Peste des petits ruminants in China: Spatial risk analysis

Spatial risk of Haemaphysalis longicornis borne Dabieshan tick virus (DBTV) in China

The uncertainty and unknowability of emerging infectious diseases have caused many major public health and security incidents in recent years. As a new tick-borne disease, Dabieshan tick virus (DBTV) necessitate systematic epidemiological and spatial distribution analysis. In this study, tick samples from Liaoning Province were collected and used to evaluate distribution of DBTV in ticks. Outbreak points of DBTV and the records of the vector Haemaphysalis longicornis in China were collected and used to establish a prediction model using niche model combined with environmental factors. We found that H. longicornis and DBTV were widely distributed in Liaoning Province. The risk analysis results showed that the DBTV in the eastern provinces of China has a high risk, and the risk is greatly influenced by elevation, land cover, and meteorological factors. The risk geographical area predicted by the model is significantly larger than the detected positive areas, indicating that the etiological survey is seriously insufficient. This study provided molecular and important epidemiological evidence for etiological ecology of DBTV. The predicted high-risk areas indicated the insufficient monitoring and risk evaluation and the necessity of future monitoring and control work.

Simulating the Spread of Peste des Petits Ruminants in Kazakhstan Using the North American Animal Disease Spread Model

In this study, we simulated the potential spread of Peste des Petits Ruminants (PPR) between small ruminant (SR) farms in the Republic of Kazakhstan (RK) in case of the disease’s introduction into the country. The simulation was based on actual data on the location and population of SR farms in the RK using the North American Animal Disease Spread Model (NAADSM). The NAADSM employs the stochastic simulations of the between-farm disease spread predicated on the SIR compartmental epidemic model. The most important epidemiological indicators of PPR, demography of SR farms, and livestock management characteristics in the RK were used for model parameterization. This article considers several scenarios for the initial introduction of PPR into the territory of Kazakhstan, based on previously identified high-risk regions and varying sizes of initially infected farms. It is demonstrated that the duration and size of the outbreak do not depend on the size of initially infected farms but rather depend on the livestock concentration and number of farms in the affected area. This implies that the outbreak may affect the largest number of farms in the case of introduction of the disease into farms in southern Kazakhstan. However, even in the most unfavorable scenario, the total number of affected farms does not exceed 2.4% of all SR farms in the RK. The size of the affected area is, in most cases, no larger than an averaged 2-level administrative division’s size, which suggests the scale of a local epidemic. The chosen model provides ample opportunity to study the impact of different control and prevention measures on the spread of PPR as well as to assess the potential economic damage.

Urbanization and Habitat Characteristics Associated with the Occurrence of Peste des Petits Ruminants in Africa

As a highly contagious viral disease, peste des petits ruminants (PPR) can cause severe socio-economic impacts in developing countries due to its threat to sheep and goat production. Previous studies have identified several risk factors for PPR at the individual or herd level. However, only a few studies explored the impacts of landscape factors on PPR risk, particularly at a regional scale. Moreover, risk factor analyses in Africa usually focused on sub-Saharan Africa while neglecting northern Africa. Based on regional occurrence data during 2006–2018, we here explored and compared the risk factors, with a focus on factors related to ruminant habitats, for the occurrence of PPR in sub-Saharan and northern Africa. Our results demonstrated different risk factors in the two regions. Specifically, habitat fragmentation was negatively correlated with PPR occurrence in sub-Saharan Africa, while positively correlated with PPR occurrence in northern Africa. Moreover, urbanization showed a positive association with PPR occurrence in sub-Saharan Africa. Our study is among the first, to our knowledge, to compare the risk factors for PPR in sub-Saharan and northern Africa and contributes to a better understanding of the effects of habitat characteristics on PPR occurrence at a regional scale.

Research Progress on Emerging Viral Pathogens of Small Ruminants in China during the Last Decade

China is the country with the largest number of domestic small ruminants in the world. Recently, the intensive and large-scale sheep/goat raising industry has developed rapidly, especially in nonpastoral regions. Frequent trading, allocation, and transportation result in the introduction and prevalence of new pathogens. Several new viral pathogens (peste des petits ruminants virus, caprine parainfluenza virus type 3, border disease virus, enzootic nasal tumor virus, caprine herpesvirus 1, enterovirus) have been circulating and identified in China, which has attracted extensive attention from both farmers and researchers. During the last decade, studies examining the etiology, epidemiology, pathogenesis, diagnostic methods, and vaccines for these emerging viruses have been conducted. In this review, we focus on the latest findings and research progress related to these newly identified viral pathogens in China, discuss the current situation and problems, and propose research directions and prevention strategies for different diseases in the future. Our aim is to provide comprehensive and valuable information for the prevention and control of these emerging viruses and highlight the importance of surveillance of emerging or re-emerging viruses.

Spatio-temporal cluster analysis and transmission drivers for Peste des Petits Ruminants in Uganda

Peste des Petits Ruminants (PPR) is a transboundary, highly contagious, and fatal disease of small ruminants. PPR causes global annual economic losses of between USD 1.5-2.0 billion across more than 70 affected countries. Despite the commercial availability of effective PPR vaccines, lack of financial and technical commitment to PPR control coupled with a dearth of refined PPR risk profiling data in different endemic countries has perpetuated PPR virus transmission. In Uganda, over the past five years, PPR has extended from north-eastern Uganda (Karamoja) with sporadic incursions in other districts /regions. To identify disease cluster hotspot trends that would facilitate the design and implementation of PPR risk-based control methods (including vaccination), we employed the space-time cube approach to identify trends in the clustering of outbreaks in neighbouring space-time cells using confirmed PPR outbreak report data (2007-2020). We also used negative binomial and logistic regression models and identified high small ruminant density, extended road length, low annual precipitation and high soil water index as the most important drivers of PPR in Uganda. The study identified (with 90 - 99% confidence) five PPR disease hotspot trend categories across subregions of Uganda. Diminishing hotspots were identified in the Karamoja region whereas consecutive, sporadic, new, and emerging hotspots were identified in central and southwestern districts of Uganda. Inter-district and cross-border small ruminant movement facilitated by longer road stretches and animal comingling precipitate PPR outbreaks as well as PPR virus spread from its initial Karamoja focus to the central and south-western Uganda. There is therefore urgent need to prioritize considerable vaccination coverage to obtain the required herd immunity among small ruminants in the new hotspot areas to block transmission to further emerging hotspots. Findings of this study provide a basis for more robust timing and prioritization of control measures including vaccination. This article is protected by copyright. All rights reserved.

Spatiotemporal characteristics analysis and potential distribution prediction of peste des petits ruminants (PPR) in China from 2007-2018

Peste des petits ruminants (PPR) is a highly infectious disease that mainly infects small ruminants. To date, PPR has been confirmed in more than 70 countries. In China, PPR has occurred in more than 20 provinces and cities. In this study, based on geographic information system (GIS), spatial analysis was used to examine the occurrence of PPR in China from 2007 to 2018. The results showed that PPR first occurred in Tibet and gradually spread to other provinces. The outbreaks of PPR were concentrated in 2014, 2015 and 2018. Combining climate factors with the maximum entropy (MaxEnt), the results also suggested that the potential risk areas of PPR outbreaks in China were mainly Jiangsu, Yunnan and Anhui in Southeast China. Finally, a phylogenetic tree was used to analyse the evolutionary relationship between the peste des petits ruminants virus (PPRV) in China and the global ones, and it was found that the one in China had a close genetic relationship with the one in Mongolia, India and Bangladesh. Understanding and forecasting the distribution of PPR in China will help policymakers develop targeted monitoring plans. Likewise, analysing the global PPRV epidemic trends will play an important role in the elimination and prevention of PPR.

Pheno- and genotypic characterization and identification of novel subtypes of Peste des Petits Ruminants virus in domestic and captive wild goats in Northern Iraq

Background

Peste des Petits Ruminants (PPR) is an acute or peracute contagious transboundary viral disease that mainly affects caprine and ovine and causes significant economic impact in developing countries. After two PPR virus outbreaks in 2011 and 2014, an investigation, from August 2015 to September 2016, was carried out in Northern Iraq when an increased morbidity and mortality rates were reported in the domestic and captive wild goats. In the present study, ten domestic goat farms and seven captive wild goat herds located in seven geographical areas of Northern Iraq were clinically, pathologically, serologically and genotypically characterized to determine the prevalence and potential cause of PPR virus outbreak.

Results

The outbreak occurred with rate of morbidity (26.1%) and mortality (11.1%) in domestic goat farms as compared to captive wild goat herds where relatively high mortality (42.9%) and low morbidity (10.9%) rates were recorded. Based on the clinical symptoms (mucopurulent nasal discharges, ulceration and erosion of oral mucosa, profuse watery diarrhea) and necropsy (hemorrhage and congestion on mucous membranes of the colon and rectum with zebra stripes lesions) results, overall, the serological test findings revealed a high frequency (47.9%) of positive samples for anti-PPRV nucleoprotein antibodies. Furthermore, the nucleoprotein (N) gene was detected in 63.2 and 89.1% of samples using conventional and reverse transcription real-time quantitative PCR assays. A phylogenetic analysis of N gene amino acid sequences clustered with the reference strain revealed lineage IV similar to the strains isolated in 2011 and 2014, respectively. However, two sub-types of lineage IV (I and II), significantly distinct from the previous strains, were also observed.

Conclusion

The phylogenetic analysis suggests that movements of goats are possible cause and one of the important factors responsible for the spread of virus across the region. The study results would help in improving farm management practices by establishing a PPR virus eradication program using regular monitoring and vaccination program to control and mitigate the risk of re-emergence of PPR virus infection in domestic and captive wild goats in Iraq.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02372-2.

1. Assessment and detection of source of re-emergence of Peste des Petits Ruminants virus in goats.

2. High rate of mortality than morbidity in domestic and captive wild goat herds.

3. Identification of novel sub-types (I&II) of lineage IV.

4. Regular monitoring and strategies for improving on-site control and trade regulations enables mitigating risk of outbreaks.

Analysis and Sequence Alignment of Peste des Petits Ruminants Virus ChinaSX2020

The peste des petits ruminants virus (PPRV) mainly infects goats and sheep and causes a highly contagious disease, PPR. Recently, a PPRV strain named ChinaSX2020 was isolated and confirmed following an indirect immunofluorescence assay and PCR using PPRV-specific antibody and primers, respectively. A sequencing of the ChinaSX2020 strain showed a genome length of 15,954 nucleotides. A phylogenetic tree analysis showed that the ChinaSX2020 genome was classified into lineage IV of the PRRV genotypes. The genome of the ChinaSX2020 strain was found to be closely related to PPRVs isolated in China between 2013 and 2014. These findings revealed that not a variety of PRRVs but similar PPRVs were continuously spreading and causing sporadic outbreaks in China.

A predictive analysis on the risk of peste des petits ruminants in livestock in the Trans-Himalayan region and validation of its transboundary transmission paths

Although the Trans-Himalayan region (THR) is an important endemic and rendezvous area of peste des petits ruminants (PPR), monitoring and prevention measurements are difficult to execute because of the rough geographical conditions. Besides, a heterogeneous breeding system and the poor veterinary service of susceptible animals compound the existing problems. Here, we propose a forecasting system to define the key points of PPR prevention and aid the countries in saving time, labor, and products to achieve the goal of the global eradication project of PPR. The spatial distribution of PPR was predicted in the THR for the first time using a niche model that was constructed with a combination of eco-geographical, anthropoid, meteorological, and host variables. The transboundary least-cost paths (LCPs) of small ruminants in the THR were also calculated. Our results reveal that the low-elevation area of the THR had a higher PPR risk and was mainly dominated by human variables. The high-elevation area had lower risk and was mainly dominated by natural variables. Eight LCPs representing corridors among India, Nepal, Bhutan, Bangladesh, and China were obtained. This confirmed the potential risk of transboundary communication by relying on PPR contamination on the grasslands for the first time. The predicted potential risk communication between the two livestock systems and landscapes (high and low elevation) might play a role in driving PPR transboundary transmission.

Mapping the risks of the spread of peste des petits ruminants in the Republic of Kazakhstan

Peste des petits ruminants (PPR) is a viral transboundary disease seen in small ruminants, that causes significant damage to agriculture. This disease has not been previously registered in the Republic of Kazakhstan (RK). This paper presents an assessment of the susceptibility of the RK's territory to the spread of the disease in the event of its importation from infected countries. The negative binomial regression model that was trained on the PPR outbreaks in China, was used to rank municipal districts in the RK in terms of PPR spread risk. The outbreak count per administrative district was used as a risk indicator, while a number of socio-economic, landscape, and climatic factors were considered as explanatory variables. Summary road length, altitude, the density of small ruminants, the maximum green vegetation fraction, cattle density, and the Engel coefficient were the most significant factors. The model demonstrated a good performance in training data (R²  = 0.69), and was transferred to the RK, suggesting a significantly lower susceptibility of this country to the spread of PPR. Hot spot analysis identified three clusters of districts at the highest risk, located in the western, eastern, and southern parts of Kazakhstan. As part of the study, a countrywide survey was conducted to collect data on the distribution of livestock populations, which resulted in the compilation of a complete geo-database of small ruminant holdings in the RK. The research results may be used to formulate a national strategy for preventing the importation and spread of PPR in Kazakhstan through targeted monitoring in high-risk areas.

Transboundary Animal Diseases, an Overview of 17 Diseases with Potential for Global Spread and Serious Consequences

Animals provide food and other critical resources to most of the global population. As such, diseases of animals can cause dire consequences, especially disease with high rates of morbidity or mortality. Transboundary animal diseases (TADs) are highly contagious or transmissible, epidemic diseases, with the potential to spread rapidly across the globe and the potential to cause substantial socioeconomic and public health consequences. Transboundary animal diseases can threaten the global food supply, reduce the availability of non-food animal products, or cause the loss of human productivity or life. Further, TADs result in socioeconomic consequences from costs of control or preventative measures, and from trade restrictions. A greater understanding of the transmission, spread, and pathogenesis of these diseases is required. Further work is also needed to improve the efficacy and cost of both diagnostics and vaccines. This review aims to give a broad overview of 17 TADs, providing researchers and veterinarians with a current, succinct resource of salient details regarding these significant diseases. For each disease, we provide a synopsis of the disease and its status, species and geographic areas affected, a summary of in vitro or in vivo research models, and when available, information regarding prevention or treatment.

Prediction for Global Peste des Petits Ruminants Outbreaks Based on a Combination of Random Forest Algorithms and Meteorological Data

Peste des Petits Ruminants (PPR) is an acute and highly contagious transboundary disease caused by the PPR virus (PPRV). The virus infects goats, sheep and some wild relatives of small domestic ruminants, such as antelopes. PPR is listed by the World Organization for Animal Health as an animal disease that must be reported promptly. In this paper, PPR outbreak data combined with WorldClim database meteorological data were used to build a PPR prediction model. Using feature selection methods, eight sets of features were selected: bio3, bio10, bio15, bio18, prec7, prec8, prec12, and alt for modeling. Then different machine learning algorithms were used to build models, among which the random forest (RF) algorithm was found to have the best modeling effect. The ACC value of prediction accuracy for the model on the training set can reach 99.10%, while the ACC on the test sets was 99.10%. Therefore, RF algorithms and eight features were finally selected to build the model in order to build the online prediction system. In addition, we adopt single-factor modeling and correlation analysis of modeling variables to explore the impact of each variable on modeling results. It was found that bio18 (the warmest quarterly precipitation), prec7 (the precipitation in July), and prec8 (the precipitation in August) contributed significantly to the model, and the outbreak of the epidemic may have an important relationship with precipitation. Eventually, we used the final qualitative prediction model to establish a global online prediction system for the PPR epidemic.

The potential distribution and dynamics of important vectors Culex pipiens pallens and Culex pipiens quinquefasciatus in China under climate change scenarios: an ecological niche modelling approach

BACKGROUND

Intense studies have been carried out on the effects of climate change on vector-borne diseases and vectors. Culex pipiens pallens and Culex pipiens quinquefasciatus are two medically concerned mosquito species in temperate and tropical areas, which serve as important disease-transmitting pests of a variety of diseases. The ongoing geographical expansion of these mosquitoes has brought an increasing threat to public health.

RESULTS

Based on mosquito occurrence records and high-resolution environmental layers, an ecological niche model was established to model their current and future potential distribution in China. Our model showed that the current suitable area for Cx. p. pallens is distributed in the central, eastern and northern parts of China, while Cx. p. quinquefasciatus is distributed in vast areas in southern China. Under future climate change scenarios, both species are predicted to expand their range to varying degrees and RCP 8.5 provides the largest expansion. Northward core shifts will occur in ranges of both species. Environmental variables which have significant impact on the distribution of mosquitoes were also revealed by our model.

CONCLUSION

Severe habitat expansion of vectors is likely to occur in the future 21st century. Our models mapped the high-risk areas and risk factors which needs to be paid attention. The results of our study can be referenced in further ecological surveys and will guide the development of strategies for the prevention and control of vector-borne diseases. © 2020 Society of Chemical Industry.

Risk assessment for the Rift Valley fever occurrence in China: Special concern in south-west border areas

Rift Valley fever (RVF) is a mosquito-borne zoonotic disease. Since its first outbreak in 1930, RVF epidemics have caused huge economic losses and public health impacts in Africa. In 2000, RVF became a disease of global concern as it spread to the Arabian Peninsula. In our study, a Geographic Information System-based risk assessment for the occurrence of Rift Valley fever in China was established by means of ecological niche modelling. Based on occurrence records (RVF records from FAO EMPRES-i, vector records from literatures and GBIF) and high-resolution environmental layers, the prediction maps of RVF occurrence probability and distribution of five potential RVF vectors in China were modelled using Maxent. An internal validation was adopted for model verification, and high AUC values were obtained (0.918 for RVF and 0.837-0.992 for vectors). By overlaying the RVF prediction map with the combined RVF vector prediction map using Fuzzy overlay tool ('AND' operator) of ArcMap 10.2, we got the first risk map of possible RVF vector transmission. This map was further overlaid with the latest livestock distribution map ('AND' operator) to generate the second risk map of possible RVF threat to domestic livestock. The south-west border provinces in China, Yunnan, Guangxi and Tibet were predicted to have a high possibility of RVF occurrence. Conditions conducive to the local amplification of RVF also exist in these areas. Temperature seasonality, mean temperature of dry season and precipitation of the driest month were considered as key environmental variables for RVF, and common environmental conditions were found conductive for vectors. It is suggested to establish proper surveillance systems in south-west border areas to minimize the possibility of RVF invasion. Our findings can serve as a valuable reference for prevention measures to be implemented.