Antibiotic use patterns and AWaRe classification in district hospitals of the North West Region of Cameroon: a cross-sectional study

¹Department of Public Health, Faculty of Health Sciences, the University of Bamenda, P.O. Box 39, Bambili, Bamenda, Cameroon, ²Department of Biomedical Sciences, the University of Bamenda, PO Box 39, Bambili, Bamenda, Cameroon, ³Department of Medical Laboratory Sciences, the University of Bamenda, PO Box 39, Bambili, Bamenda, Cameroon

^&Corresponding author
Bertrand Ngwa Sangwe, Department of Public Health, Faculty of Health Sciences, the University of Bamenda, P.O. Box 39, Bambili, Bamenda, Cameroon

Introduction    

Antimicrobial resistance(AMR) is one of the most complex global health problems today, which threatens the effective treatment of bacterial infections, leading to significant morbidity and mortality globally [1,2]. This global health problem jeopardizes the success of critical medical procedures such as cancer chemotherapy, organ transplantation, and major surgeries because these interventions rely on effective antibiotics to prevent and treat associated infections [1]. Multiple factors across human health, animal health, and environmental sectors drive the development and rapid spread of AMR. Central to this problem is the misuse and overuse of antibiotics, which create strong selective pressures that enable bacteria to develop resistance mechanisms, rendering many existing drugs ineffective [2]. This growing antimicrobial resistance complicates the management of routine infections and threatens to reverse decades of medical progress. The World Health Organization (WHO) projects a devastating future if effective measures are not implemented promptly, estimating that AMR could result in over 10 million deaths annually by 2050, with sub-Saharan Africa bearing a disproportionate burden owing to existing healthcare challenges and resource constraints[3,4].

In response to this escalating global health threat, the WHO has emphasized the importance of routine and systematic monitoring of antibiotic use as part of global antimicrobial stewardship efforts [5,6]. Such surveillance enables the identification of inappropriate prescribing patterns and informs targeted interventions to optimize antibiotic use in clinical settings. A key tool in this endeavour is the WHO AWaRe (Access, Watch, Reserve) classification system, which categorizes antibiotics based on their potential to develop resistance and clinical importance. This system guides healthcare providers in selecting appropriate antibiotics, thereby reducing unnecessary exposure to broad-spectrum agents and slowing the emergence of resistance [7,8]. WHO has established a target for at least 60% of national antibiotic consumption worldwide to be derived from the WHO Access group of antibiotics. Building on this, the United Nations General Assembly (UNGA) on AMR in 2024 adopted a global target that by 2030, at least 70% of antibiotic prescriptions should come from the WHO Access group [7,9,10].

The AWaRe guideline advocates for the use of antibiotics from the Access group, which remain the preferred choice for treating most infections. According to the AWaRe guideline, the majority of infections encountered in primary health care can be effectively treated with either no antibiotics or Access antibiotics [6,11,12]. However, there has been a global rise in the use of Watch antibiotics, which are now often prescribed for minor infections in primary health care settings where Access antibiotics will suffice. This pattern is particularly pronounced in Low and middle-income countries (LMICs), where their overall use remains substantial [6,12,13]. In resource-constrained environments such as Cameroon, the prescription and administration of antibiotics are primarily informed by empirical evidence. Given the significant knowledge gap regarding antibiotic prescription patterns in Cameroon, which is crucial for monitoring antibiotic use [14,15], this study seeks to determine antibiotic use patterns in district hospitals in the North West Region of Cameroon, in order to inform antimicrobial stewardship strategies and contribute to global efforts to optimize antibiotic use.

Methods     

Study design and setting: this was a retrospective, cross-sectional study conducted in six randomly selected district hospitals in the North West Region of Cameroon. These were Benakuma, Nkwen, Ndop, Santa, Tubah, and Wum district hospitals. These healthcare facilities serve as the primary reference centres for the surrounding urban and rural populations.

Study population and data sources: the North West Region has a total of 20 health districts and 17 district hospitals, with a total population of about two million (2,000,000) inhabitants [16,17]. To ensure representation across different levels of geographic accessibility to the regional referral hospital, district hospitals were stratified into two groups according to their proximity to the Bamenda Regional Hospital. Hospitals located nearer to the regional hospital and hospitals located farther from the regional hospital. Using a stratified random sampling approach, six district hospitals were selected, comprising three hospitals from each stratum (Nkwen, Santa, and Tubah district hospitals from the proximal stratum and Benakuma, Ndop, and Wum district hospitals from the distal stratum). The study population comprised consultation records from selected district hospitals. Retrospective antibiotic prescription data were extracted from hospital consultation registers for the year 2024.

Sample size and sampling procedure: the determination of the number of records to be screened was guided by WHO's recommendations for studies evaluating current treatment practices, which advise the inclusion of a minimum of 600 patient encounters in a cross-sectional study [18]. A target of 700 consultation records from each district hospital was systematically screened for antibiotics prescribed. Consultation records from each consultation register were arranged chronologically. The number of records to be screened from each consultation register within each facility was allocated proportionally using the formula:

Where t represented the number of records to be screened for a consultation register, n represented the number of consultation records in that register, N represented the total number of consultation records in all consultation registers in the facility, and 700 represented the target number of records to be reviewed per facility [19]. This approach follows the principle of proportional allocation, whereby the number of records selected (t) from each register reflects its proportion of the facility’s total consultation records [19]. The sampling interval (k) was calculated as k=n/t, where k represented the sampling interval, n represented the total number of consultation records in a particular register, and t represented the number of records to be selected from that register. A random starting point (r) was generated for each consultation register, as a whole number between 1 and k, inclusive. The records were then systematically screened to identify antibiotics prescribed using the sequence r, r + k, r + 2k, r + 3k, and so forth [19]. Where calculated record positions were not whole numbers, they were rounded up to the next whole number to identify the corresponding consultation records. This process continued until the allocated sample size for each register was reached [19]. Consultation records constituted the sampling units, while antibiotics prescribed were the units of analysis.

Data analysis: data were cleaned using Microsoft Excel. Each antibiotic was classified according WHO AWaRe categories (access, watch, reserve) and assigned to it respective pharmacological class using the WHO AWaRe 2023 guideline [12]. The data were subsequently imported into SPSS version 25 for analysis. Descriptive statistics were used to analyse antibiotic prescription patterns.

Ethical considerations: ethical clearance was obtained from the Institutional Review Board of the University of Bamenda, reference number 2025/0003H/UBa/IRB. In addition, administrative authorization to access hospital records was obtained from the North West Regional Delegation of Public Health (566/ATT/NWRRDPH/BRIGAD). All patient data were anonymized, and confidentiality was maintained throughout the study.

Results     

Antibiotic prescribing patterns by drug and class: a total of 3,817 antibiotics were prescribed from consultation records screened. The most prescribed antibiotic in this study was metronidazole (18.50%), followed by cefixime (12.21%). Other commonly prescribed antibiotics included ceftriaxone (9.72%), amoxicillin (8.99%), amoxicillin and clavulanic acid combination (7.26%), ciprofloxacin (6.05%), ofloxacin (5.55%), and azithromycin (5.48%). Several other antibiotics were prescribed less frequently, each accounting for less than 5% of the total antibiotics. The percentages were calculated using the total number of prescribed antibiotics (N = 3,817) as the denominator. Table 1 shows all the antibiotic types prescribed and their frequency. The antibiotics were grouped into pharmacological classes as follows: third-generation cephalosporins included cefixime, ceftriaxone, and cefotaxime; imidazoles included metronidazole and ornidazole; penicillins included amoxicillin, ampicillin, cloxacillin, benzathine-benzylpenicillin, and flucloxacillin; fluoroquinolones included ciprofloxacin, ofloxacin, levofloxacin, and norfloxacin; macrolides included azithromycin, clarithromycin, erythromycin, and spiramycin; β-lactam/β-lactamase inhibitor included amoxicillin/clavulanic acid; aminoglycosides included gentamicin and neomycin; tetracyclines included doxycycline, tetracycline, and minocycline; sulfonamide and trimethoprim combinations included sulfamethoxazole/trimethoprim; nitrofuran derivatives included nitrofurantoin; rifamycins included rifampicin; lincosamides included lincomycin; glycopeptides included vancomycin; and first-generation cephalosporins included cephalexin.

Third-generation cephalosporins were the most frequently prescribed pharmacological class, accounting for 23.26% of all antibiotics prescribed. This was followed by imidazoles, which represented 21.09%. Other commonly prescribed classes included penicillins (17.08%), fluoroquinolones (13.41%), macrolides (8.99%), and beta-lactam/beta-lactamase inhibitor combinations (7.26%). Less frequently prescribed antibiotic classes included aminoglycosides (4.03%), tetracyclines (3.04%), and sulfonamide and trimethoprim combinations (1.39%), while other antibiotic classes, such as nitrofurans (0.29%), rifamycins (0.08%), lincosamides (0.03%), glycopeptides and first generation cephalosporins (0.03%) were rarely prescribed. Table 2 shows the frequency of prescription of the different pharmacological classes of antibiotics.

Antibiotic use according to the WHO AWaRe classification: among the 3,817 antibiotics prescribed from consultation records screened. Access antibiotics constituted 54.15% (2,067), while Watch antibiotics comprised 45.85% (1,750) of the total antibiotics. No Reserve antibiotics were prescribed during the study period. The pattern of prescribed antibiotics according to the WHO AWaRe category is presented in Table 3.

Discussion     

Antibiotic prescribing patterns by drug and class: the antibiotic prescribing pattern observed in this study highlights several important trends relevant to antimicrobial stewardship and clinical practice. Metronidazole was the most commonly prescribed individual antibiotic, which is comparable to findings from similar studies from Tanzania [20,21] but differs from reports of other studies from Zambia and China, where Ceftriaxone and Amoxicillin were respectively the most prescribed antibiotics, though metronidazole was among the top 5 antibiotics prescribed in these studies [6,22]. The preference for Metronidazole compared to other antibiotics may be due to it broad-spectrum activity against anaerobic bacteria and protozoan infections and its use as first-line treatment for most common infections. In addition, other factors such as cost and wide availability compared to other antibiotics may have contributed as well to the frequent use of this antibiotic at the level of the district hospitals [23,24]. This high dependence on metronidazole suggests a tendency toward empirical treatment without microbiological confirmation. Further analysis revealed that third-generation cephalosporins were the most prescribed class of antibiotics, comprising 23.26% of all antibiotics prescribed. This finding aligns with data from the Democratic Republic of Congo [2], but contrasts with studies from Cameroon, Ethiopia, and Uganda, where penicillin was identified as the most frequently prescribed antibiotic class [25-27]. The high use of third-generation cephalosporins may be attributed to their broad-spectrum activity against both Gram-negative and gram-positive bacteria, making them a preferred drug for empirical therapy in settings with limited diagnostic capacities. The widespread availability of this class of antibiotics, low cost compared to combining narrow-spectrum antibiotics, and the familiarity of clinicians with these antibiotics may have contributed to their frequent prescription compared to the other antibiotic classes. However, the extensive use of third-generation cephalosporins raises concerns about the risk of bacteria becoming resistant to antibiotics in this class of antibiotics.

Antibiotic use according to the WHO AWaRe classification: the distribution of antibiotics according to the WHO AWaRe classification reveals that over half (54.15%) of the antibiotics prescribed belonged to the Access category. This finding is less than the 60% national target recommended by WHO and the recent global target of at least 70% Access antibiotic use adopted during the United Nations General Assembly (UNGA) on AMR. Access antibiotics are recommended as first-line treatments for the most common infections and have a lower resistance potential compared to antibiotics from the Watch and Reserve categories [12]. However, the substantial proportion of Watch antibiotics (45.85%) prescribed in this study indicates a significant use of agents with higher resistance risks. We observed that 2 watch antibiotics ranked among the top 3 most prescribed antibiotics. The absence of WHO Reserve antibiotics observed in this study may be associated with limited availability of these antibiotics at the district level or with adherence to prescription guidelines, which recommend that Reserve antibiotics should only be prescribed as a last resort for the treatment of multidrug-resistant infections [12]. In addition, critically ill patients or patients who are not responsive to treatment at the level of district hospitals may be referred to regional hospitals for treatment, which may contribute to no Reserve antibiotics being prescribed. However, these factors were not directly evaluated in the present study and should therefore be interpreted as potential explanations rather than definitive conclusions.

This trend in antibiotic prescription is consistent with similar studies from Ethiopia (54.4%), Tanzania (50.9%), Uganda (59.6%), and Zambia (48%), where the prescription of Access antibiotics were below both the WHO national target of at least 60% and the newly adopted global target of at least 70% (established in 2024 at the UNGA on AMR) [7,20,25,26,28]. This highlights room for improvement in antibiotic prescription practices. Other studies, such as those from Pakistan (25.7%), Sierra Leone (28.2%), and Sudan (29.0%), reported even lower rates of antibiotic prescription from the Access group, with about 70% of antibiotic prescriptions coming from the Watch group of antibiotics [7,29,30]. These findings emphasize the need to continuously improve antibiotic prescribing practices. Contrary to findings from our study, which did not meet the WHO national target, some studies from Ethiopia (67.87%) and Ghana (74%) met the WHO national target [31,32].

Limitations: the findings of this study should be interpreted in the context of certain limitations. Firstly, the study relied on retrospective patient consultation records, and the accuracy of the data could not be independently verified. Secondly, results were aggregated across the participating district hospitals, and hospital-specific findings were not presented. This approach was adopted to preserve the confidentiality of healthcare providers and facilities, particularly in hospitals with a very small number of prescribers, where reporting facility-level results could have enabled the identification of individual prescribers. Thirdly, the study was restricted to antibiotic-level data. Consequently, encounter-level prescription indicators such as the overall antibiotic prescribing rate were not evaluated. Furthermore, information on prescriber cadre could not be obtained from the consultation registers. Finally, the use of consultation registers as the primary data source did not provide sufficient information on antibiotic dosage, frequency, and duration to permit the calculation of standardized antibiotic consumption metrics, such as defined daily dose (DDD).

Conclusion     

This study found that metronidazole and third-generation cephalosporins were the most commonly prescribed antibiotics and antibiotic class, respectively, suggesting a reliance on broad-spectrum empirical therapy in district hospitals in the North West Region of Cameroon. These prescribing patterns raise concerns about potential antimicrobial resistance and highlight the need to strengthen antimicrobial stewardship in this setting. The study also highlights significant patterns in antibiotic prescription within district hospitals in the North West Region of Cameroon. The study showed an antibiotic prescription pattern characterized by suboptimal use of Access antibiotics and considerable dependence on Watch antibiotics, reflecting patterns reported in other low- and middle-income countries. These findings highlight ongoing challenges in achieving the WHO AWaRe target of at least 60% Access antibiotic use, as well as the recently adopted global target of at least 70% Access antibiotic use adopted during the UNGA high-level meeting on AMR. Overall, our study provides critical insights into local antibiotic prescription behaviour in district hospitals. These findings can inform policies and targeted antimicrobial stewardship programmes aimed at promoting appropriate antibiotic use by improving adherence to treatment guidelines and reducing unnecessary use of Watch antibiotics.

Competing interests     

The authors declare no competing interests.

Authors' contributions     

Bertrand Ngwa Sangwe conceptualized and designed the study, supervised data collection, performed data analysis, and drafted the manuscript. Fanny Nadia Dissak Delon and Flore Nguemaïm Ngoufo contributed to the conceptualization and design of the study, supervised data collection, participated in data analysis and interpretation of study results, and critically reviewed the manuscript. All the authors have read and approved the final version of this manuscript.

Acknowledgments     

We thank the North West Regional Delegation of Public Health and the District Hospital Directors for granting us access to consultation registers. We also acknowledge the support of the healthcare workers of different study sites for their assistance during data collection.

Tables     

Table 1: frequency distribution of antibiotics prescribed in district hospitals in the North West Region of Cameroon, January-December 2024 (N = 3,817 antibiotics)

Table 2: frequency distribution of antibiotic pharmacological classes prescribed in district hospitals in the North West Region of Cameroon, January-December 2024 (N = 3,817 antibiotics)

Table 3: proportion of prescribed antibiotics by WHO AWaRe category in district hospitals in the North West Region of Cameroon, January-December 2024 (N = 3,817 antibiotics)

References