تجزیه و تحلیل حساسیت از شاخص های زراعتی زیست محیطی از فشار بهداشتی از تولید دام موثر بر سلامت جامعه

Two Agroenvironmental hygienic pressure indicators (AHPIs) were developed to evaluate the effects of livestock production on water contamination and the risk for human health by expressing a complex public health risk via simple quantifiable figures. The first of the two AHPIs is addressing the aspect of surface water contamination while the second one is dealing with groundwater contamination. Each of the two AHPIs is built from a multiplicative model based on 25 parameters related to the transmission of bacteria through excretion by animals, survival in manure, and by run-off or infiltration water produced by rainfall. A global sensitivity approach was used to identify the most significant parameters in regard to the AHPIs output results. This analysis found that bacterial survival on the soil after manure spreading or grazing of animals (Ks), the proportion of bacteria able to reach surface water with run-off from manure on the soil (Brun-off), bacteria concentration in faeces Bconc, within-herd proportion of animals shedding the pathogenic bacteria targeted (Bprev) and the area used for pasture (A) – on bovine farms – are the most influential parameters with respect to the estimation of the AHPIs. With the exception of the latter element, these factors are all directly related to bacterial characteristics and parameters for which obtaining high quality data is most challenging. The identification of these most influential parameters will guide further research to enhance both the precision application of the AHPIs, and their use in managing public health risks.

A global sensitivity analysis was performed on agroenvironmental hygienic pressure indicators (AHPIs) aimed at evaluating the hygienic pressure from livestock production on human health. A specific factorial design was used in order to account for relations in herd composition including the type of farm and patterns of prevalence animals excreting pathogens in their faeces. This design allowed for the detection of differences in the AHPIs sensitivity for some of the most common farm types encountered in Quebec. Because the AHPIs are model-based indicators it is reasonable to expect that the sensitivity would be similar for AHPIs uses in other areas of the world with similar farm production context. From the results of this analysis, the most significant parameters for which good quality data are necessary were identified. Of all the parameters studied, the most significant identified were: the coefficient of bacterial survival in soil; the initial bacterial concentration in animal faeces; the proportion of microorganisms able to reach waters from the field; the intra-herd prevalence of shedding animals; and the area used for pasture. These are predominantly related to the bacterial dynamics in the agroenvironment, with exception of the area used for pasture Ap in the case of the dairy farm. The results clearly identify the importance of good quality microbiological data as well as a better understanding of the microbiological population dynamic of survival and movement in the agroenvironment. There remain major scientific knowledge gaps to fill for several areas where good data is needed, such as survival and movement of bacteria within storage and on the soil. For other factors such as prevalence of bacteria shedding, the task of obtaining better data does not present so much a scientific challenge as a financial one. The work presented here should allow for the prioritisation of data collection to reduce the timeframe before these tools can be of potential value as decision aid tools for the management of a common public health risk – the contamination of drinking water by pathogenic bacteria transmitted from livestock. In light of their intended capacity to be used by decision-makers, the AHPIs represent a compelling relevance to the public in terms of managing a significant risk to human health. Though better microbiological data is called for, the preliminary analysis is encouraging with regard to the AHPIs potential as a decision-making tool in regional and wider levels of management of public health risks.