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During the COVID-19 pandemic, regions were affected by a combination of economic crises: weak demand and constrained supply. Several studies have sought to analyse the heterogeneous effects of supply and demand shocks on the labour market, economic growth, and the environment. This study has a different focus, estimating both direct and indirect effects of demand and supply shocks adopted during the pandemic in Brazil and Chile. Afterwards, the paper compares the degree of regional absorption (leakage) of income resulting from each of these shocks, applying an interregional input–output model for each country. The results of this study show that income absorption by the poorest regions is relatively greater in the case of a supply shock. It can be said, therefore, that this type of shock improves the retention of income generated in the poorest regions, favouring the development of these localities and the reduction in regional inequalities. The main reason for this result is that supply policies have restricted essential sectors to a lesser extent, and these sectors are generally less concentrated in large urban centres in both Brazil and Chile. In other words, much of the interregional leakage is driven by the demand for non-essential products, mainly in the richest urban economy centres. Finally, the geographical dimension of regional inequalities leads to the economic benefit of prosperous areas in the country when shocks occur in vulnerable regions, highlighting the centre–periphery pattern in both countries. [ABSTRACT FROM AUTHOR]

Fitting Susceptible-Infected-Recovered (SIR) models to incidence data is problematic when not all infected individuals are reported. Assuming an underlying SIR model with general but known distribution for the time to recovery, this paper derives the implied differential-integral equations for observed incidence data when a fixed fraction of newly infected individuals are not observed. The parameters of the resulting system of differential equations are identifiable. Using these differential equations, we develop a stochastic model for the conditional distribution of current disease incidence given the entire past history of reported cases. We estimate the model parameters using Bayesian Markov Chain Monte-Carlo sampling of the posterior distribution. We use our model to estimate the transmission rate and fraction of asymptomatic individuals for the current Coronavirus 2019 outbreak in eight American Countries: the United States of America, Brazil, Mexico, Argentina, Chile, Colombia, Peru, and Panama, from January 2020 to May 2021. Our analysis reveals that the fraction of reported cases varies across all countries. For example, the reported incidence fraction for the United States of America varies from 0.3 to 0.6, while for Brazil it varies from 0.2 to 0.4., Competing Interests: The authors have declared that no competing interests exist.

Background: Previous studies reported the negative impact of social isolation on mental health in people with dementia (PwD) and their caregivers, butlongitudinal studies seem scarcer. Objective: To describe a one-year follow-up impact of the COVID-19 pandemic on PwD and their caregivers in both Brazil and Chile. Methods: This study analyzed the impact of the pandemic on the psychological and physical health of PwD and their family caregivers after one year of follow-up in three outpatient clinics in Brazil (n = 68) and Chile (n = 61). Results: In both countries, PwD reduced their functional capacity after one year of follow-up (p = 0.017 and p = 0.009; respectively) and caregivers reported worse physical and mental health (p = 0.028 and p = 0.039). Only in Chile, caregivers reported more sadness associated with care (p = 0.001), and reduced time sleeping (p = 0.07). Conclusions: In conclusion, the COVID-19 pandemic appears to have had a long-lasting impact on PwD and their caregivers. However, it is essential to acknowledge that the inherent progression of dementia itself may also influence changes observed over a year. [ABSTRACT FROM AUTHOR]

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