Detection of enteric bacteria in two groundwater sources and associated microbial health risks

Groundwater is present in the underground layer of the Earth's crust and constitutes about 37% of the Earth's non-ocean water (Trenberth et al. 2007). Water from groundwater sources represents approximately 50% of drinking water in the world, because it is usually less exposed to contamination, pathogen penetration and evaporation, thus making it more stable and suitable for supply when compared with surface waters (Zektser & Everett 2004). Contamination of groundwater sources may occur through anthropogenic activities such as improper sewage disposal, animal rearing and cross contamination from farmland, from runoff through soil infiltration and from natural land surface contamination (Zhang et al. 2014; Beer et al. 2015; Osvalda et al. 2016).

Human consumption of contaminated water from groundwater sources may result in an outbreak of infectious diseases that may lead to morbidity and mortality (Hunter et al. 2010; Ukpong & Okon 2013). It is estimated that 1.8 million people die every year from enteric diseases and that about 1000 children under 5 years in low- and middle-income countries die every month as a result of gastroenteritis or diarrhoea. A vast majority of these cases are due to poor drinking water (WHO 2014). For instance, Onyekachi et al. (2019) reported a regular increase of waterborne diseases in Enugu, Nigeria, from 2013 to 2015, with a slight decrease in 2016; typhoid fever was observed to have the highest frequency (48.9%), followed by diarrhoea (40%) and then dysentery (11.1%); these waterborne diseases are detected through clinical diagnosis. In addition, Olusa et al. (2017) reported that water sources in Ibulesoro community in Akure were heavily polluted and unsafe for human use.

Worldwide, Escherichia coli and faecal coliforms are used as classical faecal indicator bacteria in water quality monitoring according to the standards of the World Health Organization. Coliform bacteria are always found in the gastrointestinal tracts of humans and animals, thus making them a candidate for assessing the quality of waters used for drinking and other domestic purposes (Kolarević et al. 2011). The detection of E. coli, Salmonella, Shigella or Clostridium perfringens in water from groundwater sources is sufficient evidence that the water is not safe for drinking, except when treated. The presence of these bacteria in water often reflects faecal pollution that may originate from different sources (Olajubu & Ogunika 2014; Olalemi & Dauda 2018). Furthermore, the physicochemical properties of water such as temperature, pH, turbidity, electrical conductivity, salinity, total dissolved solids and dissolved oxygen (DO) are essential parameters to consider in the evaluation of water quality, because the intrinsic properties of water may be used to assess the nature and state of water in terms of quality (Kolarević et al. 2011).

Quantitative microbial risk assessment (QMRA) is a useful tool for determining the risk posed by pathogens in water and preventing waterborne diseases. It is composed of hazard identification, dose–response model, exposure assessment and risk characterization. Microbial risk assessment involves the estimation of the probability of experiencing an infection from exposure to pathogens (Haas et al. 1999; Choi et al. 2020). It takes into account the nature of the pathogen and the immunological status of the host such as low gastric acidity in old people, which decreases the infective dose of pathogens, and vaccination of the host, which increases the infective dose. Hosts with high levels of immunity are less susceptible to the risks of infections caused by pathogens. An evaluation of the dose–response relationship and exposure assessment are critical aspects in quantifying the risk of acquiring an illness from exposure to a pathogen (Medema et al. 1996; Teunis et al. 1999). This risk estimate approach is important for the management of water safety for human health protection.

This study set out to determine the microbial quality of two groundwater sources (borehole and well) used for drinking and other domestic purposes in Akure, Nigeria. The objectives of the study were to determine the level of faecal contamination in the borehole and well; evaluate the relationship between the physicochemical properties of water from the borehole and well and the amount of enteric bacteria; and quantitatively assess the microbial risks of the pathogens in water from the borehole and well.

Akure is a city in south-western Nigeria and is the capital of Ondo State (Figure 1). Akure is situated at 7°18′29.8N and 7°12′46.5N latitude, 5°07′34.6E and 5°15′38.5E longitude and 396 m elevation above the sea level. The city has a human population of over 800,000. The borehole is located at Red-roof Akad junction, and the well is situated in Apatapiti; both groundwater sources are located around the Federal University of Technology, Akure (FUTA) south gate, Akure Ondo State. The two groundwater sources have separate sources with a distance of about 1 km between them. The borehole and well were selected based on their usage for drinking and other domestic activities by over 1,500 people in the area. The groundwater sources were sited in areas in close proximity to septic tanks (about 10 m from the borehole and well), sludge systems (approximately 15 m from the borehole and well) and waste dumpsites (about 20 m from the borehole and well). The well was shallow and uncovered, which exposed it to various kinds of chemical contamination that make the physicochemical properties of water unstable, such as the pH and electrical conductivity. Also, the temperature of the well environment influences the temperature of the well water. Since the well was uncovered, rain water dropping into the well reduced its salinity and temperature and also added other chemical ions from the atmosphere into the water. The borehole was deeper, which caused the temperature to be low, and its storage tanks were not adequately maintained; the water pipes and storage tanks were not constantly washed to get rid of chemical deposits and biological contaminants, which influence the taste, acidic pH and other physicochemical properties of the borehole water.

Water samples from the borehole and well were collected weekly over a period of 12 weeks between May and September 2019, which was the rainy season in Nigeria in that year and which contributed to the runoff contamination of the water sources. A total of 48 non-sediment samples were collected over the study period; two samples (both microbiological and physicochemical analyses) for each groundwater source were collected every week. On each sampling occasion, about 500 ml were aseptically collected with sterile screw-capped bottles labelled appropriately and transported in a cool box with ice packs to the laboratory for analyses within 1 h.

The concentrations of E. coli, faecal coliforms, Salmonella, Shigella, Clostridium, Bifidobacterium and Campylobacter in the water from the borehole and well were determined using a membrane filtration method; 10 ml of the water samples were filtered for each media used for each organism in order to have a moderate number of counts. The membrane filters (0.45 μm) were placed on freshly prepared selective media (media that contain components that allow the growth of the specific organism of interest): membrane lauryl sulphate agar (MLSA) for the isolation of Enterobacteriaceae; the colonies from MLSA were streaked on Eosin methylene Blue (EMB) agar for the specific count of E. coli, which appear as greenish metallic sheen on EMB, a feature that differentiates it from other Enterobacteriaceae, membrane faecal coliform agar (m-FC), Salmonella Shigella agar (SSA), membrane Clostridium perfringens agar (m-CP), Bifidobacterium selective agar (BSA) and charcoal cefoperazone deoxycholate agar (CCDA) for the isolation of Campylobacter. Each medium used was to selectively allow the growth of the bacteria of interest and inhibit the growth of other bacteria present in the water samples. Agar plates were incubated at 37 °C for 24 h (MLSA and EMB), 44 °C for 24 h (m-FC) and 37 °C for 24 h (SSA, m-CP, BSA and CCDA). BSA and m-CP plates were incubated anaerobically, and colonies were counted, calculated and expressed as colony-forming units (CFUs) in 100 ml⁻¹ of water. The mean CFUs for each organism were calculated for the 12-week period of sampling. Salmonella and Shigella were distinguished by the colour of their colonies on SSA; the Salmonella colonies appear black, while Shigella colonies appear colourless/brown on SSA.

The temperature of the water was determined on-site during sample collection using a mercury-in-glass thermometer. The pH, electrical conductivity, salinity, total dissolved solids, turbidity and DO of the water samples were determined using a multi-parameter analyzer (HI98194, PH/ORP/EC/DO).

Salmonella, Shigella, Campylobacter and Clostridium are considered as pathogens that may be responsible for gastrointestinal illness in humans. Salmonella is the aetiological agent of typhoid fever and non-typhoidal salmonellosis. Humans may be infected through the ingestion of 10³ and 10⁵ cells (Mahendra & Uma 2007). Shigella causes shigellosis in humans, with symptoms ranging from mild to severe and acute diarrhoea. The ingestion of 10 to 100 viable organisms may result in infection (Crockett et al. 1996). Campylobacter is the aetiological agent of Campylobacteriosis, also known as Campylobacter enteritis, which presents symptoms such as fever, headache, abdominal pain, muscle ache, nausea, vomiting and diarrhoea. C. jejuni has been reported to be responsible for more than 80% of Campylobacter infections. The ingestion of about 500 viable Campylobacter cells may cause an infection (Medema et al. 1996). Clostridium is capable of producing enterotoxin (cpe gene) in the small intestine, which may cause gastroenteritis. Symptoms often include water diarrhoea and abdominal cramps. The ingestion of more than 10⁶ vegetative cells or spores may result in infection. These pathogens are transmitted through the ingestion of food or water contaminated with the faeces of infected persons (FDA 2012; Choi et al. 2020). In order to determine the minimum human health risks from using the water from the borehole and well for drinking and other domestic purposes, microbial risk assessment methods were applied to evaluate the human dose–response data for the pathogens (Table 1). The species and strains of the pathogens are important factors to be considered in determining the health risk assessment of human pathogens, because the species and strains of a single pathogen can have a variable dose–response. For example, some species of Shigella have an infectious dose of less than 10 organisms, while those of Salmonella can be as high as >10⁵ organisms (Mahendra & Uma 2007). However, considering all variables equal, the exponential model is a single-hit approach that describes the probability of an infection resulting from the consumption of an average number of a pathogen from a single exposure, whereas the beta-Poisson model assumes that the value defined by the dose–response curve is not a constant one and takes into account the variation in the level of infectivity of the pathogen and sensitivity of the host in their interaction (Haas et al. 1999).

For exposure assessment, the minimum human health risks from using the water from the borehole and well for drinking and other domestic purposes were estimated. An intake of 100 ml was assumed for intentional consumption and intakes of 1 and 10 ml were assumed for accidental consumption as the goal for estimating the minimum human health risks from the ingestion of water from the borehole and well.

Data obtained were transformed to log₁₀ and examined using Statistical Package for Social Sciences (SPSS) Version 23.0. The Kolmogorov–Smirnov test for normality was used to determine the distribution pattern of enteric bacteria in the water from the borehole and well. Spearman's rank correlation analysis was used to determine the relationship between the concentration of enteric bacteria and the physicochemical properties of the water from the borehole and well. The dose–response models stated above were used to estimate the risk of infection.

The mean concentrations of E. coli in water from the borehole and well were 3.7 and 1.7 log₁₀ cfu/100 ml, respectively, while those of faecal coliforms in water from the borehole and well were 4.0 and 2.4 log₁₀ cfu/100 ml, respectively. Similarly, the mean levels of Salmonella in water from the borehole and well were 3.2 and 2.3 log₁₀ cfu/100 ml, respectively, while those of Shigella in water from the borehole and well were 3.3 and 2.3 log₁₀ cfu/100 ml, respectively. In addition, the mean concentrations of Bifidobacterium in water from the borehole and well were 4.3 and 2.4 log₁₀ cfu/100 ml, respectively, while those of Campylobacter in water from the borehole and well were 3.7 and 2.8 log₁₀ cfu/100 ml, respectively. The mean concentrations of Clostridium in water from the borehole and well were 3.2 and 3.1 log₁₀ cfu/100 ml, respectively.

Of all the bacteria, Bifidobacterium had the highest concentration in water from the borehole, whereas Clostridium had the highest concentration in water from the well. On the other hand, Salmonella and Clostridium had the least concentrations in water from the borehole, whereas E. coli had the least concentration in water from the well (Figure 2).

The mean values of temperature of water from the borehole and well were 24.3 and 28.1 °C, respectively, while those of pH of water from the borehole and well were 7.2 and 6.6, respectively. Similarly, the mean values of electrical conductivity in water from the borehole and well were 137.6 and 163.5 μS/cm, respectively, whereas those of total dissolved solids in water from the borehole and well were 70.1 and 76.7 mg/l, respectively. In addition, the mean values of salinity in water from the borehole and well were 0.16 and 0.07 ppt, respectively, whereas those of DO in water from the borehole and well were 2.3 and 3.6 mg/l, respectively. The mean values of turbidity of water from the borehole and well were 1.9 and 2.5 NTU, respectively (Table 2).

Using Kolmogorov–Smirnov test for normality H₀ = 0.05, the distribution pattern of enteric bacteria in water from the borehole and well varies significantly. In water from the borehole, E. coli, Salmonella, Shigella, Bifidobacterium, Campylobacter and Clostridium with a significance of 0.200, 0.189, 0.093, 0.063, 0.200 and 0.200, respectively, were normally distributed; while faecal coliforms with a significance of 0.013 were not normally distributed. On the other hand, in water from the well, E. coli, faecal coliforms, Salmonella and Clostridium with a significance of 0.199, 0.147, 0.200 and 0.078, respectively, were normally distributed; while Shigella, Bifidobacterium and Campylobacter with a significance of 0.011, 0.008 and 0.030, respectively, were not normally distributed (Table 3).

In water from the borehole, the Spearman's correlation showed that E. coli exhibited a negative relationship with salinity (r = −0.53), whereas Salmonella had a positive relationship with temperature (r = 0.51), pH (r = 0.50) and total dissolved solids (r = 0.50) but showed a negative correlation with turbidity (r = −0.50). Similarly, Shigella demonstrated a positive relationship with electrical conductivity (r = 0.56) and total dissolved solids (r = 0.50). Bifidobacterium had a positive correlation with pH (r = 0.50) and turbidity (r = 0.80) and a negative relationship with salinity (r = −0.60). Campylobacter showed a positive correlation with turbidity (r = 0.68), while Clostridium demonstrated a negative relationship with electrical conductivity (r = −0.67), total dissolved solids (r = −0.50) and DO (r = −0.54) (Table 4). In water from the well, the Spearman's correlation showed that faecal coliforms had a positive relationship with pH (r = 0.50), whereas Salmonella demonstrated a positive relationship with temperature (r = 0.50) and DO (r = 0.50) and a negative relationship with turbidity (r = −0.56). In addition, Shigella exhibited a negative relationship with turbidity (r = −0.61), while Campylobacter showed a positive relationship with salinity (r = 0.50), and Clostridium showed a positive and negative relationship with temperature (r = 0.50) and electrical conductivity (r = −0.53), respectively (Table 5).

The probability of Salmonella infection from the consumption of 1 ml of water from the well and borehole ranged from 0.000011 to 0.00006 and from 0 to 0.00037, respectively. The consumption of 10 ml of water from the well and borehole revealed the probability of infection that ranged from 0.00011 to 0.0006 and from 0 to 0.0037, respectively. The probability of Salmonella infection from the consumption of 100 ml of water from the well and borehole ranged from 0.0011 to 0.006 and from 0 to 0.037, respectively. The mean probability of Salmonella infection from the consumption of 100 ml of water from well was 0.0024 and 0.019 from the borehole (Figure 3). The model predicts the probability of infection with exposure to a single CFU of Salmonella in water from the groundwater sources at 1.3 × 10⁻⁵. Similarly, the probability of Shigella infection from the consumption of 1 ml of water from the well and borehole ranged from 0.00014 to 0.00077 and from 0.0013 to 0.003, respectively. The consumption of 10 ml of water from the well and borehole revealed the probability of infection that ranged from 0.0014 to 0.0077 and from 0.013 to 0.03, respectively. The probability of Shigella infection from the consumption of 100 ml of water from the well and borehole ranged from 0.014 to 0.077 and from 0.13 to 0.3, respectively. The mean probability of Shigella infection from the consumption of 100 ml of water from the well was 0.032 and 0.19 from the borehole (Figure 3). The model predicts the probability of infection with exposure to a single CFU of Shigella in water from the groundwater sources at 1.9 × 10⁻⁴.

Furthermore, the probability of Campylobacter infection from the consumption of 1 ml of water from the well and borehole ranged from 0.00052 to 0.00088 and from 0.00052 to 0.0037, respectively. The consumption of 10 ml of water from the well and borehole revealed the probability of infection that ranged from 0.0052 to 0.0088 and from 0.0052 to 0.037, respectively. The probability of Campylobacter infection from the consumption of 100 ml of water from the well and borehole ranged from 0.052 to 0.088 and from 0.052 to 0.37, respectively. The mean probability of Campylobacter infection from the consumption of 100 ml of water from the well was 0.071 and 0.22 from borehole (Figure 3). The model predicts the probability of infection with exposure to a single CFU of Campylobacter in water from the groundwater sources at 1.6 × 10⁻⁴. On the other hand, the probability of Clostridium infection from the consumption of 1 ml of water from the well and borehole ranged from 7.3 × 10⁻¹¹ to 3.4 × 10⁻¹⁰ and from 3.6 × 10⁻¹¹ to 5.8 × 10⁻¹⁰, respectively. The consumption of 10 ml of water from the well and borehole revealed the probability of infection that ranged from 7.3 × 10⁻¹⁰ to 3.4 × 10⁻⁹ and from 3.6 × 10⁻¹⁰ to 5.8 × 10⁻⁹, respectively. The probability of Clostridium infection from the consumption of 100 ml of water from the well and borehole ranged from 7.3 × 10⁻⁹ to 3.4 × 10⁻⁸ and from 3.6 × 10⁻⁹ to 5.8 × 10⁻⁸, respectively. The mean probability of Clostridium infection from the consumption of 100 ml of water from the well was very low, at 2.4 × 10⁻⁸ and 3.0 × 10⁻⁸ from the borehole (Figure 3). The model predicts the probability of infection with exposure to a single CFU of Clostridium in water from the groundwater sources at 1.82 × 10⁻¹¹. Based on these predictions, the risks of infection associated with the pathogens in water from the borehole and well were in this order Clostridium<Salmonella<Campylobacter<Shigella. In addition, the risks of infection from the consumption of water from the borehole were greater than those from the well.

To compare the level of risk of infection associated with the bacteria, the mean annual probabilities of infection as a result of consuming water from the well and borehole contaminated with Salmonella, Shigella, Campylobacter and Clostridium were determined. The mean annual probability of Salmonella infection due to the ingestion of 1 ml of water from the well and borehole was 0.0087 and 0.067, respectively; 10 ml of water from the well and borehole was 0.084 and 0.5, respectively, whereas the mean annual probability of Shigella infection due to the ingestion of 1 ml of water from the well and borehole was 0.11 and 0.5, respectively; 10 ml of water from the well and borehole was 0.69 and 1.0, respectively. Similarly, the mean annual probability of Campylobacter infection due to the ingestion of 1 ml of water from the well and borehole was 0.23 and 0.55, respectively; 10 ml of water from the well and borehole was 0.93 and 1.0, respectively, whereas the mean annual probability of Clostridium infection due to the ingestion of 100 ml of water from the well and borehole was 8.8 × 10⁻⁶ and 1.1 × 10⁻⁵, respectively (Figure 4).

The microbial quality of the two groundwater sources (borehole and well) used for drinking and other domestic purposes in Akure, Nigeria, was determined. The influence of the physicochemical characteristics of water on enteric bacteria detected in the water from the borehole and well was evaluated; and the risks of infection associated with the usage of the water from the borehole and well for drinking were quantitatively assessed. The concentration of E. coli in water from the well was lower than those observed by Osvalda et al. (2016) in water from 21 wells in Gargano, southern Italy. It was also higher than those observed in six wells (W1–6), but lower than those observed in three wells (W7–9) in the peri-urban tropical lowlands of Dar es Salaam, Tanzania (Mushi et al. 2012). Similarly, the concentration of faecal coliforms in water from the borehole was higher than those reported by Ohimain et al. (2013) in boreholes situated in Yenagoa metropolis, Bayelsa State, Nigeria. It is important to note that the levels of E. coli and faecal coliforms in water from the borehole were higher than those from the well. This observation is likely a result of inadequate maintenance of the borehole and the storage tanks. The presence of septic tanks, sludge systems and waste dumpsites around the borehole and well is probably responsible for the levels of E. coli and faecal coliforms detected. The levels of E. coli and faecal coliforms in the water from the borehole and well do not conform to the guideline on the microbial quality of drinking water (WHO 2011).

The concentrations of Salmonella in water from the borehole and well were higher than those observed by Osvalda et al. (2016) in 47 aquifers in Salento, Italy. Most waterborne diseases associated with Salmonella are mostly due to the ingestion of contaminated water and inadequate water management practices (Kozlica et al. 2010). In this study, Shigella was detected in water from the borehole and well on all sampling occasions, but the concentration was higher in the borehole than in the well. Faecal contamination of water may expose the inhabitants of an area to shigellosis as the percentage of Shigella can be very high in water samples. The results obtained by Oyedum et al. (2016) showed that Shigella was about 11.7% of 13 bacterial isolates detected in the water obtained from public boreholes in Bosso Town, North Central, Nigeria. Also, Adeiza et al. (2018) detected Shigella in five out of 10 borehole water sources in Kano State, Nigeria. Campylobacter is known to be responsible for most gastroenteritis transmitted through food and water (Moore et al. 2005). The concentration of Campylobacter observed in this study was higher than those reported by Savill et al. (2001) in New Zealand recreational and drinking waters. Bifidobacterium survive for a limited time in water outside the GIT of man and animals and their presence in waters indicates recent contamination (WHO 2010). The high concentration of Bifidobacterium in water from the borehole and well suggests a recent and continuous contamination of the groundwater sources. The concentration of Clostridium observed in this study was higher than those observed by Potgieter et al. (2006) in the groundwater sources used by rural communities in Limpopo Province, South Africa, but lower than that observed by Abok et al. (2018) in site 5, LMD borehole water, Isiolo County, Kenya.

Temperature is part of the factors that determine the distribution of pathogens in groundwater (O'Dwyer et al. 2014; Engström et al. 2015). Temperature was observed to have a positive relationship with the concentration of Salmonella in water from the borehole and well, and Clostridium in water from the borehole. This is in agreement with the findings of Olalemi & Dauda (2018), where the authors observed a positive relationship between temperature and enteric bacteria in the water from selected groundwater sources in four geographical locations within Akure metropolis. The pH of water from the borehole and well was within the range of the 6.5–8.5 standard for drinking water (Istifanus et al. 2013; WHO 2017). The values of pH that correlated positively with Salmonella and Bifidobacterium in water from the borehole, and faecal coliforms in water from the well, agreed with the findings of Youssef et al. (2014), where the authors observed a positive correlation between pH and faecal coliforms in El Jadida city, Morocco. The EC of water from the borehole and well fall within the maximum limit of 1000 μS/cm for drinking water (Istifanus et al. 2013). The values of EC showed a positive correlation with Shigella in water from the borehole and a negative correlation with Clostridium in water from the borehole and well. The TDS in water from the borehole and well conform to the maximum limit of 500 mg/l for drinking water (Istifanus et al. 2013). TDS showed a negative correlation with Clostridium in water from the borehole, and the result was not expected, as TDS are meant to promote the growth of Clostridium in the water. This observation is contrary to the findings of Olalemi et al. (2020a), where the authors reported a positive relationship between TDS and Clostridium in water samples from a river in Akure, Nigeria. DO was observed to have a direct relationship with Salmonella; this is in agreement with Tirumalesh et al. (2015), where the authors observed a positive relationship between DO and faecal indicator bacteria. The DO in water from the borehole and well fall within the maximum limit of 5 mg/l for drinking water (WHO 2017). Although the level of salinity in the well was low, a positive relationship with Campylobacter was observed; this finding aligns with the report of Vahid et al. (2017), where the authors observed a positive correlation between salinity and enteric bacteria in the Persian Gulf in the Bushehr beach zone. Turbidity showed a positive correlation with Bifidobacterium and Campylobacter in water from the borehole; this is an expected result, because the higher the turbidity of water, the higher the availability of nutrients that support the growth of bacteria in water. This is in agreement with studies that have demonstrated that turbidity has a direct relationship with the load of bacteria in water (Azhdarpoor et al. 2019; Olalemi et al. 2020b). The turbidity of water from the borehole and well conforms to the maximum limit of 5 NTU (Istifanus et al. 2013).

The mean annual probabilities of Salmonella and Shigella infections due to the ingestion of 10 ml of water from the well were low compared with those from the borehole. The mean annual probabilities of Salmonella and Shigella infections observed in this study were lower than those observed by Teklehaimanot et al. (2015), where the authors reported high annual risks of S. typhimurium and S. dysenteriae infections due to the ingestion of water from upstream and downstream sampling points on rivers receiving effluents from some wastewater treatment facilities in South Africa. Conversely, the mean probability of Campylobacter infection from the consumption of water from the well and borehole was higher than the value observed by Lee et al. (2019), where the authors reported the risk of illness caused by Campylobacter jejuni from consuming ground meat to be 5.68 × 10⁻¹⁰. In addition, the probability of Clostridium infection from the consumption of water from the well and borehole was considered to be low, but higher than the value observed by Choi et al. (2020), where the authors reported the mean risk of C. perfringens-associated illness from the consumption of Kimchi in South Korea to be 1.21 × 10⁻¹⁷.

In the present study, an intake of 100 ml of water was assumed for intentional consumption, and intakes of 1 and 10 ml of water were assumed for accidental consumption as the goal for determining minimum human health risks. The World Health Organization estimated the highest acceptable risk limit of enteropathogen infection in drinking water to be 10⁻⁴ (WHO 2001). The mean probabilities of Salmonella, Shigella and Campylobacter infections from both accidental and intentional consumption of water from the borehole and well were higher than the acceptable risk limit, whereas the mean probability of Clostridium infection from accidental and intentional consumption of water from the borehole and well was lower than the acceptable risk limit. In the study area, a human population of approximately 1500 relies on the water from the borehole and well for drinking and other domestic activities. Assuming that there was uniform risk and if each person in the population was exposed to 1000 CFU (3 log) of Salmonella or Shigella or Campylobacter in the water from the borehole and well once in a year, the annual cases of infection associated with exposure to Salmonella would be predicted to be 20 cases; those associated with exposure to Shigella would be predicted to be 290 cases and those associated with exposure to Campylobacter would be predicted to be 240 cases. The risks of infection for Shigella and Campylobacter were 10 times greater than those for Salmonella. This is a result of the lower infective ability of Salmonella compared with those of Shigella and Campylobacter, since the population is predicted to be exposed to the same number of colonies of the bacteria.

In order to reduce or eliminate the risks of infection associated with the usage of water from the borehole and well for drinking, adequate treatment of the water must be a routine exercise. This will protect residents relying on the water sources from gastrointestinal illnesses. This will also reduce morbidity and ill health from diarrheal diseases in children under 5 years. Sinking boreholes and digging wells near septic tanks, sludge systems and waste dumpsites should be discouraged. In addition, boreholes and their storage tanks must be adequately maintained and wells must be covered properly.

The findings of this study demonstrated that the two groundwater sources (borehole and well) used for drinking and other domestic purposes do not have high microbial quality. The physicochemical characteristics of water from the borehole and well have a correlation with the level of enteric bacteria in the water sources. The risk of Salmonella or Shigella or Campylobacter infections from the ingestion of water from the borehole and well was greater than the acceptable risk limit, thus exposing the residents relying on the water for drinking to potential risks of gastrointestinal illness. The high rates of enteric diseases reported in the communities where the borehole and well are located are the ones associated with Salmonella, Shigella and Campylobacter. These pathogens have a low infective dose, which reflects in the high cases of enteric diseases in these communities.

The authors are grateful to the Department of Microbiology, School of Sciences, the Federal University of Technology, Akure, Ondo State, Nigeria, for providing appropriate support in terms of equipment and laboratory used for the study. The authors are also grateful to the Department of Marine Science and Technology for support in physicochemical analysis.

All relevant data are included in the paper or its Supplementary Information.