Spatial analysis of risk of morbidity and mortality by COVID-19 in Europe and the Mediterranean in the year 2020

Disease mapping seeks to represent the risk of a disease. This paper focuses on the spatial analysis of risk for pandemic COVID-19 in Europe and the Mediterranean. Morbidity and mortality data for 54 countries in ratio format were used. Two hypotheses were considered, the first one is that the data are homogeneous and the second one is that the ratios are defined in a heterogeneous manner requiring the stratification on the basis of covariables and the methodology of Jenks’ intervals. Spatial risk models were applied as well as methods for the representation of clusters. The results show that the best representation is obtained with the Poisson-Gamma Model under stratification. The variations in the ratios are due to the individual policies of each country for the management of the pandemic. The cluster analysis shows that there is a high mortality process in Eastern Europe. The behavior of the pandemic should be evaluated in the space-time process as well as in other heterogeneous and highly unequal regions.

Lifespans of Twins: Does Zygosity Matter?

Studies with twins provide fundamental insights to lifespans of humans. We aim to clarify if monozygotic and dizygotic twin individuals differ in lifespan, that is, if zygosity matters. We investigate whether a possible difference in mortality after infancy between zygosities is stable in different age cohorts, and whether the difference remains when twins with unknown zygosity are taken into account. Further, we compare the distribution of long-livers, that is, the upper-tail of the lifespan distribution, between monozygotic and same-sex dizygotic twin individuals. The Danish Twin Registry provides a nationwide cohort of 109,303 twins born during 1870 to 1990 with valid vital status. Standard survival analysis is used to compare mortality in monozygotic and dizygotic twin individuals and twin individuals with unknown zygosity. The mortality of monozygotic and dizygotic twin individuals differs slightly after taking into consideration effects of birth- and age-cohorts, gender differences, and that twins are paired. However, no substantial nor systematic differences remain when taking twins with unknown zygosity into account. Further, the distribution of long-livers is very similar by zygosity, suggesting the same mortality process. The population-based and oldest twin cohort ever studied suggests that monozygotic and dizygotic twins have similar lifespans.

Disentangling the Relative Strength of Niche Competition from Grazing-Induced Phytoplankton Mortality

The dilution method is the principal tool used to infer in situ microzooplankton grazing rates. However, grazing is the only mortality process considered in the theoretical model underlying the interpretation of dilution method experiments. Here we evaluate the robustness of mortality estimates inferred from dilution experiments when there is concurrent niche competition amongst phytoplankton. Using a combination of mathematical analysis and numerical simulations, we find that grazing rates may be overestimated – the degree of overestimation is related to the importance of niche competition relative to microzooplankton grazing. In response, we propose a conceptual method to disentangle the effects of niche competition and grazing by diluting out microzooplankton, but not phytoplankton. Our theoretical results suggest this revised “Z-dilution” method can robustly infer grazing mortality, regardless of the dominant phytoplankton mortality driver in our system. Further, we show it is possible to independently estimate both grazing mortality and niche competition if the classical and Z-dilution methods can be used in tandem. We discuss the significance of these results for quantifying phytoplankton mortality rates; and the feasibility of using the Z-dilution method in practice.

Adjusting the Measurement of the Output of the Medical Sector for Quality: A Review of the Literature

The Bureau of Economic Analysis recently created new price indexes for health care in its health care satellite account and now faces the problem of how to adjust them for quality. I review the literature on this topic and divide the articles that created quality-adjusted price indexes for individual medical conditions into those that use primarily outcomes-based adjustments and those that use only process-based adjustments. Outcomes-based adjustments adjust the indexes based on observed aggregate health outcomes, usually mortality. Process-based adjustments adjust the indexes based on the treatments provided and medical knowledge of their effectiveness. Outcomes-based adjustments are easier to implement, while process-based adjustments are more demanding in terms of data and medical knowledge. In general, the research literature shows adjusting for quality in the measurement of output in the medical sector to be quantitatively important.