We present a battery of recommended biomedical and psychosocial common data elements (CDEs) and measures that, when combined across datasets, can improve our collective understanding of COVID-19 in pregnant and lactating women and their neonates. Experts across eight large pregnancy cohort studies developed these recommendations for use by any planned or upcoming COVID-19 study that includes women of reproductive age or pregnant women. We encourage researchers to include some or all of these measures, which cover key medical and psychosocial domains relevant to pregnancy and childbirth, into their studies to maximize the potential for data harmonization while continuing to advance their own study goals. Common biomedical data elements and measures aim to accelerate our understanding of the clinical course of the disease and its effects on pregnant women and their neonates, which will continue to evolve as treatments and vaccines become available. Here we highlight CDEs and measures across seven domains, which include: Baseline Maternal / Pregnancy Characteristics; Maternal COVID-19 Treatment; Maternal Outcomes; Obstetric / Pregnancy Outcomes; Neonatal Characteristics; Neonatal COVID-19 Testing; and Early Neonatal Outcomes. Recommendations assume that information from all patient visits (e.g., prenatal visits, COVID-19 testing, and delivery) can be collected via medical chart or downloaded data from electronic health records. Common psychosocial data elements and measures aim to advance our understanding of the psychological, behavioral, and social effects of the virus and the pandemic on pregnant women and their neonates. Here we highlight CDEs and measures across six domains, including: Socioeconomic Status, Housing, and Emergent Financial Strain; Medical Care; Impact on Parenting; Stressful Life Events; Maternal Mental Health; and Health Related Behaviors.