Dengue Spatial and Temporal Patterns, French Guiana, 2001

Abstract

To study a 2001 dengue fever outbreak in Iracoubo, French Guiana, we recorded the location of all patients’ homes and the date when symptoms were first observed. A geographic information system was used to integrate the patient-related information. The Knox test, a classic space-time analysis technique, was used to detect spatiotemporal clustering. Analysis of the relative-risk (RR) variations when space and time distances vary, highlighted the maximum space and time extent of a dengue transmission focus. The results show that heterogeneity in the RR variations in space and time corresponds to known entomologic and epidemiologic factors, such as the mosquito feeding cycle and host-seeking behavior. This finding demonstrates the relevance and potential of the use of GIS and spatial statistics for elaborating a dengue fever surveillance strategy.

Concurrent Dengue and Malaria in Cayenne Hospital, French Guiana

“…Although the usual places of contamination by malaria and dengue viruses are quite different in French Guiana, considering that the incubation phase is longer for malaria than for dengue and that the population's mobility is high, a simultaneous clinical expression of the 2 diseases is plausible. Moreover, in French Guiana, dengue viruses have spread to malaria-endemic rural areas (9).…”

Técnicas Da Estatística Espacial Na Análise De Dados De Áreas No Estudo Da Dengue

“…A dinâmica de propagação de um surto de dengue em Tartagal, no norte da Argentina, foi investigada considerando o agrupamento espaço-temporal dos casos, para tal foi utilizado o teste de Knox (ROTELA et al, 2007). O teste Knox foi também usado na análise espaço-temporal dos casos de dengue em Iracoubo, Guiana Francesa (TRAN et al, 2004 PEITER, 1999). O objetivo foi analisar várias técnicas da estatística espacial no estudo da ocorrência de dengue em bairros da cidade de Lavras, Minas Gerais, cujos dados correspondem a dados de áreas (devido não se ter a localização exata de cada um dos casos de dengue), em busca de se encontrar a melhor técnica de análise da estatística espacial.…”

Geo-statistical dengue risk model using GIS techniques to identify the risk prone areas by linking rainfall and population density factors in Sri Lanka

“…After rain, more breading sites are created. But, heavy rainfall may lower dengue cases as it reduces the survival rate of Aides (Yang et al, 2009, Fouque et al, 2006, Tran et al, 2004. Heavy rainfall creates abundant outdoor breeding sources for Aedes.…”