Dembo polymerase chain reaction technique for detection of bovine abortion, diarrhea, and respiratory disease complex infectious agents in potential vectors and reservoirs

Bovine abortion, diarrhea, and respiratory disease complexes, caused by infectious agents, result in high and significant economic losses for the cattle industry. These pathogens are likely transmitted by various vectors and reservoirs including insects, birds, and rodents. However, experimental data supporting this possibility are scarce. We collected 117 samples and screened them for 44 bovine abortive, diarrheal, and respiratory disease complex pathogens by using Dembo polymerase chain reaction (PCR), which is based on TaqMan real-time PCR. Fifty-seven samples were positive for at least one pathogen, including bovine viral diarrhea virus, bovine enterovirus, Salmonella enterica ser. Dublin, Salmonella enterica ser. Typhimurium, and Neospora caninum; some samples were positive for multiple pathogens. Bovine viral diarrhea virus and bovine enterovirus were the most frequently detected pathogens, especially in flies, suggesting an important role of flies in the transmission of these viruses. Additionally, we detected the N. caninum genome from a cockroach sample for the first time. Our data suggest that insects (particularly flies), birds, and rodents are potential vectors and reservoirs of abortion, diarrhea, and respiratory infectious agents, and that they may transmit more than one pathogen at the same time.

Stochastic modelling of the effects of human-mobility restriction and viral infection characteristics on the spread of COVID-19

After several weeks of "lockdown" as the sole answer to the COVID-19 pandemic, many countries are restarting their economic and social activities. However, balancing the re-opening of society against the implementation of non-pharmaceutical measures needed for minimizing interpersonal contacts requires a careful assessment of the risks of infection as a function of the confinement relaxation strategies. Here, we present a stochastic coarse grained model that examines this problem. In our model, people are allowed to move between discrete positions on a one-dimensional grid with viral infection possible when two people are collocated at the same site. Our model features three sets of adjustable parameters, which characterize (i) viral transmission, (ii) viral detection, and (iii) degree of personal mobility, and as such, it is able to provide a qualitative assessment of the potential for second-wave infection outbreaks based on the timing, extent, and pattern of the lockdown relaxation strategy. In line with general expectations, our model predicts that a full lockdown yields the best results, namely, the lowest number of total infections. A less anticipated result was that when personal mobility is increased beyond a critical level, the risk of infection rapidly reaches a constant value, which depends solely on the population density. Furthermore, according to our model, confinement alone is not effective if it is not accompanied by a detection capacity (coupled with quarantine) that surpasses 40% of the patients during their symptomatic phase. The results of our simulation also showed that keeping the virus transmission probability to less than 0.4, which can be achieved in real life by respecting social distancing or wearing masks, is as effective as imposing a mild lockdown. Finally, we note that detection and quarantine of pre-symptomatic patients, even with a probability as low as 0.2, would reduce the final numbers of infections by a factor of ten or more. Availabilityhttp://domserv.lab.tuat.ac.jp/COVID19.html (under preparation)