Pattern and Process: Application of local and space-time spatial statistics to epidemiological data.

1. Snow Cholera data
   1. Distribution of cases
   2. Distribution of pumps
   3. Thiessen polygons around pumps
   4. Gi(d) local spatial statistic
2. Trinidad malaria cases
   1. Spatial distribution of cases
   2. Temporal distribution of cases
   3. Cases by source
   4. Cases by parasite species
   5. k-NN space-time statistic
3. Encephalitis in Illinois and the Tiger Mosquito
4. Ticks on deer around a known Lyme focus
   1. Distribution of infested deer
   2. Distribution of uninfested deer
   3. changes of distribution over time
   4. Second order statistic

• Mapping:
  • Changing distribution of cases by country of origin over time (e.g., Nigeria, India or Guyana).
  • Grouping of all cases within a given area (e.g., 25 km2), and then mapping clusters of cases (e.g. as circles with size related to number of cases). Maps can then be made for a variety of categories (temporal, origin, species, etc.).
• Spatial statistics:
  • Moran's I for the distribution of cases for the three parasite species.
  • k-NN for cases from selected continents or countries.

Readings

Page by Andy Long. Comments appreciated.