Years of life lost estimates cannot always be taken at face value: Response to “COVID-19 – exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study”

In their recent analysis, Hanlon et al. estimated the years of life lost (YLL) in people who have died with COVID-19 by following and expanding on the WHO standard approach. We welcome this research as an attempt to draw a more accurate picture of the mortality burden of this disease which has been involved in the deaths of more than 300,000 people worldwide as of May 2020. However, we argue that obtained YLL estimates (13 years for men and 11 years for women) are interpreted in a misleading way. Even with the presented efforts to control for the role of multimorbidity in COVID-19 deaths, these estimates cannot be interpreted to imply “how long someone who died from COVID-19 might otherwise have been expected to live”. By example we analyze the underlying problem which renders such an interpretation of YLL estimates impossible, and outline potential approaches to control for the problem.

How Large Fraction of A Population Must be Vaccinated before A Disease is Controlled?

The ongoing Covid-19 pandemic has already caused more than 5 million casualties despite hard restrictions and relatively high vaccine coverage in many countries. The crucial question is therefore, how large vaccination rate and how severe restrictions are required to terminate the spread of the decease, assuming that the vaccine efficiency and the basic reproduction ratio (R0) are known? To answer this question, a mathematical equation was applied to visualize the required vaccination level as function of vaccine efficiency, restriction efficiency and basic reproduction ratio (R0). In addition to the modelling study, Covid-19 data from Europe was collected during 19/11-26/11 (2021) to assess the relation between vaccination rate and incidence. The analysis indicates that a vaccination rate of ~92% (2 doses) is required to stop Delta (B.1.617.2) without severe restrictions, under conditions like those in Europe late November 2021. A third vaccine dose, improved vaccines, higher vaccination rates and/or stronger restrictions will be required to force Omicron (B.1.1.529) to expire without infecting a large fraction of the population.

Estimating the potential public health impact of fibre enrichment: a UK modelling study

For improving human health, reformulation can be a tool as it allows individuals to consume products of choice while reducing intake of less desirable nutrients, such as sugars and fats, and potentially increasing intake of beneficial nutrients such as fibre. The potential effects of reformulating foods with increased fibre on diet and on health needs to be better understood. The objective of this statistical modelling study was to understand how fibre enrichment can affect the diet and health of consumers. The UK National Diet and Nutrition Survey (NDNS) datasets from 2014 - 2015 and 2015 - 2016 were utilised to evaluate intakes of fibre and Kilocalories with a dietary intake model. Foods and beverages eligible for fibre enrichment were identified (n = 915) based on EU legislation for fibre content claims. Those people who meet Dietary Reference Values (DRVs) and fibre enrichment health outcomes such as weight, cardiovascular disease and type 2 diabetes risk reductions were quantified pre and post fibre reformulation via Reynolds et al, D’Agostino et al, and QDiabetes algorithms, respectively. The fibre enrichment intervention showed a mean fibre intake in the UK of 19.9 g/day, signifying a 2.2 g/day increase from baseline. Modelling suggested that 5.9% of subjects could achieve a weight reduction, 72.2% a reduction in cardiovascular risk, and 71.7% a reduced risk of type 2 diabetes risk with fibre fortification (all p ≤ 0.05). This study gave a good overview of the potential public health benefits of reformulating food products using a straightforward enrichment scenario.