Seasonal Outbreaks Research Articles

Understanding the public's decision-making about seasonal flu vaccination during a pandemic: Application of the precaution adoption process model.

Understanding the behavioural factors influencing flu vaccination is crucial for mitigating seasonal infection outbreaks. This study utilised the Precaution Adoption Process Model (PAPM) to examine the public's decision-making about seasonal flu vaccination through an online cross-sectional survey with 2004 participants in England, UK. Results showed varying stages of decision-making: 7% in Stage 2 (unengaged), 10% in Stage 3 (undecided), 7% in Stage 4 (decided not to vaccinate), 39% in Stage 5 (decided to vaccinate) and 38% in Stage 6 (vaccinated). Regression modelling revealed factors common across stages and unique to certain stages, such as flu vaccination history distinguishing those who received the vaccine. Vaccine knowledge (Stage 2), perceived benefits (Stage 4), perceived control and fear of needles (Stage 5) were uniquely associated with specific PAPM stages. The study discusses policy implications for integrating these findings to improve flu vaccination uptake, highlighting the importance of tailored strategies based on decision-making stages.

Short-Term Forecasting of Respiratory Virus Transmission and Severe Disease Risk Among Pediatric and Adult Populations for Public Health Planning in Ontario

Background: Influenza A presents a major public health issue in Ontario, affecting the population with regular seasonal outbreaks that lead to health and economic burdens. This study uses a collection of historical data on Influenza A cases which dates back to 2015. Objectives: Utilizing a data-driven approach, this study aims to enhance short-term forecasting of Influenza A cases. By predicting the number of cases over a 14-day horizon, we intend to provide actionable insights for public health officials to implement timely and effective interventions. The model seeks to differentiate impacts on pediatric and adult populations, thereby optimizing resource allocation and intervention strategies tailored to demographic-specific needs. Methods: Utilizing the R package tscount, tailored to count time series data, we modeled the number of Influenza A cases. This package supports generalized linear models, which are pivotal for predicting time-dependent phenomena and allow for the inclusion of past values and covariates into the models. The analysis was segmented by age group to refine predictions. Results: The model accurately forecasted 14-days of Influenza A cases for both pediatric and adult populations. Predictive performance was assessed using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE), which upheld the model's efficacy in short-term forecasting within acceptable error thresholds. Conclusions: The developed forecasting model proves effective for short-term predictions, providing insights into outbreak trends and severity. These predictions are crucial for optimizing resource distribution, informing public health advisories, and enhancing community preparedness.

Management of genomic surveillance for respiratory viral infections circulating in the territory of the city of Moscow

Introduction. Outbreaks of respiratory viral infections have an economic impact on the healthcare system and pose a threat to public well-being. Monitoring for the incidence of acute respiratory viral infections in a metropolitan area, especially during the COVID-19 pandemic, was in dire need of an adequate tool to identify mutations and variants that evade vaccine immunity and initiate an increase in incidence. Genomic surveillance was required for a timely response. Purpose of the study. Management of the Moscow Genomic Center for genomic surveillance for acute respiratory viral infections and COVID-19, with an assessment of the results during seasonal outbreaks in the capital. Materials and methods. With the support of the Moscow City Health Department, management and logistics measures were developed and implemented, the NGS testing program in patient samples on a planned basis and during the period of increased incidence of acute respiratory viral infections and COVID-19, technical procedures for high-throughput sequencing were developed, the security of data exchange and biosafety of medical personnel were ensured. Results. The Moscow Genome Center was established within the structure of the Moscow City Health Department. For the period from October 2023 to April 2024, targeted NGS data (a panel of thirty two pathogens, 6528 samples were tested): SARS-COV-2 dominated the entire period, the incidence of influenza A (H3N2) increased sharply from the beginning of December and decreased sharply by the end of January. Sars-CoV-2 genetic lineage rotation: XBB lineage dominated (most represented: XBB.1.16, XBB.1.16.11) from October to the end of January, then JN lineage prevailed (most represented: JN.1, also found: JN.1.13, JN.1.18, JN.1.19, JN.1.4). Influenza A strain rotation: H3N2 (A/Massachusetts/01/2020) and H3N2 (A/Massachusetts/38/2019) dominated from December to February. Research limitations. A targeted panel of 32 respiratory viruses most common in the Moscow population was used for NGS. Incomplete coverage of the entire viriome is a conditional limitation. Conclusion. Representative, high-quality and continuous genetic surveillance has been managed in the capital. The Moscow Genome Center has successfully implemented the NGS Testing Program and support for the Russian Genomic Resource of Microorganisms VGARus.

Distribution patterns of Calonectria (Ascomycota, Sordariomycetes, Hypocreales, Nectriaceae) species complexes related to diseased leaves and soil habitats during leaf blight outbreak season in Eucalyptus plantations in southern China.

Calonectria leaf blight caused by Calonectria species is one of the most important diseases associated with Eucalyptus plantations in Asia and South America. This study aimed to clarify the distribution patterns of Calonectria species residing in different species complexes associated with diseased trees and soils during leaf blight outbreak season in Eucalyptus plantations in southern China. In this study, 482 Calonectria isolates obtained from diseased Eucalyptus trees and soils under these trees in eight sampling sites in three provinces were identified by DNA sequence analyses of tef1, tub2, cmdA, and his3 gene regions. Six species residing in three species complexes were identified: Calonectriapseudoreteaudii and C.acaciicola in the Calonectriareteaudii species complex; C.hongkongensis, C.aconidialis, and C.chinensis in C.kyotensis species complex; and C.auriculiformis in C.cylindrospora species complex. The habitats of Calonectria in different species complexes differed, C.reteaudii species complex inhabits in both diseased trees and soils, C.kyotensis species complex only in soils. The Calonectria leaf blight in the sampled regions was caused by species in the C.reteaudii species complex but not by the species in the C.kyotensis species complex. These findings suggest that the species in the C.reteaudii species complex should receive more attention in disease management, as they are the primary cause of the disease in the sampled regions.

Evaluation of Immunochromatographic Test for Rapid Detection of Norovirus, Rotavirus, and Adenovirus in Stool Samples.

Viral enteric infections are illnesses caused by several types of viruses that primarily affect the gastrointestinal system. Globally, three major viruses associated with gastroenteritis, including norovirus (NoV), rotavirus A (RVA), and human adenovirus (HAdV), have been widely recognized. Accordingly, a rapid and sensitive diagnostic tool, such as immunochromatographic (IC) test, for diarrheal virus detection is required and helpful for rapid diagnosis. The IP-Triple I IC test kit for simultaneous triple virus detections of NoV, RVA, and HAdV was evaluated for its efficacy by using stool specimens that were known positive for these viruses by real-time RT-PCR or PCR, which was used as the gold standard method. The results revealed that the IP-Triple I IC test kit exhibited a very high level of specificity (100%) for NoV, RVA, and HAdV detections, while the sensitivity was slightly different for these three viruses. The sensitivity of detection for RVA was 86.7%, whereas those for NoV and HAdV were 70.6% and 76.2%, respectively. This IP-Triple I IC kit could detect common antigens of a wide range of NoV, RVA, and HAdV genotypes (NoV GII.2, GII.4, GII.6, GII.7, GII.10, GII.17, RVA G1P[8], G2P[4], G3P[8], G8P[8], G9P[8], HAdV-C1, -C2, -C5, -A12, -F40, and -F41). Our results revealed that the IP-Triple I IC test kit is highly effective for simultaneous, direct detection of common antigens of several genotypes of NoV, RVA, and HAdV in stool specimens and useful for screening and rapid diagnosis of diarrheal viruses during the seasonal outbreak.

SARS-CoV-2 Encephalitis versus Influenza Encephalitis: More Similarities than Differences.

From time to time, physicians face challenging diagnostic and therapeutic issues concerning the acute management of children with viral encephalitis. The aim of this article is to provide an updated narrative review on the similarities and differences between SARS-CoV-2 and influenza encephalitis. A PubMed search was performed with the function "Clinical Queries" using the key terms "SARS-CoV-2" OR "Influenza" AND "Encephalitis". The search strategy included metaanalyses, clinical trials, randomized controlled trials, reviews and observational studies. The search was restricted to the English literature and pediatric population. This article compares similarities and contrasts between SARS-CoV-2 and influenza-associated encephalitis. Encephalitis is an uncommon manifestation of both influenza and SARS-CoV-2. Both viruses are associated with fever and respiratory symptoms. However, SARS-CoV-2 patients may only have mild symptoms or be asymptomatic as silent carriers, rendering the disease spread difficult to control. Influenza patients usually have more severe symptomatology and are often bed bound for several days limiting its spread. Influenza is associated with seasonal and annual outbreaks, whereas SARS-CoV-2 has become endemic. Complications of encephalitis are rare in both viral infections but, when present, may carry serious morbidity and mortality. Many long-term sequelae of COVID- 19 infections (long COVID-19) have been described but not with influenza infections. Mortality associated with encephalitis appears higher with influenza than with SARS-CoV-2. Prophylaxis by immunization is available for both influenza and SARS-CoV-2. Specific efficacious antivirals are also available with oseltamivir for influenza and nirmatrelvir/ritonavir for SARS-CoV-2. Steroids are indicated with more severe SARS-CoV-2 but their role is not distinct in influenza disease. Encephalitis is a rare complication of influenza and SARS-CoV-2 infections. Both carry significant morbidity and mortality. Efficacious vaccines for prophylaxis and antivirals for treatment are available for both viruses.

Respiratory Diagnoses Year-Round: Unraveling the Multifaceted Pediatric Infection Cycles.

The aim of the study is to analyze the annual cycle of pediatric medically attended respiratory illnesses. Data on 141 million pediatric respiratory visits from the years 2010-2019 were obtained from the Polish National Healthcare Fund. To identify underlying patterns and trends within the aggregated data, techniques like seasonal-trend decomposition using LOESS (STL) and principal component analysis (PCA) were applied. A strongly recurring pattern was observed. Following the annual minimum in late summer, there was a sudden surge in upper respiratory infections in early September. Subsequently, overall visits declined gradually, while the share of lower respiratory infections increased, particularly during the influenza peaks from January to March. Afterwards, visits declined steadily, with an additional peak of tonsillopharyngitis noted in midsummer. Dimensionality reduction of diagnoses implied the existence of two major groups of co-occurring diagnoses, the proportions of which change over the year: one smaller but more severe, peaking during the influenza season, and the second dominating with lower severity. Age differences in diagnoses were observed, with babies showing upper respiratory infections likely diagnosed with the common cold rather than a more specific upper respiratory infection. While enhancing surveillance strategies is indeed a desirable long-term goal, it is worth noting that despite the variability observed in the onset of the influenza season, the infection cycles generally follow a relatively fixed pattern. This consistency provides a foundation for effective planning and underscores the potential for proactive measures to mitigate the impact of seasonal outbreaks.

STAR LIGHT Study: XBB.1.5 COVID-19 mRNA Vaccines Boost Systemic but Not Mucosal Immunity Against the SARS-CoV-2 JN.1 Variant in Patients with Chronic Liver Disease.

Patients with chronic liver disease (CLD) have impaired vaccine immunogenicity and an excess risk of severe COVID-19. While variant-adapted COVID-19 mRNA vaccines are recommended for vulnerable individuals, their efficacy in patients with CLD has not been studied. We present the first evaluation of XBB.1.5 COVID-19 vaccine immunogenicity against the SARS-CoV-2 JN.1 variant in patients with CLD. Serum anti-receptor binding domain (RBD) IgG, neutralization, and saliva anti-RBD IgG and IgA against wild-type SARS-CoV-2 (WT) and the XBB.1.5, EG.5.1, BA.2.86, and JN.1 variants were quantified before and 2-4 weeks following a fourth dose of XBB.1.5 mRNA vaccines. Vaccination boosted anti-RBD IgG and neutralization against all tested variants including JN.1 (each p < 0.001). Following immunization, neutralization was lower against JN.1 compared to WT, XBB.1.5, and EG.5.1 (p < 0.001, p < 0.001, and p < 0.01, respectively). Vaccination reduced neutralization failure rates against BA.2.86 and JN.1 (each p < 0.05). The evasion of vaccine-induced antibodies by the tested variants was low, indicated by the positive correlation between anti-RBD IgG and neutralization. At mucosal sites, vaccination boosted anti-RBD IgG (each p < 0.01) but failed to induce infection-blocking IgA (each p > 0.05). XBB.1.5 vaccines protect CLD patients against recent SARS-CoV-2 variants, but developing vaccines with optimized mucosal immunogenicity is required to prevent SARS-CoV-2 transmission and recurrent seasonal COVID-19 outbreaks.

Evolving epidemiology, clinical features, and genotyping of dengue outbreaks in Bangladesh, 2000-2024: a systematic review.

The 2023 dengue outbreak has proven that dengue is not only an endemic disease but also an emerging health threat in Bangladesh. Integrated studies on the epidemiology, clinical characteristics, seasonality, and genotype of dengue are limited. This study was conducted to determine recent trends in the molecular epidemiology, clinical features, and seasonality of dengue outbreaks. We analyzed data from 41 original studies, extracting epidemiological information from all 41 articles, clinical symptoms from 30 articles, and genotypic diversity from 11 articles. The study adhered to the standards of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Statement and Cochrane Collaboration guidelines. A total of 565,438 dengue cases and 2,587 fatalities were documented from January 2000 to March 2024. Notably, 60% of cases during the 2019 and 2023 outbreaks were reported in regions previously considered non-endemic. Fatalities were more frequent among women (70%). The majority of the studies (95-100%) used the NS1Ag test, followed by IgG or IgM and RT-PCR tests. New hotspots of dengue transmission were identified in the southern (Khulna, 10.8% and Barishal, 11.8%) and southeastern (Chattogram, 13.8%) regions of Bangladesh. Serotyping was conducted on 92.4% (1,456 of 1,575) of isolates between 2012 and 2023. Of the four serotypes, DENV3 was the most prevalent (57%), followed by DENV2 (30%), DENV1 (11%), and DENV4 (<1%). Genotype DENV3-I (43 of 59 isolates) was the most prevalent, followed by DENV3-II (8 of 59). The highest frequency of dengue cases was observed in August (26.3%), followed by September (22.5%), October (20.2%), and November (13.08%). Fever (90.51, 95% CI 85-100%) was the most prevalent symptom, followed by headache (57.98, 95% CI 12-100%), vomiting (51.16, 95% CI 23-91%), abdominal pain (34.12, 95% CI 12-85%), and myalgia (25.53, 95% CI 13-85%), respectively. This study provides integrated insights into the molecular epidemiology, clinical features, seasonality, and transmission of dengue in Bangladesh and highlights research gaps for future studies.

Practice guideline of influenza vaccination and antiviral drugs use in children(2024 editon)

Influenza is the most common acute respiratory infectious diseases among children in China. The annual seasonal influenza outbreak has a significant impact on children's health, poses a significant disease and socioeconomic burden, and arouses a wide public concern. In recent years, a number of new influenza vaccines and influenza antivirals have been approved for use in children, expanding the choices for prevention and treatment of influenza. Pediatric Infection Group, Chinese Society of Infectious Diseases of Chinese Medical Association and Infection Group, Pediatric Expert Committee of National Health Commission Capacity Building and Continuing Education, and China Clinical Practice Guidelines Alliance Methodology Committee organized a multidisciplinary guideline development group (GDG) consisting of experts in pediatrics, infectious diseases,epidemiologists,health policy,and guideline methodology proposed eight key issues concerning influenza vaccination and antiviral use from a practice perspective. Through research question construction, evidence retrieval and synthesis, evidence appraisal and evidence-to-decision discussion, recommendations and implementation suggestions were formulated. This guideline is intended to provide guidance for pediatricians at different facility levels and healthcare providers engaged in vaccination services,and institutional professionals dealing with prevention and control of infectious diseases.

Etiology of Acute Encephalitis Syndrome in Adults in a Tertiary Care Center in Eastern Uttar Pradesh

Seasonal outbreaks of acute encephalitis syndrome (AES) with high case fatality rates have been commonly reported among adults in India. With an increase in Japanese encephalitis virus (JEV) vaccination, the etiology of AES is also changing. However, most studies on AES in India have focused only on children and on JEV. This study was conducted in the Department of Medicine, Institute of Medical Sciences, Banaras Hindu University between 2020 and 2022 to determine the etiology of AES in adults. Blood and cerebrospinal fluid (CSF) were collected from patients 18 years or older with fever and altered sensorium for ≤15 days. We did IgM ELISA for dengue, chikungunya, West Nile virus, scrub typhus, leptospirosis from serum, CSF-IgM for JEV, and CSF–polymerase chain reaction for herpes simplex virus 1 and 2, varicella-zoster virus, enterovirus, and cartridge-based nucleic acid amplification test (CBNAAT) for tuberculous meningitis (TBM). The most common cause of AES identified in our study was TBM (16.7%), followed by leptospirosis (15.1%) and scrub typhus (11.9%). The high occurrence of TBM in our study highlights the importance of CSF-CBNAAT for all AES patients. As leptospirosis and scrub typhus are easily treatable, early detection and treatment of these infections should be recommended.

Insights into Genetic and Antigenic Characteristics of Influenza A(H1N1)pdm09 Viruses Circulating in Sicily During the Surveillance Season 2023-2024: The Potential Effect on the Seasonal Vaccine Effectiveness.

After disruption in the influenza circulation due to the emergence of SARS-CoV-2, the intensity of seasonal outbreaks has returned to the pre-pandemic levels. This study aimed to evaluate the evolution and variability of whole-genome sequences of A(H1N1)pdm09, the predominant influenza virus in Sicily (Italy) during the season 2023-2024. The potential vaccine efficacy was calculated using the pepitope model based on amino acid changes in the dominant epitope of hemagglutinin. The HA gene sequences showed several amino acid substitutions, some of which were within the major antigenic sites. The phylogenetic analysis showed that Sicilian strains grouped into two main genetic clades (6B.1A.5a.2a.1 and 6B.1A.5a.2a) and several subclades. Notably, about 40% of sequences partially drifted from the WHO-recommended vaccine strain A/Victoria/4897/2022 for the Northern Hemisphere. These sequences mostly belonged to the subclades C.1.8 and C.1.9 and harboured the amino acid mutations responsible for the modest predicted vaccine efficacy (E = 38.12% of 53%, pepitope = 0) against these viruses. Amino acid substitutions in other gene segments were also found. Since influenza viruses are constantly evolving, genomic surveillance is crucial in monitoring their molecular evolution and the occurrence of genetic and antigenic changes, and, thus, their potential impact on vaccine efficacy.

Mean daily temperatures can predict the thermal limits of malaria transmission better than rate summation.

Temperature shapes the distribution, seasonality, and magnitude of mosquito-borne disease outbreaks. Mechanistic models predicting transmission often use mosquito and pathogen thermal responses from constant temperature experiments. However, mosquitoes live in fluctuating environments. Rate summation (nonlinear averaging) is a common approach to infer performance in fluctuating environments, but its accuracy is rarely validated. We measured three mosquito traits that impact transmission (bite rate, survival, fecundity) in a malaria mosquito (Anopheles stephensi) across temperature gradients with three diurnal temperature ranges (0, 9 and 12°C). We compared thermal suitability models with temperature-trait relationships observed under constant temperatures, fluctuating temperatures, and those predicted by rate summation. We mapped results across An. stephenesi's native Asian and invasive African ranges. We found: 1) daily temperature fluctuation significantly altered trait thermal responses; 2) rate summation partially captured decreases in performance near thermal optima, but also incorrectly predicted increases near thermal limits; and 3) while thermal suitability characterized across constant temperatures did not perfectly capture suitability in fluctuating environments, it was more accurate for estimating and mapping thermal limits than predictions from rate summation. Our study provides insight into methods for predicting mosquito-borne disease risk and emphasizes the need to improve understanding of organismal performance under fluctuating conditions.

Respiratory syncytial virus infection provides protection against severe acute respiratory syndrome coronavirus challenge.

Severe acute respiratory syndrome coronavirus 2 and respiratory syncytial virus are respiratory viruses that are a major health burden worldwide. Severe acute respiratory syndrome coronavirus 2 and respiratory syncytial virus frequently have peak seasonal outbreaks during the winter months, and are capable of causing severe respiratory disease, often leading to hospitalization. The 2019 pandemic brought attention to the importance of understanding how co-circulating viruses can impact the disease severity of other respiratory viruses. It is known that many hospitalized patients are undergoing multiple viral infections at once, yet not much has been studied to understand the impact this has on other respiratory viruses or patients. How co-circulating viruses impact one another can provide critical knowledge for future interventions of hospitalized patients and potential vaccination strategies.

STING Agonist Induced Innate Immune Responses Drive Anti-Respiratory Virus Activity In Vitro with Limited Antiviral Efficacy In Vivo.

The emergence of SARS-CoV-2 and seasonal outbreaks of other respiratory viruses highlight the urgent need for broad-spectrum antivirals to treat respiratory tract infections. Stimulator of interferon genes (STING) is a key component of innate immune signaling and plays a critical role in protection of the host against viral infections. Previously the STING agonist diABZI-4, a diamidobenzimidazole-based compound, demonstrated protection against SARS-CoV-2 both in vitro and in vivo. However, its broad-spectrum antiviral activity against other respiratory viruses in human airway epithelial cells, which are the primary targets of these infections, is not well established. In this study, we demonstrated that diABZI-4 stimulated robust innate immune responses protecting lung cells against a wide range of respiratory viruses, including influenza A virus (IAV), common cold coronaviruses, SARS-CoV-2, human rhinovirus (HRV), and human parainfluenza virus. diABZI-4 was highly active in physiologically relevant human airway epithelial tissues grown at the air-liquid interface, blocking replication of IAV, SARS-CoV-2, and HRV in these tissues. Furthermore, treatment of macrophages with diABZI-4 resulted in the secretion of cytokines that protected the primary airway epithelial cells from IAV infection. Despite the promising in vitro pan-antiviral activity, intranasal administration of diABZI-4 in mice provided early, but not sustained, inhibition of IAV replication in the lungs. These data highlight the complexities of the relationship between timing of STING agonist-driven inflammatory responses and viral replication dynamics, emphasizing the development challenge posed by STING agonists as potential therapeutics against respiratory viruses.

Influence of stocking density and interaction variability on disease progression of white spot syndrome virus-infected shrimp under different risk scenarios

White spot syndrome virus (WSSV), the causative agent of white spot disease (WSD), is the most significant viral pathogen affecting farmed shrimp. As the culture model for whiteleg shrimp has evolved into a higher-intensity model, the need to study the influence of stocking density on disease progression in pond culture systems has been reinforced. Therefore, we assessed WSD progression by deriving a direct correlation between seasonal disease outbreak risk, stocking density, and viral shedding rate (WSSV genome copies/L/g) using three different stocking densities: high (210 shrimp/m2), medium (140 shrimp/m2), and low (70 shrimp/m2). In Experiment 1 (three stocking densities at 25 °C) and Experiment 2 (stocking density × temperature conditions), shrimp showed relatively high cumulative mortality within the temperature range of optimal WSSV replication (23–29 °C). Notably, the mortality trend, peak viral loads, and viral shedding of WSSV-infected shrimp occurred earlier under high-density conditions, regardless of temperature. Thereafter, this study established WSD risk scenarios based on water temperature conditions and confirmed a significant difference in mortality trends between vulnerable and less vulnerable water temperature scenarios under high- and low-density conditions. The vulnerable water temperature scenario included constant (25 °C), shifting-up (20 °C to 30 °C), and shifting-down (30 °C to 20 °C) conditions, whereas the less vulnerable water temperature scenario included constant 20 °C and 30 °C conditions. Based on mortality trends, the WSD risk scenarios revealed that the times to 50 % mortality for shrimp at high, medium, and low densities were 4, 5, and 6 days post-infection (dpi) in the vulnerable water temperature scenario, and 6, 7, and 9 dpi in the less vulnerable water temperature scenario. Viral shedding variability was evaluated based on the correlation between viral loads and viral shedding rate, and linear regression analysis revealed a significant positive correlation between viral shedding rates and viral loads in shrimp, regardless of WSD risk scenarios or stocking density conditions. Notably, a relatively enhanced viral shedding rate was observed at higher stocking densities (from low- to high-density conditions) and under vulnerable water temperature scenarios. This study suggests that increased stocking density and vulnerable water temperature scenarios could induce greater interactions among WSSV-infected shrimp. It also confirmed the potential role of risk scenarios, stocking density, and viral shedding in WSD progression, providing insights into the disease outbreak mechanisms on shrimp farms.

A comprehensive review of influenza B virus, its biological and clinical aspects.

Influenza B virus (IBV) stands as a paradox, often overshadowed by its more notorious counterpart, influenza A virus (IAV). Yet, it remains a captivating and elusive subject of scientific inquiry. Influenza B is important because it causes seasonal flu outbreaks that can lead to severe respiratory illnesses, including bronchitis, pneumonia, and exacerbations of chronic conditions like asthma. Limitations in the influenza B virus's epidemiological, immunological, and etiological evolution must be addressed promptly. This comprehensive review covers evolutionary epidemiology and pathogenesis, host-virus interactions, viral isolation and propagation, advanced molecular detection assays, vaccine composition and no animal reservoir for influenza B virus. Complex viral etiology begins with intranasal transmission of influenza B virus with the release of a segmented RNA genome that attacks host cell machinery for transcription and translation within the nucleus and the release of viral progeny. Influenza B virus prevalence in domesticated and wild canines, sea mammals, and birds is frequent, yet there is no zoonosis. The periodic circulation of influenza B virus indicates a 1-3-year cycle for monophyletic strain replacement within the Victoria strain due to frequent antigenic drift in the HA near the receptor-binding site (RBS), while the antigenic stability of Yamagata viruses portrays a more conservative evolutionary pattern. Additionally, this article outlines contemporary antiviral strategies, including pharmacological interventions and vaccination efforts. This article serves as a resource for researchers, healthcare professionals, and anyone interested in the mysterious nature of the influenza B virus. It provides valuable insights and knowledge essential for comprehending and effectively countering this viral foe, which continues to pose a significant public health threat.

Update of the COVID-19 Incidence Forecast with the Overlap of Seasonal Flu Outbreaks

Update of the COVID-19 Incidence Forecast with the Overlap of Seasonal Flu Outbreaks

Forecasting infectious diseases in Brazilian cities: Integrating socio-economic and geographic data from related cities through a machine learning approach

Supervised machine learning models and public surveillance data have been employed for infectious disease forecasting in many settings. These models leverage various data sources capturing drivers of disease spread, such as climate conditions or human behavior. However, few models have incorporated the organizational structure of different geographic locations for forecasting. Traveling waves of seasonal outbreaks have been reported for dengue, influenza, and other infectious diseases, and many of the drivers of infectious disease dynamics may be shared across different cities, either due to their geographic or socioeconomic proximity. In this study, we developed a machine learning model to predict case counts of four infectious diseases across Brazilian cities one week ahead by incorporating information from related cities. We compared selecting related cities using both geographic distance and GDP per capita. Incorporating information from geographically proximate cities improved predictive performance for two of the four diseases, specifically COVID-19 and Zika. We also discuss the impact on forecasts in the presence of anomalous contagion patterns and the limitations of the proposed methodology.

Efficacy of molnupiravir and interferon for the treatment of SARS-CoV-2 in golden Syrian hamster.

The mortality and hospitalization rate by COVID-19 dropped significantly currently, but its seasonal outbreaks make antiviral treatment still vital. The mortality and hospitazation rate by COVID-19 dropped significantly currently, but its seasonal ourbreaks make antiviral treatment still vital. In our study, syrian golden hamsters were treated with molnupiravir and interferons (IFNs) after SARS-CoV-2 infection. Their weight changes, pathological changes, virus replication and inflammation levels were evaluated. In the IFNs single treatment, only IFN-α group reduced viral load (p < 0.05) and virus titer in hamster lungs. The TNF-α expression decreased significantly in both IFNs treatment at 2dpi. Histological and immunofluorescence results showed lung damage in the IFNs groups were milder at 4dpi. In the molnupiravir/IFN-α combination treatment, weight loss and virus replication in lung were significantly decreased in the mono-molnupiravir group and combination group (p < 0.05), the expression of IL-6, TNF-α, IL-1β and MIP-1α also decreased significantly (p < 0.05), but the combination treatment was not more effective than the mono-molnupiravir treatment. Histological and immunofluorescence results showed the lung damage and inflammation in mono-molnupiravir and combination groups were milder. In summary, IFNs treatment had anti-inflammatory effect against SARS-CoV-2, only IFN-α showed a weak antiviral effect. Molnupiravir/IFN-α combination treatment was effective against SARS-CoV-2 but was not superior to mono-molnupiravir treatment. IFN-α could be considered for immunocompromised patients to stimulate and activate early immune responses.