Spatiotemporal-based clusters as a method for dengue surveillance / Uso de conglomerados basados en el tiempo y el espacio como método de vigilancia del dengue / Conglomerados espaçotemporais como método de vigilância da dengue

[ABSTRACT]. Objectives. To develop and demonstrate the use of a new method for epidemiological surveillance of dengue. Methods. This was a retrospective cohort study using data from the Health Department of São José do Rio Preto (São Paulo, Brazil). The geographical coordinates were obtained using QGIS™ (Creative Commons Corporation, Mountain View, California, United States), based on patient addresses in the dengue notification system of the Government of Brazil. SaTScan™ (Martin Kulldorff, Boston, Massachusetts, United States) was then used to create a space-time scan analysis to find statistically significant clusters of dengue. These results were plotted and visualized using Google Earth™ mapping service (Google Incorporated, Mountain View, California, United States). Results. More clusters were detected when the maximum number of households per cluster was set to 10% (11 statistically significant clusters) rather than 50% (8 statistically significant clusters). The cluster radius varied from 0.18 – 2.04 km and the period of time varied from 6 days – 6 months. The infection rate was more than 0.5 cases/household. Conclusions. When using SaTScan for space-time analysis of dengue cases, the maximum number of households per cluster should be set to 10%. This methodology may be useful to optimizing dengue surveillance systems, especially in countries where resources are scarce and government programs have not had much success controlling the disease.

[RESUMEN]. Objetivos. Elaborar un método nuevo para la vigilancia epidemiológica del dengue y hacer una demostración sobre su uso. Métodos. Se realizó un estudio retrospectivo de cohortes usando datos del Departamento de Salud de São José do Rio Preto (São Paulo, Brasil). Partiendo de la dirección de los pacientes en el sistema de notificación del dengue del Gobierno de Brasil, se usó QGIS™ (Creative Commons Corporation, Mountain View, California, Estados Unidos) para obtener sus coordenadas geográficas. Luego se usó SaTScan™ (Martin Kulldorff, Boston, Massachusetts, Estados Unidos) para crear un análisis de exploración espacio-temporal a fin de detectar conglomerados de dengue estadísticamente significativos. Por último, se usó el servicio de mapas de Google Earth™ (Google Incorporated, Mountain View, California, Estados Unidos) para graficar y visualizar estos resultados. Resultados. Se detectaron más conglomerados cuando el número máximo de viviendas por conglomerado se estableció en 10% (11 conglomerados estadísticamente significativos) en lugar de 50% (8 conglomerados estadísticamente significativos). El radio de los conglomerados se ubicó entre 0,18 y 2,04 km, y la duración entre 6 días y 6 meses. La tasa de infección fue de más de 0,5 casos por vivienda. Conclusiones. Cuando se usa SaTScan, el número máximo de viviendas por conglomerado debe establecerse en 10% para el análisis de exploración. Este método puede ser útil para optimizar los sistemas de vigilancia del dengue, especialmente en aquellos países donde los recursos son escasos y los programas gubernamentales no han tenido mucho éxito para controlar la enfermedad.

[RESUMO]. Objetivos. Desenvolver um novo método de vigilância epidemiológica da dengue e demonstrar a sua aplicação. Métodos. Estudo de coorte retrospectiva conduzido com dados obtidos da Secretaria de Saúde de São José do Rio Preto, Estado de São Paulo, Brasil. As coordenadas geográficas foram obtidas com o software QGIS™ (Creative Commons Corporation, Mountain View, Califórnia, EUA) segundo os endereços dos pacientes registrados no sistema de notificação do Programa Nacional de Controle da Dengue do Ministério da Saúde do Brasil. Foi usado o software SaTScan™ (Martin Kulldorff, Boston, Massachusetts, EUA) com o método Scan espaçotemporal para a detecção de conglomerados espaciais de casos de dengue com significância estatística. Os resultados foram representados graficamente e visualizados com a ferramenta de geomapeamento Google Earth™ (Google Incorporated, Mountain View, Califórnia, EUA). Resultados. Detectou-se um número maior de conglomerados espaciais ao se estabelecer o número máximo de domicílios por conglomerado em 10% em comparação a 50% (11 versus 8 conglomerados com significância estatística). O raio dos conglomerados espaciais detectados variou de 0,18 km a 2,04 km e o período de tempo oscilou entre 6 dias e 6 meses. A taxa de infecção foi superior a 0,5 caso por domicílio. Conclusões. O número máximo de domicílios por conglomerado deve ser de 10% ao conduzir a análise da distribuição espacial com o SaTScan. Este método pode contribuir para melhorar o desempenho dos sistemas de vigilância da dengue, sobretudo nos países com recursos limitados e resultados insatisfatórios nos programas nacionais de controle da doença.

Evaluation of the importance of fever with respect to dengue prognosis according to the 2009 WHO classification: a retrospective study.

BACKGROUND: The 2009 revised World Health Organization (WHO) guidelines for dengue describe fever as the core symptom. Accordingly, the diagnosis of non-febrile patients is complicated. The aim of this study was to evaluate the importance of fever in patients with dengue according to the 2009 revised WHO classification. METHODS: In this study, we assessed 30,670 dengue cases using enzyme-linked immunosorbent assay, detection of the non-structural protein 1, or polymerase chain reaction for diagnostic confirmation. Fisher's exact test was used to evaluate associations between fever and related clinical manifestations. The Mann-Whitney U test was used to assess the association of dengue classification with fever and time to treatment. The effects of fever and time to treatment on the risk of progression were analyzed using an ordinal logistic regression to stereotype the model. RESULTS: Disease classification was found to associate significantly with both fever and time to treatment (both P < 0.001). Non-febrile patients were nearly four-fold more likely to exhibit "dengue without warning signs" than "severe dengue" (odds ratio [OR] = 3.74; 95% confidence interval [CI]: 3.20-4.36). Patients who received treatment within 7 days were twice as likely to have "dengue without warning signs" as opposed to "severe dengue" when compared to those who waited >7 days (OR = 2.23; 95% CI: 1.78-2.80). However, this difference was negligible in the multivariate analysis (OR = 1.02; 95% CI: 0.98-1.07). CONCLUSIONS: Fever is a risk factor for disease progression in patients with dengue. However, non-febrile patients should not be neglected because this may delay treatment and could lead to more severe disease.

Spatiotemporal-based clusters as a method for dengue surveillance.

OBJECTIVES: To develop and demonstrate the use of a new method for epidemiological surveillance of dengue. METHODS: This was a retrospective cohort study using data from the Health Department of São José do Rio Preto (São Paulo, Brazil). The geographical coordinates were obtained using QGIS™ (Creative Commons Corporation, Mountain View, California, United States), based on patient addresses in the dengue notification system of the Government of Brazil. SaTScan™ (Martin Kulldorff, Boston, Massachusetts, United States) was then used to create a space-time scan analysis to find statistically significant clusters of dengue. These results were plotted and visualized using Google Earth™ mapping service (Google Incorporated, Mountain View, California, United States). RESULTS: More clusters were detected when the maximum number of households per cluster was set to 10% (11 statistically significant clusters) rather than 50% (8 statistically significant clusters). The cluster radius varied from 0.18 - 2.04 km and the period of time varied from 6 days - 6 months. The infection rate was more than 0.5 cases/household. CONCLUSIONS: When using SaTScan for space-time analysis of dengue cases, the maximum number of households per cluster should be set to 10%. This methodology may be useful to optimizing dengue surveillance systems, especially in countries where resources are scarce and government programs have not had much success controlling the disease.

Spatiotemporal-based clusters as a method for dengue surveillance / Uso de conglomerados basados en el tiempo y el espacio como método de vigilancia del dengue / Conglomerados espaçotemporais como método de vigilância da dengue

ABSTRACT Objectives To develop and demonstrate the use of a new method for epidemiological surveillance of dengue. Methods This was a retrospective cohort study using data from the Health Department of São José do Rio Preto (São Paulo, Brazil). The geographical coordinates were obtained using QGIS™ (Creative Commons Corporation, Mountain View, California, United States), based on patient addresses in the dengue notification system of the Government of Brazil. SaTScan™ (Martin Kulldorff, Boston, Massachusetts, United States) was then used to create a space-time scan analysis to find statistically significant clusters of dengue. These results were plotted and visualized using Google Earth™ mapping service (Google Incorporated, Mountain View, California, United States). Results More clusters were detected when the maximum number of households per cluster was set to 10% (11 statistically significant clusters) rather than 50% (8 statistically significant clusters). The cluster radius varied from 0.18 - 2.04 km and the period of time varied from 6 days - 6 months. The infection rate was more than 0.5 cases/household. Conclusions When using SaTScan for space-time analysis of dengue cases, the maximum number of households per cluster should be set to 10%. This methodology may be useful to optimizing dengue surveillance systems, especially in countries where resources are scarce and government programs have not had much success controlling the disease.

RESUMEN Objetivos Elaborar un método nuevo para la vigilancia epidemiológica del dengue y hacer una demostración sobre su uso. Métodos Se realizó un estudio retrospectivo de cohortes usando datos del Departamento de Salud de São José do Rio Preto (São Paulo, Brasil). Partiendo de la dirección de los pacientes en el sistema de notificación del dengue del Gobierno de Brasil, se usó QGIS™ (Creative Commons Corporation, Mountain View, California, Estados Unidos) para obtener sus coordenadas geográficas. Luego se usó SaTScan™ (Martin Kulldorff, Boston, Massachusetts, Estados Unidos) para crear un análisis de exploración espacio-temporal a fin de detectar conglomerados de dengue estadísticamente significativos. Por último, se usó el servicio de mapas de Google Earth™ (Google Incorporated, Mountain View, California, Estados Unidos) para graficar y visualizar estos resultados. Resultados Se detectaron más conglomerados cuando el número máximo de viviendas por conglomerado se estableció en 10% (11 conglomerados estadísticamente significativos) en lugar de 50% (8 conglomerados estadísticamente significativos). El radio de los conglomerados se ubicó entre 0,18 y 2,04 km, y la duración entre 6 días y 6 meses. La tasa de infección fue de más de 0,5 casos por vivienda. Conclusiones Cuando se usa SaTScan, el número máximo de viviendas por conglomerado debe establecerse en 10% para el análisis de exploración. Este método puede ser útil para optimizar los sistemas de vigilancia del dengue, especialmente en aquellos países donde los recursos son escasos y los programas gubernamentales no han tenido mucho éxito para controlar la enfermedad.

RESUMO Objetivos Desenvolver um novo método de vigilância epidemiológica da dengue e demonstrar a sua aplicação. Métodos Estudo de coorte retrospectiva conduzido com dados obtidos da Secretaria de Saúde de São José do Rio Preto, Estado de São Paulo, Brasil. As coordenadas geográficas foram obtidas com o software QGIS™ (Creative Commons Corporation, Mountain View, Califórnia, EUA) segundo os endereços dos pacientes registrados no sistema de notificação do Programa Nacional de Controle da Dengue do Ministério da Saúde do Brasil. Foi usado o software SaTScan™ (Martin Kulldorff, Boston, Massachusetts, EUA) com o método Scan espaçotemporal para a detecção de conglomerados espaciais de casos de dengue com significância estatística. Os resultados foram representados graficamente e visualizados com a ferramenta de geomapeamento Google Earth™ (Google Incorporated, Mountain View, Califórnia, EUA). Resultados Detectou-se um número maior de conglomerados espaciais ao se estabelecer o número máximo de domicílios por conglomerado em 10% em comparação a 50% (11 versus 8 conglomerados com significância estatística). O raio dos conglomerados espaciais detectados variou de 0,18 km a 2,04 km e o período de tempo oscilou entre 6 dias e 6 meses. A taxa de infecção foi superior a 0,5 caso por domicílio. Conclusões O número máximo de domicílios por conglomerado deve ser de 10% ao conduzir a análise da distribuição espacial com o SaTScan. Este método pode contribuir para melhorar o desempenho dos sistemas de vigilância da dengue, sobretudo nos países com recursos limitados e resultados insatisfatórios nos programas nacionais de controle da doença.

Low sensitivity of the tourniquet test for differential diagnosis of dengue: an analysis of 28,000 trials in patients.

BACKGROUND: The aim of this study was to evaluate the utility of the tourniquet test (TT) for dengue diagnosing. To our knowledge, no previous study with such a large sample, of this duration, with as many laboratory methods referenced, or relating the results of the TT to the 2009 WHO classification of severity has been conducted thus far. METHODS: In this study, we analyzed the records of 119,589 suspected dengue cases in a Brazilian city, with 30,670 confirmed cases. The Cohen's Kappa test was applied to evaluate the degree of agreement between the tests, and the sensitivity and specificity was calculated for the TT. RESULTS: Twenty-eight thousand six hundred thirty-five TT were performed. No association between the outcome of the TT and greater severity of infection, according to the 2009 guideline, was observed (P = 0.28); furthermore, relevant agreement with the final diagnosis (κ = 0.01; 95 % CI = 0.00 to 0.02) or individually with the IgM enzyme-linked immunoassay was not observed (κ = 0.05; 95 % CI = 0.04 to 0.06), and was even lower with PCR (κ = 0.27; 95 % CI = 0.06 to 0.49). Most importance of the TT was shown in relation to specificity (88.9 %; 95 % CI = 0.88 to 0.89) and negative predictive value (70.3 %; CI 95 % = 0.70 to 0.71). CONCLUSIONS: TT was more effective in detecting cases that were truly negative than positive. These results suggest that the TT should not be used as diagnosis of dengue.