As a result of the US Supreme Court's June 2022 decision in Dobbs v. Jackson Women's Health Organization, the landscape of reproductive health care in the United States is in the midst of seismic and rapid change. Within 100 days of the ruling, fourteen states either banned or severely restricted abortion provision; over the coming months, many more are likely to follow suit. The abrupt changes in access to abortion in the US are without precedent in terms of the number of individuals who are affected and the number of states in which there remains substantial uncertainty around enactment of further restrictions in the near future. This project addresses the urgent need for baseline data to capture the impact of state abortion restrictions expected over the coming months on the health of pregnant people, as well as the need for high quality estimates of abortion incidence both within and outside of the formal health care system. Without these data, primary public health indicators for the nation will not be available, nor will policy makers, program developers, service providers, researchers and the public have the research-based evidence needed to understand the impact of these abortion policies now and going forward. To address this critical need, we propose four linked aims. Starting in the first month of the R61 phase (Aim 1), we will begin data collection activities to measure change in abortion within and outside the formal health sector during a period of anticipated rapid state-level policy change. In Aim 1a, we will collect data on abortions occurring within the formal health sector using a new and adaptive monthly abortion surveillance system, surveying representative samples of health facilities providing abortion care. We will produce public facing monthly estimates of facility-based abortion incidence nationally, leveraging decades of historical facility-level abortion data in a Bayesian hierarchical model to improve precision. In Aim 1b, we will collect data on abortions occurring outside of the formal health care sector, measuring abortion-related complications and the healthcare needs of people self-managing abortions (SMA) by surveying SMA users and providers. Data collected in Aim 1 will be used in the R33 phase to measure the impact of state policy change and inform estimation of abortion incidence outside the formal health care sector. In Aim 2, we will assess the impact of state abortion restrictions implemented during project year 1 on the number of people obtaining facility-based abortions and the gestational age of their pregnancies, and the incidence of interstate travel to obtain facility- based abortion care. In Aim 3, we will adapt a methodology used extensively outside of the US to estimate abortion under restrictive conditions to estimate self-managed abortion incidence outside of the formal health sector. Finally, in Aim 4, we will combine data on facility-based and self-managed abortions to estimate the national incidence of abortion and abortion-related health outcomes.

The landscape of reproductive health care in the United States is in the midst of seismic and rapid shifts; abrupt changes in access to abortion in the US are without precedent in terms of the number of individuals who are affected, the number of states in which there remains substantial uncertainty around abortion policy changes in the near future, and the scale of potential effects on the lives of pregnant people. This project addresses the urgent need to assess the impact of state abortion restrictions on the health of pregnant people, as well as the need for high quality estimates of abortion incidence both within and outside of the formal health care system as these restrictions are implemented. This study will advance the field of abortion measurement by establishing estimation approaches that encompass both facility-based and self-managed procedures and are designed for a context in which the legal status of abortion is hybridized and subject to rapid, ongoing changes, laying the foundation for a new surveillance infrastructure that will be needed for the foreseeable future.