DataCamp

London health data

The UK's National Health Service publishes weekly data for consultations at a number of "sentinel" clinics and makes this data available. A dataset for one week in February 2017 has been loaded for you to analyze. It is called london, and contains data for the 32 boroughs.

You will focus on reports of "Influenza-like illness", or more simply "Flu". Your first task is to map the "Standardized Morbidity Ratio", or SMR. This is the number of cases per person, but scaled by the overall incidence so that the expected number is 1.

The london object, a spatial data frame, and the sp package are ready for you.

Get a summary of the london data.
Use spplot() to draw a map of the number of reported flu case counts.
- Recall that spplot() takes a spatial data frame and a string naming the column, in this case Flu_OBS.
Calculate the overall incidence rate of flu in London.
- This is the total number of observed flu reports divided by the total population.
- Assign the result to r.
Calculate the expected number of cases per borough.
- This is the population multiplied by the overall rate.
- Assign the result to the Flu_EXP column of london.
Calculate the standardized morbidity ratio.
- This is the observed number divided by the expected number.
- Assign the result to the Flu_SMR column of london.
Use spplot() to draw a map of the SMR.

Take Hint (-30 XP)

Exercise

London health data

Instructions