The association between ambient temperature and antimicrobial resistance of Klebsiella pneumoniae in China: a difference-in-differences analysis

Unveiling the drivers of vancomycin-resistant enterococcus in China: A comprehensive ecological study

Background

Vancomycin resistant enterococci (VRE) are now considered a global public health issue. In this study, we explored the relationship between vancomycin resistance incidence and various demographic and climatic factors.

Methods

This retrospective study was performed between January 1st, 2014 and December 31st, 2021. Data covering the consumption of vancomycin, the prevalence of vancomycin resistance, and relevant demographics were collected. Spearman's rank correlation, beta regression, and spatial statistical analysis were performed using R version 4.2.2 and ArcGIS version 10.7.

Results

Spearman's rank correlation described the positive relation between vancomycin consumption and the prevalence of vancomycin resistant Enterococcus faecium (VREfm). Multiple regression analysis showed that vancomycin consumption, rural population, proportion of population aged ≥65, annual temperature, and bed number in medical institutions per thousand people were significantly correlated with VREfm prevalence (r = 56.22, p < 0.001; r = 0.0002, p < 0.001; r = 0.06, p < 0.001; r = -0.07, p < 0.001; and r = -0.37, p < 0.001, respectively).

Conclusions

Vancomycin utilization was the predominant factor contributing to VREfm resistance; the effects of rural populations and the proportion of the population aged ≥ 65 were significant but relatively minimal. Annual temperature and the number of beds in medical institutions per thousand people were protective factors against VREfm.

Environmental factors influencing the development and spread of resistance in erythromycin-resistant streptococcus pneumoniae

Bacterial drug resistance is becoming increasingly serious, this study aims to investigate the relationship between the resistance rate of erythromycin-resistant Streptococcus pneumoniae (SP) and reasons for the epidemic under complex geographical and climatic factors in China. Data spanning from 2014 to 2021, including drug resistance rates, isolate rates, meteorological variables, and demographic statistics, were collected from the China Antimicrobial Resistance Monitoring System, the China Statistical Yearbook and China Meteorological Website. Our analysis involved nonparametric tests and the construction of multifaceted regression models for rigorous multivariate analysis. Single-factor analysis revealed significant differences in the resistance rate and isolate rate of erythromycin-resistant SP across different regions characterized by Hu Huanyong lines or different climate types. Multivariate regression analysis indicated positive correlations between the drug resistance rate and temperature, Subtropical climate, Gross Domestic Product (GDP), Hu Huanyong line, and the highest temperature in the past period (Tm); the isolate rate showed a positive correlation with regional GDP and a negative correlation with monsoon climate. The model developed in this study provides valuable insights into the resistance rate and potential relationships of erythromycin-resistant SP under complex meteorological conditions in China.

Monitoring Multi-Drug Resistant Klebsiella pneumoniae in Kitagata Hot Spring, Southwestern Uganda: A Public Health Implication

Background

The concerning frequency of K. pneumoniae in various recreational settings, is noteworthy, especially regarding multi-drug resistant (MDR) strains. This superbug is linked to the rapid spread of plasmids carrying these resistance genes. The objective of this study was to evaluate the spatiotemporal prevalence of MDR-K. pneumoniae in the Kitagata hot spring, Southwestern Uganda.

Methods

A laboratory-based descriptive longitudinal study was conducted between May and July 2023. During rainy and dry seasons, we collected eighty water samples in the morning and evening from the hot spring. The temperature at each point was measured prior to sample collection, and two samples were obtained at varying depths. 5 mL of each homogenized sample were pre-enriched in brain heart infusion broth, and subsequently in both blood and violet red bile agar. The Kirby-Bauer disk diffusion method was performed, followed by the detection of carbapenemase (CR) and extended-spectrum β-lactamase (ESBL) production. Polymerase chain reaction showed resistance genes viz. bla TEM, bla CTX-M and bla KPC. Data were analyzed using SPSS-20 to obtain chi-square tests and regression analysis.

Results

K. pneumoniae accounted for 30.0% of isolates obtained from Kitagata hot springs, with all isolates classified as multi-drug resistant. All isolates were resistant to ampicillin, rifampicin, ceftazidime, and azithromycin (79.2%). Additionally, 95.8% of isolates harbored bla TEM gene alone and both bla TEM and bla CTX genes, followed by bla KPC alone (33.3%), with 25% harboring all three resistance genes. During the dry season, K. pneumoniae had a higher prevalence (35.0%) compared to the wet season (25.0%). The prevalence of MDR-K. pneumoniae significantly increased over the course of the study. The presence of the three studied resistance genes in the isolates showed a positive correlation with the second phase of sample collection and the dry season but exhibited a negative correlation with temperature, except for isolates harboring either bla TEM alone or bla TEM+KPC+CTX genes.

Conclusion

Kitagata hot spring serves as a hotspot for continuous dissemination and acquisition of MDR-K. pneumoniae harboring resistance genes that encode for ESBL and CR production. The healthcare sector ought to implement an ongoing monitoring and surveillance system as well as robust antimicrobial resistance stewardship programs aimed at delivering health education to the community.

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.