[The wave train of COVID-19 infections]. / COVID-19: il treno di onde dei contagi.

The present work studies the epidemic curve of COVID-19 in Italy between September 2020 and mid-June 2021 in terms of poussées, that is successive waves. There is obviously only one pandemic, although the virus has spread in the form of several variants, but the daily incidence trend can also be read in terms of overlapping of events that are different from each other or, in any case, induced by various phenomena. It can be hypothesized that in this way a succession of various waves was generated, which are modelled here using appropriate adaptation curves used in the study of epidemic data. Each curve corresponds approximately to the situation that would have occurred if no element had intervened to prevent the decrease of infections after the relative peak, while their overlap is considered to describe the subsequent increases. This interpolation has no predictive purpose, being purely descriptive over the time window under consideration. The discrepancies between the superposition of the modelling curves and the real epidemic curve are therefore also highlighted, especially in the transition periods between the various poussées. Finally, the analysis carried out allows to match the trend of the epidemic in the period considered with, on one hand, the series of events and, on the other, with the containment measures adopted which may have determined the succession of increases and decreases in the incidence of infections.

[Update and review of the 2011 Italian deprivation index calculated at the census section level]. / Aggiornamento e revisione dell'indice di deprivazione italiano 2011 a livello di sezione di censimento.

OBJECTIVES: to produce for the national territory as a whole a deprivation index (ID) at the census section level, based on 2011 census data, in the same way as the Italian index based on the 2001 census, revising the formulation of some indicators. SETTING AND PARTICIPANTS: the study uses the individual data of the general population and housing census of 2011. For the calculation of the index five conditions were chosen that best describe the multidimensional concept of social and material deprivation: low level of education, being unemployed, living in rent, living in crowded house, living in a single-parent family. The index is calculated as the sum of standardized indicators and is also available categorized into quintiles. Compared to the previous formulation of the ID, the proposed revised ID made use of a low education indicator limited to the age group 15-60; for what concerns single-parent families, only the cohabitations with minor children is considered. MAIN OUTCOME MEASURES: reformulated ID and comparison measures between the two indices (correlation, kappa statistic). RESULTS: the revised index, compared with the previous one, a different quintile distribution for a significant share of census sections, with the exception of the first and fifth quintiles (that of the least deprived and the most deprived ones). CONCLUSION: given that in this field of study should be taken for granted the inexistence of a method that produces results objectively and universally valid, the review of the index proposed in this study starts from the availability of analytical data that allowed to overcome some constraints that had induced the choices of the ID proposed in 2010. Anyway, both the original and the revised index produce reliable and consistent results.

[Resources and justice: for an equity on an epidemiological basis of healthcare funding]. / Risorse e giustizia: per un'equità su base epidemiologica dei finanziamenti alla sanità.

The rules for distributing public resources for healthcare among Italian Regions are the subject of heated discussions every year among the Regions themselves. The factors of convenience with respect to those of justice very often prevail in the discussion. To think about what the best solution would be, it would be necessary to deepen the theories of justice, from utilitarianism to contractualism, from liberalism to economic egalitarianism. In any case, it would be advisable for the political choice of the allotment criteria to be made "under the veil of ignorance", i.e., independently of pure convenience. The analysis of the current division shows that the factor that practically explains the totality of the differences is the average age of the regional populations, while it does not seem to be associated with both economic and epidemiological indicators.

[Rt or RDt, that is the question!] / Rt or RDt, that is the question!

The article compares two of the most followed indices in the monitoring of COVID-19 epidemic cases: the Rt and the RDt indices. The first was disseminated by the Italian National Institute of Health (ISS) and the second, which is more usable due to the lower difficulty of calculation and the availability of data, was adopted by various regional and local institutions.The rationale for the Rt index refers to that for the R0 index, the basic reproduction number, which is used by infectivologists as a measure of contagiousness of a given infectious agent in a completely susceptible population. The RDt index, on the other hand, is borrowed from the techniques of time series analysis for the trend of an event measurement that develops as a function of time. The RDt index does not take into account the time of infection, but the date of the diagnosis of positivity and for this reason it is defined as diagnostic replication index, as it aims to describe the intensity of the development of frequency for cases recognized as positive in the population.The comparison between different possible applications of the methods and the use of different types of monitoring data was limited to four areas for which complete individual data were available in March and April 2020. The main problems in the use of Rt, which is based on the date of symptoms onset, arise from the lack of completeness of this information due both to the difficulty in the recording and to the absence in asymptomatic subjects.The general trend of RDt, at least at an intermediate lag of 6 or 7 days, is very similar to that of Rt, as confirmed by the very high value of the correlation index between the two indices. The maximum correlation between Rt and RDt is reached at lag 7 with a value of R exceeding 0.97 (R2=0.944).The two indices, albeit formally distinct, are both valid; they show specific aspects of the phenomenon, but provide basically similar information to the public health decision-maker. Their distinction lies not so much in the method of calculation, rather in the use of different information, i.e., the beginning of symptoms and the swabs outcome.Therefore, it is not appropriate to make a judgment of preference for one of the two indices, but only to invite people to understand their different potentials so that they can choose the one they consider the most appropriate for the purpose they want to use it for.

The geography and economics of forgoing medical examinations or therapeutic treatments in Italy during the economic crisis.

BACKGROUND: In Italy, the number of individuals who have forgone medical examinations or treatments for economic reasons is one of the highest in Europe. During the global economic crisis of 2008, the restrictive policies concerning access to healthcare and the quality of these services, which differs widely throughout the country, may have accentuated the territorial differences in unmet needs, thereby penalizing the more disadvantaged segments of the population. The study aimed at evaluating the geographical and socioeconomic differences, in particular the risk of poverty, that influence forgoing healthcare services in Italy. METHODS: Cross-sectional Italian data from the 2004-2015 European Survey on Income and Living Conditions (EU-SILC) were used. Hierarchical logistic models were tested, using as the outcome unmet needs for medical examinations or treatment in the preceding 12 months, and as risk factor the condition of being at risk of poverty. Age, sex, citizenship, educational level, presence of chronic or severely limiting diseases and self-perceived health were used as adjustment factors. Analyses were stratified over three time periods: pre-crisis (2004-2007), initial phase of the crisis (2008-2012) and second phase of the crisis (2013-2015). RESULTS: In Central Italy and particularly in Southern Italy, a marked increase (9.9% in 2013-2015) was seen in the overall rate of unmet needs as well as in that of unmet needs due to economic reasons. The probability of unmet needs was higher, and increased over time, for those at risk of poverty (aOR = 1.54 in 2004-07, aOR = 1.70 in 2008-12, aOR = 2.21 in 2013-15). Individuals with a low educational level, who had a chronic or severely limiting disease, who perceived their health as not good and immigrants had a higher risk of forgoing healthcare. The regions in Southern Italy had a significantly higher probability of unmet needs. CONCLUSIONS: A strong association was found between the probability of forgoing medical examination or treatment and being at risk of poverty. Study results underline the need for healthcare policies aimed at facilitating access to healthcare services, particularly in the South, by developing a progressive mechanism of contribution to healthcare costs proportional to income and by guaranteeing free access to the poor.

Self-rated health as a valid indicator for health-equity analyses: evidence from the Italian health interview survey.

BACKGROUND: Self-rated health is widely considered a good indicator of morbidity and mortality but its validity for health equity analysis and public health policies in Italy is often disregarded by policy-makers. This study had three objectives. O1: To explore response distribution across dimensions of age, chronic health conditions, functional limitations and SRH in Italy. O2: To explore associations between SRH and healthcare demand in Italy. O3: To explore the association between SRH and household income. METHODS: Cross-sectional data were obtained from the 2015 Health Interview Survey (HIS) conducted in Italy. Italian respondents (n = 20,814) were included in logistic regression analyses. O1: associations of chronic health conditions (CHC), functional limitations (FL), and age with self-rated health (SRH) were tested. O2: associations of CHC, FL, and SRH with hospitalisation (H), medical specialist consultations (MSC), and medicine use (MU) were tested. O3: associations of SRH and CHC with household income (PEI) were tested. RESULTS: O1: CHC, FL, and age had an independent summative effect on respondents' SRH. O2: SRH predicted H and MSC more than CHC; age and MU were more strongly correlated than SRH and MU. O3: SRH and PEI were significantly correlated, while we found no correlation between CHC and PEI. CONCLUSIONS: Drawing from our results and the relevant literature, we suggest that policy-makers in Italy could use SRH measures to: 1) predict healthcare demand for effective allocation of resources; 2) assess subjective effectiveness of treatments; and 3) understand geosocial pockets of health inequity that require special attention.

[A proposal for an indicator to analyse equity on the health of populations]. / Una proposta di indicatore per analizzare l'equità nei dati riguardanti la salute delle popolazioni.

In epidemiological analyses, age is often considered only as a confounder, since its role as a determinant is evident. As a result, most analyses attempt to adjust the analysis by eliminating age differences in the examined populations. Due to different phenomena, however, the effects are not always shown at the same age, then an early occurrence allows a better measurement of the risk than the general average prevalence. The indicator here proposed is defined as the age at which a certain proportion of the population assumes the analysed condition. It applies to dichotomous variables with a monotone trend, both increasing and decreasing, and can highlight risk situations to which the populations examined are exposed better than other indicators. The application of this indicator to the health data of the Eu-silc (statistics on income and living conditions) survey by Eurostat here analysed allows to highlight the important inequalities between the populations of geographical areas and social classes with different incomes. The biggest differences are observed around 50 years of age and are increasing from the three-year period 2007-2009 to the three-year period 2013/2015.

The Health Mobility Is All True Mobility? Comment on "Regional Incentives and Patient Cross-border Mobility: Evidence From the Italian Experience".

In their study, Brenna and Spandonaro analyzed the mobility into Italian regions. In particular, it analyzes the situation of 5 regions, with very different backgrounds. With this paper, we try to better define the meaning of health mobility and to find its underlying causes. Furthermore, we propose a strategy that could help in controlling mobility flows that currently are the source of health inequalities.