Association of Equine Herpesvirus 5 with Mild Respiratory Disease in a Survey of EHV1, -2, -4 and -5 in 407 Australian Horses

Equine herpesviruses (EHVs) are common respiratory pathogens in horses; whilst the alphaherpesviruses are better understood, the clinical importance of the gammaherpesviruses remains undetermined. This study aimed to determine the prevalence of, and any association between, equine respiratory herpesviruses EHV1, -2, -4 and -5 infection in horses with and without clinical signs of respiratory disease. Nasal swabs were collected from 407 horses in Victoria and included clinically normal horses that had been screened for regulatory purposes. Samples were collected from horses during Australia’s equine influenza outbreak in 2007; however, horses in Victoria required testing for proof of freedom from EIV. All horses tested in Victoria were negative for EIV, hence archived swabs were available to screen for other pathogens such as EHVs. Quantitative PCR techniques were used to detect EHVs. Of the 407 horses sampled, 249 (61%) were clinically normal, 120 (29%) presented with clinical signs consistent with mild respiratory disease and 38 (9%) horses had an unknown clinical history. Of the three horses detected shedding EHV1, and the five shedding EHV4, only one was noted to have clinical signs referable to respiratory disease. The proportion of EHV5-infected horses in the diseased group (85/120, 70.8%) was significantly greater than those not showing signs of disease (137/249, 55%). The odds of EHV5-positive horses demonstrating clinical signs of respiratory disease were twice that of EHV5-negative horses (OR 1.98, 95% CI 1.25 to 3.16). No quantitative difference between mean loads of EHV shedding between diseased and non-diseased horses was detected. The clinical significance of respiratory gammaherpesvirus infections in horses remains to be determined; however, this survey adds to the mounting body of evidence associating EHV5 with equine respiratory disease.

Avian Influenza Antibody Titer Of Laying Hens in Production Phase At District Penebel Tabanan Regency

Background: The virus of Avian Influenza (AI) H5N1 has become endemic in Indonesia since 2003. In 2012, the Avian Influenza outbreak at District Penebel caused chickens mortality in large numbers. One of the efforts to prevention the Avian Influenza outbreak is by vaccination. Therefore, supporting AI vaccination program needs diagnostic methods from post-vaccinated chickens that produce antibody titer by Hemagglutination Inhibition (HI) test. Purpose: The study aims to monitor the antibody of Avian Influenza phase I and phase II production in laying hens at District Penebel, Tabanan Regency. Method: 131 serum samples were collected from hens serums at poultry which has been sampled before. The serum sample is tested by Hemagglutination Inhibition (HI) test to calculate antibody titer. The serum is protective if the titer reacheas 24 or more, and the serum is unprotective if the titer is under 24. Data presented in 2x2 cross-sectional study contingent tabel and analyzed by Chi-Square (X2) non-parametric with the distribution. Results: Protective percentage of immunity level in production phase I in laying hens at District Penebel is 60,3%, whereas on production phase II is 43,6%. Data from the 2x2 contingent table showed an odd ratio of 1,9. The result of the Chi-Square (X2) analysis statistic represents immunity levels between production phase I and II are non-significance (p>0,05). Conclusion: Production phase I in laying hens has an immunity level 1,9x higher than production phase II. There is an association between the production phase and the protective immunity level of Avian Influenza.

Cycles of Quotidien Pandemic Instances

By silencing the knowledge of our past, it will not disappear; it transforms into a hum. The hum, as a fluid object of silence can be mournful, can represent absence. The hum that we are neglecting connects with our feelings, registering as cyclic vibrations in contact with parts of the body. The vibrato of the hum speaks of unspoken relations that, according to Tina Campt, unifies quietness with sound, surrounded by affect within a register of meaningfulness. If we don’t dare to remember, some images will enunciate—and speak to—the affective register. With the sonic integration of Radio Influenza, artist Jordan Baseman’s computerized voices narrate stories from 1918 through newspaper fragments. The audible tracks add another register to the vibrations, complicating Paul Gilroy’s “politics of transfiguration,” where the “lower frequency” is purposefully over(p)layed mainly with a different set of forgotten histories suppressed from the war narrative. Hence, the sound is felt from an audible and visual register, enacted at the level of the quotidian narratives of twentieth-century photographs and newspaper stories. If we listen to these quiet photos, to these muffled stories, can we acknowledge that just as sonic vibrations, pandemics tend to come in waves as well? In the end, the 1918 spring influenza outbreak was followed by three waves: the fall of 1918, spring of 1919, and winter of 1919. These waves of history, sound, and pandemics, can push us to resist the neglectfulness and acknowledge what we have unlearned from the cycles of quotidian instances, time and time again.

Lymphocyte monocyte ratio is an effective and simple predictor for nosocomial influenza outbreaks

ObjectivesNosocomial influenza outbreak detection remains challenging. We evaluated the diagnostic utility of blood cell parameters, along with their capacity to differentiate between hospital acquired influenza and coronavirus disease 2019 (COVID-19).MethodsWe retrospectively analyzed patients diagnosed with nosocomial influenza from January 2017 to December 2019, and patients with COVID-19 in early 2020 at a tertiary teaching hospital in Beijing, China. We compared the differences between blood cell count and ratios (lymphocyte-to-monocyte ratio [LMR], neutrophil-to-lymphocyte ratio [NLR], lymphocyte-to-platelet ratio [LPR]) at symptom onset, before (admission), and after (recovery) nosocomial influenza. We also compared the abovementioned parameters between influenza and COVID-19 patients.ResultsLymphocyte count, LMR, and LPR were significantly lower in the symptom onset than in the admission and recovery groups (p < 0.001), while NLR was higher (p < 0.001). LMR and NLR exhibited similar and consistent tendencies among different subgroups of patients with nosocomial influenza (p < 0.001). The area under the receiver operating curve (AUC) of LMR, NLR, LPR, and lymphocyte count were 0.914, 0.872, 0.806, and 0.866, respectively. The optimal LMR cut-off value was 2.50, with specificity and sensitivity of 92.0% and 81.3%, respectively. Peripheral blood cell ratios can help diagnose nosocomial influenza significantly earlier than conventional methods. For differentiating influenza and COVID-19, the AUCs of LMR was 0.825.ConclusionsLMR effectively predicts nosocomial influenza outbreaks, particularly during the COVID-19 pandemic when simultaneous transmission can be a substantial threat.

Pollen antigens and atmospheric circulation driven seasonal respiratory viral outbreak and its implication to the Covid-19 pandemic

The patterns of respiratory virus illness are expressed differently between temperate and tropical climates. Tropical outbreaks often peak in wet seasons. Temperate outbreaks typically peak during the winter. The prevailing causal hypotheses focus on sunlight, temperature and humidity variations. Yet no consistent factors have been identified to sufficiently explain seasonal virus emergence and decline at any latitude. Here we demonstrate close connections among global-scale atmospheric circulations, IgE antibody enhancement through seasonal pollen inhalation, and respiratory virus patterns at any populated latitude, with a focus on the US. Pollens emerge each Spring, and the renewed IgE titers in the population are argued to terminate each winter peak of respiratory illness. Globally circulated airborne viruses are postulated to subsequently deposit across the Southern US during lower zonal geostrophic winds each late Summer. This seasonally refreshed viral load is postulated to trigger a new influenza outbreak, once the existing IgE antibodies diminish to a critical value each Fall. Our study offers a new and consistent explanation for the seasonal diminishment of respiratory viral illnesses in temperate climates, the subdued seasonal signature in the tropics, the annually circulated virus phenotypes, and the northerly migration of influenza across the US every year. Our integrated geospatial and IgE hypothesis provides a new perspective for prediction, mitigation and prevention of the outbreak and spread of seasonal respiratory viruses including Covid-19 pandemic.

A novel data-driven methodology for influenza outbreak detection and prediction

Influenza is an infectious disease that leads to an estimated 5 million cases of severe illness and 650,000 respiratory deaths worldwide each year. The early detection and prediction of influenza outbreaks are crucial for efficient resource planning to save patient’s lives and healthcare costs. We propose a new data-driven methodology for influenza outbreak detection and prediction at very local levels. A doctor’s diagnostic dataset of influenza-like illness from more than 3000 clinics in Malaysia is used in this study because these diagnostic data are reliable and can be captured promptly. A new region index (RI) of the influenza outbreak is proposed based on the diagnostic dataset. By analysing the anomalies in the weekly RI value, potential outbreaks are identified using statistical methods. An ensemble learning method is developed to predict potential influenza outbreaks. Cross-validation is conducted to optimize the hyperparameters of the ensemble model. A testing data set is used to provide an unbiased evaluation of the model. The proposed methodology is shown to be sensitive and accurate at influenza outbreak prediction, with average of 75% recall, 74% precision, and 83% accuracy scores across five regions in Malaysia. The results are also validated by Google Flu Trends data, news reports, and surveillance data released by World Health Organization.

A New Perspective; Co-Infection of Influenza with COVID-19 During The COVID-19 Pandemic in Southern Iran

Background In the current COVID-19 pandemic, COVID-19 viral respiratory symptoms have been confused with other viral respiratory infections such as influenza. Given that both viruses cause respiratory diseases, there are important differences between these two viruses in terms of how they are spread, controlled and treated. Due to these differences, a definitive diagnosis of each infection has important implications for the public health measures that can be implemented in response to the treatment of each virus.Method In this cross-sectional retrospective study from 4th September 2020 to 5th December 2020 (time period of influenza outbreak in Iran, a total of 455 Severe Acute Respiratory Infections (SARI) patients were included. Two nasopharyngeal and one oropharyngeal throat swab samples were collected from all participants and evaluated for COVID-19 by real-time reverse transcriptase–polymerase-chain-reaction (RT-PCR) assay using the E-Gene specific primers/FAM probe and S Gene primers/ROX probe (Covitech, Iran) for SARS-CoV-2. Due to the concurrence of the study in autumn and the history of influenza outbreak at this time in Iran. Nasopharyngeal samples were collected and tested for influenza viruses A (H1N1, H3N2, seasonal flu), and Influenza B by one step qRT-PCR Master Mix (Invitrogen, United States) and AG synthesis probe and primers (Metabion, Germany) for Influenza A (H1N1, H3N2, seasonal flu) and B.Results In this study, 455 patients with SARI were hospitalized during September to December 2020. 203(44.61%) were infected with SARS-COV-2 and of these patients, one patient was positive for both COVID-19 and Influenza. The mean age was estimated 54.93 ± 17.00 and 50.65 ± 17.71 in COVID-19 and non-COVID-19 groups, respectively which was significantly different (P < 0.001). Sex distribution between two groups showed that most of COVID-19 patients were male, this is in contrast with the COVID-19 negative group, in which most of patients were female and these differences were statistically significant. (P = 0.057). Clinical outcomes of patients with diagnosed SARI were measured. The main parameters were discharge from ICU and death during hospital admission. There was no significant difference between the number of patients discharge from ICU who were COVID positive or COVID negative. In addition, there was no significant difference between the number of patients who died who were COVID positive or COVID negative.Conclusion The decline in Influenza incidence and coinfection with COVID-19 in comparison to previous years appears to be significant due to its concurrence with the COVID19 pandemic and general population awareness on observing the instructions for personal respiratory protection e.g mask-wearing, hand washing, self-isolation and public health measures. Therefore, routine testing and empirical treatment for suspected influenza coinfection in COVID-19 patients is not recommended.

Beyond flu: Trends in respiratory infection outbreaks in Ontario healthcare settings from 2007 to 2017, and implications for non-influenza outbreak management

Background: Outbreaks cause significant morbidity and mortality in healthcare settings. Current testing methods can identify specific viral respiratory pathogens, yet the approach to outbreak management remains general. Objectives: Our aim was to examine pathogen-specific trends in respiratory outbreaks, including how attack rates, case fatality rates and outbreak duration differ by pathogen between hospitals and long-term care (LTC) and retirement homes (RH) in Ontario. Methods: Confirmed respiratory outbreaks in Ontario hospitals and LTC/RH reported between September 1, 2007, and August 31, 2017, were extracted from the integrated Public Health Information System (iPHIS). Median attack rates and outbreak duration and overall case fatality rates of pathogen-specific outbreaks were compared in both settings. Results: Over the 10-year surveillance period, 9,870 confirmed respiratory outbreaks were reported in Ontario hospitals and LTC/RH. Influenza was responsible for most outbreaks (32% in LTC/RH, 51% in hospitals), but these outbreaks were shorter and had lower attack rates than most non-influenza outbreaks in either setting. Human metapneumovirus, while uncommon (<4% of outbreaks) had high case fatality rates in both settings. Conclusion: Attack rates and case fatality rates varied by pathogen, as did outbreak duration. Development of specific outbreak management guidance that takes into account pathogen and healthcare setting may be useful to limit the burden of respiratory outbreaks.