Abstract
Diggle, Giorgi, Chipeta and Macfarlane describe how researchers can assist public health planners by collecting and analysing data on the occurrence of health outcomes in space and over time. They introduce spatial and spatio-temporal modelling to describe, predict and map the distribution of health outcomes. Drawing on extensive experience, the authors show how researchers, with public health practitioners, have used these methods to map snake bite incidence in Sri Lanka and Loa loa prevalence in Cameroon, and to maintain real-time surveillance systems to predict outbreaks of foodborne disease in the United Kingdom, legionellosis in New York and malaria in Malawi. The authors caution that the methods, while increasingly useful, require sophisticated understanding of statistics, and advise researchers to explain probability maps carefully to decision makers.
| Original language | English |
|---|---|
| Title of host publication | The Palgrave Handbook of Global Health Data Methods for Policy and Practice |
| Pages | 383-401 |
| Number of pages | 19 |
| ISBN (Electronic) | 9781137549846 |
| DOIs | |
| Publication status | Published - 1 Jan 2019 |
| Externally published | Yes |