Selected article for: "âc yield and hospital bed capacity"

Author: Chen Wei; Zhengyang Wang; Zhichao Liang; Quanying Liu
Title: The focus and timing of COVID-19 pandemic control measures under healthcare resource constraints
  • Document date: 2020_4_19
  • ID: 5psqro9d_20
    Snippet: Both the duration of healthcare system overload and the final proportion of infected population were the measurements used to evaluate outbreak outcomes. The two measurements showed the same steep jump in value, indicating suppression failure ( Figure 4A , B, D&E). This jump was well captured by the suppression threshold derived from the daily reproduction number (the blue curves in respective panels). Compared to the hospital capacity in US, the.....
    Document: Both the duration of healthcare system overload and the final proportion of infected population were the measurements used to evaluate outbreak outcomes. The two measurements showed the same steep jump in value, indicating suppression failure ( Figure 4A , B, D&E). This jump was well captured by the suppression threshold derived from the daily reproduction number (the blue curves in respective panels). Compared to the hospital capacity in US, the high hospital bed capacity in Germany would yield a higher threshold for suppression ( Figure 4C , relative ∆β = 0.10). But such an advantage would be greatly reduced if interventions were delayed by a week ( Figure 4F , relative ∆β = 0.065). By regressing the threshold-level relative on the log-transformed number of beds per 1,000 population for a range of intervention onsets ( Figure 5A ), we found that hospital bed capacity would play the most important role with the intervention onset 2 days later than Wuhan. But having an advantage in hospital bed capacity would be less relevant if the onset was further delayed ( Figure 5B ). Specifically, the relative utility of transmission control in relation to bed capacity would be increased by 64.9% with a 7-day onset delay (slope shifted from 9.50 to 5.76).

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