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Antibiotic residues, their mixture toxicity, and the potential selection for antibiotic-resistant bacteria could pose a problem for water use and the ecosystem of reservoirs. This study aims to provide a comprehensive understanding of the occurrence, concentration, distribution, and ecological risks associated with various antibiotics in the Cirata reservoir, Indonesia. In our water and sediment samples, we detected 24 out of the 65 antibiotic residues analyzed, revealing a diverse range of antibiotic classes present. Notably, sulphonamides, diaminopyrimidine, and lincosamides were frequently found in the water, while the sediment predominantly contained tetracyclines and fluoroquinolones. Most antibiotic classes reached their highest concentrations in the water during the dry season. However, fluoroquinolones and tetracyclines showed their highest concentrations in the water during the wet season. Ecotoxicological risk assessments indicated that the impact of most antibiotic residues on aquatic organisms was negligible, except for fluoroquinolones. Looking at the impact on cyanobacteria, however, varying risks were indicated, ranging from medium to critical, with antibiotics like sulfamethoxazole, ciprofloxacin, norfloxacin, and lincomycin posing substantial threats. Among these, ciprofloxacin emerged as the antibiotic with the strongest risk. Furthermore, fluoroquinolones may have the potential to contribute to the selection of antibiotic-resistant bacteria. The presence of mixtures of antibiotic residues during the wet season significantly impacted species loss, with Potentially Affected Fraction of Species (msPAF) values exceeding 0.75 in almost 90% of locations. However, the impact of mixtures of antibiotic residues in sediment remained consistently low across all locations and seasons. Based on their occurrences and associated risks, 12 priority antibiotic residues were identified for monitoring in the reservoir and its tributaries. Moreover, the study suggests that river inflow serves as the most significant source of antibiotic residues in the reservoir. Further investigations into the relative share attribution of antibiotic sources in the reservoir is recommended to help identify effective interventions.

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The safe management of fecal sludge from the 3.4 billion people worldwide that use onsite sanitation systems can greatly reduce the global infectious disease burden. However, there is limited knowledge about the role of design, operational, and environmental factors on pathogen survival in pit latrines, urine diverting desiccation toilets, and other types of onsite toilets. We conducted a systematic literature review and meta-analysis to characterize pathogen reduction rates in fecal sludge, feces, and human excreta with respect to pH, temperature, moisture content, and the use of additives for desiccation, alkalinization, or disinfection. A meta-analysis of 1,382 data points extracted from 243 experiments described in 26 articles revealed significant differences between the decay rates and T99 values of pathogens and indicators from different microbial groups. The overall median T99 values were 4.8 days, 29 days, >341 days, and 429 days for bacteria, viruses, protozoan (oo)cysts, and Ascaris eggs, respectively. As expected, higher pH values, higher temperatures, and the application of lime all significantly predicted greater pathogen reduction rates but the use of lime by itself was more effective for bacteria and viruses than for Ascaris eggs, unless urea was also added. In multiple lab-scale experiments, the application of urea with enough lime or ash to reach a pH of 10 - 12 and a sustained concentration of 2,000 - 6,000 mg/L of non-protonated NH3-N reduced Ascaris eggs more rapidly than without urea. In general, the storage of fecal sludge for 6 months adequately controls hazards from viruses and bacteria, but much longer storage times or alkaline treatment with urea and low moisture or heat is needed to control hazards from protozoa and helminths. More research is needed to demonstrate the efficacy of lime, ash, and urea in the field. More studies of protozoan pathogens are also needed, as very few qualifying experiments were found for this group.

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Ensuring safe irrigation practices is vital to sustaining food production in water-scarce delta areas. Bangladesh and many other developing countries discharge untreated wastewater into their surrounding surface water bodies, serving as the primary irrigation source. This indirect irrigation of wastewater is believed to pose threats to the farmers, consumers and market vendors and may also affect crop and soil quality. To assess the risk, peri-urban farmers who use surrounding water bodies of Khulna city, Bangladesh, for crop irrigation were selected for the study. The microbial and heavy metal concentrations were measured in water samples collected from various locations over different seasons. For heavy metals As, Co, Ni, Cd, Cr, Cu and Pb, concentrations were below the detection limit, whereas Al, Fe, Mn, Ti and Zn were present but below the FAO recommendation limit for safe irrigation. The mean concentrations of microbial parameters were above the thresholds of WHO guidelines for crop irrigation intended for human consumption. Significant temporal variations in Faecal Coliform, E. coli and Enterococcus concentrations in the water samples were observed. The annual risk of infection for farmers was determined using the screening-level Quantitative Microbial Risk Assessment (QMRA). The results indicated that the annual probability of infection with pathogenic E. coli in different seasons ranges between 5 × 10-3 to 5 × 10-2, above the WHO's acceptable threshold for annual risk of infection for safe water reuse in agriculture. During the farmers' survey, around 45% reported health-related issues and more than 26% reported suffering from water-borne diseases after getting in contact with polluted surface water. This illustrates the actuality of the risks in practice. To ensure safe irrigation, the health risks need to be reduced below the acceptable limits. Suggested technical measures include adequate treatment of wastewater before disposal into rivers and access to protective equipment for farmers. This should be complemented by raising awareness through education programs among farmers to reduce accidental ingestion.

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Livestock production is often a source of multiple pollutants in rivers. However, current assessments of water pollution seldomly take a multi-pollutant perspective, while this is essential for improving water quality. This study quantifies inputs of multiple pollutants to rivers from livestock production worldwide, by animal types and spatially explicit. We focus on nitrogen (N), phosphorus (P), and Cryptosporidium (pathogen). We developed the MARINA-Global-L (Model to Assess River Inputs of pollutaNts to seAs for Livetsock) model for 10,226 sub-basins and eleven livestock species. Global inputs to land from livestock are around 94 Tg N, 19 Tg P, and 2.9 × 1021 oocysts from Cryptosporidium in 2010. Over 57% of these amounts are from grazed animals. Asia, South America, and Africa account for over 68% of these amounts on land. The inputs to rivers are around 22 Tg Total Dissolved Nitrogen (TDN), 1.8 Tg Total Dissolved P (TDP), and 1.3 × 1021 oocysts in 2010. Cattle, pigs, and chickens are responsible for 74-88% of these pollutants in rivers. One-fourth of the global sub-basins can be considered pollution hotspots and contribute 71-95% to the TDN, TDP, and oocysts in rivers. Our study could contribute to effective manure management for individual livestock species in sub-basins to reduce multiple pollutants in rivers.

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Faecal pathogens can be introduced into surface water through open defecation, illegal disposal and inadequate treatment of faecal sludge and wastewater. Despite sanitation improvements, poor countries are progressing slowly towards the United Nation's Sustainable Development Goal 6 by 2030. Sanitation-associated pathogenic contamination of surface waters impacted by future population growth, urbanization and climate change receive limited attention. Therefore, a model simulating human rotavirus river inputs and concentrations was developed combining population density, sanitation coverage, rotavirus incidence, wastewater treatment and environmental survival data, and applied to Uganda. Complementary surface runoff and river discharge data were used to produce spatially explicit rotavirus outputs for the year 2015 and for two scenarios in 2050. Urban open defecation contributed 87%, sewers 9% and illegal faecal sludge disposal 3% to the annual 15.6 log10 rotavirus river inputs in 2015. Monthly concentrations fell between -3.7 (Q5) and 2.6 (Q95) log10 particles per litre, with 1.0 and 2.0 median and mean log10 particles per litre, respectively. Spatially explicit outputs on 0.0833 × 0.0833° grids revealed hotspots as densely populated urban areas. Future population growth, urbanization and poor sanitation were stronger drivers of rotavirus concentrations in rivers than climate change. The model and scenario analysis can be applied to other locations.

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Water and wastewater utilities, water and sanitation hygiene (WASH) practitioners, and regulating bodies, particularly in developing nations, rely heavily on indicator microorganisms, as opposed to pathogens, for much of their regulatory decisions. This commentary illustrates the importance of considering pathogens and not relying only on indicator organisms when making decisions regarding water and sanitation, especially with respect to meeting the current targets of the Sustainable Development Goal (SDG) 6. We use quantitative microbial risk assessment (QMRA) to present three common scenarios that WASH and public health practitioners encounter to illustrate our point. These include 1) chlorination of surface water for drinking, 2) land application of latrine waste as a fertilizer, and 3) recreation/domestic use of surface waters impacted by wastewater discharge. We show that the calculated probabilities of risk of infection are statistically significantly higher when using treatment/survival information for pathogens versus using indicator species data. Thus, demonstrating that relying solely on indicators for sanitation decision making is inadequate if we truly want to achieve the SDG6 targets of safely managed water and sanitation services.

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Sanitation planners make complex decisions in the delivery of sanitation services to achieve health outcomes. We present findings from a stakeholder engagement workshop held in Kampala, Uganda, to educate, interact with, and solicit feedback from participants on how the relevant scientific literature on pathogens can be made more accessible to practitioners to support decision-making. We targeted Water, Sanitation and Hygiene (WASH) practitioners involved in different levels of service delivery. Practitioners revealed that different sanitation planning tools are used to inform decision-making; however, most of these tools are not user-friendly or adapted to meet their needs. Most stakeholders (68%) expressed familiarity with pathogens, yet less than half (46%) understood that fecal coliforms were bacteria and used as indicators for fecal pollution. A number of stakeholders were unaware that fecal indicator bacteria do not behave and persist the same as helminths, protozoa, or viruses, making fecal indicator bacteria inadequate for assessing pathogen reductions for all pathogen groups. This suggests a need for awareness and capacity development around pathogens found in excreta. The findings underscore the importance to engage stakeholders in the development of support tools for sanitation planning and highlighted broader opportunities to bridge science with practice in the WASH sector.

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The protozoan pathogen Cryptosporidium is an important cause of diarrhoeal disease, but in many contexts its burden remains uncertain. The Global Waterborne Pathogen model for Cryptosporidium (GloWPa-Crypto) predicts oocyst concentrations in surface water at 0.5 by 0.5° (longitude by latitude) resolution, allowing us to assess the burden specifically associated with the consumption of contaminated surface water at a large scale. In this study, data produced by the GloWPa-Crypto model were used in a quantitative microbial risk assessment (QMRA) for sub-Saharan Africa, one of the regions most severely affected by diarrhoeal disease. We first estimated the number of people consuming surface water in this region and assessed both direct consumption and consumption from a piped (treated) supply. The disease burden was expressed in disability adjusted life years (DALYs). We estimate an annual number of 4.3 × 107 (95% uncertainty interval [UI] 7.4 × 106-5.4 × 107) cases which represent 1.6 × 106 (95% UI 3.2 × 105-2.3 × 106) DALYs. Relative disease burden (DALYs per 100,000 persons) varies widely, ranging between 1.3 (95% UI 0.1-5.7) for Senegal and 1.0 × 103 (95% UI 4.2 × 102-1.4 × 103) for Eswatini. Countries that carry the highest relative disease burden are primarily located in south and south-east sub-Saharan Africa and are characterised by a relatively high HIV/AIDS prevalence. Direct surface water consumption accounts for the vast majority of cases, but the results also point towards the importance of stable drinking water treatment performance. This is, to our knowledge, the first study to utilise modelled data on pathogen concentrations in a large scale QMRA. It demonstrates the potential value of such data in epidemiological research, particularly regarding disease aetiology.

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Microbial pollution is a major problem worldwide. High concentrations of Escherichia coli have been found in Kabul River in Pakistan. E. coli concentrations vary under different socio-economic conditions, such as population and livestock densities, urbanisation, sanitation and treatment of wastewater and manure, and climate-change aspects, such as floods and droughts. In this paper, we assess potential future E. coli loads and concentrations in the Kabul River using the Soil and Water Assessment Tool with scenarios that are based on the most recent Shared Socio-economic Pathways and Representative Concentration Pathways (SSPs and RCPs) developed for the Intergovernmental Panel on Climate Change (IPCC). Scenario_1 considers moderate population and livestock density growth, planned urbanisation and strongly improved wastewater and manure treatment (based on SSP1, "Sustainability"), and moderate climate change (RCP4.5, moderate greenhouse gas (GHG) emissions). Scenario_2 considers strong population and livestock density growth, moderate urbanisation, slightly improved wastewater treatment, no manure treatment (based on SSP3, "Regional rivalry") and strong climate change (RCP8.5, high GHG emissions). Simulated E. coli responses to Scenario_2 suggest a mid-century increase in loads by 111% and a late century increase of 201% compared to baseline loads. Similarly, simulated E. coli loads are reduced by 60% for the mid-century and 78% for the late century compared to the baseline loads. When additional treatment is simulated in Scenario_1, the loads are reduced even further by 94%, 92% and 99.3% compared to the baseline concentrations when additional tertiary treatment, manure treatment or both have been applied respectively. This study is one of the first to apply combined socio-economic development and climate change scenario analysis with an E. coli concentration model to better understand how these concentrations may change in the future. The scenario analysis shows that reducing E. coli concentrations in Pakistan's rivers is possible, but requires strongly improved waste water treatment and manure management measures.

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Cryptosporidium is a leading cause of diarrhoea and infant mortality worldwide. A better understanding of the sources, fate and transport of Cryptosporidium via rivers is important for effective management of waterborne transmission, especially in the developing world. We present GloWPa-Crypto C1, the first global, spatially explicit model that computes Cryptosporidium concentrations in rivers, implemented on a 0.5 × 0.5° grid and monthly time step. To this end, we first modelled Cryptosporidium inputs to rivers from human faeces and animal manure. Next, we use modelled hydrology from a grid-based macroscale hydrological model (the Variable Infiltration Capacity model). Oocyst transport through the river network is modelled using a routing model, accounting for temperature- and solar radiation-dependent decay and sedimentation along the way. Monthly average oocyst concentrations are predicted to range from 10-6 to 102 oocysts L-1 in most places. Critical regions ('hotspots') with high concentrations include densely populated areas in India, China, Pakistan and Bangladesh, Nigeria, Algeria and South Africa, Mexico, Venezuela and some coastal areas of Brazil, several countries in Western and Eastern Europe (incl. The UK, Belgium and Macedonia), and the Middle East. Point sources (human faeces) appears to be a more dominant source of pollution than diffuse sources (mainly animal manure) in most world regions. Validation shows that GloWPa-Crypto medians are mostly within the range of observed concentrations. The model generally produces concentrations that are 1.5-2 log10 higher than the observations. This is likely predominantly due to the absence of recovery efficiency of the observations, which are therefore likely too low. Goodness of fit statistics are reasonable. Sensitivity analysis showed that the model is most sensitive to changes in input oocyst loads. GloWPa-Crypto C1 paves the way for many new opportunities at the global scale, including scenario analysis to investigate the impact of global change and management options on oocysts concentrations in rivers, and risk analysis to investigate human health risk.

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Rotavirus (RV) and diarrheagenic are waterborne pathogens commonly causing diarrhea in children below five years old worldwide. Our study is a first step toward a loads-concentrations-risk modeling and scenario analysis framework. We analyzed current and future human RV and indicator (EC) emissions from sanitation facilities to surface waters in Uganda using two process-based models. Emissions were estimated for the baseline year 2015 and for three scenarios in 2030 using population, excretion rates, sanitation types, and wastewater treatment. The first model is a downscaled GloWPa-Rota H1 version, producing emissions at a 1-km resolution. The second model is newly developed for Kampala and adds emissions from pit latrines and septic tanks excluded in the first model. The scenarios Business as Usual, Industrious, and Low Emissions reflect government prospects in sanitation coverage and wastewater treatment. For the first model, 6.14 × 10 RV particles d and 1.31 × 10 EC colony-forming units (CFU) d are emitted to surface waters in 2015. The RV emissions are expected to increase in 2030 by 75% for Business as Usual and 212% for Industrious and decrease by 58% in Low Emissions. Emissions from the second model are higher for Kampala than in the first model, at 3.74 × 10 vs. 5.95 × 10 RV particles d and 8.18 × 10 vs. 1.75 × 10 EC CFU d in 2015, most of which come from the onsite-not-contained category. Simulated emissions for Kampala show the importance of including onsite sanitation in our modeling. Our study is replicable in other locations and helps identify key emission sources, their hotspots, and the importance of wastewater treatment. The scenarios can guide future sanitation safety planning.

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Microbial surface water quality is important, as it is related to health risk when the population is exposed through drinking, recreation or consumption of irrigated vegetables. The microbial surface water quality is expected to change with socio-economic development and climate change. This study explores the combined impacts of future socio-economic and climate change scenarios on microbial water quality using a coupled hydrodynamic and water quality model (MIKE21FM-ECOLab). The model was applied to simulate the baseline (2014-2015) and future (2040s and 2090s) faecal indicator bacteria (FIB: E. coli and enterococci) concentrations in the Betna river in Bangladesh. The scenarios comprise changes in socio-economic variables (e.g. population, urbanization, land use, sanitation and sewage treatment) and climate variables (temperature, precipitation and sea-level rise). Scenarios have been developed building on the most recent Shared Socio-economic Pathways: SSP1 and SSP3 and Representative Concentration Pathways: RCP4.5 and RCP8.5 in a matrix. An uncontrolled future results in a deterioration of the microbial water quality (+75% by the 2090s) due to socio-economic changes, such as higher population growth, and changes in rainfall patterns. However, microbial water quality improves under a sustainable scenario with improved sewage treatment (-98% by the 2090s). Contaminant loads were more influenced by changes in socio-economic factors than by climatic change. To our knowledge, this is the first study that combines climate change and socio-economic development scenarios to simulate the future microbial water quality of a river. This approach can also be used to assess future consequences for health risks.

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Understanding the environmental pathways of Cryptosporidium is essential for effective management of human and animal cryptosporidiosis. In this paper we aim to quantify livestock Cryptosporidium spp. loads to land on a global scale using spatially explicit process-based modeling, and to explore the effect of manure storage and treatment on oocyst loads using scenario analysis. Our model GloWPa-Crypto L1 calculates a total global Cryptosporidium spp. load from livestock manure of 3.2 × 1023 oocysts per year. Cattle, especially calves, are the largest contributors, followed by chickens and pigs. Spatial differences are linked to animal spatial distributions. North America, Europe, and Oceania together account for nearly a quarter of the total oocyst load, meaning that the developing world accounts for the largest share. GloWPa-Crypto L1 is most sensitive to oocyst excretion rates, due to large variation reported in literature. We compared the current situation to four alternative management scenarios. We find that although manure storage halves oocyst loads, manure treatment, especially of cattle manure and particularly at elevated temperatures, has a larger load reduction potential than manure storage (up to 4.6 log units). Regions with high reduction potential include India, Bangladesh, western Europe, China, several countries in Africa, and New Zealand.

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Cryptosporidium is a pathogenic protozoan parasite and is a leading cause of diarrhoea worldwide. The concentration of Cryptosporidium in the surface water is a determinant for probability of exposure and the risk of disease. Surface water concentrations are expected to change with population growth, urbanisation and changes in sanitation. The objective of this paper is to assess the importance of future changes in population, urbanisation and sanitation on global human emissions of Cryptosporidium to surface water. The GloWPa-Crypto H1 (the Global Waterborne Pathogen model for Human Cryptosporidium emissions version 1) model is presented and run for 2010 and with scenarios for 2050. The new scenarios are based on the Shared Socio-economic Pathways (SSPs) developed for the climate community. The scenarios comprise assumptions on sanitation changes in line with the storylines and population and urbanisation changes from the SSPs. In SSP1 population growth is limited, urbanisation large and sanitation and waste water treatment strongly improve. SSP1* is the same as SSP1, but waste water treatment does not improve. SSP3 sees large population growth, moderate urbanisation and sanitation and waste water treatment fractions that are the same as in 2010. Total global Cryptosporidium emissions to surface water for 2010 are estimated to be 1.6×1017 oocysts per year, with hotspots in the most urbanised parts of the world. In 2050 emissions are expected to decrease by 24% or increase by 52% and 70% for SSP1, SSP3 and SSP1* respectively. The emissions increase in all scenarios for countries in the Middle East and Africa (MAF) region, while emissions in large parts in Europe decrease in scenarios SSP1 and SSP3. Improving sanitation by connecting the population to sewers, should be combined with waste water treatment, otherwise (SSP1*) emissions in 2050 are expected to be much larger than in a situation with strong population growth and slow development of safe water and improved sanitation (SSP3). The results show that population increase, urbanisation and changes in sanitation should be considered when water quality and resulting health risks are estimated by water managers or public health specialists.

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The authors wish to make the following corrections to their paper [1].[...].

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The observed seasonality of foodborne disease suggests that climatic conditions play a role and that changes in the climate may affect the presence of pathogens. However, it is hard to determine whether this effect is direct or whether it works indirectly through other factors, such as farm management. This study aimed to identify the climate and management variables that are associated with the contamination (presence and concentration) of leafy green vegetables with E. coli. This study used data about E. coli contamination from 562 leafy green vegetables (lettuce and spinach) samples taken between 2011 and 2013 from 23 open-field farms in Belgium, Brazil, Egypt, Norway, and Spain. Mixed-effect logistic and linear regression models were used to study the statistical relationship between the dependent and independent variables. Climate variables and agricultural management practices together had a systematic influence on E. coli presence and concentration. The variables important for E. coli presence included the minimum temperature of the sampling day (odds ratio = 1.47), region, and application of inorganic fertilizer. The variables important for concentration (R(2) = 0.75) were the maximum temperature during the 3 days before sampling and the region. Temperature had a stronger influence (had a significant parameter estimate and the highest R(2)) than did management practices on E. coli presence and concentration. Region was a variable that masked many management variables, including rainwater, surface water, manure, inorganic fertilizer, and spray irrigation. Climate variables had a positive relationship with E. coli presence and concentration. Temperature, irrigation water type, fertilizer type, and irrigation method should be systematically considered in future studies of fresh produce safety.

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Group A rotaviruses (RV) are the major cause of acute gastroenteritis in infants and young children globally. Waterborne transmission of RV and the presence of RV in water sources are of major public health importance. In this paper, we present the Global Waterborne Pathogen model for RV (GloWPa-Rota model) to estimate the global distribution of RV emissions to surface water. To our knowledge, this is the first model to do so. We review the literature to estimate three RV specific variables for the model: incidence, excretion rate and removal during wastewater treatment. We estimate total global RV emissions to be 2 × 1018 viral particles/grid/year, of which 87% is produced by the urban population. Hotspot regions with high RV emissions are urban areas in densely populated parts of the world, such as Bangladesh and Nigeria, while low emissions are found in rural areas in North Russia and the Australian desert. Even for industrialized regions with high population density and without tertiary treatment, such as the UK, substantial emissions are estimated. Modeling exercises like the one presented in this paper provide unique opportunities to further study these emissions to surface water, their sources and scenarios for improved management.

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The likelihood of leafy green vegetable (LGV) contamination and the associated pathogen growth and survival are strongly related to climatic conditions. Particularly temperature increase and precipitation pattern changes have a close relationship not only with the fate and transport of enteric bacteria, but also with their growth and survival. Using all relevant literature, this study reviews and synthesises major impacts of climate change (temperature increases and precipitation pattern changes) on contamination sources (manure, soil, surface water, sewage and wildlife) and pathways of foodborne pathogens (focussing on Escherichia coli O157 and Salmonella spp.) on pre-harvested LGVs. Whether climate change increases their prevalence depends not only on the resulting local balance of the positive and negative impacts but also on the selected regional climate change scenarios. However, the contamination risks are likely to increase. This review shows the need for quantitative modelling approaches with scenario analyses and additional laboratory experiments. This study gives an extensive overview of the impacts of climate change on the contamination of pre-harvested LGVs and shows that climate change should not be ignored in food safety management and research.

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