Selected article for: "capacity factor and epidemiological outcome"

Author: Wei Aun Yap; Dhesi Baha Raja
Title: Time-variant strategies for optimizing the performance of non-pharmaceutical interventions (NPIs) in protecting lives and livelihoods during the COVID-19 pandemic
  • Document date: 2020_4_17
  • ID: 180x1fvb_17
    Snippet: Epidemiological outcomes. Epidemiological outcome measures and non-epidemiological proxy measures are simulated. Epidemiological outcome measures are: (i) Percent of the initial population ultimately infected on Day 365, (ii) deaths per 1,000, (iii) peak prevalence and incidence rates, (iv) days to peak prevalence and incidence. Increased deaths due to an overwhelmed health system are not counted under the deaths per 1,000 outcome measure but are.....
    Document: Epidemiological outcomes. Epidemiological outcome measures and non-epidemiological proxy measures are simulated. Epidemiological outcome measures are: (i) Percent of the initial population ultimately infected on Day 365, (ii) deaths per 1,000, (iii) peak prevalence and incidence rates, (iv) days to peak prevalence and incidence. Increased deaths due to an overwhelmed health system are not counted under the deaths per 1,000 outcome measure but are modelled using a proxy measure which is the sum of the squares of daily prevalence throughout the simulation period that is above a health system capacity threshold. The health system capacity threshold is based on the world average hospital beds per capita (World Development Indicators 2020) and adjusted for the mean duration of hospitalization, the proportion of symptomatic "I" cases, the proportion of symptomatic patients requiring hospitalization. The daily prevalence above this threshold was squared to penalize extreme breaches of this day-to-day capacity threshold. This measure of an overwhelmed health system is referred to here as the 'over-capacity factor'.

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