Dataset Information

Forecasting COVID-19-Associated Hospitalizations under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results from an Extended SEIR Compartmental Model.

ABSTRACT: The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of 17 April 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world's centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment L was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.

SUBMITTER: Reno C

PROVIDER: S-EPMC7290384 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Forecasting COVID-19-Associated Hospitalizations under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results from an Extended SEIR Compartmental Model.

Reno Chiara C Lenzi Jacopo J Navarra Antonio A Barelli Eleonora E Gori Davide D Lanza Alessandro A Valentini Riccardo R Tang Biao B Fantini Maria Pia MP

Journal of clinical medicine 20200515 5

The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of 17 April 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world's centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we u ...[more]

PMID: 32429121

Similar Datasets

Project description:With several human cases reported annually since 2008 and the unapparent risk of infection of blood donors, the West Nile virus (WNV) is emerging as an important health issue in Europe. Italy, as well as other European countries, experienced a recrudescence of the virus circulation in 2018, which led to an increased number of human cases. An integrated surveillance plan was activated in the Emilia-Romagna and Lombardy regions (Northern Italy) since 2008 in order to monitor the intensity and timing of WNV circulation. A fundamental part of this plan consists in entomological surveillance. In 2018, the surveillance plan made it possible to collect 385,293 mosquitoes in 163 stations in the two Regions. In total 269,147 Culex mosquitoes were grouped into 2,337 pools and tested for WNV, which was detected in 232 pools. Circulation started in the central part of the Emilia-Romagna region in the middle of June, about one month before the previous seasons. Circulation suddenly expanded to the rest of the region and reached the Lombardy region in the middle of July. WNV circulated more intensively in the eastern part of the surveyed area, as confirmed by the highest number of human cases. A relationship between the number of mosquitoes collected and the virus incidence emerged, but the data obtained highlighted that the probability of detecting the virus in a given site was less than expected with a higher number of collected mosquitoes. A significant relationship was observed between the temperature recorded one week before the sampling and the number of collected mosquitoes, as well as between the estimated number of WNV-positive mosquitoes and the temperature recorded two weeks before the sampling. The two weeks delay in the influence of temperature on the positive mosquitoes is in line with the time of the virus extrinsic incubation in the mosquito. This finding confirms that temperature is one of the principal drivers in WNV mosquito infection. The surveillance system demonstrated the ability to detect the virus circulation early, particularly in areas where circulation was more intense. This allowed evaluating the effect of mosquito abundance and weather factors on virus circulation.

Project description:IntroductionItaly became the second epicenter of the novel coronavirus disease 2019 (COVID-19) pandemic after China, surpassing by far China's death toll. The disease swept through Lombardy, which remained in lockdown for about two months, starting from the 8th of March. As of that day, the isolation measures taken in Lombardy were extended to the entire country. Here, assuming that effectively there was one case "zero" that introduced the virus to the region, we provide estimates for: (a) the day-zero of the outbreak in Lombardy, Italy; (b) the actual number of asymptomatic infected cases in the total population until March 8; (c) the basic (R0)and the effective reproduction number (Re) based on the estimation of the actual number of infected cases. To demonstrate the efficiency of the model and approach, we also provide a tentative forecast two months ahead of time, i.e. until May 4, the date on which relaxation of the measures commenced, on the basis of the COVID-19 Community Mobility Reports released by Google on March 29.MethodsTo deal with the uncertainty in the number of the actual asymptomatic infected cases in the total population Volpert et al. (2020), we address a modified compartmental Susceptible/ Exposed/ Infectious Asymptomatic/ Infected Symptomatic/ Recovered/ Dead (SEIIRD) model with two compartments of infectious persons: one modelling the cases in the population that are asymptomatic or experience very mild symptoms and another modelling the infected cases with mild to severe symptoms. The parameters of the model corresponding to the recovery period, the time from the onset of symptoms to death and the time from exposure to the time that an individual starts to be infectious, have been set as reported from clinical studies on COVID-19. For the estimation of the day-zero of the outbreak in Lombardy, as well as of the "effective" per-day transmission rate for which no clinical data are available, we have used the proposed SEIIRD simulator to fit the numbers of new daily cases from February 21 to the 8th of March. This was accomplished by solving a mixed-integer optimization problem. Based on the computed parameters, we also provide an estimation of the basic reproduction number R0 and the evolution of the effective reproduction number Re. To examine the efficiency of the model and approach, we ran the simulator to "forecast" the epidemic two months ahead of time, i.e. from March 8 to May 4. For this purpose, we considered the reduction in mobility in Lombardy as released on March 29 by Google COVID-19 Community Mobility Reports, and the effects of social distancing and of the very strict measures taken by the government on March 20 and March 21, 2020.ResultsBased on the proposed methodological procedure, we estimated that the expected day-zero was January 14 (min-max rage: January 5 to January 23, interquartile range: January 11 to January 18). The actual cumulative number of asymptomatic infected cases in the total population in Lombardy on March 8 was of the order of 15 times the confirmed cumulative number of infected cases, while the expected value of the basic reproduction number R0 was found to be 4.53 (min-max range: 4.40- 4.65). On May 4, the date on which relaxation of the measures commenced the effective reproduction number was found to be 0.987 (interquartiles: 0.857, 1.133). The model approximated adequately two months ahead of time the evolution of reported cases of infected until May 4, the day on which the phase I of the relaxation of measures was implemented over all of Italy. Furthermore the model predicted that until May 4, around 20% of the population in Lombardy has recovered (interquartile range: ∼10% to ∼30%).

Project description:BackgroundThis research was performed in an area belonging to the province of the city of Bologna (Emilia-Romagna region, Northern Italy). The purpose of the present survey was to record the local knowledge concerning traditional uses of wild food plants and related practices, such as gathering, processing, cooking, therapeutic uses, with the aim of preserving an important part of the local cultural heritage.MethodsThirty-nine people still retaining Traditional Local Knowledge (TLK) were interviewed between March-April 2012 and September-October 2013 by means of open and semi-structured ethnobotanical interviews. For each plant species mentioned, we recorded the botanical family, the English common name, the Italian common and/or folk names, the parts of the plant used, the culinary preparation, and the medicinal usage. The relative frequency of citation index (RFC), a tool that measures the local cultural importance of a plant species, was also included.ResultsThe folk plants mentioned by the respondents belonged to 33 botanical families, of which the Rosaceae (14 plants) and the Asteraceae (9 plants) were the most representative. The species with the highest RFC index (0.77) were Crepis vesicaria subsp. taraxacifolia (Thuill) Thell and Taraxacum officinale Weber. Eleven folk plants were indicated as having therapeutic effects. T. officinale Weber, C. vesicaria subsp. taraxacifolia (Thuill) Thell and Sonchus spp., which are used as food, were reported to be depurative, blood cleaning, refreshing, diuretic and laxative. The most commonly used species was Urtica spp, which was also the most frequently cited for medicinal uses.ConclusionsThe present survey documented the wild food plant traditional knowledge of an area belonging to the province of the city of Bologna (Emilia-Romagna region, Northern Italy). The general perception obtained is that on one side the TLK related to wild food plants has strongly been eroded, mainly due to immigration and urbanization phenomena, whereas on the other side these plants are revaluated today because they are perceived as healthy and also because they represent the preservation of biodiversity and a way of getting back to nature.

Project description:Several viruses can be transmitted by mosquitoes. We searched some of these viruses in 20,778 mosquitoes, collected in 95 traps on the plains of Emilia-Romagna (North of Italy) in 2021. We detected West Nile virus (WNV) and Usutu virus (USUV) in pools of Culex (Cx.) pipiens. In addition, we detected two insect-specific flaviviruses in three pools of Aedes (Ae.) caspius and in two of Ae. vexans. Tahyna virus (TAHV) was detected in six pools, three of Ae. caspius and three of Cx. pipiens, and one isolated strain was obtained from one of the Ae. caspius pools. Moreover, we detected TAHV in pools of several mosquito species (Ae. caspius, Ae. vexans, Ae. albopictus, Anopheles maculipennis s.l.) collected in the previous year of surveillance. Our data indicate Ae. caspius as the species most infected with TAHV in the surveyed area. Together with the likely plasticity of the cycle, we reported strong genome stability of the TAHV, probably linked to a successful adaptation of the virus to its ecological niche. Interestingly, in six pools of Cx. pipiens we detected two associated viruses among USUV, WNV, TAHV and all the three viruses in two pools. This result allows us to assume the presence of particular conditions that prompt the circulation of arboviruses, creating the conditions for viral hot spots. While no human diseases related to Tahyna virus were reported in Italy, its detection over the years suggests that it is worth investigating this virus as a potential cause of disease in humans in order to assess its health burden. IMPORTANCE We reported in this work the detection of three Arboviruses (Arthropod-borne viruses) in mosquitoes collected in Emilia-Romagna in 2021. In addition to West Nile and Usutu viruses, which were reported from more than 10 years in the study area, we detected and isolated Tahyna virus (TAHV). We also reported detections of TAHV obtained in previous years of surveillance in different species of mosquitoes. TAHV is the potential causative agent of summer influenza-like diseases and also of meningitis. Even if human cases of disease referable to this virus are not reported in Italy, its relevant presence in mosquitoes suggests investigating the possibility they could.

Project description:OBJECTIVES:Develop predictive models for a paediatric population that provide information for paediatricians and health authorities to identify children at risk of hospitalisation for conditions that may be impacted through improved patient care. DESIGN:Retrospective healthcare utilisation analysis with multivariable logistic regression models. DATA:Demographic information linked with utilisation of health services in the years 2006-2014 was used to predict risk of hospitalisation or death in 2015 using a longitudinal administrative database of 527?458 children aged 1-13 years residing in the Regione Emilia-Romagna (RER), Italy, in 2014. OUTCOME MEASURES:Models designed to predict risk of hospitalisation or death in 2015 for problems that are potentially avoidable were developed and evaluated using the C-statistic, for calibration to assess performance across levels of predicted risk, and in terms of their sensitivity, specificity and positive predictive value. RESULTS:Of the 527?458 children residing in RER in 2014, 6391 children (1.21%) were hospitalised for selected conditions or died in 2015. 49?486 children (9.4%) of the population were classified in the 'At Higher Risk' group using a threshold of predicted risk >2.5%. The observed risk of hospitalisation (5%) for the 'At Higher Risk' group was more than four times higher than the overall population. We observed a C-statistic of 0.78 indicating good model performance. The model was well calibrated across categories of predicted risk. CONCLUSIONS:It is feasible to develop a population-based model using a longitudinal administrative database that identifies the risk of hospitalisation for a paediatric population. The results of this model, along with profiles of children identified as high risk, are being provided to the paediatricians and other healthcare professionals providing care to this population to aid in planning for care management and interventions that may reduce their patients' likelihood of a preventable, high-cost hospitalisation.

Dataset Information

Forecasting COVID-19-Associated Hospitalizations under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results from an Extended SEIR Compartmental Model.

Publications

Forecasting COVID-19-Associated Hospitalizations under Different Levels of Social Distancing in Lombardy and Emilia-Romagna, Northern Italy: Results from an Extended SEIR Compartmental Model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets