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Struct Chang Econ Dyn ; 56: 310-329, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1039569

ABSTRACT

We exploit the provincial variability of COVID-19 cases registered in Italy to select the territorial predictors of the pandemic. Absent an established theoretical diffusion model, we apply machine learning to isolate, among 77 potential predictors, those that minimize the out-of-sample prediction error. We first estimate the model considering cumulative cases registered before the containment measures displayed their effects (i.e. at the peak of the epidemic in March 2020), then cases registered between the peak date and when containment measures were relaxed in early June. In the first estimate, the results highlight the dominance of factors related to the intensity and interactions of economic activities. In the second, the relevance of these variables is highly reduced, suggesting mitigation of the pandemic following the lockdown of the economy. Finally, by considering cases at onset of the "second wave", we confirm that the territorial distribution of the epidemic is associated with economic factors.

2.
J Immunother Cancer ; 8(2)2020 10.
Article in English | MEDLINE | ID: covidwho-873574

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has overwhelmed the health systems worldwide. Data regarding the impact of COVID-19 on cancer patients (CPs) undergoing or candidate for immune checkpoint inhibitors (ICIs) are lacking. We depicted the practice and adaptations in the management of patients with solid tumors eligible or receiving ICIs during the COVID-19 pandemic, with a special focus on Campania region. METHODS: This survey (25 questions), promoted by the young section of SCITO (Società Campana di ImmunoTerapia Oncologica) Group, was circulated among Italian young oncologists practicing in regions variously affected by the pandemic: high (group 1), medium (group 2) and low (group 3) prevalence of SARS-CoV-2-positive patients. For Campania region, the physician responders were split into those working in cancer centers (CC), university hospitals (UH) and general hospitals (GH). Percentages of agreement, among High (H) versus Medium (M) and versus Low (L) group for Italy and among CC, UH and GH for Campania region, were compared by using Fisher's exact tests for dichotomous answers and χ2 test for trends relative to the questions with 3 or more options. RESULTS: This is the first Italian study to investigate the COVID-19 impact on cancer immunotherapy, unique in its type and very clear in the results. The COVID-19 pandemic seemed not to affect the standard practice in the prescription and delivery of ICIs in Italy. Telemedicine was widely used. There was high consensus to interrupt immunotherapy in SARS-CoV-2-positive patients and to adopt ICIs with longer schedule interval. The majority of the responders tended not to delay the start of ICIs; there were no changes in supportive treatments, but some of the physicians opted for delaying surgeries (if part of patients' planned treatment approach). The results from responders in Campania did not differ significantly from the national ones. CONCLUSION: Our study highlights the efforts of Italian oncologists to maintain high standards of care for CPs treated with ICIs, regardless the regional prevalence of COVID-19, suggesting the adoption of similar solutions. Research on patients treated with ICIs and experiencing COVID-19 will clarify the safety profile to continue the treatments, thus informing on the most appropriate clinical conducts.


Subject(s)
Antineoplastic Agents, Immunological/administration & dosage , Betacoronavirus/immunology , Coronavirus Infections/epidemiology , Medical Oncology/statistics & numerical data , Neoplasms/drug therapy , Pneumonia, Viral/epidemiology , Adult , Antineoplastic Agents, Immunological/adverse effects , B7-H1 Antigen/antagonists & inhibitors , B7-H1 Antigen/immunology , Betacoronavirus/pathogenicity , COVID-19 , CTLA-4 Antigen/antagonists & inhibitors , CTLA-4 Antigen/immunology , Coronavirus Infections/immunology , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Drug Prescriptions/statistics & numerical data , Female , Geography , Humans , Infection Control/standards , Italy/epidemiology , Male , Medical Oncology/standards , Neoplasms/immunology , Oncologists/statistics & numerical data , Pandemics/prevention & control , Pneumonia, Viral/immunology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , Practice Patterns, Physicians'/standards , Practice Patterns, Physicians'/statistics & numerical data , Prevalence , Programmed Cell Death 1 Receptor/antagonists & inhibitors , Programmed Cell Death 1 Receptor/immunology , SARS-CoV-2 , Surveys and Questionnaires/statistics & numerical data , Time-to-Treatment
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