north-south diffusion direction, which is across the North, West-Central and South districts of Tainan City. Spatial regression models were used to quantify factors associated with transmission. This analysis indicated that neighborhoods with high proportions of residential area (or low wetland cover) were associated with dengue transmission. However, these association patterns were non-linear. The findings presented here can help Taiwanese public health agencies to understand the fundamental epidemiological characteristics and diffusion patterns of the 2015 dengue outbreak in Tainan City. This type of information is fundamental for policy making to prevent future uncontrolled dengue outbreaks, given that results from this study suggest that control interventions should be emphasized in the North and West-Central districts of Tainan city, in areas with a moderate percentage of residential land cover. Full article
(This article belongs to the Special Issue Spatio-Temporal Analysis of Infectious Diseases)
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