
==== Front
Clin Infect Dis
Clin Infect Dis
cid
Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America
1058-4838
1537-6591
Oxford University Press US

10.1093/cid/ciad220
ciad220
Supplement Article
AcademicSubjects/MED00290
High-level Colonization With Antibiotic-Resistant Enterobacterales Among Individuals in a Semi-Urban Setting in South India: An Antibiotic Resistance in Communities and Hospitals (ARCH) Study
https://orcid.org/0000-0002-5464-1028
Kumar C P Girish Laboratory Division, Indian Council of Medical Research - National Institute of Epidemiology, Chennai, India

Bhatnagar Tarun ICMR School of Public Health, Indian Council of Medical Research - National Institute of Epidemiology, Chennai, India

Sathya Narayanan G Laboratory Division, Indian Council of Medical Research - National Institute of Epidemiology, Chennai, India

Swathi S S Laboratory Division, Indian Council of Medical Research - National Institute of Epidemiology, Chennai, India

Sindhuja V Laboratory Division, Indian Council of Medical Research - National Institute of Epidemiology, Chennai, India

Siromany Valan A Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

VanderEnde Daniel Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

Malpiedi Paul Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

Smith Rachel M Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

Bollinger Susan Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

Babiker Ahmed Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA

Styczynski Ashley Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA

Antibiotic Resistance in Communities and Hospitals India Team Arul K
Asish P R
Kumar M Chella
Varghese Elizabeth
Gowtham M M E
Heamchandsaravanan A R
Kalaiyarasi K
Kanagasivam C
Karthick N N
Kavitha M
Grace D Lavanya
Lavanya P
Mercury R
Mohan M Murali
Purushothaman M
Sabarinathan R
Saranya J
Kumar M P Sarath
Shameena N
Sridharan R A
Rao T Subba
Vasanthi K
Veeravel G
Murhekar Manoj Dr
Desai Meghna Dr
Srivatsan Arasi Dr
Kalgudi Rajshekar Dr
Velayudhan Anoop Dr
Surie Diya Dr

C. P. G. K. and T. B. contributed equally to this work.

Correspondence: C. P. G. Kumar, Laboratory Division, Indian Council of Medical Research - National Institute of Epidemiology, Ayapakkam, Chennai, 600077, India (girishkumar@nie.gov.in).
Potential conflicts of interest. A. B. reports receipt of grant funding from the Antibiotic Resistance Leadership Group and support from the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under award UM1AI104681. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

01 7 2023
05 7 2023
05 7 2023
77 Suppl 1 The Evolving Challenges of Antibiotic Resistance in Low- and Middle-Income Countries: Priorities and Solutions S111S117
© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America.
2023
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

Abstract

Background

Antimicrobial resistance poses a significant threat to public health globally. We studied the prevalence of colonization with extended-spectrum cephalosporin-resistant Enterobacterales (ESCrE), carbapenem-resistant Enterobacterales (CRE), and colistin-resistant Enterobacterales (Col-RE) in hospitals and the surrounding community in South India.

Methods

Adults from 2 hospitals and the catchment community who consented to provide stool specimens were enrolled. Stools were plated on CHROMagar selective for ESCrE, CRE, and Col-RE. Bacterial identification and antibiotic susceptibility testing were done using Vitek 2 Compact and disc diffusion testing. Colistin broth microdilution was performed for a subset of isolates. Prevalence estimates were calculated with 95% confidence intervals (CIs), and differences were compared across populations using the Pearson χ  2 or Fisher exact test.

Results

Between November 2020 and March 2022, 757 adults in the community and 556 hospitalized adults were enrolled. ESCrE colonization prevalence was 71.5% (95% CI, 68.1%–74.6%) in the community and 81.8% (95% CI, 78.4%–84.8%) in the hospital, whereas CRE colonization prevalence was 15.1% (95% CI, 12.7%–17.8%) in the community and 22.7% (95% CI, 19.4%–26.3%) in the hospital. Col-RE colonization prevalence was estimated to be 1.1% (95% CI, .5%–2.1%) in the community and 0.5% (95% CI, .2%–1.6%) in the hospital. ESCrE and CRE colonization in hospital participants was significantly higher compared with community participants (P < .001 for both).

Conclusions

High levels of colonization with antibiotic-resistant Enterobacterales were found in both community and hospital settings. This study highlights the importance of surveillance of colonization in these settings for understanding the burden of antimicrobial resistance.

We measured intestinal colonization with antimicrobial-resistant bacteria in a suburban setting in South India. Colonization rates of extended-spectrum cephalosporin-resistant, carbapenem-resistant, and colistin-resistant Enterobacterales were 71.5%, 15.1%, and 1.1% in community and 81.8%, 22.7%, and 0.5% in hospital participants, respectively.

antimicrobial resistance
carbapenem-resistant enterobacterales
difficult-to-treat resistant
extended spectrum β-lactamases–producing enterobacterales
colonization
CDC 10.13039/100000030 Global Health 10.13039/100006090 Security 10.13039/100011200 ICMR-NIE NU2GGH001859-03-03
==== Body
pmcAntimicrobial resistance (AMR) is a significant global health threat, leading to difficult or impossible-to-treat infections [1]. Infections caused by AMR bacteria place a tremendous burden on individuals and healthcare systems, from increased morbidity and mortality to prolonged hospital stays, higher treatment costs, and the potential for onward transmission [2, 3]. An estimated 4.95 million deaths were associated with AMR in 2019, with 1.27 million deaths directly attributable to AMR [4].

Some of the most significant AMR threats highlighted by the World Health Organization (WHO) and the US Centers for Disease Control and Prevention are extended-spectrum β-lactamase (ESBL)–producing Enterobacterales and carbapenem-resistant Enterobacterales (CRE) [5, 6]. These organisms were initially described among patients in hospital settings [7, 8]. However, over the past few decades, they have been increasingly identified as causing community-onset infections [9–11]. Colonization studies of ESBL-producing Enterobacterales of healthy travelers returning from countries in sub-Saharan Africa and South Asia suggest community-level colonization pressure prevails in these regions [12]. Colistin resistance is also of particular concern in many low- and middle-income countries (LMICs) where it is frequently a last-resort antibiotic for treating multidrug-resistant or extensively drug-resistant gram-negative bacterial infections, including CRE.

Intestinal colonization with AMR bacteria is an important precursor for AMR infection and can contribute to unrecognized transmission in hospitals and communities [13]. Measurement of AMR colonization, along with an evaluation of relevant epidemiologic data, can enable a better understanding of the landscape of AMR in community and healthcare settings. Additionally, colonizing AMR isolates could serve as indicators for the early identification of novel or emerging resistance phenotypes to inform public health prevention and containment strategies and policies. However, few studies have characterized colonization with AMR bacteria. To better understand the extent and transmission of colonizing AMR organisms in the Indian context, we conducted a cross-sectional study to estimate the prevalence of 3 types of AMR colonization among community- and hospital-based populations: extended-spectrum cephalosporin-resistant Enterobacterales (ESCrE), CRE, and colistin-resistant Enterobacterales (Col-RE).

METHODS

Study Setting

We conducted a period prevalence survey in a semi-urban area of Chennai with 18 109 households previously enumerated for establishing a demographic and health surveillance (DHS) cohort. We selected 2 secondary-level hospitals that serve the survey population: a 500-bed public hospital (hospital 1) and a 250-bed private hospital (hospital 2). The study was part of the Antibiotic Resistance in Communities and Hospitals (ARCH) studies conducted across 6 countries to evaluate the population-based prevalence of colonization with clinically significant AMR organisms [14].

Study Population

Eligible community participants were aged ≥18 years; without fever, diarrhea, or cough at the time of interview and specimen collection; and had slept overnight in the household for at least 4 weeks before the visit by the study staff. Eligible hospitalized adults were admitted to the study hospitals and were aged ≥18 years and without diarrhea, gastrointestinal bleeding, or severe neutropenia (absolute neutrophil count <500 cells/µL). Patients in coronavirus disease 2019 (COVID-19) wards were excluded due to limited access as well as to maintain the safety of the study staff.

Sample Size

Assuming that 20% of adults in the community or hospital were colonized with at least 1 of the AMR phenotypes, a sample size of 1000 was needed for an effective enrollment of 750 individuals from the community, and a sample size of 678 was needed for an effective enrollment of 509 inpatients from the hospitals. Each hospital's bed count proportion was used to estimate the number of inpatients to be sampled. The detailed methodology for sample size estimation in the ARCH studies is described elsewhere [14].

Sampling Design

A simple random sample of households was selected from among enumerated households in the DHS area. Within each household, 1 individual was then randomly chosen among eligible adults for enrollment. On each day of hospital surveillance, all newly admitted patients in the eligible (non–COVID-19) wards who were not approached for enrollment on the previous day were considered for enrollment by study staff.

Data Collection

Trained study staff approached the households selected from the sampling frame in the survey site and obtained permission from the head of household or household representative. After explaining the study in the local language, Tamil, we obtained informed consent from the adult participant from each enrolled household. The study staff administered a questionnaire and collected demographic data about household members and household characteristics from the consented participants. Data for the consented hospital inpatients were retrieved from their hospital case records. All patients were able to consent for themselves.

Laboratory Procedures

Hospital and community participants provided self-collected stool specimens in a stool collection kit as instructed by the study staff [14]. For hospital participants who were unable to do self-collection, the stool was collected from a bedpan. All stool samples were transported at 4°C to the laboratory for same-day processing. ESwab (COPAN Diagnostics, Inc, CA) was used for inoculating the stool specimens onto CHROMagar ESBL, mSuperCARBA, and COL-APSE agar plates and incubated at 37°C for 18–24 hours. From each CHROMagar plate, up to 3 unique colony morphotypes were selected for further analysis. Selected isolates were subjected to bacterial identification and antimicrobial susceptibility testing on the bioMerieux Vitek 2 Compact platform using gram-negative ID and AST N281 cards. Ceftazidime was the only third-generation cephalosporin included on the AST N281 card. Due to concerns that this would not adequately capture all ESCrEs with CTX-M–type ESBL, all isolates that grew on the CHROMagar ESBL plate and tested susceptible to ceftazidime underwent ceftriaxone disc diffusion testing [15]. All isolates that were classified as colistin-resistant and a subset that was colistin-intermediate by Vitek testing were retested using broth microdilution (BMD) for confirmation [16].

Operational Definitions

The 2022 Clinical Laboratory and Standards Institute interpretative criteria were used [16]. Isolates were classified as ESCrE (a phenotype suggestive of ESBL production) if they were resistant to ceftazidime or ceftriaxone and susceptible or intermediate to the carbapenems (doripenem, meropenem, and imipenem) tested. Isolates were classified as CRE if they were resistant to 1 or more carbapenems. ESCrE and CRE were considered mutually exclusive categories. Col-RE included isolates that tested resistant (minimum inhibitory concentration [MIC], ≥4) by both Vitek and BMD assays, plus a subset of isolates that tested intermediate (MIC ≤2) by Vitek but resistant by BMD. Escherichia coli, Klebsiella spp., and Enterobacter spp. isolates that were intermediate or resistant to all β-lactams and fluoroquinolones tested were classified as having a difficult-to-treat resistant (DTR) phenotype [17].

Statistical Methods

We calculated the frequency and proportion of bacterial species isolated from the stool samples collected. The prevalence of persons with ESCrE, CRE, Col-RE, and DTR phenotypes was calculated with 95% confidence intervals (CIs), and differences were compared using a 2-sample test for proportion with or without Yates correction when appropriate. Differences in the prevalence between the 2 hospitals and between hospital wards were assessed using the Pearson χ  2 test or Fisher exact test when appropriate. The analyses were performed using R Studio (RStudio Team, 2022) and IBM SPSS Statistics for Windows, Version 25.0 (IBM Corp, Armonk, NY).

Ethical Approval

The Institutional Human Ethics Committee of Indian Council of Medical Research-National Institute of Epidemiology and the Health Ministry's Screening Committee approved the study.

RESULTS

Enrollment

Between November 2020 and March 2022, the field teams approached 1848 residents in the community and 1397 hospitalized patients. Of those approached, 757 (41.0%) in the community and 556 (39.8%) in the hospitals agreed to provide both survey responses and stool samples. Overall, 430 (56.8%) community and 310 (55.8%) hospitalized participants were female. The mean age of participants was 45.2 years (standard deviation [SD], 14.1; range, 18–83) in the community and 45.5 years (SD, 16.4; range, 18–85) in the hospitals. Among hospitalized participants, the median time from admission to stool collection was 3 days (interquartile range, 2–4). Of the 556 hospitalized participants, 289 (52.0%) were from the internal medicine ward, 144 (25.9%) from the obstetrics/gynecology ward, 71 (12.8%) from surgery/orthopedics wards, and 52 (9.3%) from the intensive care units (ICUs; Table 1).

Table 1. Demographic and Clinical Characteristics of Community and Hospital Participants in a Semi-Urban Setting in South India: 2020–2022

Characteristic	Community N = 757	Hospital N = 556	
n (%)	n (%)	
Gender	Male	327 (43.2)	246 (44.2)	
	Female	430 (56.8)	310 (55.8)	
Age group, y	18–24	44 (5.8)	57 (10.3)	
	25–49	430 (56.8)	258 (46.4)	
	50–64	195 (25.8)	152 (27.3)	
	≥65	88 (11.6)	89 (16)	
Hospital ward	General medicine	…	289 (52)	
	Intensive care unit	…	52 (9.4)	
	Obstetrics/Gynecology	…	144 (25.9)	
	Surgical/Orthopedics	…	71 (12.8)	
Comorbidity	Cardiovascular disease	…	59 (10.6)	
	Diabetes mellitus	…	51 (9.2)	
	Hypertension	…	47 (8.5)	
	Respiratory diseases	…	27 (4.9)	
	Anemia	…	12 (2.2)	
	Othersa	…	29 (5.2)	
Includes liver disease, malignancy, chronic kidney disease, pulmonary edema, sepsis, epilepsy, hyperthyroidism, and hernia.

Isolation of AMR Enterobacterales

Overall, 1767 isolates from the community and 1518 isolates from hospitalized participants were confirmed as Enterobacterales. The most commonly isolated organisms were E. coli (64.0% from the community, 66.9% from hospitals) and Klebsiella pneumoniae (29.3% from the community, 26.9% from hospitals).

Prevalence of Colonization by AMR Enterobacterales

At least 1 target phenotype (ESCrE, CRE, or Col-RE) was detected in 77.7% (n = 588) of participants from the community and 90.3% (n = 502) of hospitalized participants. Among the 757 community participants, 541 (71.5%; 95% CI, 68.1%–74.6%) were colonized with ESCrE and 114 (15.1%; 95% CI, 12.7%–17.8%) with CRE (Table 2). Of 556 inpatients, 455 (81.8%; 95% CI, 78.4%–84.8%) were colonized with ESCrE and 126 (22.7%; 95% CI, 19.4%–26.3%) with CRE. DTR phenotype prevalence was 10.8% (95% CI, 8.8%–13.2%) among community participants and 20% (95% CI, 16.8%–23.5%) among hospitalized participants. The prevalence of ESCrE, CRE, and DTR phenotypes was significantly higher among hospital vs community enrollees (P <.001 for all). The prevalence of Col-RE in the community (1.1%; 95% CI, .5%–2.1%) and hospital (0.5%; 95% CI, .2%–1.6%) was not statistically different (P = .478). The prevalence of ESCrE, CRE, and DTR phenotypes was similar between the 2 hospitals (Table 3). Among the hospital wards, the prevalence was highest for ESCrE in obstetrics/gynecology wards (86.8%), for CRE in ICUs (28.8%), and for DTR phenotypes in internal medicine wards (20.8%), though the differences were not statistically significant across different inpatient wards. Although most individuals were colonized with at least 1 target phenotype, co-colonization with multiple target phenotypes was more common among hospitalized participants (Table 4).

Table 2. Prevalence of Extended-Spectrum Cephalosporin-Resistant Enterobacterales, Carbapenem-Resistant Enterobacterales, Colistin-Resistant Enterobacterales, and Difficult-to-Treat Resistant Phenotype Colonization in Community and Hospital Participants in a Semi-Urban Setting in South India: 2020–2022

Resistance Pattern	Community	Hospital	P Value	
N	n	% (95% CI)	N	n	% (95% CI)	
Overall	
Extended-spectrum cephalosporin-resistant enterobacterales	757	541	71.5 (68.1–74.6)	556	455	81.8 (78.4–84.8)	<.001	
Carbapenem-resistant enterobacterales	757	114	15.1 (12.7–17.8)	556	126	22.7 (19.4–26.3)	<.001	
Colistin-resistant enterobacterales	757	8	1.1 (.5–2.1)	556	3	.5 (.2–1.6)	.478	
Difficult-to-treat resistant phenotypesa	757	82a	10.8 (8.8–13.2)	556	111a	20 (16.8–23.5)	<.001	
No Enterobacter spp. met the difficult-to-treat resistant definition.

Abbreviation: CI, confidence interval.

Table 3. Distribution of Extended-Spectrum Cephalosporin-Resistant Enterobacterales, Carbapenem-Resistant Enterobacterales, and Difficult-to-Treat Resistant Phenotype Colonization in Study Hospital Participants in a Semi-Urban Setting in South India: 2020–2022

Characteristic	N	Extended-Spectrum Cephalosporin-Resistant Enterobacterales	P Value	Carbapenem-Resistant Enterobacterales	P Value	Difficult-to-Treat Resistant Phenotypes	P Value	
n (%)	n (%)	n (%)	
Hospital	
 Hospital 1	345	277 (80.3)	.227	79 (22.9)	.865	70 (20.3)	.806	
 Hospital 2	211	178 (84.4)		47 (22.3)		41 (19.4)		
Ward	
 General medicine	289	231 (79.9)	.332	65 (22.5)	.720	60 (20.8)	.946	
 Intensive care unit	52	41 (78.8)		15 (28.8)		9 (17.3)		
 Obstetrics/Gynecology	144	125 (86.8)		31 (21.5)		28 (19.4)		
 Surgical/Orthopedics	71	58 (81.7)		15 (21.1)		14 (19.7)		

Table 4. Colonization Resistance Patterns Among Community and Hospital Participants in a Semi-Urban Setting in South India: 2020–2022

Resistance Pattern	Community	Hospital	P Value	
N = 757	N = 556	
n (%)	n (%)	
Resistant phenotypea	
ESCrE	
 No ESCrE	216 (28.5)	101 (18.2)	<.001	
 Only 1 ESCrE	287 (37.9)	132 (23.7)	<.001	
 2 ESCrE	182 (24.0)	182 (32.7)	.001	
 ≥3 ESCrE	72 (9.5)	141 (25.4)	<.001	
CRE	
 No CRE	643 (84.9)	430 (77.3)	.001	
 Only one CRE	67 (8.9)	56 (10.1)	.512	
 2 CRE	36 (4.8)	49 (8.8)	.005	
 ≥3 CRE	11 (1.4)	21 (3.8)	.012	
Mono-/Co-colonization statusb,c	
 Only ESCrE	468 (61.8)	375 (67.4)	.036	
 Only CRE	46 (6.1)	47 (8.5)	.097	
 ESCrE and CRE	66 (8.7)	77 (13.8)	.003	
 ESCrE and Col-RE	5 (0.7)	1 (0.2)	.389	
Abbreviations: Col-RE, colistin-resistant enterobacterales; CRE, carbapenem-resistant enterobacterales; ESCrE, extended-spectrum cephalosporin-resistant enterobacterales.

Col-RE colonization was seen in 8 community and 3 hospital participants.

Exclusive Col-RE colonization was seen in 1 community participant.

ESCrE, CRE, and Col-RE co-colonization was seen in 2 community and 2 hospital

participants.

DISCUSSION

In this cross-sectional study, we documented a high prevalence of colonization with ESCrE among adults in the community and adults admitted to the study hospitals as well as a substantial minority of participants with CRE colonization. Although colonization with CRE was less common than colonization with ESCrE, the prevalence of CRE in this study is concerning, given the limited number of treatment options for infections caused by these organisms. Col-RE was detected at much lower levels, indicating only low-level circulation of this phenotype in the study population.

The high prevalence of ESCrE colonization found in the community demonstrates that ESCrE is endemic in this population and is not confined to the healthcare setting. Indeed, the difference between community and hospital prevalence of ESCrE, although significant, may not be meaningful given the magnitude of community colonization pressure on healthcare facilities and apparent equilibration across the hospital–community divide. Earlier studies of ESBL-producing Enterobacterales from communities in India showed lower colonization prevalence—from 3.2% in Puducherry to 19% in Tamil Nadu [18, 19]. These differences likely represent differences in the study settings and varying methodologies, including laboratory methods and AMR definitions (ESBL-producing Enterobacterales vs ESCrE). The present study demonstrates high levels of ESCrE circulation in the community that are unlikely to be influenced by traditional hospital-based infection prevention and control (IPC) practices. Addressing the sources and causes of ESCrE and other multidrug-resistant organisms (MDROs) in the community through attention to animal husbandry practices, water and sanitation improvements, IPC practices in primary care settings, and programs that promote outpatient antibiotic stewardship is critical to reducing the spread in communities as well as the colonization pressure on hospitals.

The high level of ESCrE colonization in our study hospitals is consistent with reports from hospitals from other parts of India, including Kerala [20], Karnataka [21], and Uttar Pradesh [22], where colonization prevalence estimates ranging from 63% to 92% have been reported. CRE colonization, in contrast, was higher than recently reported from hospitalized patients in Chennai (7.8%) [23], Pune (2.5%) [24], and Delhi (11%) [25]. However, these estimates were collected prior to the COVID-19 pandemic, which has accelerated the spread of MDROs worldwide [26, 27]. Additionally, different laboratory methods could have contributed to differences in estimates. While the measures of inpatient colonization in this study are stark reminders of the importance of robust IPC programs in hospitals, the similarity between the community and hospital rates of CRE and ESCrE seen in this study suggests that the ability to impact overall rates of CRE and ESCrE via prevention of acquisition in healthcare facilities may be limited. However, given the high burden in the community, efforts should be implemented to promote early detection of colonization of admitted patients along with appropriate IPC measures to prevent further transmission within hospitals.

While we did not find exceptionally high rates of CRE in community participants, it is a valuable addition to the very scant existing data on the burden of this resistance phenotype among community dwellers. The discovery of the New Delhi metallo-β-lactamase (NDM-1) enzyme in drinking water and groundwater in New Delhi in 2010 shows that genetic markers of carbapenem resistance were present in the environment at a time before such resistance genotypes were detected clinically [28]. The subsequent recovery of bacteria possessing NDM-1 and other antibiotic-resistance genes from the aquatic environment has generated concern about the role of wastewater and pharmaceutical effluents in the expansion of highly drug-resistant pathogens in the environment in India [29–31]. A better understanding of the risk factors that lead to community colonization could inform colonization screening for patients on admission. Additionally, subsequent genomic analyses on isolates from this study may provide some insight into the movement of genetic mechanisms of resistance, particularly carbapenemases, and resistant bacterial strains between community and hospital environments either via person-to-person transmission or person-to-environment-to-person transmission.

Though not widely used in high-income countries where newer combination antibiotics are available, colistin remains an important antibiotic in many resource-limited settings where it is one of the few available treatment options for gram-negative MDROs. As a result, WHO listed colistin as one of the “highest priority critically important antimicrobials” [32]. In this study, a low prevalence (<5%) of colistin resistance was seen among both community and hospitalized adult participants. While this finding is reassuring, it contrasts with another report on colistin resistance in India that showed high rates of colistin-resistant colonization (53.8%), as determined by BMD, among cancer patients in Chennai, India [33]. This may be due to differences in the underlying populations between studies, such as the number of ICU or cancer patients or those with longer lengths of stay, which made up a minority of participants in this study. Regardless, attention to rates of colistin resistance, particularly in combination with carbapenem and cephalosporin resistance, is critical to prevent the development of untreatable infections in resource-limited settings.

The DTR phenotype is a type of treatment-limiting co-resistance among invasive infections and has been associated with worse clinical outcomes [32, 34, 35]. While it has yet to be validated in LMICs or in colonizing organisms, we are the first to describe DTR phenotypes in community and hospital colonization in India. The prevalence of DTR phenotypes among E. coli, K. pneumoniae, and Enterobacter spp. in the community (10.8%) and hospital (20%) represents a substantial pool of persons who have the potential to develop serious, difficult-to-treat infections with increased morbidity and mortality. Examining and monitoring the level of DTR phenotypes among colonizing Enterobacterales has significance given the therapeutic and IPC implications this phenotype denotes.

In this study, we used a robust sampling strategy that included established methodologies to identify AMR colonization accurately. For the first time, we evaluated population-level MDRO colonization in a community in India and compared it with surrounding hospitals. However, one of the study's limitations is that the prevalence estimates may not be generalizable to other areas of India or other age groups (eg, children). Additionally, colonization estimates in the hospital may have been underestimated as patients were enrolled relatively early during their hospital course. The sensitivity of the chromogenic media is reportedly greater than 93% for the detection of ESBL- and carbapenemase-producing organisms in stool [36]. However, we did not verify the sensitivity in the present study, which could have affected our estimates of MDRO colonization. Furthermore, due to resource constraints, Vitek was the primary method used for colistin susceptibility testing, despite known inaccuracies associated with this method [37]. Although a subset of isolates (n = 339, 10.3%) were retested using BMD, Col-RE prevalence and co-colonization may be slightly underestimated because of the reliance on Vitek results.

Since colonization often precedes infection, colonization surveillance provides an upstream opportunity to detect early trends in resistance that are likely to have clinical significance. Use of a point prevalence approach minimizes the resources required while giving a “status update.” Comparison of clinical and colonizing isolates will be useful to understand the pathogenic potential and genetic relatedness of the colonizing organisms. In addition to drug-resistance data, epidemiological and clinical data are important to formulate and drive AMR intervention strategies.

In conclusion, we have shown high colonization levels with MDROs among hospital and community participants, including a surprising abundance of CRE in the community. This adds to the understanding of the burden of AMR in India and emphasizes the need for community-level intervention strategies in addition to hospital IPC measures to mitigate the spread of MDROs. Given the similar levels of these phenotypes across the hospital–community divide, additional isolate analysis, including whole-genome sequencing, would be helpful to elucidate the relationship between these organisms in community and hospital participants. Similarly, understanding whether similar or divergent risk factors are associated with CRE and ESCrE, as well as protective factors in noncolonized individuals, will be helpful in guiding future prevention and mitigation measures. Finally, though colistin resistance was low in this study population, it remains an important phenotype for surveillance programs due to its activity against MDROs, especially in countries without other treatment options.

Notes

Acknowledgments. The authors thank the study participants, participating hospitals’ staff, and Antibiotic Resistance in Communities and Hospitals India study team members: K. Arul, P. R. Asish, M. Chella Kumar, Elizabeth Varghese, M. M. E. Gowtham, A. R. Heamchandsaravanan, K. Kalaiyarasi, C. Kanagasivam, N. N. Karthick, M. Kavitha, D. Lavanya Grace, P. Lavanya, R. Mercury, M. Murali Mohan, M. Purushothaman, R. Sabarinathan, J. Saranya, M. P. Sarath Kumar, N. Shameena, R. A. Sridharan, T. Subba Rao, K. Vasanthi, and G. Veeravel for their participation and contributions. The authors also thank Dr Manoj Murhekar, Dr Meghna Desai, Dr Arasi Srivatsan, Dr Rajshekar Kalgudi, Dr Anoop Velayudhan, and Dr Diya Surie for their support and contributions to the study.

Disclaimer. The findings and conclusions presented here are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention (CDC).

Supplement sponsorship. This article appears as part of the supplement “The Evolving Challenges of Antibiotic Resistance in Low- and Middle-Income Countries: Priorities and Solutions,” sponsored by the U.S. Centers for Disease Control and Prevention, and Health Security Partners.

Financial support. This work was supported by the US CDC (cooperative agreement for Global Health Security to Indian Council of Medical Research - National Institute of Epidemiology; grant NU2GGH001859).
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