Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project.

BackgroundDuring the COVID-19 pandemic, large-scale diagnostic testing and contact tracing have proven insufficient to promptly monitor the spread of infections.AimTo develop and retrospectively evaluate a system identifying aberrations in the use of selected healthcare services to timely detect COVID-19 outbreaks in small areas.MethodsData were retrieved from the healthcare utilisation (HCU) databases of the Lombardy Region, Italy. We identified eight services suggesting a respiratory infection (syndromic proxies). Count time series reporting the weekly occurrence of each proxy from 2015 to 2020 were generated considering small administrative areas (i.e. census units of Cremona and Mantua provinces). The ability to uncover aberrations during 2020 was tested for two algorithms: the improved Farrington algorithm and the generalised likelihood ratio-based procedure for negative binomial counts. To evaluate these algorithms' performance in detecting outbreaks earlier than the standard surveillance, confirmed outbreaks, defined according to the weekly number of confirmed COVID-19 cases, were used as reference. Performances were assessed separately for the first and second semester of the year. Proxies positively impacting performance were identified.ResultsWe estimated that 70% of outbreaks could be detected early using the proposed approach, with a corresponding false positive rate of ca 20%. Performance did not substantially differ either between algorithms or semesters. The best proxies included emergency calls for respiratory or infectious disease causes and emergency room visits.ConclusionImplementing HCU-based monitoring systems in small areas deserves further investigations as it could facilitate the containment of COVID-19 and other unknown infectious diseases in the future.

Maternal and infant NR3C1 and SLC6A4 epigenetic signatures of the COVID-19 pandemic lockdown: when timing matters.

Stress exposure during pregnancy is critically linked with maternal mental health and child development. The effects might involve altered patterns of DNA methylation in specific stress-related genes (i.e., glucocorticoid receptor gene, NR3C1, and serotonin transporter gene, SLC6A4) and might be moderated by the gestational timing of stress exposure. In this study, we report on NR3C1 and SLC6A4 methylation status in Italian mothers and infants who were exposed to the COVID-19 pandemic lockdown during different trimesters of pregnancy. From May 2020 to February 2021, 283 mother-infant dyads were enrolled at delivery. Within 24 h from delivery, buccal cells were collected to assess NR3C1 (44 CpG sites) and SLC6A4 (13 CpG sites) methylation status. Principal component (PC) analyses were used to reduce methylation data dimension to one PC per maternal and infant gene methylation. Mother-infant dyads were split into three groups based on the pregnancy trimester (first, second, third), during which they were exposed to the COVID-19 lockdown. Mothers and infants who were exposed to the lockdown during the first trimester of pregnancy had lower NR3C1 and SLC6A4 methylation when compared to counterparts exposed during the second or third trimesters. The effect remained significant after controlling for confounders. Women who were pregnant during the pandemic and their infants might present altered epigenetic biomarkers of stress-related genes. As these epigenetic marks have been previously linked with a heightened risk of maternal psychiatric problems and less-than-optimal child development, mothers and infants should be adequately monitored for psychological health during and after the pandemic.

Is Brain-Derived Neurotropic Factor Methylation Involved in the Association Between Prenatal Stress and Maternal Postnatal Anxiety During the COVID-19 Pandemic?

Background The COVID-19 pandemic is a collective trauma that may expose susceptible individuals to high levels of stress. Pregnant women represent a high-risk population, considering that pregnancy is a period of heightened neuroplasticity and susceptibility to stress through epigenetic mechanisms. Previous studies showed that the methylation status of the BDNF gene is linked with prenatal stress exposure. The goals of this study were (a) to assess the association between pandemic-related stress and postnatal anxiety and (b) to investigate the potential role of maternal BDNF methylation as a significant mediator of this association. Methods In the present study, we report data on the association among pandemic-related stress during pregnancy, maternal BDNF methylation, and postnatal anxiety symptoms. Pandemic-related stress and postnatal anxiety were assessed through self-report instruments. BDNF methylation was estimated in 11 CpG sites in DNA from mothers’ buccal cells. Complete data were available from 108 mothers. Results Results showed that pandemic-related stress was associated with an increased risk of postnatal anxiety, r = 0.20, p < 0.05. CpG-specific BDNF methylation was significantly associated with both prenatal pandemic-related stress, r = 0.21, p < 0.05, and postnatal maternal anxious symptoms, r = 0.25, p = 0.01. Moreover, a complete mediation by the BDNF CpG6 methylation emerged between pandemic-related stress during pregnancy and postnatal maternal anxiety, ACME = 0.66, p < 0.05. Conclusion These findings suggest that BDNF epigenetic regulation by pandemic-related stress might contribute to increase the risk of anxiety in mothers. Policymakers should prioritize the promotion of health and wellbeing in pregnant women and mothers during the present healthcare emergency.