The Premise Condition Index (PCI), proposed by Tun-Lin and colleagues in 1995, is a score that considers the conditions of a premise as well its yards and degree of shading. They hypothesized that the higher its value the greater the probability of the premise having the presence of Aedes aegypti. This study aimed to evaluate if there is a correspondence between PCI and Ae. aegypti infestation in four areas of a large city in the State of São Paulo, Brazil, if the inclusion of new categories related to the presence of animals in premises would increase the probability of detecting predictive areas for vector control actions and, if so, to propose an expanded PCI. The positivity of the premises for the presence of Ae. aegypti was modeled considering a Bernoulli probability distribution, in a Bayesian context using the Integrated Nested Laplace Approximation. The study showed that, in general, the higher the value of the PCI of a premise, the more likely it is to have the presence of Ae. aegypti, and the inclusion of information on the animals' presence can increase the discriminatory power of PCI. These results support the proposition of an extended PCI that would consider, in addition to the conditions of the premise, the presence of animals to classify it regarding the risk of the presence of Ae. aegypti.

Tun-Lin及其同事在1995年提出的前提条件指数（Premise Condition Index，PCI）是一个考虑前提条件，场地码数和阴影程度的分数。他们假设其价值越高，前提是埃及伊蚊存在的可能性越大。这项研究旨在评估PCI和Ae之间是否存在对应关系。埃及如果在房地内增加与动物的存亡有关的新类别，将增加巴西圣保罗州一个大城市的四个区域的虫害，从而增加发现媒介控制行动预测区域的可能性，如果有，建议扩展的PCI。Ae存在的前提的积极性。使用集成嵌套拉普拉斯近似在贝叶斯环境中考虑伯努利概率分布对aegypti进行建模。该研究表明，一般而言，前提的PCI值越高，则存在Ae的可能性就越大。aegypti，并且包含有关动物存在信息的信息都可以提高PCI的歧视能力。这些结果支持扩展PCI的提议，除了前提条件外，该扩展还将考虑e 伊蚊。