Module 3 - Advanced Methods II: Time Series Analysis (TSA) and Spatial Analysis (SA)

This course is an introduction to both Time Series Analysis (TSA) and Spatial Analysis (SA), as well as to the use and analysis of respectively time-related and spatial health data. It combines practical skills with the study of the theory and applications for analysis of time-related data on one side, using R software and spatial data on the other using SaTScan software, Epi Info™ 7 and Google Earth, as they relate to population health.

Date & place: Monday 23rd to Friday 27th March 2015 at the Institute of Public Health of Serbia “Dr Milan Jovanović Batut”, Belgrade, Serbia.

Yo can download the programme here.

Content & Teaching methods

  • Introduction to R software
  • Time Series without seasonability
  • Time Series with seasonability
  • ARIMA / SARIMA
  • Box-Jenkins methodology
  • Spatial epidemiology
  • Mapping with Epi Info 7
  • Introduction to Google Earth
  • Spatial cluster detection & analysis with Sat Scan

Interactive lectures (10%) and practical sessions with hands-on exercises, case studies, and group work.

 

a) Understand how time-series analysis and to spatial analysis link to public health surveillance;

b) Get the basic epidemiological applications of a time series: description, explanation, prediction;

c) Understand the theoretical principles of time series, namely trend, periodicity, seasonality, white noise; and also the concepts of autocorrelation and stationarity, including application of transformations, filters, periodograms and correlograms.

d) Be acquainted with the use of TSA to forecast, predict and set thresholds for outbreak detection.

e) Identify the particularities of spatial data that distinguish it from non-spatial data,

f) Describe specific uses of spatial analysis within the field of public health,

g) Understand spatial cluster detection and analysis.

Coordinator of the module

  • Adela Paez Jimenez, MediPIET Scientific coordinator – ECDC, Sweden with the support of the National Institute of Public Health of Serbia

Facilitators / experts

  • Marc Sáez, Professor of Statistics and Econometrics Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Spain;
  • Maria Antonia Barceló, Associate Professor of Statistics and Econometrics Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Spain;
  • Joana Gomes Dias, Expert Biostatistics -Biostatistical, Geospatial and Molecular Surveillance Support Unit, European Centre for Disease Prevention and Control;
  • Diana Gómez-Barroso, Geographic Information System Specialist, Surveillance Department, National Center of Epidemiology, Instituto de Salud Carlos III- Spain;
  • Fernando Vallejo Ruiz, Biostatistician, Surveillance Department, National Center of Epidemiology, Instituto de Salud Carlos III- Spain;
  • Rebeca Ramis Prieto, Biostatistician, Surveillance Department, National Center of Epidemiology, Instituto de Salud Carlos III- Spain;
  • Uros Rakic, Geographic Information System Specialist, Institute of Public Health Serbia.

Administration and logistics

  • Enric Ibarz. Project Officer – MediPIET. FIIAPP, Spain
  • Roberto Medina. Support Officer – MediPIET. FIIAPP, Spain