Estimating Global and Country-Specific Excess Mortality during the Covid-19 Pandemic

Estimating the true mortality burden of COVID-19 for every country in the world is a difficult, but crucial, public health endeavor. Attributing deaths, direct or indirect, to COVID-19 is problematic. A more attainable target is the "excess deaths," the number of deaths in a particular period, relative to that expected during "normal times," and we develop a model for this endeavor. The excess mortality requires two numbers, the total deaths and the expected deaths, but the former is unavailable for many countries, and so modeling is required for such countries. The expected deaths are based on historic data, and we develop a model for producing estimates of these deaths for all countries. We allow for uncertainty in the modeled expected numbers when calculating the excess. The methods we describe were used to produce the World Health Organization (WHO) excess death estimates. To achieve both interpretability and transparency we developed a relatively simple overdispersed Poisson count framework within which the various data types can be modeled. We use data from countries with national monthly data to build a predictive log-linear regression model with time-varying coefficients for countries without data. For a number of countries, subnational data only are available, and we construct a multinomial model for such data, based on the assumption that the fractions of deaths in subregions remain approximately constant over time. Our inferential approach is Bayesian, with the covariate predictive model being implemented in the fast and accurate INLA software. The subnational modeling was carried out using MCMC in Stan. Based on our modeling, the point estimate for global excess mortality during 2020-2021 is 14.8 million, with a 95% credible interval of (13.2, 16.6) million.

The link between family identification, loneliness, and symptom severity in people with eating disorders

Families play an important role in eating disorder (ED) recovery, and it has been suggested that they can ameliorate the loneliness associated with EDs. However, the psychological mechanisms through which this occurs have yet to be systematically explored. Utilising the Social Identity Approach to Health, we explore whether identification with one's family group positively predicts health in people with self-reported EDs due to its potential to reduce feelings of loneliness. We investigate this in two online questionnaire studies (N = 82;N = 234), one conducted before the COVID-19 pandemic and the second conducted in its early stages. In both studies, mediation analyses demonstrated that family identification was associated with fewer and less severe self-reported ED symptoms, and in the context of the COVID-19 pandemic, reduced self-reported ED-related impact and anxiety. In both studies, these benefits were suggestive of a protective role of family identification against loneliness. Our findings provide a framework for understanding in general why families can be considered an important social recovery resource and should be included in the treatment of adult EDs. Please refer to the Supplementary Material section to find this article's Community and Social Impact Statement. © 2022 The Authors. Journal of Community & Applied Social Psychology published by John Wiley & Sons Ltd.