<p>Hospital-acquired infections (HAIs) are a major public health challenge worldwide. They involve complex and varied transmission dynamics between healthcare workers (HCWs) and patients. Different hospital wards have different risks for acquiring and spreading HAIs. Intensive care units (ICUs) have a higher transmission risk than non-ICU wards. To evaluate how this heterogeneity influences HAI transmission dynamics, we developed a two-patch mathematical model. It represents ICU and non-ICU wards and focuses on HCW mobility between them. Our analysis used a Lagrangian mobility perspective. We found that maintaining hand hygiene compliance of at least 80% can lower the basic reproduction number below one. However, if 20% or more of HCWs spend significant time in the ICU, the transmission risk remains high. These results highlight the importance of considering ward-specific risks. They are crucial for developing effective disease control strategies.</p>

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Modelling the spatiotemporal variations in hospital-acquired infections with fractional derivatives

  • Salamida Daudi,
  • Mlyashimbi Helikumi,
  • Eva Lusekelo,
  • Steady Mushayabasa

摘要

Hospital-acquired infections (HAIs) are a major public health challenge worldwide. They involve complex and varied transmission dynamics between healthcare workers (HCWs) and patients. Different hospital wards have different risks for acquiring and spreading HAIs. Intensive care units (ICUs) have a higher transmission risk than non-ICU wards. To evaluate how this heterogeneity influences HAI transmission dynamics, we developed a two-patch mathematical model. It represents ICU and non-ICU wards and focuses on HCW mobility between them. Our analysis used a Lagrangian mobility perspective. We found that maintaining hand hygiene compliance of at least 80% can lower the basic reproduction number below one. However, if 20% or more of HCWs spend significant time in the ICU, the transmission risk remains high. These results highlight the importance of considering ward-specific risks. They are crucial for developing effective disease control strategies.