Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

A Pregnant Adolescent with COVID-19 and Multisystem Inflammatory Syndrome in Children

Multisystem inflammatory syndrome in children (MIS-C), a new condition related to coronavirus disease 2019 (COVID-19) in the pediatric population, was recognized by physicians in the United Kingdom in April 2020. Given those up to the age of 21 years can be affected, pregnant adolescents and young adults are susceptible. However, there is scant information on how MIS-C may affect pregnancy and whether the presentation differs in the pregnant population. We report a case of a pregnant adolescent with COVID-19 and MIS-C with a favorable outcome. This case highlights the considerations in managing a critically ill pregnant patient with a novel illness and the importance of a multidisciplinary team in coordinating care

Perinatal depression before and during the COVID-19 pandemic in New York CityAJOG Global Reports at a Glance

BACKGROUND: Quarantining and isolation during previous pandemics have been associated with higher levels of depression symptomatology. Studies in other countries found elevated rates of anxiety and/or depression among pregnant people during the COVID-19 pandemic compared with prepandemic rates. New York City was the initial epicenter of the pandemic in the United States, and the effects of the pandemic on perinatal depression in this population are not well known. OBJECTIVE: This study aimed to evaluate the rates of perinatal depression before and during the COVID-19 pandemic. STUDY DESIGN: This is a single-center retrospective cohort study of patients screened for perinatal depression with the Edinburgh Postnatal Depression Scale at 2 private academic practices in New York City. This screen is done in these practices at the time of the glucose challenge test and at the postpartum visit. Patients aged ≥18 years who completed a screen at a postpartum visit and/or glucose challenge test from February 1, 2019 to July 31, 2019 and from February 1, 2020 to July 31, 2020 were identified, and the 2019 and 2020 groups were compared. The primary outcome was a positive screen, defined as ≥13 and ≥15 for postnatal and prenatal screens, respectively. Secondary outcomes included monthly changes in rates of positive screens and factors associated with perinatal depression. Data were analyzed using Mann–Whitney U test, chi-square, or Fisher exact test, and univariate and multivariate analyses with P.99). This finding persisted after adjusting for baseline differences (adjusted odds ratio, 0.89; 95% confidence interval, 0.38–1.86; P=.76). There were no differences in rates of positive Edinburgh Postnatal Depression Scale by month. Several risk factors were associated with a positive screen, including being unmarried (P<.001), pulmonary disease (P=.02), depression (P<.001), anxiety (P=.01), bipolar disorder (P=.009), and use of anxiolytics (P=.04). CONCLUSION: There were no differences in the rates of perinatal depression between the periods before and during the COVID-19 pandemic. The rate of perinatal depression in this cohort was below the reported averages in the literature. Fewer women were screened for perinatal depression in 2020, which likely underestimated the prevalence of depression in our cohort. These findings highlight potential gaps in care in a pandemic setting