Drug resistance has become a matter of great concern, with many bacteria now resist multiple antibiotics. This study depicts the occurrence of antibiotic-resistant bacteria (ARB) and resistance patterns in five full-scale hospital wastewater treatment plants (WWTPs). Samples of raw influent wastewater, as well as pre- and post-disinfected effluents, were monitored for targeted ARB and resistance genes in September 2022 and February 2023. Shifts in resistance profiles of Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii antimicrobial-resistant indicators in the treated effluent compared to that in the raw wastewater were also worked out. Ceftazidime (6.78 × 105 CFU/mL) and cefotaxime (6.14 × 105 CFU/mL) resistant species showed the highest concentrations followed by ciprofloxacin (6.29 × 104 CFU/mL), and gentamicin (4.88 × 104 CFU/mL), in raw influent respectively. WWTP-D employing a combination of biological treatment and coagulation/clarification for wastewater decontamination showed promising results for reducing ARB emissions from wastewater. Relationships between treated effluent quality parameters and ARB loadings showed that high BOD5 and nitrate levels were possibly contributing to the persistence and/or selection of ARBs in WWTPs. Furthermore, antimicrobial susceptibility tests of targeted species revealed dynamic shifts in resistance profiles through treatment processes, highlighting the potential for ARB and ARGs in hospital wastewater to persist or amplify during treatment.

  • A compelling evidence for the occurrence, burden and patterns of bacterial antimicrobial resistance in hospital WWTPs was presented.

  • PACl coagulation technology followed by biological treatment showed a higher removal performance.

  • Resistance patterns were significantly shifted following biological treatment and chlorine disinfection.

  • Resistant burdens were associated with effluent TSS, BOD5, NO3- and free chlorine levels.

The emergence of drug-resistant pathogens, within a striking range of infectious agents, is a broad concern that represents an increasing priority across the globe. In 2021, antimicrobial resistance was listed as one of the top 10 worldwide public health threats by the World Health Organization (WHO) (WHO 2021a), jeoparding the achievements of modern medicine. According to WHO, various Enterobacteriaceae (including Klebsiella, Escherichia coli, Serratia, and Proteus), Pseudomonas, and Acinetobacter are the most critical groups of antibiotic-resistant ‘priority pathogens’, which can result in severe infections that are frequently fatal, including pneumonia and bloodstream infections (Willyard 2017). Antimicrobial-resistant infections were responsible for at least 1.27 million deaths all over the world in 2019 and contributed to roughly 5 million deaths in 2022 (Thompson 2022). It seems to be playing out previous projections in that the total number of deaths from drug-resistant diseases will reach 10 million per year by 2050 if measures are never put into action to contain resistance to antimicrobials (Control & Prevention 2021; WHO 2021b).

While this is a burgeoning area of research, it needs to be acknowledged that lack of sanitation and inadequate infection control promotes the spread of pathogenic bacteria, some of which can resist antimicrobial treatment (Musoke et al. 2021). Wastewater discharges from healthcare settings, such as hospitals, are likely to contain particularly elevated loads of antimicrobial pollution. Antimicrobials used in hospitals are ranked as highly important by WHO, despite the fact that their total usage in primary care centers is greater than their use in hospitals (WHO 2018). For the sake of clarity, primary medical care is preventive care and thus deals with basic and common requirements of people and families. The idea is to keep people out of hospitals for care and they mostly deal with preventive aspects like vaccination, birth control etc. Hospitals, on the other hand, are in actual care and have beds and more sophisticated equipment and services. Patients with acute illness or injury who seek specialized requirements and advanced forms of care mostly refer to these establishments. Effluents from such settings are a constant source of discharges of antibiotic-resistant bacteria (ARB) and antibiotic-resistant genes (ARGs), which might create drug resistance ‘hotspots’ mainly through horizontal resistance gene transfer if not adequately treated (Quintela-Baluja et al. 2019; Majumder et al. 2021). Resistance emerges as a result of mutations in pathogenic agents and selection pressure from antibiotic use that gives a competitive advantage for altered strains (Lien et al. 2017).

Wastewater treatment plants (WWTPs), on the other hand, are an important component of the multiple-barrier approach to reduce levels of antimicrobial compounds, ARB, and ARGs that involve a diverse range of physical, chemical and biological processes (Bürgmann et al. 2018). Depending on the design and scale of the treatment utility as well as its operating conditions, however, the plant may have limited capacity to reduce the concentrations of resistant pathogens or neutralize antimicrobial residues in effluent to levels that remove the risk of promoting persistence before release into the environment (Bouki et al. 2013; Carraro et al. 2016). Currently, little data are available on the occurrence and diversity of active pharmaceutical ingredients, ARB and ARGs in hospital influent wastewater as well as their fate in full-scale treatment utilities (Kumari et al. 2020). The reported concentrations of the antimicrobials detected in hospital wastewater habitats all over the world typically range from ng/L to μg/L and continue to linger there for a long time (Michael et al. 2013), suggesting that they could act as a major source of antimicrobial resistance dissemination in the ecosystem. Some studies in low- and middle-income countries (LMICs) indicate that hospital wastewater is often directly injected into the groundwater or flows to waterways with limited or no treatment (Ekwanzala et al. 2020). Some hospital settings, indeed, discharge their effluent to the city sewer and then municipal WWTPs that are typically not designed for treating high concentrations of antimicrobial compounds, ARB or ARGs (Parida et al. 2021).

Misuse and overuse of antimicrobials as well as excessive rates of hospitalization coupled with increased prevalence of hospital infections represent an especially dangerous problem in LMICs, such as Iran. Pattern analysis of population-weighted antibiotic consumption in Iran between the years 2000 and 2016 revealed that antibiotic consumption has increased from 33.6 per 1000 inhabitants per day (DID) to 60 DID during the study period. Compared to the average consumption of Organization for Economic Co-operation and Development (OECD) countries, Iran has consumed antibiotics almost triple times (Abbasian et al. 2019), implying that overuse of antibiotics in this upper-middle-income community is a serious issue. National reports further demonstrate that many antibiotics in the country have been ineffective due to drug resistance. Extended-spectrum β-lactamase (ESBL) producing species which are advantaged by the presence of several enzymes capable of hydrolyzing penicillin and inhibiting broad-spectrum beta-lactam antibiotics, such as cephalosporins and monobactams, are frequently isolated in healthcare settings (Ansharieta et al. 2021). In light of published reports, microbial resistance of penicillin derivatives is about 60–70% and sometimes it reaches up to 90% (Ghannadi 2018). Drug resistance has also been observed in cephalosporin derivatives tacking document trends in antibiotic use into consideration over time (Ghannadi 2018; Zahedi bialvaei et al. 2018). Klebsiella pneumoniae resistant to carbapenems, E. coli resistant to fluoroquinolones, and Pseudomonas spp. were the most common among all microorganisms tested in Iran (Zahedi bialvaei et al. 2018). These antibiotic-resistant species are also usually of concern in healthcare practices around the world (Bouki et al. 2013).

Research on the state and profile of antibiotic resistance in isolated ARB from hospital wastewaters in Iran is rarely reported (Nasr &Yazdanbakhsh 2008). To investigate the impact of treatment plant design and its operation on the fate and persistence of antimicrobial compounds, bacteria and resistance genes in wastewater, five full-scale hospital WWTPs were examined in Tehran, the capital city of Iran. The plants are exploiting a biological treatment and hypochlorite disinfection or a combination of biological treatment and coagulation/clarification for hospital wastewater decontamination. Regulatory surveillances are based on the minimum standards for secondary treatment and include three major effluent parameters, i.e., 5-day BOD, TSS, and pH as well as residual disinfectant concentration, without concerns for the evolution of new resistant strains. Two null hypotheses (H0) were thus examined in this study: (H01) differences in the design and operation of treatment plants do not influence the concentration of target ARB in treated effluent, and (H02) conventional treatment of hospital wastewater does not further increase ARB or lead to the emergence of new resistant strains. The results of this study will provide effective technical support for designing and operation hospital effluent treatment utilities to assess the potential and the worth of upgrading existing plants to more advanced/optimized technologies.

Specifications of WWTPs

Hospital wastewater samples were collected from five tertiary public hospitals located in Tehran metropolitan, Iran. All the hospitals perform as referral centers for the community under the auspicious Shahid Beheshti University of Medical Sciences. The specifications of these hospitals and the corresponding wastewater treatment utilities in terms of clean-up processes, disinfection procedures and biosolids handling are summarized in Table 1. All treatment plants employ traditional wastewater treatment processes comprising conventional biological treatment and hypochlorite disinfection. Figure SI-1 (Supplementary Information) depicts the simplified flow diagram for biological and chemical processes used for wastewater treatment as well as sampling sites in studied full-scale hospital WWTPs.

Table 1

Wastewater treatment characteristics

WWTPTotal no. of covered bedsInflow (m3/day)Type of WWTPEffluent receiving mediaDisinfection process
A – Taleghani 620 200–300 IDEAa City sewer Calcium hypochlorite 
B – Shohada-e-Tajrish 420 300 Conventional ASb City sewer Calcium hypochlorite 
C – Imam Hossein 592 500–700 Extended aeration AS City sewer Calcium hypochlorite 
D – Loqman 420 300 Conventional AS + Coagulation/clarification River Calcium hypochlorite 
E – Bazarganan 175 110 Extended aeration AS Adsorption well Calcium hypochlorite 
WWTPTotal no. of covered bedsInflow (m3/day)Type of WWTPEffluent receiving mediaDisinfection process
A – Taleghani 620 200–300 IDEAa City sewer Calcium hypochlorite 
B – Shohada-e-Tajrish 420 300 Conventional ASb City sewer Calcium hypochlorite 
C – Imam Hossein 592 500–700 Extended aeration AS City sewer Calcium hypochlorite 
D – Loqman 420 300 Conventional AS + Coagulation/clarification River Calcium hypochlorite 
E – Bazarganan 175 110 Extended aeration AS Adsorption well Calcium hypochlorite 

aIntermittent Decanted Extended Aeration.

bActivated sludge.

The biological clean-up of WWTP-A involves a sequential process of intermittent decanted extended aeration (IDEA). This process is an advanced configuration of sequencing batch reactor (SBR), which is advantaged by the continuity of flow into the system. In addition to the high removal efficiency of organic matter, IDEA is sought to present a good efficiency for nitrogen and phosphorus removal. The accepted ratio of food to microorganisms (F/M) for this system is 0.004 L/day with 2,000–5,000 mg mixed liquor suspended solids (MLSS)/L. Free chlorine from calcium hypochlorite is used for effluent disinfection which flows directly to the city sewer, reaching municipal WWTP (Figure SI-1a, Supplementary Information). The WWTP-B is operated in parallel via a conventional extended aeration process with hydraulic retention time in the order of 24 h. Primary sedimentation is not used and the biological treatment is followed by secondary clarification in multiple basins. Calcium hypochlorite (2–3 kg/day) is manually added to the treated effluent, which is then released into the city sewer (Figure SI-1b, Supplementary Information). A fairly similar design has been employed in WWTP-C. The bioconversion of organics is accomplished through conventional extended aeration, while its effluent is treated using a hypochlorite disinfection process before being discharged into the municipal sewerage network (Figure SI-1c, Supplementary Information). WWTP-D employs traditional hospital sewage treatment works of initial sedimentation, biodegradation, chemical treatment (secondary clarification), filtration, and disinfection (Figure SI-1d, Supplementary Information). Polyaluminum chloride (PAC) is employed during chemical treatment (coagulation), while the settled outflow is treated using sand filtration and then disinfection processes before being discharged into Nawab River (Figure SI-1d, Supplementary Information). The wastewater generated in Bazarganan medical center (WWTP-E) is passed through primary treatment (grit removal and preliminary sedimentation) before it enters into the biological treatment including nitrification and secondary clarification. Free chlorine from calcium hypochlorite is used for disinfection and chlorine-treated wastewater is directly discharged underground through adsorption wells (Figure SI-1e, Supplementary Information).

Sample collection and processing

Wastewater samples used in this work were collected in September 2022 and February 2023. Sampling was duplicated following the next 2 weeks in each event and the arithmetic average result of the two tests was reported in this paper. Composite samples were collected from raw inflow as well as outflows of pre- and post- disinfection under stable operating conditions. 1 L samples were collected three times a day at about 3-h intervals (from 8 am to 3 pm) in sterile amber-colored containers and brought to the university laboratory kept in a portable icebox. Upon arrival at the laboratory, bacteria were concentrated aseptically by vacuum-filtration of samples through 0.22-μm-pore-size membrane filters (Schleicher & Schuell). The filtrate was collected for antimicrobial compound analysis (see Section 2.4). Each dirty membrane was aseptically removed, sliced into smaller pieces and placed in a sterilized conical tube containing 50 mL saline phosphate buffer (PBS). The suspension was then subjected to sonication (5 min, 35 KHz) (Bandelin Sonorex, Germany). The samples were next severely vortexed (15 min) to detach bacterial cells from the membranes. All the tubes subsequently underwent centrifugation for 15 min at 2,000 g to concentrate the suspension down to 2 mL, which were stored at −20 °C until further use (Rafiee et al. 2014). In parallel, 1 mL of concentrated aliquot sample was taken before centrifugation to analyze bacterial count, identification and susceptibility testing (see Section 2.5). Final concentrations were accordingly adjusted taking the initial volume of collected samples into account.

Wastewater analyses

The untreated hospital wastewater, as well as effluent samples before and after chlorine disinfection were collected. The samples were analyzed for basic chemical parameters including total, suspended and dissolved solids (TS/TSS/TDS), chemical and biochemical oxygen demand (COD and BOD5), total kjeldahl nitrogen (TKN), ammonia nitrogen (NH3-N), nitrate (-N) and phosphate (). Temperature, pH, dissolved oxygen (DO), and free residual chlorine were measured in real-time during sampling. These parameters were tested according to the standard methods for the examination of water and wastewater (Baird et al. 2017).

Antibiotics analysis

Extraction and analysis of antibiotics in raw and treated effluent were carried out according to the EPA Method 1694 (Englert 2007) with some modifications. Briefly, 1,000 mL filtered hospital wastewater samples were loaded onto a Bond Elute C18 cartridge with a flow rate of 10–15 mL/min which was previously washed with a mixture of distilled water and methanol (10 mL/10 mL). Following the filtration of the sample, the cartridge was washed with 5 mL of distilled water and placed in a vacuum for an hour to dry. About 6 mL of methanol was then slowly passed through the cartridge and the collected was finally dried with nitrogen gas to a volume of 1 mL. The extracted antibiotic compounds were analyzed with chromatography-mass spectrometry (LC-MS) at μg/L level (Chiemchaisri et al. 2022). Six types of commonly prescribed antibiotics in hospitals all over the country (Iran) were chosen for antibiotic determination: Ciprofloxacin (CIP), Azithromycin (AZM), Meropenem (MEM), Imipenem (IPM), Gentamicin (GEN) and Ceftriaxone (CRO). Standards of antibiotics were all supplied by Sigma-Aldrich (St Louis, MI, USA).

Enumeration and identification of bacterial isolates and sensitivity test

Bacterial counts

Samples were subjected to the conventional heterotrophic plate count (HPC) test to estimate the abundance of ARB in each sample. They were first serially diluted in a series of consecutive decimal steps (using autoclaved physiological saline) of each sample and immediately plated onto R2A agar to which targeted antibiotics had already been amended. Four classes of antibiotics from three types were worked out and used for the isolation of resistant bacteria in our study: (1) Fluoroquinolones: CIP, (2) Aminoglycoside: GEN, (3) Ceftazidime: ceftazidime (CAZ) and cefotaxime (CTX). These antibiotics were chosen based on commonly prescribed drugs in studied hospitals and their working concentrations exceeded the minimum inhibitory concentrations for targeted resistant species in accordance with Clinical Laboratory Standards Institute (CLSI) guidelines (Franklin et al. 2012) (see Table S1, Supplementary material). Each antimicrobial agent was individually applied into the media together with cyclohexamide, 200 mg/mL, as an antifungal additive (Munir et al. 2011). Accordingly, 100 μL of the aliquot was streaked on R2A agar media and plates underwent incubation for 24–48 h at 37 °C which was followed by a subsequent 5 days incubation at 27 °C (Brooks et al. 2007). Similarly, total cultivable heterotrophic bacteria were estimated by cultivating samples on R2A agar medium in the absence of antibiotics.

Biochemical tests

Hospital wastewater specimens were assessed looking for the existence of resistant Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii on account of their reported abundances in wastewater from healthcare systems (Wang et al. 2018), relevance to public health (Denissen et al. 2022), and ease of culturing. The chosen species are members of ESKAPEE pathogens including Enterococcus faecium, Staphylococcus aureus, K. pneumoniae, A. baumannii, P. aeruginosa, Enterobacter spp. and E. coli that are multi-drug-resistant (MDR) bacteria and present increasing treatment challenges for healthcare institutions and public health worldwide. These species were presumptively identified using selective media (eosin methylene blue agar (EMB), cetrimide agar, and McConkey, respectively) with a volume of 100 μL using a conventional pour plate method and subsequently confirmed by biochemical tests. Identification of isolates was then confirmed using gram staining and biochemical analyses with indole formation, methyl red, Voges-Proskauer, urea hydrolysis, H2S production, motility, triple sugar iron agar (TSI), citrate, oxidase, catalase, and coagulase tests (Vashist et al. 2013).

Antimicrobial sensitivity test

Following the identification of bacteria from selective media culture and biochemical tests, the standard Kirby-Bauer disk diffusion method was employed to assess the antimicrobial susceptibility profile of bacterial isolates as delineated by CLSI (Weinstein 2021). A 24-h pure culture colony from each isolated bacterium was inoculated into tubes each harbored 5 mL of Mueller-Hinton broth and was incubated to attain a 0.5 McFarland turbidity standard within about 4 h. Sterile cotton swabs were used to create a bacterial lawn of bacterial isolates onto Mueller-Hinton agar plates and the commercial disks (Mast Group, Merseyside, UK) with the following antibiotics were tested: MEM (10 μg), IMP (10 μg), CIP (5 μg), GEN (10 μg), CAZ (30 μg), and CTX (30 μg). After incubation for 18 h at 35 °C, the diameter of the non-growth halo of each disk was measured in millimeter and the results were interpreted according to the break point established by the CLSI 2021 guidelines as susceptible, moderate, or resistant (Weinstein 2021). Prior to the determination of the resistance spectrum, the quality of all antibiotic disks was checked in line with the manufacturer's instructions using ATCC 25922 (E. coli).

Bacterial isolates were also analyzed by combination disk for ESBL employing ceftazidime and ceftazidime/clavulanic acid as well as cefotaxime and cefotaxime/clavulanic acid disks and the results were interpreted based on CLSI recommendations. The diameters of inhibition zones were compared for the CTX and CAZ disks with that of the ceftazidime/ and cefotaxime/clavulanic acid disc (Weinstein 2021). An increase in inhibition zone diameter of A ≥ 5 mm in the presence of clavulanic acid was interpreted as positive for the presence of ESBL in the tested bacteria. We used ATCC 25922 (E. coli) and ATCC 700603 (K. pneumoniae) as negative and positive quality control species for ESBL production, respectively.

Extraction of DNA

The classic manual freeze and boiling method was employed for DNA extraction from both the concentrated wastewater samples as well as pure bacterial isolates of E. coli, P. aeruginosa, and A.baumannii . The extraction was conducted by placing one milliliter of each sample (or bacterial colonies inoculated into micro tubes containing 1 mL of PBS) within 1.5 mL of micro tubes, which then underwent alternating freezing of the samples in liquid nitrogen and the subsequent thawing in boiling water bath for at least three times. It was then subjected to centrifugation (18,000 g) for 10 min. The upper supernatant was collected in new tubes. The quality of extracts was assessed by a NanoDrop spectrophotometer (Thermo Scientific, Rockwood, TN, USA). The 260/280 ratio ranged from 1.85 to 1.97 and DNA concentrations ranged from 14.1 to 21.0 μg/mL. The extracted DNA samples were kept at −20 °C until further examination.

Qualitative PCR of selected ARGs

Amplification reactions were performed to assess the presence and diversity of resistant species in raw and treated hospital wastewater samples. Seven resistance genes of interest in two main categories, including metallo-β-lactams (i.e., blaNDM and blaVIM) and ESBLs (i.e., blaPER, blaGES, blaTEM, blaCTX_M and blaSHV) were worked out. Targeted ARGs were chosen based on the ARB most frequently detected in our samples and on account of their importance in local hospital-acquired infections. Meanwhile, the integrase gene intI1 was included in our assays, as it is typically associated with genes conferring resistance to drugs (Gillings et al. 2015). The primer sequences designed for amplifying the selected genes and reaction conditions used in PCR amplifications are shown in Table S2, Supplementary material. The specific primers of all genes were obtained from previous publications (Giakkoupi et al. 2003; Goudarzi et al. 2013; Fallah et al. 2014; Strauß et al. 2015; Shariati et al. 2018; Loqman et al. 2021) and verified for specificity through the BLAST alignment tool (www.ncbi.nlm.nih.gov).

Briefly, 20 ng template DNA and 20 pM of each primer together with master in DNA-free PCR buffer (Roche, Germany) was employed in each 25 μL of reaction, which was accomplished on Eppendorf, Mastercycler gradient thermal cycler (Eppendorf, Hamburg, Germany). The products of the reaction were loaded onto 1.5% (w/v) agarose gel containing ethidium bromide and were observed after electrophoresis (Bio-Rad made in the USA). To obtain a broader picture, PCR products were also analyzed for DNA sequencing which in turn underwent BLAST2 algorithms from the National Center for Biotechnology for ARB identification.

Data analysis and statistics

All measurements were conducted in triplicate and the arithmetic mean of the three measurement results was reported here. Statistical analysis was performed using IBM SPSS software (SPSS Inc, Chicago, IL). Data related to wastewater/effluent sample characteristics were averaged and presented as means ± standard deviations (SD) when they were normally distributed, otherwise, they were reported as a median (range). One-tailed Student's t-tests and one-way ANOVAs were worked out to perform the statistical analysis (i.e., for comparison of average concentrations) and to illustrate the scale of significant difference between sampling points and seasons and among WWTPs. Also, the SPSS was utilized to produce Pearson/Spearman correlations at a 95% confidence level. Relationships between effluent properties and ARB loading were examined using bivariate regression analyses. ARB target concentrations were used as the Y variables, while plant effluent pH, BOD5, COD, TSS, TKN, -N, and free residual chlorine were outlined as the predictors. For all analyses, the statistical difference was set at an α = 0.05.

General treatment performance of studied WWTPs

The component-specific properties of untreated wastewater and the performance of treatment utilities are summarized in Tables 2 and 3. The pH values of raw inflows and the treatment plant effluents met biological treatment requirements and were in the range of discharge standards of the receiving media. TSS concentrations for the hospital wastewaters ranged from 10 to 305 mg/L (average 78 mg/L) in September 2022 and from 10 to 390 mg/L (average 138 mg/L) in February 2023. While, except WWTP-B, other facilities met hospital effluent legislations (Khan et al. 2021); two out of the five hospitals exceeded the discharge limit values determined by national standards for secondary treatment in the cold season.

Table 2

The component-specific properties of untreated and treated wastewater (September 2022)

PlantpH
TSS (mg/L)
BOD5 (mg/L)
COD (mg/L)
BOD5/COD (mg/L)
-N (mg/L)
TKN (mg/L)
(mg/L)
Cl2 (mg/L)
IEIEIPEIPEIPEIPEIPEIPE
A 7.6 200 32 130 206 22 37 0.63 10.2 7.9 5.4 1.0 8.2 6.4 30 24 19 4.7 4.6 3.7 >1 
B 6.5 75 305 220 16 270 41 37 0.81 10.2 9.3 5.6 0.6 28.7 20.7 46 45 15 13.4 20.2 12 >1 
C 6.5 132 22 235 301 41 34 0.78 11.4 0.4 0.1 0.6 21.8 13 42 36 35 9.0 6.6 1.8 
D 6.5 175 10 105 150 44 44 0.70 19.6 0.1 0.1 0.2 8.2 7.3 42 33 28 3.6 0.4 3.1 >1 
E 6.5 110 20 170 247 44 36 0.69 18.6 0.3 0.2 4.5 22.2 24.4 48 40 19 8.4 4.4 4.9 >1 
PlantpH
TSS (mg/L)
BOD5 (mg/L)
COD (mg/L)
BOD5/COD (mg/L)
-N (mg/L)
TKN (mg/L)
(mg/L)
Cl2 (mg/L)
IEIEIPEIPEIPEIPEIPEIPE
A 7.6 200 32 130 206 22 37 0.63 10.2 7.9 5.4 1.0 8.2 6.4 30 24 19 4.7 4.6 3.7 >1 
B 6.5 75 305 220 16 270 41 37 0.81 10.2 9.3 5.6 0.6 28.7 20.7 46 45 15 13.4 20.2 12 >1 
C 6.5 132 22 235 301 41 34 0.78 11.4 0.4 0.1 0.6 21.8 13 42 36 35 9.0 6.6 1.8 
D 6.5 175 10 105 150 44 44 0.70 19.6 0.1 0.1 0.2 8.2 7.3 42 33 28 3.6 0.4 3.1 >1 
E 6.5 110 20 170 247 44 36 0.69 18.6 0.3 0.2 4.5 22.2 24.4 48 40 19 8.4 4.4 4.9 >1 

I, influent; P, pre-chlorination; E, effluent.

Table 3

The component-specific properties of untreated and treated wastewater (February 2023)

PlantpH
TSS (mg/L)
BOD5 (mg/L)
COD (mg/L)
BOD5/COD (mg/L)
-N (mg/L)
TKN (mg/L)
(mg/L)
Cl2 (mg/L)
IEIEIPEIPEIPEIPEIPEIPE
A 6.0 6.0 160 180 50 123 36 34 0.41 11.8 0.2 6.3 1.2 34.5 6.8 28 18 20 6.0 7.9 7.3 
B 6.0 5.5 240 390 235 492 36 26 0.48 16.7 0.3 0.3 0.4 26 32 46 30 17 1.0 5.9 13 > 1 
C 6.5 6.5 180 70 220 12 20 448 35 36 0.49 8.4 14 7.0 2.3 0.5 0.7 40 36 36 12.7 9.1 9.4 
D 6.0 6.0 160 40 90 361 32 34 0.25 8.0 0.1 0.2 0.7 11.3 11.7 39 34 31 9.5 1.1 0.5 0.2 
E 6.0 6.0 115 10 105 177 45 44 0.60 4.7 0.4 0.3 8.1 24.3 25.3 42 49 20 5.4 4.4 5.3 
PlantpH
TSS (mg/L)
BOD5 (mg/L)
COD (mg/L)
BOD5/COD (mg/L)
-N (mg/L)
TKN (mg/L)
(mg/L)
Cl2 (mg/L)
IEIEIPEIPEIPEIPEIPEIPE
A 6.0 6.0 160 180 50 123 36 34 0.41 11.8 0.2 6.3 1.2 34.5 6.8 28 18 20 6.0 7.9 7.3 
B 6.0 5.5 240 390 235 492 36 26 0.48 16.7 0.3 0.3 0.4 26 32 46 30 17 1.0 5.9 13 > 1 
C 6.5 6.5 180 70 220 12 20 448 35 36 0.49 8.4 14 7.0 2.3 0.5 0.7 40 36 36 12.7 9.1 9.4 
D 6.0 6.0 160 40 90 361 32 34 0.25 8.0 0.1 0.2 0.7 11.3 11.7 39 34 31 9.5 1.1 0.5 0.2 
E 6.0 6.0 115 10 105 177 45 44 0.60 4.7 0.4 0.3 8.1 24.3 25.3 42 49 20 5.4 4.4 5.3 

I, influent; P, pre-chlorination; E, effluent.

The wastewater of hospitals in this study demonstrated a comparable content of organic matter and nitrogenous compounds as reported in Europe, Asia, and south America (Majumder et al. 2021). The 5-day BOD concentration in untreated hospital wastewaters ranged from 105 to 235 mg/L with the average concentration being 156 mg/L in warm season. Likewise, inflow BOD5 values ranged from 50 to 235 mg/L (average 140 mg/L) in February. The average COD concentration in hospital wastewater of studied WWTPs was found to be 278 mg/L (150–301 mg/L) in September 2022 and 320 mg/L (123–492 mg/L) in February 2023, which again were in the range of COD values reported in hospitals from all over the world. A high BOD concentration of 1,268 mg/L has been already noticed in effluents coming out of a hospital in Brazil (Wilde et al. 2014). The average BOD5/COD ratio for wastewater in the cold season was 0.44 (0.25–0.60) which, contrary to expectations, was considerably lower than the average biodegradability index values for studied hospital wastewater in the warm season, which was 0.72 (0.63–0.81). Hospital wastewaters are known to have high concentrations of toxic and highly persistent compounds (including pharmaceutically active compounds, surfactants, and disinfectants among others) (Emmanuel et al. 2005; Verlicchi et al. 2010). Although the considerably high biocompatibility indices (BOD5/COD ratio) of wastewater in our study during warm season indicate that such effluents are amenable to treat using conventional bioremediation technologies (Verlicchi et al. 2010; Meo et al. 2014; Carraro et al. 2016; Majumder et al. 2021), the index was fairly below the generally acceptable range for sewage during cold season, making it more challenging to biodegradation. Evidence regarding the biocompatibility of hospital wastewater around the world is not conclusive. Some studies in Asia and Europe have reported low biodegradability index (BOD5/COD ratio) of 0.29–0.34, respectively (Judd 2016; Sun et al. 2016); but high BOD5/COD values of 0.64, 0.75, and 0.85 has also been reported in some hospital effluents from Thailand (Prasertkulsak et al. 2016), Iran (Karami et al. 2018), and Brazil (Wilde et al. 2014), respectively. It is worth mentioning here that these views are at odds with scientific research which documents caution in employing biological treatment for hospital or pharmaceutical wastewater because of concerns about creating ideal conditions for the evolution of new resistant strains (Bürgmann et al. 2018). Therefore, the decision of whether or not to treat hospital wastewater biologically should also consider the antibiotic residues and pathogens present as well as the potential to contribute to the evolution of new resistant strains. Meanwhile, and TKN content of untreated wastewater varied slightly with an average of 14 and 41.6 mg/L in summer, and 9.92 and 39 mg/L in the cold season, respectively.

Given that the performance of a well-equipped hospital wastewater treatment plant can be affected by unpredictable conditions like unforeseeable consumption of antibiotics on certain days, it was not possible to draw a meaningful conclusion relating to the removal performance of WWTPs. Nevertheless, the treatment performance of studied utilities shows very high removal of organic matter, in terms of average BOD5 and COD (i.e., 98.7 and 82.49% in September 2022 and 96.5 and 83.7% in February 2023, respectively). Likewise, 77.90 and 42.89% removals were noticed for and TKN in September, respectively, as compared with 70.38 and 34.98% in February. Detailed data for each treatment plant is summarized in Tables 4 and 5. The diverging results between studied WWTPs could be in part due to differences in their design and operation. Overloading and poor operation of WWTP-B, as evidenced by on-site observations, affect wastewater treatment performance to a large extent. Overall, the average concentrations of in the effluent from WWTPs were less than half of the concentration observed in the influent. The increased -N concentration associated with the decrease of ammonium in almost all WWTPs could be assigned to the conversion of -N to -N, and in light of the presence of excess aerobic conditions, denitrification of nitrate could not be accomplished. Higher nitrate concentrations have become major concerns of the treatment plant operation in Bazarganan hospital (WWTP-E), where the effluent is directly discharged into adsorption wells. These results are consistent with those of Casas et al. (2015) who reported negative nitrate removal in staged moving bed biofilm reactors (MBBRs). All measured parameters except for TSS and -N met the national effluent regulatory targets and show roughly similar results as compared to the conventional and advanced units dealing with hospital wastewater around the world (Liu et al. 2010; Khan et al. 2021).

Table 4

The performance of full-scale hospital WWTPs in September 2022a

Removal percentage (%)
WWTPTSSBOD5CODTKN-N
A – Taleghani 83.75 99.23 81.98 46.57 36.67 −540.00 20.64 
B – Shohada-e-Tajrish −306.66 97.27 86.17 45.10 67.39 −3,350.00 10.45 
C – Imam Hossein 83.02 99.15 88.73 99.21 16.67 −2,066.67 80.00 
D – Loqman 94.28 99.05 70.31 99.64 33.33 −3,550.00 13.89 
E – Bazarganan 81.82 98.82 85.27 98.98 60.42 −442.22 41.67 
Removal percentage (%)
WWTPTSSBOD5CODTKN-N
A – Taleghani 83.75 99.23 81.98 46.57 36.67 −540.00 20.64 
B – Shohada-e-Tajrish −306.66 97.27 86.17 45.10 67.39 −3,350.00 10.45 
C – Imam Hossein 83.02 99.15 88.73 99.21 16.67 −2,066.67 80.00 
D – Loqman 94.28 99.05 70.31 99.64 33.33 −3,550.00 13.89 
E – Bazarganan 81.82 98.82 85.27 98.98 60.42 −442.22 41.67 

aNegative removal means that the concentration had been increased over treatment process instead of getting declined.

Table 5

The performance of full-scale hospital WWTPs in February 2023a

Removal percentage (%)
WWTPTSSBOD5CODTKN-N
A – Taleghani − 12.50 94.00 72.36 46.61 28.57 − 466.67 − 21.67 
B – Shohada-e-Tajrish − 62.50 99.57 94.62 98.26 63.48 − 7,900.00 − 1,240.00 
C – Imam Hossein 61.11 90.91 92.04 16.67 10.00 − 69.56 25.98 
D – Loqman 75.00 100.00 90.61 97.00 20.51 − 1,571.42 94.74 
E – Bazarganan 91.30 98.10 75.10 93.40 52.38 − 212.34 1.85 
Removal percentage (%)
WWTPTSSBOD5CODTKN-N
A – Taleghani − 12.50 94.00 72.36 46.61 28.57 − 466.67 − 21.67 
B – Shohada-e-Tajrish − 62.50 99.57 94.62 98.26 63.48 − 7,900.00 − 1,240.00 
C – Imam Hossein 61.11 90.91 92.04 16.67 10.00 − 69.56 25.98 
D – Loqman 75.00 100.00 90.61 97.00 20.51 − 1,571.42 94.74 
E – Bazarganan 91.30 98.10 75.10 93.40 52.38 − 212.34 1.85 

aNegative removal means that the concentration had been increased over treatment process instead of getting declined.

Antibiotics occurrence and removal in WWTPs

The selection of antibiotics for analysis was carried out through information disseminated by the hospitals and national reports that addressed the pharmacological therapies against nosocomial infections. A questionnaire survey concerning antimicrobial consumption was accordingly conducted in studied hospitals. β-lactamase inhibitors, quinolones, cephalosporins, penicillin, nitroimidazoles, aminoglycosides, carbapenems, and macrolides were respectively the most frequently used antibiotics in these hospitals.

Out of six antibiotics analyzed, while just Ciprofloxacin residual concentrations of raw influent were detected during September (3.33 μg/L), both Ciprofloxacin (6.34 μg/L) and Azithromycin (11.4 μg/L) were detected in raw influent during February sampling (Figure 1). It is evident from the peer-reviewed literature databases that up to 80% of the administered dose of drugs and antibiotics can be excreted as the active pharmaceutical ingredients or their intermediate metabotypes depending on the class of antibiotics and how it is used (Larsson 2013). Ciprofloxacin is a fluoroquinolone antibiotic used to combat a number of bacterial infections, including respiratory tract, skin, and urinary tract infections, among others (Yoon et al. 2020). Ciprofloxacin ranks first in the characterization of hospital effluents around the world, followed by Sulfamethoxazole, Trimethoprim, Norfloxacin, and Ofloxacin (Majumder et al. 2019). In a study conducted by Diwan et al. (2010), Ciprofloxacin was among the most widespread and highly concentrated (237 μg/L) antimicrobial compounds in hospital effluents in India (Diwan et al. 2010). Traces of Ciprofloxacin (38.6 μg/L) were also reported in some hospital wastewater in Portugal (Majumder et al. 2019). Azithromycin concentrations equivalent to 11.4 ± 6.3 μg/L were also detected. The use of Azithromycin has been promoted during the COVID-19 pandemic owing to the anti-inflammatory properties that allow it to act favorably against inflammation in pneumonia (Stellari et al. 2014; Mirtaleb et al. 2021). Very recently, Mirzaie et al. (2022) reported that mean Azithromycin concentrations in the influent wastewater of two hospitals in Bushehr (Iran) reached 110 and 896 ng/L, representing six and 48-fold rise compared with those registered in 2017 (earlier than COVID 19). In line with our study, also Aydin et al. (2019) reported Azithromycin concentrations of 163 μg/L from effluents of 16 hospitals in Turkey. Over the years, many researchers have also detected Azithromycin in hospital wastewater (Kasprzyk-Hordern et al. 2008; Oliveira et al. 2015; K'oreje et al. 2016; Balakrishna et al. 2017; Majumder et al. 2019). It is further worth mentioning here that antibiotic concentrations detected in untreated raw wastewater in February 2023 were higher than the values in September 2022. This finding could be attributed to the so-called 6th wave of the COVID-19 outbreak in Iran (Anonymous 2022). Interestingly, other target antimicrobials (viz. MEM, IMP, GEN and CRO) in raw influent samples were determined below the detection limit value. This finding deviates from the literature that reports the occurrence of a wide range of antimicrobials in hospital wastewater and could be assigned to the major limitation in this study regarding analyses detection limit. Numerous investigations looked at antibiotic residues in hospital wastewater; however, the results are divergent. Hospital wastewater in Thailand was found to host a wide variety of Fluoroquinolones in 100% of studied samples, with Norfloxacin and Ciprofloxacin being the most prevalent with respective concentrations of 12.11 and 9.60 μg/L (Hamjinda et al. 2018). Likewise, Norfloxacin, Ofloxacin, and Ciprofloxacin appeared at relatively higher concentrations of 12–25 μg/L, 14–35 μg/L, and 3–14 g/L in some hospital wastewaters in Vietnam (Nguyen et al. 2017).
Figure 1

Ciprofloxacin (5.49 ± 6.7 μg/L) and Azithromycin (11.4 ± 6.3 μg/L) concentrations in September 2022 and February 2023 as compared to different countries (Aydin et al. 2019; Majumder et al. 2021; Omuferen et al. 2022).

Figure 1

Ciprofloxacin (5.49 ± 6.7 μg/L) and Azithromycin (11.4 ± 6.3 μg/L) concentrations in September 2022 and February 2023 as compared to different countries (Aydin et al. 2019; Majumder et al. 2021; Omuferen et al. 2022).

Close modal

Antibiotic concentrations were also traced in the secondary effluent and chlorinated outflow of WWTPs. However, only traces of Ciprofloxacin and Azithromycin in some hospital's effluents (September/February) were determined and all of the studied antibiotics except for ciprofloxacin (950 ng/L) were below the method quantification limit value in outflow samples. Unquestionably, the studied WWTPs depicted high elimination rates for antimicrobials. The amount of identified antibiotics in the treatment effluents was not subject to temporal variations by season. It appeared that hypochlorination gave reasonable removal for antibiotic residues compared with the biological treatment. In line with our findings, Batt et al. (2007) also showed that after chlorine disinfection in three sewage treatment plants, the concentration of Ciprofloxacin, Sulfamethoxazole, and Tetracycline was reduced to 0–70 ng/L, 10–70 ng/L, and 0–14 ng/L, respectively. Also, Renew & Huang (2004) reported that chlorination could reduce the concentration of some micro pollutants in wastewater. These results are indeed consistent with bench-scale experiments demonstrating the high sensitivity of fluoroquinolones, sulfonamides, and trimethoprim to react with chlorine (Adams et al. 2002; Huber et al. 2003; Dodd &Huang 2004). In conclusion, the treatment facilities in our study demonstrate variation in removal efficiencies of detected antimicrobials (Ciprofloxacin and Azithromycin) in a range of 54–100%.

Quantification of total and relevant ARB

The average concentration of heterotrophic bacteria in raw hospital wastewaters, quantified by HPC, ranged from 3.2 × 105 to 3.7 × 106 per mL in September 2022 and from 3.0 × 104 to 1.07 × 107 per mL in February 2023 (Table 6). Also, we chose to quantify heterotrophic bacteria resistant to CIP, GEN, CAZ, and CTX antimicrobials. The quantity of cultivable ARB from all sampling points is presented in Tables 7 and 8. The highest concentration of CIP-resistant species in inlet hospital wastewater reached up to 4.07 × 105 CFU/mL (WWTP-B) during the cold season and 7.4 × 104 CFU/mL (WWTP-B) during the warm season. However, relatively lower frequencies of GEN-resistant ARB (7.2 × 102 CFU/mL) were observed during February 2023.

Table 6

The bacterial loads in different sampling points, quantified by heterotrophic plate count (HPC)

WWTPHPC (logCFU/mL) – September
HPC (logCFU/mL) – February
Raw influentPre-disinfected effluentPost-disinfected effluentRaw influentPre-disinfected effluentPost- disinfected effluent
A – Taleghani 5.61 4.83 1.82 6.17 4.77 3.30 
B – Shohada-e-Tajrish 6.56 4.77 1.17 7.02 4.32 
C – Imam Hossein 6.03 3.54 5.14 4.30 3.47 
D – Loqman 5.68 2.47 0.30 5.11 2.07 
E – Bazarganan 5.50 3.60 0.84 4.47 3.69 1.49 
WWTPHPC (logCFU/mL) – September
HPC (logCFU/mL) – February
Raw influentPre-disinfected effluentPost-disinfected effluentRaw influentPre-disinfected effluentPost- disinfected effluent
A – Taleghani 5.61 4.83 1.82 6.17 4.77 3.30 
B – Shohada-e-Tajrish 6.56 4.77 1.17 7.02 4.32 
C – Imam Hossein 6.03 3.54 5.14 4.30 3.47 
D – Loqman 5.68 2.47 0.30 5.11 2.07 
E – Bazarganan 5.50 3.60 0.84 4.47 3.69 1.49 
Table 7

Concentrations and types of ARB and genes in different samples of WWTPs (September 2022)a

WWTPARB detected (logCFU/mL)
ARGs detected
Raw influent
Post-disinfected effluent
Raw influentSecondary treatment effluentPost-disinfected effluent
CIPGMCAZCTXCIPGMCAZCTX
A 4.08 3.93 5.08 5.10 0.48 0.30 1.37 1.38 blaTEM, blaSHV and blaPER – – 
B 4.86 4.96 6.13 6.08 0.78 0.69 blaSHV blaTEM, blaCTX_M and blaNDM – 
C 4.60 4.41 5.60 5.56 blaTEM and blaCTX_M blaCTX_M and blaPER – 
D 4.23 4.09 5.24 5.21 blaCTX_M – – 
E 4.08 3.92 5.08 5.02 blaTEM and blaSHV blaCTX_M – 
WWTPARB detected (logCFU/mL)
ARGs detected
Raw influent
Post-disinfected effluent
Raw influentSecondary treatment effluentPost-disinfected effluent
CIPGMCAZCTXCIPGMCAZCTX
A 4.08 3.93 5.08 5.10 0.48 0.30 1.37 1.38 blaTEM, blaSHV and blaPER – – 
B 4.86 4.96 6.13 6.08 0.78 0.69 blaSHV blaTEM, blaCTX_M and blaNDM – 
C 4.60 4.41 5.60 5.56 blaTEM and blaCTX_M blaCTX_M and blaPER – 
D 4.23 4.09 5.24 5.21 blaCTX_M – – 
E 4.08 3.92 5.08 5.02 blaTEM and blaSHV blaCTX_M – 

aData are based on PCR screening of a certain number of isolates.

Table 8

Concentrations and types of ARB and genes in different samples of WWTPs (February 2023)a

WWTPARB detected (logCFU/mL)
ARGs detected
Raw influent
Post-disinfected effluent
Raw influentSecondary treatment effluentPost-disinfected effluent
CIPGMCAZCTXCIPGMCAZCTX
A 4.73 4.64 5.74 5.72 2.00 1.86 2.89 2.86 blaTEM and blaCTX_M blaTEM and blaPER blaSHV and blaPER 
B 5.61 5.46 6.59 6.55 blaNDM and blaPER blaNDM and blaPER – 
C 3.74 3.58 4.75 4.70 2.16 1.98 3.10 3.06 blaCTX_M – blaTEM 
D 3.72 3.39 4.61 4.61 0.70 0.38 1.66 1.64 blaSHV – – 
E 2.98 2.86 4.01 4.01 0.05 −0.05 1.08 1.07 – – – 
WWTPARB detected (logCFU/mL)
ARGs detected
Raw influent
Post-disinfected effluent
Raw influentSecondary treatment effluentPost-disinfected effluent
CIPGMCAZCTXCIPGMCAZCTX
A 4.73 4.64 5.74 5.72 2.00 1.86 2.89 2.86 blaTEM and blaCTX_M blaTEM and blaPER blaSHV and blaPER 
B 5.61 5.46 6.59 6.55 blaNDM and blaPER blaNDM and blaPER – 
C 3.74 3.58 4.75 4.70 2.16 1.98 3.10 3.06 blaCTX_M – blaTEM 
D 3.72 3.39 4.61 4.61 0.70 0.38 1.66 1.64 blaSHV – – 
E 2.98 2.86 4.01 4.01 0.05 −0.05 1.08 1.07 – – – 

aData are based on PCR screening of a certain number of isolates.

The concentration ranges of targeted ARB in September and February revealed no significant difference for CIP, GEN, CAZ, and CTX (p > 0.05). Nonetheless, unreasonably higher counts of CAZ resistance were observed in September compared to values in February from raw samples (p > 0.05). CAZ-resistant ARB loads were appreciably higher in WWTP-B compared to samples from other treatment plants during both sampling periods (p < 0.001) (Tables 7 and 8). However, heterotrophic bacteria from untreated wastewater samples did not differ significantly among WWTPs (p > 0.05) (Figure 2). It is somewhat surprising that the concentration of heterotrophic bacteria was higher in untreated samples collected from WWTPs A and B, while the opposite trend was noticed for the remaining WWTPs (i.e., C, D, and E). The reason for this is not clear but it may have something to do with medical services provided by the hospital.
Figure 2

Heterotrophic bacteria from untreated wastewater samples in WWTPs.

Figure 2

Heterotrophic bacteria from untreated wastewater samples in WWTPs.

Close modal
In line with the removal of total heterotrophic bacteria (0.8–3 log), secondary treatment was performed satisfactorily in ARB (CIP-, GEN-, CAZ-, and CTX-resistant) removal for all four target-resistant bacteria. Log removal values were calculated based on ARB counts in the untreated inflow samples and the effluent samples from both secondary clarification and post-chlorination during the warm (September) and cold (February) seasons, which are depicted in Figure 3(a) and 3(b), respectively. Among studied sewage treatment plants, the highest removals in the warm season following secondary treatment were noticed for WWTP-D (employing a combination of biological and chemical treatment followed by filtration), WWTP-C and WWTP-E (employing extended aeration and conventional activated sludge, respectively). Furthermore, in WWTP-A, all ARB decreased, ranging from 3.61 log (CIP) to 3.72 log (CTX). In WWTP-B, conventional treatment removed CIP- and GEN-resistant bacteria almost completely, whereas CZA and CTX showed a 5.35 and 5.39 log decline, respectively. Concerning all WWTPs, the secondary treatment attained more than 5 log removal in the outlet of the secondary clarifier, which accords with pioneering reports (Cheng et al. 2020). The bacteria aggregated in mixed liquor are removed by settling in the secondary clarifier. Moreover, some higher unicellular organisms (such as ciliates and flagellates) and metazoa (e.g., rotifers) may prey on dispersed bacteria, which in turn result in declined concentrations of bacteria and thus turbidity in the plant outflow (Mahmood & Elliott 2006). Nevertheless, WWTP-D outperformed other treatment utilities in ARB removal in the cold season. In reality, wastewater treatment units do not act independently but are designed to work in combination. The removal of suspended and colloidal particles in coagulation/filtration processes makes chlorination more effective. We did observe statistically meaningful differences in terms of log removals for targeted ARB (p < 0.001) across traditional treatment methods and WWTP-D employing chemical treatment and filtration in excess of biological degradation and also WWTP-E concerning nitrate removal. The final outflow released an average bacterial load of 12 ± 20.06 CFU/mL.
Figure 3

ARB removal for all the four target-resistant bacteria: (a) September and (b) February. Data are based on HPC analysis.

Figure 3

ARB removal for all the four target-resistant bacteria: (a) September and (b) February. Data are based on HPC analysis.

Close modal

Even though clarified effluent chlorination greatly reduced the levels of ARB in wastewater, the final effluent released from WWTPs still contained concerning amounts of susceptible heterotrophic species (up to 3,000 CFU/mL) as well as tiny numbers of ARB and the concomitant genes in cold season which could be a potential source of ARB/ARGs entry into the natural environment. There were 3.61–3.72 log removal for treatment plants A and more than 5 log for treatment plants B, C, D, and E recorded after disinfection in September 2022. Also, there were 2.73–2.86 log, more than 5 log, 1.57–1.64 log, 2.95–2.98 log, and 2.87–2.96 log removal recorded after disinfection in February 2023 for treatment plants A, B, C, D, and E, respectively. Likewise, a higher proportion (46%) of CTX was found in WWTP-A in September. The highest values of CAZ-ARB were also noticed at the WWTP-C hospital discharge point in February, which reached up to 1,260 CFU/mL.

ARB was not detectable in WWTPs C, D and E during the warm season and contrary to expectations, in WWTP-B during the cold season in the outflow of the treatment plant. Concerning the failure of secondary treatment in a later facility, as evidenced by high TSS concentrations in the effluent, it was expected that the performance of the disinfection process could be compromised mainly by protecting the effect of particulates on pathogens during disinfection. However, the observed finding was unexpected and suggests that the results may be caused by increased concentrations of chlorine during disinfection. While the concentrations of target ARB declined further with wastewater chlorination, and the difference reached significance in pre- and post-chlorinated effluents in the cold season (p < 0.05) (Table 6) the pros and cons of ARB removal and chlorine toxicity in the environment need to be considered. The literature is somewhat contradictory with respect to the fate of ARB during hospital effluent disinfection. In support of our findings, Munir et al. (2011) observed high quantities of tetracycline and sulfonamide resistant species and corresponding sulfonamide resistance genes in untreated wastewater from five hospitals in Michigan. Munir et al. also reported appreciably declined loads of ARB in the treated effluent, while the difference in bacterial quantities was not statistically significant before and after chlorination. Moreover, these results are questioned with a putatively promoted frequency of conjugative horizontal gene through alteration of cell membrane permeability during chlorine disinfection or generated chloramines (Guo et al. 2015; Zhang et al. 2019). Despite the fact that chlorination could reduce a load of bacteria in the effluent, the peer-reviewed literature already includes reports demonstrating that it may favor the transfer of resistance genes (Herraiz-Carboné et al. 2021).

Antimicrobial susceptibility

E. coli, A. baumannii, and P. aeruginosa were, respectively, the most frequently isolated ARB species in raw wastewater. The antimicrobial susceptibility profiles of targeted ARB in warm and cold seasons revealed significant differences for E. coli, P. aeruginosa, and A. baumannii (Tables 9 and 10). E. coli isolates from untreated wastewater samples collected in September 2022 from WWTPs A, B, and D were found to be resistant to CTX. The resistance diagram indeed showed that they resisted CIP in samples from WWTPs B and D and MEM in samples from WWTP-B. E. coli isolates were indeed not ESBL. The isolates, however, not only still resisted CIP and MEM but also developed resistance to CAZ and GEN in secondary effluent from WWTP-B.

Table 9

Phenotyping properties of E. coli, P. aeruginosa, and A. baumannii isolated from WTTPs during warm season

 
 
Table 10

Phenotyping properties of E. coli, P. aeruginosa, and A. baumannii isolated from WTTPs during cold season

 
 

Higher abundances of resistant ARB and targeted genes were observed in the cold season compared to the corresponding profile in September from raw samples. The exploited processes in treatment utilities and their operational conditions seem to affect the profile of antimicrobial resistance through wastewater treatment. Among different WWTPs, the antimicrobial susceptibility profiles in secondary effluent from hospitals A, B, and C showed resistance to a higher number of antimicrobials tested, whereas in hospital D all species were sensitive to tested antimicrobials and in hospital E a complete shift in resistance profile from CIP and CTX to GEN, CTX, and CAZ were noticed. To our knowledge, reports about the assistance of chemical coagulation in improving drug resistance removal from wastewater remain scarce (de Ilurdoz et al. 2022). Nonetheless, this result corroborates the findings of a great deal of the previous work concerning tertiary clean-up technologies like ozonation, activated carbon adsorption, and chemical precipitation which have been claimed to be successful in antibiotics and ARGs removal under optimal conditions (Nakada et al. 2007; Le-Minh et al. 2010). However, the removal performance seemingly is influenced by dissolved solids in treated effluent, while few data are available from well-equipped sewage treatment plants dissolved organic matter and inorganic anions in treated effluent proved to have a considerable impact on their removal performance (Wang et al. 2020). Secondary effluent from WWTPs-A and B indicated roughly the same resistance profile as raw influent, except that MEM resistance was developed in treatment plant A.

In P. aeruginosa, resistance to CIP, MEM, IPM, and CAZ was observed in outflow samples from secondary treatment of WWTP-B during September 2022, whereas it was sensitive to all antimicrobials tested in inlet wastewater. The detection of resistant Pseudomonas in the treated effluent and not in the influent could be a consequence of the species enrichment with the treatment, and not exactly an occurrence of resistance acquisition. As a matter of fact, the effect of ARB enrichment with the treatment has been described in pioneering literature (Bouki et al. 2013; Miller et al. 2016). There is, nevertheless, wide-ranging research into the stimulated antibiotic resistance due mainly to horizontal gene transfer among survived microbial species in wastewater if the treatment utilities do not perform effectively (Miller et al. 2016). The proximity of bacterial cells in activated sludge flocs allows the transfer of genes between ARB and non-ARB. Nonetheless, depending on the design and operating conditions of clean-up units in WWTPs, the fate and behavior of resistant species could significantly differ (Bouki et al. 2013). Other treatment utilities performed excellent (100%) in Pseudomonas removal through biological treatment in September 2022. The resistance profiles in WWTPs-A, B, and C from clarified samples during February 2023, nevertheless, were the same as inflow raw wastewater and biological treatment did not shift the resistance profile. However, susceptible Pseudomonas in WWTP-D influent were all removed during secondary treatment (a combination of biological and chemical treatment). Resistance to MEM was developed in Pseudomonas during biological treatment in WWTP-E.

A. baumannii were all removed or remained susceptible during biological treatment in the warm season. The exception was that the resistance profile was unchanged in WWTP-C. There was a resistance diagram switch during the cold season recorded after biological treatment to CTX and CAZ in this treatment facility. The profile remained the same in treatment plant A. Again, we did not observe Acinetobacter spp. in outflow samples form secondary treatment of WWTP-D. Similarly, they were sensitive to all antimicrobials in treated samples from WWTP-B and E while the species resisted CIP, GEN, and CTX.

Although disinfection performed satisfactorily (≥3.61 log removal) in ARB removal during September 2022, the resistance profile remained unchanged after disinfection for treatment plants A and C, in the paucity of free residual chlorine. While the concentrations of target ARB declined further with wastewater chlorination, E. coli seemed to develop resistance to IPM (Tables 9 and 10). E. coli was not detectable in effluent samples during the warm season nor in the outflow of WWTPs B, D, and E during the cold season. Similarly, P. aeruginosa and A. baumannii were the isolated species in disinfected effluent from treatment plants A and C without free chlorine measurement. It is worth mentioning here that the lack of free chlorine in treatment plant outflow in spite of hypochlorite addition could be attributed to its prompt consumption by remaining organics. The worst profile was noticed in WWTP-A, which showed resistance to CIP, MEM, CTX, CAZ, and IPM in February 2023. Nonetheless, we did not observe a shift in resistance profiles after disinfection for treatment plants. The literature is somewhat contradictory with respect to the fate and modulation of antimicrobial resistance patterns in ARB during hospital effluent disinfection. Hiller et al. (2019) asserted that disinfection did not take much part in the reduction of antibiotic resistance genes and bacteria, but even induced the emergence of resistance in some cases. A potential effect of free chlorine on cell membrane could, therefore, also have through breaking the chemical bonds in their membrane a synergistic effect of Cl2 on the horizontal gene transfer, likewise resulting in the same pattern of bacterial antimicrobial resistance. These results collectively support the possibility that disinfection may lead to the emergence of antibiotic resistance.

The effect of operating factors on ARB removal

Associations between treated effluent quality parameters (pH, BOD5, COD, TSS, TKN, -N, and free residual chlorine) and ARB loading at all five participating WWTPs by Pearson/Spearman correlations are summarized in Table 11. Our analysis showed only three statistically significant correlations (p-values < 0.05). ARB loadings obtained from testing the four targets (CIP-, GEN-, CAZ-, and CTX-resistant) were positively correlated with effluent BOD5 levels, demonstrating effect sizes ranging from 0.08 to 0.096. The effect size was most pronounced on CAZ-, CTX-, CIP- and GEN-resistant bacteria, respectively. ARB loading increased with decreasing and Cl2 possibly reflecting the cell's retention time and excess oxygen concentrations. Also, it can be inferred that the high doses of chlorine needed to overcome the breakpoint of wastewater could result in selection pressure of resistant microbes; however, maybe the high dose is enough to actually kill the resistant bacteria so they do not survive, while low dose just induces selection pressure. Other relationships were not statistically appreciable. Interestingly, ARB loading did not correlate with TSS loading, despite being one of the most commonly reported indicators in the literature. We also repeated the analyses excluding WWTP-B (in view of super chlorination of effluent), which did change the associations between effluent TSS. The highest ARB loads were seen when TSS ranged between 70 and 180. TSS values for this analysis ranged between 10 and 180 mg/L with a mean value of 48.12 mg/L. More detailed information on the relationships between effluent ARB burden and BOD5, , Cl2, and TSS can be found in Table 11.

Table 11

Relationship between WWTPs, operating parameters on ARB removal

ARBPearson/Spearman correlationspHCODBOD5TSSaTKNCl2
CIP r or ρ −0.103 −0.139 0.790** 0.714** 0.351 −0.606** −0.769** 
p 0.587 0.464 <0.001 <0.001 0.057 <0.001 <0.001 
Effect size 0.007 0.009 0.086 0.083 0.025 0.051 0.080 
GM r or ρ −0.108 −0.140 0.77** 0.741** 0.329 −0.602** −0.768** 
p 0.570 0.462 <0.001 <0.001 0.076 <0.001 <0.001 
Effect size −0.007 0.009 0.080 0.076 0.023 0.050 0.080 
CAZ r or ρ −0.094 −0.130 0.821** 0.672** 0.373* −.605** −.758** 
p 0.623 0.493 <0.001 <0.001 0.042 <0.001 <0.001 
Effect size 0.006 0.009 0.096 0.069 0.027 0.051 0.077 
CTX r or ρ −0.094 −0.131 0.815** 0.679** 0.370* −0.606** −0.761** 
p 0.620 0.489 <0.001 <0.001 0.044 <0.001 <0.001 
Effect size 0.006 0.009 0.094 0.07 0.027 0.051 −0.078 
ARBPearson/Spearman correlationspHCODBOD5TSSaTKNCl2
CIP r or ρ −0.103 −0.139 0.790** 0.714** 0.351 −0.606** −0.769** 
p 0.587 0.464 <0.001 <0.001 0.057 <0.001 <0.001 
Effect size 0.007 0.009 0.086 0.083 0.025 0.051 0.080 
GM r or ρ −0.108 −0.140 0.77** 0.741** 0.329 −0.602** −0.768** 
p 0.570 0.462 <0.001 <0.001 0.076 <0.001 <0.001 
Effect size −0.007 0.009 0.080 0.076 0.023 0.050 0.080 
CAZ r or ρ −0.094 −0.130 0.821** 0.672** 0.373* −.605** −.758** 
p 0.623 0.493 <0.001 <0.001 0.042 <0.001 <0.001 
Effect size 0.006 0.009 0.096 0.069 0.027 0.051 0.077 
CTX r or ρ −0.094 −0.131 0.815** 0.679** 0.370* −0.606** −0.761** 
p 0.620 0.489 <0.001 <0.001 0.044 <0.001 <0.001 
Effect size 0.006 0.009 0.094 0.07 0.027 0.051 −0.078 

aExcluding WWTP-B.

**Correlation is significant at 0.01 level.

Antibiotic resistance dissemination is a topic of global concern. In this study, we demonstrated the occurrence, burden and patterns of bacterial antimicrobial resistance in full-scale hospital WWTPs. Collectively, our study suggested that shifts in resistance profiles of targeted ARB as well as the persistence and amplifications of ARGs through treatment processes could be an environmental risk factor contributing to drug resistance globally. This study will provide significant data and findings for future studies and underlines the necessity to identify treatment processes that are universally effective for reducing multiple ARB and ARGs in WWTPs. There are major limitations in this study concerning a small sample size and study design that could be addressed in future research.

Our study provides compelling evidence for the occurrence, burden and patterns of bacterial antimicrobial resistance in five full-scale hospital WWTPs in Tehran (Iran) between September 2022 and February 2023. Generally, very high removal of targeted antibiotics (>97%) and resistant microbes (≥5 log) were observed at all WWTPs. However, a treatment facility employing PACl coagulation technology in addition to biological treatment showed the potential to confer a higher elimination capacity compared to conventional WWTPs. While secondary clarification revealed the highest log removal of ARB, resistance patterns were appreciably altered following biological treatment and chlorine disinfection in studied sewage treatment plants, particularly during cold weather (February). Effects of treatment were unique for each target ARB (E. coli, P. aeruginosa, and A. baumannii) even passing through the same types of treatment unit, underscoring the need to identify treatment processes that are universally effective for reducing multiple ARB and ARGs. We further compared the correlations between treated effluent ARB loadings and basic physicochemical parameters in the studied hospital WWTPs. Our analyses revealed that resistant microbes burden in hospital treatment facilities is positively associated with effluent TSS and BOD5; however, while and free chlorine residual levels helped to reduce resistant bacteria, the disinfection process selected for resistance.

The authors thank Shahid Beheshti University of Medical Sciences for partial funding of the project. We also would like to acknowledge contributing hospitals for their collaboration in this research.

M.R. contributed to conceptualization, methodology, writing – original draft preparation, review and editing; M.E.-K. contributed to sampling, experiments and investigation, writing – original draft preparation; H.D. contributed to methodology; A.E. contributed to Methodology; A.Y. contributed to methodology; F.A. contributed to data analysis and investigation, writing – original draft preparation; M.J.-R. contributed to writing – original draft preparation; A.H. contributed to experiments and investigation.

Shahid Beheshti University of Medical Sciences, Tehran, Iran (Grant No. 30281).

All authors have read, understood, and complied as applicable with the statement on ‘Ethical responsibilities of Authors’.

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

The authors declare there is no conflict.

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