Foto del docente

Gerardo Astorino

Adjunct professor

Department of Medical and Surgical Sciences

Professore a contratto a titolo gratuito per attività professionalizzanti nelle scuole di specializzazione di area sanitaria, ex D.I. 68/2015

Department of Medical and Surgical Sciences

Publications

vai alle Pubblicazioni

Publications prior to 2004

  1. COVID-19 cases before and after the “I stay at home”
    decree, Bologna Local Health Authority, Italy

    Elisa Stivanello, Vincenza Perlangeli, Davide Resi, Paolo Marzaroli, Lorenzo Pizzi,Paolo Pandolfi on behalf of the Bologna Public Health Department COVID-19 group*
    Department of Public Health, Azienda USL di Bologna, Bologna, Italy
    *The members of the Bologna Public Health Department COVID-19 group are listed at the end of the article
    Summary. Background and aim of the work: Various measures have been taken by the Italian Government to contain and mitigate the COVID-19 outbreak and on March 11th a decree called “I stay at home” put the whole nation under lockdown. Our aim is to describe sociodemographic and transmission profile of COVID-19 cases that were transmitted before and after the introduction of the decree in the Bologna Local Health Authority. Methods: Cases were classified as transmitted before or after the decree according to the date of last contact with a COVID-19 case or, if this date was unavailable, we used the date of onset of symptoms considering the incubation period. Sociodemographic, clinical and epidemiological information was
    collected by using the infectious disease monitoring database, hospital discharge, deprivation index and long term care facility databases. Results: In the period after the publication of the decree, there were more elderly, females, strangers, retired, residents in nursing homes and deprived people than in the first period. There were
    also more health care personnel and less professionals/managers, sales or office workers. In both phases, family is mentioned as the first community attended although less frequently in the second group. Conclusions: The profile of the new COVID-19 cases changed during the outbreak suggesting a differential effect of lockdown
    measures on the population. An equity lens should be used when analyzing the impact of pandemia and the measures taken to curb it. (www.actabiomedica.it) Key words: COVID-19, mitigation measures, containment measures, prevention, equity Acta Biomed 2020; Vol. 91, N. 3: IN PRESS DOI: 10.23750/abm.v91i3.9750 © Mattioli 1885
    COV I D - 1 9 u p d at e
    Introduction
    At the end of December 2019, China reported a cluster of pneumonia cases of unknown origin that would later be identified as severe acute respiratory syndrome coronavirus 2 (1). Since then, the disease,
    designed as Coronavirus Disease (COVID-19), spread to various countries and was declared a pandemia on March 2020 by WHO (2,3).
    Measures to contain and mitigate the epidemics have been taken by different countries. Containing measures including case isolation, contact tracing, quarantine and mitigation measures including general
    lockdown and social distance, seem to have worked (4) during the COVID-19 outbreak in China. Systematic review suggested that social distancing measures can be effective interventions to reduce transmission and mitigate the impact of an influenza pandemic (5). Nevertheless, given the many uncertainties regarding pathogen
    transmissibility and virulence, the effectiveness and generalizability of these efforts are still unknown (5,6).
    Timing, duration and compliance of the implementation of these measures increase the variability and the delay of their effect. It is also unknown whether they impact differently on different populations and whether in some population subgroups their effect is more rapid.
    2 E. Stivanello, V. Perlangeli, D. Resi, et al.
    In Italy the first local case of COVID-19 was diagnosed on 20 February and since then the epidemic spread in many regions disproportionately, hitting some northern areas with an exponential rise (7,8).
    The Italian Government took several restrictive measures during the following weeks, at the beginning at a local scale and with a containment goal and later at a national scale and with a mitigation goal: mandatory quarantine, active surveillance, suspension of all public events, banning of mass gatherings, closure of all educational
    institutes, and finally on 11 March a decree labeled “I Stay at home” was issued. This decree put the entire country under lockdown. All commercial and administrative activities that were considered not
    essential were suspended, all movement of people was forbidden unless for proven necessity (health, work or food supply) and self isolation when sick was highly recommended. The number of new cases kept on increasing till March 20 and then slightly decreased and
    as on April 14th they were 2972 new daily cases (9,10).
    Our aim is to describe the sociodemographic and transmission profile of COVID-19 cases that were transmitted after the introduction of the “Stay at home” decree in the Bologna Local Health Authority
    (LHA), Northern Italy as of April 14thand compare them with the cases transmitted before the introduction of the decree.
    Methods Bologna LHA is in the Emilia Romagna Region, the Italian region that as of April 14th has the highest number of COVID-19 cases after Lombardy. Bologna LHA covers an area of about 880.000 inhabitants.
    The new cases were classified into two groups: “before decree” group if the date of contact with a COVID-19 case was before 12 March (first day of the implementation of the decree) and as “after decree”group if the date of contact was 12 March or afterwards.
    If the date of the last contact with a confirmed case was unavailable we used the date of onset of
    symptoms. If the onset of symptoms occurred before 14 March we classified the case as transmitted before the lockdown, if the onset of symptoms occurred after March 25 (date of implementation of the decree + 14 days for the incubation period) we classified the case as transmitted after the decree. In order to avoid any misclassification, all other cases were excluded.
    Confirmed cases and contacts are defined according to ECDC (11). Diagnostic testing is done in accordance with the Ministry of Health Guidelines (12). During the study period the test was performed only to subjects with an epidemiological link with another case and symptoms such as fever and/or cough and/or dyspnoea or to subjects with an interstitial pneumonia.
    In Bologna, since the beginning of the outbreak, all confirmed cases of COVID-19 occurring in the area are notified at the Public Health Department who carries out contact tracing and surveillance according to national protocols. People with confirmed COVID-19 are interviewed by telephone to collect information on profession, clinical and transmission characteristics (symptoms, date of onset, travel history, and close contacts with known COVID-19, attendance for any reason of community and dates of last contact with positive cases). All the information is registered in a
    regional electronic database (SMI: Infectious Disease Surveillance) that already contains the main demographic information (age, gender, residency, citizenship) of all residents. When cases are unable to be interviewed because of physical or cognitive problems, medical personnel or cares are involved. The SMI database was the main tool we used to identify the new cases and to retrieve most of the sociodemographic and transmission characteristics. We grouped profession as: managers/professionals, sales workers/office staff, semiskilled and unskilled workers,
    all health personnel (physicians, nurses, assistants, chemists, laboratory and radiology personnel, cleaners, ambulance drivers and all other personal service), service workers (excluding health personnel), retired and other non working categories. Urban residency was attributed to cases with a residency in Bologna town. We grouped the community that the cases mentioned as attended, into five categories: family, hospital, work (excluding hospital environment), long term care facilities (LTCF) and others. As LTCFs include a broad spectrum of homes for elderly, to identify the residents in nursing home, we used the nursing home database. In addition to each case we attributed the Charlson Comorbidity Index to clinically characterize the populaCOVID-
    19 cases before and after the “I stay at home” decree, Bologna Local Health Authority, Italy 3
    tion. This index considers 19 categories of comorbidity that are defined by using the hospitalization discharge database of the two previous years (13). In this paper this index is expressed in 3 categories: no comorbidity, one comorbidity and two or more comorbidities.
    To describe the socioeconomic feature we used the Deprivation Index. The Deprivation index is developed using variables from the 2011 General Census of Population and Housing (14). Five traits that represented the multidimensionality of the social and material deprivation concept were considered: low level of  education, unemployment, non-home ownership, oneparent family and household overcrowding. The index  is calculated by summing standardized indicators. The
    index is classified in 5 groups very rich, rich, average,deprived and very deprived.
    Variables are presented as absolute and relative frequency. Person’s chi-square test was used to compare variables.
    The present is a retrospective study and no additional diagnostic tool or information was collected. As only routine and anonymized data were used, no informed consent was needed. Because the analysis was conducted as part of the surveillance activities of a public health institute, there was no need for approval by an institutional review board. Nevertheless, the study was conducted in accordance to the GDPR (General Data Protection Regulation) n° 679 07/04/2016, and Italian Law about personal data treatment (D. Lgs 30 giugno 2003). Results From 28 February to 14 April the Public Health Department of the Bologna LHA registered 2882 COVID-19 cases, corresponding to the 0.33% of the population. 
    Figure 1 shows the rapid increase in the number of cases by date of onset of symptom and date of diagnosis and the reduction of the number of new cases. 1034 cases were classified as transmitted before the decree and 1418 after the publication of the “I Stay at home” decree. 430 were excluded because the date of last contact with a positive case was missing and the onset of symptoms occurred between 14 and 25 March e.g. a period that does not allow to allocate the cases to one group or another. Table 1 shows the profile of the two groups, before and after decree. In the first group there were more males than females and the most common agegroup
    was 45 to 64 years. In the second period there Figure 1. 4 E. Stivanello, V. Perlangeli, D. Resi, et al. Table 1. Sociodemographic, clinical characteristics and community attended before and after the decree, Bologna LHA, 28 February – 14 April Before decree After decree P n % n %
    Total cases 1034 100 1418 100 Gender F 463 46,49 829 59,34 M 533 53,51 568 40,66 <0.0001
    Agegroup, years <15 14 1,35 25 1,76 0.4242 15-24 23 2,22 52 3,67 0,0405 25-44 218 21,08 313 22,07 0,5566 45-64 425 41,10 388 27,36 <0.0001 65-75 151 14,60 135 9,52 0.0001
    >75 203 19,63 505 35,61 <0.0001 Citizenship Italian 963 93,13 1272 89,70 Non italian 71 6,87 146 10,30 0,003 Urban residency 515 49,81 655 46,19 0,077 Residency in nursing homes 15 1,45 190 13,40 <0,0001 Profession Professionals/mangers 87 8,41 30 2,12 <0.001 Sales workers/office staff 197 19,05 112 7,90 <0.001 Unskilled and semiskilled workers 65 6,29 54 3,81 0.005 Health Person nel 222 21,47 433 30,54 <0,001 Service workers (excl health personnel)

    (continued on next page)
    COVID-19 cases before and after the “I stay at home” decree, Bologna Local Health Authority, Italy 5 were more women than men and the most common agegroup was the 75 years and over.
    Italians were by far the majority of cases in both groups though non Italian citizenship was higher in the “after decree” group (P=0,003). In the first period about 50% of the persons were
    rich or very rich according to the Deprivation Index, in the second period 36,9% were rich and very rich, while deprived and very deprived increased from 34% to the 47%. This distribution is maintained also after excluding residents in nursing homes (data not shown). In the second period there is a lower proportion of professionals/managers, sales or office workers (P<0,0001) and a higher proportion of health personnel and retired people (P<0,0001). In both groups family is mentioned as the first community attended even if the frequency is lower in the “after decree”
    group (P=0,001). In the second period work was mentioned less frequently as community attended (P<0,0001) whereas hospital was mentioned more often (P=0,002). Residents in nursing homes were more frequent in the second period and this was confirmed by the attendance
    to all types of LTCFs (P<0,0001). In the second period there were less cases without morbidities (P=0,004). 
    Discussion
    In this work we describe retrospectively all new cases of COVID-19 that were likely transmitted before or after the “I Stay at home” decree in Bologna LHA area from the beginning of the outbreak to April 14th. We identified 1418 cases transmitted after the introduction of the decree and show that these cases differ in terms of various features when compared to the initial cases of the outbreak. During the second period there are more women, vulnerable people because of age or comorbidities and more health personnel but less professionals, managers and sales workers/office staff than in the first period. In addition we observed also a change in the distribution of socioeconomic categories over time.
    The higher prevalence of males that is observed during the first period is in line with other studies
    on COVID-19 (15). The change in gender distribution over time suggests that the measures to control transmission had a differential effect according to gender. Women provide most of the informal care within family and given their predominant role as front line health care workers (16) are more exposed to the disease similarly to what happened in previous outbreaks (17).
    After the decree, there were more elderly and residents in LTCFs. The decree did not address the problem of LTCFs directly, visits to these facilities were already banned since the beginning of March. Though, as Mc Michael has recently reported, once COVID-19 has been introduced into a LTCFs has the potential to spread rapidly and widely (18). Residents of LTCF are at higher risk of infections and exposure (19) the nursing home provides a milieu that is conductive to
    Before decree After decree P n % n % Deprivation index*

    Table 1. Sociodemographic, clinical characteristics and community attended before and after the decree, Bologna LHA, 28 February – 14 April *only on residents; §the sum is different from total because some gave multiple answers 6 E. Stivanello, V. Perlangeli, D. Resi, et al. outbreaks of infectious diseases due to the close proximity of susceptible patients in the institutional setting
    and subsequent cross transmission of organisms among patients through contact with staff members or environmental contamination (20). Very recent studies show that a large proportion of COVID-19 infections are undocumented and that the total force of infection is mediated through these undocumented infections. 
    Identification and isolation of currently undocumented infections has in fact been recommended by some authors to fully control the epidemics (6,21). The changes in professions during the two phases  directly stems from the decree, most commercial and administrative activities were suspended and teleworking was enhanced for professionals or office staff whereas health personnel had to continue working maintaining the risk of being exposed. Rich and very rich were more frequent among cases of the first period than among cases of the second period whereas deprived or very deprived were more frequent among cases of the second period. This change could arise from different factors and not only from the lockdown. For example, rich people likely
    own larger and bigger houses where transmission within household during lockdown is more difficult, and besides the lockdown, they also have more tools to adopt behavioral changes to protect themselves and their relatives as the epidemic spread. Research on risk of transmission across population of different socioeconomic level is needed. Authors underscores that
    COVID-19 exacerbates inequalities in some countries and that part of the disproportionate impact of the COVID-19 pandemic on some community is due to structural factors that prevent those communities from practicing social distancing. In addition, front line workers are disproportionately the poorer belonging to segregated communities (22). This is a descriptive study of two groups of COVID- 19 cases with a transmission before and after the
    “I stay at home” decree. Given this type of study we cannot infer that changes between the two groups are attributable  to t he decree. Modification in the groups profile depends also on other decrees, measures and on behavioral changes that might have been adopted at different speed across the population. Nevertheless it is clear that the profile of the new cases changed over
    time and in some population subgroups COVID-19 transmission has slowed down more rapidly than in others. Further, the accuracy of respondents in reporting information is questionable, and in particular, the degree to which cases  were able to accurately recall the date of last contact and date of onset of symptom is unclear. As Sjödin et al. underline transmission continues
    to occur during lockdown especially when the reduction of activities is not complete and the household size is large (23). Specific stringent protective measures and public health strategies should be implemented for all categories that remain on the front line or for person such as residents of LTCF that cannot enjoy the benefits of general lockdown measures. Last but not least, efforts should be made to address gender and health inequity aspects and identify solutions
    to practice measures such as social distance or proper quarantine with an equity approach. To ensure that COVID-19 work is grounded in health justice, we must generate and publicly report data on how it affects different populations and social groups and use a health equity lens to examine if and how the pandemic (and the measures taken to control it) is exacerbating
    inequities.
    Acknowledgment Bologna Public Health Department COVID-19 group: Astorino Gerardo, Morena Baldini, Nicola Bossio, Elena Bovolenta, Veronica Canal, Chiara D’Eusebio, Mauro Di Bitetto,
    Filippo Ferretti, Giulia Gherardi, Maurizio Liberti, Angelo Lo Russo, Patrizia Maurizi, Francesca Mezzetti, Muriel AssuntaMusti, Marisa Padovan, Maria C ristina Pirazzini, Luciana Prete, Flavia Rallo, Filippo Sandorfi, Tiziana Sanna, Michela Stillo, Andrea Ubiali. Conflict of interest: Each author declares that he or she has no commercial associations (e.g. consultancies, stock ownership, equity interest, patent/licensing arrangement etc.) that might pose a conflict
    of interest in connection with the submitted article References 1. Zhu N, Zhang D, Wang W et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med
    2020;382:727-733.COVID-19 cases before and aft er the “I stay at home” decree, Bologna Local Health Authority, Italy 7 2. World Health Organization (WHO) Emergency Committee.
    WHO Director-General›s opening remarks at the media briefing on COVID-19 - 11 March 2020. Geneva: WHO, 2020. Available from: https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarksat- the-media-briefing-on-covid-19---11-march-2020
    3. Cucinotta M, Vanelli M. WHO Declares COVID-19 a Pandemic. Acta Biomed 2020;91:157-160.
    4. Anderson RM, Heesterbeek H, Klinkenberg D et al. How will country-based mitigation measures influence the course of the COVID-19 epidemic? Lancet 2020;395:931-934. 5. Fong MW, Gao H, Wong JY et al. Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare
    Settings-Social Distancing Measures. Emerg Infect Dis 2020;26:976-984. 6. Li R, Pei S, Chen B et al. .Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus
    (SARS-CoV2) Science 2020; 368:489-493. 7. Flaxman S , Mishra S, Gandy A et al. Estimating the number of infections and  the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries. https:// www.imperial.ac.uk/media/imperial-college/medicine/
    sph/ide/gida-fellowships/Imperial-College-COVID19- Europe-estimates-and-NPI-impact-30-03-2020.pdf 8. Remuzzi A, Remuzzi G. COVID-19 and Italy: what next? 9. Signorelli C, Scognamiglio T, Odone A. COVID-19 in Italy: impact of containment measures and prevalence estimates
    of infection in the general population. Acta Biomed. 2020;91(3-S):175-179. 10. Dipartimento della Protezione Civile. COVID-19 Italia. Monitoraggio della situazione Accessed on March 15.
    http://opendatadpc.maps.arcgis.com/apps/opsdashboard/ index.html#/b0c68bce2cce478eaac82fe38d4138b1 11. ECDC. European Centre for Disease Prevention and Control.
    Case definition and European surveillance for COVID-19, as of 2 March 2020.12. Ministry of Health. Circolare del Ministero della salute 9marzo 2020.13. Charlson ME, Pompei P, Ales KL et al. A new method ofclassifying prognostic comorbidity in longitudinal studies:development and validation. J Chronic Dis 1987; 40:373-83.14. Caranci N, Biggeri A, Grisotto L et al. The Italian deprivation index at census block level: definition, description and association with general mortality. Epidemiol Prev 2010; 34(4):167-76. 15. Guan WJ, Ni ZY, Hu Y et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020;382:1708-1720.
    16. Boniol M, McIsaac M, Xu L et al. Gender equity in the health workforce: analysis of 104 countries. World Health Organization, 2019. https://apps.who.int/iris/handle/10665/311314.
    17. Wenham C, Smith J, Morgan R. Gender and COVID-19 Working GroupCOVID-19: the gendered impacts of the outbreak. Lancet 2020;395:846-848. 18. McMichael TM, Currie DW, Clark S et al. Epidemiology of Covid-19 in a Long-Term Care Facility in King County, Washington. N Engl J Med 2020 published online Mar 27. doi: 10.1056/NEJMoa2005412. 19. Nicolle LE, Strausbaugh LJ, Garibaldi RA. Infections and antibiotic resistance in nursing homes.
    Clin Microbiol Rev 1996;1:1-17. 20. Montoya A, Mody L. Common infections in nursing
    homes: a review of current issues and challenges. Aging health 2011; 7(6): 889–899.
    21. Lavezzo E, Franchin E, Ciavarella C et al. Suppression of COVID-19 outbreak in the municipality of Vo’ Italy. doi: https://doi.org/10.1101/2020.04.17.20053157
    22. van Dorn A, Cooney RE, Sabin ML. COVID-19 exacerbating inequalities in the US report from New York. Lancet 2020; 395:3243-3244.23. Sjödin H, Wilder-Smith A, Osman S et al. Only strict quarantine measures can curb the coronavirus disease (COVID- 19) outbreak in Italy, 2020. Euro Surveill 2020;25(13). doi: 10.2807/1560-7917.ES.2020.25.13.2000280. Received: 8 May 2020
    Accepted: 14 May 2020 Correspondence:Elisa Stivanello Department of Public Health, Azienda USL di Bologna,Bologna, Italy
    Tel. +39 051 2869398
    Fax +39 051 2869394
    E-mail: Elisa.stivanello@ausl.bologna.it

Latest news

At the moment no news are available.