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Covid-19 appeared in Wuhan (China), by December 2019 and rapidly spread to the rest of the world. Many countries adopted measures against its spread to protect people and national healthcare services. However, at the moment, more than 2.5 million people got infected and more than 175 thousand died in the 213 countries, areas and territories reached by the disease (official records at April 23, 2020). Countries began to adopt also measures to protect the economy and to prepare the economic recovery, once the effects are tremendous worldwide. In Portugal, measures allowed a flattered curve for Covid-19 spread. In this paper, we use an analogy to the 'drop of honey effect' to show how this curve develops. The 'drop of honey effect' is studied in terms of chaos theory and dynamic systems and is used as a framework to the way systems change in social phenomena.

AbstractIn the spreading of infectious diseases, an important number to determine is how many other people will be infected on average by anyone who has become infected themselves. This is known as the reproduction number. This paper describes a non-parametric inverse method for extracting the full transfer function of infection, of which the reproduction number is the integral. The method is demonstrated by applying it to the timeline of hospitalisation admissions for covid-19 in the Netherlands up to May 20 2020, which is publicly available from the site of the Dutch National Institute of Public Health and the Environment (rivm.nl).

Abstract Background When an emerging infectious disease like severe acute respiratory syndrome (SARS) strikes suddenly, many wonder the public's overwhelming fears of SARS may deterred patients from seeking routine care from hospitals and/or interrupt patient's continuity of care. In this study, we sought to estimate the influence of pregnant women's fears of severe acute respiratory syndrome (SARS) on their choice of provider, mode of childbirth, and length of stay (LOS) for the delivery during and after the SARS epidemic in Taiwan. Methods The National Health Insurance data from January 01, 2002 to December 31, 2003 were used. A population-based descriptive analysis was conducted to assess the changes in volume, market share, cesarean rate, and average LOS for each of the 4 provider levels, before, during and after the SARS epidemic. Results Compared to the pre-SARS period, medical centers and regional hospitals dropped 5.2% and 4.1% in market share for childbirth services during the peak SARS period, while district hospitals and clinics increased 2.1% and 7.1%, respectively. For changes in cesarean rates, only a significantly larger increase was observed in medical centers (2.2%) during the peak SARS period. In terms of LOS, significant reductions in average LOS were observed in all hospital levels except for clinics. Average LOS was shortened by 0.21 days in medical centers (5.6%), 0.21 days in regional hospitals (5.8%), and 0.13 days in district hospitals (3.8%). Conclusion The large amount of patients shifting from the maternity wards of more advanced hospitals to those of less advanced hospitals, coupled with the substantial reduction in their length of maternity stay due to their fears of SARS could also lead to serious concerns for quality of care, especially regarding a patient's accessibility to quality providers and continuity of care.

A 95-year-old male developed general subcutaneous petechiae, tongue hematoma, and melena two days after receiving the second BNT162b2 mRNA COVID-19 vaccine. Two days later, his platelet count decreased to below 1,000/µl. Laboratory testing was positive for a slight increase in D-dimer, Helicobacter pylori (H. pylori) immunoglobulin G (IgG) antibody, lupus anticoagulant, and anticardiolipin IgG antibody levels. There were no severe infections or symptomatic thrombosis. Platelet transfusions were transiently effective. He was diagnosed with newly developed immune thrombocytopenia (ITP). We administered prednisolone (PSL) at 0.5 mg/kg/day and intravenous immunoglobulin (IVIG) at 0.4 g/kg/day. From the following day, his platelet count rapidly increased, with an improvement in bleeding tendency. H. pylori was eradicated after platelet count recovery. Thrombocytopenia did not relapse although PSL was tapered three months later. Causes of thrombocytopenia after SARS-CoV-2 vaccination include ITP, vaccine-induced immune thrombotic thrombocytopenia, and thrombotic thrombocytopenic purpura. Differential diagnosis is important to determine the proper therapy. Case reports of newly diagnosed ITP after SARS-CoV-2 vaccination have been increasing recently. In these cases, including ours, the responses to steroids and IVIG were good. Further follow-up studies are needed to manage thrombocytopenia following SARS-CoV-2 vaccination.

Abstract Aims Although the new coronavirus (SARS-CoV-2) may cause an acute multiorgan syndrome (COVID-19), data are emerging on mid- and long-term sequelae of COVID-19 pneumonia. Since no study has hitherto investigated the role of both cardiac and pulmonary ultrasound techniques in detecting such sequelae, this study aimed at evaluating these simple diagnostic tools to appraise the cardiopulmonary involvement occurring after COVID-19 pneumonia. Methods and results Twenty-nine patients fully recovered from COVID-19 pneumonia were considered at our centre. On admission, all patients underwent 12-lead electrocardiogram (ECG) and transthoracic echocardiography (TTE) evaluation. Compression ultrasound (CUS) and lung ultrasound (LUS) were also performed. Finally, in each patient, pathological findings detected on LUS were correlated with the pulmonary involvement occurring after COVID-19 pneumonia as assessed on thoracic computed tomography (CT). Out of 29 patients (mean age 70 ± 10 years old; M 69%), prior cardiovascular and pulmonary comorbidities were recorded in 22 (76%). Twenty-seven patients (93%) were in sinus rhythm and two (7%) in atrial fibrillation. ECG repolarization abnormalities were extremely common (93%) and reflected the high prevalence of pericardial involvement on TTE (86%). Likewise, pleural abnormalities were frequently observed (66%). TTE signs of left and right ventricular dysfunction were reported in two patients only, but values of systolic pulmonary artery pressure were abnormal in 16 (55%) despite absence of prior comorbidities in 44% of them. Regarding LUS evaluation, most patients displayed abnormal values of diaphragmatic thickness and excursion (93%) which well correlated with the high prevalence (76%) of on pathological findings on CT scan. CUS ruled out deep vein thrombosis in all patients. Conclusions Data on cardiopulmonary sequelae after COVID-19 pneumonia are scarce. In our study, simple diagnostic tools (TTE and LUS) proved clinically useful for detection of cardiopulmonary involvement after COVID-19 pneumonia.

Početkom 2020. godine se pandemija izazvana SARS- CoV-2 virusom proširila i na Republiku Hrvatsku (RH). Zbog toga je donesen određeni broj zakona i propisa kojima je u proljeće uveden niz mjera koje su ograničile kretanje i promijenile ponašanje stanovnika (tzv. „lockdown”). Također su postupno donesene i mjere kojima se regulira provođenje zdravstvene zaštite, odnosno pojačane mjere dezinfekcije i zaštite od širenja navedenog virusa u ustanovama za pružanje zdravstvene zaštite (1, 2). Sve navedeno je imalo utjecaj na izvođenje nacionalnih preventivnih programa protiv raka (NPP), ali i ostalih radioloških pregleda. Tako su u neke države prijavile pad broja pregleda tijekom najintenzivnijih mjera od 7 do 70% (2). U našem slučaju, broj pregleda se smanjio od oko 50% (za kompjuteriziranu tomografiju - CT) pa sve do 80% za mamografiju. Ukupno je broj radioloških pretraga učinjenih na Odjelu za kliničku radiologiju, Opće županijske bolnica Požega, do sredine studenog 2020. godine, u odnosu na prethodnu godinu, bio sljedeći: radiografija 71%, CT 94%, MR 82%, mamografija 97%. Budući da je snimanje mamografije najuspješniji program u sklopu NPP, prikazat ćemo te podatke. Na razini RH je prije pandemije prosječan odaziv bio oko 37%, dok je nakon ukidanja mjera odaziv se popeo na 55- 63%, ovisno o mjesecu, sve do rujna, kada se epidemija razmahala u RH, te je odaziv pao na svega 21%. U Požeško-Slavonskoj županiji je odaziv u pravilu bio bolji, pa je prije pandemije odgovor bio 62%, a nakon ukidanja mjera 68%, da bi u rujnu pao na 27%. Stoga možemo reći kako je stanovništvo odgovorilo na ukidanje mjera i smanjenje opasnosti od pandemije s boljim odgovorom na pozive u sklopu NPP. Možemo očekivati kako će navedeno imati utjecaj na kašnjenje otkrivanja tumora (4)

A sedentary lifestyle is any type of activity that only expends a small amount of energy with an energy expenditure of not more than 1.5 METs when sitting or lying down. this has a very bad impact on health. These activities have a very bad impact on health. During the COVID-19 pandemic, people face many big challenges, one of which is social distancing in a sedentary lifestyle. The objective of this study is to describe changes in sedentary lifestyles among cardiovascular disease patients during the COVID-19 pandemic. The research design used was a literature review using 3 databases (Pubmed, Proquest, and Science Direct). The process of searching for articles using keywords and Boolean operators (AND, OR, or NOT) aims to define and expand the literature. The review found that the sedentary lifestyle increased up to 8 hours/day. In addition to what has been mentioned 4 other articles also mention an increase in sedentary lifestyle time and an increase in sitting time, this is in accordance with research conducted on the average daily duration of sedentary behaviour is 8.3 hours between Koreans and 7, 7 hours among American adults due to government regulations during the pandemic. All articles show that people who tend to be older and male have a higher risk of developing cardiovascular cases that lead to death during the COVID-19 pandemic. So it is necessary to expand the scope of information about the importance of physical activity so that all people with cardiovascular disease have high vigilance.

This study's main purpose is to provide helpful information using blood samples from COVID-19 patients as a non-medical approach for helping healthcare systems during the pandemic. Also, this paper aims to evaluate machine learning algorithms for predicting the survival or death of COVID-19 patients. We use a blood sample dataset of 306 infected patients in Wuhan, China, compiled by Tangji Hospital. The dataset consists of blood's clinical indicators and information about whether patients are recovering or not. The used methods include K-nearest neighbor (KNN), decision tree (DT), logistic regression (LR), support vector machine (SVM), random forest (RF), stochastic gradient descent (SGD), bagging classifier (BC), and adaptive boosting (AdaBoost). We compare the performance of machine learning algorithms using statistical hypothesis testing. The results show that the most critical feature is age, and there is a high correlation between LD and CRP, and leukocytes and CRP. Furthermore, RF, SVM, DT, AdaBoost, DT, and KNN outperform other machine learning algorithms in predicting the survival or death of COVID-19 patients.