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1 Present address: Room 419, 4/F, JC School of Public Health and Primary Care Building, Prince of Wales Hospital, Shatin, N.T., Hong Kong.
Kin On Kwok
Correspondence
Corresponding author at: JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
1 Present address: Room 419, 4/F, JC School of Public Health and Primary Care Building, Prince of Wales Hospital, Shatin, N.T., Hong Kong.
Affiliations
JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaStanley Ho Center for Emerging Infectious Diseases, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaHong Kong Institute of Asia-Pacific Studies, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaShenzhen Research Institute of the Chinese University of Hong Kong, Shenzhen, China
1 Present address: Room 419, 4/F, JC School of Public Health and Primary Care Building, Prince of Wales Hospital, Shatin, N.T., Hong Kong. 2 Present address: Room 429, 4/F, JC School of Public Health and Primary Care Building, Prince of Wales Hospital, Shatin, N.T., Hong Kong.
We read with interest the paper by Seaton and colleagues who reported 38.3% of SARS-CoV-2 hospitalized patients were prescribed antibiotics based on a one-day prevalence survey during the peak of the initial COVID-19 epidemic Scotland.
), the authors attributed their low prevalence of antibiotic use to their national antimicrobial stewardship initiatives. However, caution should be exercised when interpreting such reported rates of antibiotic use because they are dependent on the types of SARS-CoV-2 patients who were hospitalized. In addition, to further unravel the impact of the COVID-19 pandemic on antibiotic prescribing, it is useful to compare the antibiotic use in the community in the pre-pandemic period and that in the peri-pandemic period. To this end, we report the dispensing pattern of antibiotics in public hospitals for managing COVID-19 cases and compare the change of antibiotic use by such cases in general outpatient settings unrelated to COVID-19 from 2018 to 2020 in Hong Kong.
In this study, inpatient records of COVID-19 cases admitted to hospitals affiliated with the Hospital Authority were retrieved up to 3 March 2021. Pharmacy dispensing records of general outpatient settings for this cohort was available from 2018 onwards. Inpatient antibiotic use was expressed as defined daily doses (DDD)/ days of therapy (DOT) per 1000 bed-days. Outpatient antibiotic use was expressed as DDD per 100,000 person-days, where each case's person-day contribution was assumed as 365 days in 2018 and 2019, and as the number of days prior to their diagnosis of COVID-19 in 2020. Co-infections alongside COVID-19, based on ICD-9 discharge diagnoses and empiric classification of physicians, were grouped into bacterial or others. More methodological details is in Appendix I.
As of 3 March 2021, there were 11,047 laboratory-confirmed COVID-19 cases in Hong Kong, of which 11,004 were hospitalized and were included in the analysis. The mean (SD) age at hospital admission was 44.7 (19.9) years, with 8.2% of cases aged <18 years. Patient characteristics are summarized in Table S1. Antibiotic use was 251.0 DOT per 1000 bed-days and 289.7 DDD per 1000 bed-days among 10,106 adult cases. There were 29.1% of cases treated with antibiotics, but only 1.84% had confirmed bacterial co-infections. Of the overall antibiotic use, 6.1% was prescribed to cases with bacterial co-infections (confirmed: 9.6 DDD per 1000 bed-days; presumed: 8.1 DDD per 1000 bed-days) (Table 1). Antibiotic use was common in cases without any co-infections (66.1%, 191.4 DDD per 1000 bed-days) or when the co-condition was uncertain (13.7%, 39.8 DDD per 1000 bed-days). Almost all inpatient antibiotic use fell into the WHO's AWaRe classification list (access: 54.6%; watch: 42.0%; reserve: 1.16%) (Fig. 1). Cefoperazone/sulbactam, and ticarcillin/tazobactam, which are not recommended by WHO for clinical use, were also prescribed. In general outpatient settings from 2018 to 2020, community antibiotic use dropped from 52.8 to 45.9 DDD per 100,000 person-days (Table S2). This decreasing trend was also observed for individual antibiotics, except for amoxicillin/clavulanic acid, the use of which increased from 25.9 to 29.3 DDD per 100,000 person-days.
Table 1Antibiotic use by co-infections among adult COVID-19 cases treated with antibiotics.
Antibiotic class
ATC code
Co-infections
Bacterial only
Other viral/ fungal
Indeterminate/ unknown
Multiple types
None
Total
Confirmed
Presumed
Tetracyclines
J01AA
0.94
0.74
0.82
4.34
2.16
20.5
29.5
Penicillins with extended spectrum
J01CA
0.00
0.00
0.08
0.10
0.03
0.53
0.73
Beta-lactamase resistant penicillins
J01CF
0.98
0.00
0.04
0.16
1.13
1.55
3.86
Combinations of penicillins
J01CR
2.88
4.23
2.90
18.6
10.9
115.6
155.1
Cephalosporins, 1st generation
J01DB
0.00
0.05
0.00
0.00
0.00
0.12
0.16
Cephalosporins, 2nd generation
J01DC
0.05
0.08
0.00
0.25
0.31
0.95
1.63
Cephalosporins, 3rd generation
J01DD
1.43
0.85
0.96
6.07
5.64
31.1
46.0
Cephalosporins, 4th generation
J01DE
0.14
0.00
0.00
0.27
1.90
0.72
3.03
Carbapenems
J01DH
0.63
0.67
0.24
2.62
3.18
5.09
12.4
Other cephalosporins and penems
J01DI
0.00
0.00
0.00
0.00
0.40
0.00
0.40
Combinations of sulfonamides and trimethoprim, including derivatives
J01EE
0.03
0.39
0.02
0.65
1.97
1.40
4.47
Macrolides
J01FA
0.43
0.00
0.32
1.19
1.17
3.67
6.78
Lincosamides
J01FF
0.00
0.00
0.00
0.04
0.00
0.00
0.04
Aminoglycosides
J01GB
0.17
0.00
0.00
0.00
0.30
0.08
0.55
Fluoroquinolones
J01MA
1.21
0.59
0.48
3.45
2.82
7.53
16.1
Glycopeptides
J01XA
0.50
0.25
0.04
1.28
1.44
1.07
4.59
Polymixins
J01XB
0.00
0.00
0.00
0.00
0.24
0.16
0.40
Imidazole derivatives
J01XD
0.10
0.05
0.14
0.35
0.32
0.62
1.58
Nitrofuran derivatives
J01XE
0.00
0.18
0.00
0.08
0.06
0.26
0.57
Other antibacterials†
J01XX
0.15
0.03
0.02
0.36
0.69
0.51
1.75
Total
9.63
8.10
6.05
39.8
34.7
191.4
289.7
Numbers in table are defined daily doses per 1000 bed-days. † Fosfomycin, linezolid, daptomycin. ATC: Anatomical therapeutic chemical.
With data from the same individuals prior to and amid the pandemic, we draw inferences based on a self-controlled case series method that eliminates all time-invariant confounding.
Our results have three public health implications.
First, this study adds to the literature with the rate of antibiotic use in a complete cohort of cases, which is more adaptable to regions with a low prevalence of COVID-19. In Hong Kong, the number of cases was low such that hospitalization can be used as an isolation strategy (i.e. all cases were hospitalized). With the inclusion of mild and asymptomatic cases, it is not surprising that our reported rate is lower than that of other countries (74.6%
) where cases were abundant and only severe cases could be hospitalized. Therefore, caution should be exercised when generalizing our reported rate of antibiotic use among COVID-19 patents (29.1%) to countries with overwhelming numbers of cases.
Second, our results indicate that antibiotic overuse is high among hospitalized COVID-19 cases, highlighting the importance of safeguarding antibiotic stewardship during a pandemic. Although our rate of antibiotic use (29.1%) is lower than that of other countries (74.6%
it was much higher than that of bacterial co-infections (1.8% in our cohort). While it is understandable that the lack of specific therapy for COVID-19 and uncertainty in clinical manifestation can trigger a high rate of empiric antibiotic prescriptions, the scarcity of bacterial co-infections, which was evidenced in many studies,
suggests restrictive guidelines of antibiotic use are needed. Empiric antibiotic use might be withheld in cases with mild symptoms. In addition, the prescription of antibiotics in the “Watch” (42%), “Reserve” (1.7%) and “Not recommended” (2.3%) groups of the WHO's AWaRe classification system during this pandemic pushed the antibiotic pipeline closer to collapse.
Third, stewardship with monitoring of selected antibiotics should be implemented in outpatient settings. Consistent with significant decline in the community antibiotic use in Canada during the pandemic,
such decline was also observed in Hong Kong, indicating a slowdown of emergence of antimicrobial resistance in the community. However, caution should be taken when extrapolating such a decline globally because the epidemic size and intervention policies vary by region. In Hong Kong, the government adopted a suppress‐and‐lift strategy
such that the antibiotic use in outpatient settings were less driven by COVID-19 itself. However, in regions where the health system was on the brink of collapse, antibiotic use in the community may skyrocket. In addition, caution should be taken when assuming declining use of individual antibiotics. In our cohort, the increasing use of amoxicillin/clavulanic acid probably evidences the treatment of infections in the community, once present, to evade hospitalization in the peri-pandemic period. In fact, an ecological study in England also found that certain broad-spectrum antibiotics were taking up a larger proportion despite an overall decrease in antibiotic use in the community.
This study has two limitations. First, we assumed that antibiotics prescribed in the public outpatient settings were unrelated to COVID-19. Though cases, before diagnosis, might have obtained antibiotics for COVID-19 from public outpatient settings, this possibility was minimal because of the intense contact-tracing (and the following quarantine) in place and that hospitalization was the isolation strategy such that treatment of COVID-19 should predominantly take place in hospitals. Second, we only had data from the public healthcare sector such that a complete description of antibiotic use in the community is limited by the lack of data from the private healthcare sector.
Declaration of Competing Interest
The authors declare no conflict of interest.
CRediT authorship contribution statement
Kin On Kwok: Conceptualization, Formal analysis, Data interpretation, Writing original draft. Wan In Wei: Conceptualization, Formal analysis, Data interpretation, Writing original draft. Bosco Hon Ming Ma: Formal analysis, Data interpretation, Writing review & editing. Margaret Ip: Data interpretation, Writing review & editing. Heidi Cheung: Data interpretation, Writing review & editing. Elsie Hui: Data interpretation, Writing review & editing. Arthur Tang: Data interpretation, Writing review & editing. Edward Mcneil: Formal analysis, Data interpretation, Writing review & editing. Samuel Yeung Shan Wong: Conceptualization, Data interpretation, Writing review & editing. Eng Kiong Yeoh: Conceptualization, Data curation, Data interpretation, Writing review & editing.
Acknowledgment
This work is funded by the Health and Medical Research Fund (Reference Nos. INF-CUHK-1, 17160302, 18170312, CID-CUHK-A, COVID1903008). KOK also thanks General Research Fund (Reference Nos. 14112818, 24104920), Wellcome Trust Fund (United Kingdom, 200861/Z/16/Z), and Group Research Scheme of The Chinese University of Hong Kong. In addition, the authors would like to thank the Hospital Authority and Department of Health for providing the data.
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