Mycobacterium avium subspecies paratuberculosis (MAP) causes chronic, wasting, and progressive enteritis in cattle, bringing significant economic losses in livestock industries. MAP has spread worldwide mainly due to movement of animals. The objective of this study was to determine the MAP seroprevalence in cattle in the Xinjiang Uygur Autonomous Region, Northwest China, and evaluate the difference between intensive farming herds (cattle number in a herd is more than 200, and the cattle cannot have access to pasture) and free-range herds (the cattle are bred by individual households, a herd is defined as the cattle are bred in a village or town in this study). A total of 3157 serum specimens were collected from 42 herds in nine different regions. This included 1481 specimens from 18 intensive farming herds in four regions and 1676 specimens from 24 free-range herds in six regions. Antibody against MAP was tested with commercial ELISA test kits. The results showed that the overall apparent prevalence was 4.8% (95% CI, 4.1 to 5.6%) at animal level, and 50.0% (21/42) at herd level. The apparent prevalence in intensive farming herds and free-range herds were 9.5% (141/1481) and 0.7% (11/1676) at the animal-level, 88.9%(16/18) and 20.8% (5/24) at herd level, respectively, with a significant statistical difference between these two farming modes (p < 0.01). Cattle in intensive farming herds had a relatively higher risk to be infected with MAP than those in free-range herds (RR = 14.4). This study demonstrates that apparent prevalence of MAP infection in dairy cattle differs with farming modes at the animal level and herd level, and farming density could be an important risk factor associated with the presence of MAP infected cattle. This study provides important epidemiological data for bovine MAP control in Xinjiang, Northwest China.

Hepatitis E virus (HEV) causes infections in humans and a wide range of animal hosts. Wild boar is an important natural reservoir of HEV genotypes 3–6 (HEV-3–HEV-6), but comparative analysis of HEV infections in both feral and farmed wild boars remains limited. In this study, samples from 599 wild boars were collected during 2017–2020, including 121 feral wild boars (collected 121 fecal, 121 serum, and 89 liver samples) and 478 farmed wild boars (collected 478 fecal and 478 serum samples). The presence of anti-HEV IgG antibodies were detected by the HEV-IgG enzyme-linked immunosorbent assay (ELISA) kit. HEV RNA was detected by reverse transcription polymerase chain reaction (RT-PCR), targeting the partial ORF1 genes from fecal and liver samples, and the obtained genes were further genotyped by phylogenetic analysis. The results showed that 76.2% (95% CI 72.1–79.9) of farmed wild boars tested anti-HEV IgG seropositive, higher than that in feral wild boars (42.1%, 95% CI 33.2–51.5, p < 0.001). HEV seropositivity increased with age. Wild boar HEV infection presented a significant geographical difference (p < 0.001), but not between sex (p = 0.656) and age (p = 0.347). HEV RNA in fecal samples was detected in 13 (2.2%, 95% CI 1.2–3.7) out of 599 wild boars: 0.8% (95% CI 0.0–4.5, 1/121) of feral wild boars and 2.5% (95% CI 1.3–4.3, 12/478) of farmed wild boars. Phylogenetic analysis showed that all these viruses belonged to genotype HEV-4, and further grouped into sub-genotypes HEV-4a, HEV-4d, and HEV-4h, of which HEV-4a was first discovered in the wild boar populations in China. Our results suggested that farms could be a setting for amplification of HEV. The risk of HEV zoonotic transmission via rearing and consumption of farmed wild boars should be further assessed.

Hepatitis E virus (HEV) causes infections in humans and animals. HEV have been identified in pig farms, markets and swine workers, but studies with parallel observations along the poultry and pork supply chains remains limited. This study aimed to characterize HEV infection risks in workers along the meat supply chain. Two rounds of cross-sectional surveys were performed among swine and poultry workers in pig and poultry farms, slaughterhouses, wholesale and retail live poultry markets, live pig markets and pork markets. Human sera from the workers and the general population were collected and tested for HEV specific IgM/IgG antibodies by commercial indirect-ELISA test kits. Risk factors of HEV seropositivity associated with different occupational settings were identified using logistic regression. 47.0% (156/332) of the swine workers and 40.2% (119/296) of the poultry workers were seropositive, compared to 26.1% (35/134) in the general population. Multivariable analysis showed that human HEV infection risk increased along the pork supply chain, with the highest risk at pig slaughterhouses (adjusted OR = 3.19, 95% CI = 1.49–6.88) and pork markets (adjusted OR = 2.02, 95% CI = 1.04–3.97), but no significant higher risk was observed among poultry workers. Swine occupational exposure is associated with HEV infection, especially in workers in pig slaughterhouses and pork markets. Strengthening control measures in these settings is important for HEV control and long term HEV elimination.

The record-breaking number of dengue cases reported in Guangdong, China in 2014 has been topic for many studies. However, the spatial and temporal characteristics of this unexpectedly explosive outbreak are still poorly understood. We adopt an integrated approach to ascertain the spatial-temporal progression of the outbreak in each city in Guangdong as well as in each district in Guangzhou, where the majority of cases occurred. We utilize the Richards model, which determines the waves of reported cases at each location and identifies the turning point for each wave, in combination with a spatial association analysis conducted by computing the standardized G* statistic that measures the degree of spatial autocorrelation of a set of geo-referenced data from a local perspective. We found that Yuexiu district in Guangzhou was the initial hot spot for the outbreak, subsequently spreading to its neighboring districts in Guangzhou and other cities in Guangdong province. Hospital isolation of cases during early stage of outbreak in neighboring Zhongshan (in effort to prevent disease transmission to the vectors) might have played an important role in the timely mitigation of the disease. Integration of modeling approach and spatial association analysis allows us to pinpoint waves that spread the disease to communities beyond the borders of the initially affected regions.

Wenzhou mammarenavirus (WENV) is a zoonotic pathogen newly discovered in east and southeast Asia. WENV has been found in wild rodent animals around the world while its standing is barely understood in Guangzhou city, where is known as a region of outbreak hotspot for zoonotic emerging infectious diseases. To investigate the prevalence and genomic characteristics of mammarenavirus in Guangzhou City, lung tissue samples from wild rodent species were collected from five districts of Guangzhou City in the year 2015 and 2016. The viral RNA was extracted and then subjected to mammarenavirus-specific PCR. The result revealed approximately 1.0% (3/306) nucleic acid positivity for lung tissue samples obtained from three rodent species: Mus musculus, Rattus flavipectus, and Rattus norvegicus. Viral metagenomic sequencing of three samples was then carried out and two full segment L and three full segment S sequences were obtained. Phylogenetics analysis indicated the sequences of the new mammarenavirus strain have 76.2% - 94.4% similarity to known WENV encoded genes, with the highest similarity to the WENV 9–24 strain. Population structure analysis grouped all known WENV into seven lineages, and this WENV Guangzhou strain was grouped with WENV 9–24 as well. Though the seroprevalence result was not available, our data provides the first nucleic acid evidence of circulating WENV in Guangzhou city, and it suggested WENV had a broader host tropism than previously known.