Antibiotics (Apr 2022)

Evaluation of the Correspondence between the Concentration of Antimicrobials Entering Sewage Treatment Plant Influent and the Predicted Concentration of Antimicrobials Using Annual Sales, Shipping, and Prescriptions Data

  • Takashi Azuma,
  • Takashi Nakano,
  • Ryuji Koizumi,
  • Nobuaki Matsunaga,
  • Norio Ohmagari,
  • Tetsuya Hayashi

DOI
https://doi.org/10.3390/antibiotics11040472
Journal volume & issue
Vol. 11, no. 4
p. 472

Abstract

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The accuracy and correspondence between the measured concentrations from the survey and predicted concentrations on the basis of the three types of statistical antimicrobial use in Japan was evaluated. A monitoring survey of ten representative antimicrobials: ampicillin (APL), cefdinir (CDN), cefpodoxime proxetil (CPXP), ciprofloxacin (CFX), clarithromycin (CTM), doxycycline (DCL), levofloxacin (LFX), minocycline (MCL), tetracycline (TCL), and vancomycin (VMC), in the influent of sewage treatment plant (STP) located in urban areas of Japan, was conducted. Then, the measured values were verified in comparison with the predicted values estimated from the shipping volumes, sales volumes, and prescription volumes based on the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB). The results indicate that the correspondence ratios between the predicted concentrations calculated on the basis of shipping and NDB volumes and the measured concentrations (predicted concentration/measured concentration) generally agreed for the detected concentration of antimicrobials in the STP influent. The correspondence ratio on the basis of shipping volume was, for CFX, 0.1; CTM, 2.9; LFX, 0.5; MCL, 1.9; and VMC, 1.7, and on the basis of NDB volume the measured concentration was CFX, 0.1; CTM, 3.7; DCL, 0.4; LFX, 0.7; MCL, 1.9; TCL, 0.6; and VMC, 1.6. To our knowledge, this is the first report to evaluate the accuracy of predicted concentrations based on sales, shipping, NDB statistics and measured concentrations for antimicrobials in the STP influent.

Keywords