Spatio-temporal patterns of tuberculosis incidence in Ribeirao Preto, State of Sao Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

Introduction: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirao Preto, State of Sao Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. Methods: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. Results: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirao Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. Conclusions: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

Do Higher Temperatures Increase Growth in the Nocturnal Gecko Homonota darwini (Gekkota: Phyllodactylidae)? A Skeletochronological Assessment Analyzed at Temporal and Geographic Scales

Recent studies predict that several lineages of tropical animals are at particular risk given current estimates of global climate change. Yet, much uncertainty exists on the effects of climate shifts in ectothermic species from cool temperate regions such as Patagonia. In this study, we focus on the impact of environmental temperature on growth, age at sexual maturity, and life-span of the Patagonian gecko Homonota darwini. Skeletochronological methods were used to assess the bone growth rates Of individuals from three populations at different geographic and temporal scales: two populations from Chubut (warm site; 1941 and 2010) and one population from Rio Negro (cold site; 1997-1998). Populations displayed similar bone arrangement and the growth patterns fit a von Bertalanffy curve. Three populations attained reproductive size at a minimum age of 3 yr, but at the cold site two specimens were shown to mature in 4 yr. We found no differences in juvenile growth rates in body size or bone zone width between juveniles of 1 to 3 yr of age from the 1941 warm site and the 2010 warm site. However, these traits appeared to be higher at these two warm sites than at the cold site, which is consistent with the climatic differences among the three localities. Our results suggest that higher temperatures positively affect growth, denoting that global warming might benefit H. darwini, especially the southern populations.

Spatio-temporal patterns of tuberculosis incidence in Ribeirão Preto, State of São Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.