Semiparametric modeling of the spatial distribution of occupational accident risk in the casual labor market, Piracicaba, southeast Brazil

The objective of this study was to estimate the spatial distribution of work accident risk in the informal work market in the urban zone of an industrialized city in southeast Brazil and to examine concomitant effects of age, gender, and type of occupation after controlling for spatial risk variation. The basic methodology adopted was that of a population-based case-control study with particular interest focused on the spatial location of work. Cases were all casual workers in the city suffering work accidents during a one-year period; controls were selected from the source population of casual laborers by systematic random sampling of urban homes. The spatial distribution of work accidents was estimated via a semiparametric generalized additive model with a nonparametric bidimensional spline of the geographical coordinates of cases and controls as the nonlinear spatial component, and including age, gender, and occupation as linear predictive variables in the parametric component. We analyzed 1,918 cases and 2,245 controls between 1/11/2003 and 31/10/2004 in Piracicaba, Brazil. Areas of significantly high and low accident risk were identified in relation to mean risk in the study region (p < 0.01). Work accident risk for informal workers varied significantly in the study area. Significant age, gender, and occupational group effects on accident risk were identified after correcting for this spatial variation. A good understanding of high-risk groups and high-risk regions underpins the formulation of hypotheses concerning accident causality and the development of effective public accident prevention policies.

Characterization of heat waves affecting mortality rates of broilers between 29 days and market age

Climate may affect broiler production, especially where there are heat waves, which may cause high mortality rates due to the heat stress. Heat wave prediction and characterization may allow early mitigation actions to be taken. Data Mining is one of the tools used for such a characterization, particularly when a large number of variables is involved. The objective of this study was to classify heat waves that promote broiler chicken mortality in poultry houses equipped with minimal environmental control. A single day of heat, a heat-shock day, is capable of producing high broiler mortality. In poultry houses equipped with fans and evaporative cooling, the characterization of heat waves affecting broiler mortality between 29 days of age and market age presented 89.34% Model Accuracy and 0.73 Class Precision for high mortality. There was no influence on high mortality (HM) of birds between 29 and 31 days of age. Maximum temperature humidity index (THI) above 30.6 ºC was the main characteristic of days when there was a heat wave, causing high mortality in broilers older than 31 days. The high mortality of broilers between 31 and 40 days of age occurred when maximum THI was above 30.6 ºC and maximum temperature of the day was above 34.4 ºC. There were two main causes of high mortality of broilers older than 40 days: 1) maximum THI above 30.6 ºC and minimum THI equal or lower than 15.5 ºC; 2) maximum THI above 30.6 ºC, minimum THI lower than 15.5 ºC, and the time of maximum temperature later than 15:00h. The heat wave influence on broiler mortality lasted an average of 2.7 days.