https://www.selleckchem.com/products/guanidine-thiocyanate.html Cancer atlases often provide estimates of cancer incidence, mortality or survival across small areas of a region or country. A recent example of a cancer atlas is the Australian cancer atlas (ACA), that provides interactive maps to visualise spatially smoothed estimates of cancer incidence and survival for 20 different cancer types over 2148 small areas across Australia. The present study proposes a multivariate Bayesian meta-analysis model, which can model multiple cancers jointly using summary measures without requiring access to the unit record data. This new approach is illustrated by modelling the publicly available spatially smoothed standardised incidence ratios for multiple cancers in the ACA divided into three groups common, rare/less common and smoking-related. The multivariate Bayesian meta-analysis models are fitted to each group in order to explore any possible association between the cancers in three remoteness regions major cities, regional and remote areas across Australia. The correlationple cancer types jointly. These proposed multivariate meta-analysis models could be useful when unit record data are unavailable because of privacy and confidentiality requirements. Publicly available spatially smoothed disease estimates can be used to explore additional research questions by modelling multiple cancer types jointly. These proposed multivariate meta-analysis models could be useful when unit record data are unavailable because of privacy and confidentiality requirements. Members of the Anopheles hyrcanus group have been incriminated as important malaria vectors. This study aims to identify the species and explore the insecticide susceptibility profile within the Anopheles hyrcanus group in Ubon Ratchathani Province, northeastern Thailand where increasing numbers of malaria cases were reported in 2014. Between 2013 and 2015, five rounds of mosquito collections were conducted using human la