TITLE

Analysis of Spatio-Temporal Disease Pattern using Spatial Auto Correlation Methods: Case of Acute Gastroenteritis in Coimbatore District, Tamilnadu, India

AUTHOR(S)
Joseph, Pawlin Vasanthi; Brindha, B.; Joshua, Vasna; Devi, Prashanthi; Balasubramanian, S.
PUB. DATE
July 2014
SOURCE
Indian Journal of Public Health Research & Development;Jul-Sep2014, Vol. 5 Issue 3, p296
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Background and Objectives: In epidemiology many of the infectious disease events do not occur randomly in geographical context but occur in clusters. Geographical or spatial analysis comes into play due to the existence of spatial dependence in data. The main objective was to examine the variation in the prevalence of Acute Gastroenteritis using space time autocorrelation methods and to explore possible factors that might have influenced these variations in the study area. Method: To identify the spatial similarity between the estimated Acute gastroenteritis values in the study region spatial autocorrelation was attempted to study the aggregated data of disease incidences. Different methods for measuring seasonal variations was adopted - Simple Averages, Ratio to Trend, Ratio to Moving Average and Link-Relative Methods. Results: The results show that a high incidence is recorded in the I and IV quarters, in all the taluks of Coimbatore district. It is observed that the incidence of Acute gastroenteritis is high in the months of January, February, March, April and November for all the taluks of Coimbatore district. The seasonal trend observations displayed a more comprehensive pattern of disease movement rather than the monthly pattern. Interpretation and conclusion: It is evident that Acute Gastroenteritis is a seasonally dependent disease with more number of cases increasing in the winter season and less cases in the summer season. This methodology will improve the accuracy of public health forecasting and will help in developing mechanisms to combat large seasonal surges of infectious diseases.
ACCESSION #
96892812

 

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