Progression Of Pandemic Research Articles

Unveiling the Underlying Severity of Multiple Pandemic Indicators

Background: Multiple interconnected key metrics are frequently available to track the pandemic progression. One of the difficulties health planners face is determining which provides the best description of the status of the health challenge.Methods: The aim of this study is to capture the information provided by multiple pandemic magnitudes in a single metric. Drawing on official Spanish data, we apply techniques of dimension reduction of time series to construct a synthetic pandemic indicator that, based on the multivariate information, captures the evolution of disease severity over time. Three metrics of the evolution of the COVID-19 pandemic are used to construct the composite severity indicator: the daily hospitalizations, ICU admissions and deaths attributable to the coronavirus. The time-varying relationship between the severity indicator and the number of positive cases is investigated. Results: A single indicator adequately explained the variability of the three time series during the analyzed period (May 2020–March 2022). The severity indicator was stable until mid-March 2021, then fell sharply until October 2021, before stabilizing again. The period of decline coincided with mass vaccination. By age group, the association between underlying severity and positive cases in those aged 80+ was almost 20 times higher than in those aged 20-49.Conclusion: Our methodology can be applied to other infectious diseases to monitor their severity evolution with a single metric. The synthetic indicator may be useful in assessing the impact of public health interventions on reducing disease severity.

Adverse effects of COVID-19 vaccine in the paediatric population: a focus on the cardiovascular system.

The COVID-19 pandemic had an unprecedented impact on healthcare systems and exists globally. To control pandemic progression, COVID-19 vaccines were developed and licensed for use in the adult population in early 2021 and became available in paediatric cohorts several months later. Since then, several studies have reported adverse events and severe adverse events in the adult and paediatric cohorts. The question remains whether there exists a significant risk to paediatric COVID-19 vaccination. This study reviews the classification and presentation of severe adverse events and discusses relevant reports in the literature. An emphasis is put on cardiovascular severe adverse events and adverse events. This paper also provides current and future perspectives relative to the pandemic, its control, and the future of vaccine immunology.

Indirect effectiveness of COVID-19 vaccines in the pre-omicron and omicron periods: A nation-wide test-negative case-control study in Brazil

ObjectivesMass COVID-19 immunization campaigns altered the pandemic's progress by protecting the vaccine recipient and reducing transmission. However, evidence for indirect vaccine effectiveness (IVE) is limited due to the difficulties of ascertaining this type of protection. MethodsUsing linked national Brazilian databases, we adapted the test-negative design to evaluate the IVE against symptomatic infection. We analyzed data from January 1 to December 1, 2021 (pre-omicron) and January 1 to April 30, 2022 (omicron BA.1 and BA.2). We compared the probability of testing positive across various levels of second ancestral-strain monovalent COVID-19 vaccine dose coverage, including only unvaccinated individuals in the main analysis and both vaccinated and unvaccinated individuals in additional analyses. Sensitivity analysis focused on children younger than 12 years who did not have access to COVID-19 vaccines during the pre-omicron period. ResultsWe included 11,039,315 unvaccinated individuals tested during the pre-omicron study period. IVE was minimal until 30% vaccination coverage (<10%), then it followed a dose-dependent pattern, peaking at 37.7 (95% confidence interval 32-42.8) at 70% coverage. For children younger than 12 years, IVE peaked at 59.8% (95% confidence interval 52.7-65.9) at 70% coverage. During the omicron period, IVE remained constant at about 5% across all comparisons. ConclusionsOur findings confirm that high vaccination coverage using vaccines that prevent infection indirectly protects the community. However, IVE was substantially higher during the pre-omicron period.

Evolution and impact of COVID-19: A comprehensive overview

This article focuses on COVID-19 during different times, from 2019 to 2024. Which include the background of COVID-19, structures, prevention spread ways and vaccines. Introducing these things about COVID-19 can help people know more about this various, although COVID-19 does not affect humans as much as it used to, and can help people know what got improved during the COVID-19 time, such as the vaccine. By reading this article, people can know more about the details of COVID-19 and can also know more ways to protect themselves. Also, readers can know different kinds of the variant with time goes then appears in the world, and development in the vaccine. This paper explores COVID-19's impact on humanity, the evolution of the virus, and advances in vaccines and treatments, providing insights into the pandemic's progression and response.

Deep Learning Based Multi-Parameter Assistive System for COVID-19 Diagnosis

Epidemics like the COVID-19 epidemic are major global problems, some of which spread rapidly, causing high mortality rates. The rapid spread of such diseases leaves behind the production and global use of medical testing tools, and during this period, the undetected disease spreads quickly and becomes hard to control. Therefore, non-medical digital technologies with faster disease prediction are needed. The studies on deep learning, a subfield of artificial intelligence, reveal that it is possible to predict disease more quickly. It will be possible to stop the pandemic progress with minimal damage if the best predictive approach is used. Lives are saved when the disease is detected early. A dataset containing low-dose CT scan images, gender, age, weight, COVID-19 PCR test result, and symptoms including cough, fever, shortness of breath, chest pain, and fatigue were used in this study. The primary goal is developing an assistive system for diagnosing COVID-19 disease based on deep learning using this dataset. The deep learning technique used in this study has a multi-branch architecture consisting of both classical artificial neural networks and convolutional neural networks. As a result of this study, it was concluded that the developed technique can be used not only for COVID-19 but also for different diseases and is open to development with data from more patients.

How viruses spread across space and time: forecasting pandemic progression by modelling geographico-temporal interactions

The COVID-19 pandemic has revealed severe flaws in the global healthcare systems ability to respond to unexpected health catastrophes. Much of the confusion and mishandling of the situation could be attributed to the failure in accurately predicting the spread of the virus across geographical locations. A global resource shortage in essential medical supplies and equipment, such as personal protective equipment (PPE) and ventilators, led to a compromised global supply chain. As a result, resources could not be allocated as needed to curb the spread of the pathogen in the most efficacious way. Although forecast models and machine learning algorithms have served as invaluable tools in devising effective response strategies, a large majority of these models were limited by their ability to describe the intricate interactions that underlie the spatio-temporal dynamics of viral proliferation. To address this issue, we employed a vector autoregression model to help capture the evolution of the disease across both the spatial and the temporal axes. Unlike traditional autoregression models, the present model is able to account for statistical regularities that exist both within a given region, and between geographical locations. Our results demonstrate that this approach accurately described the relationships across domestic and international localities throughout the evolution of the disease.

Dynamic clade transitions and the influence of vaccination on the spatiotemporal circulation of SARS-CoV-2 variants

Since 2021, the emergence of variants of concern (VOC) has led Brazil to experience record numbers of in COVID-19 cases and deaths. The expanded spread of the SARS-CoV-2 combined with a low vaccination rate has contributed to the emergence of new mutations that may enhance viral fitness, leading to the persistence of the disease. Due to limitations in the real-time genomic monitoring of new variants in some Brazilian states, we aimed to investigate whether genomic surveillance, coupled with epidemiological data and SARS-CoV-2 variants spatiotemporal spread in a smaller region, can reflect the pandemic progression at a national level. Our findings revealed three SARS-CoV-2 variant replacements from 2021 to early 2022, corresponding to the introduction and increase in the frequency of Gamma, Delta, and Omicron variants, as indicated by peaks of the Effective Reproductive Number (Reff). These distinct clade replacements triggered two waves of COVID-19 cases, influenced by the increasing vaccine uptake over time. Our results indicated that the effectiveness of vaccination in preventing new cases during the Delta and Omicron circulations was six and eleven times higher, respectively, than during the period when Gamma was predominant, and it was highly efficient in reducing the number of deaths. Furthermore, we demonstrated that genomic monitoring at a local level can reflect the national trends in the spread and evolution of SARS-CoV-2.

Progress Toward Achieving and Sustaining Maternal and Neonatal Tetanus Elimination - Worldwide, 2000-2022.

Tetanus remains a considerable cause of mortality among undervaccinated mothers and their infants following unhygienic deliveries, especially in low-income countries. Strategies of the maternal and neonatal tetanus elimination (MNTE) initiative, which targets 59 priority countries, include strengthening antenatal immunization of pregnant women with tetanus toxoid-containing vaccines (TTCVs); conducting TTCV supplementary immunization activities among women of reproductive age in high-risk districts; optimizing access to skilled birth attendants to ensure clean deliveries and umbilical cord care practices; and identifying and investigating suspected neonatal tetanus cases. This report updates a previous report and describes progress toward MNTE during 2000-2022. By December 2022, 47 (80%) of 59 priority countries were validated to have achieved MNTE. In 2022, among the 50 countries that reported coverage with ≥2 doses of TTCV among pregnant women, 16 (32%) reported coverage of ≥80%. In 2022, among 47 validated countries, 26 (55%) reported that ≥70% of births were assisted by skilled birth attendants. Reported neonatal tetanus cases worldwide decreased 89%, from 17,935 in 2000 to 1,995 in 2021; estimated neonatal tetanus deaths decreased 84%, from 46,898 to 7,719. However, the global disruption of routine immunization caused by the COVID-19 pandemic impeded MNTE progress. Since 2020, reported neonatal tetanus cases have increased in 18 (31%) priority countries. Integration of MNTE strategies into priority countries' national postpandemic immunization recovery activities is needed to achieve and sustain global elimination.

Parenting during the Covid-19 Pandemic: Family Changes, Challenges and Resilience

The COVID-19 pandemic led to unprecedented measures and restrictions that disrupted families' lives, forcing them to reorganize their routines. This study investigated the parenting experiences in terms of changes and challenges, including positive effects and family resilience indicators. Unlike most studies which have limited their focus to the first period of lockdown or are based on questionnaires, this study covers the period from the first to the fifth wave of the pandemic in France (March 2020-November 2021) and relies on a large qualitative survey. 282 French parents living at home with at least one child under 18 years of age participated in the study. On an online platform, parents were asked to answer two open-ended questions. A thorough coding of the verbatim was carried out according to an empirical-inductive approach by two independent raters. The qualitative results were completed by quantitative analyses. Four major themes emerged from the responses to the first question (perceived improvement, perceived deterioration, no perceived change, and mixed feelings), and five challenges were identified for the second question (organizational challenges, family challenges, psychological challenges, health challenges, and no challenge). Parents reported more improvements in their parenting experience than deteriorations. Organizational challenges were mentioned more than twice as often as health challenges. Nearly a quarter of participants declared no perceived change in their lives as parents. It appears that French parents were able to tap into their resources without reducing their parenting abilities, and for many of them, this also resulted in improved parenting. After the severe lockdowns, the pandemic's progression revealed ongoing challenges and opportunities to strengthen family resilience. Despite initial relief, the pandemic left lasting impacts on family dynamics, with studies noting improvements in organization and reduced stress, but also ongoing difficulties in readjusting routines and concerns about children's well-being.

Leveraging Global Fund's investments to expand innovative public-private provider engagement in TB.

TB remains a significant global health threat, claiming 1.3 million lives annually. The COVID-19 pandemic disrupted progress in the global TB response. Most patients with TB initially seek care from private providers, whereas only a small proportion are engaged by national programmes. The Global Fund is the major international source of funding for TB responses and supports the scale-up of innovative private-public mix (PPM) models in TB. We collected programmatic and financial data on TB from 11 priority countries implementing PPM activities. Country examples and trends in the budget of Global Fund grants were analysed. These countries account for 60% of the global TB burden and Global Fund TB portfolio. PPM contributed 29% of national TB notifications in 2022 (range: 8% to 49%). During 2021-2023, US$1.4 billion was allocated for TB and US$155 million (11%) for PPM, while PPM contributed to 35% of national TB notification targets. PPM budgets increased over time from US$43 million (2002 to 2014) to US$129 million (2024 to 2026). The Global Fund's investments facilitated the expansion of innovative PPM models, improved access, and enhanced TB responses. Our indicative analysis underscores the need for evidence-based planning, collaboration, and increased domestic investment to accelerate the end of TB.

Phylogenetic inference of inter-population transmission rates for infectious diseases.

Estimating transmission rates is a challenging yet essential aspect of comprehending and controlling the spread of infectious diseases. Various methods exist for estimating transmission rates, each with distinct assumptions, data needs, and constraints. This study introduces a novel phylogenetic approach called transRate, which integrates genetic information with traditional epidemiological approaches to estimate inter-population transmission rates. The phylogenetic method is statistically consistent as the sample size (i.e. the number of pathogen genomes) approaches infinity under the multi-population susceptible-infected-recovered model. Simulation analyses indicate that transRate can accurately estimate the transmission rate with a sample size of 200 ~ 400 pathogen genomes. Using transRate, we analyzed 40,028 high-quality sequences of SARS-CoV-2 in human hosts during the early pandemic. Our analysis uncovered significant transmission between populations even before widespread travel restrictions were implemented. The development of transRate provides valuable insights for scientists and public health officials to enhance their understanding of the pandemic's progression and aiding in preparedness for future viral outbreaks. As public databases for genomic sequences continue to expand, transRate is increasingly vital for tracking and mitigating the spread of infectious diseases.

Declining Chinese attitudes toward the United States amid COVID-19

In this paper, we present findings from four separate studies using different data sources and methods to examine Chinese attitudes toward the United States amid the COVID-19 pandemic. The empirical results consistently indicate a marked and significant decline in Chinese attitudes toward the US between late 2019 and the end of 2022. Using a quasi-experimental design and granular survey data that exploit daily variations in public opinion, we offer additional evidence that the decline in Chinese attitudes toward the United States followed a distinct pattern not true for Chinese attitudes toward other countries. Specifically, the rise in Chinese unfavorability toward the United States closely corresponded to the heightened Chinese attention to the pandemic's progression in the United States. These results collectively suggest a causal effect of COVID-19, shedding light on how public health crises, international relations, and media jointly shape the increasing enmity between the two great powers.

A Hybrid Digital Parenting Program Delivered Within the Malaysian Preschool System: Protocol for a Feasibility Study of a Small-Scale Factorial Cluster Randomized Trial.

The United Nations' Sustainable Development Goal 4, and particularly target 4.2, which seeks to ensure that, by 2030, all children have access to quality early childhood development, care, and preprimary education so that they are ready for primary education, is far from being achieved. The COVID-19 pandemic compromised progress by disrupting education, reducing access to well-being resources, and increasing family violence. Evidence from low- and middle-income countries suggests that in-person parenting interventions are effective at improving child learning and preventing family violence. However, scaling up these programs is challenging because of resource constraints. Integrating digital and human-delivered intervention components is a potential solution to these challenges. There is a need to understand the feasibility and effectiveness of such interventions in low-resource settings. This study aims to determine the feasibility and effectiveness of a digital parenting program (called Naungan Kasih in Bahasa Melayu [Protection through Love]) delivered in Malaysia, with varying combinations of 2 components included to encourage engagement. The study is framed around the following objectives: (1) to determine the recruitment, retention, and engagement rates in each intervention condition; (2) to document implementation fidelity; (3) to explore program acceptability among key stakeholders; (4) to estimate intervention costs; and (5) to provide indications of the effectiveness of the 2 components. This 10-week factorial cluster randomized trial compares ParentText, a chatbot that delivers parenting and family violence prevention content to caregivers of preschool-aged children in combination with 2 engagement components: (1) a WhatsApp support group and (2) either 1 or 2 in-person sessions. The trial aims to recruit 160 primary and 160 secondary caregivers of children aged 4-6 years from 8 schools split equally across 2 locations: Kuala Lumpur and Negeri Sembilan. The primary outcomes concern the feasibility and acceptability of the intervention and its components, including recruitment, retention, and engagement. The effectiveness outcomes include caregiver parenting practices, mental health and relationship quality, and child development. The evaluation involves mixed methods: quantitative caregiver surveys, digitally tracked engagement data of caregivers' use of the digital intervention components, direct assessments of children, and focus group discussions with caregivers and key stakeholders. Overall, 208 parents were recruited at baseline December 2023: 151 (72.6%) primary caregivers and 57 (27.4%) secondary caregivers. In January 2024, of these 208 parents, 168 (80.8%) enrolled in the program, which was completed in February. Postintervention data collection was completed in March 2024. Findings will be reported in the second half of 2024. This is the first factorial cluster randomized trial to assess the feasibility of a hybrid human-digital playful parenting program in Southeast Asia. The results will inform a large-scale optimization trial to establish the most effective, cost-effective, and scalable version of the intervention. OSF Registries; https://osf.io/f32ky. DERR1-10.2196/55491.

Water, Sanitation, and Hygiene Infrastructure and Resources in Schools in Belize during the COVID-19 Pandemic, 2021-2023.

Access to water, sanitation, and hygiene (WASH) resources in schools is critical for disease prevention and control, especially during public health emergencies. In Belize, systematic, national data on WASH in schools are needed to inform public health decisions and interventions. From December 2021 to January 2022, a national survey was sent electronically to government and government-aided primary and secondary schools in Belize (N = 308) to gather information on WASH services. From the survey, 12 pilot schools were selected based on the highest self-reported need for WASH resources to participate in additional evaluation and intervention, which included environmental nudges, supplemental supply provision, and hand hygiene education. To understand how the progression of the COVID-19 pandemic may have influenced hand hygiene, facility assessments to evaluate access to hand hygiene resources were conducted in person when most schools reopened for face-to-face learning during the pandemic (March 2022) and 15 months later (June 2023). Among the schools participating in the national survey (N = 221), 55% reported times when water was not available at the schools. Almost 9 in 10 schools (89%) had a functional handwashing station, and 47% reported always having soap for handwashing. Between baseline and follow-up at the 12 pilot schools, we observed decreases in the proportion of functional handwashing access points (-11%), functional handwashing access points accessible for individuals with disabilities (-17%) and small children (-29%), and functional alcohol-based hand rub dispensers (-13%). Despite the ongoing COVID-19 pandemic, we observed gaps in WASH resources in schools in Belize during the onsite assessments at the pilot schools. Schools should be encouraged and provided with WASH resources to maintain vigilance for disease control measures.

Early and contemporary drivers of the HIV-1 group M pandemic.

HIV emerged silently taking time to spread and become visible only through geographically isolated clusters of life-threatening immunodeficiency, known as AIDS since the early 80s. The clusters of infection expanded, overlapping to evolve into a pandemic that is ongoing and almost as silent. Phylogenetic analysis places the emergence of HIV-1 group M, the subtype responsible for the pandemic, in the human population more than 100 years ago. Once established, the rate and direction of spread of HIV-1 from local, to national, to contemporary pandemic proportions have varied over time and place. The literature presents many theories on the emergence and drivers of the spread of the virus over the past century. Here, historical evidence and phylogenetic models are reviewed to seek clarity on the emergence, geographic spread and key world events that mark the progression of the HIV-1 pandemic. This narrative review places particular focus on: war (both its direct and indirect affects), trade and economic expansion, changes in sexual behaviors, and public health policy. Investigating the impact of major world events and policy on the emergence and spread of HIV-1 may aid better understanding of what influences the viruses transmission dynamic. By identifying multilateral targets that influence transmission, up-scaled efforts to effectively control, if not remove, HIV-1 from the human population become a possibility. Suggestions for revisions in HIV-1 global public health policy are discussed. Refocused efforts to tackle HIV-1 transmission and replace the need to manage the pathology of this terrible disease are both ethically and economically just.

SARS-CoV-2 vaccination may mitigate dysregulation of IL-1/IL-18 and gastrointestinal symptoms of the post-COVID-19 condition

The rapid development of safe and effective vaccines helped to prevent severe disease courses after SARS-CoV-2 infection and to mitigate the progression of the COVID-19 pandemic. While there is evidence that vaccination may reduce the risk of developing post-COVID-19 conditions (PCC), this effect may depend on the viral variant. Therapeutic effects of post-infection vaccination have been discussed but the data for individuals with PCC remains inconclusive. In addition, extremely rare side effects after SARS-CoV-2 vaccination may resemble the heterogeneous PCC phenotype. Here, we analyze the plasma levels of 25 cytokines and SARS-CoV-2 directed antibodies in 540 individuals with or without PCC relative to one or two mRNA-based COVID-19 vaccinations as well as in 20 uninfected individuals one month after their initial mRNA-based COVID-19 vaccination. While none of the SARS-CoV-2 naïve individuals reported any persisting sequelae or exhibited PCC-like dysregulation of plasma cytokines, we detected lower levels of IL-1β and IL-18 in patients with ongoing PCC who received one or two vaccinations at a median of six months after infection as compared to unvaccinated PCC patients. This reduction correlated with less frequent reporting of persisting gastrointestinal symptoms. These data suggest that post-infection vaccination in patients with PCC might be beneficial in a subgroup of individuals displaying gastrointestinal symptoms.

A comparison between different patient groups for diabetes management during phases of the COVID-19 pandemic: a retrospective cohort study in Ontario, Canada

BackgroundWith the onset of the COVID-19 pandemic and the large uptake in virtual care in primary care in Canada, the care of patients with type 2 diabetes has been greatly affected. This includes decreased in-person visits, laboratory testing and in-person assessments such as blood pressure (BP). No studies have investigated if these changes persisted with pandemic progression, and it is unclear if shifts impacted patient groups uniformly. The purpose of this paper was to examine changes in diabetes care pre, early, and later pandemic across different patient groups.MethodsA repeated cross-sectional design with an open cohort was used to investigate diabetes care in adults with type 2 diabetes for a 6-month interval from March 14 to September 13 over three consecutive years: 2019 (pre-pandemic period), 2020 (early pandemic period), and 2021 (later pandemic period). Data for this study were abstracted from the University of Toronto Practice-Based Research Network (UTOPIAN) Data Safe Haven, a primary care electronic medical records database in Ontario, Canada. Changes in diabetes care, which included primary care total visits, in-person visits, hemoglobin A1c (HbA1c) testing, and BP measurements were evaluated across the phases of the pandemic. Difference in diabetes care across patient groups, including age, sex, income quintile, prior HbA1c levels, and prior BP levels, were assessed.ResultsA total of 39,401 adults with type 2 diabetes were included in the study. Compared to the 6-month pre-pandemic period, having any in-person visits decreased significantly early pandemic (OR = 0.079 (0.076–0.082)), with a partial recovery later pandemic (OR = 0.162 (95% CI: 0.157–0.169). Compared to the pre-pandemic period, there was a significant decrease early pandemic for total visits (OR = 0.486 (95% CI: 0.470–0.503)), HbA1c testing (OR = 0.401 (95% CI: 0.389–0.413)), and BP measurement (OR = 0.121 (95% CI: 0.116–0.125)), with partial recovery later pandemic.ConclusionsAll measures of diabetes care were substantially decreased early pandemic, with a partial recovery later pandemic across all patient groups. With the increase in virtual care due to the COVID-19 pandemic, diabetes care has been negatively impacted over 1-year after pandemic onset.

Influence of Seasonality and Public-Health Interventions on the COVID-19 Pandemic in Northern Europe.

Most government efforts to control the COVID-19 pandemic revolved around non-pharmaceutical interventions (NPIs) and vaccination. However, many respiratory diseases show distinctive seasonal trends. In this manuscript, we examined the contribution of these three factors to the progression of the COVID-19 pandemic. Pearson correlation coefficients and time-lagged analysis were used to examine the relationship between NPIs, vaccinations and seasonality (using the average incidence of endemic human beta-coronaviruses in Sweden over a 10-year period as a proxy) and the progression of the COVID-19 pandemic as tracked by deaths; cases; hospitalisations; intensive care unit occupancy and testing positivity rates in six Northern European countries (population 99.12 million) using a population-based, observational, ecological study method. The waves of the pandemic correlated well with the seasonality of human beta-coronaviruses (HCoV-OC43 and HCoV-HKU1). In contrast, we could not find clear or consistent evidence that the stringency of NPIs or vaccination reduced the progression of the pandemic. However, these results are correlations and not causations. We hypothesise that the apparent influence of NPIs and vaccines might instead be an effect of coronavirus seasonality. We suggest that policymakers consider these results when assessing policy options for future pandemics. The study is limited to six temperate Northern European countries with spatial and temporal variations in metrics used to track the progression of the COVID-19 pandemic. Caution should be exercised when extrapolating these findings.

Outbreak prediction of COVID-19 using Recurrent neural network using Wireless Sensor Network

A multitude of outbreak prediction models are employed on a global scale to facilitate informed decision-making and the implementation of appropriate control measures in light of the COVID-19 pandemic. The authorities are now focusing on a straightforward epidemiological and statistical methodology for forecasting the global COVID-19 epidemic. These models are widely recognized within the media landscape. Long-term prediction has been found to have poor precision in typical models due to the presence of considerable uncertainty and insufficient vital data. Despite several efforts that have been undertaken to tackle this issue, there is a necessity to enhance the fundamental generalization and robustness of current models. There is a need for a comparative analysis of recurrent neural networks (RNN) and long short-term memory models (LSTM) in order to forecast the breakout of COVID-19, in comparison to the currently existing models. The architectural design incorporates the concept of the attention mechanism, specifically, the use of attention inside hidden data. This methodology enables the identification of patterns and the prioritization of time-sensitive information, leading to the creation of a network that is easily comprehensible. This research presents a proposal for utilizing RNN with LSTM to anticipate outbreaks of COVID-19. Additionally, we have incorporated a learning vector time embedding into our methodology, as the inclusion of time in a vector representation may be seamlessly integrated into many architectures. The model provides a forecast of the progression of the COVID-19 pandemic in Europe’s most severely affected nations, including Italy, France, Spain, as well as a country in North America, specifically Canada. This study proposes that variations in behavior across different nations indicate the potential efficacy of employing machine learning as a modelling tool for understanding and predicting the spread of epidemics. This paper provides an initial benchmarking analysis to demonstrate the potential of recurrent neural networks (RNNs) for future academic investigations. The study presents a unique method that combines RNNs with LSTM to effectively forecast flare-ups. The experimental results show that our proposed LSTM model performs better than existing models with lesser RMSE and MAPE values.

Comparison of sinonasal symptoms in upper respiratory tract infections during the infectious diseases season of November 2023 to March 2024-a cross-sectional study.

Upper respiratory tract infections (URTIs) are among the most common reasons for patients consulting a general practitioner (GP) during the infectious diseases season, with viruses being the predominant cause. The COVID-19 pandemic has significantly impacted GPs' perception of these infections. The pandemic's progression, especially with the emergence of the Omicron variant, has complicated the diagnosis and treatment of URTIs, with evolving symptoms. The aim of this study was to assess the differences in symptoms reported by patients with various infections, such as COVID-19, influenza, common cold, and post-viral rhinosinusitis, during the infectious diseases season of November 2023 to March 2024. The study was conducted in a primary health care clinic, providing care for a population of approximately 10,000 people, among adult patients presenting with URTI symptoms during the 2023/2024 infectious diseases season. Patients qualified for the study were swabbed for SARS-CoV-2, influenza A and B and respiratory syncytial virus (RSV) antigens. Symptoms were assessed with the use of a semi-structured questionnaire. Of the 1810 patients presenting with symptoms of URTIs, 276 patients were included in the study. Among patients with COVID-19, symptoms of nasal obstruction (p = 0.005) and nasal discharge (p = 0.001) were less common than in those with influenza or common cold. However, these nasal symptoms were significantly more frequent among patients with COVID-19 who had confirmed previous immunization (COVID-19 history or vaccination) (p = 0.028). The incidence of individual sinonasal symptoms varies significantly depending on the aetiological agent of the URTI. This observation may not only help clinicians make the correct diagnosis, but also suggests an inflammatory response in the nasal mucosa and paranasal sinuses that is dependent on the aetiological agent. The study also indicates that this response is altered within the same virus species following immunization. The study's limitations include a small sample size (276 patients), focus on one season and one GP practice, and reliance on clinical signs and antigen tests. Nonetheless, the findings provide valuable insights. Further research with larger patient groups and extended follow-up periods is required to confirm these findings.