Diagnosis Of COVID-19 Research Articles

Placental Histopathological Changes and the Level of Anti-Spike Antibody After Covid-19 Vaccination During Pregnancy: A Case Series

Background: COVID-19 infection during pregnancy could be associated with placental histopathological changes such as vascular diseases and malperfusion. There are studies showing that mRNA vaccines are not associated with significant placental pathological changes. Our objective was to evaluate the placental histopathology in pregnant women who received Sinopharm, an inactivated virus vaccine, during pregnancy. Case Presentation: The study included placental samples collected from mothers who gave birth of living singletons through elective cesarean sections performed between March 2022 and May 2022 at Imam Khomeini Hospital Complex. The study included women who had no history of positive reverse transcription polymerase chain reaction (RT-PCR) testing for COVID-19 during pregnancy, and had received at least one dose of COVID-19 vaccine during their pregnancy. Humoral levels of anti-SARS-CoV-2 spike IgG were measured in both the mothers and neonates. Results: The study included 20 mother-neonate pairs. The mean maternal age was 34±3.6 years, and all mothers received Sinopharm vaccine as their first and second doses. The last vaccine dose was administered during pregnancy, with 3 mothers receiving it in the first trimester, 9 in the second trimester, and 8 in the third trimester. The histopathological findings in the placental samples included decidual vasculopathy, subchorionic thrombosis, and chronic histiocytic intervillositis. All mothers and neonates, except one pair, were positive for anti-spike antibody. Conclusion: Multiple abnormal histopathological findings were reported in placenta of vaccinated mothers. However, similar to previous studies, these placental findings are considered mild lesions and have been observed in both vaccinated and unvaccinated mothers.

COVID-19 in children with somatic pathology

The coronavirus infection is a pressing issue in modern healthcare, yet the characteristics of the SARS-CoV-2 infection course in children with comorbidities remain insufficiently studied. The aim of this study was to evaluate the clinical form, severity, and duration of SARS-CoV-2 virus shedding in pediatric patients with somatic diseases, depending on the comorbid pathology. Materials and Methods. A comprehensive single-center retrospective study was conducted, analyzing 314 medical records of patients hospitalized in the infectious diseases department of the Russian Children’s Clinical Hospital in Moscow over 11 months in 2022. The inclusion criterion was the presence of a laboratory-confirmed COVID-19 diagnosis. Results. Children with comorbidities were found to be predisposed to a more severe course of SARS-CoV-2 infection compared to the pediatric population in general. Children with hematological diseases were at the highest risk of adverse outcomes from COVID-19. Patients with oncological and hematological diseases and primary immunodeficiencies shed the SARS-CoV-2 virus significantly longer than patients with other somatic pathologies. The duration of SARS-CoV-2 RNA detection in patients with severe COVID-19 was significantly longer, which also correlated with the severity of the underlying somatic disease. Conclusion. Children with comorbidities are at risk for a more severe and prolonged course of SARS-CoV-2 infection.

A timespace of zero‐COVID in Southwest China: Building community, governing time

AbstractIn this article, I take the organization of universal COVID testing as a point of departure for understanding the lived experiences of China's zero‐COVID policy and look at “the Community” (shequ) as a dynamic interface between the state and urban residents during the liminal time of a global pandemic. Drawing on Bryant and Knight's notion of “vernacular timespace” (2019), I analyze the timespace of zero‐COVID as a state‐regulated future orientation interwoven with collective anticipation of crisis, bureaucratic temporal governance, and contestations over time as a form of agency in everyday life. Instead of assuming a unitary form of present‐future relationship that was homogeneous and unchallenged, I argue that the collective anticipation of a public health crisis was constantly shaped, managed, and contested throughout the processes of pandemic community building. This research hopes to enrich reflections on the interplays of time, power, and legitimacy in post‐pandemic urban governance.

QUALIDADE PARA GARANTIR A CONFIABILIDADE DOS RESULTADOS DOS TESTES DA COVID 19

Objective: To analyze and identify the main quality criteria essential to ensure the reliability of COVID-19 test results performed in clinical laboratories. Literature Review: Ensuring the quality of COVID-19 testing is vital for the effectiveness of pandemic control strategies. This involves meticulous care with the selection and implementation of tests, the formation and training of teams, and adherence to standards and good practices. Only with an ongoing commitment to quality and accuracy can we ensure that test results reflect the true situation of COVID-19 infection and aid in public health decision-making.Conclusion: To ensure the reliability of COVID-19 test results, it is essential to take a comprehensive approach that encompasses test accuracy, sample quality, rigorous validation, staff qualification, and transparency.

Perceptions of Pharmacy Faculty Regarding Factors Contributing to Declining First-Time NAPLEX Pass Rates.

Identify perceptions from pharmacy faculty across the Academy concerning factors that may be influencing NAPLEX first-time pass rates to highlight potential focused areas of further research based on common experiences. An anonymous 43-item Qualtrics™ questionnaire was distributed to faculty members from the American Association of Colleges of Pharmacy. Questions were predominantly 5-point Likert scale items (5=very large impact) and encompassed six domains: pharmacy school factors, COVID-19 educational modifications, testing factors, standardized testing, applicant preparedness, and student factors. Demographic data as well as perceptions were reported with means and standard deviations. In total 600 responses were analyzed. Respondents were predominantly female (66%) and white (78%). Most had a Doctor of Pharmacy degree, residency training, and were practicing as a licensed pharmacist within the Southern and Midwestern US. Respondents indicated that the decline in NAPLEX first-time pass rates is a moderate to large problem (mean 3.64, standard deviation [SD] 0.891), and the top potential influencing factors include student quality (mean 3.99, SD 0.876), student's critical thinking (mean 3.90, SD 0.947), study habits (mean 3.74, SD 0.920), and admission standards (mean 3.67, SD 1.082). The top 4 factors indicated by respondents as impacting NAPLEX first-time pass rates were related to the student quality. This result highlights the importance of exploring issues related to pharmacy admissions and the need to implement effective strategies to support an increasing number of potentially less prepared pharmacy students.

A Qualitative Evaluation of the Usability and Accessibility of Home COVID-19 Tests Among People with Disabilities

Home COVID-19 test kits are increasingly available in the United States, and efforts are underway to develop ones that are more accessible to people with disabilities. The primary objective of this research was to assess the usability and accessibility of existing home COVID-19 tests among people with disabilities. The aim is to better understand their needs and provide evidence for improved product design. A survey that included short-response questions about user experience with various home COVID-19 test kits was completed by 219 people with vision and mobility-related disabilities. A thematic analysis identified three overarching themes: Ease of Use, Privacy and Autonomy in Home COVID-19 Testing, and Recommendations for Improvement. The results of this study contribute to an increased understanding of how to design appropriate, accessible home COVID-19 test kits for people with disabilities.

Role of intravenous vitamin C on outcomes in hospitalized patients with moderate or severe COVID-19: a real life data of Turkish patients.

We aimed to examine the efficacy of intravenous vitamin C (IV-VC) in the treatment of hospitalized patients with moderate or severe COVID-19. We conducted a single-center and retrospective study including patients with COVID-19 diagnosis who were hospitalized. Patients were categorized into three groups as those who received low-dose (LDVC group, 2g/day, n = 183) or high-dose IV-VC (HDVC group, 25g/day, n = 41) and who did not receive IV-VC (control group, n = 46). 270 patients aged 19-97years were enrolled. The median length of stay (LOS) was significantly high (9days) in patients treated with high-dose VC when compared to patients treated with low-dose VC and control patients (6 vs 5days, respectively). Need for intensive care unit (ICU) transfer was found to be significantly low in patients treated with low-dose VC (25.7%); contrarily, control patients had significantly higher rates of ICU transfer (67.4%), when compared to patients treated with high-dose VC (39%). Mortality of the LDVC group was significantly lower than that of the HDVC group (11.5 vs 29.3%). However, mortality rates were similar between the control and HDVC groups (21.7 vs 29.3%). According to the multivariate stepwise logistic regression mortality analysis, percent of change (∆%)-BUN was the most significant variable (p < 0.001), the second significant variable was ∆%-AST (p = 0.002), the third significant variable was respiratory distress (p = 0.002), and the fourth significant variable was the IV-VC groups (p = 0.017). The mortality risk of those in the LDVC group was 10.2 times low compared to the control group. Similarly, the risk of mortality in the HDVC group was 6.5 times lower than that of the control group. Especially low and continious doses of IV-VC suggest fewer days of in-hospital LOS and survival benefit in hospitalized patients with moderate and severe COVID-19. Logistic regression analysis revealed that high-dose VC supplementation also had a mortality-reducing effect.

A Comparison of Clinical and Laboratory Features in Neonatal Proven Sepsis and COVID-19

Background: The clinical manifestations of COVID-19 in neonates are generally mild and commonly require only supportive treatment. However, it is important to note that they can sometimes present with symptoms like bacterial sepsis, which can lead to confusion in diagnosis. In this study, our objective was to compare laboratory data and clinical manifestations between 2 groups to identify opportunities for reducing the unnecessary use of antibiotics. Methods: The study was conducted as a cross-sectional study between January 2020 and 2023 on neonates who were admitted to the neonatal intensive care unit or the neonatal ward of Children’s Medical Center in Tehran, Iran. We specifically compared the laboratory data and clinical characteristics of neonates who tested positive for either a blood culture or a reverse transcription polymerase chain reaction for COVID-19. Results: Sixty-seven neonates in COVID-19 group and 68 neonates in the bacterial sepsis group entered. Prominent symptoms in the bacterial sepsis group include vomiting, seizure, apnea, mottling, increased need for ventilation and laboratory findings showing elevated levels of C-reactive protein and thrombocytopenia. In the COVID-19 group, patient exhibit symptoms such as cough, diarrhea, fever and laboratory findings that indicate neutropenia and leukopenia. Symptoms of nervous involvement were rare in this group. Conclusion: It is crucial to carefully assess the symptoms, laboratory results and overall condition of the patient before deciding on antibiotic initiation. By combining rapid COVID-19 testing and clinical variables, it is possible to identify low-risk infants who are unlikely to have bacterial infections.

Exploring Factors Influencing Patient Delay Behavior in Oral Cancer: The Development of a Risk Prediction Model in Western China

Background and Aims: To study the unknown influencing factors of delayed medical treatment behavior in oral cancer patients in western China and to develop a prediction model on the risk of delayed medical treatment in oral cancer patients. Method: We investigated oral cancer patients attending a tertiary Grade A dental hospital in western China from June 2022 to July 2023. The logistic regression and four machine learning models (nearest neighbors, the RBF SVM, random forest, and QDA) were used to identify risk factors and establish a risk prediction model. We used the established model to predict the data before and after the COVID-19 pandemic and test whether the prediction effect can still remain stable and accurate under the interference of COVID-19. Result: Out of the 495 patients included in the study, 122 patients (58.65%) delayed seeking medical treatment before the lifting of the restrictions of the pandemic, while 153 patients (53.13%) did so after the lifting of restrictions. The logistic regression model revealed that living with adult children was a protective factor for patients in delaying seeking medical attention, regardless of the implementation of pandemic control measures. After comparing each model, it was found that the statistical indicators of the random forest algorithm such as the AUC score (0.8380) and specificity (0.8077) ranked first, with the best prediction performance and stable performance. Conclusions: This study systematically elucidates the critical factors influencing patient delay behavior in oral cancer diagnosis and treatment, employing a comprehensive risk prediction model that accurately identifies individuals at an elevated risk of delay. It represents a pioneering large-scale investigation conducted in western China, focusing explicitly on the multifaceted factors affecting the delayed medical treatment behavior of oral cancer patients. The findings underscore the imperative of implementing early intervention strategies tailored to mitigate these delays. Furthermore, this study emphasizes the pivotal role of robust social support systems and positive family dynamics in facilitating timely access to healthcare services for oral cancer patients, thereby potentially improving outcomes and survival rates.

Abstract 4135303: Acute Pericarditis Secondary to Secukinumab Therapy

Background: Pericarditis is the most common pericardial disease worldwide and has a high recurrence rate of 15-30%. It is primarily idiopathic but can arise from infectious and non-infectious causes; drug related cases are rare. Secukinumab, a fully human anti-interleukin-17A monoclonal antibody used for treating psoriasis, has been identified through the FDA Adverse Event Reporting System as potentially inducing pericarditis, though literature is scant. We report a case of acute pericarditis related to secukinumab use. Case presentation: A 28-year-old male with history of psoriasis on secukinumab therapy presented with sharp, central chest pain, and progressive shortness of breath for 3 weeks. He was evaluated for similar chest pain 3 weeks prior; CT chest showed small pericardial effusion and he was managed with analgesics without improvement. This admission, he had tachycardia, and ECG showed sinus rhythm with diffuse ST elevation and PR depression (Figure 1A). Troponin I levels were normal and inflammatory markers were elevated. Transthoracic echocardiogram (TTE) revealed a large pericardial effusion without tamponade physiology (Figure 1B). CT chest confirmed large pericardial effusion, increased in size compared to CT done 3 weeks prior (Figure 2). He was diagnosed with pericarditis and started on ibuprofen and colchicine which improved his symptoms. Search for viral etiology including testing for COVID, influenza A and B, RSV, hepatitis and HIV were negative. Immunological workup for ANA and rheumatoid factor was negative. Thus, secukinumab was thought to be the likely culprit. Follow-up TTE in 3 months showed resolution of pericardial effusion. Conclusion: This case underscores the importance of considering medication-induced pericarditis in patients presenting with typical symptoms, especially when on treatment with drugs like secukinumab. Given the growing evidence from pharmacovigilance databases and the severe potential outcomes of untreated pericarditis, clinicians should maintain vigilance for such adverse effects. Further research is warranted to clarify the mechanisms by which secukinumab may contribute to pericardial inflammation in order to optimize management strategies in affected patients.

Factors Affecting Procedural Pain and Discomfort Experienced by Individuals During Nasopharyngeal Swabbing: A Cross-Sectional Study.

This descriptive and cross-sectional study investigated the individual factors that affect procedural pain and discomfort in individuals who had nasopharyngeal swabs by nurses. A total of 193 participants in two COVID-19 test centers located in a city in Southeastern Türkiye between April and May 2022 were included in this study. Personal information form was used to collect data. The visual analog scale was used to assess the pain and discomfort. Risk factors related to pain and discomfort were investigated through a logistic regression model. During the nasopharyngeal swabbing, it was determined that pain was stronger in women and those who considered nasopharyngeal swabbing as a painful procedure (p < .05). Also, discomfort was stronger in women and those who considered nasopharyngeal swabbing as an uncomfortable procedure (p < .05). It was determined that the participants' discomfort scores were higher than their pain scores. Women and individuals with negative opinions about the procedure experienced more pain and discomfort during the nasopharyngeal swabbing. Most of the participants complained more about discomfort than pain. It is recommended to apply alternate test methods and conduct nurse-led information studies to reduce the anticipation of procedural pain/discomfort.

An artificial intelligence-enabled consumables tracking system for medical laboratories

Abstract The medical laboratory plays a crucial role within a hospital setting and is responsible for the examination and analysis of patient specimens to accurately diagnose various ailments. The burden on medical laboratory personnel has significantly increased, particularly in the context of the ongoing global COVID-19 pandemic. Worldwide, the implementation of comprehensive and extended COVID-19 screening programs has placed a significant strain on healthcare professionals. This burden has led to exhaustion among medical employees, limiting their ability to effectively track laboratory resources, such as medical equipment and consumables. Therefore, this study proposed an artificial intelligence (AI)-based solution that contributes to a more efficient and less labor-intensive workflow for medical workers in laboratory settings. With the ultimate goal to reduce the burden on healthcare providers by streamlining the process of monitoring and managing these resources, the objective of this study is to design and develop an AI-based system for consumables tracking in medical laboratories. In this work, the effectiveness of two object detection models, namely, YOLOv5x6 and YOLOv8l, for the administration of consumables in medical laboratories was evaluated and analyzed. A total of 570 photographs were used to create the dataset, capturing the objects in a variety of settings. The findings indicate that both detection models demonstrate a notable capability to achieve a high mean average precision. This underscores the effectiveness of computer vision in the context of consumable goods detection scenarios and provides a reference for the application of real-time detection models in tracking systems within medical laboratories.

Health Disparities in Hospitalized Pediatric Patients with Autism Spectrum Disorder and COVID-19

Background/Objectives: Pediatric patients with autism spectrum disorder (ASD) face unique challenges, especially amongst individuals from historically minoritized racial groups. ASD has also been associated with an increased mortality from COVID-19. This study aims to explore the differences in sociodemographic factors and health outcomes (as measured by length of stay) amongst hospitalized pediatric patients with COVID-19 infections and a diagnosis of ASD compared to individuals with a COVID-19 infection alone; Methods: We performed a retrospective cohort study examining pediatric patients (ages birth to 21) who were hospitalized with a diagnosis of ASD and COVID-19 compared to patients with a diagnosis of COVID-19 alone between January 2019 and June 2023 using Epic Systems Corporation’s Cosmos, a de-identified dataset aggregated from electronic health record data. We examined differences in demographic factors and length of stay (LOS) between groups by utilizing chi-square and Wilcoxon rank sum tests. Multiple logistic regression models were utilized to assess the association between length of stay and diagnosis; Results: A total of 21,708 distinct pediatric patients with a diagnosis of ASD and COVID-19 or COVID-19 alone were included in the analytical dataset. Patients with ASD and COVID-19, compared to patients with COVID-19 alone, had a higher proportion of individuals identifying as male and White. Patients with COVID-19 alone, compared to individuals with ASD and COVID-19, had higher proportions of individuals identifying as Black or African American. Higher proportions of individuals with ASD and COVID-19 had public insurance, compared to individuals with COVID-19 alone. Having a diagnosis of ASD and COVID, after controlling for covariates, was associated with higher odds of having a length of stay greater than the three days (cutoff value determined by the median LOS of three days) compared to having a diagnosis of COVID alone (aOR 1.19, 95% CI 1.04–1.35); Conclusions: Our study highlights the health disparities experienced during hospitalizations by pediatric patients with ASD and COVID-19. Further studies should address barriers and support health outcomes for pediatric patients with ASD.

Deep learning-based Covid-19 diagnosis: a thorough assessment with a focus on generalization capabilities

The Covid-19 pandemic has significantly spurred the development of deep learning (DL) models for the pathology automatic diagnosis based on CT scan images. However, the assumption about the generalization of the proposed models remains to be assessed and shown for concrete clinical use. In this work, we have investigated the real value of widely used public datasets for the elaboration of DL models that are dedicated to automatic diagnosis of Covid-19 using CT scans. We have collected various international public datasets from 13 countries. Different Convolutional Neural Networks (CNNs) have been trained and their performances carefully assessed. Two evaluations have been conducted: (1) an internal evaluation following a cross-validation procedure, and (2) an external evaluation on real patients coming from new and different sources. The objective is to assess the generalization capabilities considering real-world conditions: different acquisition conditions, devices and configurations. Three families from the most effective CNN models have been selected (ResNet, DenseNet and EfficientNet). These have been fine-tuned, evaluated and used within a training methodology based on transfer learning. The most effective models have been further customized in order to create new models that are dedicated to the task at hand. These models have significantly improved the diagnosis performance.

Risk Factors of the Severity of COVID-19 Infection in Infants

Background: The global COVID-19 crisis has profoundly affected populations worldwide. While it is widely accepted that older individuals are at greater risk of severe illness, data indicate that in newborns and infants, the disease is generally not fatal. Objectives: This cross-sectional study aimed to examine the roles of laboratory tests and clinical symptoms in determining the severity of COVID-19 infection in infants younger than three months. Methods: This study included all infants less than three months old with positive PCR tests for COVID-19 admitted to the Children's Medical Center between October 2020 and March 2022. We analyzed the association between disease severity and clinical symptoms, as well as laboratory findings. Results: Sixty-four neonates and infants under three months of age with COVID-19 participated in the study. Our findings suggest that lower birth weight and gestational age are associated with increased disease severity. Infants with underlying medical conditions were found to have a higher risk of reaching stage IIb or greater severity. Among laboratory and clinical findings, only white blood cell (WBC) count and cough symptoms showed a significant correlation with disease severity. Conclusions: Clinical evaluations, along with factors such as birth weight, gestational age, and underlying conditions, appear more effective in guiding decision-making for COVID-19 severity in infants. Further studies are necessary to explore the influence of these factors on COVID-19 severity in this age group.

A combination between transfer learning models and UNet++ for COVID-19 diagnosis

A combination between transfer learning models and UNet++ for COVID-19 diagnosis

Clinical profile, risk factors, disease severity, and outcome for COVID-19 disease in patients with tuberculosis on treatment under the National Tuberculosis Elimination Program: a cohort of 1400 patients.

COVID-19 affected millions of people worldwide, and tuberculosis (TB) continues to affect millions of people each year. The combined pandemic of COVID-19 and TB had a catastrophic effect on healthcare policies and healthcare setups around the globe. The clinical profile and factors affecting the outcome of COVID-19 disease in TB patients on treatment in field conditions have not been studied in detail. The present study attempted to study the occurrence of COVID-19 among patients on TB treatment in terms of severity of COVID-19 disease and outcome of both COVID-19 and TB in patients at National Tuberculosis Elimination Program treatment centers over a period of one year during peak COVID-19 times. Out of 1400 TB patients enrolled, 65 (5%) suffered from COVID-19 disease. Of the 65 TB patients with COVID-19 disease, 37 (57%) were male and under 45 years old, 33 (51%) had a TB diagnosis after first receiving a COVID-19 diagnosis, 29 (45%) had a TB diagnosis first, and received anti-TB treatment before receiving a COVID-19 diagnosis, and only 3 patients (5%) had a COVID-19 and TB diagnosis concurrently. The majority of 59 (91%) patients had mild COVID-19 disease. The outcome of TB treatment was available in 25 patients out of these 65 COVID-19-positive patients, with 21 (84%) patients having a favorable outcome. Out of the 65 COVID-19-positive patients, 4/25 (16%) had unfavorable outcomes, with one patient (4%) failing TB treatment and two patients (8%) dying. This is the first study from India that studied the occurrence and course of COVID-19 among a large number of TB patients taking anti-TB treatment under programmatic conditions. Due to the similarity in symptoms of TB and certain viral respiratory illnesses, a protocol should be established for health care to check patients for both illnesses.

Association of COVID-19 Vaccine Intake with Diagnosis, Hospitalization, and Oxygenation/Ventilation: A Longitudinal Analysis, 2021–2022, Japan

Background/Objectives: Japan’s COVID-19 vaccination campaign achieved high coverage by 2022, yet limited national-level data has hindered evaluations of vaccine effectiveness. This study analyzed the impact of vaccines on infection outcomes while considering socioeconomic and behavioral factors in the Japanese population. Methods: A total of 19,482 individuals aged 16–81 years, who participated in both the 2021 (baseline) and 2022 (follow-up) waves of an Internet-based survey, were analyzed. Vaccine intake during the follow-up period (0/1/2+ doses) served as the exposure, while outcomes included COVID-19 diagnosis, hospitalization, and receipt of oxygenation/ventilation. Adjusted prevalence ratios (APRs) were calculated using Poisson regression models, controlling for baseline characteristics such as vaccination status, infection history, underlying medical conditions, socioeconomic factors, and preventive behaviors. Results: Overall, 81.6% of respondents received at least 1 dose of COVID-19 vaccine during the follow-up period. Among those without COVID-19 history at baseline (N = 19,182), 10.9% were diagnosed with COVID-19 in the past year, and 6.6% in the past 2 months. Respondents who received 1 or 2+ doses had lower diagnosis rates (APR = 0.76 and 0.43, respectively). For the past 2 months, only those with 2+ doses showed a significant reduction (APR = 0.51). Among 1999 diagnosed cases, those with 1 or 2+ doses showed lower hospitalization and oxygenation/ventilation likelihoods, though these differences were not statistically significant. Conclusions: The results supported the protective effect of COVID-19 vaccines against infection. Continued research is essential to further clarify the complex influence of vaccination, individual characteristics, and preventive behaviors on COVID-19 morbidity at the population level.

Designing and Validating a Survey for National-Level Data During the COVID-19 Pandemic in Sri Lanka: Cross-Sectional Mobile Phone Surveys.

The COVID-19 pandemic has generated a demand for timely data, resulting in a surge of mobile phone surveys for tracking the impacts of and responses to the pandemic. Mobile phone surveys have become a preferred mode of data collection across low- and middle-income countries. This study piloted 2 population-based, cross-sectional mobile phone surveys among Sri Lankan residents in 2020 and 2021 during the COVID-19 pandemic. The surveys aimed to gather data on knowledge, attitudes, and practices, vaccine acceptability, availability, and barriers to COVID-19 testing, and use of a medicine distribution service. The study used Surveda, an open-source survey tool developed by the NCD (noncommunicable disease) Mobile Phone Survey Data 4 Health Initiative, for data collection and management. The surveys were conducted through interactive voice response using automated, prerecorded messages in Sinhala, Tamil, and English. The sample design involved random sampling of mobile phone numbers, stratified by sex, proportional to the general population. Eligibility criteria varied between surveys, targeting adults aged 35 years and older with any noncommunicable disease for the first survey and all adults for the second survey. The data were adjusted to population estimates, and statistical analysis was conducted using SAS (SAS Institute) and R software (R Core Team). Descriptive statistics, Rao-Scott chi-square tests, and z tests were used to analyze the data. Response rates, cooperation rates, and productivity of the sampling approach were calculated. In the first survey, n=5001, the overall response rate was 7.5%, with a completion rate of 85.6%. In the second survey, n=1250, the overall response rate was 10.9%, with a completion rate of 61.9%. Approximately 3 out of 4 adults reported that they avoided public places (888/1175, 75.6%), more than two-thirds avoided public transportation (808/1173, 68.9%), and 9 out of 10 practiced physical distancing (1046/1167, 89.7%). Approximately 1 out of 10 Sri Lankan persons reported being tested for COVID-19, and the majority of those received a polymerase chain reaction test (112/161, 70%). Significantly more males than females reported being tested for COVID-19 (98/554, 17.8% vs 61/578, 10.6%, respectively; P<.001). Finally, the majority of adult Sri Lankan people reported that they definitely or probably would get the COVID-19 vaccination (781/1190, 65.7%). The surveys revealed that, overall, the adult Sri Lankan population adhered to COVID-19 mitigation strategies. These findings underscore the use of mobile phone surveys in swiftly and easily providing essential data to inform a country's response during the COVID-19 pandemic, obviating the need for face-to-face data collection.

Unveiling Symptomatic Pathways of COVID-19: An In-depth Analysis Employing SLIM Association Rule Mining

In order to achieve a thorough comprehension of COVID-19, it is imperative to elucidate the interconnections among its symptoms. The proposed methodology aims to discern patterns that can effectively diagnose the emergence of symptoms, thereby improving diagnostic accuracy and potentially yielding significant breakthroughs. The current study facilitates identifying patterns that signify symptoms' occurrence and convergence. The SLIM algorithm is introduced as a novel method for systematically analyzing large symptom datasets, and its application is presented in this study. The reason for this goes beyond the capabilities of conventional methods, enabling greater diagnostic precision and illuminating new investigational avenues. The present study predicts and identifies COVID-19-related symptoms with greater accuracy, which enhances our understanding of the disease's symptomatology and encourages further study in the area. The results of this study have improved the experience and management of COVID-19's diagnosis, treatment, and pathophysiology, thereby contributing to a better grasp of the virus and bolstering global efforts to manage and mitigate it.