Functional data analysis characterizes the shapes of the first COVID-19 epidemic wave in Italy.
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ABSTRACT:
SUBMITTER: Boschi T
PROVIDER: S-EPMC8405612 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:There is evidence that adoption of non-pharmaceutical containment measures (NPMs) may have had a major impact on Covid-19 epidemic dynamics, and mitigated its effect on healthcare system. Optimal timing of implementation of these measures however is not known. In Italy, a national lockdown was decided on March 11th 2020 and ended 4th of May. At that time, cumulative incidence (CI) was different in Italian regions which ranged from <5 cases/100,000 to >11 cases/100,000 inhabitants. In this paper, we aim to evaluate how level of incidence in different regions at the time of implementation of NPMs affected CI and had an impact on the healthcare system in terms of ICU bed occupancy and mortality rates. We used regional daily new COVID-19 diagnosed cases as well number of people hospitalized in ICU and number of deaths for period February 24-May 11 from all the 19 Italian regions and two autonomous provinces. For each region we calculated: temporal daily trend of cumulative cases of Covid-19/100,000 inhabitants, daily trend of ICU bed occupancy and mortality rate at the end of period. We found that the epidemic curves show similar trends for all regions and all tend to flatten between 11-32 days. However, after 2 months, regions with lower CI at lockdown remained at substantially lower CI (<265 cases/100,000), had a peak of percentage of cases hospitalized in ICU which did not exceed 79.4% and a mortality<0.27/1,000. On the other hand, in regions with higher incidence at lockdown, CI reached 382-921 cases/100,000, the peak of percentage of cases hospitalized in ICU and mortality rate reached 270%, and 1.5/1,000, respectively. Our data suggests that level of CI at the moment of lockdown is important to control the subsequent spread of infection so NPMs should be adopted very early during the course of Covid-19 epidemic, in order to mitigate the impact on the healthcare system and to reduce related mortality.
| S-EPMC7846280 | biostudies-literature
Project description:Thailand was the first country reporting the first Coronavirus disease 2019 (COVID-19) infected individual outside mainland China. Here we delineated the course of the COVID-19 outbreak together with the timeline of the control measures and public health policies employed by the Thai government during the first wave of the COVID-19 outbreak in Thailand. Based on the comprehensive epidemiological data, we reconstructed the dynamics of COVID-19 transmission in Thailand using a stochastic modeling approach. Our stochastic model incorporated the effects of individual heterogeneity in infectiousness on disease transmission, which allows us to capture relevant features of superspreading events. We found that our model could accurately capture the transmission dynamics of the first COVID-19 epidemic wave in Thailand. The model predicted that at the end of the first wave, the number of cumulative confirmed cases was 3091 (95%CI: 2782-3400). We also estimated the time-varying reproduction number (Rt) during the first epidemic wave. We found that after implementing the nationwide interventions, the Rt in Thailand decreased from the peak value of 5.67 to a value below one in less than one month, indicating that the control measures employed by the Thai government during the first COVID-19 epidemic wave were effective. Finally, the effects of transmission heterogeneity and control measures on the likelihood of outbreak extinction were also investigated.
| S-EPMC8821624 | biostudies-literature
Project description:As the COVID-19 outbreak traveled through various Italian regions, all national and local administrations issued measures to counter the spread of the contagion and organize healthcare. The Italian healthcare system is, indeed, a decentralized system with 21 regional health systems (RHSs), with different models of healthcare service delivery and organization. This study investigates whether a different organization of RHSs would have led to different management of the COVID-19 epidemic, and evaluates the effect of different approaches in epidemic management on the COVID-19 epidemiological trend. A set of indicators is identified by conducting an online synchronous Focus Group, involving an experts panel. A Pearson's correlation test was performed on the values assumed by the historical series of indicators investigate correlations among the trends represented by the indicators or between them and external factors. The comparison between the experiences of the different Italian regions, regarding the management of the epidemic, has helped to confirm and emphasize the importance of a community-based approach in health care-integrated with the hospital's functions for the care of complex conditions and the need for specialized assistance.
| S-EPMC8125969 | biostudies-literature
Project description:BackgroundPiacenza is the closest city to the first coronavirus disease 2019 (COVID-19) cluster in Italy and has the highest national COVID-19 death rates per population. The objective of this study is to present characteristics and outcomes of patients admitted to medical departments of the Hospital of Piacenza during the first wave of the epidemic.MethodsA total of 218 patients with confirmed or suspect COVID-19 and severe pneumonia were included from February 21st to May 15th, 2020. Routinely-collected clinical and laboratory data were retrospectively retrieved from electronic medical files. A Cox proportional-hazards model was fit to assess the association of treatment and other variables with death.ResultsMedian age of patients was 68 years; 150 patients (69%) had comorbidities, mainly hypertension (107, 49%). Overall, 185 (85%) patients had acute respiratory distress syndrome (ARDS) on admission, including 103 (47%) with moderate or severe ARDS. Chest computed tomography scan showed bilateral disease in 201 (98%) and extensive lung involvement in 79 (50%) patients. Most patients received antiviral treatment (187, 86%) and corticosteroids (134, 61%). All patients received respiratory support and 64 (29%) were admitted to intensive care unit. As of June 30th, 100 patients (46%) died, 109 patients (50%) were discharged, and 9 patients (4%) were still hospitalized. In multivariable Cox analysis, age above 65 years, having more than one comorbidity, severe ARDS, low platelet counts, and high LDH levels at admission were associated with mortality, while having diarrhea at admission was associated with survival. The use of antivirals or corticosteroids was not associated with survival.ConclusionsOverall case fatality rates were high and associated with comorbidities, extensive lung involvement, ARDS at admission, and advanced age. The use of antivirals was not associated with increased survival.
| S-EPMC7723761 | biostudies-literature
Project description:The aim of this study is to explore qualitatively bereavement experiences of family members who have lost a significant other to coronavirus disease 2019 (COVID-19) in relation to mourners' needs and resources. Twenty individuals bereaved by the first wave of COVID-19 from the most heavily impacted Italian region were interviewed via video call between 1 and 3 months after their loss. Through a thematic analysis, four main themes were identified: reconstructions of the loss experience, responses to grief, resources and looking forward. The suddenness of the death and lack of farewell by means of a funeral prevented participants from realizing the loss and undertaking a meaning-making process. When anger was the main reaction to the loss, mourners focussed all their attention on denouncing medical and government institutions. Acceptance occurred particularly in those who found a way to share their grief and use it as a turning point. Participants relied mainly on informal support offered virtually, but mourners may have sought out in-person comfort in the long term. The results of this study propose new insights for COVID-19 bereavement support and trace the path for health promotion within a community shook by a communal grief experience. Please refer to the Supplementary Material section to find this article's Community and Social Impact Statement.
| S-EPMC9083240 | biostudies-literature
Project description:The effects of exposure to atmospheric pollution on the incidence and mortality due to COVID-19 have been studied but not for sulfur dioxide (SO2) in most studies. However, most studies failed to consider important cofounding factors in the estimation of health effects of air pollution. The objective of the study was to assess the short- and long-term effects of air pollution on the COVID-19 risk and fatality in Lombardy and Veneto. Air pollutants were studied based on monitoring station information in Lombardy and Veneto from January 2013 to May 2020. The daily number of cases and deaths of COVID-19 were collected from the reports of the Italian Ministry of Health in Italy. A generalized linear model with the generalized estimating equation method was used to evaluate the effects of short- and long-term exposure to air pollution on the COVID-19 outbreak in Lombardy and Veneto. After adjusting for other covariates, we found that short-term exposure to PM2.5 and PM10 had a tendency to increase the incidence and mortality of COVID-19 than long-term exposure, while for other air pollutants, including SO2 and NO2, long-term exposure was more significant than short-term exposure. Both short- and long-term exposure of SO2 resulted in increased health effects on COVID-19 pandemic. Our findings suggest that exposure to atmospheric pollution has a significant impact on COVID-19 pandemic and call for further researches to deeply investigate this topic.
| S-EPMC8123517 | biostudies-literature
Project description:ObjectiveIn this study, we investigated the impact of COVID-19 NPIs in South Africa to understand their effectiveness in the reduction of transmission of COVID-19 in the South African population. This study also investigated the COVID-19 testing, reporting, hospitalised cases, excess deaths and COVID-19 modelling in the first wave of the COVID-19 epidemic in South Africa.MethodsA semi-reactive stochastic COVID-19 model, the ARI COVID-19 SEIR model, was used to investigate the impact of NPIs in South Africa to understand their effectiveness in the reduction of COVID-19 transmission in the South African population. COVID-19 testing, reporting, hospitalised cases and excess deaths in the first COVID-19 epidemic wave in South Africa were investigated using regressional analysis and descriptive statistics.FindingsThe general trend in population movement in South African locations shows that the COVID-19 NPIs (National Lockdown Alert Levels 5,4,3,2) were approximately 30% more effective in reducing population movement concerning each increase by 1 Alert Level. The translated reduction in the effective SARS-CoV-2 daily contact number (β) was 6.12% to 36.1% concerning increasing Alert Levels. Due to the implemented NPIs, the effective SARS-CoV-2 daily contact number in the first COVID-19 epidemic wave in South Africa was reduced by 58.1-71.1% while the peak was delayed by 84 days. The estimated COVID-19 reproductive number was between 1.98 to 0.40. During South Africa's first COVID-19 epidemic wave, the mean COVID-19 admission status in South African hospitals was 58.5%, 95% CI [58.1-59.0] in the general ward, 13.4%, 95% CI [13.1-13.7] in the intensive care unit, 13.3%, 95% CI [12.6-14.0] on oxygen, 6.37%, 95% CI [6.23-6.51] in high care, 6.29%, 95% CI [6.02-6.55] on ventilator and 2.13%, 95% CI [1.87-2.43] in isolation ward respectively. The estimated mean South African COVID-19 patient discharge rate was 11.9 days per patient. While the estimated mean of the South African COVID-19 patient case fatality rate (CFR) in hospital and outside the hospital was 2.06%, 95% CI [1.86-2.25] (deaths per admitted patients) and 2.30%, 95% CI [1.12-3.83](deaths per severe and critical cases) respectively. The relatively high coefficient of variance in COVID-19 model outputs observed in this study shows the uncertainty in the accuracy of the reviewed COVID-19 models in predicting the severity of COVID-19. However, the reviewed COVID-19 models were accurate in predicting the progression of the first COVID-19 epidemic wave in South Africa.ConclusionThe results from this study show that the COVID-19 NPI policies implemented by the Government of South Africa played a significant role in the reduction of COVID-19 active, hospitalised cases and deaths in South Africa's first COVID-19 epidemic wave. The results also show the use of COVID-19 modelling to understand the COVID-19 pandemic and the impact of regressor variables in an epidemic.
| S-EPMC10403893 | biostudies-literature
Project description:Italy was a country severely hit by the first coronavirus disease 2019 (COVID-19) pandemic wave in early 2020. Mortality studies have focused on the overall excess mortality observed during the pandemic. This paper investigates the cause-specific mortality in Italy from March 2020 to April 2020 and the variation in mortality rates compared with those in 2015-2019 regarding sex, age, and epidemic area. Causes of death were derived from the national cause-of-death register. COVID-19 was the leading cause of death among males and the second leading cause among females. Chronic diseases, such as diabetes and hypertensive, ischemic heart, and cerebrovascular diseases, with decreasing or stable mortality rates in 2015-2019, showed a reversal in the mortality trend. Moreover, mortality due to pneumonia and influenza increased. No increase in neoplasm mortality was observed. Among external causes of death, mortality increased for accidental falls but reduced for transport accidents and suicide. Mortality from causes other than COVID-19 increased similarly in both genders and more at ages 65 years or above. Compared with other areas in Italy, the Lombardy region showed the largest excess in mortality for all leading causes. Underdiagnosis of COVID-19 at the beginning of the pandemic may, to some extent, explain the mortality increase for some causes of death, especially pneumonia and other respiratory diseases.
| S-EPMC8776013 | biostudies-literature
Project description:BackgroundAt the onset of the COVID-19 pandemic, support for breastfeeding was disrupted in many countries. Italy was severely impacted by the pandemic and is known to have the lowest exclusive breastfeeding rate of all European countries. Considering the inverse association between anxiety and breastfeeding, maternal concerns about the COVID-19 emergency could reduce breastfeeding rates. The aim of the study is to explore the association between infant feeding practices and maternal COVID-19 concerns.MethodsThis paper is a secondary analysis of the cross-sectional study COVID-ASSESS conducted in Italy in 2020. The original survey was administered in two phases: during the first lockdown and during the reopening. The survey included five sections: socio-demographic, medical history, concerns about the COVID-19 pandemic, infant feeding practices and psychometric evaluation. Participants were considered eligible for the post-hoc analyses if they were exclusively breastfeeding or they were feeding with infant formula (either alone or with breastfeeding) at the time of the interview.ResultsBetween phase 1 and phase 2 there was a decrease in anxiety and concerns about the danger of COVID-19 to general health, except for concerns about their baby's health. Women using formula were more concerned about all the health topics investigated. Moreover, they showed higher levels of stress, state anxiety, somatization and PTSD symptoms.ConclusionBreastfeeding during the first pandemic lockdown in Italy seems to have been an independent factor associated with lower anxiety about COVID-19, fewer psychopathological symptoms, and a positive experience of infant feeding.
| S-EPMC9445494 | biostudies-literature
Project description:ObjectivesIn this data collation study, we aimed to provide a comprehensive database describing the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19) throughout the main provinces in China.MethodsFrom mid-January to March 2020, we extracted publicly available data regarding the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted descriptive analyses of the epidemic in the six most-affected provinces.ResultsSchool closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends differed among provinces. Compared with Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as the local transmission of COVID-19 declined, switching the focus of measures to the testing and quarantine of inbound travellers may have helped to sustain the control of the epidemic.ConclusionsAggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database containing these indicators and information regarding control measures is a useful resource for further research and policy planning in response to the COVID-19 epidemic.
| S-EPMC7603985 | biostudies-literature