Skip to main content
Download PDF

First global report about the prevalence of multi-drug resistant Haemophilus influenzae: a systematic review and meta-analysis

BMC Infectious Diseases volume 24, Article number: 90 (2024) Cite this article

Abstract

Background

In recent decades, the prevalence of antibiotic resistance is increasing in Haemophilus influenzae (Haemophilus influenzae), which poses important challenges to global health. This research offers a comprehensive meta-analysis of the global epidemiology of multi-drug resistant (MDR) H. influenzae.

Methods

In this study, we conducted a meta-analysis based on PRISMA checklist. Electronic databases including PubMed, ISI Web of Science, Scopus, EMBASE, and Google Scholar were reviewed using keywords related to H. influenzae and antibiotic resistance. Eligible studies were selected based on stringent inclusion and exclusion criteria. Then, data from these studies were analyzed using the Comprehensive Meta-Analysis (CMA) software.

Results

Of 375 retrieved articles, 16 met the inclusion criteria. These studies were conducted from 2003 to 2023 and analyzed data from 19,787 clinical isolates of H. influenzae. The results showed different levels of resistance of H. influenzae to different antibiotics: ampicillin (36%), azithromycin (15.3%), ceftriaxone (1.4%), etc. The global prevalence for beta-lactamases producing H. influenzae and MDR H. influenzae was measured 34.9% and 23.1%, respectively. The prevalence rate of MDR H. influenzae was higher in Asian countries (24.6%) compared to Western regions (15.7%). MDR H. influenzae had the highest prevalence in meningitis cases (46.9%) and the lowest prevalence in acute otitis media (0.5%).

Conclusions

The prevalence of MDR H. influenzae has been increasing worldwide, especially in Asian regions. This highlights the urgent need for monitoring and implementation of effective antibiotic stewardship programs globally.

Peer Review reports

Background

The increase of antibiotic resistance in the era of modern medicine represents one of the most important challenges that the global health community is facing. At the center of this problem is the Haemophilus influenzae (H. influenzae) bacterium, which historically has been the leading cause of bacterial meningitis and other invasive conditions in pediatrics [1]. This Gram-negative coccobacillus presents with a variety of pathologies, causing conditions ranging from relatively benign otitis media to severe diseases such as septicemia [2]. Before to the advent of the H. influenzae type b (Hib) vaccine, the global burden of invasive Hib diseases was notably significant. Although this vaccine is advantageous in reducing the challenges caused by Hib, the apparent emergence of non-typeable H. influenzae (NTHi) strains has been implicated, particularly in respiratory pathologies [3, 4].

The presence of many challenges can lead to the acceleration of antibiotic resistance of this bacterium. The velocity and extent of antibiotic resistance, especially in bacterial species like H. influenzae are disconcertingly high [1, 5]. This intensification of resistance can be attributed to a combination of factors including, excessive use of antibiotics, self-administration of drugs, short treatment courses, and unrestricted antibiotic procurement in certain areas [6,7,8]. The implications of these actions are profound; the ineffectiveness of monotherapy leads to prolonged disease duration, increased health care costs, and increased mortality [9].

According to the registered reports, the phenomenon of antibiotic resistance in H. influenzae contains various pharmaceutical agents, from traditional drugs such as ampicillin and chloramphenicol to newer compounds like fluoroquinolones [10, 11]. The genetic basis of such resistance lies mainly in the absorption of resistance-causing genetic elements, which is facilitated through mechanisms such as conjugation and transformation. This evolving genetic perspective poses significant challenges to existing treatment strategies for clinicians, and complicates the treatment path for what was once a simple bacterial infection [12].

In the present meta-analysis we conducted a comprehensive study on the global antibiotic resistance of this bacterium, based on geographical distribution. We focused on MDR H. influenzae strains, which in turn highlights new antibiotic stewardship strategies against this pathogen in healthcare settings.

Methods

Search strategy

In the present study, we conducted a comprehensive systematic review and meta-analysis on the prevalence of multidrug-resistant H. influenzae worldwide, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist [13]. Major electronic databases, namely Medline, ISI Web of Science, Scopus, EMBASE, Google Scholar, and ProQuest were scoured. Aligned with the Medical Subject Headings (MeSH), Key terms such as “Haemophilus influenzae”, “H. influenzae”, “Antibiotic resistance”, “Multi-drug resistance”, and “MDR”, were integrated in this research. The search had no restrictions on language or date of publication. To ensure completeness, article citations were manually checked to identify any potentially overlooked studies.

Study selection according to the Clinical and Laboratory Standards Institute

In order to assess the eligibility of documents, all content of articles including title, abstract, and full text of relevant studies were evaluated. Inclusion criteria were: 1) original studies that investigated the prevalence of MDR H. influenzae in clinical samples; 2) articles related to H. influenzae infection in human subjects; 3) retrospective as well as cross-sectional studies; 4) articles that evaluated antimicrobial/antibiotic susceptibility testing (AST) according to the Clinical and Laboratory Standards Institute (CLSI) guideline. Our exclusion criteria were as follows: 1) duplicate studies; 2) article types (e.g. letters to the editor, case reports, reviews, and congress abstracts); 3) animal studies; 4) studies with insufficient information. Two independent authors participated in this step and discrepancies were resolved through discussion.

Quality appraisal and data extraction

The Joanna Briggs Institute (JBI) checklist was used to assess the quality assessment of relevant studies [14]. In this context, studies were included if they achieved at least 6 scores. Next, the required information was extracted from eligible studies, including: I) first author, II) publication year, III) country, IV) infection type, V) number of H. influenzae isolates, VI) prevalence of antibiotic resistance to ampicillin, amoxicillin, tetracycline, chloramphenicol, cefotaxime, ciprofloxacin, rifampin, sulfamethoxazole, cefuroxime, azithromycin, cefotaxime, ceftriaxone, levofloxacin, meropenem, VII) prevalence of beta-lactamase strains, VIII) prevalence of MDR H. influenzae, as well as IX) diagnostic method. Two independent authors were involved in the process, and discordance was determined by a third author.

Statistical analysis

Data were synthesized using the Comprehensive Meta-Analysis (CMA) software, version 2.2 (Biostat, Englewood, NJ). The Cochrane Q-test (p < 0.05) and the I-squared (I2) index were used to measure the heterogeneity of studies. In case of significant heterogeneity, random-effects model based on the DerSimonian and Laird approach was applied. In addition, meta-regression techniques were used to investigate the impact of potential moderators. Publication bias was evaluated through the Egger’s p value test, Begg’s p value test, and funnel plot. If significant publication bias was detected, the trim-fill method was used to estimate any potential missing studies.

Results

Literature search

Overall, 375 pertinent documents were retrieved from database searches (Fig. 1). After initial evaluation of titles and abstracts, 209 articles were excluded. The main reasons for removing duplicates were included: non-original researches, animal-based studies, and the absence of reports on MDR H. influenzae. A comprehensive evaluation of the full text of 83 papers was then performed for potential inclusion. Upon further scrutiny, and supplemented by manual bibliographic searches, a total of 16 studies met the criteria for inclusion in our systematic review and meta-analysis. The data of these studies are summarized in Table 1 [1, 10, 11, 15,16,17,18,19,20,21,22,23,24,25,26,27].

Fig. 1
figure 1

Flow-diagram of study selection process

Full size image
Table 1 Characteristics of included studies
Full size table

Characteristics of included studies

These investigations focused on the prevalence of MDR H. influenzae in different regions: Spain (n = 3), Portugal (n = 1), China (n = 5), Taiwan (n = 2), Bangladesh (n = 1), Iran (n = 1), Japan (n = 1), Ethiopia (n = 1), and Australia (n = 1). The time range of these studies covers from 2003 to 2023. The methods used in the studies included the evaluation of antibiotic susceptibility of clinical isolates of H. influenzae; for example disc diffusion, E-test, and broth dilution techniques. These clinical species of H. influenzae were isolated from a wide range of disorders including invasive infections, meningitis, acute otitis media (AOM), and acute respiratory infections. Cumulatively, in our analysis, we incorporated data from 19,787 H. influenzae clinical isolates, which encompassed both Hib and non-Hib serotypes. It is noteworthy that two studies exclusively assessed the AST of the Hib serotype infections [16, 19]. Of the total H. influenzae isolates, approximately 46.8 ± 8.9% were identified as Hib strain.

Characteristics of H. influenzae antibiotic resistance

In this meta-analysis, the antibiotic resistance trends of H. influenzae were determined as follows: amoxicillin, 6.3% (95% CI: 2.5–15; I2: 84.33; p = 0.01; Egger’s p = 0.01; Begg’s p = 0.02), ampicillin, 36% (95% CI: 25.6–48; I2: 94.38; p = 0.01; Egger’s p = 0.01; Begg’s p = 0.01), azithromycin, 15.3% (95% CI: 6.7–31.1; I2: 89.28; p = 0.01; Egger’s p = 0.03; Begg’s p = 0.05), ceftriaxone, 1.4% (95% CI: 0.2–10.2; I2: 73.91; p = 0.01; Egger’s p = 0.1; Begg’s p = 0.4), cefotaxime, 3.6% (95% CI: 1.3–9.5; I2: 80.17; p = 0.01; Egger’s p = 0.03; Begg’s p = 0.1), cefuroxime, 19.1% (95% CI: 9.7–34.0; I2: 91.14; p = 0.01; Egger’s p = 0.03; Begg’s p = 0.01), chloramphenicol, 17.2% (95% CI: 10.3–27.1; I2: 90.59; p = 0.01; Egger’s p = 0.1; Begg’s p = 0.01), ciprofloxacin, 1.7% (95% CI: 0.3–8.8; I2: 88.27; p = 0.01; Egger’s p = 0.01; Begg’s p = 0.5), levofloxacin, 7.5% (95% CI: 1.9–25.5; I2: 90.78; p = 0.01; Egger’s p = 0.09; Begg’s p = 0.3), meropenem, 4.3% (95% CI: 0.6–26.0; I2: 92.77; p = 0.01; Egger’s p = 0.07; Begg’s p = 0.5), rifampin, 8.9% (95% CI: 2.5–27.2; I2: 92.31; p = 0.01; Egger’s p = 0.01; Begg’s p = 0.3), sulfamethoxazole, 45.6% (95% CI: 34.9–56.7; I2: 92.39; p = 0.01; Egger’s p = 0.2; Begg’s p = 0.3), and tetracycline, 19.9% (95% CI: 8.3–40.4; I2: 95.3; p = 0.01; Egger’s p = 0.08; Begg’s p = 0.1).

Characteristics of MDR H. influenzae

The global prevalence of beta-lactamases producing H. influenzae and MDR H. influenzae was established at 34.9% (95% CI: 24.0-47.7; I2: 93.56; p = 0.01; Egger’s p = 0.01; Begg’s p = 0.01) and 23.1% (95% CI: 14.7–34.4; I2: 93.9; p = 0.01; Egger’s p = 0.04; Begg’s p = 0.01), respectively (Fig. 2). Furthermore, our data revealed an increasing trend in the prevalence of beta-lactamases producing H. influenzae, from 22.1% (95% CI: 10.4–40.9) during 2003–2007 to 48.1% (95% CI: 35.5–61.0), a more than twofold increase, during 2019–2023. In contrast, the trend for MDR H. influenzae has remained stable over the past two decades. Specifically, the pooled prevalence rates of MDR H. influenzae were 22.8% (95% CI: 13.0-36.8), 20.8% (95% CI: 16.5–25.9), and 27.8% (95% CI: 11.8–52.5), during 2003–2007, 2008–2012, and 2019–2023, respectively.

Fig. 2
figure 2

Forest plot of meta-analysis on the prevalence of beta-lactamases producing H. influenzae and multidrug resistant H. influenzae

Full size image

After analyzing the geographical distribution, it was found that the prevalence of MDR H. influenzae in Asian countries was significantly higher than in Western regions, with rates of 24.6% (95% CI: 12.9–41.8) and 15.7% (95% CI: 6.7–32.6), respectively. When the study was classified according to the type of infection, the incidence of MDR H. influenzae was most pronounced in cases of meningitis with 46.9% (95% CI: 40.1–53.9) and the lowest prevalence was related to cases of AOM with 0.5% (95% CI: 0.0-7.4). The overall prevalence of MDR H. influenzae for invasive infections was 24.1% (95% CI: 12.0-42.5), while for acute respiratory infections it was 18.2% (95% CI: 6.6–41.1).

In addition, a meta-regression analysis was performed to examine the potential effects of several moderating factors including, publication year, methodology, geographical latitude, and type of infection, on the pooled estimates. The results showed that the year of publication had a discernible impact on the aggregated estimates pertaining to MDR H. influenzae infection, as described in Table 2.

Table 2 Meta-regression analysis of moderator variables influencing the overall estimates regarding prevalence of MDR H. influenzae
Full size table

Publication bias

In the present meta-analysis, potential publication bias was carefully assessed using both Begg’s and Egger’s p value tests. Moreover, any observed asymmetry in the funnel plot was interpreted as indicating significant publication bias. Collective evidence from these methods confirms the presence of publication bias in the studies included in this analysis. Notwithstanding this, the trim-fill method was used to rectify and stabilize the overall effect estimates. The results after applying the trim-fill method further bolstered the strength of the pooled estimates (Fig. 3).

Fig. 3
figure 3

Funnel plot depicting publication bias of studies reporting the prevalence MDR H. influenzae

Full size image

Discussion

Our meta-analysis sheds light on the complex global patterns of MDR H. influenzae outbreaks. To the best of our knowledge, this is the first global meta-analysis on the prevalence of MDR H. influenzae. One of the notable observations is the high prevalence of this bacterium in Asian countries (24.6%) compared to Western regions (15.7%). This notable difference can be caused by both internal and external factors in the healthcare system. Previous research on the H. influenzae infection in Taiwan identified the presence of extensively drug-resistant (XDR) H. influenzae strains as early as 2007, and documented the consistent drug resistance status maintained by these strains [1]. Also, another study that focused on antibiotic susceptibility in Africa from 1978 to 2011 was consistent with our findings; emphasizing the non-susceptibility of H. influenzae isolates to several useful antibiotics; according to their statistics, the rate of non-susceptibility to erythromycin, trimethoprim/sulfamethoxazole, tetracycline, ampicillin (or penicillin) was measured as 69.8%, 48.1%, 37.5%, and 34.7%, respectively [28]. In addition, the results of resistance to several antibiotics in Africa such as ampicillin (34.7%), ceftriaxone (0.9%), cefotaxime (2.6%), and trimethoprim/sulfamethoxazole (48.1%) were almost similar to our results in the present meta-analysis. The number of isolates and the type of geographical region are considered as the two main reasons for the difference between the studies.

Some antibiotic-resistant bacteria such as sulfonamide-resistant Streptococcus pyogenes and penicillin-resistant Staphylococcus aureus, primarily have been linked to hospitals, places where we are faced with high consumption of antibiotics [29]. Such environments may serve as centers for the development and spread of drug resistance. Several factors, such as antibiotic prescribing habits, access to health care, and population density, all influence resistance patterns [30]. Notably, there is a significant variation in the prevalence of MDR H. influenzae among different infections. To illustrate, the occurrence of meningitis at 46.9% in contrast to AOM at 0.5% may be attributed to changes in bacterial pathogenicity, antibiotic utilization, laboratory diagnostic techniques, and host response. In essence, these factors collectively contribute to the observed difference in the incidence of meningitis and AOM [31].

Adding to the problem is that certain regions such as Asia and Central/Southern Europe have reported significantly lower incidence rates compared to other global regions. Interestingly, a stepwise logistic regression analysis from a study on 2091 H. influenzae isolates with disc diffusion-based AST elucidated specific demographic patterns, showing that male patients were less likely to harbor MDR H. influenzae strains [1]. Despite our focus on MDR H. influenzae, in many cases, antimicrobial prescriptions are made without knowledge of the causative organism. Vancomycin plus cefotaxime or ceftriaxone is the standard empirical antibiotic therapy for bacterial meningitis in children and newborns. On the other hand, azithromycin and clarithromycin are also alternative treatments in patients with AOM who have penicillin allergy [12, 32].

In our study, the prevalence of resistant H. influenzae to azithromycin was 15.3%. Given our initial concern about multi-drug resistance in H. influenzae, it is important to monitor changes in resistance patterns against a broader range of antibiotics. While the prevalence of invasive infections (24.1%) and acute respiratory infections (18.2%) is at steady state, it indicates a uniform degree of antibiotic resistance spread in these categories, which requires ‎equal attention. ‎After meningitis, childhood pneumonia and bacteremia are the most common diseases caused by Hib strains, and pneumonia is particularly dominant in developing countries [33]. The potential effect of seasonality on the prevalence of antimicrobial resistance is consistent. In a systematic review and meta-analysis by Martinez et al., they observed stable antimicrobial resistance rates in colder months for S. pneumoniae [34].

This observation aligns with our findings and suggest that respiratory infections, which are more common in colder seasons, maintain a consistent antibiotic resistance. In our meta-analysis, the global prevalence of beta-lactamases producing H. influenzae was established at 34.9%, which should be considered as a serious concern. This enzyme confers resistance against a variety of penicillin-based drugs by hydrolyzing their beta-lactam ring structure. Our findings are in line with a systematic review and meta-analysis operated by Mather et al., where resistance in Gram-negative bacteria, including H. influenzae, was frequently reported in terms of their ability to produce beta-lactamase enzymes [35]. Also, a particularly alarming observation from another study by Ginsburg et al. is the increasing trend of beta-lactamase production among Hib isolates, indicating a new concern for the African continent [28].

In addition, we showed that the prevalence of beta-lactamase producing H. influenzae is increasing, from 22.1% in 2007 − 2003 to 48.1% in 2023 − 2019. This surge emphasizes the heightened clinical reliance on beta-lactamases for treating H. ‎influenzae-mediated infections. Ceftriaxone, cefotaxime, or cefuroxime are also suggested for the treatment of pneumonia and bacteremia caused by beta-lactamase producing H. influenzae strains; on the other hand, ampicillin is suggested for beta-lactamase-negative strains [36]. Based on our results, the prevalence of resistance to ceftriaxone, cefotaxime, cefuroxime, and ampicillin was 1.4%, 4.1%, 19.1%, and 36%, respectively. In another meta-analysis conducted by Vaez et al., the prevalence of H. influenzae strains resistant to these antibiotics was estimated at 33.1%, 22.3%, 13.7%, and 54.8%, respectively [37].

Despite the modest increase in the pooled prevalence of both beta-lactamase producing H. ‎influenzae and MDR H. influenzae, it is clear that we stand on precarious ground.‎ It seems necessary to formulate and implement an antibiotic stewardship strategy to neutralize the emergence of XDR H. influenzae strains. Although the present study is comprehensive, it is not without limitations; the observed publication ‎bias, despite adjustments, may still affect the final pooled estimates. Furthermore, meta-analysis relies on published data, which may not represent unpublished studies or gray literature, potentially leading to over- or underestimation of true prevalence. In addition, inherent changes in the included studies in terms of methodology, sample size, and demographic distribution can cause heterogeneity in the results.

On the other hand, the strengths of this study lie in its expansive scope, detailed methodological approach, incorporation of a broad range of geographies, and infection types. We believe this study can offers a robust overview of the global landscape of MDR H. influenzae, serving as a pivotal resource for clinicians, researchers, and policymakers. Finally, while this meta-analysis offers pivotal insights into the prevalence of MDR H. influenzae across geographies and infection types, continued vigilance and updated research are essential to track, understand, and mitigate the spread of antibiotic resistance globally.

Conclusions

The global health community is facing a daunting challenge in the field of antibiotic resistance, with H. influenzae at the forefront. Our comprehensive meta-analysis shows an alarming increase in resistance, especially for beta-lactamase producing strains, which almost doubled from 2003 to 2023. Although the rate of MDR H. influenzae has remained relatively stable over the past two decades, its continued prevalence is particularly concerning in cases of meningitis. According to our results, it seems that there is a higher prevalence of MDR H. influenzae in Asian countries as compared to the Western countries. In general, therapeutic measures include implementation of stewardship programs, appropriate use of antibiotics, public awareness campaigns, and conducting new treatment research.

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

Abbreviations

H. influenzae :

Haemophilus influenzae

MDR:

Multidrug-resistant

MDR H. influenzae :

Multidrug-resistant H. influenzae

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

JBI:

Joanna Briggs Institute

CMA:

Comprehensive Meta-Analysis

CI:

Confidence interval

OR:

Odds ratio

References

  1. Su P-Y, Huang A-H, Lai C-H, Lin H-F, Lin T-M, Ho C-H. Extensively drug-resistant Haemophilus influenzae–emergence, epidemiology, risk factors, and regimen. BMC Microbiol. 2020;20(1):1–10.

    Article  Google Scholar 

  2. Dworkin MS, Park L, Borchardt SM. The changing epidemiology of invasive Haemophilus influenzae Disease, especially in persons⩾ 65 years old. Clin Infect Dis. 2007;44(6):810–6.

    Article  PubMed  Google Scholar 

  3. Gilsdorf JR. Hib vaccines: their impact on Haemophilus influenzae type b Disease. J Infect Dis. 2021;224(Supplement4):321–S330.

    Article  Google Scholar 

  4. Agrawal A, Murphy TF. Haemophilus influenzae Infections in the H. influenzae type b conjugate vaccine era. J Clin Microbiol. 2011;49(11):3728–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Kuo S-C, Chen P-C, Shiau Y-R, Wang H-Y, Jui-Fen Lai I, Huang W, et al. Levofloxacin-resistant haemophilus influenzae, Taiwan, 2004–2010. Emerg Infect Dis. 2014;20(8):1386.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Williams J, Moosdeen F. Antibiotic resistance in Haemophilus influenzae: epidemiology, mechanisms, and therapeutic possibilities. Rev Infect Dis. 1986;8(Supplement5):555–S561.

    Article  Google Scholar 

  7. Bae S, Lee J, Lee J, Kim E, Lee S, Yu J, et al. Antimicrobial resistance in Haemophilus influenzae respiratory tract isolates in Korea: results of a nationwide acute Respiratory Infections surveillance. Antimicrob Agents Chemother. 2010;54(1):65–71.

    Article  CAS  PubMed  Google Scholar 

  8. Abavisani M, Hoseinzadeh M, Khayami R, Kodori M, Soleimanpour S, Sahebkar A. Statins, allies against antibiotic resistance? Curr Med Chem. 2023. https://doi.org/10.2174/0929867331666230829141301.

    Article  PubMed  Google Scholar 

  9. Aslam B, Wang W, Arshad MI, Khurshid M, Muzammil S, Rasool MH, et al. Antibiotic resistance: a rundown of a global crisis. Infect Drug Resist. 2018;11:1645–58.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Yamada S, Seyama S, Wajima T, Yuzawa Y, Saito M, Tanaka E, et al. β-Lactamase-non-producing ampicillin-resistant Haemophilus influenzae is acquiring multidrug resistance. J Infect Public Health. 2020;13(4):497–501.

    Article  PubMed  Google Scholar 

  11. Chen D, Wen S, Feng D, Xu R, Liu J, Peters BM, et al. Microbial virulence, molecular epidemiology and pathogenic factors of fluoroquinolone-resistant Haemophilus influenzae Infections in Guangzhou, China. Ann Clin Microbiol Antimicrob. 2018;17(1):1–9.

    Article  Google Scholar 

  12. Tristram S, Jacobs MR, Appelbaum PC. Antimicrobial resistance in Haemophilus influenzae. Clin Microbiol Rev. 2007;20(2):368–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4(1):1–9.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Sterne JA, Egger M, Smith GD. Investigating and dealing with publication and other biases in meta-analysis. BMJ. 2001;323(7304):101–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Shen X, Lu Q, Deng L, Yu S, Zhang H, Deng Q, et al. Resistance of Haemophilus influenzae isolates in children under 5 years old with acute Respiratory Infections in China between 2000 and 2002. J Int Med Res. 2007;35(4):554–63.

    Article  CAS  PubMed  Google Scholar 

  16. Awulachew E, Diriba K, Awoke N. Bacterial isolates from CSF samples and their antimicrobial resistance patterns among children under five suspected to have Meningitis in Dilla University Referral Hospital. Infect Drug Resist. 2020;13:4193–202.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Pumarola F, Marès J, Losada I, Minguella I, Moraga F, Tarragó D, et al. Microbiology of bacteria causing recurrent acute otitis media (AOM) and AOM treatment failure in young children in Spain: shifting pathogens in the post-pneumococcal conjugate vaccination era. Int J Pediatr Otorhinolaryngol. 2013;77(8):1231–6.

    Article  PubMed  Google Scholar 

  18. Rahman M, Hossain S, Baqui AH, Shoma S, Rashid H, Nahar N, et al. Haemophilus influenzae type-b and non-b-type invasive Diseases in urban children (< 5 years) of Bangladesh: implications for therapy and vaccination. J Infect. 2008;56(3):191–6.

    Article  PubMed  Google Scholar 

  19. Tamargo I, Fuentes K, Llop A, Oteo J, Campos J. High levels of multiple antibiotic resistance among 938 Haemophilus influenzae type b Meningitis isolates from Cuba (1990–2002). J Antimicrob Chemother. 2003;52(4):695–8.

    Article  CAS  PubMed  Google Scholar 

  20. Campos J, Román F, Pérez-Vázquez M, Aracil B, Oteo J, Cercenado E. Antibiotic resistance and clinical significance of Haemophilus influenzae type f. J Antimicrob Chemother. 2003;52(6):961–6.

    Article  CAS  PubMed  Google Scholar 

  21. Bajanca P, Canica M. Emergence of nonencapsulated and encapsulated non-b-type invasive Haemophilus influenzae isolates in Portugal (1989–2001). J Clin Microbiol. 2004;42(2):807–10.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Zhou M, Fu P, Fang C, Shang S, Hua C, Jing C, et al. Antimicrobial resistance of Haemophilus influenzae isolates from pediatric hospitals in Mainland China: report from the ISPED program, 2017–2019. Indian J Med Microbiol. 2021;39(4):434–8.

    Article  CAS  PubMed  Google Scholar 

  23. Yuan M, Ma M, Jiang H, Fan M, Sun Y, Zhou B, et al. Characterization of serotypes and molecular drug resistance patterns of in Kunming Children. Pol J Microbiol. 2023;72(2):125–31.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Bowman-Derrick S, Harris TM, Beissbarth J, Kleinecke M, Lawrence K, Wozniak TM, et al. Can non-typeable Haemophilus influenzae carriage surveillance data infer antimicrobial resistance associated with otitis media? Pediatr Investig. 2023;7(01):13–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Mojgani N, Rahbar M, Taqizadeh M, Ashtiani MP, Mohammadzadeh M. Biotyping, capsular typing, and antibiotic resistance pattern of Haemophilus influenzae strains in Iran. Jpn J Infect Dis. 2011;64(1):66–8.

    Article  PubMed  Google Scholar 

  26. Wang S, Lo W, Chou C, Chen Y, Tsai S, Chu M, et al. Low rate of nasopharyngeal carriage and high rate of ampicillin resistance for Haemophilus influenzae among healthy children younger than 5 years old in northern Taiwan. J Microbiol Immunol Infect. 2008;41(1):32.

    PubMed  Google Scholar 

  27. Shen X, Lu Q, Deng L, Yu S, Zhang H, Deng Q, et al. Surveillance of antimicrobial susceptibility of Haemophilus influenzae isolates from children in Beijing, Shanghai, and Guangzhou 2000–2002. Zhonghua Yi Xue Za Zhi. 2004;84(16):1335–9.

    CAS  PubMed  Google Scholar 

  28. Ginsburg AS, Tinkham L, Riley K, Kay NA, Klugman KP, Gill CJ. Antibiotic non-susceptibility among Streptococcus pneumoniae and Haemophilus influenzae isolates identified in African cohorts: a meta-analysis of three decades of published studies. Int J Antimicrob Agents. 2013;42(6):482–91.

    Article  CAS  PubMed  Google Scholar 

  29. Levy SB, Marshall B. Antibacterial resistance worldwide: causes, challenges and responses. Nat Med. 2004;10(Suppl 12):122–S129.

    Article  Google Scholar 

  30. Tang KWK, Millar BC, Moore JE. Antimicrobial Resistance (AMR). Br J Biomed Sci. 2023;80:11387.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Gessner B. Worldwide variation in the incidence of Haemophilus influenzae type b Meningitis and its association with ampicillin resistance. Eur J Clin Microbiol Infect Dis. 2002;21:79–87.

    Article  CAS  PubMed  Google Scholar 

  32. Lieberthal AS, Carroll AE, Chonmaitree T, Ganiats TG, Hoberman A, Jackson MA, et al. The diagnosis and management of acute otitis media. Pediatrics. 2013;131(3):e964–999.

    Article  PubMed  Google Scholar 

  33. Peltola H. Worldwide Haemophilus influenzae type b Disease at the beginning of the 21st century: global analysis of the Disease burden 25 years after the use of the polysaccharide vaccine and a decade after the advent of conjugates. Clin Microbiol Rev. 2000;13(2):302–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Martinez EP, Cepeda M, Jovanoska M, Bramer WM, Schoufour J, Glisic M, et al. Seasonality of antimicrobial resistance rates in respiratory bacteria: a systematic review and meta-analysis. PLoS ONE. 2019;14(8):e0221133.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Mather MW, Drinnan M, Perry JD, Powell S, Wilson JA, Powell J. A systematic review and meta-analysis of antimicrobial resistance in paediatric acute otitis media. Int J Pediatr Otorhinolaryngol. 2019;123:102–9.

    Article  PubMed  Google Scholar 

  36. Bradley JS. Management of community-acquired pediatric Pneumonia in an era of increasing antibiotic resistance and conjugate vaccines. Pediatr Infect Dis J. 2002;21(6):592–8.

    Article  PubMed  Google Scholar 

  37. Vaez H, Sahebkar A, Pourfarzi F, Yousefi-Avarvand A, Khademi F. Prevalence of antibiotic resistance of Haemophilus Influenzae in Iran-a meta-analysis. Iran J Otorhinolaryngol. 2019;31(107):349.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We appreciate from both Jiroft University of Medical Sciences and Iranshahr University of Medical Sciences.

Funding

We have received a grant from Jiroft University of Medical Sciences. Grant ID: IR.JMU.REC.1402.064.

Author information

Authors and Affiliations

  1. Student Research Committee, Mashhad University of Medical Sciences, Mashhad, Iran

    Mohammad Abavisani

  2. Department of Microbiology and Virology, School of Medicine, Iranshahr University of Medical Sciences, Iranshahr, Iran

    Masoud Keikha

  3. Department of Microbiology and Virology, School of Medicine, Jiroft University of Medical Sciences, Jiroft, Iran

    Mohsen Karbalaei

Authors
  1. Mohammad Abavisani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Masoud Keikha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohsen Karbalaei
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

MA has contributed to design of the work and analysis of data. MA and MK1 have drafted the work and substantively revised it. MA and MK2 have reviewed and revised the draft manuscript. All authors read and approved the final manuscript. We confirmed all authors have contributed in all stages of manuscript such as literature search, data extraction, quality assessment, etc.

Corresponding authors

Correspondence to Masoud Keikha or Mohsen Karbalaei.

Ethics declarations

Ethics approval and consent to participate

Not applicable (this paper was provided based on researching in global databases).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

 Search strategy.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abavisani, M., Keikha, M. & Karbalaei, M. First global report about the prevalence of multi-drug resistant Haemophilus influenzae: a systematic review and meta-analysis. BMC Infect Dis 24, 90 (2024). https://doi.org/10.1186/s12879-023-08930-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12879-023-08930-5

Keywords

BMC Infectious Diseases

ISSN: 1471-2334

Contact us