Emerging Antibiotic Resistance in Vibrio cholerae: A Study of Cholera Prevalence and Resistance Patterns in Zambia's Copperbelt Province

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Cholera remains a significant public health challenge in Zambia, particularly in the Copperbelt Province, where antibiotic-resistant Vibrio cholerae strains are increasingly threatening treatment efficacy. This study aimed to determine the prevalence of cholera and the antibiotic resistance patterns of Vibrio cholerae isolates at three tertiary hospitals in the region. Methods A retrospective cross-sectional study was conducted across three major referral hospitals in the Copperbelt Province (Arthur Davison Children's Hospital, Kitwe Teaching Hospital, and Ndola Teaching Hospital) during the cholera outbreak from January to April 2024. Clinical samples from suspected cholera cases were analysed, and antimicrobial susceptibility testing followed Clinical Laboratory Standards Institute guidelines and the European Committee on Antimicrobial Susceptibility Testing methodology for Vibrio cholerae. To isolate Vibrio cholerae , alkaline peptone water and thiosulfate-citrate-bile salt-sucrose agar were utilized. The isolates were identified based on colony morphology, Gram staining, biochemical testing, and serotyping. Antimicrobial susceptibility testing was conducted by determining the minimum inhibitory concentration using the agar dilution method. Descriptive statistics were employed to assess the prevalence of Vibrio cholerae , and chi-square tests were applied with p-values of < 0.05 indicating statistical significance. Results Of the 892 suspected cases, 334 (37.4%) were confirmed as V. cholerae through culture. The highest number of V. cholerae confirmed cases was recorded at Ndola Teaching Hospital (24.8%), followed by Kitwe Teaching Hospital (9.9%), while Arthur Davison Children’s Hospital (2.8%) reported the lowest. High antimicrobial resistance was observed to ampicillin (98.6%), co-trimoxazole (96.8%) and imipenem (91.5%). In contrast, erythromycin (100%), ceftriaxone (96%) and gentamicin (85.7%) remained highly effective. The most common multidrug-resistant V. cholerae profile showed resistance to four or more antibiotics (14.6%). This was followed by resistance to the combination of ampicillin, ceftazidime, and co-trimoxazole (4.1%) and ampicillin, co-trimoxazole, and imipenem (2%). Conclusion The high prevalence of antibiotic-resistant V. cholerae in the Copperbelt Province highlights the urgent need for enhanced antimicrobial stewardship and surveillance programs to guide cholera treatment. The sustained efficacy of erythromycin and ceftriaxone suggests their potential as first-line treatments, but ongoing resistance monitoring is crucial. Antimicrobial stewardship cholera multidrug resistance Vibrio cholerae Zambia Figures Figure 1 Figure 2 Background Cholera is a severe diarrheal disease caused by the bacterium Vibrio cholerae , typically spread through contaminated water. It remains a significant public health challenge, particularly in regions with inadequate water, sanitation and hygiene (WASH) infrastructure [ 1 ]. The disease is typically spread through contaminated water and food, and its impact is most severe in low-resource settings, where overcrowding and poor sanitation exacerbate transmission [ 2 ]. In 2023, Sub-Saharan Africa experienced the 7th cholera pandemic, with reported cases rising to 535,321 and 4,007 deaths from 472,697 in 2022. Globally, cholera cases were reported in 45 countries in 2023, an increase from 44 in 2022 and 35 in 2021. While Africa saw a 125% surge in cases, the Middle East and Asia experienced a 32% decline [ 3 ]. Alarmingly, 60% of annual cholera-related deaths occur in Sub-Saharan Africa, underscoring the region's vulnerability to this disease [ 4 ]. Zambia, like many countries in Sub-Saharan Africa, has faced recurrent cholera outbreaks since 1977, with endemic transmission in regions such as Lusaka, Luapula, and the Copperbelt Province [ 5 ]. The Copperbelt Province, a densely populated and rapidly urbanizing area, is particularly susceptible to cholera due to its inadequate sanitation infrastructure, limited access to clean water, and high population mobility [ 6 ]. The 2024 cholera outbreak in Zambia was the most severe to date, with 19,719 cases and 682 deaths reported nationwide [ 7 ]. However, localized data on cholera prevalence and antibiotic resistance patterns in the Copperbelt Province remain scarce, hindering the development of targeted public health strategies. The global emergence of antimicrobial resistance (AMR) has further complicated cholera management, with Vibrio cholerae strains showing increasing resistance to commonly used antibiotics, such as tetracycline, chloramphenicol, and ciprofloxacin [ 8 ]. This resistance threatens the effectiveness of current treatment protocols, particularly in resource-limited settings like Zambia, where access to alternative antibiotics is often constrained [ 9 ]. While studies have documented varying resistance patterns in other regions of Zambia and neighbouring countries [ 10 , 11 ], there is a critical lack of data on the antibiotic resistance profiles of V. cholerae strains circulating in the Copperbelt Province. This knowledge gap limits the ability to design effective treatment guidelines and underscores the need for localized surveillance. This study addresses these gaps by determining the prevalence of cholera and the antibiotic resistance patterns of V. cholerae strains in three major referral hospitals in the Copperbelt Province. By integrating epidemiological and microbiological data, this research seeks to provide critical insights into the local dynamics of cholera transmission and resistance, informing more effective public health interventions and treatment strategies. The findings of this study will contribute to the growing body of knowledge on AMR in V. cholerae and support efforts to combat cholera in Zambia and beyond. Materials and Methods Study Design, Site and Population This was a hospital-based, retrospective cross-sectional study conducted at three tertiary hospitals in the Copperbelt Province: Arthur Davison Children's Hospital, Kitwe Teaching Hospital, and Ndola Teaching Hospital. These hospitals were selected due to their high patient volume during the cholera outbreak and their ISO 15189:2022-accredited laboratories, ensuring standardized diagnostic procedures. The study analysed clinical samples collected between January and April 2024, during the peak of the cholera outbreak in Zambia. The study population consisted of clinical samples sent to microbiology laboratories from patients suspected of having cholera infection, indicated by acute watery diarrhoea. The sampling frame included all Vibrio species detected during the study period. Both inpatients and outpatients with recorded demographic data, including age, sex, stool culture results, and antimicrobial susceptibility test (AST) results, were included in the study. Samples missing key variables such as age, sex, stool culture results, or AST results were excluded from the analysis. A total of 892 suspected cholera cases were included, providing sufficient statistical power to detect significant trends in resistance patterns based on similar studies [ 10 , 11 ]. The flowchart illustrating the study selection process is shown in Fig. 1 . Specimen processing Rectal swabs or stool samples were collected from suspected cholera cases using Cary Blair transport medium or clean stool containers and transported to the microbiology laboratory for processing [ 11 ]. A portion of each stool sample or rectal swab was directly inoculated and cultured onto Blood Agar (BA), MacConkey (MAC) and Thiosulfate-Citrate-Bile Salts-Sucrose (TCBS). The culture plates were incubated at 35°C-37°C for 18–24 hours. Secondly, samples were enriched in alkaline peptone water (APW) for 4–6 hours, followed by subculturing onto BA, MAC, and TCBS agar within the same incubation period [ 12 ]. On TCBS agar, suspected Vibrio cholerae colonies appeared as shiny yellow colonies due to sucrose fermentation. Suspected V. cholerae colonies were further sub-cultured on non-selective agar-Mueller Hinton for further confirmatory tests. Gram staining and a series of biochemical tests, including the oxidase test, were conducted to identify Vibrio species. [ 11 , 13 ]. Oxidase-positive colonies were further identified using several biochemical tests: Triple Sugar Iron (TSI) agar, Lysine Iron Agar (LIA), Sulphur Indole Motility (SIM) test, and the Citrate test. Additionally, serotyping was performed with antisera (Deben Diagnostics Ltd) to differentiate between Vibrio cholerae O1 or O139 , as well as serotyping for Ogawa or Inaba strains. A culture result was classified as positive when Vibrio cholerae O1 or 139 was isolated from stool samples. Conversely, a result was deemed negative if V. cholerae was not detected or if a non-O1/non-O139 strain of V. cholerae was isolated [ 13 , 14 ]. Antimicrobial Susceptibility Testing The antibiotic resistance profile of V. cholerae isolates was assessed using the Kirby-Bauer disk diffusion method on Mueller-Hinton agar, following Clinical Laboratory Standards Institute (CLSI) and European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines [ 12 , 15 , 16 ]. The antibiotics tested were selected based on their common use in cholera treatment and availability in the study laboratories. These included: ampicillin (10 µg), cotrimoxazole (trimethoprim/sulfamethoxazole) (1.25/23.75 µg), cefotaxime (30 µg), ceftazidime (30 µg), chloramphenicol (30 µg), ciprofloxacin (5 µg), ceftriaxone (30 µg), erythromycin (15 µg), and tetracycline (30 µg). Susceptibility testing was conducted by determining the minimum inhibitory concentration using the agar dilution method [ 13 ]. Clinical breakpoints for susceptibility testing were determined according to CLSI (M45) and EUCAST guidelines for Vibrio cholerae [ 12 , 15 , 16 ]. The interpretation of AST results was based on the zone of inhibition, categorized as susceptible, intermediate, or resistant. [ 17 ]. Quality Control for AST Routine quality control (QC) measures were implemented in each batch of AST to ensure accuracy, precision, and reliability. This included the use of control strains, Escherichia coli American type culture collection (ATCC) 25922 and Pseudomonas aeruginosa ATCC 27853, to validate the performance of media, reagents, and equipment [ 15 , 16 ]. This was performed to maintain consistency and compliance with established standards, following guidelines from CLSI [ 16 ]. Data collection and analysis Clinical and laboratory data were carefully reviewed for accuracy before being entered into a structured Microsoft Excel spreadsheet designed as a data collection tool. Data were extracted from the Laboratory Information System and microbiology registers to ensure completeness and reliability. To ensure consistency and validity, data were randomly checked and cross-matched by two independent reviewers. Discrepancies were resolved through discussion and re-examination of the original records. Statistical analysis was conducted using SPSS version 26. Descriptive statistics, including medians and proportions, were used to summarize the data and determine Vibrio cholerae prevalence and the distribution of study covariates. Missing data were handled through list-wise deletion, and sensitivity analyses were conducted to assess the impact of missing data on the results. Chi-square tests were used to compare resistance patterns across hospitals, with a p-value of < 0.05 considered statistically significant. Results Prevalence of Cholera in the Copperbelt Province During the study period, a total of 892 suspected cholera cases were reported across the three major referral hospitals in the Copperbelt Province. Of these, Vibrio cholerae was confirmed through culture in 334 cases, yielding an overall prevalence of 37.4%. Among the three hospitals, Ndola Teaching Hospital recorded the highest number of confirmed cases (n = 221, 24.8%), followed by Kitwe Teaching Hospital (n = 88, 9.9%), while Arthur Davison Children’s Hospital reported the lowest prevalence (n = 25, 2.8%) (Fig. 2 ). The age distribution revealed that the highest proportion of cases (n = 80, 26.1%) occurred among individuals aged 30–39 years, while the lowest (n = 14, 4.6%) was observed in those aged 70 years and above. The male-to-female ratio was 1.09:1, indicating a slightly higher number of male cases, with a median age of 31 years. Antimicrobial Resistance Patterns of Vibrio Cholerae The antibiotic susceptibility testing of Vibrio cholerae isolates demonstrated high resistance to several commonly used antibiotics, with high resistance observed for ampicillin (98.6%, n = 136), co-trimoxazole (96.8%, n = 90), imipenem (91.5%, n = 43), chloramphenicol (67.7%, n = 21), ceftazidime (54.1%, n = 59), ciprofloxacin (23.4%, n = 36), and tetracycline (25.8%, n = 25), rendering these drugs ineffective for cholera treatment (Table 1 ). In contrast to the high resistance observed for several antibiotics, certain drugs demonstrated strong efficacy against Vibrio cholerae isolates. Erythromycin (100%, n = 24), ceftriaxone (96%, n = 24), gentamicin (85.7%, n = 6), cefuroxime (81.8%, n = 9), ciprofloxacin (76.6%, n = 118) and tetracycline (74.2%, n = 72) and, respectively. Table 1 Antimicrobial Resistance Patterns of Vibrio cholerae Antimicrobial Agent Disk Content (µg) Susceptible (%) Resistant (%) High-Resistance Antibiotics Ampicillin 10 2 (1.4) 136 (98.6) Co-trimoxazole 25 3 (3.2) 90 (96.8) Imipenem 10 4 (8.5) 43 (91.5) Moderate-Resistance Antibiotics Chloramphenicol 30 10 (32.3) 21 (67.7) Ceftazidime 30 50 (45.9) 59 (54.1) Low-Resistance Antibiotics Ciprofloxacin 5 118 (76.6) 36 (23.4) Tetracycline 30 72 (74.2) 25 (25.8) High-Susceptibility Antibiotics Erythromycin 15 25 (100.0) 0 (0.0) Ceftriaxone 30 24 (96.0) 1 (4.0) Gentamicin 10 6 (85.7) 1 (14.3) Cefuroxime 10 9 (81.8) 2 (18.2) µg: Microgram, %: Percentage Multidrug Resistance Patterns Multidrug resistance (MDR), defined as resistance to three or more antibiotic classes, was detected in 33.7% (83/246) of the isolates. The most prevalent MDR profile involved resistance to four or more antibiotics (n = 36, 14.6%), followed by resistance to Ampicillin-Ceftazidime-Co-trimoxazole (n = 10, 4.1%), Ampicillin-Co-trimoxazole-Imipenem (n = 5, 2%), and Ampicillin-Amikacin-Co-trimoxazole (n = 5, 2%) (Table 2 ). Table 2 Multidrug Resistance Patterns in Vibrio cholerae Isolates Multidrug Resistance Profile Frequency (n) Percentage (%) Resistance to 4 or more antibiotics 36 14.6 Ampicillin + Ceftazidime + Co-trimoxazole 10 4.1 Ampicillin + Co-trimoxazole + Imipenem 5 2.0 Ampicillin + Amikacin + Co-trimoxazole 5 2.0 Other combinations 27 11.0 Total 83 33.7 Discussion This study investigated the prevalence of cholera and the antibiotic resistance patterns of Vibrio cholerae isolates from three major referral hospitals in Zambia’s Copperbelt Province. The findings revealed an overall cholera prevalence of 37.4%, with significant variations across hospitals. Ndola Teaching Hospital recorded the highest number of confirmed cases (24.8%), followed by Kitwe Teaching Hospital (9.9%), while Arthur Davison Children’s Hospital reported the lowest prevalence (2.8%). High levels of AMR were observed, particularly in ampicillin (98.6%), co-trimoxazole (96.8%), and imipenem (91.5%). In contrast, erythromycin (100%), ceftriaxone (96%), and gentamicin (85.7%) remained highly effective. Alarmingly, MDR was detected in 33.7% of isolates, with resistance to four or more antibiotics being the most prevalent profile (14.6%). The prevalence of confirmed Vibrio cholerae cases in this study (37.4%) is consistent with findings from similar settings. For example, Chiyangi et al. (2017), reported a prevalence of 40.8% in Lusaka, Zambia [ 18 ], while William et al. (2020), documented a prevalence of 38% in the Democratic Republic of Congo [ 19 ]. Similarly, Bitew et al. (2024) reported a slightly lower prevalence of 30.1% in Ethiopia [ 12 ], which still falls within a comparable range. However, our prevalence was notably higher than the 20.6% reported by Kerketta et al. (2025) in Odisha, India [ 20 ]. These variations may be attributed to differences in study populations, geographical and environmental factors, and public health infrastructure. For instance, the high prevalence in the Copperbelt Province may reflect the region’s poor sanitation, overcrowding, and limited access to clean water, which facilitate cholera transmission. The high resistance rates observed in this study align with global trends of increasing AMR in Vibrio cholerae . For example, Kerketta et al. (2025) reported 100% resistance to ceftazidime and imipenem in India [ 20 ], consistent with our findings of 54.1% and 91.5% resistance, respectively. Similarly, Bitew (2024) documented 70% resistance to cefotaxime and 56.8% to ampicillin in Ethiopia [ 12 ], mirroring our results of 31.8% and 98.6% resistance. These findings underscore the growing threat of AMR in cholera treatment, particularly in resource-limited settings like Zambia, where access to alternative antibiotics is often constrained. However, there are notable differences in resistance patterns across regions. For instance, Chiyangi et al. (2017) reported lower resistance levels to erythromycin (32.4%), ciprofloxacin (26.5%), and chloramphenicol (8.8%) in Lusaka, Zambia [ 18 ], compared to our findings of 100% susceptibility to erythromycin, 76.6% susceptibility to ciprofloxacin, and 67.7% resistance to chloramphenicol. Ceftriaxone also showed high susceptibility (96%), followed by cefuroxime (81.8%) and gentamicin (85.7%), suggesting their continued reliability. Ciprofloxacin and tetracycline, both commonly used in cholera treatment, maintained moderate susceptibility rates of 76.6% and 74.2%, respectively. These findings align with those of Chiyangi et al. (2017), who reported 100% susceptibility of V. cholerae isolates to ampicillin, cefotaxime, and gentamicin, further reinforcing their potential as effective treatment options [ 18 ]. Additionally, Chiyangi et al. found that 94.1% of strains were susceptible to tetracycline, with 5.9% showing intermediate resistance, which is slightly higher than the 74.2% susceptibility observed in our study. Furthermore, the study aligns with Bitew’s (2024) findings that most of the isolates were susceptible to ciprofloxacin, chloramphenicol, tetracycline and gentamicin. The continued effectiveness of these antibiotics emphasizes their role in cholera treatment; however, ongoing surveillance is essential to monitor emerging resistance trends and guide appropriate therapeutic strategies [ 12 ]. The overall MDR rate of 33.7% in this study is notably higher than the 6.45% reported by Gupta et al. (2016) in Nepal [ 13 ] but lower than the 64.5% documented by Shah et al. (2023) in Kenya [ 21 ]. These variations may be attributed to differences in study design, sample sizes, and the availability of antibiotics in different regions. For example, the high MDR rate in Kenya may reflect the widespread use of antibiotics in both clinical and community settings, while the lower rate in Nepal may be linked to stricter antibiotic regulations and more effective public health interventions [ 13 , 21 ]. In the Copperbelt Province, the high MDR rate underscores the urgent need for enhanced antimicrobial stewardship programs to regulate antibiotic use and prevent the further spread of resistant strains. The sustained efficacy of erythromycin and ceftriaxone suggests that these antibiotics should be prioritized as first-line treatments for cholera in the Copperbelt Province. However, the high MDR rate highlights the urgent need for enhanced antimicrobial stewardship programs to regulate antibiotic use and prevent further resistance. Public health interventions should also focus on improving WASH infrastructure to reduce cholera transmission and the spread of resistant strains. This study has several limitations that should be acknowledged. First, the hospital-based design may not fully capture community-wide cholera cases, potentially underestimating the true burden of the disease. Second, the absence of whole-genome sequencing (WGS) limits our understanding of the genetic mechanisms driving resistance, which is critical for developing targeted interventions. Third, the cross-sectional design restricts the ability to analyse long-term trends in AMR. Finally, the small number of cases for certain antibiotics may have limited the statistical power to detect significant differences in resistance patterns. To the best of our knowledge, the current study provides the first localized AMR data on Vibrio cholerae in the Copperbelt Province, offering critical epidemiological insights into cholera prevalence and resistance patterns in the region. Despite the limitations highlighted, the current study provides localized data on cholera prevalence and AMR patterns in the Copperbelt Province, offering critical insights for public health interventions. Future research should focus on longitudinal studies to monitor resistance trends over time, community-based studies to capture a broader range of cases, and the use of WGS to identify resistance genes and inform targeted interventions. Conclusion This study highlights the increasing prevalence of multidrug-resistant Vibrio cholerae in Zambia’s Copperbelt Province, posing a serious threat to effective cholera treatment. The persistence of resistance to first-line antibiotics calls for urgent updates to treatment protocols and strengthened AMR surveillance. Given Zambia’s recurrent cholera outbreaks, enhanced surveillance, antimicrobial stewardship, and improved WASH initiatives are essential for reducing the disease burden and preventing future outbreaks. Abbreviations AMR – Antimicrobial Resistance APW – Alkaline Peptone water AST – Antimicrobial susceptibility testing ATCC – American Type Culture Collection BA – Blood agar CLSI – Clinical Laboratory Standards Institute EUCAST - European Committee on Antimicrobial Susceptibility Testing LIA – Lysine Iron Agar MAC – MacConkey agar MDR – Multidrug resistance SIM – Sulphur, Indole, Motility TCBS – Thiosulfate Citrate Bile Salts Sucrose TSI – Triple Sugar Iron WASH – Water, Sanitation and hygiene WGS – whole-genome sequencing QC – Quality control Declarations Ethics approval and consent to participate. Ethical approval for this study was obtained from the Mulungushi University School of Medicine and Health Sciences Research Committee Board (IRB: 00012281, FWA: 0002888; Reference No. SMHS-MU1-2025-28) and the National Health Research Authority, Zambia (NHRA8108/25/02/2025) on February 25, 2025. Written informed consent was waived due to the retrospective nature of the study and the minimal risk posed to participants. To ensure confidentiality, patient information was anonymized, and all data were encrypted using encryption within the data collection and analysis tool. Access to the data was strictly restricted to the study authors through password-protected systems minimizing the risk of unauthorized access or disclosure. Clinical Trial number Not applicable (N/A) Consent for publication Not Applicable Availability of data and material The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors have no conflicts of interest to declare. Funding Not applicable Authors' contributions DC conceived the study. JN, RM, and NC collected the data. DC analysed the data and wrote the manuscript. AC, EC, NC, MC, and MC reviewed the manuscript. All authors read and approved the final version. Acknowledgements We thank the laboratory personnel and staff at Arthur Davison Children’s Hospital, Kitwe Teaching Hospital, and Ndola Teaching Hospital for their invaluable support during this work. We also acknowledge Mulungushi University School of Medicine and Health Sciences and the National Health Research Authority (NHRA) of Zambia for their institutional and ethical support. References Chowdhury F, Ross AG, Islam MT, McMillan NAJ, Qadri F. Diagnosis, Management, and Future Control of Cholera. Clin Microbiol Rev [Internet]. 2022;35. 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Prevalence and diversity of enteric pathogens among cholera treatment centre patients with acute diarrhea in Uvira, Democratic Republic of Congo. BMC Infect Dis. 2020;20:741. Kerketta S, Rout UK, Kshatri JS, Kerketta AS, Paikaray AK, Dash A, et al. An acute diarrheal disease outbreak in urban setting of Odisha, India. BMC Infect Dis. 2025;25:283. Shah MM, Bundi M, Kathiiko C, Guyo S, Galata A, Miringu G, et al. Antibiotic-Resistant Vibrio cholerae O1 and Its SXT Elements Associated with Two Cholera Epidemics in Kenya in 2007 to 2010 and 2015 to 2016. Weil AA, editor. Microbiol Spectr. 2023;11:e04140-22. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Jul, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Revision requested 16 Apr, 2025 Reviews received at journal 07 Apr, 2025 Reviewers agreed at journal 01 Apr, 2025 Reviewers agreed at journal 01 Apr, 2025 Reviews received at journal 27 Mar, 2025 Reviewers agreed at journal 27 Mar, 2025 Reviewers invited by journal 27 Mar, 2025 Editor assigned by journal 23 Mar, 2025 Submission checks completed at journal 23 Mar, 2025 First submitted to journal 20 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6266244","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":439803298,"identity":"cc442ec3-964c-4abd-95ce-d8f357a90efc","order_by":0,"name":"David Chisompola","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYDCCAwxsDAlgFnMDwwcgxcZOvBbGBsYZIC3MxGhhgGph5gHbRkAH3wHmZw8e/LGJNmdvbPxs82ubPB8zA+OHjzm4tUgeYDM3SGxLy93Zc7BZOrfvtmEbMwOz5MxtuLUYHOBhk0hsOJy74UZig3Ruz21GoBY2Zl5CWhL+gLU0/7bsuW1PpBY2sJY2aYYftxMJapE8zGYmAfVLm2Vvw+3kNmbGZrx+4Tve/Ezyxx+b3O3szYdv/Phz23Z+e/PBDx/xaIHHggGIYGwDkw141CN7Ckz+IU7xKBgFo2AUjCwAALFtVB8kziUyAAAAAElFTkSuQmCC","orcid":"","institution":"Arthur Davison Children’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"David","middleName":"","lastName":"Chisompola","suffix":""},{"id":439803299,"identity":"c012a8f5-1b72-4426-aa83-23a4eb24eba0","order_by":1,"name":"John Nzobokela","email":"","orcid":"","institution":"Ndola Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Nzobokela","suffix":""},{"id":439803301,"identity":"0d4e587b-9c54-44b8-b4ee-68f83c604942","order_by":2,"name":"Roy Moono","email":"","orcid":"","institution":"Arthur Davison Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Roy","middleName":"","lastName":"Moono","suffix":""},{"id":439803302,"identity":"27c45245-1a26-4524-aaea-76e576b2e9fd","order_by":3,"name":"Elijah Chinyante","email":"","orcid":"","institution":"Ndola Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Elijah","middleName":"","lastName":"Chinyante","suffix":""},{"id":439803303,"identity":"7a047b08-c5d5-4e0e-be1a-3b8d460587eb","order_by":4,"name":"Allen Chipipa","email":"","orcid":"","institution":"Ndola Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Allen","middleName":"","lastName":"Chipipa","suffix":""},{"id":439803305,"identity":"674b48a1-50ca-4d98-9990-d0c8791d5dd0","order_by":5,"name":"Nancy Chapuswike","email":"","orcid":"","institution":"Kitwe Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Nancy","middleName":"","lastName":"Chapuswike","suffix":""},{"id":439803308,"identity":"d0b05297-34e3-447b-a2fc-65ff21d65ace","order_by":6,"name":"Moses Chakopo","email":"","orcid":"","institution":"Arthur Davison Children’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Moses","middleName":"","lastName":"Chakopo","suffix":""},{"id":439803310,"identity":"fb73b5bc-86ee-41b0-bf37-8b69847413ba","order_by":7,"name":"Nswana Mukuma","email":"","orcid":"","institution":"Provincial Health Office","correspondingAuthor":false,"prefix":"","firstName":"Nswana","middleName":"","lastName":"Mukuma","suffix":""},{"id":439803311,"identity":"57368cec-e8e7-4489-95b1-992e5b27af73","order_by":8,"name":"Martin Chakulya","email":"","orcid":"","institution":"Mulungushi University School of Medicine and Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Chakulya","suffix":""}],"badges":[],"createdAt":"2025-03-20 05:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6266244/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6266244/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-025-11259-w","type":"published","date":"2025-07-01T15:56:54+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80709286,"identity":"e47c818c-9dbc-4fe7-a342-587af9b1daa7","added_by":"auto","created_at":"2025-04-16 08:54:34","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":41219,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eParticipant selection\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6266244/v1/c50127e7bc36afa73fe47f97.jpg"},{"id":80709288,"identity":"d18afec6-8ea5-4e43-acda-71e095a54ef8","added_by":"auto","created_at":"2025-04-16 08:54:34","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35051,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of Confirmed Cholera Cases\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6266244/v1/da18e70970ddb9a8a1559fc8.jpg"},{"id":86178851,"identity":"32dbc709-3aab-4a6b-932e-f29d92b0dabc","added_by":"auto","created_at":"2025-07-07 16:00:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":843894,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6266244/v1/d3d33ac9-8227-4318-9954-f8a1c3bc41b7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Emerging Antibiotic Resistance in Vibrio cholerae: A Study of Cholera Prevalence and Resistance Patterns in Zambia's Copperbelt Province","fulltext":[{"header":"Background","content":"\u003cp\u003eCholera is a severe diarrheal disease caused by the bacterium \u003cem\u003eVibrio cholerae\u003c/em\u003e, typically spread through contaminated water. It remains a significant public health challenge, particularly in regions with inadequate water, sanitation and hygiene (WASH) infrastructure [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The disease is typically spread through contaminated water and food, and its impact is most severe in low-resource settings, where overcrowding and poor sanitation exacerbate transmission [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In 2023, Sub-Saharan Africa experienced the 7th cholera pandemic, with reported cases rising to 535,321 and 4,007 deaths from 472,697 in 2022. Globally, cholera cases were reported in 45 countries in 2023, an increase from 44 in 2022 and 35 in 2021. While Africa saw a 125% surge in cases, the Middle East and Asia experienced a 32% decline [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Alarmingly, 60% of annual cholera-related deaths occur in Sub-Saharan Africa, underscoring the region's vulnerability to this disease [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eZambia, like many countries in Sub-Saharan Africa, has faced recurrent cholera outbreaks since 1977, with endemic transmission in regions such as Lusaka, Luapula, and the Copperbelt Province [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The Copperbelt Province, a densely populated and rapidly urbanizing area, is particularly susceptible to cholera due to its inadequate sanitation infrastructure, limited access to clean water, and high population mobility [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The 2024 cholera outbreak in Zambia was the most severe to date, with 19,719 cases and 682 deaths reported nationwide [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, localized data on cholera prevalence and antibiotic resistance patterns in the Copperbelt Province remain scarce, hindering the development of targeted public health strategies.\u003c/p\u003e \u003cp\u003eThe global emergence of antimicrobial resistance (AMR) has further complicated cholera management, with \u003cem\u003eVibrio cholerae\u003c/em\u003e strains showing increasing resistance to commonly used antibiotics, such as tetracycline, chloramphenicol, and ciprofloxacin [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This resistance threatens the effectiveness of current treatment protocols, particularly in resource-limited settings like Zambia, where access to alternative antibiotics is often constrained [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. While studies have documented varying resistance patterns in other regions of Zambia and neighbouring countries [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], there is a critical lack of data on the antibiotic resistance profiles of \u003cem\u003eV. cholerae\u003c/em\u003e strains circulating in the Copperbelt Province. This knowledge gap limits the ability to design effective treatment guidelines and underscores the need for localized surveillance.\u003c/p\u003e \u003cp\u003eThis study addresses these gaps by determining the prevalence of cholera and the antibiotic resistance patterns of \u003cem\u003eV. cholerae\u003c/em\u003e strains in three major referral hospitals in the Copperbelt Province. By integrating epidemiological and microbiological data, this research seeks to provide critical insights into the local dynamics of cholera transmission and resistance, informing more effective public health interventions and treatment strategies. The findings of this study will contribute to the growing body of knowledge on AMR in \u003cem\u003eV. cholerae\u003c/em\u003e and support efforts to combat cholera in Zambia and beyond.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design, Site and Population\u003c/h2\u003e \u003cp\u003eThis was a hospital-based, retrospective cross-sectional study conducted at three tertiary hospitals in the Copperbelt Province: Arthur Davison Children's Hospital, Kitwe Teaching Hospital, and Ndola Teaching Hospital. These hospitals were selected due to their high patient volume during the cholera outbreak and their ISO 15189:2022-accredited laboratories, ensuring standardized diagnostic procedures. The study analysed clinical samples collected between January and April 2024, during the peak of the cholera outbreak in Zambia.\u003c/p\u003e \u003cp\u003eThe study population consisted of clinical samples sent to microbiology laboratories from patients suspected of having cholera infection, indicated by acute watery diarrhoea. The sampling frame included all \u003cem\u003eVibrio\u003c/em\u003e species detected during the study period. Both inpatients and outpatients with recorded demographic data, including age, sex, stool culture results, and antimicrobial susceptibility test (AST) results, were included in the study. Samples missing key variables such as age, sex, stool culture results, or AST results were excluded from the analysis. A total of 892 suspected cholera cases were included, providing sufficient statistical power to detect significant trends in resistance patterns based on similar studies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The flowchart illustrating the study selection process is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \n\u003ch3\u003eSpecimen processing\u003c/h3\u003e\n\u003cp\u003eRectal swabs or stool samples were collected from suspected cholera cases using Cary Blair transport medium or clean stool containers and transported to the microbiology laboratory for processing [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A portion of each stool sample or rectal swab was directly inoculated and cultured onto Blood Agar (BA), MacConkey (MAC) and Thiosulfate-Citrate-Bile Salts-Sucrose (TCBS). The culture plates were incubated at 35\u0026deg;C-37\u0026deg;C for 18\u0026ndash;24 hours. Secondly, samples were enriched in alkaline peptone water (APW) for 4\u0026ndash;6 hours, followed by subculturing onto BA, MAC, and TCBS agar within the same incubation period [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn TCBS agar, suspected \u003cem\u003eVibrio cholerae\u003c/em\u003e colonies appeared as shiny yellow colonies due to sucrose fermentation. Suspected \u003cem\u003eV. cholerae\u003c/em\u003e colonies were further sub-cultured on non-selective agar-Mueller Hinton for further confirmatory tests. Gram staining and a series of biochemical tests, including the oxidase test, were conducted to identify \u003cem\u003eVibrio\u003c/em\u003e species. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Oxidase-positive colonies were further identified using several biochemical tests: Triple Sugar Iron (TSI) agar, Lysine Iron Agar (LIA), Sulphur Indole Motility (SIM) test, and the Citrate test. Additionally, serotyping was performed with antisera (Deben Diagnostics Ltd) to differentiate between \u003cem\u003eVibrio cholerae O1\u003c/em\u003e or \u003cem\u003eO139\u003c/em\u003e, as well as serotyping for \u003cem\u003eOgawa\u003c/em\u003e or \u003cem\u003eInaba\u003c/em\u003e strains. A culture result was classified as positive when \u003cem\u003eVibrio cholerae O1\u003c/em\u003e or \u003cem\u003e139\u003c/em\u003e was isolated from stool samples. Conversely, a result was deemed negative if \u003cem\u003eV. cholerae\u003c/em\u003e was not detected or if a non-O1/non-O139 strain of \u003cem\u003eV. cholerae\u003c/em\u003e was isolated [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eAntimicrobial Susceptibility Testing\u003c/h3\u003e\n\u003cp\u003eThe antibiotic resistance profile of \u003cem\u003eV. cholerae\u003c/em\u003e isolates was assessed using the Kirby-Bauer disk diffusion method on Mueller-Hinton agar, following Clinical Laboratory Standards Institute (CLSI) and European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The antibiotics tested were selected based on their common use in cholera treatment and availability in the study laboratories. These included: ampicillin (10 \u0026micro;g), cotrimoxazole (trimethoprim/sulfamethoxazole) (1.25/23.75 \u0026micro;g), cefotaxime (30 \u0026micro;g), ceftazidime (30 \u0026micro;g), chloramphenicol (30 \u0026micro;g), ciprofloxacin (5 \u0026micro;g), ceftriaxone (30 \u0026micro;g), erythromycin (15 \u0026micro;g), and tetracycline (30 \u0026micro;g). Susceptibility testing was conducted by determining the minimum inhibitory concentration using the agar dilution method [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Clinical breakpoints for susceptibility testing were determined according to CLSI (M45) and EUCAST guidelines for \u003cem\u003eVibrio cholerae\u003c/em\u003e [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The interpretation of AST results was based on the zone of inhibition, categorized as susceptible, intermediate, or resistant. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eQuality Control for AST\u003c/h3\u003e\n\u003cp\u003eRoutine quality control (QC) measures were implemented in each batch of AST to ensure accuracy, precision, and reliability. This included the use of control strains, \u003cem\u003eEscherichia coli\u003c/em\u003e American type culture collection (ATCC) 25922 and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e ATCC 27853, to validate the performance of media, reagents, and equipment [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This was performed to maintain consistency and compliance with established standards, following guidelines from CLSI [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eData collection and analysis\u003c/h3\u003e\n\u003cp\u003eClinical and laboratory data were carefully reviewed for accuracy before being entered into a structured Microsoft Excel spreadsheet designed as a data collection tool. Data were extracted from the Laboratory Information System and microbiology registers to ensure completeness and reliability. To ensure consistency and validity, data were randomly checked and cross-matched by two independent reviewers. Discrepancies were resolved through discussion and re-examination of the original records.\u003c/p\u003e \u003cp\u003eStatistical analysis was conducted using SPSS version 26. Descriptive statistics, including medians and proportions, were used to summarize the data and determine \u003cem\u003eVibrio cholerae\u003c/em\u003e prevalence and the distribution of study covariates. Missing data were handled through list-wise deletion, and sensitivity analyses were conducted to assess the impact of missing data on the results. Chi-square tests were used to compare resistance patterns across hospitals, with a p-value of \u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Cholera in the Copperbelt Province\u003c/h2\u003e \u003cp\u003eDuring the study period, a total of 892 suspected cholera cases were reported across the three major referral hospitals in the Copperbelt Province. Of these, \u003cem\u003eVibrio cholerae\u003c/em\u003e was confirmed through culture in 334 cases, yielding an overall prevalence of 37.4%. Among the three hospitals, Ndola Teaching Hospital recorded the highest number of confirmed cases (n\u0026thinsp;=\u0026thinsp;221, 24.8%), followed by Kitwe Teaching Hospital (n\u0026thinsp;=\u0026thinsp;88, 9.9%), while Arthur Davison Children\u0026rsquo;s Hospital reported the lowest prevalence (n\u0026thinsp;=\u0026thinsp;25, 2.8%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The age distribution revealed that the highest proportion of cases (n\u0026thinsp;=\u0026thinsp;80, 26.1%) occurred among individuals aged 30\u0026ndash;39 years, while the lowest (n\u0026thinsp;=\u0026thinsp;14, 4.6%) was observed in those aged 70 years and above. The male-to-female ratio was 1.09:1, indicating a slightly higher number of male cases, with a median age of 31 years.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAntimicrobial Resistance Patterns of\u003c/b\u003e \u003cb\u003eVibrio Cholerae\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe antibiotic susceptibility testing of \u003cem\u003eVibrio cholerae\u003c/em\u003e isolates demonstrated high resistance to several commonly used antibiotics, with high resistance observed for ampicillin (98.6%, n\u0026thinsp;=\u0026thinsp;136), co-trimoxazole (96.8%, n\u0026thinsp;=\u0026thinsp;90), imipenem (91.5%, n\u0026thinsp;=\u0026thinsp;43), chloramphenicol (67.7%, n\u0026thinsp;=\u0026thinsp;21), ceftazidime (54.1%, n\u0026thinsp;=\u0026thinsp;59), ciprofloxacin (23.4%, n\u0026thinsp;=\u0026thinsp;36), and tetracycline (25.8%, n\u0026thinsp;=\u0026thinsp;25), rendering these drugs ineffective for cholera treatment (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast to the high resistance observed for several antibiotics, certain drugs demonstrated strong efficacy against \u003cem\u003eVibrio cholerae\u003c/em\u003e isolates. Erythromycin (100%, n\u0026thinsp;=\u0026thinsp;24), ceftriaxone (96%, n\u0026thinsp;=\u0026thinsp;24), gentamicin (85.7%, n\u0026thinsp;=\u0026thinsp;6), cefuroxime (81.8%, n\u0026thinsp;=\u0026thinsp;9), ciprofloxacin (76.6%, n\u0026thinsp;=\u0026thinsp;118) and tetracycline (74.2%, n\u0026thinsp;=\u0026thinsp;72) and, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAntimicrobial Resistance Patterns of \u003cem\u003eVibrio cholerae\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntimicrobial Agent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDisk Content (\u0026micro;g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSusceptible (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResistant (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-Resistance Antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e136 (98.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e90 (96.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImipenem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43 (91.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate-Resistance Antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChloramphenicol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21 (67.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCeftazidime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50 (45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59 (54.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-Resistance Antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCiprofloxacin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e118 (76.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36 (23.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72 (74.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25 (25.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-Susceptibility Antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCeftriaxone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (96.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (4.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGentamicin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (85.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (14.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCefuroxime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (18.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u0026micro;g: Microgram, %: Percentage\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMultidrug Resistance Patterns\u003c/h3\u003e\n\u003cp\u003eMultidrug resistance (MDR), defined as resistance to three or more antibiotic classes, was detected in 33.7% (83/246) of the isolates. The most prevalent MDR profile involved resistance to four or more antibiotics (n\u0026thinsp;=\u0026thinsp;36, 14.6%), followed by resistance to Ampicillin-Ceftazidime-Co-trimoxazole (n\u0026thinsp;=\u0026thinsp;10, 4.1%), Ampicillin-Co-trimoxazole-Imipenem (n\u0026thinsp;=\u0026thinsp;5, 2%), and Ampicillin-Amikacin-Co-trimoxazole (n\u0026thinsp;=\u0026thinsp;5, 2%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultidrug Resistance Patterns in \u003cem\u003eVibrio cholerae\u003c/em\u003e Isolates\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultidrug Resistance Profile\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResistance to 4 or more antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmpicillin\u0026thinsp;+\u0026thinsp;Ceftazidime\u0026thinsp;+\u0026thinsp;Co-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmpicillin\u0026thinsp;+\u0026thinsp;Co-trimoxazole\u0026thinsp;+\u0026thinsp;Imipenem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmpicillin\u0026thinsp;+\u0026thinsp;Amikacin\u0026thinsp;+\u0026thinsp;Co-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther combinations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e83\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e33.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the prevalence of cholera and the antibiotic resistance patterns of \u003cem\u003eVibrio cholerae\u003c/em\u003e isolates from three major referral hospitals in Zambia\u0026rsquo;s Copperbelt Province. The findings revealed an overall cholera prevalence of 37.4%, with significant variations across hospitals. Ndola Teaching Hospital recorded the highest number of confirmed cases (24.8%), followed by Kitwe Teaching Hospital (9.9%), while Arthur Davison Children\u0026rsquo;s Hospital reported the lowest prevalence (2.8%). High levels of AMR were observed, particularly in ampicillin (98.6%), co-trimoxazole (96.8%), and imipenem (91.5%). In contrast, erythromycin (100%), ceftriaxone (96%), and gentamicin (85.7%) remained highly effective. Alarmingly, MDR was detected in 33.7% of isolates, with resistance to four or more antibiotics being the most prevalent profile (14.6%).\u003c/p\u003e \u003cp\u003eThe prevalence of confirmed \u003cem\u003eVibrio cholerae\u003c/em\u003e cases in this study (37.4%) is consistent with findings from similar settings. For example, Chiyangi et al. (2017), reported a prevalence of 40.8% in Lusaka, Zambia [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], while William et al. (2020), documented a prevalence of 38% in the Democratic Republic of Congo [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Similarly, Bitew et al. (2024) reported a slightly lower prevalence of 30.1% in Ethiopia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], which still falls within a comparable range. However, our prevalence was notably higher than the 20.6% reported by Kerketta et al. (2025) in Odisha, India [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. These variations may be attributed to differences in study populations, geographical and environmental factors, and public health infrastructure. For instance, the high prevalence in the Copperbelt Province may reflect the region\u0026rsquo;s poor sanitation, overcrowding, and limited access to clean water, which facilitate cholera transmission.\u003c/p\u003e \u003cp\u003eThe high resistance rates observed in this study align with global trends of increasing AMR in \u003cem\u003eVibrio cholerae\u003c/em\u003e. For example, Kerketta et al. (2025) reported 100% resistance to ceftazidime and imipenem in India [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], consistent with our findings of 54.1% and 91.5% resistance, respectively. Similarly, Bitew (2024) documented 70% resistance to cefotaxime and 56.8% to ampicillin in Ethiopia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], mirroring our results of 31.8% and 98.6% resistance. These findings underscore the growing threat of AMR in cholera treatment, particularly in resource-limited settings like Zambia, where access to alternative antibiotics is often constrained.\u003c/p\u003e \u003cp\u003eHowever, there are notable differences in resistance patterns across regions. For instance, Chiyangi et al. (2017) reported lower resistance levels to erythromycin (32.4%), ciprofloxacin (26.5%), and chloramphenicol (8.8%) in Lusaka, Zambia [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], compared to our findings of 100% susceptibility to erythromycin, 76.6% susceptibility to ciprofloxacin, and 67.7% resistance to chloramphenicol. Ceftriaxone also showed high susceptibility (96%), followed by cefuroxime (81.8%) and gentamicin (85.7%), suggesting their continued reliability. Ciprofloxacin and tetracycline, both commonly used in cholera treatment, maintained moderate susceptibility rates of 76.6% and 74.2%, respectively. These findings align with those of Chiyangi et al. (2017), who reported 100% susceptibility of \u003cem\u003eV. cholerae\u003c/em\u003e isolates to ampicillin, cefotaxime, and gentamicin, further reinforcing their potential as effective treatment options [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Additionally, Chiyangi et al. found that 94.1% of strains were susceptible to tetracycline, with 5.9% showing intermediate resistance, which is slightly higher than the 74.2% susceptibility observed in our study. Furthermore, the study aligns with Bitew\u0026rsquo;s (2024) findings that most of the isolates were susceptible to ciprofloxacin, chloramphenicol, tetracycline and gentamicin. The continued effectiveness of these antibiotics emphasizes their role in cholera treatment; however, ongoing surveillance is essential to monitor emerging resistance trends and guide appropriate therapeutic strategies [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe overall MDR rate of 33.7% in this study is notably higher than the 6.45% reported by Gupta et al. (2016) in Nepal [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] but lower than the 64.5% documented by Shah et al. (2023) in Kenya [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. These variations may be attributed to differences in study design, sample sizes, and the availability of antibiotics in different regions. For example, the high MDR rate in Kenya may reflect the widespread use of antibiotics in both clinical and community settings, while the lower rate in Nepal may be linked to stricter antibiotic regulations and more effective public health interventions [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In the Copperbelt Province, the high MDR rate underscores the urgent need for enhanced antimicrobial stewardship programs to regulate antibiotic use and prevent the further spread of resistant strains.\u003c/p\u003e \u003cp\u003eThe sustained efficacy of erythromycin and ceftriaxone suggests that these antibiotics should be prioritized as first-line treatments for cholera in the Copperbelt Province. However, the high MDR rate highlights the urgent need for enhanced antimicrobial stewardship programs to regulate antibiotic use and prevent further resistance. Public health interventions should also focus on improving WASH infrastructure to reduce cholera transmission and the spread of resistant strains.\u003c/p\u003e \u003cp\u003eThis study has several limitations that should be acknowledged. First, the hospital-based design may not fully capture community-wide cholera cases, potentially underestimating the true burden of the disease. Second, the absence of whole-genome sequencing (WGS) limits our understanding of the genetic mechanisms driving resistance, which is critical for developing targeted interventions. Third, the cross-sectional design restricts the ability to analyse long-term trends in AMR. Finally, the small number of cases for certain antibiotics may have limited the statistical power to detect significant differences in resistance patterns.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, the current study provides the first localized AMR data on Vibrio cholerae in the Copperbelt Province, offering critical epidemiological insights into cholera prevalence and resistance patterns in the region. Despite the limitations highlighted, the current study provides localized data on cholera prevalence and AMR patterns in the Copperbelt Province, offering critical insights for public health interventions. Future research should focus on longitudinal studies to monitor resistance trends over time, community-based studies to capture a broader range of cases, and the use of WGS to identify resistance genes and inform targeted interventions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the increasing prevalence of multidrug-resistant \u003cem\u003eVibrio cholerae\u003c/em\u003e in Zambia\u0026rsquo;s Copperbelt Province, posing a serious threat to effective cholera treatment. The persistence of resistance to first-line antibiotics calls for urgent updates to treatment protocols and strengthened AMR surveillance. Given Zambia\u0026rsquo;s recurrent cholera outbreaks, enhanced surveillance, antimicrobial stewardship, and improved WASH initiatives are essential for reducing the disease burden and preventing future outbreaks.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAMR \u0026ndash; Antimicrobial Resistance\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAPW \u0026ndash; Alkaline Peptone water\u003c/p\u003e\n\u003cp\u003eAST \u0026ndash; Antimicrobial susceptibility testing\u003c/p\u003e\n\u003cp\u003eATCC \u0026ndash; American Type Culture Collection\u003c/p\u003e\n\u003cp\u003eBA \u0026ndash; Blood agar\u003c/p\u003e\n\u003cp\u003eCLSI \u0026ndash; Clinical Laboratory Standards Institute\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEUCAST - European Committee on Antimicrobial Susceptibility Testing\u003c/p\u003e\n\u003cp\u003eLIA \u0026ndash; Lysine Iron Agar\u003c/p\u003e\n\u003cp\u003eMAC \u0026ndash; MacConkey agar\u003c/p\u003e\n\u003cp\u003eMDR \u0026ndash; Multidrug resistance\u003c/p\u003e\n\u003cp\u003eSIM \u0026ndash; Sulphur, Indole, Motility\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTCBS \u0026ndash; Thiosulfate Citrate Bile Salts Sucrose\u003c/p\u003e\n\u003cp\u003eTSI \u0026ndash; Triple Sugar Iron\u003c/p\u003e\n\u003cp\u003eWASH \u0026ndash; Water, Sanitation and hygiene\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWGS \u0026ndash; whole-genome sequencing\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQC \u0026ndash; Quality control\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Mulungushi University School of Medicine and Health Sciences Research Committee Board (IRB: 00012281, FWA: 0002888; Reference No. SMHS-MU1-2025-28) and the National Health Research Authority, Zambia (NHRA8108/25/02/2025) on February 25, 2025. Written informed consent was waived due to the retrospective nature of the study and the minimal risk posed to participants. To ensure confidentiality, patient information was anonymized, and all data were encrypted using encryption within the data collection and analysis tool. Access to the data was strictly restricted to the study authors through password-protected systems minimizing the risk of unauthorized access or disclosure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable (N/A)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDC conceived the study. JN, RM, and NC collected the data. DC analysed the data and wrote the manuscript. AC, EC, NC, MC, and MC reviewed the manuscript. All authors read and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the laboratory personnel and staff at Arthur Davison Children\u0026rsquo;s Hospital, Kitwe Teaching Hospital, and Ndola Teaching Hospital for their invaluable support during this work. We also acknowledge Mulungushi University School of Medicine and Health Sciences and the National Health Research Authority (NHRA) of Zambia for their institutional and ethical support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChowdhury F, Ross AG, Islam MT, McMillan NAJ, Qadri F. Diagnosis, Management, and Future Control of Cholera. Clin Microbiol Rev [Internet]. 2022;35. Available from: https://journals.asm.org/doi/10.1128/cmr.00211-21\u003c/li\u003e\n\u003cli\u003eMusa SS, Ezie KN, Scott GY, Shallangwa MM, Ibrahim AM, Olajide TN, et al. The challenges of addressing the cholera outbreak in Cameroon. Public Health Pract. 2022;4:100295. \u003c/li\u003e\n\u003cli\u003eWHO. Data show marked increase in annual cholera deaths. World Health Organ WHOn. 2024;481\u0026ndash;95. \u003c/li\u003e\n\u003cli\u003eMwaba J, Debes AK, Shea P, Mukonka V, Chewe O, Chisenga C, et al. Identification of cholera hotspots in Zambia: A spatiotemporal analysis of cholera data from 2008 to 2017. Akullian A, editor. PLoS Negl Trop Dis. 2020;14:e0008227. \u003c/li\u003e\n\u003cli\u003eGething PW, Ayling S, Mugabi J, Muximpua OD, Kagulura SS, Joseph G. Cholera risk in Lusaka: A geospatial analysis to inform improved water and sanitation provision. Jeuland M, editor. PLOS Water. 2023;2:e0000163. \u003c/li\u003e\n\u003cli\u003eGulumbe BH, Chishimba K, Shehu A, Chibwe M. Zambia\u0026rsquo;s battle against cholera outbreaks and the path to public health resilience: a narrative review. J Water Health. 2024;22:2257\u0026ndash;75. \u003c/li\u003e\n\u003cli\u003eMinistry of Health Zambia. National Daily Cholera Update. 2024 Feb 21 [cited 2025 Mar 11]; Available from: https://www.facebook.com/share/p/18ZZbsGwja/\u003c/li\u003e\n\u003cli\u003eDas B, Verma J, Kumar P, Ghosh A, Ramamurthy T. Antibiotic resistance in Vibrio cholerae: Understanding the ecology of resistance genes and mechanisms. Vaccine. 2020;38:A83\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003ePhiri TM, Imamura T, Mwansa PC, Mathews I, Mtine F, Chanda J, et al. Increased Prevalence of Antimicrobial Resistance in Vibrio cholerae in the Capital and Provincial Areas of Zambia, January 2023\u0026ndash;February 2024. Am J Trop Med Hyg. 2025;tpmd240558. \u003c/li\u003e\n\u003cli\u003eShah MM, Bundi M, Kathiiko C, Guyo S, Galata A, Miringu G, et al. Antibiotic-Resistant Vibrio cholerae O1 and Its SXT Elements Associated with Two Cholera Epidemics in Kenya in 2007 to 2010 and 2015 to 2016. Weil AA, editor. Microbiol Spectr. 2023;11:e04140-22. \u003c/li\u003e\n\u003cli\u003eRamamurthy T, Das B, Chakraborty S, Mukhopadhyay AK, Sack DA. Diagnostic techniques for rapid detection of Vibrio cholerae O1/O139. Cholera Control Three Cont Vaccines Antibiot WASH. 2020;38:A73\u0026ndash;82. \u003c/li\u003e\n\u003cli\u003eBitew A, Gelaw A, Wondimeneh Y, Ayenew Z, Getie M, Tafere W, et al. Prevalence and antimicrobial susceptibility pattern of Vibrio cholerae isolates from cholera outbreak sites in Ethiopia. BMC Public Health. 2024;24:2071. \u003c/li\u003e\n\u003cli\u003eGupta PK, Pant ND, Bhandari R, Shrestha P. Cholera outbreak caused by drug resistant Vibrio cholerae serogroup O1 biotype ElTor serotype Ogawa in Nepal; a cross-sectional study. Antimicrob Resist Infect Control. 2016;5:23. \u003c/li\u003e\n\u003cli\u003eAbana D, Gyamfi E, Dogbe M, Opoku G, Opare D, Boateng G, et al. Investigating the virulence genes and antibiotic susceptibility patterns of Vibrio cholerae O1 in environmental and clinical isolates in Accra, Ghana. BMC Infect Dis. 2019;19:76. \u003c/li\u003e\n\u003cli\u003eKaratuna O, Matuschek E, \u0026Aring;hman J, Caidi H, Kahlmeter G. \u003cem\u003eVibrio\u003c/em\u003e species: development of EUCAST susceptibility testing methods and MIC and zone diameter distributions on which to determine clinical breakpoints. J Antimicrob Chemother. 2024;79:375\u0026ndash;82. \u003c/li\u003e\n\u003cli\u003eClinical and Laboratory Standards Institute (CLSI). M45 Methods for Antimicrobial Dilution and Disk Susceptibility Testing of Infrequently Isolated or Fastidious Bacteria. 3rd ed. Wayne, PA; 2018. \u003c/li\u003e\n\u003cli\u003eParvin I, Shahunja KM, Khan SH, Alam T, Shahrin L, Ackhter MstM, et al. Changing Susceptibility Pattern of Vibrio cholerae O1 Isolates to Commonly Used Antibiotics in the Largest Diarrheal Disease Hospital in Bangladesh during 2000\u0026ndash;2018. Am J Trop Med Hyg. 2020;103:652\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eChiyangi H, Muma JB, Malama S, Manyahi J, Abade A, Kwenda G, et al. Identification and antimicrobial resistance patterns of bacterial enteropathogens from children aged 0\u0026ndash;59 months at the University Teaching Hospital, Lusaka, Zambia: a prospective cross sectional study. BMC Infect Dis. 2017;17:117. \u003c/li\u003e\n\u003cli\u003eWilliams C, Cumming O, Grignard L, Rumedeka BB, Saidi JM, Grint D, et al. Prevalence and diversity of enteric pathogens among cholera treatment centre patients with acute diarrhea in Uvira, Democratic Republic of Congo. BMC Infect Dis. 2020;20:741. \u003c/li\u003e\n\u003cli\u003eKerketta S, Rout UK, Kshatri JS, Kerketta AS, Paikaray AK, Dash A, et al. An acute diarrheal disease outbreak in urban setting of Odisha, India. BMC Infect Dis. 2025;25:283. \u003c/li\u003e\n\u003cli\u003eShah MM, Bundi M, Kathiiko C, Guyo S, Galata A, Miringu G, et al. Antibiotic-Resistant Vibrio cholerae O1 and Its SXT Elements Associated with Two Cholera Epidemics in Kenya in 2007 to 2010 and 2015 to 2016. Weil AA, editor. Microbiol Spectr. 2023;11:e04140-22. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Antimicrobial stewardship, cholera, multidrug resistance, Vibrio cholerae, Zambia","lastPublishedDoi":"10.21203/rs.3.rs-6266244/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6266244/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction\u003c/h2\u003e \u003cp\u003eCholera is a severe diarrheal disease caused by the bacterium \u003cem\u003eVibrio cholerae\u003c/em\u003e, typically spread through contaminated water. Cholera remains a significant public health challenge in Zambia, particularly in the Copperbelt Province, where antibiotic-resistant \u003cem\u003eVibrio cholerae\u003c/em\u003e strains are increasingly threatening treatment efficacy. This study aimed to determine the prevalence of cholera and the antibiotic resistance patterns of \u003cem\u003eVibrio cholerae\u003c/em\u003e isolates at three tertiary hospitals in the region.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective cross-sectional study was conducted across three major referral hospitals in the Copperbelt Province (Arthur Davison Children's Hospital, Kitwe Teaching Hospital, and Ndola Teaching Hospital) during the cholera outbreak from January to April 2024. Clinical samples from suspected cholera cases were analysed, and antimicrobial susceptibility testing followed Clinical Laboratory Standards Institute guidelines and the European Committee on Antimicrobial Susceptibility Testing methodology for \u003cem\u003eVibrio cholerae.\u003c/em\u003e To isolate \u003cem\u003eVibrio cholerae\u003c/em\u003e, alkaline peptone water and thiosulfate-citrate-bile salt-sucrose agar were utilized. The isolates were identified based on colony morphology, Gram staining, biochemical testing, and serotyping. Antimicrobial susceptibility testing was conducted by determining the minimum inhibitory concentration using the agar dilution method. Descriptive statistics were employed to assess the prevalence of \u003cem\u003eVibrio cholerae\u003c/em\u003e, and chi-square tests were applied with p-values of \u0026lt;\u0026thinsp;0.05 indicating statistical significance.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 892 suspected cases, 334 (37.4%) were confirmed as \u003cem\u003eV. cholerae\u003c/em\u003e through culture. The highest number of \u003cem\u003eV. cholerae\u003c/em\u003e confirmed cases was recorded at Ndola Teaching Hospital (24.8%), followed by Kitwe Teaching Hospital (9.9%), while Arthur Davison Children\u0026rsquo;s Hospital (2.8%) reported the lowest. High antimicrobial resistance was observed to ampicillin (98.6%), co-trimoxazole (96.8%) and imipenem (91.5%). In contrast, erythromycin (100%), ceftriaxone (96%) and gentamicin (85.7%) remained highly effective. The most common multidrug-resistant \u003cem\u003eV. cholerae\u003c/em\u003e profile showed resistance to four or more antibiotics (14.6%). This was followed by resistance to the combination of ampicillin, ceftazidime, and co-trimoxazole (4.1%) and ampicillin, co-trimoxazole, and imipenem (2%).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe high prevalence of antibiotic-resistant \u003cem\u003eV. cholerae\u003c/em\u003e in the Copperbelt Province highlights the urgent need for enhanced antimicrobial stewardship and surveillance programs to guide cholera treatment. The sustained efficacy of erythromycin and ceftriaxone suggests their potential as first-line treatments, but ongoing resistance monitoring is crucial.\u003c/p\u003e","manuscriptTitle":"Emerging Antibiotic Resistance in Vibrio cholerae: A Study of Cholera Prevalence and Resistance Patterns in Zambia's Copperbelt Province","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-16 08:54:29","doi":"10.21203/rs.3.rs-6266244/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-16T17:07:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-08T01:58:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258583067384106832125345748333558341500","date":"2025-04-01T09:41:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58039290991402194816454555140932325761","date":"2025-04-01T09:06:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-27T13:11:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82189724416361868336382168178776282711","date":"2025-03-27T07:46:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-27T07:01:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-24T03:13:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-24T03:13:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-03-20T05:20:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b2db0d8d-9952-48f3-86f0-04e409c2118b","owner":[],"postedDate":"April 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-07T15:59:11+00:00","versionOfRecord":{"articleIdentity":"rs-6266244","link":"https://doi.org/10.1186/s12879-025-11259-w","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2025-07-01 15:56:54","publishedOnDateReadable":"July 1st, 2025"},"versionCreatedAt":"2025-04-16 08:54:29","video":"","vorDoi":"10.1186/s12879-025-11259-w","vorDoiUrl":"https://doi.org/10.1186/s12879-025-11259-w","workflowStages":[]},"version":"v1","identity":"rs-6266244","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6266244","identity":"rs-6266244","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}