ABSTRACT
COVID-19 is battling with many countries in the world, including Nigeria, and it has affected various sectors. Contact tracing technique without Statisticians in the team as recommended by WHO is being used in Nigeria to curb the spread of COVID-19 virus, yet confirmed cases is on the increase daily. This study proposed the integration of Statistical techniques for improving contact tracing efforts to stop the spread of the virus. A fitted model using the R package, and Adaptive Cluster Sampling mechanism was embedded. Parameters of the model were estimated using Markov Chain Monte-Carlo (MCMC) Algorithm with Winbugs software. Trace plot and correlogram were used for MCMC diagnostics to examine the goodness of fit of the model. The fitted model was used to obtain a predictive distribution for predicting the estimated number of COVID-19 carriers in Nigeria. The model has a good fit since It converged to the representation of the target posterior within the 95% highest posterior density (HPD) interval, its chains mixed well, and autocorrelation is quite similar at each lag. Estimated number of COVID-19 carriers were well estimated and higher in each state than confirmed cases. The present contact tracing process is inefficient to track COVID-19 carriers, hence integrated contact tracing technique with the involvement of Statisticians was recommended. .