Influence of spatial heterogeneity on an emerging infectious disease: the case of dengue epidemics

Favier, Charly; Schmit, Delphine; Müller‐Graf, Christine; Cazelles, Bernard; Dégallier, Nicolas; Mondet, Bernard; Dubois, Marc

doi:10.1098/rspb.2004.3020

Cited by 104 publications

(99 citation statements)

References 26 publications

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“…Models were fitted separately according to hierarchically structured theory 19 especially considering two levels of exposure: local level (within households) and global levels (social and demographic conditions). 20 Most of the variables were analyzed in the original format but the variable representing the population with restricted mobility was split in three categories according to the percentiles 25 and 50, to better fit the model.…”

Section: Discussionmentioning

confidence: 99%

Spatial Vulnerability to Dengue in a Brazilian Urban Area During a 7-Year Surveillance

et al. 2007

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This study considers the vulnerability of the urban area of the City of Belo Horizonte to dengue. A total number of 89,607 cases registered in the surveillance system from 1996 to 2002 were analyzed. Seven epidemic waves were identified during this period. Cases were grouped into 2,563 census areas, and three risk categories were proposed based on how many times each area reached a threshold established for each epidemic wave. The association between the risk categories and the socioeconomic, demographic and urban-infrastructure characteristics was evaluated. Analysis included Kruskal-Wallis test variance comparisons and multivariate regression using multinomial models. Incidence rates differed significantly among the three risk categories in most of the epidemic waves. The factors that best characterized the areas were low educational level ( e 4 years of schooling), low income of the head of the family ( e 2 minimum wages per household), household density, and proportion of children and elderly women. Information related to basic sanitation was not enough to discriminate levels of susceptibility to dengue, and study of population density and concentration of establishments considered vulnerable to vector infestation yielded questionable results. It is important to consider different levels of exposure of the population to explain the heterogeneous pattern of distribution of dengue cases in an urban setting. Understanding the dynamics of dengue fever is essential for surveillance purposes, to improve control measures and to avoid epidemics of this disease.

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Section: Discussionmentioning

confidence: 99%

Spatial Vulnerability to Dengue in a Brazilian Urban Area During a 7-Year Surveillance

et al. 2007

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“…16,[23][24][25][26][27][28][29] In the past several decades, dengue cases have been detected in rural areas in Thailand, Indonesia, India, Malaysia, Peru, Brazil and Cameroon. [30][31][32][33] The vector for dengue transmission and dengue virus antigen in mosquitoes has also been detected in these regions.…”

Section: Discussionmentioning

confidence: 99%

Hospital-Based Prevalence of Malaria and Dengue in Febrile Patients in Bangladesh

Faruque

Zaman

Alamgir³

et al. 2012

The American Society of Tropical Medicine and Hygiene

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Acknowledgments: We thank the head of the departments of medicine and pediatric units of the participating hospitals for their consistent support; the surveillance physicians and field assistants for their continuous effort in collecting data; Abdur Rouf Siddique and Md. Zakaria Hossain for providing technical support for sample collection throughout the study; Dorothy Southern for her guidance in writing and reviewing the drafts; and M. Abu Yushuf Sharker for his statistical support in data analysis.

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“…Modeling approaches demonstrate that dengue epidemics vary spatially on a local scale due to the nature of the human population structure (Favier et al, 2005;Halstead, 2008). Socioeconomic characteristics of households related to uncontrolled urbanization, migration, deficiencies in water supply and garbage disposal, and vector control activities can play a significant role in the spatio-temporal distribution of dengue virus transmission (Caprara et al, 2009;Gómez-Dantés et al, 2011;Gómez-Dantés and Ramsey, 2009;Martín et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal and neighborhood characteristics of two dengue outbreaks in two arid cities of Mexico

et al. 2017

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Little is currently known about the spatial-temporal dynamics of dengue epidemics in arid areas. This study assesses dengue outbreaks that occurred in two arid cities of Mexico, Hermosillo and Navojoa, located in northern state of Sonora. Laboratory confirmed dengue cases from Hermosillo (N=2,730) and Navojoa (N=493) were geocoded by residence and assigned neighborhood-level characteristics from the 2010 Mexican census. Kernel density and Space-time cluster analysis was performed to detect high density areas and space-time clusters of dengue. Ordinary Least Square regression was used to assess the changing socioeconomic characteristics of cases over the course of the outbreaks. Both cities exhibited contiguous patterns of space-time clustering. Initial areas of dissemination were characterized in both cities by high population density, high percentage of occupied houses, and lack of healthcare. Future research and control efforts in these regions should consider these space-time and socioeconomic patterns.

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Influence of spatial heterogeneity on an emerging infectious disease: the case of dengue epidemics

Cited by 104 publications

References 26 publications

Spatial Vulnerability to Dengue in a Brazilian Urban Area During a 7-Year Surveillance

Spatial Vulnerability to Dengue in a Brazilian Urban Area During a 7-Year Surveillance

Hospital-Based Prevalence of Malaria and Dengue in Febrile Patients in Bangladesh

Spatio-temporal and neighborhood characteristics of two dengue outbreaks in two arid cities of Mexico

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