Space-Time Clustering Analyses of Occurrence of Cerebral Palsy in Northern England for Births 1991 to 2003

Características epidemiológicas da paralisia cerebral em crianças e adolescentes em uma capital do nordeste brasileiro

RESUMO O objetivo deste estudo foi descrever a prevalência de paralisia cerebral entre crianças e adolescentes, seus subtipos, as possíveis comorbidades e as características socioeconômicas das famílias. Foi realizado um estudo epidemiológico do tipo transversal a partir de um inquérito de base populacional sobre a paralisia cerebral em crianças e adolescentes na cidade de Aracaju (SE), Brasil. O estudo obteve informações sobre 240 crianças e adolescentes com paralisia cerebral a partir das respostas a um questionário feitas por seus responsáveis. Foi encontrada a prevalência de período de 1,37 em cada mil. Alguns bairros possuem prevalência de três a quatro vezes maior, revelando que a taxa de prevalência total não é um indicador homogêneo. A maioria dos participantes foi do sexo masculino (56,25%), de raça/cor declarada como parda ou preta (67,50%), sendo que a média de idade foi de 8,56 anos. A paralisia cerebral de tipo espástica bilateral foi a mais frequente (45,42%) e a comorbidade referida na maioria dos casos foi a epilepsia (48,33%). A renda familiar mensal correspondia a $252,87 dólares. O estudo revelou que as crianças e adolescentes com paralisia cerebral são, em grande parte, pertencentes a minorias sociais, de raça/cor parda ou preta, e suas famílias vivem na linha da extrema pobreza.

Spatial analysis of cerebral palsy in children and adolescents and its association with health vulnerability

Cerebral Palsy (CP) is commonly associated with low socioeconomic status. Use of spatial statistics and a Geographic Information Systems (GIS) are scarce and may contribute to the understanding of CP in a social context. To that end a spatial analysis of CP in children and adolescents was performed to analyze the association of CP with levels of vulnerability in a city (Aracaju, Sergipe) in north-eastern Brazil. In addition, an ecological study was conducted with data obtained from a populationbased survey and secondary data. Exploratory spatial data analysis and linear regression were used. A total of 288 CP cases were identified, with a prevalence of 1.65/1,000 and differences among city neighbourhoods ranging from 0-4/1,000. The mean age of cases studied was 9 years 1 month, with a standard deviation of 5 years 2 months. Most study subjects with cerebral palsy (163) were male (56.4%). The distribution of CP in the study population was not homogeneous throughout the territory. Some areas had clusters, with more cases associated with areas of high vulnerability. Spatial data analysis using GIS was useful to gain an epidemiological understanding of CP distribution that can guide decisionmaking with respect to production, distribution, and regulation of health goods as well as services at the local level.

A review of spatial methods in epidemiology, 2000-2010

Understanding the impact of place on health is a key element of epidemiologic investigation, and numerous tools are being employed for analysis of spatial health-related data. This review documents the huge growth in spatial epidemiology, summarizes the tools that have been employed, and provides in-depth discussion of several methods. Relevant research articles for 2000-2010 from seven epidemiology journals were included if the study utilized a spatial analysis method in primary analysis (n = 207). Results summarized frequency of spatial methods and substantive focus; graphs explored trends over time. The most common spatial methods were distance calculations, spatial aggregation, clustering, spatial smoothing and interpolation, and spatial regression. Proximity measures were predominant and were applied primarily to air quality and climate science and resource access studies. The review concludes by noting emerging areas that are likely to be important to future spatial analysis in public health.

Surveillance of febrile patients in a district and evaluation of their spatiotemporal associations: a pilot study

BACKGROUND

Fever is an undifferentiated clinical feature that may enhance the sensitivity of syndromic surveillance systems. By studying the spatiotemporal associations of febrile patients, it may allow early detection of case clustering that indicates imminent threat of infectious disease outbreaks in the community.

METHODS

We captured consecutive emergency department visits that led to hospitalization in a district hospital in Hong Kong during the period of 12 Sep 2005 to 14 Oct 2005. We recorded demographic data, provisional diagnoses, temperature on presentation and residential location for each patient-episode, and geocoded the residential addresses. We applied Geographical Information System technology to study the geographical distribution these cases, and their associations within a 50-m buffer zone spatially. A case cluster was defined by three or more spatially associated febrile patients within each three consecutive days.

RESULTS

One thousand and sixty six patient-episodes were eligible for analysis; 42% of them had fever (>37 degrees C; oral temperature) on presentation. Two hundred and four patient-episodes (19.1%) came from residential care homes for elderly (RCHE). We detected a total of 40 case clusters during the study period. Clustered cases were of older age; 57 (33.3%) were residents of RCHE. We found a median of 3 patients (range: 3 - 8) and time span of 3 days (range: 2 - 8 days) in each cluster. Twenty five clusters had 2 or more patients living in the same building block; 18 of them were from RCHE.

CONCLUSIONS

It is technically feasible to perform surveillance on febrile patients and studying their spatiotemporal associations. The information is potentially useful for early detection of impending infectious disease threats.

Are transient environmental agents involved in the cause of primary biliary cirrhosis? Evidence from space-time clustering analysis

The cause of primary biliary cirrhosis (PBC) is unclear. Both genetic and environmental factors are likely to contribute. Some studies have suggested that one or more infectious agents may be involved. To examine whether infections may contribute to the cause of PBC, we have analyzed for space-time clustering using population-based data from northeast England over a defined period (1987-2003). Space-time clustering is observed when excess cases of a disease are found within limited geographical areas at limited periods of time. If present, it is suggestive of the involvement of one or more environmental components in the cause of a disease and is especially supportive of infections. A second-order procedure based on K-functions was used to test for global space-time clustering using residential addresses at the time of diagnosis. The Knox method determined the spatiotemporal range over which global clustering was strongest. K-function tests were repeated using nearest neighbor thresholds to adjust for variations in population density. Individual space-time clusters were identified using Kulldorff's scan statistic. Analysis of 1015 cases showed highly statistically significant space-time clustering (P < 0.001). Clustering was most marked for cases diagnosed within 1-4 months of one another. A number of specific space-time clusters were identified. In conclusion, these novel results suggest that transient environmental agents may play a role in the cause of PBC.