Background: Wastewater is increasingly being used in the agricultural sector to cope with the depletion of freshwater resources as well as water stress linked to changing climate conditions. As wastewater irrigation expands, research focusing on the human health risks is critical because exposure to a range of contaminants must be weighed with the benefits to food security, nutrition and livelihoods. Objectives: The goal of this paper was to review research examining health risks and exposure pathways associated with wastewater irrigation to identify research trends and gaps. Methods: We conducted a review of the literature and identified a total of 126 studies published from 1995 to 2013. Findings were summarized based on several themes including types of exposure pathways, wastewater contaminants, methodological approaches and the geographical distribution of research. Results: Only 23 studies used epidemiological methods, while most research applied alternative methods to estimate risk, such as quantitative risk assessment models or comparisons of crop contamination to established guidelines for wastewater reuse. A geographic breakdown demonstrated a focus on microbiological contaminants in specific regions such as sub-Saharan Africa and Southeast Asia, despite growing chemical risks associated with rapid urbanization and industrialization that may change the types and distribution of wastewater contaminants. Conclusions: To provide a more comprehensive understanding of the health risks of wastewater use in agriculture, future research should consider multiple exposure routes, long-term health implications, and increase the range of contaminants studied, particularly in regions heavily dependent on wastewater irrigation. Citation: Dickin SK, Schuster-Wallace CJ, Qadir M, Pizzacalla K. 2016. A review of health risks and pathways for exposure to wastewater use in agriculture. Environ Health Perspect 124:900–909; http://dx.doi.org/10.1289/ehp.1509995

Agriculture is directly related to food security as it determines the global food supply. Research in agriculture to predict crop productivity and losses helps avoid high food demand with little supply and price spikes. Here, we review ten crop models and one intercomparison project used for simulating crop growth and productivity under various impacts from soil–crop–atmosphere interactions. The review outlines food security and production assessments using numerical models for maize, wheat, and rice production. A summary of reviewed studies shows the following: (1) model ensembles provide smaller modeling errors compared to single models, (2) single models show better results when coupled with other types of models, (3) the ten reviewed crop models had improvements over the years and can accurately predict crop growth and yield for most of the locations, management conditions, and genotypes tested, (4) APSIM and DSSAT are fast and reliable in assessing broader output variables, (5) AquaCrop is indicated to investigate water footprint, quality and use efficiency in rainfed and irrigated systems, (6) all models assess nitrogen dynamics and use efficiency efficiently, excluding AquaCrop and WOFOST, (7) JULES specifies in evaluating food security vulnerability, (8) ORYZA is the main crop model used to evaluate paddy rice production, (9) grain filling is usually assessed with APSIM, DAISY, and DSSAT, and (10) the ten crop models can be used as tools to evaluate food production, availability, and security.

The purpose of this study was to better understand the gender violence risks that exist in communities where poor water, sanitation, and hygiene (WaSH) access is a known problem. Focus groups and key informant interviews were used to capture the lived experiences of community and health care practitioners from Rwanda, Tanzania, Uganda, and Kenya. This article provides lived narratives of the various cultural and environmental conditions leading to assaults directly attributable to inadequate WaSH. The results shed light on the complex intersections between water access and violence and have significant implications for achieving gender equity and universal access to WaSH.

The Water-associated Disease Index (WADI) was developed to identify and visualize vulnerability to different water-associated diseases by integrating a range of social and biophysical determinants in map format. In this study vulnerability is used to encompass conditions of exposure, susceptibility, and differential coping capacity to a water-associated health hazard. By assessing these conditions, the tool is designed to provide stakeholders with an integrated and long-term understanding of subnational vulnerabilities to water-associated disease and contribute to intervention strategies to reduce the burden of illness. The objective of this paper is to describe and validate the WADI tool by applying it to dengue. A systemic ecohealth framework that considers links between people, the environment and health was applied to identify secondary datasets, populating the index with components including climate conditions, land cover, education status and water use practices. Data were aggregated to create composite indicators of exposure and of susceptibility in a Geographic Information System (GIS). These indicators were weighted by their contribution to dengue vulnerability, and the output consisted of an overall index visualized in map format. The WADI was validated in this Malaysia case study, demonstrating a significant association with dengue rates at a sub-national level, and illustrating a range of factors that drive vulnerability to the disease within the country. The index output indicated high vulnerability to dengue in urban areas, especially in the capital Kuala Lumpur and surrounding region. However, in other regions, vulnerability to dengue varied throughout the year due to the influence of seasonal climate conditions, such as monsoon patterns. The WADI tool complements early warning models for water-associated disease by providing upstream information for planning prevention and control approaches, which increasingly require a comprehensive and geographically broad understanding of vulnerability for implementation.