A repeated cross-sectional analysis on the economic impact of SARS-CoV-2 pandemic at the hospital level in Italy.

Italy was the first country in Europe to be hit by the Severe Acute Respiratory Syndrome Coronavirus 2. Little research has been conducted to understand the economic impact of providing care for SARS-CoV-2 patients during the pandemic. Our study aims to quantify the incremental healthcare costs for hospitalizations associated to being discharged before or after the first SARS-CoV-2 case was notified in Italy, and to a positive or negative SARS-CoV-2 notified infection. We used data on hospitalizations for 9 different diagnosis related groups at a large Italian Research Hospital with discharge date between 1st January, 2018 and 31st December 2021. The median overall costs for a hospitalization increased from 2410EUR (IQR: 1588-3828) before the start of the pandemic, to 2645EUR (IQR: 1885-4028) and 3834EUR (IQR: 2463-6413) during the pandemic, respectively for patients SARS-CoV-2 negative and positive patients. Interestingly, according to results of a generalized linear model, the highest increases in the average costs sustained for SARS-CoV-2 positive patients with respect to patients discharged before the pandemic was found among those with diagnoses unrelated to COVID-19, i.e. kidney and urinary tract infections with CC (59.71%), intracranial hemorrhage or cerebral infarction (53.33), and pulmonary edema and respiratory failure (47.47%). Our study highlights the economic burden during the COVID-19 pandemic on the hospital system in Italy based on individual patient data. These results contribute to the to the debate around the efficiency of the healthcare services provision during a pandemic.

The New Quadrivalent Adjuvanted Influenza Vaccine for the Italian Elderly: A Health Technology Assessment.

BACKGROUND: The elderly, commonly defined as subjects aged ≥65 years, are among the at-risk subjects recommended for annual influenza vaccination in European countries. Currently, two new vaccines are available for this population: the MF59-adjuvanted quadrivalent influenza vaccine (aQIV) and the high-dose quadrivalent influenza vaccine (hdQIV). Their multidimensional assessment might maximize the results in terms of achievable health benefits. Therefore, we carried out a Health Technology Assessment (HTA) of the aQIV by adopting a multidisciplinary policy-oriented approach to evaluate clinical, economic, organizational, and ethical implications for the Italian elderly. METHODS: A HTA was conducted in 2020 to analyze influenza burden; characteristics, efficacy, and safety of aQIV and other available vaccines for the elderly; cost-effectiveness of aQIV; and related organizational and ethical implications. Comprehensive literature reviews/analyses were performed, and a transmission model was developed in order to address the above issues. RESULTS: In Italy, the influenza burden on the elderly is high and from 77.7% to 96.1% of influenza-related deaths occur in the elderly. All available vaccines are effective and safe; however, aQIV, such as the adjuvanted trivalent influenza vaccine (aTIV), has proved more immunogenic and effective in the elderly. From the third payer's perspective, but also from the societal one, the use of aQIV in comparison with egg-based standard QIV (eQIV) in the elderly population is cost-effective. The appropriateness of the use of available vaccines as well as citizens' knowledge and attitudes remain a challenge for a successful vaccination campaign. CONCLUSIONS: The results of this project provide decision-makers with important evidence on the aQIV and support with scientific evidence on the appropriate use of vaccines in the elderly.

A quantitative assessment of epidemiological parameters required to investigate COVID-19 burden.

Solid estimates describing the clinical course of SARS-CoV-2 infections are still lacking due to under-ascertainment of asymptomatic and mild-disease cases. In this work, we quantify age-specific probabilities of transitions between stages defining the natural history of SARS-CoV-2 infection from 1965 SARS-CoV-2 positive individuals identified in Italy between March and April 2020 among contacts of confirmed cases. Infected contacts of cases were confirmed via RT-PCR tests as part of contact tracing activities or retrospectively via IgG serological tests and followed-up for symptoms and clinical outcomes. In addition, we provide estimates of time intervals between key events defining the clinical progression of cases as obtained from a larger sample, consisting of 95,371 infections ascertained between February and July 2020. We found that being older than 60 years of age was associated with a 39.9% (95%CI: 36.2-43.6%) likelihood of developing respiratory symptoms or fever ≥ 37.5 °C after SARS-CoV-2 infection; the 22.3% (95%CI: 19.3-25.6%) of the infections in this age group required hospital care and the 1% (95%CI: 0.4-2.1%) were admitted to an intensive care unit (ICU). The corresponding proportions in individuals younger than 60 years were estimated at 27.9% (95%CI: 25.4-30.4%), 8.8% (95%CI: 7.3-10.5%) and 0.4% (95%CI: 0.1-0.9%), respectively. The infection fatality ratio (IFR) ranged from 0.2% (95%CI: 0.0-0.6%) in individuals younger than 60 years to 12.3% (95%CI: 6.9-19.7%) for those aged 80 years or more; the case fatality ratio (CFR) in these two age classes was 0.6% (95%CI: 0.1-2%) and 19.2% (95%CI: 10.9-30.1%), respectively. The median length of stay in hospital was 10 (IQR: 3-21) days; the length of stay in ICU was 11 (IQR: 6-19) days. The obtained estimates provide insights into the epidemiology of COVID-19 and could be instrumental to refine mathematical modeling work supporting public health decisions.

Effectiveness and economic assessment of routine larviciding for prevention of chikungunya and dengue in temperate urban settings in Europe.

In the last decades, several European countries where arboviral infections are not endemic have faced outbreaks of diseases such as chikungunya and dengue, initially introduced by infectious travellers from tropical endemic areas and then spread locally via mosquito bites. To keep in check the epidemiological risk, interventions targeted to control vector abundance can be implemented by local authorities. We assessed the epidemiological effectiveness and economic costs and benefits of routine larviciding in European towns with temperate climate, using a mathematical model of Aedes albopictus populations and viral transmission, calibrated on entomological surveillance data collected from ten municipalities in Northern Italy during 2014 and 2015.We found that routine larviciding of public catch basins can limit both the risk of autochthonous transmission and the size of potential epidemics. Ideal larvicide interventions should be timed in such a way to cover the month of July. Optimally timed larviciding can reduce locally transmitted cases of chikungunya by 20% - 33% for a single application (dengue: 18-22%) and up to 43% - 65% if treatment is repeated four times throughout the season (dengue: 31-51%). In larger municipalities (>35,000 inhabitants), the cost of comprehensive larviciding over the whole urban area overcomes potential health benefits related to preventing cases of disease, suggesting the adoption of more localized interventions. Small/medium sized towns with high mosquito abundance will likely have a positive cost-benefit balance. Involvement of private citizens in routine larviciding activities further reduces transmission risks but with disproportionate costs of intervention. International travels and the incidence of mosquito-borne diseases are increasing worldwide, exposing a growing number of European citizens to higher risks of potential outbreaks. Results from this study may support the planning and timing of interventions aimed to reduce the probability of autochthonous transmission as well as the nuisance for local populations living in temperate areas of Europe.

Bayesian mixture models for assessment of gene differential behaviour and prediction of pCR through the integration of copy number and gene expression data.

We consider modeling jointly microarray RNA expression and DNA copy number data. We propose Bayesian mixture models that define latent Gaussian probit scores for the DNA and RNA, and integrate between the two platforms via a regression of the RNA probit scores on the DNA probit scores. Such a regression conveniently allows us to include additional sample specific covariates such as biological conditions and clinical outcomes. The two developed methods are aimed respectively to make inference on differential behaviour of genes in patients showing different subtypes of breast cancer and to predict the pathological complete response (pCR) of patients borrowing strength across the genomic platforms. Posterior inference is carried out via MCMC simulations. We demonstrate the proposed methodology using a published data set consisting of 121 breast cancer patients.