The novel Coronavirus (COVID-19) has been declared a global pandemic by the WHO, with 216 countries registering coronavirus outbreaks. Governments have put in place various interventions to respond to the rapid growth of infection and death (1) which have had considerable negative impacts on society. With no COVID-19
vaccine available, countries have been relying on non-pharmaceutical public health interventions (2) . Mitigation and containment strategies were targeted to flatten the contagion curve and reduce the rate of transmission, and to ensure the sustainability of health care systems in dealing with limited ICU capacity and equipment. The international experience suggests that technologies such as contact tracing, drones and robots have played a crucial role in the fight against the virus in some countries, however the experience is mixed and their overall effectiveness is still uncertain. (3) .
Italy was the first Western country to experience the COVID-19 emergency with a spiral of infections and deaths placing the country at the top of the international rankings, overtaking China on 19 th March 2020. The COVID-19 burden has challenged the cost and sustainability of regional healthcare systems and the concomitant safety of healthcare professionals, requiring a + 3.6% GDP increase in public health expenditure compared to the previous year for hospital reorganisation, community infrastructure, health personnel recruiting and equipment supply (4). The incidence of the virus has been particularly severe in Northern regions, moderate in
Central regions and mild in the Southern regions of Italy (5) . The Italian government implemented a wide range of measures to balance the complex trade-offs between ethical, public health, legal and economic problems. In the early phase of the epidemic, the Italian government applied targeted measures to the most affected areas. As of 9th March 2020, the policy interventions were extended homogeneously to all the regions despite the varied severity of the spread. The national exit strategy plan announced at the end of April began on 4 th May 2020 with the gradual relaxation of containment measures carried out in three different phases.
This paper aims to investigate and assess policy interventions implemented in Italy and the impact on health and non-health outcomes. The literature offers different measures providing a systematic cross-country tracking of COVID-19 policies (1, (6) (7) (8) . Our analysis considers a set of interventions with targeted objectives in the escalation and de-escalation phases across Italian regions from 22 nd January 2020 to 9 nd August 2020.
The remainder of this paper is organised as follows. In section 2, we present an overview of the health profile of the population and health care system of Italy. Section 3 presents the analysis of COVID-19 epidemiological trends at national and regional levels. In section 4, we describe and analyse scaling-up and scaling-down policies implemented in Italy based on a comparative conceptual framework (8) . This section considers various interventions such as measures to contain the spread of the virus, policies for prevention and cure, interventions for economic stimulus, and the introduction of new health technology. Section 5 gives an overview of the response of the health care system. In section 6, we discuss the long-term challenges and spillover effects arising from the pandemic and associated government interventions. The final section presents the implications of our results for policy and draws conclusions.
It is important to understand Italy's demographic and epidemiological features to recognise the factors associated with COVID-19. With a population of over 60 million and a surface area of over 300,000 km 2 , Italy is one of the largest and most populous countries in Europe. It is a highly developed country (9) , with the eighth largest economy in the world. The government is a parliamentary republic, with a multi-level governance system across twenty administrative regions and 107 provinces and metropolitan cities.
The Italian Constitution recognises health as a fundamental individual and collective right and stipulates that care should be guaranteed to disadvantaged people (10, 11) . This is reflected in the Italian healthcare system (Servizio Sanitario Nazionale, or SSN), established in 1978 to provide universal coverage to all citizens, EU nationals, and legal residents. Further, emergency and basic services are provided for undocumented immigrants. Since 1993, health policies and constitutional reform have driven a decentralisation of the SSN (12) . The decentralisation is reflected in the financing, provision, and governance of the twenty regional health systems (see in Table 1 in the appendix). Regional models range from integrated model to a quasi-market in Lombardy (13) . Italian healthcare expenditure amounts to 8.8% of GDP, on par with OECD average (14) . The general budget is pooled nationally and distributed to the regions. In 2018, government compulsory healthcare expenditure per capita was USD 2,545 (PPP), below the OECD average of USD 3, 994 (14) . Across regions the healthcare expenditure per capita is heterogeneous, ranging from USD 2,483 in Campania to USD 3, 251 in Friuli Venezia Giulia (15). National government financing accounted for 74.2% of total health spending in 2018, while out-of-pocket payments for 23.1% and voluntary schemes for the remaining 2.7% (14).
Arguably, having one of the best healthcare systems worldwide (16, 17) , Italy has the second highest life expectancy at birth (83.6 years) among European countries, and the eighth highest in the world (18) (19). As a result, its population (median age 46.3 years, 22% over 65 years) is the oldest in Europe and the second oldest in the world (20, 21). Italy's longevity is associated with high morbidity rates, with 40% of the total population having a chronic condition, and nearly 21% being affected by multi-chronic conditions (18) (22) . Behavioural risk factors such as diet, tobacco smoking, high body mass index, alcohol consumption and low physical activity levels contribute to the Italian population burden of disease (23). Empirical data confirms that age and morbidity are factors associated with COVID-19 mortality (24) (see Table 2 in the appendix). Among the deaths recorded in the sample period, 96.% are older than 60 years, and 96% had at least one underlying comorbidity/condition (25) (See Figure 1 in the appendix). In the early stages of the pandemic, the incidence was higher amongst men, however, in April, the distribution evened out (see Figure 2 in the appendix), limiting the role sex plays in the incidence of mortality arising from the diseases. As of 21st July 2020, 54% of confirmed cases were female (See Figure 2 in the appendix 
In Italy, COVID-19 data is made available by different institutions at national and regional levels. The inconsistency of data between different administrative levels has been a major issue (see Table 3 in the Appendix). The Italian government started to publish data on 24th February 2020, with a reasonable degree of transparency, but only a moderate level of accessibility. Important data such as ICU survival rates, hospitalised patients' outcomes, number and occupation of new beds introduced since the emergency are still missing (see Table 3 in the appendix).
This section describes the epidemiological trend of COVID-19 throughout the country. COVID-19 appeared in Italy in late January 2020, when two Chinese tourists tested positive. One month later, patient 1 was detected in Lombardy. In the following days, Lombardy and Veneto became the two initial clusters of infection, experiencing a rapid escalation of cases. Increased surveillance, through contact tracing and testing of both symptomatic and asymptomatic persons exposed to positive cases, revealed that the virus had already been spreading in many municipalities of Southern Lombardy since January 2020 (28). The contagious nature of COVID-19 caused cases to rapidly spread throughout the country (28). Nationally, the peak of contagion To compare the epidemiological figures at the regional level, we used the day each region's 50 th case was confirmed as the start of that region's outbreak. Similarly, for the numbers of deaths, we used the day the 10th fatality was recorded. We arbitrary set these starting points to reduce potential bias of the testing strategy and deaths recording at the beginning of the outbreak. Figure 3 in the appendix shows the distribution of COVID-19 cases and fatalities in Italy. Lombardy was the most affected region followed by Veneto, Emilia Romagna and Piemonte. To compensate for the likely underestimation of cases due to the classification method and the testing strategy, the Italian Bureau of Statistics (ISTAT) compared the excess deaths recorded in the first four months of 2020 with the average number of deaths across all causes in the first four months of 2015-2019 (29). This empirical analysis covers a sample of Italian municipalities (87% in March, 92% in April and 93.1% in May).
As a result, the integrated surveillance indicates that 54% of excess mortality registered in March, 82% in April and 8.5% in May 2020 can be attributed to COVID-19. The unexplained number of deaths might be attributed to three main causes: i) the higher mortality associated with the cases that were not tested; ii) indirect mortality in untested patients who died from organ dysfunctions possibly caused by COVID-19; and iii) indirect mortality due to strains on the healthcare system in the most affected areas (29). 
The Italian government declared a state of emergency on 31 st January 2020. As the first Western country to experience a major outbreak of COVID-19, Italy was faced with escalating crisis in a period of extreme uncertainty. In the absence of a COVID-19 vaccine, the only measures to contain the spread of the virus are case isolation, contact tracing and lockdown measures. The decentralised nature of the Italian health care system combined with the heterogeneous epidemiological incidence at the regional level created the need for a diverse set of policies responsive to emerging patterns, rather than a one-size fits all approach. The policy interventions (8) are categorised as follows:
1.
Policy interventions to contain the spread of the virus (behaviour, containment, mitigation) (see Roadmap 2 and Table 4 in the appendix);
Policy interventions for prevention and cure (treatments, health monitoring) (see Roadmap 3 and Table   5 in the appendix);
Technological interventions for testing, tracing and treating (see Roadmap 3 and Table 7 in the appendix);
Each policy categorisation has its own spectrum of escalating and de-escalating measures. The escalation implies the implementation of stricter or more invasive policy intervention, while the de-escalation implies the opposite.
Scaling-up and scaling-down interventions are ranked on an ordinal scale gradient that ranges from 0 to 3, where policies are classified as none (0); minimum (1); medium (2); significant (3); very significant (4) based on their significance and invasiveness. Therefore, the upper extreme of the gradient gathers the implementation of all the other measures that belong to the lower levels of the spectrum. For instance, referring to the policy interventions to contain the spread of the virus, the significance gradient ranges from no restriction to enforced lockdown ( Table 4 in the appendix). Looking at the technology interventions, the gradient measures the invasiveness ranging from no interventions to centralised GPS contact tracing ( Table 6 in the appendix).
The comparative and conceptual framework (8) uses a systematic approach to categorise policies targeted to specific objectives. It is a tool to assess the impact of policies on different sets of health and non-health related outcomes. We focus our evaluation on the following outcomes: daily reported number of deaths; case fatality rate; confirmation rate; ICU saturation; FTSE MIB index value; and unemployment rate. Despite death data might be biased as mentioned above, daily reported number of deaths and case fatality rate are selected to represent epidemiological outcomes. Such outcomes are preferred to the confirmed cases indicators as the number of fatalities is less likely to be underestimated due to the country testing strategy (1) . Furthermore, the case fatality rate provides an estimate of the daily severity of the disease over time. ICU saturation reflects the response capacity of the healthcare system. The confirmation rate shows the testing strategy variation over time, ceteris paribus 1 . The financial and economic indicators reflect the investors' expectations of the Italian economy. The unemployment rate provides a measure on how the containment measures impact the job market and the productivity nationally. We break down the analysis at regional level for all of the outcomes except for the FTSE MIB Index Value and unemployment rate, which are at national level. The analysis does not include other relevant health and non-health outcomes due to data availability or inconsistency during the period considered (i.e. length of stay in hospital, readmission rate, ICU death rate and survival rate, public and private health care expenditure, public and private bed and personnel repurposing, public and private service provision, domestic violence, mental health demand). As a robustness check, the outcomes considered are compared with the Oxford COVID-19 Government Response Tracker that includes the response, stringency, containment and health and economic support indices (1).
We report an overview of the policy categorisation considering their major impact on some outcomes of interest. Among the four policy categories mentioned above, categories 2 and 3 are combined as there is an overlap between the preventive measures and the technology development and utilisation. 
In the absence of a COVID-19 vaccine, the introduction of health resources and technology plays a fundamental role in preventing the spread of the virus. Roadmap 3 reports the principal interventions adopted by the Italian government relative to the triple Ts strategy: testing, tracing and treatment. Technological solutions using geolocation tools have been used with success to control the spread of the virus in China, Singapore and South Korea (30) . The effectiveness of such technologies relies on wide adoption, however, one possible barrier to this is the perceived invasiveness and potential breaches of privacy (31, 32) . During the outbreak, the Ministry of Health issued national guidelines for testing. The testing criteria were updated at later stages (see Table 8 in the appendix), adopting WHO and European Commission recommendations. The strictness of the criteria reflected the necessity to ration the supply of swabs, reagents and laboratory capacity. Despite the national guidelines, a homogeneous testing strategy has not been consistently applied over time, across regions, neither in terms of number nor modality (5) (see Figure 4 in the appendix). Amongst the three most affected regions, Lombardy ran fewer tests than Veneto and Emilia Despite the huge expansion of the digital health sector in Italy (with 7% increase, i.e. 1.39 billion Euro), digital health strategies are decentralised, resulting in inconsistent utilisation across different regions (37) .
The COVID-19 pandemic and the related lockdown measures have led to unprecedented economic costs around the world. The pandemic is a global shock that has affected the international economy, from financial markets where asset prices have decreased and volatility has increased characterising both the impact and future uncertainty involved with the pandemic (38), to the impacts on the supply-chain (39) . Decision-making necessary to prevent an economic collapse in such a context involves a trade-off between public health and economic prosperity (40, 41) . Using some micro and macro indicators, this section shows that Italy has suffered Roadmap 4 describes the principal economic interventions implemented by the substantial economic losses.
Italian government and the European Central Bank. To prevent the economic collapse of the country, Italy has implemented several fiscal policies. The two most significant policies were the "Cura Italia" decree implemented on 16 th March 2020 and the "Decreto Liquidità" implemented on the 8th April 2020. The "Cura Italia" brought an immediate tax boost of 16 billion Euro to help most affected sectors, strengthen the healthcare system and provide unemployment benefits. The "Cura Italia" decree was reinforced when the Council of Ministers approved the "Decreto Liquidità" (Decree-law of 8th April 2020, n. 23), allocating a total of 563 billion Euro to assist businesses by offering loan guarantees and a certain targeted tax relief. For instance, it provided 100 billion Euro as credit for small and medium enterprises, and injecting liquidity into the banking system. Furthermore, the Decree earmarks 200 billion Euro to support exporting enterprises located in Italy to access liquidity. The State and the Export credit agency cover respectively 10 % and 90% of the guarantee to support enterprises financial obligations (42).
Despite the substantial fiscal stimulus, the country has experienced the biggest quarterly economic contraction since the 2008 financial crisis. According to the latest data provided by the Italian Bureau of Statistics (ISTAT) (43), the GDP in the first quarter of 2020 decreased by 5.4% in comparison to the first quarter of 2019. The overall GDP contraction estimated for 2020 is a contraction of 8.3% (44). The crisis also impacted international trade flows. Figure 5 in the appendix shows the monthly index of import and export in millions of Euro. In the quarter March-May 2020, despite the growth in May, the economic trend is conditioned by a sharp downturn of the previous months and is largely negative for both exports and imports (respectively -29.0% and -27.7% compared to the previous quarter December 2019-February 2020) (45). According to the latest data provided by the Italian Bureau of Statistics (ISTAT) (45), in May 2020, exports record a marked decline on an annual basis (-30.4%), but with improvements compared to April (-41.5%), for both the non-EU area (-31.5% ) and the EU (-29.4%). Compared to exports, the contraction in imports (-35.2%) is wider and summarizes the drops in purchases from both markets (-38.2% from non-EU countries, -32.9% from the EU area). In May 2020, the trade balance is estimated to increase by 199 million Euro (from +5,385 million in May 2019 to +5,584 million in May 2020). Net of energy products, the balance is +6,603 million Euro (it was +8,777 million in May 2019).
Considering the domestic market, retail sales recorded a collapse for non-alimentary goods, partly offset by a marked increase in e-commerce (see Figure 6 in the appendix). Among the non-alimentary goods, the large negative variations correspond to the clothing and fur sector, followed by goods such as games, footwear and travel items. Pharmaceutical products also recorded a negative variation (46).The negative variation recorded in these sectors is likely to impact the economic fabric of the country, mainly composed by small and medium enterprises with limited investments in digitalisation directed toward to the online market.
The perceived trade-off between public health benefits and the economic impact seemed to cover a central role in the exit phase as well. Until the 26 th April 2020, the government imposed a homogenous exit strategy. As the number of cases decreased, regional governors put pressure on central government to relax some restrictions on economic activities. After 17 th May 2020, the government's policy changed, leaving the exit strategy to be decided by each region. This choice implied a heterogenous re-opening of economic activities, which helped small and medium scale companies to re-start their businesses. After the lockdown, with the de-escalation measures, the government faced a crucial phase in terms of economic recovery. To invert the negative economic trend, the Italian government announced a massive fiscal and monetary stimulus on 16 th May 2020. The decree "Rilancio" allocated around 155 billion Euro in five main areas with the aim of reorganising the hospital network to deal with COVID-19 emergency. Additionally, it guaranteed liquidity and support for Italian companies, aiding their stability during the emergency period and encouraging their revival at the time of recovery.
This section describes the policy implemented by the government to cope with the limited capacity of the health care system and the challenges of the COVID-19 pandemic. The central government is responsible for public health interventions; however, the decentralisation of the Italian healthcare system hindered the implementation of a homogeneous strategy. Regional health care systems differ widely in terms of hospital organisation (public versus private), equipment (number of beds etc.) and medical workforce (15).
Following a decree implemented on 1 st February 2020, the government facilitated the urgent increase of hospital beds in all regions by 50% in ICU and 100% in pulmonology and infectious disease wards. The measure entailed the immediate redistribution of hospitalised patients to accredited private structures to ease the pressure on the public system. The National Health System is composed of 80% public and 20% private beds, with substantial regional variations, ranging from 21.2% of public beds in Lombardy to 97.9% in Basilicata (15).
Increasing the number of ICU beds appears to have largely prevented saturation, except for Lombardy, which experienced an overloading of the system from 1st April 2020 (see Figure 7 in the appendix). The available data does not give further information on patient outcomes. Patients' length of stay, discharge, re-admission and mortality rate data are necessary to fully evaluate the healthcare system performance and the health policies implemented by the government (47).
The overall standard national health budget increase for 2020 amounts to 1.4 billion Euro with a Decree of 17 th March (4). As part of this budget increase, the government spent 356 million Euro to implement the "Aid Distribution System", distributing disposable and durable medical materials to each region (28). The most common disposable materials distributed were masks (90%), gloves (4%), and diagnostic kits (2%). Durables materials included glasses (89%) and thermometers (3%). Veneto received the highest amount of materials and Molise the least. Between 24 th March and 19 th April 2020, the government also distributed 4,532 ventilators, of which 15% went to Lombardy and 13% to Emilia Romagna. Following a decree implemented on 9 th March 2020, the government committed 660 million Euro to hire 20,000 medical personnel on six-month contracts.
Regions autonomously managed this hiring process, making it hard to access the relevant data (28). On 19 th May, "Decreto Rilancio" allocates 1,500 million Euro to National Emergency fund and 2,723 million Euro to strengthen emergency departments and community care (4).
This section has two aims. Firstly, we test whether the escalation and de-escalation stringency measures to contain the spread of the virus were justified by the underlying epidemiological trend for all the regions, using the t-test analysis. Our goal is to test whether differences in means of scaling-up and scaling-down policies are statistically significant. The daily death trend is chosen as the indication of the epidemiological trend. Secondly, we describe through a graphical analysis how the health and non-health outcomes were impacted by the policies presented in the conceptual framework. The graphical analysis aims at evaluating if differences in the levels of the policies gradient have had a detectable impact on given outcomes across different areas of the country and may be assessed over different lags of time 2 .
In the absence of a counterfactual scenario, we run a t-test analysis on the mean of the daily number of deaths for each region throughout the period of each single policy (see Table 2 ). The analysis defines whether the difference in the daily number of deaths between each containment policies implemented in the escalation and de-escalation phase is statistically significant to justify the implementation of a more or less stringent policy.
Despite the death trend might be influenced by other policy interventions (such as increase of the ICU capacity and more effective preventive method), it still is more reliable compared to other epidemiological measures. The analysis covers the period 24 th February to 9 th August 2020. A value between 0 (no intervention) and 4 (very significant intervention) is assigned to each policy to represent its strictness (see Table 1 in the appendix). The policy classifications of Lombardy, Emilia Romagna and Veneto are displayed in three separate columns since targeted lockdown measurers were implemented before the national lockdown (see Table 2 in the appendix).
Overall, the escalation measures were found to be justified by the underlying death trend. Considering the very that the enhanced testing capacity corresponds to the flattening of the case fatality rate and to a reduced confirmation rate (see Figure 8 in the appendix).
In early March 2020, significant containment interventions were required to ensure the sustainability of the Italian healthcare system, especially in Northern regions. The lockdown implemented on the 9 th of March 2020, and the closure of business activities of the 22 nd March 2020 coincides with a decreasing trend in daily mortality, especially in northern regions in late March (see Figure 9 in the appendix). Faster policies escalation in the epicentre of the pandemic might have resulted in a lower peak of deaths, flattening the contagion curve (see Figure 9 in the appendix). Despite the substantial distribution of equipment throughout the regions, the ICU wards were close to full capacity in the Northern regions. Although Northern and Central regions faced a similar increase in the saturation rate until 14 th March 2020, the lockdown timing seemed to be effective in the Central and Southern regions where the severity of the contagion was mitigated, starting to flattener before than in Northern regions (see Figure 9 in the appendix). The case fatality rate stabilisation coincides with the government's announcement of the exit strategy at the end of April 2020 (see Figure 9 in the appendix).
During the period considered in the analysis, the government did not invest resources for the development of tracing technology, which was instead developed for free by a private company. On 9 th May 2020, at the start of the exit phase, the government launched a seroprevalence study on a sample of 150,000 individuals. However, significant technological interventions seemed to be far from having any impact on the outcomes considered (daily number of reported deaths and ICU saturation) due to delayed implementation (see Figure 10 in the appendix). The case fatality rate flattened, and the confirmation rate decreased even though minimal technological interventions were in place (see Figure 10 in the appendix). The impact of significant technological interventions could be better assessed if a second wave of COVID-19 (or similar diseases) were to occur in the future.
The stringency of the measures is negatively correlated with socio-economic factors. Figure 12 in the appendix shows an inverse relationship between the stringency of the containment measures and the stock market index value. Figure 12 in the appendix shows the daily performance of FTSE MIB and the response to major fiscal stimulus packages in Italy. The period from February to mid-March 2020 saw some of the most significant daily drops in the performance of FTSE MIB index. Following the two major decrees, "Cura Italia" and "Decreto
Liquidità", it recorded an increase. In particular, the week beginning 16 th March 2020 showed an increase in FTSE MIB (see Figure 11 in the appendix). Since 25th May 2020, the FTSE MIB index has steadily increased, in response to the stimulus and improving expectations surrounding the recovery effort associated with COVID-19. The lockdown and the subsequent closure of most activities also affected the job market although the unemployment rate did not entirely reflect the lockdown effect due to the reduction in the labour force that decreased by 5% in April 2020 compared to January 2020 decreasing (36) (see Figure 12 in the appendix). The results displayed in this analysis are consistent with the Oxford COVID-19 Government Response Tracker indices (see Figures 13,14,15 and 16 in the appendix) (1). COVID-19 also had a huge impact on patients' access to health care, essential services, and education facilities.
The high saturation rate in ICU due to a large number of severe COVID-19 cases caused a 23.5% decline in organ donation. As of 4th March 2020, schools and universities closed their facilities and began offering online classes. Although online schooling may represent an effective means of education provision, access is dependent on the availability of internet connection and electronic equipment (i.e. computer, laptop, tablets). With schools remaining closed during the exit strategy, and concerns for a potential second wave in Autumn, the inequality in access may persist, with potential long-term consequences.
The outbreak of COVID-19 significantly affected Italy with severe health, social and economic consequences. The production of future government policy; with the transparency and ready availability of data essential. evidence-based interventions is relevant for reducing uncertainty around the interventions, thereby maximising the resource and investment allocations. A detailed appraisal of the data management system between regions and central government is missing and represents a limitation for further studies.
The threat of future pandemics should drive the government's investments and resources to prevent and promote public health, strengthening community and territorial services, which demonstrate to be particularly successful in some regions to respond to health services organisation and delivery challenges. As far as the sustainability of the healthcare system is concerned, policymakers should focus on the elaboration of the promotion, prevention and early intervention framework to prevent suicide and lower the long-term impact on people's mental health due to isolation, social distancing and high stress levels. Mental health programs should be targeted for different population groups, prioritising those at higher risk. Moving forward governments need to identify and implement plans to mitigate the negative effects of a pandemic on vulnerable groups across society which includes elderly in the home care facilities, students, families with children and the impacted workforce. Ischemic heart disease (28%) 4
Atrial Fibrillation (22.2%) 5
Chronic renal failure (20%)
Chronic Obstructive Pulmonary Disease (16.6%) 7
Dementia (16.1%) 8
Active cancer in the past 5 years (15.9%) 9
Hearth failure (15.7%) Source: Data provided by ISS (25) (3) Prime Minister signed "Phase 2" Decree-starting from the 4th May. It has three phases 1.
From the 4 th May: 1) Parks reopening; 2) Free movement in the same region; 3) Free movement in different regions has to be justified by heath, work reasons; 3) Relatives visiting with personal protections; 4) sport activities is allowed at 2 meters social distancing form others; 5) athletes training will be allowed for individual sports; 6) funeral ceremonies open air: 15 people maximum; 7) bar and restaurants take away; 8). restart of activities: manufacturing, building companies, transportations respecting security and hygienic -new security guidelines 2.
From the 18 th May: 1) Reopening of commercial activities, museums, libraries; 2) team sport activities allowed.
From the 1  programs of the biomedical and telemedicine sector,  strengthening of the national system of production of medical devices and  services aimed at the prevention of health emergencies 15/05/2020 Significant (3) Decree "Rilancio"  155 billion financing workers, firms, healthcare system, touristic sector  55 billion to finance the firms' debt (1) 