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. 2024 Dec 17;79(6):1346-1353.
doi: 10.1093/cid/ciae313.

Socioeconomic Disparities and the Prevalence of Antimicrobial Resistance

Lauren N Cooper  1 , Alaina M Beauchamp  2 , Tanvi A Ingle  3 , Marlon I Diaz  4 , Abdi D Wakene  1 , Chaitanya Katterpalli  5 , Tony Keller  5 , Clark Walker  5 , Seth Blumberg  6   7 , Sanjat Kanjilal  8   9 , Jonathan H Chen  10 , Alexander P Radunsky  11 , Zachary M Most  12 , John J Hanna  1   11   13 , Trish M Perl  2   11 , Christoph U Lehmann  1 , Richard J Medford  1   11   13   14
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Socioeconomic Disparities and the Prevalence of Antimicrobial Resistance

Lauren N Cooper et al. Clin Infect Dis. .

Abstract

Background: The increased prevalence of antimicrobial-resistant (AMR) infections is a significant global health threat, resulting in increased disease, deaths, and costs. The drivers of AMR are complex and potentially impacted by socioeconomic factors. We investigated the relationships between geographic and socioeconomic factors and AMR.

Methods: We collected select patient bacterial culture results from 2015 to 2020 from electronic health records of 2 expansive healthcare systems within the Dallas-Fort Worth, Texas, metropolitan area. Among individuals with electronic health records who resided in the 4 most populous counties in Dallas-Fort Worth, culture data were aggregated. Case counts for each organism studied were standardized per 1000 persons per area population. Using residential addresses, the cultures were geocoded and linked to socioeconomic index values. Spatial autocorrelation tests identified geographic clusters of high and low AMR organism prevalence and correlations with established socioeconomic indices.

Results: We found significant clusters of AMR organisms in areas with high levels of deprivation, as measured by the area deprivation index (ADI). We found a significant spatial autocorrelation between ADI and the prevalence of AMR organisms, particularly for AmpC β-lactamase and methicillin-resistant Staphylococcus aureus, with 14% and 13%, respectively, of the variability in prevalence rates being attributable to their relationship with the ADI values of the neighboring locations.

Conclusions: We found that areas with a high ADI are more likely to have higher rates of AMR organisms. Interventions that improve socioeconomic factors such as poverty, unemployment, decreased access to healthcare, crowding, and sanitation in these areas of high prevalence may reduce the spread of AMR.

Keywords: antimicrobial resistance; antimicrobial-resistant organisms; area deprivation index; social vulnerability index; sociodemographic factors.

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Conflict of interest statement

Potential conflicts of interest . The authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Figures

Figure 1.
Figure 1.
A, Area deprivation index (ADI) decile ranks for the 4 most populous counties of the Dallas–Fort Worth, Texas, metropolitan area. B, Social vulnerability index (SVI) percentile ranks for the same 4 counties. Numbers of census block groups (A) and census tracts (B) for each rank are identified in parentheses.
Figure 2.
Figure 2.
Antimicrobial resistance (AMR) prevalence per 1000 census tract population in 4 counties in the Dallas–Fort Worth, Texas, metropolitan area. Each panel indicates the AMR prevalence per 1000 census tract population for an organism, using a gradient scale ranging from light for a prevalence of <1 count per 1000 census tract population to dark for a prevalence of >9 counts per 1000 census tract population. The number of census tracts for each prevalence is indicated in parentheses. A, AmpC β-lactamase (AmpC). B, Carbapenem-resistant Enterobacterales (CRE). C, ESBL—extended-spectrum β-lactamase (ESBL). D, Methicillin-resistant Staphylococcus aureus (MRSA). E, Vancomycin-resistant Enterococcus (VRE).
Figure 3.
Figure 3.
Hot and cold spot analysis of antimicrobial resistance (AMR) prevalence per 1000 population at the census tract level for the 4 most populous counties in the Dallas–Fort Worth metropolitan area. A, AmpC β-lactamase (AmpC). B, carbapenem-resistant Enterobacterales (CRE). C, Extended-spectrum β-lactamase (ESBL). D, Methicillin-resistant Staphylococcus aureus (MRSA). E, Vancomycin-resistant Enterococcus (VRE). The significance level for all panels is P ≤ .05, and the number of census tracts for each category is provided parenthetically.
Figure 4.
Figure 4.
Colocation of the area deprivation index (ADI) and antimicrobial resistance (AMR) prevalence of 5 organisms of interest, including AmpC β-lactamase (AmpC; A), carbapenem-resistant Enterobacterales (CRE; B), extended-spectrum β-lactamase (ESBL; C), methicillin-resistant Staphylococcus aureus (MRSA; D), and vancomycin-resistant Enterococcus (VRE; E). Census block groups in which higher AMR prevalence can be attributed to higher values of ADI in surrounding block groups are labeled as high-high, while lower AMR prevalence attributed to lower values of ADI in surrounding block groups are labeled as low-low. The significance level for all panels is P ≤ .05, and the number of census block groups for each category is provided parenthetically.
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References

    1. World Health Organization . Antimicrobial resistance. Available at: https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance. Accessed 5 September 2023.
    1. Wernli D, Harbarth S, Levrat N, Pittet D. A “whole of United Nations approach” to tackle antimicrobial resistance? A mapping of the mandate and activities of international organisations. BMJ Glob Health 2022; 7:e008181. - PMC - PubMed
    1. Centers for Disease Control and Prevention . COVID-19: U.S. impact on antimicrobial resistance, special report 2022. Hyattsville, MD: Centers for Disease Control and Prevention, 2022.
    1. Antimicrobial Resistance Collaborators . Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet 2022; 399:629–55. - PMC - PubMed
    1. Kim EJ, Marrast L, Conigliaro J. COVID-19: magnifying the effect of health disparities. J Gen Intern Med 2020; 35:2441–2. - PMC - PubMed

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