A stochastic model for relative risk estimation of leptospirosis in Malaysia

• Published in: Journal of Physics: Conference Series
• Main Author: Ideris S.H.; Malim M.R.; Shaadan N.
• Format: Conference paper
• Language: English
• Published: Institute of Physics Publishing 2019
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076096871&doi=10.1088%2f1742-6596%2f1366%2f1%2f012118&partnerID=40&md5=da0a9fabba17801d30cdc3585efd005e

The relative risk of a disease is the observed probability that a member of an exposed group will develop the disease relative to the expected probability that a member of a susceptible group will develop the same disease. The estimation of relative risk is important for disease mapping; it is a method used to illustrate the geographical distribution of a disease occurrence for identifying areas that need more attention. Better estimates of risk would subsequently produce more accurate maps of disease risk. The study on relative risk estimation of leptospirosis in Malaysia is very scarce. Most of the related studies involved only the demographic of the disease. Furthermore, most of the mathematical modelling and statistical analyses used for disease transmission models have been deterministic; do not consider the potential of random effects. Thus, the objective of this study is to propose a discrete-time discrete-space stochastic model for relative risk estimation of leptospirosis in Malaysia based on a SIR-SI transmission model. The proposed model was demonstrated using Malaysia leptospirosis dataset (2012-2016) to estimate and analyse the expected relative risks of leptospirosis for all states. The results showed that the averages of estimated relative risks are between 0.340 and 2.898. Kelantan and Terengganu are the two most vulnerable states of leptospirosis for every epidemiology year from 2012 to 2016. © Published under licence by IOP Publishing Ltd.