Skip to main content
NCBI home page
International Health logoLink to International Health
. 2025 Oct 23;18(2):154–165. doi: 10.1093/inthealth/ihaf111

Prevalence of Clostridioides difficile contamination in healthcare and non-healthcare environments: a global systematic review and meta-analysis

Mohammad Hasan Rabiee 1, Lida Abdolmohammadi Khiav 2, Mohammad Hossein Fallah Mehrabadi 3,✉
PMCID: PMC13017374  PMID: 41127891

Abstract

Clostridioides difficile infection is a significant public health challenge. This study aimed to determine the overall prevalence of C. difficile contamination in healthcare and non-healthcare environments around the world from 2014 to 2024. In this systematic review, we searched five international databases. Random and fixed-effects models were used to estimate the pooled prevalence with 95% CIs. Among the 49 eligible studies and 20 779 environmental samples, 4507 samples were positive for C. difficile contamination. The overall prevalence was estimated as 0.26 (95% CI 0.23 to 0.28). The pooled prevalence according to the detection method was 0.26 (95% CI 0.21 to 0.32) and 0.62 (95% CI 0.50 to 0.74) using a culture test and PCR, respectively. The overall prevalence was 0.18 (95% CI 0.16 to 0.20) and 0.36 (95% CI 0.30 to 0.42) in the healthcare and non-healthcare environment, respectively. The prevalence in non-healthcare environments was 0.42, 0.38, 0.33 and 0.04 on farms, in public places, in the home and veterinary hospitals, respectively. The findings reveal a significant prevalence of C. difficile contamination across various environments worldwide. This alarming trend underscores the pressing need to prioritize environmental factors and implement effective disinfection strategies as part of comprehensive control programs aimed at tackling this disease.

Keywords: Clostridium difficile, environment, healthcare, prevalence, systematic review

Introduction

Clostridium difficile or Clostridioides difficile is an anaerobic Gram-positive bacterium that is found as a flora of healthy infants. This bacterium can cause disease with severe diarrhea and inflammation of the colon or colitis, and overuse of antibiotics facilitate its occurrence.1,2 The bacterium produces two exotoxins, toxin A (TcdA) and toxin B (TcdB), which are associated with the severity of the disease. Toxin A (308 kDa) causes inflammation, resulting in the secretion of intestinal fluids and colonic mucosal damage. Toxin B (270 kDa) also causes mucosal damage. Furthermore, C. difficile produces CD, including a cell binding component (CDTb) and an enzymatic component (CDTa) with ADP ribosyltransferase activity, leading to cytoskeleton disorganization. Other virulence factors include endospore, S-layers, flagella and fimbriae, as well as other virulence factors.3

The occurrence of the disease known as C. difficile infection (CDI) is associated with clinical symptoms that include watery diarrhea, abdominal pain, dehydration, fever, nausea and weight loss. In other words, the disease can cause a range of gastrointestinal issues from mild to severe that can be life-threatening.4 Considering the importance of the disease, Centers for Disease Control and Prevention (CDC) classified CDI as an urgent public health issue in 2013; there were 250 000 infections and 14 000 deaths reported by the CDC in 2013. The crude incidence rate of CDI was reported as 130.28 per 100 000 persons by the CDC in the CDI Surveillance report in 2017. According to the latest update of the report, the crude incidence rate of CDI in 2022 was 116.1 cases per 100 000 persons.5

It has been proven that, besides asymptomatic carriers, the environment plays a crucial role in the transmission of CDI, particularly within healthcare settings. Contaminated surfaces in hospitals can harbor C. difficile spores, which are highly resistant to environmental stressors and can persist for months or even years. These spores can be transferred to patients through direct contact with contaminated surfaces or via healthcare workers, contributing to the spread of infection. Enhanced cleaning protocols, including the use of sporicidal disinfectants, are essential to mitigate the risk.6,7

To date, several researchers have reported the contamination rate in various healthcare and non-healthcare environmental settings. Despite this, no attempt has been made to summarize the reported contamination rate worldwide in recent years. Therefore, to fill this gap and improve our understanding of the current global prevalence of contamination, this study was conducted to evaluate the overall prevalence of C. difficile contamination in both healthcare and non-healthcare environments in the last decade (2014–2024).

Methods

Search strategy

We conducted a global systematic review by searching five international databases, namely, PubMed, Science Direct, Springer, CABI Direct and Google Scholar. The search covered the period from January 2014 to January 2024 and utilized the following keywords: ‘Clostridium spp.’, ‘difficile AND environment’, ‘difficile AND healthcare’, ‘difficile AND equipment’ and ‘difficile AND public’. We searched for these combinations in the titles, keywords and abstracts of published papers in the aforementioned databases. The study protocol was registered in the open science framework (OSF) registries for systematic reviews with the following doi: https://doi.org/10.17605/OSF.IO/G8BTQ.

Study selection process

Studies with insufficient data, irrelevant and duplicated data were excluded from the analysis. Scientist evaluated studies related to C. difficile contamination by screening their titles and abstracts, then reviewed the full text of papers for quality assessment after eliminating duplicates. In addition, the references of eligible papers were searched to find additional eligible articles. Scientist conducted separate assessments of the articles' quality.

Eligibility criteria

Articles were considered eligible if they met the following inclusion criteria: (i) they were conducted on environmental samples; and (ii) they reported the prevalence of C. difficile contamination. However, papers that met the following criteria were excluded from the analysis: (i) they were conducted before 2014; (ii) they did not report the prevalence of C. difficile contamination; or (iii) they were case reports or experimental studies.

Data extraction

The investigators used a form specifically designed to extract data from eligible papers. Data from the papers were extracted into summary tables containing information on author(s) name(s), publication year, detection methods, country, region, setting, sample type, total number of samples and the total number of confirmed C. difficile samples.

Quality assessment

The authors reviewed eligible research articles using Critical Appraisal Skills Programme (CASP) Checklists to evaluate cross-sectional studies. This tool has special items to evaluate the quality of a paper, using 10–12 items for each checklist. These checklists evaluate the strengths and weaknesses of articles, the quality of the study design and the applicability of studies. The precise checklist was applied to each paper according to the type of study. For each item, the possible answers were ‘Yes’, ‘No’ or ‘Can’t tell’. Scientist assessed the articles’ quality separately, and discrepancies were resolved via group discussion. For each item, an answer of ‘Yes’ was scored as 1, while answers of ‘No’ or ‘Can’t tell’ were set as 0. Therefore, the maximum score of cross-sectional studies in this systematic review was 11. Articles with scores of ≥75% of the total score were classified as good quality. Articles with scores of 25–75% of the total score were classified as moderate quality articles and articles with scores of <25% of the total score were classified as poor quality articles.8

Statistical analysis

We employed both random and fixed-effects models to calculate the pooled prevalence and 95% CIs. To evaluate heterogeneity among the studies, we utilized Cochran’s Q test and the I2 index. A random-effects model was selected for estimation when the I2 index was >50% and the p-value from Cochran’s Q test was <0.1. Forest plots illustrate the proportions of individual studies, the pooled prevalence and the heterogeneity across studies. The meta-analysis was performed using Stata version 14.

Results

Search results and eligibility

Initially, 3678 articles were obtained from the electronic database search. However, 3629 (98.86%) were excluded due to irrelevancy, duplicated documents, lack of access to the full text or insufficient data. Finally, 49 (1.33%) were deemed eligible and subjected to analysis.6–54 A flowchart illustrating the screening of papers is presented in Figure 1. Extracted data from studies included in the meta-analysis (up to 1 January 2024) are presented in Table 1.

Figure 1.

Figure 1.

Open in a new tab

PRISMA flowchart presenting the selection of articles analyzed in this systematic review and meta-analysis. PRISMA: Preferred Reporting Items for Systematic reviews and Meta-Analyses.

Table 1.

Characteristics of the studies included in the meta-analysis

Study number First author Year Country Setting Diagnostic methods Sample size number Positive number Reference
1 Aliramezani 2019 Iran Healthcare Culture/other test 1435 2 9
2 Büchler 2022 Switzerland Healthcare Culture/other test 206 37 10
3 Doughari 2021 Nigeria Healthcare Culture 150 18 11
4 Islam 2019 Bangladesh Non-healthcare Culture 94 11 12
5 Janezic 2018 Slovenia Non-healthcare Culture/other test 90 31 13
6 Janezic 2020 Slovenia Non-healthcare Culture 25 12 14
7 Jinhee 2022 USA Healthcare and non-healthcare - 6966 1794 15
Mexico, Peru, Guatemala, Brazil, France, Germany, Italy, Taiwan, India Non-healthcare - 891 194
8 Kabała 2022 Poland Healthcare Culture/other test 116 6 16
9 Kiersnowska 2022 Poland Healthcare Culture 116 6 17
10 Lemiech-Mirowska 2023 Poland Healthcare Culture 100 7 18
11 Lim 2020 Australia Healthcare Culture 302 159 19
12 Perumalsamy 2019 Australia Healthcare Culture 159 96 20
13 Reigadas 2020 Spain Healthcare Culture/other test 476 73 21
14 Riley 2018 Australia Non-healthcare PCR 145 86 22
15 Shivaperumal 2021 Australia Non-healthcare Culture 97 65 23
16 Rodriguez 2019 Belgium Non-healthcare Culture/other test 112 45 24
17 Sofjan 2020 Bangladesh Healthcare Culture 400 44 25
18 Srinivasa 2019 USA Healthcare Culture/other test 101 14 26
19 Villagomez-Estrada 2019 Spain Non-healthcare Culture/other test 100 4 27
20 Weppner 2021 USA Healthcare Culture 76 17 28
21 Zhou 2021 China Healthcare Culture 608 12 29
22 Blau 2023 Germany Non-healthcare Culture and other test 79 30 30
23 O’Shaughnessy 2019 Canada Non-healthcare Culture/other test 350 144 31
24 Simecka 2019 USA Healthcare Culture/other test 630 24 32
25 Khun 2023 Vietnam Healthcare and non-healthcare Culture 199 65 33
26 Warren 2022 USA Healthcare Culture 758 121 34
27 Lim 2022 Australia Healthcare Culture 600 185 35
28 Endres 2018 USA Healthcare Culture/other test 50 14 36
29 Tsai 2022 Taiwan Non-healthcare Culture/other test 29 7 37
30 Moradigaravand 2018 UK Non-healthcare Culture/other test 20 18 38
31 Garey 2020 USA Healthcare Culture 659 55 39
32 Shoaei 2019 Iran Healthcare Culture/other test 92 9 40
33 Odoyo 2020 Kenya Healthcare Culture 57 43 41
PCR 57 43
34 Brown 2018 Canada Healthcare PCR 96 50 42
Culture 48 21
35 Moono 2017 Australia Non-healthcare Culture/other test 311 182 43
36 Alam 2017 USA Healthcare and non-healthcare - 2538 418 44
37 Orden 2018 Spain Non-healthcare Culture/other test 40 21 45
Open in a new tab

Table 1.

Continued

Study number Author Year Country Setting Diagnostic methods Sample size number Positive number Reference
38 Taha 2022 Egypt Non-healthcare Culture 200 38 46
39 Alves 2022 Portugal Non-healthcare Culture/other test 60 35 47
40 Redding 2021 USA Non-healthcare Culture/other test 92 28 48
41 Usui 2017 Japan Non-healthcare Culture/other test 14 5 49
42 Marcos 2021 Ireland Non-healthcare Culture/other test 180 68 50
43 Alam 2014 USA Non-healthcare Culture/other test 127 41 51
44 Leitner 2020 Austria Healthcare Culture 92 0 52
45 Ali 2021 India Non-healthcare Culture/other test 6 1 53
46 Lim 2020 Australia Non-healthcare - 142 32 54
47 Janezic 2016 Slovenia Non-healthcare Culture/other test 183 44 55
48 Baghani 2020 Iran Non-healthcare Culture/other test 72 1 56
49 Shaughnessy 2016 USA Non-healthcare Culture/other test 233 31 57
Open in a new tab

Characteristics of eligible studies

In general, 49 studies measured C. difficile contamination in healthcare and non-healthcare settings. Among these, 25 (51.02%) measured contamination in healthcare settings. Non-healthcare settings consisted of farms, public places, homes and veterinary hospitals. Of the 49 eligible studies, 21 (42.85%) were published before 2020. Based on WHO regions, two were conducted in Africa, while 13, 16, four, three and 11 were conducted in America, Europe, Eastern Mediterranean, South-East Asia and Western Pacific, respectively.

Quality of the eligible studies

Of the 49 original articles, considering the total CASP scores, 31 (63.26%) met all the approval criteria; 46 (93.87%) were classified as good quality and three (6.13%) were classified as moderate quality. No articles were classified as being of poor quality.

Prevalence of C. difficile contamination

Overall, 20 779 environmental samples were investigated in healthcare and non-healthcare settings. Among these, 4507 samples were positive for C. difficile contamination using different detection methods. Meta-analysis indicated that the pooled prevalence of C. difficile contamination using random effects was estimated as 0.26 (95% CI 0.23 to 0.28). There was a high degree of heterogeneity in the prevalence estimates between different studies. It was observed that the Q statistic was 6767.31 (df=48), p<0.01 and I2=99.29% (Table 2 and Figure 2).

Table 2.

Pooled prevalence of C. difficile contamination in healthcare and non-healthcare environments

Total Heterogeneity Heterogeneity
Number Sample Number Pooled between
Independent variable of studies size positive prevalence 95% CI Q statistic I2 (%) p subgroup bias
Diagnostic test
 Culture 19 4740 975 0.26 0.21–0.32 1709.52 98.95 0.00 0.00
 Culture and other test 26 5204 915 0.27 0.21–0.33 1655.63 98.49 0.00
 PCR 3 298 179 0.62 0.50–0.74 0 0 0.00
Region
 Africa 2 264 104 0.31 0.27–0.36 - - - 0.00
 Eastern Mediterranean 4 1799 50 0.07 0.01–0.13 56.58 94.70 0.00
 America 13 12 724 2772 0.23 0.17–0.29 813.01 98.52 0.00
 South-East Asia 3 500 56 0.11 0.08–0.14 - - -
 Western Pacific 11 2606 894 0.41 0.23–0.58 1365.82 99.27 0.00
 Europe 16 1995 437 0.28 0.20–0.36 815.86 98.16 0.00
Year
 Before 2020 21 6968 1311 0.31 0.25–0.38 2294.83 99.13 0.00 0.11
 After 2020 28 13 811 3196 0.24 0.19–0.30 4415.21 99.39 0.00
Setting
 Healthcare 25 11 475 1962 0.18 0.16–0.20 2929.39 99.18 0.00 0.00
 Non-healthcare 30 9304 2545 0.36 0.30–0.41 1157.38 97.49 0.00
Sample type
 Soil 8 530 310 0.59 0.47–0.71 60.19 88.37 0.00 0.00
 Shoe 8 2084 813 0.34 0.23–0.45 156.27 95.52 0.00
Open in a new tab

Figure 2.

Figure 2.

Open in a new tab

Forest plot of the pooled prevalence of C. difficile contamination in healthcare and non-healthcare environments.

According to diagnostic method, the pooled prevalence of C. difficile contamination by culture test was 0.26 (95% CI 0.21 to 0.32). The pooled prevalence using PCR was 0.62 (95% CI 0.50 to 0.74). Meanwhile, the pooled prevalence using a mixed method was 0.27 (95% CI 0.21 to 0.33) (Table 2 and Figure 3).

Figure 3.

Figure 3.

Open in a new tab

Forest plots of the pooled prevalence of C. difficile contamination in healthcare and non-healthcare environments according to (A) diagnostic test, (B) setting and (C) year.

The pooled prevalence of C. difficile contamination was 0.31 (95% CI 0.25 to 0.38) and 0.24 (95% CI 0.19 to 0.30) before and after 2020, respectively (Figure 3).

The pooled prevalence of C. difficile contamination according to region indicated that the highest prevalence was in the Western Pacific with a prevalence of 0.41 (95% CI 0.23 to 0.58). The lowest prevalence was in the Eastern Mediterranean with a prevalence of 0.07 (95% CI 0.01 to 0.13). The pooled prevalence in the other regions was 0.40, 0.31, 0.23 and 0.11 in Europe, Africa, America and South-East Asia, respectively. Complete results by region are shown in Table 2 and Figure 4.

Figure 4.

Figure 4.

Open in a new tab

Forest plot of the pooled prevalence of C. difficile contamination in healthcare and non-healthcare environments according to region.

The pooled prevalence of C. difficile contamination according to setting was 0.18 (95% CI 0.16 to 0.20) in the healthcare environment and 0.36 (95% CI 0.30 to 0.42) in the non-healthcare environment (Figure 3).

The pooled prevalence of C. difficile contamination according to sample type was 0.59 (95% CI 0.47 to 0.71) in soil samples and 0.34 in shoe samples (95% CI 0.32 to 0.45).

Prevalence of C. difficile contamination in healthcare environments

In total, among 11 475 environmental samples in healthcare settings, 1962 were positive for C. difficile contamination. The pooled prevalence of C. difficile contamination among environmental samples in healthcare settings was 0.18 (95% CI 0.16 to 0.20).

The pooled prevalence of C. difficile contamination in healthcare environments according to region indicated that the highest prevalence was found in the Western Pacific (0.33; 95% CI 0.10 to 0.56), followed by Africa (0.31; 95% CI 0.27 to 0.36). The prevalence for all regions is shown in Table 3.

Table 3.

Pooled prevalence of C. difficile contamination in healthcare and non-healthcare environments

Heterogeneity
Independent variable Number of studies Sample size Total number positive Pooled prevalence 95% CI Q statistic I2 (%) p Heterogeneity between subgroup bias
Healthcare
Region
 Africa 2 264 104 0.31 0.27–0.36 - - - 0.00
 Eastern Mediterranean 2 1527 11 0.00 0.00–0.00 - - -
 America 9 6359 1193 0.19 0.12–0.26 449.47 98.22 0.00
 South-East Asia 1 400 44 0.11 0.08–0.14 - - -
 Western Pacific 5 1819 481 0.33 0.10–0.56 695.26 99.42 0.00
 Europe 6 1106 129 0.08 0.02–0.15 149.67 96.66 0.00
Sample type
 Bed 7 447 43 0.09 0.04–0.15 53.52 88.79 0.00 0.00
 Chair 2 246 16 0.03 0.01–0.05 - - -
 Computer 3 108 7 0.04 0.00–0.09 - - -
 Door handle 2 32 1 0.00 0.00–0.01 - - -
 Light switch 2 98 0 0.00 0.00–0.00 - - -
 Shoe 3 643 205 0.34 0.17–0.51 - - -
 Soil 2 189 121 0.66 0.59–0.73 - - -
 Table 3 76 9 0.10 0.03–0.17 - - -
 Toilet or bathroom 5 413 97 0.14 0.01–0.28 98.88 95.95 0.00
 Wheelchair 2 40 5 0.12 0.02–0.22 - - -
 Window 2 37 4 0.01 0.00–0.04 - - -
Non-healthcare
Location
 Public 16 6797 1869 0.38 0.28–0.48 705.04 98.01 0.00 0.00
 Home 6 1607 345 0.33 0.20–0.45 138.87 96.32 0.00
 Farm 7 800 327 0.42 0.31–0.53 54.79 89.05 0.00
 Veterinary hospital 1 100 4 0.04 0.02–0.10 - - -
Open in a new tab

The pooled prevalence of C. difficile contamination according to sample type indicated that the highest contamination rates were in soil and shoes, with a prevalence of 0.66 (95% CI 0.59 to 0.73) and 0.34 (95% CI 0.17 to 0.51), respectively. This was followed by toilet or bathroom with a prevalence of 0.14 (95% CI 0.01 to 0.28), then wheelchair with a prevalence of 0.12 (95% CI 0.02 to 0.22). Complete results due to the prevalence of various sample types in healthcare settings are shown in Table 3.

Prevalence of C. difficile contamination in non-healthcare environments

Overall, among 9304 non-healthcare environmental samples, 2545 were positive for C. difficile contamination. The pooled prevalence was 0.36 (95% CI 0.30 to 0.41). The prevalence in the non-healthcare environment according to location was 0.42, 0.38, 0.33 and 0.04 on farms, in public places, in the home and veterinary hospital, respectively.

Discussion

Clostridioides difficile is a Gram-positive, spore-forming anaerobic bacterium that is the cause of antibiotic-associated diarrhea, toxic megacolon and pseudomembranous colitis, which may be life-threatening.58 The bacterium is resistant to a wide range of bactericide substances due to the endospore, which can survive for months in harsh environments. This study is the first global comprehensive systematic review concerning C. difficile contamination in healthcare and non-healthcare environments and summarizes its prevalence over the last decade (2014–2024).

In the current study, the pooled prevalence of C. difficile contamination in all environmental samples was estimated as 0.26, but was different for various levels of other variables such as diagnostic test and setting. This result indicates the notable presence of C. difficile in diverse environments across the world in the last decade. On the other hand, research data suggest that C. difficile can persist on surfaces for months. Also, the bacterium has shown resistance to various chemical agents and disinfectants in recent years. Therefore, to effectively control CDI rates, it is crucial to implement a standardized surveillance program with attention paid to the role of the environment in the transmission of the disease. In recent years, more attention and effort have been dedicated to controlling CDI, especially healthcare-associated CDI, and some countries have established guidelines for the detection and control of infection. However, there is a need to implement these programs and guidelines on a global scale, taking account of the role of the environment in the spread of the disease.

Based on our results, the pooled prevalence was 0.31 (95% CI 0.25 to 0.38) and 0.24 (95% CI 0.19 to 0.30) before and after 2020, respectively, which indirectly shows the decrease in CDI cases in recent years. Research indicates that patients treated with certain antibiotics are less likely to contaminate their surroundings, demonstrating a direct link between infection management and environmental hygiene.59 Therefore, the decreased contamination rate in the environment in recent years can be attributed to implementing a control program of CDI in several countries, especially in the healthcare system. For example, there is increasingly promising evidence that CDI rates have declined in the healthcare systems of Europe and the USA that should be implemented in other countries.

Screening is an important method for disease control, for reducing symptoms and costs. Choosing screening-accurate tools to identify contaminated samples should be considered. Assessments of diagnostic testing, extracted from studies, were included in this study. Our results based on the diagnostic method utilized indicated that the pooled prevalence was an estimated 26% (95% CI 21 to 32%) using a culture test, approximately equal to those found with a culture test plus another method, attributable to other tests being used less than culture in a large number of studies, although it was an estimated 62% (95% CI 50 to 74%) for PCR only. Most studies found that the molecular-based method is more sensitive and more specific than the culture test; therefore, it appears that PCR is suitable for screening.

Our findings indicated a pooled prevalence of 18% within the healthcare system, whereas the pooled prevalence for the non-healthcare system was 36%. However, we cannot definitively conclude that the prevalence is lower in healthcare compared with non-healthcare settings. This is because a significant portion of the non-healthcare samples were associated with public places, such as those from wastewater treatment plants and agricultural sources, including animal feces, manure and compost, which influenced our results. In any case, environmental contamination in healthcare plays an important role in the dissemination of C. difficile infection between hospital staff and patients, leading to an increase in hospital-acquired cases.

Our results for the healthcare environment indicate that shoes, toilet or bathroom and wheelchairs have the highest contamination rates. Shoe soles of healthcare personnel and community-dwelling individuals can become colonized by microorganisms through direct or indirect transmission routes. Thus, shoe soles can be recognized as agents for the spread of C. difficile spores. Exposure of shoe soles to the ultraviolet-C (UVC) device significantly decreased the contamination rate of bacteria. It is recommended that UVC devices are utilized in healthcare environments to lower the number of colony-forming units of bacteria on shoe soles, which will consequently reduce the colonization of other surfaces.

The results showed that the non-healthcare environment has a remarkable contamination rate for C. difficile. The contamination rate on farms and in the public environment was slightly higher than in the home environment. This can be attributed to the fact that, in the home environment, surfaces are continually being disinfected. It is important to note that the overall contamination rate in home environments could be significantly lower than reported, because most of the home samples were taken from shoes, soil and toilets.

Among non-healthcare environments, farms have the highest prevalence. The bacterium has been isolated from various surfaces in farms, including soil, sand and mud. It was suggested that contaminated animals could be a reservoir of C. difficile for transmission to humans.58 The genetic similarity of C. difficile strains found in animals and humans reinforces the idea that animal farms can serve as reservoirs for human infections.60,61 On the other hand, studies have shown that animals, especially pigs, cattle and poultry, can shed the bacterium in their feces, contributing to its presence in the farm environment.58 It seems that the transmission chain between animals and the community has a role in the increase of community-acquired cases. This result highlights the importance of monitoring and controlling the presence of C. difficile in agricultural settings to mitigate the risk of infection in the human population.

In addition to farms, our results indicates the presence of the bacterium in various public places, such as wastewater treatment plants, where it was detected at various stages of the treatment process. This indicates that the bacterium can endure the treatment processes typically employed at these facilities, raising concerns about its potential release into the environment and subsequent risk to public health. The presence of C. difficile in wastewater suggests that these environments could serve as reservoirs for community-associated CDI. Hence, wastewater environments are critical in the transmission dynamics of C. difficile, necessitating enhanced monitoring and treatment strategies to mitigate the risks associated with this pathogen in public health contexts.

Overall, we report a notable global contamination rate for C. difficile among diverse environments over the last decade. Based on evidence, the risk of acquired environmental infection with C. difficile was similar to the risk of contact with an infected person.62 Therefore, environmental contamination with C. difficile plays an important role in increasing the number of reservoirs of C. difficile spores, leading to an increase in community-acquired cases. Therefore, there is a need to implement programs and guidelines on a global scale, taking account of the role of the environment in the spread of the disease.

The strengths of this study include its large total sample size and extraction of detailed data. However, this study has some limitations, and the results presented here should be interpreted with regard to these limitations. One primary limitation of this review is the possibility that our search strategy missed some studies. To address this limitation, we utilized PubMed and Google Scholar, both of which cover a wide range of scientific journals. Additionally, we conducted a thorough search of the references cited in eligible papers to identify any further relevant studies. Another limitation concerns the uneven distribution of studies across different strata, such as region. After stratifying the results by various variables, some strata had relatively few studies, which may have impacted the reliability of the prevalence estimates for those strata. We have transparently described the characteristics and number of studies per strata in the current article to ensure readers are aware of this limitation. Finally, it is important to highlight that the type of environmental sample is the key variable likely affecting prevalence comparisons across different strata. Nonetheless, we have tried to interpret the results with this factor in mind to offer a more nuanced understanding of the findings.

Conclusions

The findings of our study over the past decade reveal a significant prevalence of C. difficile contamination across various environments worldwide. This alarming trend underscores a pressing need to prioritize environmental factors and implement effective disinfection strategies as part of comprehensive prevention and control programs aimed at tackling this challenging disease. By addressing the environmental reservoirs of C. difficile, we can take proactive steps to mitigate the spread of this pathogen and improve public health outcomes.

Contributor Information

Mohammad Hasan Rabiee, Department of Epidemiology, Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj 31975-148, Iran.

Lida Abdolmohammadi Khiav, Department of Anaerobic Bacterial Vaccine Production and Research, Clostridia Research Laboratory, Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj 31975-148, Iran.

Mohammad Hossein Fallah Mehrabadi, Department of Epidemiology, Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj 31975-148, Iran.

Authors’ contributions

MHR and LAK contributed equally to this work. MHFM, MHR and LAK conceived and designed the study. LAK conducted the search and extracted data from paper. MHR and MHFM performed the statistical analysis and verified the underlying data. LAK and MHR wrote the first draft of the manuscript. All the authors reviewed and approved the final report. All the authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. All the authors read and approved the final version of the manuscript.

Funding

The authors received no specific funding for this work.

Competing interests

No potential conflict of interest was reported by the authors.

Ethical approval

Not required.

Data availability

We are committed to sharing the data upon rational request.

References

  • 1. Rodriguez  C, Taminiau  B, Korsak  N, et al. Longitudinal survey of Clostridium difficile presence and gut microbiota composition in a Belgian nursing home. BMC Microbiol. 2016;16:1–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Abbasian  H, Hajimolaali  M, Yektadoost  A, et al. Antibiotic utilization in Iran 2000–2016: pattern analysis and benchmarking with organization for economic co-operation and development countries. J Res Pharm Pract. 2019;8(3):162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Khiav  LA, Zahmatkesh  A. Vaccination against pathogenic clostridia in animals: a review. Trop Anim Health Prod. 2021;53(2):1–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Riggs  MM, Sethi  AK, Zabarsky  TF, et al. Asymptomatic carriers are a potential source for transmission of epidemic and nonepidemic Clostridium difficile strains among long-term care facility residents. Clin Infect Dis. 2007;45(8):992–8. [DOI] [PubMed] [Google Scholar]
  • 5. CDC . Antibiotic Resistance Threats in the United States. U.S. Department of Health and Human Services, CDC; 2019. Available at: http://www.cdc.gov/DrugResistance/Biggest-Threats.html  [accessed 15 September 2021]. [Google Scholar]
  • 6. Rutala  WA, Weber  DJ. Role of the hospital environment in disease transmission, with a focus on Clostridium difficile. Healthcare Infection. 2013;18(1):14–22. [Google Scholar]
  • 7. Kramer  A, Schwebke  I, Kampf  G. How long do nosocomial pathogens persist on inanimate surfaces? A systematic review. BMC Infect Dis. 2006;6(1):130. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Long  HA, French  DP, Brooks  JM. Optimising the value of the critical appraisal skills programme (CASP) tool for quality appraisal in qualitative evidence synthesis. RMHSMHS. 2020;1(1):31–42. [Google Scholar]
  • 9. Aliramezani  A, Talebi  M, Golbabaei  F, et al. Characterization of Clostridioides difficile isolates recovered from hospitalized patients and the hospitals environment and air: a multicenter study. Anaerobe. 2019;59:154–8. [DOI] [PubMed] [Google Scholar]
  • 10. Büchler  AC, Wicki  M, Frei  R, et al. Matching Clostridioides difficile strains obtained from shoe soles of healthcare workers epidemiologically linked to patients and confirmed by whole-genome sequencing. J Hosp Infect. 2022;126:10–5. [DOI] [PubMed] [Google Scholar]
  • 11. Doughari  J, Kachalla  N, Jaafaru  M. Prevalence of Clostridium difficile in hospital environment within Yola Adamawa State Nigeria. Microbiol Infect Dis. 2021;5(2):1–5. [Google Scholar]
  • 12. Islam  MA, Kabir  ND, Moniruzzaman  M, et al. Clostridioides difficile ribotypes isolated from domestic environment and from patients in Bangladesh. Anaerobe. 2019;56:88–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Janezic  S, Mlakar  S, Rupnik  M. Dissemination of Clostridium difficile spores between environment and households: dog paws and shoes. Zoonoses Public Health. 2018;65(6):669–74. [DOI] [PubMed] [Google Scholar]
  • 14. Janezic  S, Smrke  J, Rupnik  M. Isolation of Clostridioides difficile from different outdoor sites in the domestic environment. Anaerobe. 2020;62:102183. [DOI] [PubMed] [Google Scholar]
  • 15. Jo  J, Gonzales-Luna  AJ, Lancaster  CK, et al. Multi-country surveillance of Clostridioides difficile demonstrates high prevalence of spores in non-healthcare environmental settings. Anaerobe. 2022;75:102543. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Kabała  M, Gofron  Z, Aptekorz  M, et al. Detection of Clostridioides difficile in hospital environment by using C diff Banana Broth™. Anaerobe. 2022;73:102408. [DOI] [PubMed] [Google Scholar]
  • 17. Kiersnowska  ZM, Lemiech-Mirowska  E, Michałkiewicz  M, et al. Detection and analysis of Clostridioides difficile spores in a hospital environment. Int J Environ Res Public Health. 2022;19(23):15670. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Lemiech-Mirowska  E, Michałkiewicz  M, Sierocka  A, et al. The hospital environment as a potential source for Clostridioides difficile transmission based on spore detection surveys conducted at paediatric oncology and gastroenterology units. Int J Environ Res Public Health. 2023;20(2):1590. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Lim  S, Collins  D, Riley  T. Environmental sources of Clostridioides (Clostridium) difficile in the hospital. Int J Infect Dis. 2020;101:274–5. [Google Scholar]
  • 20. Perumalsamy  S, Putsathit  P, Riley  TV. High prevalence of Clostridium difficile in soil, mulch and lawn samples from the grounds of Western Australian hospitals. Anaerobe. 2019;60:102065. [DOI] [PubMed] [Google Scholar]
  • 21. Reigadas  E, Vázquez-Cuesta  S, Villar-Gómara  L, et al. Role of Clostridioides difficile in hospital environment and healthcare workers. Anaerobe. 2020;63:102204. [DOI] [PubMed] [Google Scholar]
  • 22. Riley  T, Lim  SC, Moono  P, et al. High prevalence of Clostridium difficile in the Western Australian environment. Infect Dis Health. 2018;23:S20. [Google Scholar]
  • 23. Shivaperumal  N, Chang  BJ, Riley  TV. High prevalence of Clostridium difficile in home gardens in Western Australia. Appl Environ Microbiol. 2020;87(1):e01572–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Rodriguez  C, Bouchafa  L, Soumillion  K, et al. Seasonality of Clostridium difficile in the natural environment. Transbound Emerg Dis. 2019;66(6):2440–9. [DOI] [PubMed] [Google Scholar]
  • 25. Sofjan  AK, Islam  MA, Halder  K, et al. Molecular epidemiology of toxigenic Clostridioides difficile isolates from hospitalized patients and the hospital environment in Dhaka. Bangladesh Anaerobe.  2020;61:102081. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Srinivasa  VR, Hariri  R, Frank  LR, et al. Hospital-associated Clostridium difficile infection and reservoirs within the hospital environment. Am J Infect Control. 2019;47(7):780–5. [DOI] [PubMed] [Google Scholar]
  • 27. Villagómez-Estrada  S, Blanco  JL, Melo-Duran  D, et al. Detection of Clostridium difficile in the environment in a veterinary teaching hospital. Anaerobe. 2019;57:55–8. [DOI] [PubMed] [Google Scholar]
  • 28. Weppner  J, Gabet  J, Linsenmeyer  M, et al. Clostridium difficile infection reservoirs within an acute rehabilitation environment. Am J Phys Med Rehabil. 2021;100(1):44–7. [DOI] [PubMed] [Google Scholar]
  • 29. Zhou  Y, Zhou  W, Xiao  T, et al. Comparative genomic and transmission analysis of clostridioides difficile between environmental, animal, and clinical sources in China. Emerg Microbes Infect. 2021;10(1):2244–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Blau  K, Gallert  C. Prevalence, antimicrobial resistance and toxin-encoding genes of clostridioides difficile from environmental sources contaminated by feces. Antibiotics. 2023;12(1):162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. O’Shaughnessy  RA, Habing  GG, Gebreyes  WA, et al. Clostridioides difficile on Ohio swine farms (2015): A comparison of swine and human environments and assessment of on-farm risk factors. Zoonoses Public Health. 2019;66(7):861–70. [DOI] [PubMed] [Google Scholar]
  • 32. Simecka  JW, Fulda  KG, Pulse  M, et al. Primary care clinics can be a source of exposure to virulent Clostridium (now Clostridioides) difficile: an environmental screening study of hospitals and clinics in Dallas-Fort Worth region. PLoS One. 2019;14(8):e0220646. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Khun  PA, Phi  LD, Bui  HTT, et al. Environmental contamination with clostridioides (Clostridium) difficile in Vietnam. J Appl Microbiol. 2023;134(6):lxad118. [DOI] [PubMed] [Google Scholar]
  • 34. Warren  BG, Turner  NA, Addison  R, et al. The impact of infection versus colonization on Clostridioides difficile environmental contamination in hospitalized patients with diarrhea. Open Forum Infectious Diseases; 2022: Oxford University Press, UK. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Lim  SC, Collins  DA, Imwattana  K, et al. Whole-genome sequencing links Clostridium (Clostridioides) difficile in a single hospital to diverse environmental sources in the community. J Appl Microbiol. 2022;133(3):1156–68. [DOI] [PubMed] [Google Scholar]
  • 36. Endres  BT, Dotson  KM, Poblete  K, et al. Environmental transmission of Clostridioides difficile ribotype 027 at a long-term care facility; an outbreak investigation guided by whole genome sequencing. Infect Contr Hosp Epidemiol. 2018;39(11):1322–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Tsai  C-S, Cheng  Y-L, Chen  J-S, et al. Hypervirulent clostridioides difficile RT078 lineage isolates from the river: A potential reservoir for environmental transmission. J Microbiol Immunol Infect. 2022;55(5):977–81. [DOI] [PubMed] [Google Scholar]
  • 38. Moradigaravand  D, Gouliouris  T, Ludden  C, et al. Genomic survey of Clostridium difficile reservoirs in the East of England implicates environmental contamination of wastewater treatment plants by clinical lineages. Microbial Genomics. 2018;4(3):e000162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Garey  KW, Hengel  RL, Ritter  TE, et al. Evaluation of Clostridioides difficile environmental contamination surrounding C. difficile patients vs. non-C. difficile patients in Outpatient Infusion centers. Open Forum Infectious Diseases; 2020: Oxford University Press, UK. [Google Scholar]
  • 40. Shoaei  P, Shojaei  H, Khorvash  F, et al. Molecular epidemiology of Clostridium difficile infection in Iranian hospitals. Antimicrob Resist Infect Control. 2019;8:1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Odoyo  E, Kyanya  C, Mutai  W, et al. High levels of toxigenic Clostridioides difficile contamination of hospital environments: a hidden threat in hospital-acquired infections in Kenya. Access Microbiol. 2020;2(12):e000171. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Brown  KA, MacDougall  LK, Valenta  K, et al. Increased environmental sample area and recovery of Clostridium difficile spores from hospital surfaces by quantitative PCR and enrichment culture. Infect Control Hosp Epidemiol. 2018;39(8):917–23. [DOI] [PubMed] [Google Scholar]
  • 43. Moono  P, Lim  SC, Riley  TV. High prevalence of toxigenic Clostridium difficile in public space lawns in Western Australia. Sci Rep. 2017;7(1):41196. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Alam  MJ, Walk  ST, Endres  BT, et al. Community Environmental Contamination of Toxigenic Clostridium difficile. Open Forum Infectious Diseases; 2017: Oxford University Press, UK. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Orden  C, Neila  C, Blanco  JL, et al. Recreational sandboxes for children and dogs can be a source of epidemic ribotypes of Clostridium difficile. Zoonoses Public Health. 2018;65(1):88–95. [DOI] [PubMed] [Google Scholar]
  • 46. Taha  AE. Clostridioides difficile isolated from water; prevalence, antibiotic susceptibility and toxigenic activity. Int Med J. 2022;29(2):112–15. [Google Scholar]
  • 47. Alves  F, Nunes  A, Castro  R, et al. Assessment of the transmission dynamics of Clostridioides difficile in a farm environment reveals the presence of a new toxigenic strain connected to swine production. Front Microbiol. 2022;13:858310. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48. Redding  L, Huang  E, Ryave  J, et al. Clostridioides difficile on dairy farms and potential risk to dairy farm workers. Anaerobe. 2021;69:102353. [DOI] [PubMed] [Google Scholar]
  • 49. Usui  M, Kawakura  M, Yoshizawa  N, et al. Survival and prevalence of Clostridium difficile in manure compost derived from pigs. Anaerobe. 2017;43:15–20. [DOI] [PubMed] [Google Scholar]
  • 50. Marcos  P, Whyte  P, Rogers  T, et al. The prevalence of Clostridioides difficile on farms, in abattoirs and in retail foods in Ireland. Food Microbiol. 2021;98:103781. [DOI] [PubMed] [Google Scholar]
  • 51. Alam  MJ, Anu  A, Walk  ST, et al. Investigation of potentially pathogenic Clostridium difficile contamination in household environs. Anaerobe. 2014;27:31–3. [DOI] [PubMed] [Google Scholar]
  • 52. Leitner  E, Schreiner  E, Neuhold  M, et al. Low prevalence of Clostridium difficile colonization in patients in long-term care facilities in Graz, Austria: a point-prevalence study. Am J Infect Control. 2020;48(10):1144–7. [DOI] [PubMed] [Google Scholar]
  • 53. Ali  S, Singh  S, Singh  R, et al. Influence of multidrug resistance bacteria in river Ganges in the stretch of Rishikesh to Haridwar. Environ Chall. 2021;3:100068. [Google Scholar]
  • 54. Lim  SC, Knight  DR, Moono  P, et al. Clostridium difficile in soil conditioners, mulches and garden mixes with evidence of a clonal relationship with historical food and clinical isolates. Environ Microbiol Rep. 2020;12(6):672–80. [DOI] [PubMed] [Google Scholar]
  • 55. Janezic  S, Potocnik  M, Zidaric  V, et al. Highly divergent Clostridium difficile strains isolated from the environment. PLoS One. 2016;11(11):e0167101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56. Baghani  A, Alimohammadi  M, Aliramezani  A, et al. Isolation and characterization of a multidrug-resistant clostridioides difficile toxinotype V from municipal wastewater treatment plant. J Environ Health Sci Eng. 2020;18:1281–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Shaughnessy  MK, Bobr  A, Kuskowski  MA, et al. Environmental contamination in households of patients with recurrent Clostridium difficile infection. Appl Environ Microbiol. 2016;82(9):2686–92. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58. Bolton  D, Marcos  P. The environment, farm animals and foods as sources of Clostridioides difficile infection in humans. Foods. 2023;12(5):1094. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59. Biswas  J, Patel  A, Otter  J, et al. Reduction in Clostridium difficile environmental contamination by hospitalized patients treated with fidaxomicin. J Hosp Infect. 2015;90(3):267–70. [DOI] [PubMed] [Google Scholar]
  • 60. Tramuta  C, Spigaglia  P, Barbanti  F, et al. Comparison of Clostridioides difficile strains from animals and humans: first results after introduction of C. difficile molecular typing and characterization at the Istituto Zooprofilattico Sperimentale of Piemonte, Liguria e Valle d’Aosta, Italy. Comp Immunol Microbiol Infect Dis. 2021;75:101623. [DOI] [PubMed] [Google Scholar]
  • 61. Weese  JS. Clostridium (Clostridioides) difficile in animals. J Vet Diagn Invest. 2020;32(2):213–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62. Guerrero  DM, Nerandzic  MM, Jury  LA, et al. Acquisition of spores on gloved hands after contact with the skin of patients with Clostridium difficile infection and with environmental surfaces in their rooms. Am J Infect Control. 2012;40(6):556–8. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

We are committed to sharing the data upon rational request.

Articles from International Health are provided here courtesy of Oxford University Press

RESOURCES