[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.

Exploring the evidence for the effectiveness of health interventions for COVID-19 targeting migrants: a systematic review protocol.

INTRODUCTION: Owing to their inherent vulnerabilities, the burden of COVID-19 and particularly of its control measures on migrants has been magnified. A thorough assessment of the value of the interventions for COVID-19 tailored to migrants is essential for improving their health outcomes as well as promoting an effective control of the pandemic. In this study, based on evidence from primary biomedical research, we aimed to systematically identify health interventions for COVID-19 targeting migrants and to assess and compare their effectiveness. The review will be conducted within a programme aimed at defining and implementing interventions to control the COVID-19 pandemic in Italy, funded by the Italian Ministry of Health and conducted by a consortium of Italian regional health authorities. METHODS AND ANALYSES: Data sources will include the bibliographic databases MEDLINE, Embase, LOVE Platform COVID-19 Evidence, and Cochrane Central Register of Controlled Trials. Eligible studies must evaluate health interventions for COVID-19 in migrants. Two independent reviewers will screen articles for inclusion using predefined eligibility criteria, extract data of retained articles and assess methodological quality by applying the Cochrane Risk of Bias tool. Disagreements will be resolved through consensus or arbitrated by a third reviewer if necessary. In synthesising the evidence, we will structure results by interventions, outcomes and quality. Where studies are sufficiently homogenous, trial data will be pooled and meta-analyses will be performed. Data will be reported according to methodological guidelines for systematic review provided by the Cochrane Collaboration and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. ETHICS AND DISSEMINATION: This is a review of existing literature, and ethics approval is not required. We will submit results for peer-review publication and present at relevant conferences. The review findings will be included in future efforts to develop evidence-informed recommendations, policies or programmatic actions at the national and regional levels and address future high-quality research in public health.

Stratification of the risk of developing severe or lethal Covid-19 using a new score from a large Italian population: a population-based cohort study.

OBJECTIVES: To develop a population-based risk stratification model (COVID-19 Vulnerability Score) for predicting severe/fatal clinical manifestations of SARS-CoV-2 infection, using the multiple source information provided by the healthcare utilisation databases of the Italian National Health Service. DESIGN: Retrospective observational cohort study. SETTING: Population-based study using the healthcare utilisation database from five Italian regions. PARTICIPANTS: Beneficiaries of the National Health Service, aged 18-79 years, who had the residentship in the five participating regions. Residents in a nursing home were not included. The model was built from the 7 655 502 residents of Lombardy region. MAIN OUTCOME MEASURE: The score included gender, age and 29 conditions/diseases selected from a list of 61 conditions which independently predicted the primary outcome, that is, severe (intensive care unit admission) or fatal manifestation of COVID-19 experienced during the first epidemic wave (until June 2020). The score performance was validated by applying the model to several validation sets, that is, Lombardy population (second epidemic wave), and the other four Italian regions (entire 2020) for a total of about 15.4 million individuals and 7031 outcomes. Predictive performance was assessed by discrimination (areas under the receiver operating characteristic curve) and calibration (plot of observed vs predicted outcomes). RESULTS: We observed a clear positive trend towards increasing outcome incidence as the score increased. The areas under the receiver operating characteristic curve of the COVID-19 Vulnerability Score ranged from 0.85 to 0.88, which compared favourably with the areas of generic scores such as the Charlson Comorbidity Score (0.60). A remarkable performance of the score on the calibration of observed and predicted outcome probability was also observed. CONCLUSIONS: A score based on data used for public health management accurately predicted the occurrence of severe/fatal manifestations of COVID-19. Use of this score may help health decision-makers to more accurately identify high-risk citizens who need early preventive or treatment interventions.

Large-Scale Postmarketing Surveillance of Biological Drugs for Immune-Mediated Inflammatory Diseases Through an Italian Distributed Multi-Database Healthcare Network: The VALORE Project.

BACKGROUND: Biological drugs have improved the management of immune-mediated inflammatory diseases (IMIDs) despite being associated with important safety issues such as immunogenicity, infections, and malignancies in real-world settings. OBJECTIVE: The aim of this study was to explore the potential of a large Italian multi-database distributed network for use in the postmarketing surveillance of biological drugs, including biosimilars, in patients with IMID. METHODS: A retrospective cohort study was conducted using 13 Italian regional claims databases during 2010-2019. A tailor-made R-based tool developed for distributed analysis of claims data using a study-specific common data model was customized for this study. We measured the yearly prevalence of biological drug users and the frequency of switches between originator and biosimilars for infliximab, etanercept, and adalimumab separately and stratified them by calendar year and region. We then calculated the cumulative number of users and person-years (PYs) of exposure to individual biological drugs approved for IMIDs. For a number of safety outcomes (e.g., severe acute respiratory syndrome coronavirus 2 [SARS-COV-2] infection), we conducted a sample power calculation to estimate the PYs of exposure required to investigate their association with individual biological drugs approved for IMIDs, considering different strengths of association. RESULTS: From a total underlying population of almost 50 million inhabitants from 13 Italian regions, we identified 143,602 (0.3%) biological drug users, with a cumulative exposure of 507,745 PYs during the entire follow-up. The mean age ± standard deviation of biological drug users was 49.3 ± 16.3, with a female-to-male ratio of 1.2. The age-adjusted yearly prevalence of biological drug users increased threefold from 0.7 per 1000 in 2010 to 2.1 per 1000 in 2019. Overall, we identified 40,996 users of biosimilars of tumor necrosis factor (TNF)-α inhibitors (i.e., etanercept, adalimumab, and infliximab) in the years 2015-2019. Of these, 46% (N = 18,845) switched at any time between originator and biosimilars or vice versa. To investigate a moderate association (incidence rate ratio 2) between biological drugs approved for IMIDs and safety events of interest, such as optic neuritis (lowest background incidence rate 10.4/100,000 PYs) or severe infection (highest background incidence rate 4312/100,000 PYs), a total of 43,311 PYs and 104 PYs of exposure to individual biological drugs, respectively, would be required. As such, using this network, of 15 individual biological drugs approved for IMIDs, the association with those adverse events could be investigated for four (27%) and 14 (93%), respectively. CONCLUSION: The VALORE project multi-database network has access to data on more than 140,000 biological drug users (and > 0.5 million PYs) from 13 Italian regions during the years 2010-2019, which will be further expanded with the inclusion of data from other regions and more recent calendar years. Overall, the cumulated amount of person-time of exposure to biological drugs approved for IMIDs provides enough statistical power to investigate weak/moderate associations of almost all individual compounds and the most relevant safety outcomes. Moreover, this network may offer the opportunity to investigate the interchangeability of originator and biosimilars of several TNFα inhibitors in different therapeutic areas in real-world settings.

[Can diabetes and its related hypoglycemic drug treatment be considered risk factors for health outcomes in COVID-19 patients? The results of a study in the population residing in Sicily Region (Southern Italy)]. / Diabete e trattamento farmacologico con ipoglicemizzanti possono essere considerati fattori di rischio per gli esiti di salute in soggetti COVID-19? I risultati di uno studio nella popolazione residente in Sicilia.

OBJECTIVES: to evaluate the effects of a pre-existing condition of diabetes and of the use of antidiabetic drugs in the Sicilian population on different outcomes of the COVID-19 disease. DESIGN: a retrospective observational study based was used. Data deriving from the COVID-19 epidemic surveillance and from the collection of information on drugs consume by Sicilian residents. SETTING AND PARTICIPANTS: due to the data availability, the study was calibrated on the Region and included all population distinguishing by gender and age groups. MAIN OUTCOME MEASURES: the risks of cumulative incidence for COVID-19 were investigated in people who had diabetes comorbidities to incur a hospitalization for COVID-19, to be treated within an intensive care unit, and lethality. The role of previous antidiabetic drug treatments with respect to each study outcome was also investigated. RESULTS: in Sicily, from 01.03.2020 to 26.06.2020, a number of 172 cases of COVID-19 disease with diabetes comorbidity were diagnosed. The data did not show any difference in the cumulative incidence for COVID-19 between diabetics (64.2/100,000 inhabitants) and non-diabetics (56.9/100,000 inhabitants) patients. Diabetes increases the risk of hospitalization in the under 80 in both men and women (men: OR 2.62; women OR 4.31), for treatment in intensive care (men: OR 4,41; women: OR 7.74), and for death (men: OR 5.21; women OR 5.92). The analysis of drug using showed risks effect of insulin (OR 2.13) on hospitalization, sulfonylureas/glinides (OR 2.58) on intensive care and protective of metformin on death both in single component (OR 0.44) and in multicomponent (OR 0.43). CONCLUSIONS: data availability made it possible to monitor the occurrence and explore some of the characteristics of the cases with COVID-19 in Sicily. Diabetes does not seem to represent a risk factor for SARS-CoV-2 infection in Sicily, while previous diabetes condition seems to determine greater risk of hospitalization, treatment in intensive care, and lethality among over 80. There are also gender differences with almost double risks in women for hospitalization and intensive care only. Among the antidiabetic drugs investigated, there was a risk for hospitalization and intensive care while protective for deaths. This study represents an important tool for the activation of intervention programmes in the area aimed at populations with greater health risk deriving from the effects of this new pandemic.

Are diabetes and its medications risk factors for the development of COVID-19? Data from a population-based study in Sicily.

BACKGROUND AND AIMS: Diabetes mellitus (DM) has been associated with higher incidence of severe cases of COVID-19 in hospitalized patients, but it is unknown whether DM is a risk factor for the overall COVID-19 incidence. The aim of present study was to investigate whether there is an association of DM with COVID-19 prevalence and case fatality, and between different DM medications and risk for COVID-19 infection and death. METHODS AND RESULTS: retrospective observational study on all SARS-CoV-2 positive (SARS-CoV-2+) cases and deaths in Sicily up to 2020, May 14th. No difference in COVID-19 prevalence was found between people with and without DM (RR 0.92 [0.79-1.09]). Case fatality was significantly higher in SARS-CoV-2+ with DM (RR 4.5 [3.55-5.71]). No diabetes medication was associated with differences in risk for SARS-Cov2 infection. CONCLUSIONS: in Sicily, DM was not a risk factor for COVID-19 infection, whereas it was associated with a higher case fatality.