Establishment of the maternal-fetal interface is characterized by the influx of maternal NK cells, macrophages, and T cells into the decidua. Although a great deal has been learned about the function of NK cells in the decidua, comparatively little is known of decidual T cell function. NKT cells are an unusual T cell subset capable of producing both Th1-like and Th2-like cytokines. Unlike conventional αβ T cells that recognize peptides in the context of MHC molecules, NKT cells recognize glycolipids presented by the MHC class I-like molecule, CD1d. Recent reports have demonstrated that NKT cells and CD1d are present at the maternal-fetal interface. Moreover, activation of NKT cells can have dramatic effects on pregnancy. In this article, we will review basic aspects of NKT cell biology and summarize the recent literature on NKT cells at the maternal-fetal interface.

Background Many studies have focused on the characteristics of symptomatic patients with COVID-19 and clinical risk factors. This study reports the prevalence of COVID-19 in an asymptomatic population of a hospital service area (HSA) and identifies factors that affect exposure to the virus. Objective The aim of this study is to measure the prevalence of COVID-19 in an HSA, identify factors that may increase or decrease the risk of infection, and analyze factors that increase the number of daily contacts. Methods This study surveyed 1694 patients between April 30 and May 13, 2020, about their work and living situations, income, behavior, sociodemographic characteristics, and prepandemic health characteristics. This data was linked to testing data for 454 of these patients, including polymerase chain reaction test results and two different serologic assays. Positivity rate was used to calculate approximate prevalence, hospitalization rate, and infection fatality rate (IFR). Survey data was used to analyze risk factors, including the number of contacts reported by study participants. The data was also used to identify factors increasing the number of daily contacts, such as mask wearing and living environment. Results We found a positivity rate of 2.2%, a hospitalization rate of 1.2%, and an adjusted IFR of 0.55%. A higher number of daily contacts with adults and older adults increases the probability of becoming infected. Occupation, living in an apartment versus a house, and wearing a face mask outside work increased the number of daily contacts. Conclusions Studying prevalence in an asymptomatic population revealed estimates of unreported COVID-19 cases. Occupational, living situation, and behavioral data about COVID-19–protective behaviors such as wearing a mask may aid in the identification of nonclinical factors affecting the number of daily contacts, which may increase SARS-CoV-2 exposure.

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There was no significant difference in bathing habits, but there was a significant difference in laundry habits between the case and control groups. Our study further confirms that IV drug use is a risk factor for cellulitis and no access to clean clothes daily was significantly related to the development of cellulitis. Failing to obtain daily showers was not associated with an increase in infection.

BACKGROUND Many studies have focused on characteristics of symptomatic COVID-19 patients and clinical risk factors. This study reports prevalence of COVID-19 in the general population and identifies factors that affect exposure to the virus. OBJECTIVE To measure the prevalence of COVID-19 in a hospital service area and identify factors that may increase or decrease the risk of infection and exposure. METHODS This study collected survey information relating to work and living situations, income, behavior, socio-demographic characteristics and pre-pandemic health characteristics which was linked to polymerase chain reaction (PCR) testing and two different serologic assays. Positivity rate was used to calculate approximate prevalence, hospitalization rate and infection fatality rate (IFR). Survey data was used to analyze risk factors, including the number of contacts reported by study participants. RESULTS We found a positivity rate of 2.2 percent, a hospitalization rate of 1.2 percent and an adjusted IFR of 0.55 percent. Number of daily contacts with adults and seniors increases the probability of becoming infected. Occupation, living in apartment versus a house, and wearing a facial mask outside work increased probability of COVID-19 infection. CONCLUSIONS Comparing these numbers with officially reported infections leads to estimates of unreported cases. Occupational, living-situation, and behavioral data may aid in the identification of non-clinical factors affecting SARS-CoV-2 exposure and infection.