Longitudinal Projection of Herd Prevalence of Influenza A(H1N1)pdm09 Virus Infection in the Norwegian Pig Population by Discrete-Time Markov Chain Modelling

In order to quantify projections of disease burden and to prioritise disease control strategies in the animal population, good mathematical modelling of infectious disease dynamics is required. This article investigates the suitability of discrete-time Markov chain (DTMC) as one such model for forecasting disease burden in the Norwegian pig population after the incursion of influenza A(H1N1)pdm09 virus (H1N1pdm09) in Norwegian pigs in 2009. By the year-end, Norway’s active surveillance further detected 20 positive herds from 54 random pig herds, giving an estimated initial population prevalence of 37% (95% CI 25–52). Since then, Norway’s yearly surveillance of pig herd prevalence has given this study 11 years of data from 2009 to 2020 to work with. Longitudinally, the pig herd prevalence for H1N1pdm09 rose sharply to >40% in three years and then fluctuated narrowly between 48% and 49% for 6 years before declining. This initial longitudinal pattern in herd prevalence from 2009 to 2016 inspired this study to test the steady-state discrete-time Markov chain model in forecasting disease prevalence. With the pig herd as the unit of analysis, the parameters for DTMC came from the initial two years of surveillance data after the outbreak, namely vector prevalence, first herd incidence and recovery rates. The latter two probabilities formed the fixed probability transition matrix for use in a discrete-time Markov chain (DTMC) that is quite similar to another compartmental model, the susceptible–infected–susceptible (SIS) model. These DTMC of predicted prevalence (DTMCP) showed good congruence (Pearson correlation = 0.88) with the subsequently observed herd prevalence for seven years from 2010 to 2016. While the DTMCP converged to the stationary (endemic) state of 48% in 2012, after three time steps, the observed prevalence declined instead from 48% after 2016 to 25% in 2018 before rising to 29% in 2020. A sudden plunge in H1N1pdm09 prevalence amongst Norwegians during the 2016/2017 human flu season may have had a knock-on effect in reducing the force of infection in pig herds in Norway. This paper endeavours to present the discrete-time Markov chain (DTMC) as a feasible but limited tool in forecasting the sequence of a predicted infectious disease’s prevalence after it’s incursion as an exotic disease

Analysis of activity of Epithiospecifier Protein (Esp) in different parts (flowers and leaves) of Carica Papaya

Glucosinolate are sulphur-containing glucosides found in Brassicaceous plants that can be hydrolyzed enzymatically by plants myrosinase or non-enzymatically to form primarily isothiocyanates and/or simple nitriles. From a human health perspective, isothiocyanates are quite important because they are the major inducers of carcinogen detoxifying enzymes. Specifier proteins such as ESP may occur in some but not all glucosinolate-containing plants and promote the formation of biologically active non-isothiocyanate products upon myrosinase-catalyzed glucosinolate breakdown. In this study, the hydrolysis products of glucosinolates in leaf and flower in Carica papaya have been identified by using Gas Chromatography-Mass Spectrometry (GC-MS). Benzyl isothiocyanate was found as one of the hydrolysis product. Surprisingly, benzyl thiocyanate was found in Carica papaya may suggest the activity of TFP. New finding of benzene propanenitrile suggested the presence of gluconasturin in leaf and flower of Carica papaya. As the presence of benzene propanenitrile at room temperature in flower and leaf are suspected due to the presence of ESP, further studies on ESP could confirm this postulation. The ratio of epithionitrile to simple nitrile is used to analyze the ESP activity. In this study, there was no epithionitrile found as hydrolysis product. The possible explanation for this may be due to the low concentration of ferrous lon, high pH and absent of alkenyl glucosinolate In the papaya samples. More research should focus on the conditions for the ESP activity in Carica papaya as this will bring a new understanding in health benefit

Antibodies of influenza A(H1N1)pdm09 virus in pigs’ sera cross-react with other influenza A virus subtypes. A retrospective epidemiological interpretation of Norway's serosurveillance data from 2009–2017

publishedVersio

Human to animal transmission of influenza A(H1N1)pdm09 in a turkey breeder flock in Norway

Introduction: Routine surveillance samples disclosed seropositivity to influenza A virus (IAV) in a Norwegian turkey breeder flock. Simultaneous reports of influenza-like symptoms in farm workers and a laboratory confirmed influenza A(H1N1)pdm09 (H1N1pdm09) infection in one person led to the suspicion of a H1N1pdm09 infection in the turkeys. Animals and methods: H1N1pdm09 infection was confirmed by a positive haemaggutinin inhibition test using H1N1pdm09 antigens, and detection of H1N1pdm09 nucleic acid in reproductive organs of turkey hens. The flock showed no clinical signs except for a temporary drop in egg production. Previous reports of H1N1pdm09 infection in turkeys suggested human-to-turkey transmission (anthroponosis) during artificial insemination. Results and discussion: The flock remained seropositive to IAV and the homologous H1N1pdm09 antigen throughout the following 106 days, with decreasing seroprevalence over time. IAV was not detected in fertilised eggs or in turkey poults from the farm, however, maternally derived antibodies against H1N1pdm09 were found in egg yolks and in day-old poults. Genetic analyses of haemagglutinin gene sequences from one of the infected farm workers and turkeys revealed a close phylogenetic relationship, and confirmed human-to-turkey virus transmission