A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. The proposal is motivated by real‐time monitoring and short‐term forecasting of the main epidemiological indicators within the first outbreak of COVID‐19 in Italy. Accurate short‐term predictions, including the potential effect of exogenous or external variables are provided. This ensures to accurately predict important characteristics of the epidemic (e.g., peak time and height), allowing for a better allocation of health resources over time. Parameter estimation is carried out in a maximum likelihood framework. All computational details required to reproduce the approach and replicate the results are provided.

A high body mass (BMI) index has repeatedly been associated with non-atopic asthma, but the biological mechanism linking obesity to asthma is still poorly understood. We aimed to test the hypothesis that inflammation and/or innate immunity plays a role in the obesity-asthma link. DNA methylome was measured in blood samples of 61 non-atopic participants with asthma and 146 non-atopic participants without asthma (non-smokers for at least 10 years) taking part in the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) study. Modification by DNA methylation of the association of BMI or BMI change over 10 years with adult-onset asthma was examined at each CpG site and differentially methylated region. Pathway enrichment tests were conducted for genes in a priori curated inflammatory pathways and the NLRP3-IL1B-IL17 axis. The latter was chosen on the basis of previous work in mice. Inflammatory pathways including glucocorticoid/PPAR signaling (p = 0.0023), MAPK signaling (p = 0.013), NF-κB signaling (p = 0.031), and PI3K/AKT signaling (p = 0.031) were enriched for the effect modification of BMI, while NLRP3-IL1B-IL17 axis was enriched for the effect modification of BMI change over 10 years (p = 0.046). DNA methylation measured in peripheral blood is consistent with inflammation as a link between BMI and adult-onset asthma and with the NLRP3-IL1B-IL17 axis as a link between BMI change over 10 years and adult-onset asthma in non-atopic participants.

During the pandemic, Switzerland avoided stringent lockdowns and provided funds to stabilize the economy. To assess whether and in what subgroups the pandemic impacted on depressive symptoms in this specific Swiss context, we derived depression trajectories over an extended pandemic period in a Swiss cohort and related them to individuals' sociodemographic characteristics. This was a population-based cohort study. The population-based COVCO-Basel cohort in North-Western Switzerland invited 112,848 adult residents of whom 12,724 participated at baseline. Between July 2020 and December 2021, 6396 participants answered to additional 18 monthly online questionnaires. Depression symptoms were repeatedly measured by the DASS-21 scale. Group-based Trajectory Models methods were applied to identify clusters of similar depression trajectories. Trajectory clusters were characterized descriptively and with a Multinomial response model. Three distinct trajectories were identified. The 'Highly affected' trajectory (13%) had a larger presence of younger and female participants with lower average income, higher levels of past depression, and living alone. A majority of individuals in the 'Unaffected' trajectory (52%) were of medium or high average income, older average age, without previous depression symptoms, and not living alone. The 'Moderately affected' trajectory (35%) had a composition intermediate between the two opposite 'extreme' trajectories. This study is among few studies investigating depression trajectories up to the time when COVID-19 vaccination was readily available to the entire population. During these 18 months of the pandemic, depressive symptoms increased in a substantial percentage of participants. Economic support, high-quality health care system, and moderate containment measures did not sufficiently protect all population subgroups from adverse, potentially long-term psychological pandemic impacts.

The independent and interrelated long-term effects of the exposome such as air pollution, greenness, and ambient temperature on lung function are not well understood, yet relevant in the light of climate change. Pre-bronchodilation FEV1 from five mature birth cohorts (N = 4724) and three adult cohorts (N = 6052) from five European countries were used to assess cross-sectional associations with air pollution, greenness, and ambient temperature, assigned to their residential address. All two-way interactions and square terms were a priori included in building the final elastic net regression model. Elastic net regression results were put into the context of different environmental scenarios such as improvement of air quality, improvement of greenness, climate change, or their combinations. Elastic net regression of FEV1 z-scores identified non-zero coefficients for many interaction terms, indicating the importance of joint effects of exposure to air pollution, greenness, and temperature. The non-zero coefficients were bigger and more stable in adults than in children. Upon exploring lung function benefits for different environmental scenarios, an improvement of FEV1 was expected in the scenario of improving air quality or greenness. In contrast, negative changes in FEV1 z-scores were expected in the scenario of climate change, characterized by daily temperature increase in summer and decrease in winter. The beneficial FEV1 effects of improving air pollution or greenness were attenuated in the presence of climate change. Complex exposome profiles of long-term exposure to air pollution, greenness, and temperature showed associations with FEV1 in European adults, and to less extent in children and adolescents. Climate change seems to have a negative impact on lung function and modifies the association of air pollution and greenspace with lung function.

With this Letter we would like to point out the importance of a good and reliable communication of predictions, scenarios and projections about COVID-19, focusing on the Italian case.