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Article Navigation> China CDC Weekly> 2021, 3(47): 1005-1013

Vital Surveillances: Surveillance of Multidrug-Resistant Bacterial Infections in Non-Adult Patients — Zhejiang Province, China, 2014–2019

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  • Abstract

    Introduction

    Antimicrobial resistance has become a major public health threat globally. The prevalence of multidrug-resistant (MDR) bacterial infections increased substantially among inpatients under 18 years of age in recent years. In Zhejiang Province, China, the trends of drug-resistance in non-adult patients from 2014 to 2019 were monitored, aiming to determine the variation patterns and epidemiological features of MDR strains.

     Methods

    Patient data were collected from the Annual Review of Hospital Infection Resistance Survey in Zhejiang Province, 2014–2019. Statistical analysis was performed to analyze the pattern of distribution of five key bacterial pathogens in different age groups, ward settings, and bloodstream infections.

     Results

    From 2014 to 2019, a total of 30,163 multidrug-resistant strains were identified among 212,252 clinical isolates. The prevalence of extended spectrum β-lactamase-producing Enterobacteriaceae (ESBL-E), carbapenem-resistant Enterobacteriaceae (CRE), carbapenem-resistantAcinetobacter baumannii, carbapenem-resistantPseudomonas aeruginosa(CRPA), and methicillin-resistantStaphylococcus aureus(MRSA) were 40.6%, 2.3%, 14.7%, 9.0%, and 27.4%, respectively. The prevalence of these key pathogens was lower than that reported in the national surveillance system (China Antimicrobial Resistance Surveillance System and Infectious Diseases Surveillance of Pediatrics). The prevalence of ESBL-E and CRE decreased since 2015 but that of CRPA and MRSA increased from 2014 to 2018.

     Conclusions

    Despite an overall decrease in the prevalence of drug-resistant bacteria in 2019, the rising prevalence of MRSA and CRPA still warrant much attention. Multidrug-resistant bacteria prevention and control strategies should be adjusted in a timely manner based on the surveillance results.
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    • 1.

      Department of Clinical Laboratory, the Second Affiliated Hospital of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang, China

    • 2.

      Clinical Microbiology Laboratory, the Third People’s Hospital of Hangzhou, Hangzhou, Zhejiang, China

    • 3.

      China Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology, Zhejiang Agricultural and Forestry University, Hangzhou, Zhejiang, China

    • 4.

      Master of Science, New Jersey Institute of Technology, Newark, New Jersey, the United States of America

    • 5.

      National Clinical Research Center for Child Health, the Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China

    • 6.

      Department of Hospital Infection Control, Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, Zhejiang, China

    • 7.

      Department of Clinical Laboratory, the Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China

    • 8.

      Department of Laboratory Medicine, the First Affiliated People’s Hospital of Hangzhou, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China

    • 9.

      Hangzhou Red Cross Hospital, Hangzhou, Zhejiang, China

    • 10.

      Department of Clinical Laboratory, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China

    • 11.

      Department of Clinical Laboratory, Hangzhou Women’s Hospital, Hangzhou Maternity and Child Health Care Hospital, Hangzhou, Zhejiang, China

    • 12.

      Clinical Diagnostic Laboratory, People’s Hospital of Zhejiang, Hangzhou, Zhejiang, China

    • 13.

      Department of Clinical Laboratory, Hangzhou Hospital of Traditional Chinese Medicine, Hangzhou, Zhejiang, China

    • 14.

      The First Affiliated Hospital of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang, China

    • 15.

      Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong Special Administrative Region, China

    • &Joint first authors.
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  • FIGURE 1.The prevalence of CRAB, CRE, CRPA, MRSA, and ESBL-E in non-adult patients — Zhejiang Province, 2014–2019.

    Note: The error bars represent 95% CI of the prevalence. Abbreviations: CRAB=carbapenem-resistantAcinetobacter baumannii; CRE=carbapenem-resistant Enterobacteriaceae; CRPA=carbapenem-resistantPseudomonas aeruginosa; MRSA=methicillin-resistantStaphylococcus aureus; ESBL-E=extended-spectrum β-lactamase-producing Enterobacteriaceae.

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    TABLE 1.Prevalence and risk analysis of critical pathogens in intensive care unit (ICU) and non-ICU groups in non-adult patients — Zhejiang Province, 2014–2019.

    Pathogens ICU 2014 2015 2016
    Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P
    CRAB (n=889) Yes 50 38.8 (30.3–47.7) 7.4 (4.7–11.5) <0.001 113 50.5 (43.3–56.7) 6.7 (4.9–9.3) <0.001 110 43.7 (37.4–50.0) 12.0 (8.2–17.5) <0.001
    No 60 7.9 (6.1–10.0) 1 130 12.9 (10.9–15.2) 1 51 6.1 (4.5–7.9) 1
    CRE (n=6,278) Yes 17 5.7 (3.3–8.9) 3.3 (2.0–5.6) <0.001 54 7.1 (5.4–9.2) 3.3 (2.4–4.4) <0.001 54 6.0 (4.5–7.7) 2.6 (1.9–3.5) <0.001
    No 107 1.8 (1.5–2.2) 1 210 2.3 (2.0–2.6) 1 239 2.4 (2.1–2.7) 1
    CRPA (n=604) Yes 18 31.0 (19.5–44.5) 9.4 (4.7–18.6) <0.001 31 24.4 (24.7–45.2) 9.5 (5.6–16.1) <0.001 30 29.1 (20.6–38.9) 7.2 (4.3–12.1) <0.001
    No 25 4.6 (3.0–6.7) 1 43 5.3 (3.8–7.0) 1 48 5.4 (4.0–7.1) 1
    MRSA (n=4,361) Yes 33 21.4 (15.2–28.2) 0.8 (0.6–1.2) 0.393 101 40.9 (34.7–47.3) 2.0 (1.5–2.5) <0.001 108 41.2 (35.2–47.4) 2.0 (1.5–2.6) <0.001
    No 1,028 24.4 (23.1–25.8) 1 1,824 26.1 (25.1–27.2) 1 1,852 26.1 (25.1–27.1) 1
    ESBL–E (n=4,124) Yes 93 45.1 (38.2–52.2) 1.1 (0.8–1.5) 0.467 254 49.3 (44.9–53.7) 1.4 (1.1–1.6) 0.001 307 47.2 (43.3–51.1) 1.4 (1.2–1.7) <0.001
    No 1,668 42.6 (41.0–44.1) 1 2,525 41.9 (40.6–43.1) 1 2565 38.6 (37.4–39.8) 1
    Pathogens ICU 2017 2018 2019
    Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P
    CRAB (n=889) Yes 86 32.2 (26.6–38.2) 6.1 (4.2–8.9) <0.001 84 40.0 (34.2–48.0) 7.7 (5.3–11.2) <0.001 33 24.4 (17.5–32.6) 4.4 (2.7–7.3) <0.001
    No 55 7.2 (5.5–9.3) 1 64 8.3 (6.4–10.5) 1 45 6.8 (5.0–9.0) 1
    CRE (n=6,278) Yes 56 5.3 (4.0–6.8) 2.8 (2.1–3.8) <0.001 41 4.9 (3.5–6.5) 2.7 (1.9–3.8) <0.001 38 4.7 (3.3–6.4) 2.5 (1.8–3.6) <0.001
    No 189 1.9 (1.7–2.2) 1 174 1.8 (1.6–2.1) 1 170 1.9 (1.6–2.2) 1
    CRPA (n=604) Yes 26 23.9 (16.2–33.0) 5.8 (3.4–9.8) <0.001 39 33.1 (24.7–42.3) 5.6 (3.6–8.7) <0.001 36 33.3 (24.6–43.1) 4.6 (2.9–7.3) <0.001
    No 46 5.1 (3.8–6.8) 1 88 8.1 (6.5–9.9) 1 77 9.8 (7.8–12.1) 1
    MRSA (n=4,361) Yes 83 29.0 (23.8–34.7) 1.0 (0.8–1.3) 0.883 123 41.4 (35.5–46.9) 1.7 (1.4–2.2) <0.001 102 34.3 (29.0–40.0) 1.4 (1.1–1.8) 0.005
    No 2,058 28.6 (27.6–29.7) 1 2,238 28.8 (27.7–29.8) 1 2,118 27.0 (26.0–28.0) 1
    ESBL–E (n=4,124) Yes 411 52.8 (49.2–56.3) 1.7 (1.4–1.9) <0.001 320 53.8 (49.7–57.8) 1.9 (1.6–2.2) <0.001 258 43.4 (39.4–47.5) 1.2 (1.0–1.4) 0.034
    No 2,630 40.0 (38.8–41.2) 1 2,464 38.0 (36.8–39.2) 1 2,263 39.0 (37.7–40.2) 1
    Abbreviations: CRAB=carbapenem-resistantAcinetobacter baumannii; CRE=carbapenem-resistant Enterobacteriaceae; CRPA=carbapenem-resistantPseudomonas aeruginosa; MRSA=methicillin-resistantStaphylococcus aureus; ESBL-E=extended-spectrum β-lactamase-producing Enterobacteriaceae.
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    TABLE 2.Prevalence and risk analysis of critical pathogen in different age groups of non-adult patients — Zhejiang Province, 2014–2019.
    Pathogens Age group, years 2014 2015 2016
    Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P
    CRAB (n=889) <1 23 14.9 (9.7–21.6) 1.9 (1.1–3.3) <0.001 113 28.8 (24.4–33.6) 3.0 (2.2–4.3) <0.001 71 23.1 (18.5–28.3) 5.7 (3.5–9.2) <0.001
    1–5 39 8.6 (6.2–11.5) 1 61 11.8 (9.1–14.8) 1 25 5.0 (3.3–7.3) 1
    6–14 26 12.0 (8.0–17.1) 1.5 (0.9–2.5) 37 14.5 (10.4–19.4) 1.3 (0.8–2.0) 41 17.6 (12.9–23.1) 4.0 (2.4–6.8)
    15–17 22 34.9 (23.3–48.0) 5.7 (3.1–10.6) 32 50.8 (37.9–63.6) 7.8 (4.4–13.6) 24 44.4 (30.9–58.6) 15.2 (7.8–29.7)
    CRE (n=6,278) <1 16 1.0 (0.6–1.7) 1 0.014 82 2.8 (2.2–3.4) 1 <0.001 94 3.0 (2.4–3.6) 1 <0.001
    1–5 66 2.3 (1.8–3.0) 1.3 (1.3–4.0) 96 2.4 (1.9–2.9) 0.9 (0.6–1.2) 92 2.2 (1.8–2.7) 0.7 (0.5–1.0)
    6–14 31 2.1 (1.4–2.9) 2.0 (1.1–3.7) 54 2.2 (1.6–2.8) 0.8 (0.5–1.1) 71 2.5 (2.2–3.2) 0.9 (0.6–1.2)
    15–17 11 2.8 (1.4–5.0) 2.8 (1.3–6.0) 32 6.3 (4.4–8.8) 2.4 (1.6–3.6) 36 6.3 (4.4–8.5) 2.2 (1.5–3.2)
    CRPA (n=604) <1 8 8.5 (3.7–16.1) 2.9 (1.0–7.9) 0.014 20 11.0 (6.9–16.5) 2.1 (1.1–4.1) 0.009 27 15.7 (10.6–22.0) 3.4 (1.9–6.2) <0.001
    1–5 8 3.1 (1.4–6.1) 1 20 5.5 (3.4–8.3) 1 21 5.2 (3.3–7.9) 1
    6–14 13 6.4 (3.5–10.7) 2.1 (0.9–5.2) 23 7.8 (5.0–11.5) 1.5 (0.8–2.7) 24 7.2 (4.7–10.5) 1.4 (0.8–2.6)
    15–17 14 26.9 (15.6–41.0) 11.4 (4.5–28.9) 11 16.4 (8.5–27.5) 3.4 (1.5–7.5) 6 7.1 (2.7–14.9) 1.4 (0.5–3.6)
    MRSA (n=4,361) <1 330 36.8 (33.6–40.0) 3.5 (2.3–5.2) <0.001 497 30.9 (28.6–33.2) 1.3 (1.0–1.6) <0.001 531 27.8 (25.8–29.9) 1.1 (0.8–1.4) 0.308
    1–5 465 22.6 (20.8–24.5) 1.7 (1.2–2.6) 924 26.0 (24.6–27.5) 1.0 (0.8–1.3) 890 26.8 (25.3–28.4) 1.1 (0.8–1.3)
    6–14 236 19.7 (17.5–22.1) 1.5 (1.0–2.2) 418 24.0 (22.0–26.1) 0.9 (0.7–1.2) 456 25.1 (23.2–27.2) 0.9 (0.7–1.2)
    15–17 30 14.4 (9.9–19.9) 1 86 26.2 (21.5–31.3) 1 83 26.2 (21.4–31.4) 1
    ESBL–E (n=4,124) <1 556 53.0 (49.9–56.1) 2.0 (1.5–2.7) <0.001 1,002 52.1 (49.8–54.4) 2.0 (1.6–2.6) <0.001 1025 44.8 (42.8–46.9) 1.6 (1.2–2.0) <0.001
    1–5 738 40.2 (38.0–42.5) 1.2 (0.9–1.6) 1,004 39.4 (37.5–41.3) 1.2 (0.9–1.5) 970 36.7 (34.9–38.6) 1.1 (0.9–1.4)
    6–14 383 38.0 (35.0–41.1) 1.1 (0.8–1.5) 665 37.6 (35.4–39.9) 1.1 (0.9–1.4) 762 37.4 (35.3–39.6) 1.2 (0.9–1.5)
    15–17 84 35.9 (29.8–42.4) 1 108 35.2 (29.8–40.8) 1 115 33.9 (28.9–39.2) 1
    Pathogens Age group, years 2017 2018 2019
    Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P
    CRAB (n=889) <1 41 14.6 (10.7–19.3) 1.8 (1.1–2.9) <0.001 27 11.9 (8.0–16.8) 1.4 (0.8–3.2) <0.001 16 8.2 (4.8–13.0) 0.9 (0.5–1.7) <0.001
    1–5 35 8.8 (6.2–12.0) 1 39 8.9 (6.4–11.9) 1 31 9.0 (6.2–12.5) 1
    6–14 38 14.1 (10.2–18.9) 1.7 (1.0–2.8) 42 18.4 (13.6–24.1) 2.3 (1.4–3.7) 19 8.8 (5.4–13.3) 1.0 (0.5–1.8)
    15–17 27 33.8 (23.6–45.2) 5.3 (3.0–9.4) 40 48.2 (37.1–59.4) 9.5 (5.6–16.4) 12 28.6 (15.7–44.6) 4.0 (1.9–8.7)
    CRE (n=6,278) <1 83 2.7 (2.1–3.3) 1 0.002 74 2.2 (1.8–2.8) 1 <0.001 75 2.4 (1.9–3.0) 1 0.014
    1–5 70 1.8 (1.4–2.2) 0.7 (0.5–0.9) 55 1.5 (1.2–2.0) 0.7 (0.5–1.0) 59 1.8 (1.4–2.3) 0.7 (0.5–1.1)
    6–14 68 2.1 (1.7–2.7) 0.8 (0.6–1.1) 59 2.1 (1.6–2.7) 0.9 (0.7–1.3) 53 1.9 (1.4–2.5) 0.8 (0.5–1.1)
    15–17 24 4.0 (2.6–5.9) 1.5 (1.0–2.4) 27 4.6 (3.0–6.6) 2.1 (1.3–3.3) 21 3.8 (2.3–5.7) 1.6 (1.0–2.6)
    CRPA (n=604) <1 14 7.9 (4.4–12.8) 1.8 (0.8–3.6) 0.007 24 10.6 (6.9–15.2) 1.5 (0.8–2.5) <0.001 14 8.4 (4.7–13.7) 0.9 (0.5–1.7) 0.001
    1–5 18 4.7 (2.8–7.3) 1 33 7.5 (5.2–10.4) 1 33 9.4 (6.6–13.0) 1
    6–14 28 7.8 (5.2–11.0) 1.7 (0.9–3.2) 38 8.9 (6.4–12.1) 1.2 (0.7–2.0) 50 16.4 (12.5–21.1) 1.9 (1.2–3.0)
    15–17 12 15.6 (8.3–25.6) 3.8 (1.7–8.2) 32 28.1 (20.1–37.3) 4.8 (2.8–8.3) 16 22.2 (13.3–33.6) 2.7 (1.4–5.3)
    MRSA (n=4,361) <1 638 32.1 (30.1–34.2) 1.3 (1.0–1.7) 0.001 709 31.5 (29.6–33.5) 1.1 (0.9–1.4) 0.041 597 29.5 (27.5–27.5) 1.1 (0.9–1.4) 0.074
    1–5 890 27.4 (25.9–29.0) 1.1 (0.8–1.4) 939 28.4 (26.9–30.0) 1.0 (0.8–1.2) 933 26.4 (25.0–27.9) 1.0 (0.8–1.2)
    6–14 534 27.5 (25.5–29.5) 1.1 (0.8–1.4) 599 28.0 (26.1–29.9) 0.9 (0.7–1.2) 586 26.4 (24.6–28.3) 1.0 (0.7–1.2)
    15–17 79 26.3 (21.4–31.7) 1 114 29.5 (25.0–34.3) 1 104 27.3 (22.9–32.1) 1
    ESBL–E (n=4,124) <1 1030 47.7 (25.5–49.8) 1.5 (1.2–1.9) <0.001 969 42.4 (40.4–44.5) 1.5 (1.2–1.9) <0.001 891 42.8 (40.7–45.0) 1.5 (1.2–1.9) <0.001
    1–5 968 39.1 (37.2–41.1) 1.1 (0.9–1.3) 935 39.8 (37.8–41.8) 1.4 (1.1–1.7) 718 38.0 (35.8–40.2) 1.2 (1.0–1.6)
    6–14 899 38.6 (36.6–40.6) 1.1 (0.8–1.3) 759 36.5 (34.4–38.6) 1.2 (0.9–1.5) 789 38.4 (36.2–40.5) 1.3 (1.0–1.6)
    15–17 144 37.3 (32.5–42.3) 1 121 32.6 (27.9–37.6) 1 123 33.2 (28.4–38.2) 1
    Abbreviations: CRAB=carbapenem-resistantAcinetobacter baumannii; CRE=carbapenem-resistant Enterobacteriaceae; CRPA=carbapenem-resistantPseudomonas aeruginosa; MRSA=methicillin-resistantStaphylococcus aureus; ESBL-E=extended-spectrum β-lactamase-producing Enterobacteriaceae.
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    TABLE 3.Prevalence and risk analysis of critical pathogen in BSI non-adult patients — Zhejiang Province, 2014–2019.

    BSI 2014 2015 2016
    Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P
    CRAB (n=889) Yes 5 23.8 (8.2–47.2) 2.3 (0.8–6.3) 0.202 6 20.0 (7.7–38.6) 1.0 (0.4–2.5) 0.973 5 20.0 (6.8–40.7) 1.5 (0.5–4.0) 0.641
    No 105 12.1 (10.0–14.5) 1 237 19.8 (17.5–22.1) 1 156 14.6 (12.5–16.9) 1
    CRE (n=6,278) Yes 6 2.3 (0.8–4.8) 1.2 (0.5–2.6) 0.737 23 4.8 (3.1–7.1) 1.9 (1.2–3.0) 0.003 23 4.3 (2.8–6.5) 1.7 (1.1–2.6) 0.018
    No 118 2.0 (1.6–2.3) 1 241 2.5 (2.2–2.9) 1 270 2.6 (2.3–3.0) 1
    CRPA (n=604) Yes 2 12.5 (1.6–38.3) 1.9 (0.4–8.7) 0.722 7 14.9 (6.2–28.3) 2.1 (0.9–4.8) 0.145 3 13.0 (2.8–33.6) 1.8 (0.5–6.2) 0.587
    No 41 7.0 (5.0–9.3) 1 67 7.8 (6.1–9.8) 1 75 7.7 (6.1–9.6) 1
    MRSA (n=4,361) Yes 25 29.1 (19.8–39.9) 1.3 (0.8–2.1) 0.301 49 34.3 (26.5–42.7) 1.4 (1.0–2.1) 0.037 56 31.5 (24.7–38.8) 1.3 (0.9–1.8) 0.141
    No 1,036 24.2 (23.0–25.5) 1 1876 26.5 (25.5–27.5) 1 1904 26.5 (25.5–27.6) 1
    ESBL–E (n=4,124) Yes 91 53.8 (46.0–61.5) 1.6 (1.2–2.2) 0.003 102 37.9 (32.1–44.0) 0.8 (0.6–1.1) 0.125 143 41.6 (36.3–47.0) 1.1 (0.9–1.4) 0.386
    No 1,670 42.2 (40.7–43.8) 1 2,677 42.6 (41.4–43.9) 1 2,729 39.2 (38.1–40.4) 1
    BSI 2017 2018 2019
    Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P Positive Prevalence
    (%) (95% CI)    		 Odds ratio (95% CI) P
    CRAB (n=889) Yes 7 26.9 (11.6–47.8) 2.4 (1.0–5.8) 0.091 9 33.3 (16.5–54.0) 2.9 (1.3–6.6) 0.016 3 16.7 (3.6–41.4) 1.9 (0.5–6.6) 0.554
    No 134 13.4 (11.3–15.7) 1 139 14.6 (12.4–17.0) 1 75 9.6 (7.6–11.9) 1
    CRE (n=6,278) Yes 29 5.9 (4.0–8.4) 2.9 (2.0–4.4) <0.001 14 3.0 (1.6–4.9) 1.5 (0.8–2.5) 0.174 18 4.3 (2.6–6.8) 2.2 (1.3–3.6) 0.002
    No 216 2.1 (1.8–2.4) 1 201 2.1 (1.8–2.4) 1 190 2.0 (1.8–2.4) 1
    CRPA (n=604) Yes 3 13.6 (2.9–34.9) 2.1 (0.6–7.2) 0.442 3 9.4 (2.0–25.0) 0.9 (0.3–2.9) 1 1 3.0 (0.1–15.8) 0.2 (0.0–1.5) 0.153
    No 69 7.0 (5.5–8.8) 1 124 10.6 (8.9–12.5) 1 112 13.0 (10.9–15.5) 1
    MRSA (n=4,361) Yes 33 25.8 (18.5–34.3) 0.9 (0.6–1.3) 0.471 52 34.9 (27.3–43.1) 1.3 (0.9–1.8) 0.123 41 29.3 (21.9–37.6) 1.1 (0.8–1.6) 0.581
    No 2,108 28.7 (27.7–29.7) 1 2,309 29.1 (28.1–30.1) 1 2179 27.2 (26.2–28.2) 1
    ESBL–E (n=4,124) Yes 145 43.4 (38.0–48.9) 1.1 (0.9–1.4) 0.44 134 41.6 (36.2–47.2) 1.1 (0.9–1.4) 0.385 117 41.2 (35.4–47.2) 1.1 (0.8–1.4) 0.522
    No 2,896 41.3 (40.1–42.4) 1 2,650 39.2 (38.0–40.4) 1 2,404 39.3 (38.1–40.5) 1
    Abbreviations: BSI=blood stream infection; CRAB=carbapenem-resistantAcinetobacter baumannii; CRE=carbapenem-resistant Enterobacteriaceae; CRPA=carbapenem-resistantPseudomonas aeruginosa; MRSA=methicillin-resistantStaphylococcus aureus; ESBL-E=extended-spectrum β-lactamase-producing Enterobacteriaceae.
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Surveillance of Multidrug-Resistant Bacterial Infections in Non-Adult Patients — Zhejiang Province, China, 2014–2019

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Abstract

Introduction

Antimicrobial resistance has become a major public health threat globally. The prevalence of multidrug-resistant (MDR) bacterial infections increased substantially among inpatients under 18 years of age in recent years. In Zhejiang Province, China, the trends of drug-resistance in non-adult patients from 2014 to 2019 were monitored, aiming to determine the variation patterns and epidemiological features of MDR strains.

 Methods

Patient data were collected from the Annual Review of Hospital Infection Resistance Survey in Zhejiang Province, 2014–2019. Statistical analysis was performed to analyze the pattern of distribution of five key bacterial pathogens in different age groups, ward settings, and bloodstream infections.

 Results

From 2014 to 2019, a total of 30,163 multidrug-resistant strains were identified among 212,252 clinical isolates. The prevalence of extended spectrum β-lactamase-producing Enterobacteriaceae (ESBL-E), carbapenem-resistant Enterobacteriaceae (CRE), carbapenem-resistantAcinetobacter baumannii, carbapenem-resistantPseudomonas aeruginosa(CRPA), and methicillin-resistantStaphylococcus aureus(MRSA) were 40.6%, 2.3%, 14.7%, 9.0%, and 27.4%, respectively. The prevalence of these key pathogens was lower than that reported in the national surveillance system (China Antimicrobial Resistance Surveillance System and Infectious Diseases Surveillance of Pediatrics). The prevalence of ESBL-E and CRE decreased since 2015 but that of CRPA and MRSA increased from 2014 to 2018.

 Conclusions

Despite an overall decrease in the prevalence of drug-resistant bacteria in 2019, the rising prevalence of MRSA and CRPA still warrant much attention. Multidrug-resistant bacteria prevention and control strategies should be adjusted in a timely manner based on the surveillance results.
  • 1. Department of Clinical Laboratory, the Second Affiliated Hospital of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang, China
  • 2. Clinical Microbiology Laboratory, the Third People’s Hospital of Hangzhou, Hangzhou, Zhejiang, China
  • 3. China Australia Joint Laboratory for Animal Health Big Data Analytics, College of Animal Science and Technology, Zhejiang Agricultural and Forestry University, Hangzhou, Zhejiang, China
  • 4. Master of Science, New Jersey Institute of Technology, Newark, New Jersey, the United States of America
  • 5. National Clinical Research Center for Child Health, the Children’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
  • 6. Department of Hospital Infection Control, Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, Zhejiang, China
  • 7. Department of Clinical Laboratory, the Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
  • 8. Department of Laboratory Medicine, the First Affiliated People’s Hospital of Hangzhou, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
  • 9. Hangzhou Red Cross Hospital, Hangzhou, Zhejiang, China
  • 10. Department of Clinical Laboratory, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
  • 11. Department of Clinical Laboratory, Hangzhou Women’s Hospital, Hangzhou Maternity and Child Health Care Hospital, Hangzhou, Zhejiang, China
  • 12. Clinical Diagnostic Laboratory, People’s Hospital of Zhejiang, Hangzhou, Zhejiang, China
  • 13. Department of Clinical Laboratory, Hangzhou Hospital of Traditional Chinese Medicine, Hangzhou, Zhejiang, China
  • 14. The First Affiliated Hospital of Zhejiang University, Zhejiang University, Hangzhou, Zhejiang, China
  • 15. Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong Special Administrative Region, China
    • Corresponding author:

    Rong Zhang,zhang-rong@zju.edu.cn

    Online Date:November 19 2021
    Issue Date:November 19 2021
    doi:10.46234/ccdcw2021.244
  • &Joint first authors.

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  • The prevalence of bacterial resistance to antibiotics has risen globally since mid-1990s, posing a severe risk to public health (1). Multidrug-resistant (MDR) organisms, which were defined as a strain resistant to three or more classes of antimicrobial drugs within the antimicrobial spectrum, pose an increasing challenge to global health.

    Despite the increasing global attention to MDR infection, little research has been conducted on MDR infections in non-adult populations. Few available data suggested that epidemiology, risk factors, and outcomes of MDR infections were comparable with those observed in adults (2).

    Most of the MDR organisms in Chinese children showed decreasing trends in recent years, except for imipenem-resistantEscherichia coli, imipenem-resistantKlebsiella pneumoniae,and methicillin-resistantStaphylococcus aureus(MRSA) (2). It is undeniable that multidrug-resistant bacterial infections lead to longer hospital stays and higher mortality rate (3). Among them, carbapenem-resistantAcinetobacter baumannii(CRAB), carbapenem-resistantPseudomonasaeruginosa(CRPA), carbapenem-resistant Enterobacteriaceae (CRE), and extended spectrum β-lactamase-producing Enterobacteriaceae (ESBL-E) were classified as critical priority pathogens and MRSA as high priority pathogen in thePriority Pathogens Listof the World Health Organization (WHO). Infections caused by those key pathogens have aroused wide public concern.

    Constant surveillance of the epidemiological trends of drug-resistant organisms is critical since MDR infections remain strongly associated with treatment failures and high mortality rates, particularly among pediatric patients. This report provides valuable information on MDR organism infections in non-adults in Zhejiang Province that could help facilitate better infection control and healthcare.

    • METHODS

    • Clinical data were obtained from the Annual Review of Hospital Infection Resistance Survey in Zhejiang Province, 2014–2019. Hospitals that participated in the study were distributed across 11 cities in Zhejiang Province: Hangzhou, Jiaxing, Huzhou, Shaoxing, Ningbo, Zhoushan, Taizhou, Jinhua, Quzhou, Lishui, and Wenzhou. Hospitals in China are classified into 3 categories (primary, secondary, and tertiary institutions) based on their medical service capacity. All the hospitals in the study were secondary or tertiary hospitals accredited to perform pathogen identification and anti-microbial susceptibility testing (Supplementary Table S1). The prevalence of CRE, ESBL-E, CRAB, CRPA, and MRSA isolates were determined by analyzing data exported from WHONET software (version 5.6, WHO) with SPSS software (version 23.0, SPSS Inc., Chicago, IL, USA). In group comparisons, Pearson’s chi-square and Fisher’s exact tests were used. In all models, there was statistical significance withP<0.05.

    RESULTS

    • A total of 212,252 non-duplicate strains collected from 2014 to 2019 were analyzed in this study. Among them, 30,163 strains were found to be multidrug-resistant. These included 15,758 ESBL-producing strains of the Enterobacteriaceae family (ESBL-E, accounting for 40.6% of Enterobacteriaceae strains), 1,349 CRE (2.3% of Enterobacteriaceae), 881 CRAB (14.7% ofAcinetobacter baumannii), 507 CRPA (9.0% ofPseudomonas aeruginosa), and 11,668 MRSA (27.4% ofStaphylococcus aureus). MRSA and ESBL-E were the most common pathogens, accounting for 90.9% of all drug-resistant infections (52.2% for ESBL-E and 38.7% for MRSA infections). Sample characteristics were provided in theSupplementary Table S1.

      The prevalences of CRAB, CRE, CRPA, MRSA, and ESBL-E recorded in different years were displayed inFigure 1. The prevalence of CRE decreased from 2.7% (95% CI 2.4%–3.0%) in 2016 to 2.1% (95% CI 1.9%–2.4%) in 2019, and the prevalence of ESBL-E also consistently declined from 42.7% (95% CI 41.2%–44.2%) in 2014 to 39.4% (95% CI 38.2%–40.6%) in 2019. The highest prevalence of CRAB (19.8%, 95% CI 17.6%–22.1%), was recorded in 2015, and a decrease was observed afterwards. It is worth noting that the prevalence of CRPA fluctuated during 2014–2016 and increased significantly from 7.18% (95% CI 5.2%–9.5%) in 2017 to 12.7% (95% CI 10.6%–15.0%) in 2019. MRSA appeared to be another emerging threat. The prevalence of MRSA increased significantly from 24.3% (95% CI 23.1%–25.6%) in 2014 to 29.2% (95% CI 28.2%–30.2%) in 2018 and remained at a high level (27.2%, 95% CI 26.3%–28.2%) after dropping in 2019.

      Figure 1.

      The prevalence of CRAB, CRE, CRPA, MRSA, and ESBL-E in non-adult patients — Zhejiang Province, 2014–2019.

      Note: The error bars represent 95% CI of the prevalence. Abbreviations: CRAB=carbapenem-resistant Acinetobacter baumannii; CRE=carbapenem-resistant Enterobacteriaceae; CRPA=carbapenem-resistant Pseudomonas aeruginosa; MRSA=methicillin-resistant Staphylococcus aureus; ESBL-E=extended-spectrum β-lactamase-producing Enterobacteriaceae.

      The prevalence and risk analysis of CRAB, CRE, CRPA, MRSA, and ESBL-E in ICU and non-ICU groups were described inTable 1. The prevalence and odds ratio (OR) in ICU group were significantly higher than that in non-ICU group. For CRAB, CRE, and CRPA, the prevalence and OR of ICU group were significantly higher than that in non-ICU group (P<0.001). For MRSA, the prevalence was close in ICU and non-ICU groups in 2014 and 2017, and the OR was not statistically significant in these years. For the remaining year, high prevalence and OR of MRSA in ICU group were observed (P<0.05). For ESBL-E, the prevalence in both the non-ICU group and the ICU group showed a high level, 38.0% to 42.6%, respectively. The OR in ICU group was slightly higher than that in non-ICU group.

      Prevalence and risk levels of CRAB, CRE, CRPA, MRSA, and ESBL-E in different age groups were shown inTable 2. For CRAB, the age group with the lowest risk was 1 to 5 years old, and the highest risk age group was 15 to 17 years old. For CRE, the lowest risk age group in 2014 was found to be among children less than 1 year old; all the other age groups exhibited significantly higher risk (P=0.014, <0.05). The prevalence of CRPA in different age groups varied like that of CRAB during the study period, with the lowest risk age group being 1 to 5 years old, and the highest risk age group being 15 to 17 years old. For MRSA, the age group <1 year exhibited the highest risk. The age group <1 year also exhibited the highest risk of ESBL-E infection from 2014 onwards, and other age groups showed similar risk level.

      Regarding antimicrobial resistance (AMR) in bloodstream infection (BSI) (Table 3), CRAB exhibited no significant difference between BSI and non-BSI consistently for six years. The risk level of CRE in BSI was significantly higher than non-blood samples (except for in 2014 and in 2018,P>0.05). For CRPA, no significant risk was found, but the prevalence decreased from 12.5% (95% CI 1.6%–38.3%) in 2014 to 3.0% (95% CI 0.1%–15.8%) in 2019. The prevalence of MRSA remained stable throughout, and the risk level in blood samples was only significantly higher than that of non-blood samples in 2015 (OR=1.4, 95% CI 1.0–2.1,P=0.037, <0.05). The prevalence of ESBL-E decreased since 2014 and there was no significant change in the risk of ESBL-E in BSI from 2015 to 2019.

    CONCLUSIONS

    • The overall prevalences of the five key pathogens were lower than that recorded in the China Antimicrobial Resistance Surveillance System (CARSS) and Infectious Diseases Surveillance of Pediatrics (ISPED). Comparison of results from ISPED 2017–2019 (4-6) indicated that the prevalence of CRE not only remained at a low level (2.0% to 2.7% from our datavs. 8.2% to 10.8% from ISPED), but also exhibited a decreasing trend since 2016 (P=0.004, <0.05). The only exception is carbapenem-resistantKlebsiella pneumonia, being an upward trend observable in ISPED (6). Though the prevalence of CRPA was lower than the data from ISPED (5), the prevalence has risen continuously since 2017. ESBL-E decreased since 2014 but the prevalence remained at a high level. The decrease was also observed in CRAB since 2015 and the prevalence recorded each year was lower than that of CARSS (2). The prevalence of MRSA kept increasing in the first few years (24.3% in 2014 to 29.2% in 2018) but then fell in 2019 (27.2%). The trend and prevalence of MRSA was in general agreement with the report of CARSS (27.5%–29.5%) (2). These data suggested that the prevalence of MRSA and CRPA should be prioritized due to their high prevalence and increasing trends.

      Investigating the pattern of pathogens in the ICU environment, especially for MDR organisms, will help develop specific prevention and control strategies. A recent study in a tertiary teaching hospital in western China reported thatAcinetobacter baumanniiwas the leading cause of infection in almost every ICU (7). In this study, ESBL-E was the most prevalent pathogen in ICU non-adult patients in Zhejiang Province (43.4% to 53.8%). High prevalences of CRAB, CRPA, and MRSA were also reported, suggesting a complex ICU environment. Risk analysis identified ICU admission as a risk factor for MDR infection, especially those due to CRAB (OR ranged from 4.4 to 12.0) and CRPA (OR ranged from 4.6 to 9.5). This finding is consistent with previous studies (8-9). Therefore, monitoring the pathogens exposure and incident infections in ICU environment is critical.

      Bloodstream infections (BSIs) represent a major cause of mortality and morbidity worldwide. In addition, antimicrobial-resistant organisms, most notably MRSA and ESBL-E, have emerged as the important etiological agents of community-acquired BSI (10). In our study, the prevalence of ESBL-E was the most common pathogen of bloodstream infections, followed by MRSA. The results agreed with the observations from a population-based and large multicenter cohort study in the US and Europe (11). The high prevalence of ESBL-E may be related to inappropriate antibiotic use. One study showed that clinical isolation of ESBL-producingE. colior ESBL-producingKlebsiellaspp. was closely linked to the third-generation cephalosporin treatment (12).

      In China, third-generation cephalosporin is the most common antibiotics to treat infections in neonates and older children and therefore may be overused in hospitals (13). MRSA is another critical pathogen associated with significant clinical morbidity and mortality. The prevalence of MRSA in adults is stable in Zhejiang Province and is similar to that in children (from 33.0% in 2014 to 29.8% in 2017) according to the China Antimicrobial Surveillance Network (14). In addition, the MDR pathogens responsible for BSI vary significantly in different regions in China. The predominant pathogen of BSI in our study is ESBL-E, whereas MRSA was the predominant BSI pathogen in Hubei Province (15). Risk analysis indicated that BSI had been a risk factor for CRE infection for many years, but a significant difference was not observed among other bacterial groups.

      Surveillance carried out in Zhejiang Province indicated that great attention should be paid to MDR organisms, especially for CRPA and MRSA. Some measures should be taken to alleviate the threat of AMR. On the one hand, for hospital-acquired infections, it is necessary to monitor the ICU environment, where broad-spectrum antibiotic use and the presence of MDR bacteria are common. On the other hand, antimicrobial stewardship programs should be advocated, especially for antibiotic prescription in the community since, in accordance with China Health Care Policy, pediatric patients were referred to community hospitals first, where the misuse and overuse of antibiotics occur frequently. Encouragingly, the government of China has started explorations of AMR. In 2016, National Action Plan for Containing Antibacterial Resistance (2016–2020) was published, aiming at reducing antimicrobial resistance through the synergy between national, regional, and local levels. Surveillance of MDR pathogens in clinical patients is necessary for monitoring AMR.

      There were some limitations in this surveillance study. First, due to the differences in medical conditions, data collected from hospitals in rural areas might be lower than the actual value. Second, symptomatic patients were more likely to visit medical institutions compared with asymptomatic ones, which may lead to selection bias. Finally, the lack of available data on antibiotic prescription in the community may influence the analysis of community-sourced infection.

      In conclusion, conducting surveillance of multidrug-resistant bacterial infections in non-adult patients to depict the prevalence and variation trends will support better diagnosis and clinical treatment.

      Pathogens ICU 2014 2015 2016
      Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P
      CRAB (n=889) Yes 50 38.8 (30.3–47.7) 7.4 (4.7–11.5) <0.001 113 50.5 (43.3–56.7) 6.7 (4.9–9.3) <0.001 110 43.7 (37.4–50.0) 12.0 (8.2–17.5) <0.001
      No 60 7.9 (6.1–10.0) 1 130 12.9 (10.9–15.2) 1 51 6.1 (4.5–7.9) 1
      CRE (n=6,278) Yes 17 5.7 (3.3–8.9) 3.3 (2.0–5.6) <0.001 54 7.1 (5.4–9.2) 3.3 (2.4–4.4) <0.001 54 6.0 (4.5–7.7) 2.6 (1.9–3.5) <0.001
      No 107 1.8 (1.5–2.2) 1 210 2.3 (2.0–2.6) 1 239 2.4 (2.1–2.7) 1
      CRPA (n=604) Yes 18 31.0 (19.5–44.5) 9.4 (4.7–18.6) <0.001 31 24.4 (24.7–45.2) 9.5 (5.6–16.1) <0.001 30 29.1 (20.6–38.9) 7.2 (4.3–12.1) <0.001
      No 25 4.6 (3.0–6.7) 1 43 5.3 (3.8–7.0) 1 48 5.4 (4.0–7.1) 1
      MRSA (n=4,361) Yes 33 21.4 (15.2–28.2) 0.8 (0.6–1.2) 0.393 101 40.9 (34.7–47.3) 2.0 (1.5–2.5) <0.001 108 41.2 (35.2–47.4) 2.0 (1.5–2.6) <0.001
      No 1,028 24.4 (23.1–25.8) 1 1,824 26.1 (25.1–27.2) 1 1,852 26.1 (25.1–27.1) 1
      ESBL–E (n=4,124) Yes 93 45.1 (38.2–52.2) 1.1 (0.8–1.5) 0.467 254 49.3 (44.9–53.7) 1.4 (1.1–1.6) 0.001 307 47.2 (43.3–51.1) 1.4 (1.2–1.7) <0.001
      No 1,668 42.6 (41.0–44.1) 1 2,525 41.9 (40.6–43.1) 1 2565 38.6 (37.4–39.8) 1
      Pathogens ICU 2017 2018 2019
      Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P
      CRAB (n=889) Yes 86 32.2 (26.6–38.2) 6.1 (4.2–8.9) <0.001 84 40.0 (34.2–48.0) 7.7 (5.3–11.2) <0.001 33 24.4 (17.5–32.6) 4.4 (2.7–7.3) <0.001
      No 55 7.2 (5.5–9.3) 1 64 8.3 (6.4–10.5) 1 45 6.8 (5.0–9.0) 1
      CRE (n=6,278) Yes 56 5.3 (4.0–6.8) 2.8 (2.1–3.8) <0.001 41 4.9 (3.5–6.5) 2.7 (1.9–3.8) <0.001 38 4.7 (3.3–6.4) 2.5 (1.8–3.6) <0.001
      No 189 1.9 (1.7–2.2) 1 174 1.8 (1.6–2.1) 1 170 1.9 (1.6–2.2) 1
      CRPA (n=604) Yes 26 23.9 (16.2–33.0) 5.8 (3.4–9.8) <0.001 39 33.1 (24.7–42.3) 5.6 (3.6–8.7) <0.001 36 33.3 (24.6–43.1) 4.6 (2.9–7.3) <0.001
      No 46 5.1 (3.8–6.8) 1 88 8.1 (6.5–9.9) 1 77 9.8 (7.8–12.1) 1
      MRSA (n=4,361) Yes 83 29.0 (23.8–34.7) 1.0 (0.8–1.3) 0.883 123 41.4 (35.5–46.9) 1.7 (1.4–2.2) <0.001 102 34.3 (29.0–40.0) 1.4 (1.1–1.8) 0.005
      No 2,058 28.6 (27.6–29.7) 1 2,238 28.8 (27.7–29.8) 1 2,118 27.0 (26.0–28.0) 1
      ESBL–E (n=4,124) Yes 411 52.8 (49.2–56.3) 1.7 (1.4–1.9) <0.001 320 53.8 (49.7–57.8) 1.9 (1.6–2.2) <0.001 258 43.4 (39.4–47.5) 1.2 (1.0–1.4) 0.034
      No 2,630 40.0 (38.8–41.2) 1 2,464 38.0 (36.8–39.2) 1 2,263 39.0 (37.7–40.2) 1
      Abbreviations: CRAB=carbapenem-resistantAcinetobacter baumannii; CRE=carbapenem-resistant Enterobacteriaceae; CRPA=carbapenem-resistantPseudomonas aeruginosa; MRSA=methicillin-resistantStaphylococcus aureus; ESBL-E=extended-spectrum β-lactamase-producing Enterobacteriaceae.

      Table 1.Prevalence and risk analysis of critical pathogens in intensive care unit (ICU) and non-ICU groups in non-adult patients — Zhejiang Province, 2014–2019.
      Pathogens Age group, years 2014 2015 2016
      Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P
      CRAB (n=889) <1 23 14.9 (9.7–21.6) 1.9 (1.1–3.3) <0.001 113 28.8 (24.4–33.6) 3.0 (2.2–4.3) <0.001 71 23.1 (18.5–28.3) 5.7 (3.5–9.2) <0.001
      1–5 39 8.6 (6.2–11.5) 1 61 11.8 (9.1–14.8) 1 25 5.0 (3.3–7.3) 1
      6–14 26 12.0 (8.0–17.1) 1.5 (0.9–2.5) 37 14.5 (10.4–19.4) 1.3 (0.8–2.0) 41 17.6 (12.9–23.1) 4.0 (2.4–6.8)
      15–17 22 34.9 (23.3–48.0) 5.7 (3.1–10.6) 32 50.8 (37.9–63.6) 7.8 (4.4–13.6) 24 44.4 (30.9–58.6) 15.2 (7.8–29.7)
      CRE (n=6,278) <1 16 1.0 (0.6–1.7) 1 0.014 82 2.8 (2.2–3.4) 1 <0.001 94 3.0 (2.4–3.6) 1 <0.001
      1–5 66 2.3 (1.8–3.0) 1.3 (1.3–4.0) 96 2.4 (1.9–2.9) 0.9 (0.6–1.2) 92 2.2 (1.8–2.7) 0.7 (0.5–1.0)
      6–14 31 2.1 (1.4–2.9) 2.0 (1.1–3.7) 54 2.2 (1.6–2.8) 0.8 (0.5–1.1) 71 2.5 (2.2–3.2) 0.9 (0.6–1.2)
      15–17 11 2.8 (1.4–5.0) 2.8 (1.3–6.0) 32 6.3 (4.4–8.8) 2.4 (1.6–3.6) 36 6.3 (4.4–8.5) 2.2 (1.5–3.2)
      CRPA (n=604) <1 8 8.5 (3.7–16.1) 2.9 (1.0–7.9) 0.014 20 11.0 (6.9–16.5) 2.1 (1.1–4.1) 0.009 27 15.7 (10.6–22.0) 3.4 (1.9–6.2) <0.001
      1–5 8 3.1 (1.4–6.1) 1 20 5.5 (3.4–8.3) 1 21 5.2 (3.3–7.9) 1
      6–14 13 6.4 (3.5–10.7) 2.1 (0.9–5.2) 23 7.8 (5.0–11.5) 1.5 (0.8–2.7) 24 7.2 (4.7–10.5) 1.4 (0.8–2.6)
      15–17 14 26.9 (15.6–41.0) 11.4 (4.5–28.9) 11 16.4 (8.5–27.5) 3.4 (1.5–7.5) 6 7.1 (2.7–14.9) 1.4 (0.5–3.6)
      MRSA (n=4,361) <1 330 36.8 (33.6–40.0) 3.5 (2.3–5.2) <0.001 497 30.9 (28.6–33.2) 1.3 (1.0–1.6) <0.001 531 27.8 (25.8–29.9) 1.1 (0.8–1.4) 0.308
      1–5 465 22.6 (20.8–24.5) 1.7 (1.2–2.6) 924 26.0 (24.6–27.5) 1.0 (0.8–1.3) 890 26.8 (25.3–28.4) 1.1 (0.8–1.3)
      6–14 236 19.7 (17.5–22.1) 1.5 (1.0–2.2) 418 24.0 (22.0–26.1) 0.9 (0.7–1.2) 456 25.1 (23.2–27.2) 0.9 (0.7–1.2)
      15–17 30 14.4 (9.9–19.9) 1 86 26.2 (21.5–31.3) 1 83 26.2 (21.4–31.4) 1
      ESBL–E (n=4,124) <1 556 53.0 (49.9–56.1) 2.0 (1.5–2.7) <0.001 1,002 52.1 (49.8–54.4) 2.0 (1.6–2.6) <0.001 1025 44.8 (42.8–46.9) 1.6 (1.2–2.0) <0.001
      1–5 738 40.2 (38.0–42.5) 1.2 (0.9–1.6) 1,004 39.4 (37.5–41.3) 1.2 (0.9–1.5) 970 36.7 (34.9–38.6) 1.1 (0.9–1.4)
      6–14 383 38.0 (35.0–41.1) 1.1 (0.8–1.5) 665 37.6 (35.4–39.9) 1.1 (0.9–1.4) 762 37.4 (35.3–39.6) 1.2 (0.9–1.5)
      15–17 84 35.9 (29.8–42.4) 1 108 35.2 (29.8–40.8) 1 115 33.9 (28.9–39.2) 1
      Pathogens Age group, years 2017 2018 2019
      Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P
      CRAB (n=889) <1 41 14.6 (10.7–19.3) 1.8 (1.1–2.9) <0.001 27 11.9 (8.0–16.8) 1.4 (0.8–3.2) <0.001 16 8.2 (4.8–13.0) 0.9 (0.5–1.7) <0.001
      1–5 35 8.8 (6.2–12.0) 1 39 8.9 (6.4–11.9) 1 31 9.0 (6.2–12.5) 1
      6–14 38 14.1 (10.2–18.9) 1.7 (1.0–2.8) 42 18.4 (13.6–24.1) 2.3 (1.4–3.7) 19 8.8 (5.4–13.3) 1.0 (0.5–1.8)
      15–17 27 33.8 (23.6–45.2) 5.3 (3.0–9.4) 40 48.2 (37.1–59.4) 9.5 (5.6–16.4) 12 28.6 (15.7–44.6) 4.0 (1.9–8.7)
      CRE (n=6,278) <1 83 2.7 (2.1–3.3) 1 0.002 74 2.2 (1.8–2.8) 1 <0.001 75 2.4 (1.9–3.0) 1 0.014
      1–5 70 1.8 (1.4–2.2) 0.7 (0.5–0.9) 55 1.5 (1.2–2.0) 0.7 (0.5–1.0) 59 1.8 (1.4–2.3) 0.7 (0.5–1.1)
      6–14 68 2.1 (1.7–2.7) 0.8 (0.6–1.1) 59 2.1 (1.6–2.7) 0.9 (0.7–1.3) 53 1.9 (1.4–2.5) 0.8 (0.5–1.1)
      15–17 24 4.0 (2.6–5.9) 1.5 (1.0–2.4) 27 4.6 (3.0–6.6) 2.1 (1.3–3.3) 21 3.8 (2.3–5.7) 1.6 (1.0–2.6)
      CRPA (n=604) <1 14 7.9 (4.4–12.8) 1.8 (0.8–3.6) 0.007 24 10.6 (6.9–15.2) 1.5 (0.8–2.5) <0.001 14 8.4 (4.7–13.7) 0.9 (0.5–1.7) 0.001
      1–5 18 4.7 (2.8–7.3) 1 33 7.5 (5.2–10.4) 1 33 9.4 (6.6–13.0) 1
      6–14 28 7.8 (5.2–11.0) 1.7 (0.9–3.2) 38 8.9 (6.4–12.1) 1.2 (0.7–2.0) 50 16.4 (12.5–21.1) 1.9 (1.2–3.0)
      15–17 12 15.6 (8.3–25.6) 3.8 (1.7–8.2) 32 28.1 (20.1–37.3) 4.8 (2.8–8.3) 16 22.2 (13.3–33.6) 2.7 (1.4–5.3)
      MRSA (n=4,361) <1 638 32.1 (30.1–34.2) 1.3 (1.0–1.7) 0.001 709 31.5 (29.6–33.5) 1.1 (0.9–1.4) 0.041 597 29.5 (27.5–27.5) 1.1 (0.9–1.4) 0.074
      1–5 890 27.4 (25.9–29.0) 1.1 (0.8–1.4) 939 28.4 (26.9–30.0) 1.0 (0.8–1.2) 933 26.4 (25.0–27.9) 1.0 (0.8–1.2)
      6–14 534 27.5 (25.5–29.5) 1.1 (0.8–1.4) 599 28.0 (26.1–29.9) 0.9 (0.7–1.2) 586 26.4 (24.6–28.3) 1.0 (0.7–1.2)
      15–17 79 26.3 (21.4–31.7) 1 114 29.5 (25.0–34.3) 1 104 27.3 (22.9–32.1) 1
      ESBL–E (n=4,124) <1 1030 47.7 (25.5–49.8) 1.5 (1.2–1.9) <0.001 969 42.4 (40.4–44.5) 1.5 (1.2–1.9) <0.001 891 42.8 (40.7–45.0) 1.5 (1.2–1.9) <0.001
      1–5 968 39.1 (37.2–41.1) 1.1 (0.9–1.3) 935 39.8 (37.8–41.8) 1.4 (1.1–1.7) 718 38.0 (35.8–40.2) 1.2 (1.0–1.6)
      6–14 899 38.6 (36.6–40.6) 1.1 (0.8–1.3) 759 36.5 (34.4–38.6) 1.2 (0.9–1.5) 789 38.4 (36.2–40.5) 1.3 (1.0–1.6)
      15–17 144 37.3 (32.5–42.3) 1 121 32.6 (27.9–37.6) 1 123 33.2 (28.4–38.2) 1
      Abbreviations: CRAB=carbapenem-resistantAcinetobacter baumannii; CRE=carbapenem-resistant Enterobacteriaceae; CRPA=carbapenem-resistantPseudomonas aeruginosa; MRSA=methicillin-resistantStaphylococcus aureus; ESBL-E=extended-spectrum β-lactamase-producing Enterobacteriaceae.

      Table 2.Prevalence and risk analysis of critical pathogen in different age groups of non-adult patients — Zhejiang Province, 2014–2019.

      BSI 2014 2015 2016
      Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P
      CRAB (n=889) Yes 5 23.8 (8.2–47.2) 2.3 (0.8–6.3) 0.202 6 20.0 (7.7–38.6) 1.0 (0.4–2.5) 0.973 5 20.0 (6.8–40.7) 1.5 (0.5–4.0) 0.641
      No 105 12.1 (10.0–14.5) 1 237 19.8 (17.5–22.1) 1 156 14.6 (12.5–16.9) 1
      CRE (n=6,278) Yes 6 2.3 (0.8–4.8) 1.2 (0.5–2.6) 0.737 23 4.8 (3.1–7.1) 1.9 (1.2–3.0) 0.003 23 4.3 (2.8–6.5) 1.7 (1.1–2.6) 0.018
      No 118 2.0 (1.6–2.3) 1 241 2.5 (2.2–2.9) 1 270 2.6 (2.3–3.0) 1
      CRPA (n=604) Yes 2 12.5 (1.6–38.3) 1.9 (0.4–8.7) 0.722 7 14.9 (6.2–28.3) 2.1 (0.9–4.8) 0.145 3 13.0 (2.8–33.6) 1.8 (0.5–6.2) 0.587
      No 41 7.0 (5.0–9.3) 1 67 7.8 (6.1–9.8) 1 75 7.7 (6.1–9.6) 1
      MRSA (n=4,361) Yes 25 29.1 (19.8–39.9) 1.3 (0.8–2.1) 0.301 49 34.3 (26.5–42.7) 1.4 (1.0–2.1) 0.037 56 31.5 (24.7–38.8) 1.3 (0.9–1.8) 0.141
      No 1,036 24.2 (23.0–25.5) 1 1876 26.5 (25.5–27.5) 1 1904 26.5 (25.5–27.6) 1
      ESBL–E (n=4,124) Yes 91 53.8 (46.0–61.5) 1.6 (1.2–2.2) 0.003 102 37.9 (32.1–44.0) 0.8 (0.6–1.1) 0.125 143 41.6 (36.3–47.0) 1.1 (0.9–1.4) 0.386
      No 1,670 42.2 (40.7–43.8) 1 2,677 42.6 (41.4–43.9) 1 2,729 39.2 (38.1–40.4) 1
      BSI 2017 2018 2019
      Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P Positive Prevalence
      (%) (95% CI)      		 Odds ratio (95% CI) P
      CRAB (n=889) Yes 7 26.9 (11.6–47.8) 2.4 (1.0–5.8) 0.091 9 33.3 (16.5–54.0) 2.9 (1.3–6.6) 0.016 3 16.7 (3.6–41.4) 1.9 (0.5–6.6) 0.554
      No 134 13.4 (11.3–15.7) 1 139 14.6 (12.4–17.0) 1 75 9.6 (7.6–11.9) 1
      CRE (n=6,278) Yes 29 5.9 (4.0–8.4) 2.9 (2.0–4.4) <0.001 14 3.0 (1.6–4.9) 1.5 (0.8–2.5) 0.174 18 4.3 (2.6–6.8) 2.2 (1.3–3.6) 0.002
      No 216 2.1 (1.8–2.4) 1 201 2.1 (1.8–2.4) 1 190 2.0 (1.8–2.4) 1
      CRPA (n=604) Yes 3 13.6 (2.9–34.9) 2.1 (0.6–7.2) 0.442 3 9.4 (2.0–25.0) 0.9 (0.3–2.9) 1 1 3.0 (0.1–15.8) 0.2 (0.0–1.5) 0.153
      No 69 7.0 (5.5–8.8) 1 124 10.6 (8.9–12.5) 1 112 13.0 (10.9–15.5) 1
      MRSA (n=4,361) Yes 33 25.8 (18.5–34.3) 0.9 (0.6–1.3) 0.471 52 34.9 (27.3–43.1) 1.3 (0.9–1.8) 0.123 41 29.3 (21.9–37.6) 1.1 (0.8–1.6) 0.581
      No 2,108 28.7 (27.7–29.7) 1 2,309 29.1 (28.1–30.1) 1 2179 27.2 (26.2–28.2) 1
      ESBL–E (n=4,124) Yes 145 43.4 (38.0–48.9) 1.1 (0.9–1.4) 0.44 134 41.6 (36.2–47.2) 1.1 (0.9–1.4) 0.385 117 41.2 (35.4–47.2) 1.1 (0.8–1.4) 0.522
      No 2,896 41.3 (40.1–42.4) 1 2,650 39.2 (38.0–40.4) 1 2,404 39.3 (38.1–40.5) 1
      Abbreviations: BSI=blood stream infection; CRAB=carbapenem-resistantAcinetobacter baumannii; CRE=carbapenem-resistant Enterobacteriaceae; CRPA=carbapenem-resistantPseudomonas aeruginosa; MRSA=methicillin-resistantStaphylococcus aureus; ESBL-E=extended-spectrum β-lactamase-producing Enterobacteriaceae.

      Table 3.Prevalence and risk analysis of critical pathogen in BSI non-adult patients — Zhejiang Province, 2014–2019.

Reference (15)

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