TRACING THE SPATIO TEMPORAL PATH OF PEAK MALARIA INCIDENCES USING WALK ANALYSIS AND GIS

Abstract

Epidemic risk is a dynamic phenomenon with changing geographic pattern based on the temporal variations, in determinant factors including weather and other eco epidemiological characteristics of area at high risk. Epidemic early warning systems should take account of non uniform effects of these factors by space and time and hence temporal dimensions could be considered in spatial models of epidemic risks (Abeku, 2004).Based on this concept, the present study is aimed to analyse the geographical based time expansion of malarial transmission. Monthly malaria incidences data for a period of 101 months (Jan 1996- May 2004) recorded from Salem distrct, India were used for the study To estimate the spatial effects based on two components i.e., the overall difference among the regions and the rate of change over time for these regions, a spatio-temporal analysis for fixed and random effects are performed. The model was used to identify if additional cases are coming from malarial predominant areas (High Incidence areas), from moderate areas, or from low incidence areas. The conditional auto regressive model is used to model the random effects. Correlated Walk and Random Walk analysis is used to show the movement of the disease over time. Markov Chain Monte Carlo simulation is used to obtain estimates of the posterior and predictive quantities of interest. CrimeStat is used to analyze statistically and Arcview 3.2 is used to map the results at different time periods and maps of smoothed time incidence. The results have significant implication over space and time and can be used for malaria control activities in the study area and also other infected areas. Based on the time and space aspect, the regional malarial control authorities have an opportunity to assess the risk of encountering the disease infection and to plan prevention measures accordingly. This study also provides an indication to any association between time trend and basic malarial incidence.