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  • Libisema: 1
  • CONFERENCE ROOM
  • That’s a pretty high rate. Are certain age groups or weight categories more affected?
  • We also need to analyse the travel history and interaction with wildlife. These factors could help us identify the source of the outbreak.
  • The incidence rate is calculated as (55,890 / 625,000) * 1,000, which gives us approximately 89.42 cases per 1,000 individuals.
  • Demographic analysis helps identify patterns and disparities in disease impact across subgroups.
  • Libisema: 2
  • Let’s run some statistical tests. We can use chi-square to check if co-morbidities are linked to infection rates.
  • 1 2 3 4 5
  • Agreed. We can also perform regression analysis to predict the likelihood of infection based on multiple variables like age, weight, and travel history.
  • Statistical tests, such as chi-square, assess associations between risk factors and infection rates.
  • Libisema: 3
  • I'll pull together all the data and clean it up for analysis. We should also check for any biases—we can’t afford to overlook anything.
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  • NURSE ELIZABETH
  • Data cleaning and preparation ensure accuracy in the subsequent quantitative analysis.
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