Search

Two Agroenvironmental Hygienic Pressure Indicators (AHPIs) have been proposed as model-based indicators for the public health risk of surface and ground water contamination by enteropathogens from agroenvironmental sources. Each of these indicators summarises twenty five parameters. The scientific goal of this work was to assess in an ex-ante way the usefulness of these indicators. One of the major reasons why many models and indicators fail to be used is the lack of the necessary data. Hence, the first step of the study assessed the availability of the data necessary for computing the AHPIs for the province of Quebec. Another reason for lack of usage is if the indicators do not meet the needs of the targeted audience. Consequently, this article also demonstrates key aspects of the AHPIs that make them a tool that is likely to be useful for the end-user. The evaluation of the availability and quality of available data for use in the AHPI led to minor modifications to the AHPI original parameters and equations. These modifications are presented. Once modified, adequate data were acquired to compute the indicator for Escherichia coli for surface and groundwater for all livestock farms in the province of Québec, Canada. Data related to the microbial aspect of the AHPIs such as pathogen presence in livestock, its survival time in storage or on the soil, and its movement with water were the most difficult to obtain. For example, E. coli was used as a general indicator of faecal contamination in the absence of province-wide data on intra-herd contamination by specific human enteropathogens. Maps were generated and interpreted for their biophysical meaning to illustrate how the indicator values could be interpreted by various stakeholders involved in the public health management of water contamination from animal agriculture production and how this could be useful. [Copyright &y& Elsevier]

Contaminated surface water poses a risk to human populations and is a challenge for public health authorities. Climatic change, intensification of agriculture, urban development of coastal areas, and declining freshwater sources may contribute significantly to the risk of surface water contamination and increase incidence of waterborne diseases. Monitoring of surface water quality requires early detection of problems in order to minimize any negative impact on public health. Tele-epidemiology uses remote sensing and geospatial technologies to characterize the spatial and temporal variability of environmental determinants involved in the epidemiology of some diseases. By offering a systematic and integrated approach to water and risk management in public health, tele-epidemiology can be an efficient tool to assess surface water quality and any associated health risks. [ABSTRACT FROM PUBLISHER]

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 (B run-off ), bacteria concentration in faeces B conc, within-herd proportion of animals shedding the pathogenic bacteria targeted (B prev) 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. [Copyright &y& Elsevier]