Estimating the effect of increasing ambient temperature on antimicrobial resistance in China: A nationwide ecological study with the difference-in-differences approach

Changing climate and socioeconomic factors contribute to global antimicrobial resistance

Climate change poses substantial challenges in containing antimicrobial resistance (AMR) from a One Health perspective. Using 4,502 AMR surveillance records involving 32 million tested isolates from 101 countries (1999-2022), we analyzed the impact of socioeconomic and environmental factors on AMR. We also established forecast models based on several scenarios, considering antimicrobial consumption reduction, sustainable development initiatives and different shared socioeconomic pathways under climate change. Our findings reveal growing AMR disparities between high-income countries and low- and middle-income countries under different shared socioeconomic pathway scenarios. By 2050, compared with the baseline, sustainable development efforts showed the most prominent effect by reducing AMR prevalence by 5.1% (95% confidence interval (CI): 0.0-26.6%), surpassing the effect of antimicrobial consumption reduction. Key contributors include reducing out-of-pocket health expenses (3.6% (95% CI: -0.5 to 21.4%)); comprehensive immunization coverage (1.2% (95% CI: -0.1% to 8.2%)); adequate health investments (0.2% (95% CI: 0.0-2.4%)) and universal access to water, sanitation and hygiene services (0.1% (95% CI: 0.0-0.4%)). These findings highlight the importance of sustainable development strategies as the most effective approach to help low- and middle-income countries address the dual challenges of climate change and AMR.

Warming is Associated With More Encoded Antimicrobial Resistance Genes and Transcriptions Within Five Drug Classes in Soil Bacteria: A Case Study and Synthesis

The effect of warming on anti-microbial resistance (AMR) genes in the environment has critical implications for public health but is little studied. We collected published soil bacterial genomes from the BV-BRC database and tested the correlation between reported optimal growth temperature and the number of encoded AMR genes. Furthermore, we tested the relationship between temperature and AMR gene transcription in a natural ecosystem by analysing soil transcriptomes from a warming manipulation experiment in an Alaskan boreal forest. We hypothesised that there is a positive relationship between warming and AMR prevalence in gene content in bacterial genomes and transcriptomic sequences, and that this effect would vary by drug class. Regarding the bacterial genomes, we found a positive relationship between the fraction of encoded AMR genes and the reported optimal temperature of soil bacteria. The drug classes tetracycline and lincosamide/macrolide/streptogramin had the strongest positive relationship with reported optimal temperature. For the case study in a natural ecosystem, we found 61 significantly upregulated AMR gene-associated transcripts spanning eight drug classes in warmed plots. In the Alaskan soil samples, we found that warming elicited the strongest positive effect on transcripts targeting lincosamide/streptogramin, beta-lactam and phenicol/quinolone antibiotics. Overall, higher temperatures were linked to AMR gene prevalence.

Factors associated with clinical antimicrobial resistance in China: a nationwide analysis

BACKGROUND

Antimicrobial resistance (AMR) represents a critical global health threat, necessitating the identification of factors that contribute to its emergence and proliferation. We used a "One Health" perspective to evaluate the association of human and veterinary antibiotic usage, environmental factors, socio-economic factors, and health care factors with clinical AMR in China.

METHODS

We analyzed data from 31 provincial-level administrative divisions in China, encompassing 20,762,383 bacterial isolates sourced from the China Antimicrobial Resistance Surveillance System dataset between 2014 and 2022. A β regression model was used to explore the relationship of AMR with multiple variables. We also estimated the contribution of factors associated with AMR, and evaluated the avoidable risk of AMR under six different measures during 2019 according to available guidelines.

RESULTS

AMR had positive associations with human antibiotic usage, veterinary antibiotic usage, particulate matter smaller than 2.5 µm (PM2.5) level, population density, gross domestic product per capita, and length of hospital stay, and a 1 unit increase in the level of above independent variables were associated with a percentage change in the aggregate AMR of 1.8% (95% CI: 1.1, 2.5), 2.0% (95% CI: 0.6, 3.4), 0.9% (95% CI: 0.4, 1.4), 0.02% (95% CI: 0.01, 0.03), 0.5% (95% CI: 0.1, 0.8), and 8.0% (95% CI: 1.2, 15.3), respectively. AMR had negative associations with city water popularity, city greenery area per capita, and health expenditure per capita, and a 1 unit increase in the level of above independent variables were associated with a percentage change in the aggregate AMR of -4.2% (95% CI: -6.4, -1.9), -0.4% (95% CI: -0.8, -0.07), and -0.02% (95% CI: -0.04, -0.01), respectively. PM2.5 might be a major influencing factor of AMR, accounting for 13.7% of variation in aggregate AMR. During 2019, there was estimated 5.1% aggregate AMR could be attributed to PM2.5, corresponding to 25.7 thousand premature deaths, 691.8 thousand years of life lost, and 63.9 billion Chinese yuan in the whole country. Human antibiotic usage halved, veterinary antibiotic usage halved, city water popularity improved, city greenery area improved, and comprehensive measures could decrease nationwide aggregate AMR by 8.5, 0.5, 1.3, 4.4, and 17.2%, respectively.

CONCLUSIONS

The study highlights the complex and multi-dimensional nature of AMR in China and finds PM2.5 as a possible major influencing factor. Despite improvements in decreasing AMR, future initiatives should consider integrated strategies to control PM2.5 and other factors simultaneously to decrease AMR.

Enhancing antimicrobial resistance surveillance and research: a systematic scoping review on the possibilities, yield and methods of data linkage studies

BACKGROUND

Surveillance data on antimicrobial resistance (AMR) determinants such as antibiotic use, prevalence of AMR, antimicrobial stewardship, and infection prevention and control are mostly analysed and reported separately, although they are inextricably linked to each other. The impact of surveillance and research can be enhanced by linking these data. This systematic scoping review aims to summarize the studies that link AMR data and evaluate whether they yield new results, implications, or recommendations for practice.

METHODS

For this review, data linkage is defined as the process of linking records, from at least two independent data sources on either (I) at least two AMR determinants or (II) one AMR determinant and one or more general population characteristics. Data linkage should be performed on the level of a certain entity which, in the context of this review, can encompass persons, healthcare institutes, geographical regions or countries. A systematic literature search was performed on February 7th 2025 in Embase.com, PubMed and Scopus to identify AMR data linkage studies.

RESULTS

Forty-eight articles were included in our review. Most data linkage studies used two data sources, and most studies were published in the last 5 years (n = 23 in 2020-2024). A predominance of studies linked data on geographical location, and thirteen studies linked data on individual patient level. Findings demonstrate that the majority of studies (43/48) had added value and provided recommendations for clinical practice and future policies or had suggestions for further research and surveillance. Additionally, data linkage studies appeared to be suitable for hypothesis generating. Several limitations were identified. Most studies had ecological designs, which are prone to ecological fallacy and unobserved confounding, making it hard to establish causality.

CONCLUSION

This systematic scoping review showed that AMR data linkage studies are increasingly performed. They have potential to gain a more comprehensive understanding of AMR dynamics by generating hypotheses, assisting in optimisation of surveillance, and interpretation of data in the context of guideline/policy development. To increase the added value of data linkage, more studies should be performed to improve knowledge on methodological approaches, data access, data management, and governance issues.

CLINICAL TRIAL NUMBER

Not applicable.

Environmental Antimicrobial Resistance: Implications for Food Safety and Public Health

Antimicrobial resistance (AMR) is a serious global health issue, aggravated by antibiotic overuse and misuse in human medicine, animal care, and agriculture. This study looks at the different mechanisms that drive AMR, such as environmental contamination, horizontal gene transfer, and selective pressure, as well as the severe implications of AMR for human and animal health. This study demonstrates the need for concerted efforts across the scientific, healthcare, agricultural, and policy sectors to control the emergence of AMR. Some crucial strategies discussed include developing antimicrobial stewardship (AMS) programs, encouraging targeted narrow-spectrum antibiotic use, and emphasizing the significance of strict regulatory frameworks and surveillance systems, like the Global Antimicrobial Resistance and Use Surveillance System (GLASS) and the Access, Watch, and Reserve (AWaRe) classification. This study also emphasizes the need for national and international action plans in combating AMR and promotes the One Health strategy, which unifies environmental, animal, and human health. This study concludes that preventing the spread of AMR and maintaining the effectiveness of antibiotics for future generations requires a comprehensive, multidisciplinary, and internationally coordinated strategy.

Analyzing the correlation between quinolone-resistant Escherichia coli resistance rates and climate factors: A comprehensive analysis across 31 Chinese provinces

BACKGROUND

The increasing problem of bacterial resistance, particularly with quinolone-resistant Escherichia coli (QnR eco) poses a serious global health issue.

METHODS

We collected data on QnR eco resistance rates and detection frequencies from 2014 to 2021 via the China Antimicrobial Resistance Surveillance System, complemented by meteorological and socioeconomic data from the China Statistical Yearbook and the China Meteorological Data Service Centre (CMDC). Comprehensive nonparametric testing and multivariate regression models were used in the analysis.

RESULT

Our analysis revealed significant regional differences in QnR eco resistance and detection rates across China. Along the Hu Huanyong Line, resistance rates varied markedly: 49.35 in the northwest, 54.40 on the line, and 52.30 in the southeast (P = 0.001). Detection rates also showed significant geographical variation, with notable differences between regions (P < 0.001). Climate types influenced these rates, with significant variability observed across different climates (P < 0.001). Our predictive model for resistance rates, integrating climate and healthcare factors, explained 64.1% of the variance (adjusted R-squared = 0.641). For detection rates, the model accounted for 19.2% of the variance, highlighting the impact of environmental and healthcare influences.

CONCLUSION

The study found higher resistance rates in warmer, monsoon climates and areas with more public health facilities, but lower rates in cooler, mountainous, or continental climates with more rainfall. This highlights the strong impact of climate on antibiotic resistance. Meanwhile, the predictive model effectively forecasts these resistance rates using China's diverse climate data. This is crucial for public health strategies and helps policymakers and healthcare practitioners tailor their approaches to antibiotic resistance based on local environmental conditions. These insights emphasize the importance of considering regional climates in managing antibiotic resistance.