Participant characteristics
A total of 351 individuals participated in this study, with the vast majority (80.1%, n = 281) living in high-income countries (HIC) and the remaining 19.9% (n = 70) from low- and middle-income countries (LMIC). Among the participants, 51.9% (n = 182) were female, 46.4% (n = 163) were male and 1.7% (n = 6) did not enclose their gender. Half of the study sample (51.0%, n = 179) was between 40 and 60 years-of-age, 26.8% (n = 94) were younger than 40, and 22.2% (n = 78) were older than 60. Regarding occupational background, the vast majority (86.3%, n = 303) held positions at the government, while 12.8% (n = 45) worked for non-governmental organizations. Regarding participants working at a governmental body, 52.1% (n = 183) were working at a municipal or regional level, 18.2% (n = 64) held positions on provincial levels, and 7.1% (n = 25) were working on a national level. Educational backgrounds were mostly master/doctoral degrees (44.7%, n = 157), followed by bachelor (40.7%, n = 143), and lower levels of education (14.0%, n = 49). Regarding field of expertise, 46.4% (n = 163) had a scientific background (i.e. human health or life sciences), whereas the other half (53.6%, n = 188) had an expertise in other backgrounds. Most participants were living in suburban areas (62.7%, n = 220). Demographic characteristics except gender were significantly different between HIC and LMIC subsets (p < 0.05). A detailed demographic characteristics of participants is shown in Table 1.
[Table 1: Sociodemographic description and political features of all participants, and stratified for low-and-middle income and high-income countries. Differences between subsets were analyzed by Fisher exact tests.]
Representatives from 15 different countries participated. Most participants were coming from the Netherlands (48.7%, n = 171), followed by Spain (27.6%, n = 97) and Myanmar (9.7%, n = 34). All represented countries are shown in Fig. 1.
[Figure 1: Spatial plot of all countries represented in current multinational study: the Netherlands (48.7%, n = 171), Spain (27.6%, n = 97), Myanmar (9.7%, n = 34), India (3.1%, n = 11), Nigeria (2.6%, n = 9), Mexico (1.7%, n = 6), Morocco (1.4%, n = 5), Australia (1.1%, n = 4), Brasil (1.1%, n = 4), Belgium (0.9%, n = 3), Canada (0.9%, n = 3), Curaçao (0.3%, n = 1), Guatemala (0.3%, n = 1), Panama (0.3%, n = 1) and Singapore (0.3%, n = 1) ]
Overall knowledge, attitude and perception scores
Cumulative scores were calculated for: 1) personal knowledge, 2) personal attitude and perception, and 3) political knowledge, attitude and perception. The mean and median scores of personal attitude and perception from all participants were 6.99 and 7.50 out of 10, respectively. Both the mean and median scores on personal attitude and perception were significantly different between HIC (mean of 7.31, median of 7.50) and LMIC (mean of 5.70, median of 5.83) participants (p < 0.001). For the knowledge score, a statistically significant difference was only observed for the median score (p < 0.05), but not for the mean score. The median score was significantly higher for LMIC participants (7.31) compared to HIC participants (5.70). The political KAP scores were similar between HIC and LMIC participants. Spearman correlation showed that personal knowledge and personal attitude and perception were inversely correlated (Table 2).
Table 2: Cumulative median and mean scores per assessment for all participants, and stratified for high-income country (HIC) and low- and middle-income (LMIC) country participants. Spearman correlation results are shown for the comparison of knowledge and personal attitude and perception scores.
Knowledge assessment
Only a small proportion (30.2%) of participants knew that antibiotic resistance will account for more deaths than cancer in the next 30 years. The level of knowledge of this AMR burden was higher in participants from LMIC (48.6%) than those from HIC (25.6%) (p < 0.001). More than half of all participants (67.2%) answered correctly that antibiotics cannot be used for viral infections. Most participants (81.8%) were well-informed that antibiotics misuse and abuse in animal husbandry can negatively affect human health, which again differed significantly between LMIC participants (92.9%) and HIC participants (79.0%) (p < 0.05). The vast majority of participants (78.9%) were aware that emerging resistant organisms from other countries or continents can become a problem in their own country. Less participants (69.8%) knew that it is not easy to discover and produce new antibiotics. The role of hygiene in tackling AMR was acknowledged by half (54.4%) of all participants with higher scores seen in LMIC participants (75.7%) than HIC participants (49.1%) (p < 0.001).
[Figure 2: Barplot on knowledge among all participants, and stratified for high-income country (HIC) and low- and middle-income country (LMIC) participants.The correct answer option (yes/no) is shown behind each statement. Significance as *** for p < 0.001, ** for p < 0.01 and * for p < 0.05]
Univariate and multivariate logistic regressions were performed to identify which demographic factors are main determinants for the difference in knowledge levels between participants. Education level was significantly associated with both good and fair knowledge scores (p < 0.05). The proportion of getting good scores declined as the education level decreased (54.8% of master/doctoral, 41.3% of bachelor, 22.5% in lower education graduates). Upon multivariate analysis, the association between education level and good and fair score remained significant but only between master/PhD holders and high school graduates (79.6% vs 38.8% for fair score, respectively). Another associated factor for good and fair knowledge scores was a scientific field of expertise. Furthermore, good knowledge scores were significantly associated with age (< 40 years vs. 40–60 years) and country of nationality (Spanish vs. Dutch).
[Table 3: Univariate (odds ratio, OR) and multivariate analysis (adjusted odds ratio, aOR) of good and fair knowledge and demographic variables.]
Perception and attitude assessment
To assess the personal perception and attitude towards antimicrobial consumption and resistance, the perception and attitude questionnaire assessed the behavior about antibiotics use and familiarity with AMR as a public health concern. The results indicated that 38.3% of LMIC participants consumed antibiotics quite often (i.e. at least once every three years) compared to a significant lower proportion of 8.8% among HIC participants (p < 0.001). Regarding the completion of an antibiotic treatment, 78.8% of LMIC participants reported that they always finish their treatment whereas this perception and practice was significantly higher among HIC participants with 95.2% reporting to always finish their antibiotic treatment (p < 0.001). Furthermore, only 5.5% of all participants did not believe that antibiotic resistance can become a health emergency issue, and this perception was more prevalent among LMIC participants (10.5% of LMIC participants shared this view). This difference in proportion was not statistically significant between LMIC and HIC participants. Regarding the actors that should be held responsible for tackling AMR, 30.9% of LMIC participants reported that hospitals, veterinary clinics, and pharmaceutical industries are responsible for AMR and should solve the problem on their own. From the HIC perspective, only 10.9% shared this view and the difference was statistically significant (p < 0.001) between the two subsets. Lastly, 75% reported that the current COVID-19 pandemic increased their awareness of public health and the role of government in outbreak prevention and preparedness.
[Figure 3: Barplot on good personal attitude and perception among all participants, and stratified for high-income country (HIC) and low- and middle-income country (LMIC) participants. Significance as *** for p < 0.001, ** for p < 0.01 and * for p < 0.05.]
Of all participants, 41.6% and 83.8% had a good and fair personal attitude and perception, respectively. Upon univariate and multivariate analysis several factors were found to be associated with a good and fair attitude and perception (Table 4). Similarly as described for good and fair knowledge scores, higher levels of education and scientific field of expertise were associated with a better attitude and perception. Additionally, LMIC participants were less likely to have a good or fair perception and attitude with an adjusted OR of 0.33 (95% CI 0.14–0.75) for a good score compared to HIC participants.
[Table 4: Univariate (odds ratio, OR) and multivariate analysis (adjusted odds ratio, aOR) of good and fair personal attitude and perception and demographic variables]
Political activity and involvement
To capture the comprehension of the current political effort and plan in tackling AMR, the questionnaire assessed the participants’ knowledge and awareness about the current state of political involvement and engagement related to main pillars in fighting against AMR. Only 26.7% of HIC participants reported that a national action plan on antimicrobial resistance (NAP-AMR) has been implemented, whereas 46.9% of LMIC participants were aware of the implementation of a NAP-AMR in their country. This difference was statistically significant (p < 0.01). More than half (53.1%) of LMIC participants reported that AMR is gaining more popularity in policies and regulations in the country, compared to a smaller proportion (39.2%) of HIC participants. More than half of HIC participants (56.1%) reported that AMR interventions both address human and animal health, which was statistically different from LMIC participants (40.3%) (p < 0.05). In accordance, more LMIC participants (51%) reported that AMR plans mainly focus on human health and not on the contribution of livestock. A significantly smaller proportion (33.9%) of HIC participants agreed with this statement (p < 0.05). More HIC participants (34.7%) than LMIC participants (19.7%) reported that hospitals in their regions have taken actions to control AMR. On the contrary, almost half of LMIC participants (47.6%) indicated that hospitals are willing to take action, but lack funding to do so. The proportion that highlighted this financial restraint was only 39.3% among HIC participants (p < 0.05). When the participants were inquired about the national budget and funding for AMR, not even half (35.6%) of all participants reported that the funding and resources had increased in recent years and would be increasing more in the future. Nearly everyone (80.1%) was well aware of the fact that a One Health approach should be integrated in monitoring AMR in their country, and more interventions should integrate this interdisciplinary vision. This awareness was, however, more pronounced among LMIC individuals (87.8%) compared to HIC individuals (72.8%) (p < 0.05).
[Figure 4: Barplot on first part of statements assessing the political knowledge, attitude and perception (KAP) among all participants, and stratified for high-income country (HIC) and low- and middle-income country (LMIC) participants. Significance as *** for p < 0.001, ** for p < 0.01 and * for p < 0.05.]
[Figure 5: Barplot on second part of statements assessing the political knowledge, attitude and perception (KAP) among all participants, and stratified for high-income country (HIC) and low- and middle-income country (LMIC) participants. Significance as *** for p < 0.001, ** for p < 0.01 and * for p < 0.05.]
None of the sociodemographic and occupational variables were associated with overall political KAP scores (Supplementary file 3). The last section of the survey contained four open questions to get a better understanding of the current strategies and interventions that address AMR within the participant’s governmental level. It aimed to identify the challenges in designing and implementing new AMR strategies. Representatives from all countries addressed the need of sufficient financial resources, promoting awareness and educating the general public on the involved risks, and tightening of the regulations and prescription behaviours to make antibiotics less easily accessible (Supplementary file). Participants from the Netherlands in particular highlighted the need of a coherent international approach rather than a national strategy to mitigate the AMR burden. Many Dutch participants also emphasized on the need for more research on the environmental transmission, especially the contribution of livestock and the transmission via wastewater. Participants from Myanmar unanimously reported that the lack of knowledge and awareness of AMR among the general public,and politicians and healthcare workers should be the main focus area to address AMR, whereas there was less mention of the environmental aspects in spread and control of AMR. One Burmese representative said that “implementing policies on AMR (example, an act to reduce antibiotics in animal feed) will be complicated; it could have an effect on markets and economies of farmers”. Various participants from Spain reported that surveillance programs have been developed to better monitor the presence of antibiotic resistant organisms and residues in food products.
In terms of interventions in place, most participants mentioned national and provincial interventions and action plans, and participants working for local authorities mainly mentioned that AMR is not being addressed on a regional level. As an example, one Spanish participant reported that “at the municipal level, we do not have direct powers on how to influence this issue”. This was in accordance with the funding source for AMR interventions, as the majority of financial resources were national in all countries.