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Mortality and Excess Mortality: Improving FluMOMO.
Portugal, Luís.
  • Portugal L; Partner and Managing Director ACTUARIAL Group, PhD Mathematical Sciences, University of Liverpool, Fellow Actuary, IAP (Portugal), England, UK.
J Environ Public Health ; 2021: 5582589, 2021.
Article in English | MEDLINE | ID: covidwho-1262417
ABSTRACT
FluMOMO is a universal formula to forecast mortality in 27 European countries and was developed on EuroMOMO context, http//www.euromomo.eu. The model has a trigonometric baseline and considers any upwards deviation from that to come from flu or extreme temperatures. To measure it, the model considers two variables influenza activity and extreme temperatures. With the former, the model gives the number of deaths because of flu and with the latter the number of deaths because of extreme temperatures. In this article, we show that FluMOMO lacks important variables to be an accurate measure of all-cause mortality and flu mortality. Indeed, we found, as expected, that population ageing and exposure to the risk of death cannot be excluded from the linear predictor. We model weekly deaths as an autoregressive process (lag of one together with a lead of one week). This step allowed us to avoid FluMOMO trigonometric baseline and have a fit to weekly deaths through demographic variables. Our model uses data from Portugal between 2009 and 2020, on ISO-week basis. We use negative binomial-generalized linear models to estimate the weekly number of deaths as an alternative to traditional overdispersion Poisson. As explanatory variables were found to be statistically significant, we registered the number of deaths from the previous week, the influenza activity index, the population average age, the heat waves, the flu season, the number of deaths with COVID-19, and the population exposed to the risk of dying. Considering as excess mortality the number of deaths above the best estimate of deaths from our model, we conclude that excess mortality in 2020 (net of COVID-19 deaths, heat wave of July, and ageing) is low or inexistent. The model also allows us to have the number of deaths arising from flu and we conclude that FluMOMO is overestimating deaths from flu by 78%. Averages from the probability of dying are obtained as well as the probability of dying from flu. The latter is shown to be decreasing over time, probably due to the increase of flu vaccination. Higher mortality detected with the start of COVID-19, in March-April 2020, was probably due to COVID-19 deaths not recognized as COVID-19 deaths.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Population / Mortality / Influenza, Human Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Female / Humans / Male Country/Region as subject: Europa Language: English Journal: J Environ Public Health Year: 2021 Document Type: Article Affiliation country: 2021

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Population / Mortality / Influenza, Human Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Female / Humans / Male Country/Region as subject: Europa Language: English Journal: J Environ Public Health Year: 2021 Document Type: Article Affiliation country: 2021