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Wastewater-based viral surveillance is a promising approach to monitor the circulation of SARS-CoV-2 in the general population. The aim of this study was to develop an analytical method to detect SARS-CoV-2 RNA in urban wastewater, to be implemented in the framework of a surveillance network in the Lombardy region (Northern Italy). This area was the first hotspot of COVID-19 in Europe. Composite 24h samples were collected weekly in eight cities from end-March to mid-June 2020 (first peak of the epidemic). The method developed and optimized, involved virus concentration, using PEG centrifugation, and one-step real-time RT-PCR for analysis. SARS-CoV-2 RNA was identified in 65 (61%) out of 107 samples, and the viral concentrations (up to 2.1 E +05 copies/L) were highest in March-April. By mid-June, wastewater samples tested negative in all the cities. Viral loads were used for inter-city comparison and Brembate, Ranica and Lodi had the highest. The pattern of decrease of SARS-CoV-2 in wastewater was closely comparable to the decline of active COVID-19 cases in the population, reflecting the effect of lock-down. Wastewater surveillance of SARS-CoV-2 can integrate ongoing virological surveillance of COVID-19, providing information from both symptomatic and asymptomatic individuals, and monitoring the effect of health interventions.

BackgroundDuring the spring of 2020, the SARS-CoV-2 epidemic has caused significant resource strain in hospitals of Lombardy, Italy, with the demand for intensive care beds for COVID-19 patients exceeding the overall pre-crisis capacity. In this study, we evaluate the effect of healthcare strain on ICU admission and survival.MethodsWe used data on 43,538 patients admitted to a hospital in the region between February 20 and July 12, 2020, of which 3,993 (9.2%) were admitted to an ICU. We applied logistic regression to model the probability of being admitted to an ICU and the probability of survival among ICU patients. Negative binomial regressions were used to model the time between hospital and ICU admission and the length of stay in ICU.ResultsDuring the period of highest hospital strain (March 16 – April 22), individuals older than 70 years had a significantly lower probability of being admitted to an ICU and significantly longer times between hospital and ICU admission, indicating elective admission due to constrained resources. Healthcare strain did not have a clear effect on mortality, with the overall proportion of deaths declining from 52.1% (95%CI 49.8-54.5) for ICU patients admitted to the hospital before March 16, to 43.4% (95%CI 41.5-45.6) between March 16 and April 22, to 27.6% (95%CI 20.0-35.2) after April 22.ConclusionsThese data demonstrate and quantify the adoption of elective admission to ICUs during the peak phase of the SARS-CoV-2 epidemic in Lombardy. However, we show that for patients admitted to ICUs, clinical outcomes progressively improved despite the saturation of healthcare resources.

BackgroundCOVID-19 case fatality rate in hospitalized patients varies across countries and studies, but reliable estimates specific for age, sex, and comorbidities are needed to design trials for COVID-19 interventions. Aim of this study is to provide population-based survival curves of hospitalized COVID-19 patients.MethodsA cohort study was conducted in Lombardy, Veneto, and Reggio Emilia using COVID-19 registries linked to hospital discharge databases containing patient clinical histories. All patients with positive SARS-CoV-2 RT-PCR test on oral/nasopharyngeal swabs hospitalized from 21st February to 21st April 2020 were identified. Kaplan Meier survival estimates were calculated at 14 and 30 days for death in any setting, stratifying by age, sex and Charlson Index.FindingsOverall, 42,926 hospitalized COVID-19 patients were identified. Patients’ median age was 69 years (IQR: 57-79), 62·6% were males, 69·4% had a Charlson Index of 0. In total, 11,205 (26·1%) patients died over a median follow-up of 24 days (IQR: 10-35). Survival curves showed that 22·0% of patients died within 14 days and 27·6% within 30 days of hospitalization. Survival was higher in younger patients and in females. Younger patients with comorbidities had a lower survival than older ones with comorbidities.InterpretationOver 27% of hospitalized COVID-19 patients died within one month in three areas of Northern Italy that were heavily affected by SARS-CoV-2 infection. Such a high fatality rate suggests that trials should focus on survival and have follow-up of at least one month.FundingThe study did not receive any external funding.Research in contextEvidence before this studyTwo recent systematic reviews with meta-analyses report case fatality rates of three to four percent in COVID-19 patients. Most studies on hospitalized cohorts report only slightly higher figures. These figures do not correspond to those derived from routinely collected clinical data in most European countries, reporting a 10% case fatality rate which has been increasing over time since the epidemic started.Robust and precise survival estimates of hospitalized COVID-19 patients which take into account prognostic factors such as age, sex and burden of comorbidities are needed to design appropriate phase II and phase III clinical studies of drugs targeting COVID-19.Added value of this studyIn this study we present the first survival estimates by age, sex and Charlson index for a large population-based cohort of Italian hospitalized COVID-19 patients.Implications of all the available evidenceOver 27% of COVID-19 patients died within one month from hospital admission. Such a high fatality rate suggests that studies should prioritize mortality as primary outcome. Furthermore, we found that the fatality rate reaches a plateau 30 days after hospitalization, suggesting that studies should have at least one month of follow up to observe deaths; shorter follow-up could lead to overestimation of treatment benefits.