Efficient Direct and Limited Environmental Transmission of SARS-CoV-2 Lineage B.1.22 in Domestic Cats

The susceptibility of domestic cats to infection with SARS-CoV-2 has been demonstrated by several experimental studies and field observations. We performed an extensive study to further characterize the transmission of SARS-CoV-2 between cats, through both direct and indirect contact. To that end, we estimated the transmission rate parameter and the decay parameter for infectivity in the environment. Using four groups of pair-transmission experiment, all donor (inoculated) cats became infected, shed virus, and seroconverted, while three out of four direct contact cats got infected, shed virus, and two of those seroconverted. One out of eight cats exposed to a SARS-CoV-2-contaminated environment became infected but did not seroconvert. Statistical analysis of the transmission data gives a reproduction number R0 of 2.18 (95% CI = 0.92 to 4.08), a transmission rate parameter β of 0.23 day-1 (95% CI = 0.06 to 0.54), and a virus decay rate parameter μ of 2.73 day-1 (95% CI = 0.77 to 15.82). These data indicate that transmission between cats is efficient and can be sustained (R0 > 1), however, the infectiousness of a contaminated environment decays rapidly (mean duration of infectiousness 1/2.73 days). Despite this, infections of cats via exposure to a SARS-CoV-2-contaminated environment cannot be discounted if cats are exposed shortly after contamination. IMPORTANCE This article provides additional insight into the risk of infection that could arise from cats infected with SARS-CoV-2 by using epidemiological models to determine transmission parameters. Considering that transmission parameters are not always provided in the literature describing transmission experiments in animals, we demonstrate that mathematical analysis of experimental data is crucial to estimate the likelihood of transmission. This article is also relevant to animal health professionals and authorities involved in risk assessments for zoonotic spill-overs of SARS-CoV-2. Last but not least, the mathematical models to calculate transmission parameters are applicable to analyze the experimental transmission of other pathogens between animals.

The Context-Dependent Effects of Host Competence, Competition, and Pathogen Transmission Mode on Disease Prevalence

AbstractBiodiversity in communities is changing globally, including the gain and loss of host species in host-pathogen communities. Increased host diversity can cause infection prevalence in a focal host to increase (amplification) or decrease (dilution). However, it is unclear what general rules govern the context-dependent effects, in part because theories for pathogens with different transmission modes have developed largely independently. Using a two-host model, we explore how the pathogen transmission mode and characteristics of a second host (disease competence and competitive ability) influence disease prevalence in a focal host. Our work shows how the theories for pathogens with environmental transmission, density-dependent direct transmission, and frequency-dependent direct transmission can be unified. Our work also identifies general rules about how host and pathogen characteristics affect amplification/dilution. For example, higher-competence hosts promote amplification, unless they are strong interspecific competitors; strong interspecific competitors promote dilution, unless they are large sources of new infections; and dilution occurs under frequency-dependent direct transmission more than density-dependent direct transmission, unless interspecific host competition is sufficiently strong. Our work helps explain how the characteristics of the pathogen and a second host affect disease prevalence in a focal host.

Characterization of bluetongue virus serotype 28

Bluetongue virus (Reoviridae; Orbivirus, BTV), which is usually transmitted by biting midges, affects wild and domestic ruminants worldwide, thereby causing an economically important disease. Recently, a putative new BTV strain was isolated from contaminated vaccine batches. In this study, we investigated the genomic and clinical characteristics of this isolate, provisionally designated BTV-28. Phylogenetic analysis of BTV-28 segment 2 (Seg-2) showed that it is related to Seg-2 from BTV serotypes 4, 10, 11, 17, 20 and 24, sharing 64%-66% identity in nucleotide sequences (nt) and 59%-62% in amino acid (aa) sequences of BTV VP2. BTV-28 Seg-6 is related to the newly reported XJ1407 BTV isolate, sharing 76.70% nt and 90.87% aa sequence identity. Seg-5 was most closely related to a South African BTV-4 strain, and all other segments showed close similarity to BTV-26. Experimental infection by injection of 6-month-old ewes caused clinical signs in all injected animals, lasting from 2 to 3 days to several weeks post-infection, including high body temperature, conjunctivitis, nasal discharge and rhinitis, facial oedema, oral hyperaemia, coronitis, cough, depression and tongue cyanosis. Naïve control animals, placed together with the infected sheep, displayed clinical signs and were positive for viral RNA, but their acute disease phase was shorter than that of BTV-injected ewes. Control animals that were kept in a separated pen did not display any clinical signs and were negative for viral RNA presence throughout the experiment. Seroconversion was observed in the injected and in one of the two contact-infected animals. These findings demonstrate that BTV-28 infection of sheep can result in clinical manifestation, and the clinical signs detected in the contact animals suggest that it might be directly transmitted between the mammalian hosts.

Efficient Data Gathering in 3D Linear Underwater Wireless Sensor Networks Using Sink Mobility

Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability.