Animal experiments have shown that non-human primates, cats, ferrets, hamsters, rabbits and bats can be infected by SARS-CoV-2. In addition, SARS-CoV-2 RNA has been detected in felids, mink and dogs in the field. Here, we describe an in-depth investigation using whole genome sequencing of outbreaks on 16 mink farms and the humans living or working on these farms. We conclude that the virus was initially introduced from humans and has since evolved, most likely reflecting widespread circulation among mink in the beginning of the infection period several weeks prior to detection. Despite enhanced biosecurity, early warning surveillance and immediate culling of infected farms, transmission occurred between mink farms in three big transmission clusters with unknown modes of transmission. Sixty-eight percent (68%) of the tested mink farm residents, employees and/or contacts had evidence of SARS-CoV-2 infection. Where whole genomes were available, these persons were infected with strains with an animal sequence signature, providing evidence of animal to human transmission of SARS-CoV-2 within mink farms.

An epidemic of high-pathogenicity avian influenza (HPAI) A virus subtype H7N7 occurred in The Netherlands in 2003 that affected 255 flocks and led to the culling of 30 million birds. To evaluate the effectiveness of the control measures, we quantified between-flock transmission characteristics of the virus in 2 affected areas, using the reproduction ratio Rh. The control measures markedly reduced the transmission of HPAI virus: Rh before detection of the outbreak in the first infected flock was 6.5 (95% confidence interval [CI], 3.1-9.9) in one area and 3.1 in another area, and it decreased to 1.2 (95% CI, 0.6-1.9) after detection of the first outbreak in both areas. The observation that Rh remained >1 suggests that the containment of the epidemic was probably due to the reduction in the number of susceptible flocks by complete depopulation of the infected areas rather than to the reduction of the transmission by the other control measures.

No abstract

Early detection and control curtail outbreaks.

Knowledge on the transmission tree of an epidemic can provide valuable insights into disease dynamics. The transmission tree can be reconstructed by analysing either detailed epidemiological data (e.g. contact tracing) or, if sufficient genetic diversity accumulates over the course of the epidemic, genetic data of the pathogen. We present a likelihood-based framework to integrate these two data types, estimating probabilities of infection by taking weighted averages over the set of possible transmission trees. We test the approach by applying it to temporal, geographical and genetic data on the 241 poultry farms infected in an epidemic of avian influenza A (H7N7) in The Netherlands in 2003. We show that the combined approach estimates the transmission tree with higher correctness and resolution than analyses based on genetic or epidemiological data alone. Furthermore, the estimated tree reveals the relative infectiousness of farms of different types and sizes.

African swine fever (ASF) entered Georgia in 2007 and the EU in 2014. In the EU, the virus primarily spread in wild boar (Sus scrofa) in the period from 2014-2018. However, from the summer 2018, numerous domestic pig farms in Romania were affected by ASF. In contrast to the existing knowledge on ASF transmission routes, the understanding of risk factors and the importance of different transmission routes is still limited. In the period from May to September 2019, 655 Romanian pig farms were included in a matched case-control study investigating possible risk factors for ASF incursion in commercial and backyard pig farms. The results showed that close proximity to outbreaks in domestic farms was a risk factor in commercial as well as backyard farms. Furthermore, in backyard farms, herd size, wild boar abundance around the farm, number of domestic outbreaks within 2 km around farms, short distance to wild boar cases and visits of professionals working on farms were statistically significant risk factors. Additionally, growing crops around the farm, which could potentially attract wild boar, and feeding forage from ASF affected areas to the pigs were risk factors for ASF incursion in backyard farms. In 2007, African swine fever (ASF) spread from the African continent, where the disease is endemic, into Georgia then on through Eastern Europe, reaching the European Union in 2014. During the first years of the epidemic in the EU (2014-early 2017), the disease mainly affected wild boar, with sporadic spill-over to domestic pigs 1. In 2017, ASF spread to Romania, initially resulting in a small number of outbreaks in domestic pig farms in the county of Satu Mare, which neighbours Hungary and Ukraine. In July 2018, ASF occurred in two counties neighbouring Satu Mare, but also in five counties around the Danube delta close to the Black Sea in the South East part of Romania. In July 2018, 334 outbreaks were detected, mostly in domestic farms, predominantly in the South East. From then on, ASF spread widely in Romania with outbreaks in more than 1,000 domestic pig farms in 2018 and about 2,500 in 2019 (Animal Disease Notification System of the European Commission (ADNS)).

This present study is the first to quantify the transmission of avian influenza virus H5N1 within flocks during the 2004 epidemic in Thailand. It uses the flock-level mortality data to estimate the transmission-rate parameter ( beta ) and the basic reproduction number (R(0)). The point estimates of beta varied from 2.26/day (95% confidence interval [CI], 2.01-2.55) for a 1-day infectious period to 0.66/day (95% CI, 0.50-0.87) for a 4-day infectious period, whereas the accompanying R(0) varied from 2.26 (95% CI, 2.01-2.55) to 2.64 (95% CI, 2.02-3.47). Although the point estimates of beta of backyard chickens and fighting cocks raised together were lower than those of laying hens and broiler chickens, this difference was not statistically significant. These results will enable us to assess the control measures in simulation studies. They also indicate that, for the elimination of the virus, a critical proportion of the susceptible poultry population in a flock (i.e., 80% of the population) needs to be vaccinated.

This study was conducted to investigate space and time clusters of highly pathogenic avian influenza A (H5N1) virus infection and to determine risk factors at the subdistrict level in Thailand. Highly pathogenic avian influenza A (H5N1) was diagnosed in 1890 poultry flocks located in 953 subdistricts during 2004-2007. The ecologic risk for H5N1 virus infection was assessed on the basis of a spatial-based case-control study involving 824 case subdistricts and 3296 control subdistricts from 6 study periods. Risk factors investigated in clustered areas of H5N1 included human and animal demographic characteristics, poultry production systems, and wild birds and their habitats. Six variables remained statistically significant in the final model: flock density of backyard chickens (odds ratio [OR], 0.98), flock density of fighting cocks (OR, 1.02), low and high human density (OR, 0.60), presence of quail flocks (OR, 1.21), free-grazing duck flocks (OR, 2.17), and a poultry slaughterhouse (OR, 1.33). We observed a strong association between subdistricts with H5N1 virus-infected poultry flocks and evidence of prior and concomitant H5N1 infection in wild birds in the same subdistrict.