Causal Effect Estimation Under Spatial Confounding and Interference R package spaci version 0.1.1 Implements the distance-adjusted propensity score with interference (iDAPS) and recoverU+ methods for estimating the average treatment effect on the treated (ATT) from spatial observational data in the presence of both spatial confounding and spatial interference. iDAPS matches units on a data-driven composite of propensity-score distance, spatial proximity and neighbourhood-exposure distance. recoverU+ is a doubly robust estimator that augments the propensity-score and control-outcome models with a partially recovered spatial confounder and a neighbourhood-exposure term. The package also provides the naive propensity score, DAPS and recoverU comparators, and a simulator for the spatial confounding/interference data-generating process. Software Depends: R (>= 4.1.0) Imports: stats Suggests: geoR, ggplot2, readxl, testthat (>= 3.0.0), knitr, rmarkdown Isqeel Ogunsola <isqeel.ogunsola@postgrad.manchester.ac.uk> Comprehensive R Archive Network (CRAN) Isqeel Ogunsola [aut, cre], Olatunji Johnson [aut], Thomas House [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=spaci/LICENSE) 2026-09-21 application/tgz https://CRAN.R-project.org/package=spaci doi:10.32614/CRAN.package.spaci