Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance

Early outbreak detection is a key aspect in the containment of infectious diseases, as it enables the identification and isolation of infected individuals before the disease can spread to a larger population. Instead of detecting unexpected increases of infections by monitoring confirmed cases, syndromic surveillance aims at the detection of cases with early symptoms, which allows a more timely disclosure of outbreaks. However, the definition of these disease patterns is often challenging, as early symptoms are usually shared among many diseases and a particular disease can have several clinical pictures in the early phase of an infection. As a first step toward the goal to support epidemiologists in the process of defining reliable disease patterns, we present a novel, data-driven approach to discover such patterns in historic data. The key idea is to take into account the correlation between indicators in a health-related data source and the reported number of infections in the respective geographic region. In an preliminary experimental study, we use data from several emergency departments to discover disease patterns for three infectious diseases. Our results show the potential of the proposed approach to find patterns that correlate with the reported infections and to identify indicators that are related to the respective diseases. It also motivates the need for additional measures to overcome practical limitations, such as the requirement to deal with noisy and unbalanced data, and demonstrates the importance of incorporating feedback of domain experts into the learning procedure.

Early Symptoms of Patients With COVID-19 in Family Medicine Centers in South India: A Retrospective Study

Introduction: A recent Cochrane review on the diagnostic accuracy of initial signs and symptoms of COVID-19 reported on the lack of evidence from studies conducted in community-based health-care settings. Since a broad spectrum of patients present to primary health-care services, testing for patients with noninfluenza-like illness and atypical presentations is debatable. Hence, there is an urgent need for documenting the early presenting symptoms of COVID-19 among patients seeking medical care in primary health-care settings. Aim: In this study, we aim to document the early symptoms of patients with COVID-19 and the proportion of asymptomatic infection in family medicine centers in South India. Design: This is a retrospective study of the early symptoms of patients who tested positive between June and December 2020. The data and clinical notes of patients were retrieved from the hospital information system. Setting: This study was undertaken by the Department of Family Medicine (DFM) in a private not-for-profit academic institution in South India. The DFM provides primary and secondary health-care services to nearly 1,50,000 patients from the local urban communities. Results: A total of 330 patients were tested for COVID-19 and the study included 94 patients who tested positive. Around 37% participants were asymptomatic. The commonest symptom was fever (58.6%), followed by tiredness/myalgia (48.3%), loss of taste or smell or appetite (43.1%), and cough or cold (37.9%). Most participants (78.2%) were hospitalized and the rest (21.8%) were home-quarantined. Only 5 (5.7%) of them died due to COVID-19 infection. Conclusion: The results of the study reiterates the role of social distancing, self-isolation, proper masking, and greater vaccination coverage as significant public health interventions.

The Impact of Study Mode (Online vs. Hybrid) on Early Symptoms of Depression and Coping Strategies among University Students in Poland in Time of COVID-19 Pandemic—Preliminary Study

Introduction: mental health has been one of the most important issues surrounding the COVID-19 pandemic; mental disorders can be exacerbated by isolation during lockdowns or online learning. The aim of this study was to analyze the relationship between non-clinical (early) symptoms of depressed moods, personality traits, and coping strategies, as well as whether the learning mode (online versus hybrid) differentiates the experiences of these early symptoms and coping strategies. Methods: 114 university students aged 19 to 34, whose education model was changed from stationary to hybrid or online due to COVID-19 restrictions, participated in the study. The participants completed the online questionnaire, which consisted of two sections: (1) demographic questions to characterize the subjects and 44 questions based on the literature review. (2) Mini-COPE Inventory. Results: the study showed that the fully online study mode has a negative impact on the mental health of students; hybrid students are more likely to use active and positive coping strategies, which effectively help to control negative thoughts and/or reduce negative mental states. Conclusions: the COVID-19 pandemic has had significant psychological effects that will extend to coming years; therefore, implementing systemic psychological care is of utmost importance.

Horizontality in the 2010s: Social Movements, Collective Activities, Social Fabric, and Conviviality

Horizontality is a salient social phenomenon of the last decade. It asserts itself against hierarchies in social movements and countless other collective practices around the world. It constitutes a characteristic of an emergent sociality that demands the attention of the social sciences. The 2010s are a moment as important as “the Sixties”, a time when Ivan Illich called for the development of tools of conviviality, and horizontality may be categorized as one of them. Today’s horizontality may be related to that of populations that have been the focus of anthropologists interested in their longstanding propensity to work against the affirmation of the authority of commanding. Public squares, roundabouts, and the courtyards of apartment buildings welcome the early symptoms of democratic experimentation that circulates also among groups, collectivities, and associations with varied purposes. In all these places, equality asserts itself and cuts across differences. The Yellow Vests and an educational cooperative in São Paulo are the empirical foundation of this study.

Prognosis of Pancreatic Cancer in Hamadan, Iran (2008-2018): A case Series Study

Background: The present study aimed to determine the prognosis of pancreatic cancer from 2008 to 2018 in Hamadan, Iran. A case series study was conducted retrospectively at Beheshti Hospital in Hamadan, Iran. Methods: A total of 409 cases that had been diagnosed with pancreatic cancer from 2008 to 2018 were assessed. The variables included age, gender, pathological type, location involved, early symptoms, metastasis, prognosis and treatments, was extracted from the files and recorded in checklist. Data were analyzed by using SPSS/20 software. Results: The mean of age was 66.23±13.06 year. The most frequent of pancreatic cancers was Adenocarcinomas (66.7%). The highest frequency of early symptoms was jaundice (53.1%) and weight loss (12.7%). The highest frequency of pancreatic cancer lesions was more in the head of pancreas (68.7%). Most patients had metastasis at the beginning of diagnosis (82.3%). Most metastases were in liver (31.5%) and peritoneum (25.2%). The prognosis of the pancreatic cancer is significantly related to the lesion location and the consumption of alcohol, cigarettes and substance abuse (p <0.05), but it wasn’t correlated with age, sex and pathological type (p> 0.05). The 1-year and 5-year survival rates were (22.3%) and (9.5%), respectively. The lowest and the highest in 5-year survival rate were (7.8%) and (18.8%) in adenocarcinoma and carcinoma type. Conclusion: More preventive considerations were found to be beneficial among this population.

The Feature Extraction for Coronavirus Disease Classification Techniques

COVID-19 has been an epidemic since the end of 2019. The number of patients with COVID-19 continues to escalate until new variants emerge. The COVID-19 detection procedure begins with detecting early symptoms, furthermore confirmed by the swab and CXR methods. The process of swab and CXR takes a relatively long time since in CXR some patients have the same symptoms as pneumonia. This study carried out the classification of COVID-19 and not COVID-19 with feature extraction techniques and classification methods. The result of this study capable to identify CXR with COVID-19 and an accuracy of 96.5%. In addition, this study even compares the classification results without using feature extraction techniques. The comparison result showed that feature extraction was able to significantly improve accuracy.

Breast Cancer in Middle Euphrates Region of Iraq: Risk Factors, Presenting Symptoms and Time to Medical Help-Seeking

Background: Breast cancer is the most frequently occurring tumor and the first cause of death in females. Low level of understanding early symptoms leads to a late diagnosis and high mortality rates. Aims: To describe presenting symptoms, risk factors, and medical care delays among breast cancer patients in Iraq. Materials & Methods: A retrospective, descriptive study conducted in Al-Hussein center in Karbala province of Iraq between February 2012 and August 2020.Results: There were 101 female patients with breast cancer, median age was 45 years. Most of our patients diagnosed incidentally and only 17.82% of our patients were performing breast self examination. Lack of physical activity was the most common risk factors in more than 74% of patients. Painless breast lump was the most frequent symptom in 85.14% of patients. Majority of our patients 58.42% asked medical help within six months. Limited knowledge about symptoms was the common barriers for early diagnosis in 43.94% of patients. Conclusion: Lack of knowledge about breast cancer had a major concern in our region. Increasing awareness about early symptoms and risk factors is very important for early diagnosis and proper management.