A review of spatial causal inference methods for environmental and epidemiological applications

The scientific rigor and computational methods of causal inference have had great impacts on many disciplines, but have only recently begun to take hold in spatial applications. Spatial casual inference poses analytic challenges due to complex correlation structures and interference between the treatment at one location and the outcomes at others. In this paper, we review the current literature on spatial causal inference and identify areas of future work. We first discuss methods that exploit spatial structure to account for unmeasured confounding variables. We then discuss causal analysis in the presence of spatial interference including several common assumptions used to reduce the complexity of the interference patterns under consideration. These methods are extended to the spatiotemporal case where we compare and contrast the potential outcomes framework with Granger causality, and to geostatistical analyses involving spatial random fields of treatments and responses. The methods are introduced in the context of observational environmental and epidemiological studies, and are compared using both a simulation study and analysis of the effect of ambient air pollution on COVID-19 mortality rate. Code to implement many of the methods using the popular Bayesian software OpenBUGS is provided

An efficient strategy for evaluating new non-invasive screening tests for colorectal cancer: the guiding principles.

New screening tests for colorectal cancer (CRC) are rapidly emerging. Conducting trials with mortality reduction as the end point supporting their adoption is challenging. We re-examined the principles underlying evaluation of new non-invasive tests in view of technological developments and identification of new biomarkers. A formal consensus approach involving a multidisciplinary expert panel revised eight previously established principles. Twelve newly stated principles emerged. Effectiveness of a new test can be evaluated by comparison with a proven comparator non-invasive test. The faecal immunochemical test is now considered the appropriate comparator, while colonoscopy remains the diagnostic standard. For a new test to be able to meet differing screening goals and regulatory requirements, flexibility to adjust its positivity threshold is desirable. A rigorous and efficient four-phased approach is proposed, commencing with small studies assessing the test's ability to discriminate between CRC and non-cancer states (phase I), followed by prospective estimation of accuracy across the continuum of neoplastic lesions in neoplasia-enriched populations (phase II). If these show promise, a provisional test positivity threshold is set before evaluation in typical screening populations. Phase III prospective studies determine single round intention-to-screen programme outcomes and confirm the test positivity threshold. Phase IV studies involve evaluation over repeated screening rounds with monitoring for missed lesions. Phases III and IV findings will provide the real-world data required to model test impact on CRC mortality and incidence. New non-invasive tests can be efficiently evaluated by a rigorous phased comparative approach, generating data from unbiased populations that inform predictions of their health impact