Antibiotic resistance and COVID-19, the growing infectious disease pandemics of the 21st century: Modelling the burden and transmission of antibiotic resistance and prevention of COVID-19

Noortje Grejanne Godijk

Research output: ThesisDoctoral thesis 1 (Research UU / Graduation UU)

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Abstract

Antibiotic resistant bacteria (ARB) and COVID-19 are both important infectious diseases of the 21st century. During my PhD I firstly summarized the available knowledge on ARB transmission pathways, I studied whether ARB increase the total number of infections or whether they replace infections with susceptible bacteria and I explored a new method to estimate the ARB disease burden. I identified a knowledge gap between the frequency of exposure to ARB and the probability of ARB acquisition. Certain exposure events may be high-risk, but if exposure is infrequent, the contribution of a more frequent, low-risk exposure may be higher. Furthermore, I found that for Escherichia coli, replacement of susceptible infections with resistant infections is more likely than an increase in the total number of infections. This implies that only different characteristics of resistant E. coli, e.g. a higher mortality, can cause an increase of the disease burden, rather than an increasing number of infections. Secondly, I investigated which measures are effective in inhibiting further spread of COVID-19. Self-initiated measures, such as hand washing, distancing and face masks can reduce infections by more than 50% and postpone the peak number of infected, if virus awareness is quickly raised. In addition, we found that the spread of other infectious diseases is influenced by corona measures. For example, Dutch heterosexuals indicated that not being able to make an appointment with the general practitioner or the sexual health center was the main reason that they were unable to take a test for sexually transmitted diseases.
Original languageEnglish
Awarding Institution
  • University Medical Center (UMC) Utrecht
Supervisors/Advisors
  • Bonten, Marc, Primary supervisor
  • Bootsma, Martin, Co-supervisor
Award date1 Sept 2022
Publisher
Print ISBNs978-94-6458-483-7
DOIs
Publication statusPublished - 1 Sept 2022

Keywords

  • antibiotic resistance
  • COVID-19
  • mathematical modelling
  • epidemiology
  • E. coli
  • ESBL
  • corona virus
  • burden
  • transmission
  • antibiotic resistant bacteria

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