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The basic reproduction number of an infectious agent is the average number of infections one case can generate over the course of the infectious period, in a naïve, uninfected population. It is well-known that the estimation of this number may vary due to several methodological issues, including different assumptions and choice of parameters, utilized models, used datasets and estimation period. With the spreading of the novel coronavirus (2019-nCoV) infection, the reproduction number has been found to vary, reflecting the dynamics of transmission of the coronavirus outbreak as well as the case reporting rate. Due to significant variations in the control strategies, which have been changing over time, and thanks to the introduction of detection technologies that have been rapidly improved, enabling to shorten the time from infection/symptoms onset to diagnosis, leading to faster confirmation of the new coronavirus cases, our previous estimations on the transmission risk of the 2019-nCoV need to be revised. By using time-dependent contact and diagnose rates, we refit our previously proposed dynamics transmission model to the data available until January 29th , 2020 and re-estimated the effective daily reproduction ratio that better quantifies the evolution of the interventions. We estimated when the effective daily reproduction ratio has fallen below 1 and when the epidemics will peak. Our updated findings suggest that the best measure is persistent and strict self-isolation. The epidemics will continue to grow, and can peak soon with the peak time depending highly on the public health interventions practically implemented.
An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov)-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Diarrhea outbreaks in pig farms have raised major concerns in Europe and USA, as they can lead to dramatic pig losses. During a suspected outbreak in Belgium of porcine epidemic diarrhea virus (PEDV), we performed viral metagenomics to assess other potential viral pathogens. Although PEDV was detected, its low abundance indicated that other viruses were involved in the outbreak. Interestingly, a porcine bocavirus and several enteroviruses were most abundant in the sample. We also observed the presence of a porcine enterovirus genome with a gene insertion, resembling a C28 peptidase gene found in toroviruses, which was confirmed using re-sequencing, bioinformatics, and proteomics approaches. Moreover, the predicted cleavage sites for the insertion suggest that this gene was being expressed as a single protein, rather than a fused protein. Recombination in enteroviruses has been reported as a major mechanism to generate genetic diversity, but gene insertions across viral families are rather uncommon. Although such inter-family recombinations are rare, our finding suggests that these events may significantly contribute to viral evolution.
Identification of an enterovirus recombinant with a torovirus-like gene insertion during a diarrhea outbreak in fattening pigs

We propose a compartmental disease transmission model with an asymptomatic (or subclinical) infective class to study the role of asymptomatic infection in the transmission dynamics of infectious diseases with asymptomatic infectives, e.g., influenza. Analytical results are obtained using the respective ratios of susceptible, exposed (incubating), and asymptomatic classes to the clinical symptomatic infective class. Conditions are given for bistability of equilibria to occur, where trajectories with distinct initial values could result in either a major outbreak where the disease spreads to the whole population or a lesser outbreak where some members of the population remain uninfected. This dynamic behavior did not arise in a SARS model without asymptomatic infective class studied by Hsu and Hsieh (SIAM J. Appl. Math. 66(2), 2006). Hence, this illustrates that depending on the initial states, control of a disease outbreak with asymptomatic infections may involve more than simply reducing the reproduction number. Moreover, the presence of asymptomatic infections could result in either a positive or negative impact on the outbreak, depending on different sets of conditions on the parameters, as illustrated with numerical simulations. Biological interpretations of the analytical and numerical results are also given.

On the Role of Asymptomatic Infection in Transmission Dynamics of Infectious Diseases