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Impact of the World Antimicrobial Awareness Week on public interest between 2015 and 2020: A Google Trends analysis

  • Koichi Keitoku
    Affiliations
    Department of Medicine, John A. Burns School of Medicine, University of Hawai'i, Honolulu, HI 96813, USA
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  • Yoshito Nishimura
    Correspondence
    Corresponding author: Yoshito Nishimura, Department of Medicine, John A. Burns School of Medicine, University of Hawai'i, 1356 Lusitana St. 7th Floor, Honolulu, Hawaii 96813, USA. Tel: +1-808-586-2910.
    Affiliations
    Department of Medicine, John A. Burns School of Medicine, University of Hawai'i, Honolulu, HI 96813, USA

    Department of General Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama 7008558, Japan
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  • Hideharu Hagiya
    Affiliations
    Department of General Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama 7008558, Japan
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  • Toshihiro Koyama
    Affiliations
    Department of Pharmaceutical Biomedicine, Graduate School of Medicine, Dentistry, and Pharmaceutical Sciences, Okayama University, Okayama 7008530, Japan
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  • Fumio Otsuka
    Affiliations
    Department of General Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama 7008558, Japan
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Open AccessPublished:August 11, 2021DOI:https://doi.org/10.1016/j.ijid.2021.08.018

      Highlights

      • World Antimicrobial Awareness Week did not improve public awareness of antimicrobial resistance (AMR).
      • The COVID-19 pandemic may have reduced public interest in AMR.
      • Google Trends data were used as a surrogate for public awareness.

      Abstract

      Objectives

      To evaluate the impact of the World Antimicrobial Awareness Week (WAAW) on public awareness of antimicrobial resistance using Google Trends analysis.

      Methods

      The impact of WAAW on public awareness of ‘antimicrobial resistance’ (AMR), ‘antibacterial’, and ‘antibiotics’ in Japan, the UK, the United States, and worldwide from 2015 to 2020 was analyzed, using the relative search volume (RSV) of Google Trends as a surrogate. A joinpoint regression analysis was performed to identify a statistically significant time point of a change in trend.

      Results

      No joinpoints around WAAW were identified in Japan, the United Kingdom, or the United States from 2015 to 2020 with RSVs of ‘AMR’, whereas increasing RSVs were noted worldwide in 2017 and 2020. Further, there were decreasing RSVs of ‘antibiotics’ in the first half of 2020, which could be due to the COVID-19 pandemic. The study results suggest that WAAW did little to improve public awareness of AMR in the selected countries despite its contribution worldwide.

      Conclusions

      This study implies that we need to develop a more effective method to improve public awareness to fight against AMR.

      KEYWORDS

      1. Introduction

      The emergence of antimicrobial resistance (AMR) is a major health threat facing humanity. The World health Organization (WHO) recognizes AMR as one of the top 10 global public health threats (

      World Health Organization. Antimicrobial resistance; 2020. Available from: https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance. [Accessed May 7 2021].

      ). A previous study suggested that death attributable to AMR would reach 10 million by 2050 if no action was taken (

      Jim ON. Tackling drug-resistant infections globally: final report and recommendations. 2016.

      ). Further, AMR has been one of the chief agendas of the Group of 20 Health Ministers’ Meeting (
      • Matsumura H
      • Nishimura Y
      • Horiuchi H
      • Higashira T
      • Kita Y
      • Nishizawa H.
      G20 Okayama Health Ministers’ Meeting: lessons learned and way forward.
      ; Ministry of Health, 2019;
      • Nishizawa H
      • Nishimura Y
      • Matsumura H
      • Horiuchi H
      • Higashira T
      • Kita Y
      • et al.
      G20 Okayama Health Ministers' Meeting: Conclusions and commitments.
      ), suggesting the urgent need to promote antimicrobial stewardship.
      A reason for the emergence of AMR is the overuse of antibiotics. An internet survey conducted among the general public in Japan showed that almost half of the respondents answered that antibiotics were effective against viral infections such as the common cold and influenza (
      • Kamata K
      • Tokuda Y
      • Gu Y
      • Ohmagari N
      • Yanagihara K.
      Public knowledge and perception about antimicrobials and antimicrobial resistance in Japan: A national questionnaire survey in 2017.
      ). Another study revealed that Japanese primary care physicians prescribed antibiotics for the common cold if patients strongly preferred them (
      • Gu Y
      • Fujitomo Y
      • Soeda H
      • Nakahama C
      • Hasegawa N
      • Maesaki S
      • et al.
      A nationwide questionnaire survey of clinic doctors on antimicrobial stewardship in Japan.
      ). Medical students in Japan were also reported not to have as much knowledge on appropriate antimicrobial use as expected (
      • Hagiya H
      • Ino H
      • Tokumasu K
      • Ogawa H
      • Miyoshi T
      • Ochi K
      • et al.
      Antibiotic literacy among Japanese medical students.
      ). Thus, it is imperative to advocate the importance of the prudent use of antibiotics and antimicrobial stewardship for healthcare workers and the general public.
      Given the increasing concern regarding AMR, the WHO endorsed a global action plan to tackle this problem at the 68th World Health Assembly conducted in May 2015 and thereafter established the ‘World Antibiotics Awareness Week’ (WAAW) to take place in the third week of November every year in order to advocate the importance of AMR (

      World Health Organization. World Antimicrobial Awareness Week; 2021b. Available from: https://www.who.int/campaigns/world-antimicrobial-awareness-week. [Accessed February 7 2021].

      , 2021c). Meanwhile, the WHO called member states to develop a national action plan (NAP). Responding to the call, the Japanese government published its own NAP in April 2016 (
      • Kusama Y
      • Tsuzuki S
      • Muraki Y
      • Koizumi R
      • Ishikane M
      • Ohmagari N.
      The effects of Japan's National Action Plan on Antimicrobial Resistance on antimicrobial use.
      ). The Japanese government has also developed awareness-raising tools such as leaflets and websites and has implemented awareness-raising events on WAAW (Ministry of Health Labour and Welfare Japan, 2021).
      The measures described in the Japanese NAP have been effective to some extent in reducing antimicrobial consumption (
      • Kusama Y
      • Tsuzuki S
      • Muraki Y
      • Koizumi R
      • Ishikane M
      • Ohmagari N.
      The effects of Japan's National Action Plan on Antimicrobial Resistance on antimicrobial use.
      ;
      • Muraki Y
      • Yagi T
      • Tsuji Y
      • Nishimura N
      • Tanabe M
      • Niwa T
      • et al.
      Japanese antimicrobial consumption surveillance: First report on oral and parenteral antimicrobial consumption in Japan (2009-2013).
      ;
      • Tsutsui A
      • Yahara K
      • Shibayama K.
      Trends and patterns of national antimicrobial consumption in Japan from 2004 to 2016.
      ); however, there have been no studies to evaluate the effectiveness of these action plans to improve public awareness on AMR. Given that the internet has become the critical source for health-related information, online health information-seeking behavior can be utilized as a surrogate for public attention (
      • Zhao X
      • Fan J
      • Basnyat I
      • Hu B.
      Online Health Information Seeking Using “#COVID-19 Patient Seeking Help” on Weibo in Wuhan, China: Descriptive Study.
      ). Therefore, the aim of this study was to evaluate whether WAAW successfully increased public awareness of AMR in Japan, in comparison to the United Kingdom (UK) and the United States (USA) where awareness on AMR is a priority, and worldwide, using online search data.

      2. Methods

      2.1 Data source

      Google Trends is a publicly available data source generated based on the total Google search data (

      LLC G. Google Trends; 2021. Available from: https://trends.google.com/trends/. [Accessed May 7 2021].

      ) and has been utilized for social and behavioral health research (
      • Brodeur A
      • Clark AE
      • Fleche S
      • Powdthavee N.
      COVID-19, lockdowns and well-being: Evidence from Google Trends.
      ;
      • Cacciamani GE
      • Bassi S
      • Sebben M
      • Marcer A
      • Russo GI
      • Cocci A
      • et al.
      Consulting "Dr. Google" for Prostate Cancer Treatment Options: A Contemporary Worldwide Trend Analysis.
      ;
      • Havelka EM
      • Mallen CD
      • Shepherd TA.
      Using Google Trends to assess the impact of global public health days on online health information seeking behaviour in Central and South America.
      ;
      • Motosko C
      • Zakhem G
      • Ho R
      • Saadeh P
      • Hazen A.
      Using Google to Trend Patient Interest in Botulinum Toxin and Hyaluronic Acid Fillers.
      ;
      • Patel JC
      • Khurana P
      • Sharma YK
      • Kumar B
      • Ragumani S.
      Chronic lifestyle diseases display seasonal sensitive comorbid trend in human population evidence from Google Trends.
      ;
      • Patel JC
      • Khurana P
      • Sharma YK
      • Kumar B
      • Sugadev R.
      Google trend analysis of climatic zone based Indian severe seasonal sensitive population.
      ;
      • Peng Y
      • Li C
      • Rong Y
      • Chen X
      • Chen H.
      Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning.
      ;
      • Russo GI
      • di Mauro M
      • Cocci A
      • Cacciamani G
      • Cimino S
      • Serefoglu EC
      • et al.
      Consulting "Dr Google" for sexual dysfunction: a contemporary worldwide trend analysis.
      ;
      • Sharma M
      • Sharma S.
      The Rising Number of COVID-19 Cases Reflecting Growing Search Trend and Concern of People: A Google Trend Analysis of Eight Major Countries.
      ;
      • Tabuchi T
      • Fukui K
      • Gallus S.
      Tobacco Price Increases and Population Interest in Smoking Cessation in Japan Between 2004 and 2016: A Google Trends Analysis.
      ;
      • Zitting KM
      • Lammers-van der Holst HM
      • Yuan RK
      • Wang W
      • Quan SF
      • Duffy JF.
      Google Trends reveals increases in internet searches for insomnia during the 2019 coronavirus disease (COVID-19) global pandemic.
      ). This analysis allows the relative popularity of specific search terms in a particular category (for example, ‘health’), place, and time range to be determined, suggesting how popular the terms are at a certain time point. The relative popularity is noted as a relative search volume (RSV) with a scale of 0–100 (100 indicating the highest popularity) (
      • Havelka EM
      • Mallen CD
      • Shepherd TA.
      Using Google Trends to assess the impact of global public health days on online health information seeking behaviour in Central and South America.
      ;
      • Motosko C
      • Zakhem G
      • Ho R
      • Saadeh P
      • Hazen A.
      Using Google to Trend Patient Interest in Botulinum Toxin and Hyaluronic Acid Fillers.
      ;
      • Patel JC
      • Khurana P
      • Sharma YK
      • Kumar B
      • Sugadev R.
      Google trend analysis of climatic zone based Indian severe seasonal sensitive population.
      ;
      • Peng Y
      • Li C
      • Rong Y
      • Chen X
      • Chen H.
      Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning.
      ).

      2.2 Search input

      The search strategy using Google Trends is summarized in Figure 1 based on protocols reported in previous studies (
      • Havelka EM
      • Mallen CD
      • Shepherd TA.
      Using Google Trends to assess the impact of global public health days on online health information seeking behaviour in Central and South America.
      ;
      • Peng Y
      • Li C
      • Rong Y
      • Chen X
      • Chen H.
      Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning.
      ;
      • Tabuchi T
      • Fukui K
      • Gallus S.
      Tobacco Price Increases and Population Interest in Smoking Cessation in Japan Between 2004 and 2016: A Google Trends Analysis.
      ). Search inputs were selected based on the extent of relevance to WAAW through discussions among the research teams, including infectious disease specialists. Hence, the search inputs included terms such as ‘antimicrobial resistance’, ‘antibacterial’, and ‘antibiotics’, and their Japanese counterparts ‘yakuzai-taisei’, ‘kokin-yaku’, and ‘kosei-busshitsu’, respectively. All three Japanese terms are nouns generally recognized and used by the public. The location of the search included Japan, UK, USA, and worldwide. These three English search inputs were used for the search designating the UK, USA, and worldwide as the location, and the respective three Japanese counterparts for the search in Japan.

      2.3 Search variables

      All searches were conducted with a ‘Search Term’ option in a Health category to specifically extract the popularity of each search input (with a ‘Topic’ option, search volumes of subtopics or relevant themes were also included). Time scales were selected for each year (from 2015 to 2020), as well as a 72-month period (January 1, 2015 to December 31, 2020) to visualize the weekly and monthly trends of the RSVs. Based on a full year analysis, weekly RSVs were obtained (each year contains 52 or 53 weeks; of note, WAAW occurred in the 47th week of 2015, 2016, 2018, 2019, and 2020, and the 46th week of 2017). For the 72-month period search, monthly aggregated RSVs were analyzed.

      2.4 Statistical analyses

      A joinpoint regression model with the Joinpoint Regression Program (version 4.9.0.0, March 2021, Statistical Research and Applications Branch, National Cancer Institute, USA) (

      National Cancer Institute. Joinpoint Trend Analysis Software; 2021. Available from: https://surveillance.cancer.gov/joinpoint/. [Accessed May 13 2021].

      ) was implemented to analyze the time trend in the Google Trends RSV data. The software enables time points called joinpoints to be identified, where a temporal trend changes significantly. The analysis criteria were set to find up to three joinpoints. The weekly or monthly percentage changes (WPCs or MPCs) between trend-change points were determined with 95% confidence intervals (CI). The threshold for statistical significance was defined as a P-value <0.05, which indicated the level where the slope differed from zero.

      2.5 Ethical approval

      Publicly available data published by Google Trends (Google LLC, Mountain View CA, USA) were used. This study was approved by the Institutional Review Board of Okayama University Hospital with a waiver for informed consent, as the study intended to retrospectively analyze open data (No. 1910-009). All research methods were performed in accordance with relevant guidelines and regulations.

      3. Results

      3.1 Trends in the search volume for the term ‘antimicrobial resistance’

      Table 1 and Figure 2 describe the trends and trend changes of the weekly RSVs for the search term ‘yakuzai-taisei’ used in Japan and ‘antimicrobial resistance’ used in the UK, USA, and worldwide, in each full year from 2015 to 2020. With respect to the search results in Japan, a big surge was observed in week 11 in 2015, around the World Health Assembly when the WHO proposed the need for an AMR global action plan. However, no joinpoints were noted from 2015 to 2020 around the time of WAAW in Japan, the UK, or the USA. With regard to the search results worldwide, the third joinpoint was noted in week 48 in 2017 (2 weeks after WAAW), before which there was a significant increase in the RSV by 7.92% (P < 0.001) and after which there was a significant decrease in the RSV by 34.9% (P < 0.001). Further, in 2020, there was the second joinpoint in week 47 (WAAW), following which a significant decrease in the RSV by 27.8% (P < 0.001) was noted.
      Table 1Trend changes in relative search volumes for ‘antimicrobial resistance’, 2015–2020
      WordCountry/yearPeriod 1Period 2Period 3Period 4
      Weeks/ monthsWPC/ MPC (%)Weeks/ monthsWPC/ MPC (%)Weeks/ monthsWPC/ MPC (%)Weeks/ monthsWPC/ MPC (%)
      AMRJapan/20151–11−35.25*11–2638.77*26–31−47.3631–527.97
      Japan/20191–13−27.41*13–16116.9816–522.03
      USA/2015–20201–8−24.02*8–1149.7611–720.44
      Worldwide/20161–500.2850–52−58.33
      Worldwide/20171–912.08*9–34−2.98*34–487.92*48–53−34.90*
      Worldwide/20181–490.0349–52−24.58
      Worldwide/20191–490.3749–52−31.99
      Worldwide/20201–43−0.5143–4726.4147–52−27.80*
      Worldwide/2015–20201–271.40*27–72−0.13
      AMR, antimicrobial resistance; MPC, monthly percentage change; WPC, weekly percentage change. *Significantly different from zero (P < 0.05).
      Periods were separated into periods 1–4, when the trend changes were statistically detected in the joinpoint regression analysis during the study period.
      For the results of 2015–2020, the monthly percentage changes (MPC) are shown. For individual year results, the average weekly percentage changes (WPC) are shown.
      Figure 2
      Figure 2Trends in relative search volume of ‘antimicrobial resistance’ and its Japanese counterpart, 2015–2020.
      The weekly relative search volume (RSV) for the search term ‘antimicrobial resistance’ and its Japanese counterpart ‘yakuzai-taisei’ is described. World Antimicrobial Awareness Week (WAAW) occurred in the 47th week of 2015, 2016, 2018, 2019, and 2020, and the 46th week of 2017. In the search results for the worldwide analysis in 2017 and 2020, the third joinpoints were identified around the time of WAAW (during the 48th week and 47th week, respectively). The number of slopes is determined by the number of joinpoints identified by the analysis. Joinpoints are the time points when statistically significant changes in the linear slopes are noted.
      *Significantly different from zero (P < 0.05).

      3.2 Trends in the search volume for the term ‘antibacterial’

      Table 2 and Figure 3 describe the trends in the RSVs for the search term ‘kokin-yaku’, used in Japan, and ‘antibacterial’, used in the UK, USA, and worldwide, in each full year from 2015 to 2020. With respect to the search results in Japan, there was no significant increase or decrease in the RSVs throughout the year. Nevertheless, with regard to the search results worldwide, two significant points were found in 2016; however, they did not correspond to WAAW. Of note, in 2020, there were statistically significant changes in trend around week 10 of the year in the UK, USA, and worldwide. However, there were no joinpoints associated with the search terms around the time of WAAW.
      Table 2Trend changes in relative search volumes for ‘antibacterial’, 2015–2020
      WordCountry/yearPeriod 1Period 2Period 3Period 4
      Weeks/ monthsWPC/ MPC (%)Weeks/ monthsWPC/ MPC (%)Weeks/ monthsWPC/ MPC (%)Weeks/ monthsWPC/ MPC (%)
      AntibacterialJapan/20201–500.1450–52−27.14
      UK/20201–1140.13*11–14−39.7514–52−2.96*
      UK/2015–20201–600.55*60–6361.2863–72−14.53*
      USA/20171–433.464–17−4.28*17–530.72*
      USA/20201–71.017–1064.7310–17−16.53*17–52−1.67*
      USA/2015–20201–600.26*60–6341.2263–72−12.81*
      Worldwide/20161–172.16*17–20−12.1120–362.00*36–52−1.68*
      Worldwide/20201–73.327–1073.95*10–15−21.23*15–52−1.82*
      Worldwide/2015–20201–600.37*60–6341.35*63–72−10.97*
      MPC, monthly percentage change; WPC, weekly percentage change. *Significantly different from zero (P < 0.05).
      Periods were separated into periods 1–4, when the trend changes were statistically detected in the joinpoint regression analysis during the study period.
      For the results of 2015–2020, the monthly percentage changes (MPC) are shown. For individual year results, the average weekly percentage changes (WPC) are shown.
      Figure 3
      Figure 3Trends in relative search volume of ‘antibacterial’ and its Japanese counterpart, 2015–2020.
      The weekly relative search volume (RSV) for the search term ‘antibacterial’ and its Japanese counterpart ‘kokin-yaku’ is described. No joinpoints were identified around the time of WAAW during the study period with the search terms. The number of slopes is determined by the number of joinpoints identified by the analysis. Joinpoints are the time points when statistically significant changes in the linear slopes are noted.
      *Significantly different from zero (P < 0.05).

      3.3 Trends in the search volume for the term ‘antibiotics’

      Table 3 and Figure 4 demonstrate the trends in the RSVs for the search term ‘kosei-busshitsu’, used in Japan, and ‘antibiotics’, used in the UK, USA, and worldwide, in each full year from 2015 to 2020. There were multiple points with trend changes; however, no joinpoints were found around the time of WAAW using these search terms. Based on the search results in the UK, USA, and worldwide, there was a significant increase in the RSVs in the latter half of each year from 2015 to 2019. However, in Japan, no joinpoints possibly associated with WAAW were detected. Interestingly, there were similar trend changes between weeks 7 and 11 in 2020 in all countries and regions.
      Table 3Trend changes in relative search volumes of ‘antibiotics’, 2015–2020
      WordCountry/yearPeriod 1Period 2Period 3Period 4
      Weeks/ monthsWPC/ MPC (%)Weeks/ monthsWPC/ MPC (%)Weeks/ monthsWPC/ MPC (%)Weeks/ monthsWPC/ MPC (%)
      AntibioticsJapan/20161–39−0.3239–521.84
      Japan/20181–13−2.51*13–213.6721–25−7.4925–520.80*
      Japan/20191–13−2.92*13–189.3418–22−7.5022–520.46
      Japan/20201–71.857–21−3.30*21–520.59*
      Japan/2015–20201–620.19*62–65−10.7865–721.80
      UK/20151–37−1.28*37–4011.3540–520.15
      UK/20161–33−0.81*33–521.80*
      UK/20171–45−0.24*45–534.85*
      UK/20181–34−0.76*34–522.08*
      UK/20191–31−0.75*31–521.41*
      UK/20201–120.4012–20−4.62*20–520.37*
      UK/2015–20201–630.70*63–66−10.4566–722.63
      USA/20151–27−0.48*27–520.55*
      USA/20161–71.837–31−0.82*31–521.11*
      USA/20171–36−0.46*36–531.42*
      USA/20181–25−0.99*25–520.90*
      USA/20191–36−0.55*36–521.38*
      USA/20201–110.0711–17−6.66*17–520.39*
      USA/2015–20201–620.53*62–66−10.9665–721.01
      Worldwide/20151–27−0.66*27–520.68*
      Worldwide/20161–71.05*10–24−1.10*24–520.60*
      Worldwide/20171–34−0.38*34–530.93*
      Worldwide/20181–26−0.78*26–520.79*
      Worldwide/20191–25−0.55*25–520.60*
      Worldwide/20201–100.7510–19−4.53*19–291.20*29–520.12
      Worldwide/2015–20201–630.58*63–66−8.6066–722.51
      MPC, monthly percentage change; WPC, weekly percentage change. *Significantly different from zero (P < 0.05).
      Periods were separated into periods 1–4, when the trend changes were statistically detected in the joinpoint regression analysis during the study period.
      For the results of 2015–2020, the monthly percentage changes (MPC) are shown. For individual year results, the average weekly percentage changes (WPC) are shown.
      Figure 4
      Figure 4Trends in relative search volume of ‘antimicrobial’ and its Japanese counterpart, 2015–2020.
      The weekly relative search volume (RSV) for the search term ‘antimicrobial’ and its Japanese counterpart ‘kosei-busshitsu’ is described. No joinpoints were identified around the time of WAAW during the study period with the search terms. The number of slopes is determined by the number of joinpoints identified by the analysis. Joinpoints are the time points when statistically significant changes in the linear slopes are noted.
      *Significantly different from zero (P < 0.05).

      3.4 Monthly trends in RSVs between 2015 and 2020

      Table 1, Table 2, Table 3 and Figure 5 show the monthly trends and trend changes in RSVs between 2015 and 2020 for the search term combinations such as ‘antimicrobial resistance’, ‘antibacterial’, and ‘antibiotics’ and their Japanese counterparts. Table 4 describes the average weekly and monthly trends during the period. With regard to the search result for ‘yakuzai-taisei’, a counterpart of ‘AMR’ in Japanese, there was a significant continuous increase with the average MPC by 0.8% (P < 0.001) in Japan, while no joinpoints were observed in the UK. There were two joinpoints in the USA, in month 8 (August 2015) and month 11 (November 2015). There was a joinpoint in month 27 (March 2017) worldwide. For the search result of ‘kokin-yaku’, a counterpart of ‘antibacterial’ in Japanese, there was a significant continuous increase with the average MPC by 0.9% (P < 0.001). Similar trends were observed in the UK, USA, and worldwide, with two joinpoints, in month 60 (December 2019) and month 63 (March 2020). With respect to the search result for ‘kosei-busshitsu’, a Japanese counterpart of ‘antibiotics’, and the search results for ‘antibiotics’, although no statistically significant continuous trends were observed during the period, similar upsloping trends (months 1–62 (January 2015 to February 2020) in Japan and the USA and months 1–63 (January 2015 to March 2020) in the UK and worldwide)) were observed with a following significant decline.
      Figure 5
      Figure 5Trends in relative search volume between 2015 and 2020 with relevant search terms.
      Relative search volume (RSV) for the search terms ‘antimicrobial resistance’, ‘antibacterial’, ‘antibiotics’ and their Japanese counterparts between 2015 and 2020.
      *Significantly different from zero (P < 0.05).
      Table 4Average weekly or monthly trends in relative search volumes of ‘antimicrobial resistance’ and related words, 2015–2020
      Word (years)Average WPC or MPC (%) (95% CI)
      JapanUSAUKWorldwide
      AMR2015−2.0 (−17.9, 17.0)1.3 (−1.9, 4.7)1.1 (−2.3, 4.6)0.1 (−0.5, 0.8)
      2016−2.3 (−5.1, 0.5)0.4 (−2.1, 3.0)−1.0 (−3.3, 1.4)−3.1 (−6.9, 0.8)
      20171.1 (−1.1, 3.3)−0.7 (−3.0, 1.5)−2.3 (−5.4, 0.8)−1.8 (−4.6, 1.2)
      2018−0.6 (−3.7, 2.6)0 (−2.3, 2.4)0 (−3.1, 3.2)−1.6 (−4.7, 1.6)
      2019−1.5 (−15.0, 14.0)1.0 (−1.4, 3.4)0.5 (−2.2, 3.3)−1.9 (−4.7, 1.0)
      2020−0.6 (−1.9, 0.7)0.5 (−1.8, 3.0)−2.3 (−5.1, 0.5)−1.8 (−5.8, 2.5)
      2015–20200.8* (0.3, 1.4)−0.6 (−6.6, 5.7)0 (−0.5, 0.6)0.4 (0, 0.9)
      Antibacterial2015−0.3 (−0.9, 0.2)0 (−0.6, 0.7)−0.8 (−2.3, 0.8)−0.1 (−0.4, 0.2)
      20160.2 (−0.5, 0.8)0.1 (−0.4, 0.6)−1.2 (−2.6, 0.2)0 (−2.2, 2.3)
      20170.4 (−0.1, 0.8)1.1 (−0.9, 3.1)−0.2 (−1.1, 0.6)−0.1 (−0.4, 0.2)
      20180.1 (−0.3, 0.5)0.3 (−0.3, 0.8)−0.1 (−1.3, 1.2)−0.2 (−0.5, 0.1)
      20190.2 (−0.3, 0.7)0.1 (−0.3, 0.5)−0.6 (−1.5, 0.3)−0.2 (−0.5, 0.1)
      2020−1.1 (−2.9, 0.8)−0.6 (−4.3, 3.3)1.4 (−7.8, 11.6)0 (−2.1, 2.1)
      2015–20200.9* (0.7, 1.1)−0.1 (−1.6, 1.5)0.5 (−2.9, 4.0)0.3 (−0.6, 1.2)
      Antibiotics20150.3* (0, 0.6)0 (−0.2, 0.2)−0.2 (−1.8, 1.3)0 (−0.1, 0.1)
      20160.2 (−0.3, 0.8)0.3 (−0.1, 0.7)0.2 (−0.2, 0.5)0.2 (0, 0.5)
      20170.1 (−0.2, 0.3)0.2 (0, 0.4)0.5* (0.1, 0.9)0.1 (0, 0.2)
      2018−0.2 (−1.7, 1.3)0 (−0.2, 0.2)0.2 (−0.1, 0.6)0 (−0.1, 0.1)
      2019−0.2 (−1.9, 1.6)0.1 (−0.2, 0.3)0.1 (−0.1, 0.4)0.1 (−0.1, 0.2)
      2020−0.4 (−0.9, 0.2)−0.5* (−1.0, −0.1)−0.4 (−1.1, 0.2)−0.5* (−0.8, −0.2)
      2015–2020−0.1 (−1.2, 0.9)0.1 (−0.7, 0.9)0.4 (−0.8, 1.5)0.3 (−0.4, 1.1)
      AMR, antimicrobial resistance; CI, confidence interval; MPC, monthly percentage change; WPC, weekly percentage change. *Significantly different from zero (P < 0.05).
      For the results of 2015–2020, average monthly percentage changes are shown, from month 1 (January 2015) to month 72 (December 2020). For each individual year results, average weekly percentage changes are shown.

      4. Discussion

      This study evaluated how WAAW affected public awareness about AMR using the RSV as a surrogate. This is the first attempt to uncover public awareness regarding AMR using Google Trends. The results of this study showed that WAAW did not have a significant impact on general public interest in either AMR or antibiotics in Japan, the UK, and USA. However, there was a significant increase in the search volume for AMR in 2017 and 2020 worldwide around WAAW (Figure 2). These findings suggest that WAAW and its related campaigns in countries including Japan may not have effectively contributed to increasing public awareness of AMR. Interestingly, the RSVs for antibiotics in every country or region showed a considerable decline in 2020, when the COVID-19 global pandemic took place.
      Although previous studies have reported that the Japanese NAP and related movements successfully reduced antibiotic consumption (
      • Kusama Y
      • Tsuzuki S
      • Muraki Y
      • Koizumi R
      • Ishikane M
      • Ohmagari N.
      The effects of Japan's National Action Plan on Antimicrobial Resistance on antimicrobial use.
      ;
      • Muraki Y
      • Yagi T
      • Tsuji Y
      • Nishimura N
      • Tanabe M
      • Niwa T
      • et al.
      Japanese antimicrobial consumption surveillance: First report on oral and parenteral antimicrobial consumption in Japan (2009-2013).
      ;
      • Tsutsui A
      • Yahara K
      • Shibayama K.
      Trends and patterns of national antimicrobial consumption in Japan from 2004 to 2016.
      ), they have also highlighted the need for different strategies to address AMR, citing the increased use of broad-spectrum agents (
      • Tsutsui A
      • Yahara K
      • Shibayama K.
      Trends and patterns of national antimicrobial consumption in Japan from 2004 to 2016.
      ). To further promote antimicrobial stewardship or the choosing wisely concept of antibiotics, the importance of raising public awareness on AMR has been emphasized (
      • Gu Y.
      Raising awareness of antimicrobial resistance: comment on 'Reducing expectations for antibiotics in primary care: a randomised experiment to test the response to fear based messages about antimicrobial resistance'.
      ;
      • Rush L
      • Patterson C
      • McDaid L
      • Hilton S.
      Communicating antimicrobial resistance and stewardship in the national press: Lessons from sepsis awareness campaigns.
      ). A nationwide online survey conducted in 2017 showed that the majority of respondents had no opportunities to obtain information about antimicrobials, and less than half of them had heard of the term ‘AMR’ (
      • Kamata K
      • Tokuda Y
      • Gu Y
      • Ohmagari N
      • Yanagihara K.
      Public knowledge and perception about antimicrobials and antimicrobial resistance in Japan: A national questionnaire survey in 2017.
      ). Unfortunately, measures taken during WAAW in Japan indicate that they have not sufficiently contributed to raising public awareness of AMR based on the present results. To further improve public awareness, additional measures should be considered, such as the utilization of social media, given its popularity. A previous report showed that health awareness campaigns through social media reached a broad audience and attracted a large proportion of the general public (
      • Cillóniz C
      • Greenslade L
      • Dominedò C
      • Garcia-Vidal C.
      Promoting the use of social networks in pneumonia.
      ). Furthermore, to improve awareness among healthcare providers and promote the prudent use of antibiotics, mandating AMR and antimicrobial stewardship within undergraduate and postgraduate medical education needs to be considered (
      • Cillóniz C
      • Greenslade L
      • Dominedò C
      • Garcia-Vidal C.
      Promoting the use of social networks in pneumonia.
      ). In order to expand the awareness-raising activities, it is necessary to conduct periodic public surveys to follow up the effectiveness of the measures listed above.
      Interestingly, there were considerable decreasing trends in RSVs following big surges for ‘antibacterial’ and ‘antibiotics’ at the beginning of 2020 in every country and region. Around the same period, the COVID-19 pandemic emerged worldwide (

      Ministry of Health, Labour and Welfare Japan,. About Coronavirus Disease 2019 (COVID-19); 2021. Available from: https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000164708_00079.html. [Accessed January 12 2021].

      ;

      World Health Organization. WHO Coronavirus Disease (COVID-19) Dashboard; 2021a. Available from: https://covid19.who.int/table. [Accessed January 17 2021].

      ), which could have diverted public interest away from antibiotics and AMR and onto COVID-19 (
      • Arshad M
      • Mahmood SF
      • Khan M
      • Hasan R.
      Covid -19, misinformation, and antimicrobial resistance.
      ,
      • Hsu J.
      How covid-19 is accelerating the threat of antimicrobial resistance.
      ,
      • Strathdee SA
      • Davies SC
      • Marcelin JR.
      Confronting antimicrobial resistance beyond the COVID-19 pandemic and the 2020 US election.
      ). However, due to the substantial use of empiric broad-coverage antibiotics in the era of COVID-19, there seems to have been an increasing prevalence of multidrug-resistant bacteria during the pandemic when compared to the pre-COVID-19 period (
      • Pelfrene E
      • Botgros R
      • Cavaleri M.
      Antimicrobial multidrug resistance in the era of COVID-19: a forgotten plight?.
      ). While COVID-19 continues to be a global public health threat, we should not forget to fight against AMR as well, which is a hidden yet catastrophic threat behind the scene of the pandemic.
      There are several limitations to be addressed. First, because Google Trends was used as the data source, the present results included only those who had access to the internet and sought health-related information through Google search. However, the percentage of internet penetration is 91%, and the market share of Google search is approximately 75% in Japan (

      GlobalStats. Search Engine Market Share Japan; 2021. Available from: https://gs.statcounter.com/search-engine-market-share/all/japan. [Accessed May 13 2021].

      ;

      Statista. Internet penetration rate Japan 2000-2018; 2021. Available from: https://www.statista.com/statistics/255857/internet-penetration-in-japan/. [Accessed May 13 2021].

      ), which is sufficient to use Google Trends as a surrogate of public awareness. Second, Japan, the UK, and the USA have a combined population of approximately 500 million, or about 6% of the world population. Thus, data for the worldwide analysis might have been partly influenced by data from these countries. Third, Google Trends lacks full transparency and reproducibility, as suggested previously (
      • Nuti SV
      • Wayda B
      • Ranasinghe I
      • Wang S
      • Dreyer RP
      • Chen SI
      • et al.
      The Use of Google Trends in Health Care Research: A Systematic Review.
      ), since the calculation of RSVs depends on non-public mathematical assumptions and may not reflect the actual trend. We documented our search strategy in detail to address these limitations. However, we believe that our approach could satisfactorily have uncovered the movement of general awareness regarding AMR.
      In conclusion, the results of this study suggest that WAAW may not have effectively improved public awareness of AMR worldwide. As discussed above, enhancing public awareness is one of the most critical measures to fight against AMR and promote antimicrobial stewardship. While the COVID-19 pandemic has currently been a mainstay of the global health threat, we should not forget the importance of addressing AMR even at this time. Further countermeasures against AMR are essential to address this longstanding challenge.

      Declarations

      Funding: None.
      Conflict of interest: The authors declare no conflicts of interest in association with the present study.
      Author contributions: KK wrote the manuscript. YN wrote the manuscript, designed the study, and analyzed the data. HH proposed the study concept, designed the study, and analyzed the data. TK analyzed the data and critically revised the manuscript. FO supervised the research.

      Appendix. Supplementary materials

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