Social Illness Before and After the COVID-19 Pandemic: A Regional Study.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) has dramatically changed the epidemiology of several diseases. Much evidence on this has been published in the pandemic phase. In addition, many studies have shown that phenomena such as stress, substance abuse, and burnout increased in the general population during the lockdown. Unfortunately, few studies analyze the post-pandemic phase. STUDY OBJECTIVE: The study aimed to evaluate the trend of broad social problems, such as a diagnosis by the emergency department (ED), in the post-pandemic phase in the Lombardy (Italy) region. METHODS: The study is a retrospective observational cohort study. All admissions to emergency rooms in the Lombardy region registered in the Emergency Urgency OnLine (EUOL) portal made from January through June 2019 were analyzed, having as main causes: psychiatric disorders, self-harm, substance abuse, social disadvantage, and violence. All accesses in emergency rooms in the Lombardy region registered in the EUOL portal made from January 1, 2019 through June 30, 2019 were analyzed and compared with the same period in 2022. RESULTS: The study recorded an increase in the likelihood of events of self-harm (OR = 2.1; 95% CI, 1.8-2.6; P <.0001), substance abuse (OR = 1.2; 95% CI, 1.1-1.3; P <.0001), violence by others (OR = 1.3; 95% CI, 1.2-1.4; P <.0001), and social disadvantage (OR = 1.2; 95% CI, 1.1-1.4; P = .0045). The events are more concentrated in suburban areas (OR = 1.3; 95% CI, 1.2-1.4; P <.001). CONCLUSION: The increase in diagnoses of these social problems in the ED is only the culmination of a phenomenon that hides an underlying rise in social illness. In the post-COVID-19 phase, there is a need to invest in community care and social illness prevention policies.

Missed training, collateral damage from COVID 19?

BACKGROUND: during the COVID-19 pandemic a total lockdown was enforced all over Italy starting on March 9th. This resulted in the shrinking of economic activities. In addition, all formal occupational security-training courses were halted, among them the 81/08 law lectures and Basic Life Support-Defibrillation (BLS-D) laymen training courses. The aim of the study was to evaluate the impact of the pandemic on BLS-D laymen training courses in the Lombardy region. METHODS: BLS-D training courses records for the Lombardy region were analysed. The analysis was conducted from 2016 to 2020 as part of the Hippo project. RESULTS: between 2017 and 2019 BLS-D trained laymen kept increasing, moving from 53,500 trained individuals up to 74,700. In 2020 a stark reduction was observed with only 22,160 individuals trained. Formal courses were not halted completely during 2020. Still, in the months available for training, the number of individuals enrolled showed a sharp 50% reduction. CONCLUSIONS: laymen training courses for emergency management are a fundamental component of primary prevention practice. The 81/08 and 158/12 Italian laws have decreed this practice mandatory on the workplace. Following the enforcement of the lockdown and the subsequent interruption of emergency management courses, efforts will be necessary to re-establish and guarantee the high quality training of the pre-pandemic period.

Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project.

BackgroundDuring the COVID-19 pandemic, large-scale diagnostic testing and contact tracing have proven insufficient to promptly monitor the spread of infections.AimTo develop and retrospectively evaluate a system identifying aberrations in the use of selected healthcare services to timely detect COVID-19 outbreaks in small areas.MethodsData were retrieved from the healthcare utilisation (HCU) databases of the Lombardy Region, Italy. We identified eight services suggesting a respiratory infection (syndromic proxies). Count time series reporting the weekly occurrence of each proxy from 2015 to 2020 were generated considering small administrative areas (i.e. census units of Cremona and Mantua provinces). The ability to uncover aberrations during 2020 was tested for two algorithms: the improved Farrington algorithm and the generalised likelihood ratio-based procedure for negative binomial counts. To evaluate these algorithms' performance in detecting outbreaks earlier than the standard surveillance, confirmed outbreaks, defined according to the weekly number of confirmed COVID-19 cases, were used as reference. Performances were assessed separately for the first and second semester of the year. Proxies positively impacting performance were identified.ResultsWe estimated that 70% of outbreaks could be detected early using the proposed approach, with a corresponding false positive rate of ca 20%. Performance did not substantially differ either between algorithms or semesters. The best proxies included emergency calls for respiratory or infectious disease causes and emergency room visits.ConclusionImplementing HCU-based monitoring systems in small areas deserves further investigations as it could facilitate the containment of COVID-19 and other unknown infectious diseases in the future.

Changes to the Major Trauma Pre-Hospital Emergency Medical System Network before and during the 2019 COVID-19 Pandemic.

OBJECTIVES: During the coronavirus disease 2019 pandemic, emergency medical services (EMSs) were among the most affected; in fact, there were delays in rescue and changes in time-dependent disease networks. The aim of the study is to understand the impact of COVID-19 on the time-dependent trauma network in the Lombardy region. METHODS: A retrospective analysis on major trauma was performed by analysing all records saved in the EmMa database from 1 January 2019 to 31 December 2019 and from 1 January 2020 to 31 December 2020. Age, gender, time to first emergency vehicle on scene and mission duration were collected. RESULTS: In 2020, compared to 2019, there was a reduction in major trauma diagnoses in March and April, during the first lockdown, OR 0.59 (95% CI 0.49-0.70; p < 0.0001), and a reduction in road accidents and accidents at work, while injuries related to falls from height and violent events increased. There was no significant increase in the number of deaths in the prehospital setting, OR 1.09 (95% CI 0.73-1.30; p = 0.325). CONCLUSIONS: The COVID-19 pandemic has changed the epidemiology of major trauma, but in the Lombardy region there was no significant change in mortality in the out-of-hospital setting.

Smart-working policies during COVID-19 pandemic: a way to reduce work-related traumas?

Eighth of March 2020, the Italian government introduced a national lockdown to counter the exponential increase in the number of COVID-19 cases; this decision avoided putting a strain on the health system. During the lockdown all non-essential services were stopped and a "stay at home" order was imposed. The purpose is to evaluate the impact of COVID-19 lockdown on Emergency Department (ED) visits due to work-related traumas in the Lombardy region. We performed a retrospective analysis on trauma admissions to the ED registered through the regional portal (EUOL), from 1st January 2019 to 31st December 2019 and from 1st January 2020 to 31st December 2020. The number of ED admissions for traumatic injury and work-related traumas dropped by 32% between 2019 and 2020. A remarkable reduction of work-related traumas was recorded during the two pandemic waves, from March to June and in October and November. The percentage of patient in critical condition in ED slightly raised. These results are probably a consequence of the unprecedented measures imposed by the Italian government to cope with the spread of COVID-19, with important implications for work contexts. This analysis should be considered to optimise the organisation of the emergency system in other critical scenarios. We speculate that the different epidemiology of occupational injuries during the lockdown period is a consequence of smart-working policies that can be held responsible for the drastic reduction of work-related traumas.

Cardiopulmonary resuscitation missed by bystanders: Collateral damage of coronavirus disease 2019.

OBJECTIVE: The coronavirus disease 2019 (COVID-19) pandemic changed the time-dependent cardiac arrest network. This study aims to understand whether the rescue standards of cardiopulmonary resuscitation (CPR) and out-of-hospital cardiac arrest (OHCA) were handled differently during pandemic compared to the previous year. METHODS: Data for the years 2019 and 2020 were provided by the records of the Lombardy office of the Regional Agency for Emergency and Urgency. We analysed where the cardiac arrest occurred, when CPR started and whether the bystanders used public access to defibrillation (PAD). RESULTS: During 2020, there was a reduction in CPRs performed by bystanders (odds ratio [OR] = 0.936 [95% confidence interval (CI95% ) 0.882-0.993], p = .029) and in the return of spontaneous circulation (ROSC) (OR = 0.621 [CI95% 0.563-0.685], p < .0001), while there was no significant reduction in the use of PAD. Analysing only March, the period of the first wave in Lombardy, the comparison shows a reduction in bystanders CPRs (OR = 0.727 [CI95% 0.602-0.877], p = .0008), use of PAD (OR = 0.441 [CI95% 0.272-0.716], p = .0009) and in ROSC (OR = 0.179 [CI95% 0.124-0.257], p < .0001). These phenomena could be influenced by the different settings in which the OHCAs occurred; in fact, those that occurred in public places with a mandatory PAD were strongly reduced (OR = 0.49 [CI95% , 0.44-0.55], p < .0001). CONCLUSIONS: COVID-19 had a profound impact on the time-dependant OHCA network. During the first pandemic wave, CPR and PAD used by bystanders decreased. The different contexts in which OHCAs occurred may partially explain these differences.

Generating High-Granularity COVID-19 Territorial Early Alerts Using Emergency Medical Services and Machine Learning.

The pandemic of COVID-19 has posed unprecedented threats to healthcare systems worldwide. Great efforts were spent to fight the emergency, with the widespread use of cutting-edge technologies, especially big data analytics and AI. In this context, the present study proposes a novel combination of geographical filtering and machine learning (ML) for the development and optimization of a COVID-19 early alert system based on Emergency Medical Services (EMS) data, for the anticipated identification of outbreaks with very high granularity, up to single municipalities. The model, implemented for the region of Lombardy, Italy, showed robust performance, with an overall 80% accuracy in identifying the active spread of the disease. The further post-processing of the output was implemented to classify the territory into five risk classes, resulting in effectively anticipating the demand for interventions by EMS. This model shows state-of-art potentiality for future applications in the early detection of the burden of the impact of COVID-19, or other similar epidemics, on the healthcare system.

Relationship between out-of-hospital cardiac arrests and COVID-19 during the first and second pandemic wave. The importance of monitoring COVID-19 incidence.

BACKGROUND: The relationship between COVID-19 and out-of-hospital cardiac arrests (OHCAs) has been shown during different phases of the first pandemic wave, but little is known about how to predict where cardiac arrests will increase in case of a third peak. AIM: To seek for a correlation between the OHCAs and COVID-19 daily incidence both during the two pandemic waves at a provincial level. METHODS: We considered all the OHCAs occurred in the provinces of Pavia, Lodi, Cremona, Mantua and Varese, in Lombardy Region (Italy), from 21/02/2020 to 31/12/2020. We divided the study period into period 1, the first 157 days after the outbreak and including the first pandemic wave and period 2, the second 158 days including the second pandemic wave. We calculated the cumulative and daily incidence of OHCA and COVID-19 for the whole territory and for each province for both periods. RESULTS: A significant correlation between the daily incidence of COVID-19 and the daily incidence of OHCAs was observed both during the first and the second pandemic period in the whole territory (R = 0.4, p<0.001 for period 1 and 2) and only in those provinces with higher COVID-19 cumulative incidence (period 1: Cremona R = 0.3, p = 0.001; Lodi R = 0.4, p<0.001; Pavia R = 0.3; p = 0.01; period 2: Varese R = 0.4, p<0.001). CONCLUSIONS: Our results suggest that strictly monitoring the pandemic trend may help in predict which territories will be more likely to experience an OHCAs' increase. That may also serve as a guide to re-allocate properly health resources in case of further pandemic waves.

Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of COVID-19 Diffusion in the Lombardy Region (Italy).

BACKGROUND: the Lombardy region in Italy was the first area in Europe to record an outbreak of COVID-19 and one of the most affected worldwide. As this territory is strongly polluted, it was hypothesized that pollution had a role in facilitating the diffusion of the epidemic, but results are uncertain. AIM: the paper explores the effect of air pollutants in the first spread of COVID-19 in Lombardy, with a novel geomatics approach addressing the possible confounding factors, the reliability of data, the measurement of diffusion speed, and the biasing effect of the lockdown measures. METHODS AND RESULTS: all municipalities were assigned to one of five possible territorial classes (TC) according to land-use and socio-economic status, and they were grouped into districts of 100,000 residents. For each district, the speed of COVID-19 diffusion was estimated from the ambulance dispatches and related to indicators of mean concentration of air pollutants over 1, 6, and 12 months, grouping districts in the same TC. Significant exponential correlations were found for ammonia (NH3) in both prevalently agricultural (R2 = 0.565) and mildly urbanized (R2 = 0.688) areas. CONCLUSIONS: this is the first study relating COVID-19 estimated speed of diffusion with indicators of exposure to NH3. As NH3 could induce oxidative stress, its role in creating a pre-existing fragility that could have facilitated SARS-CoV-2 replication and worsening of patient conditions could be speculated.

OHCA survey in Lombardy: comparison between years 2014 and 2019 (pre COVID-19).

BACKGROUND AND AIM: The incidence of Out of Hospital Cardiac Arrest (OHCA) is estimated at 1/1000 persons/year. In the pre-Covid-19 era world, OHCA survival rate in Europe was 7-6%. The main objective is to analyze OHCA survival in the Lombardy region by highlighting the factors related to both the victims' characteristics and the chain of survival. METHODS: All OHCAs were grouped into four pre-established periods in 2019 (14-23 January; 15-24 April; 15-24 July; 14-23 October). Following the Utstein method, we selected witnessed OHCAs with presumed cardiac etiology. The outcome of each case was collected in four moments in time: Return of spontaneous circulation (ROSC), Emergency Department (ED), 24 hours and 30 days. The neurological outcome 30 days after OHCA was also investigated and stratified with the Cerebral Performance Category Score (CPC). RESULTS: We selected 456 cases of OHCA with witnessed cardiac etiology. ROSC was achieved in 121 cases (26.5%), survival in the Emergency Departments in 110 patients (24.1%), after 24 hours in 86 (18.86%) and after 30 days in 72 (15.8%). Male sex was shown to improve OHCA survival. A shockable presentation rhythm, Cardiopulmonary Resuscitation (CPR) performed by bystanders and the activation of Public Access Defibrillation (PAD) positively influenced OHCA outcome. CONCLUSIONS: Males are more predisposed to incur an OHCA event than females, but they have greater chances of survival. Factors most related to survival are: shockable rhythm, bystanders CPR and the activation of a PAD. (www.actabiomedica.it).

Treatment of out-of-hospital cardiac arrest in the COVID-19 era: A 100 days experience from the Lombardy region.

INTRODUCTION: An increase in the incidence of OHCA during the COVID-19 pandemic has been recently demonstrated. However, there are no data about how the COVID-19 epidemic influenced the treatment of OHCA victims. METHODS: We performed an analysis of the Lombardia Cardiac Arrest Registry comparing all the OHCAs occurred in the Provinces of Lodi, Cremona, Pavia and Mantua (northern Italy) in the first 100 days of the epidemic with those occurred in the same period in 2019. RESULTS: The OHCAs occurred were 694 in 2020 and 520 in 2019. Bystander cardiopulmonary resuscitation (CPR) rate was lower in 2020 (20% vs 31%, p<0.001), whilst the rate of bystander automated external defibrillator (AED) use was similar (2% vs 4%, p = 0.11). Resuscitation was attempted by EMS in 64.5% of patients in 2020 and in 72% in 2019, whereof 45% in 2020 and 64% in 2019 received ALS. At univariable analysis, the presence of suspected/confirmed COVID-19 was not a predictor of resuscitation attempt. Age, unwitnessed status, non-shockable presenting rhythm, absence of bystander CPR and EMS arrival time were independent predictors of ALS attempt. No difference regarding resuscitation duration, epinephrine and amiodarone administration, and mechanical compression device use were highlighted. The return of spontaneous circulation (ROSC) rate at hospital admission was lower in the general population in 2020 [11% vs 20%, p = 0.001], but was similar in patients with ALS initiated [19% vs 26%, p = 0.15]. Suspected/confirmed COVID-19 was not a predictor of ROSC at hospital admission. CONCLUSION: Compared to 2019, during the 2020 COVID-19 outbreak we observed a lower attitude of laypeople to start CPR, while resuscitation attempts by BLS and ALS staff were not influenced by suspected/confirmed infection, even at univariable analysis.

The Lombardy Emergency Medical System Faced with COVID-19: The Impact of Out-of-Hospital Outbreak.

OBJECTIVE: The Lombardy region was among the areas most affected by COVID-19 infection worldwide; the Lombardy Emergency Medical System (EMS) responded immediately to this emergency. We analyzed several critical aspects to understand what occurred in that region. METHODS: This retrospective study compares the events managed by the dispatch center and the characteristics of the patients transported to the hospital -age, sex, SpO2, deaths- managed by the EMS in Brescia and Bergamo provinces between March-April 2020 and March-April 2019. Ambulances' waiting time at the hospitals before discharging patients and the patients' severity at emergency department admission were also analyzed. RESULTS: EMS managed 37,340 events in March-April 2020, +51.5% versus 2019. "Breathing" or "Infective" events reported to the dispatch center increased more than ten-fold (OR 25.1, p < 0.0001) in March 2020 and two-fold in April 2020 compared to 2019 (OR 3, p < 0.0001). Deaths increased +246% (OR 1.7, p < 0.0001), and patients not transported to hospital +481% (OR 2.9, p < 0.0001) in March 2020 compared to 2019. In some hospitals, ambulances waited more than one hour before discharging the patients, and the emergency departments doubled the admission of critically ill patients. Transported patients for "Breathing" or "Infective" events were primarily males (OR 1.5, p < 0.0001). The patients had lower SpO2 in 2020 than in 2019 and they were younger. CONCLUSIONS: The Lombardy region experienced an unexpected outbreak in an extremely short timeframe and in a limited area. The EMS coped with this pandemic, covering an extremely higher number of requests, with a ten-fold increase in the number of events managed.

COVID-19 kills at home: the close relationship between the epidemic and the increase of out-of-hospital cardiac arrests.

AIMS: An increase in out-of-hospital cardiac arrest (OHCA) incidence has been reported in the very early phase of the COVID-19 epidemic, but a clear demonstration of a correlation between the increased incidence of OHCA and COVID-19 is missing so far. We aimed to verify whether there is an association between the OHCA difference compared with 2019 and the COVID-19 epidemic curve. METHODS AND RESULTS: We included all the consecutive OHCAs which occurred in the Provinces of Lodi, Cremona, Pavia, and Mantova in the 2 months following the first documented case of COVID-19 in the Lombardia Region and compared them with those which occurred in the same time frame in 2019. The cumulative incidence of COVID-19 from 21 February to 20 April 2020 in the study territory was 956 COVID-19/100 000 inhabitants and the cumulative incidence of OHCA was 21 cases/100 000 inhabitants, with a 52% increase as compared with 2019 (490 OHCAs in 2020 vs. 321 in 2019). A strong and statistically significant correlation was found between the difference in cumulative incidence of OHCA between 2020 and 2019 per 100 000 inhabitants and the COVID-19 cumulative incidence per 100 000 inhabitants both for the overall territory (ρ 0.87, P < 0.001) and for each province separately (Lodi: ρ 0.98, P < 0.001; Cremona: ρ 0.98, P < 0.001; Pavia: ρ 0.87, P < 0.001; Mantova: ρ 0.81, P < 0.001). CONCLUSION: The increase in OHCAs in 2020 is significantly correlated to the COVID-19 pandemic and is coupled with a reduction in short-term outcome. Government and local health authorities should seriously consider our results when planning healthcare strategies to face the epidemic, especially considering the expected recurrent outbreaks.

Business Intelligence applied to Emergency Medical Services in the Lombardy region during SARS-CoV-2 epidemic

BACKGROUND AND AIM OF THE WORK: On the 21st of February, the first patient was tested positive for SARS-CoV-2 at Codogno hospital in the Lombardy region. From that date, the Regional Emergency Medical Services (EMS) Trust (AREU) of the Lombardy region decided to apply Business Intelligence (BI) to the management of EMS during the epidemic. The aim of the study is to assess in this context the impact of BI on EMS management outcomes. METHODS: Since the beginning of the COVID-19 outbreak, AREU is using BI daily to track the number of first aid requests received from 112. BI analyses the number of requests that have been classified as respiratory and/or infectious episodes during the telephone dispatch interview. Moreover, BI allows identifying the numerical trend of episodes in each municipality (increasing, stable, decreasing). RESULTS: AREU decides to reallocate in the territory the resources based on real-time data recorded and elaborated by BI. Indeed, based on that data, the numbers of vehicles and personnel have been implemented in the municipalities that registered more episodes and where the clusters are supposed to be. BI has been of paramount importance in taking timely decisions on the management of EMS during COVID-19 outbreak. Conclusions: Even if there is little evidence-based literature focused on BI impact within the health care, this study suggests that BI can be usefully applied to promptly identify clusters and patterns of the SARS-CoV-2 epidemic and, consequently, make informed decisions that can improve the EMS management response to the outbreak.