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

Influence of Host and Landscape-Associated Factors in the Infection and Transmission of Pathogens: The Case of Directly Transmitted Virus in Mammals

BACKGROUND

Among pathogens associated with mammals, numerous viruses with a direct transmission route impact human, domestic and wild species health. Host and landscape factors affect viral infection and transmission dynamics of these viruses, along with barriers to host dispersal and gene exchange. However, studies show biases toward certain locations, hosts and detected pathogens, with regional variations in similar host-virus associations.

METHODS

Using a systematic review, in two electronic repositories for articles published until December 2022, we analysed the available information on host- and landscape-associated factors influencing the infection and transmission of directly transmitted viruses in mammals.

RESULTS

In the analysis, about 50% of papers examined either host traits, landscape composition or configuration measures, while approximately 24% combined host and landscape-associated factors. Additionally, approximately 17% of the articles included climatic data and 30% integrated factors related to anthropogenic impact, as these variables have a role in host density, distribution and virus persistence. The most significant and frequent host traits used as predictor variables were sex, age, body weight, host density and species identity. Land cover was the most evaluated landscape attribute, while some explored configuration variables like edge density and fragmentation indexes. Finally, temperature, precipitation and features such as human population density and human footprint index were also typically measured and found impactful.

CONCLUSION

Given the many contributions host- and landscape-related factors have in pathogen dynamics, this systematic study contributes to a better knowledge of host-virus dynamics and the identification of variables and gaps that can be used for disease prevention.

PTEN Regulates Myofibroblast Activation in Valvular Interstitial Cells based on Subcellular Localization

Aortic valve stenosis (AVS) is characterized by altered mechanics of the valve leaflets, which disrupts blood flow through the aorta and can cause left ventricle hypotrophy. These changes in the valve tissue result in activation of resident valvular interstitial cells (VICs) into myofibroblasts, which have increased levels of αSMA in their stress fibers. The persistence of VIC myofibroblast activation is a hallmark of AVS. In recent years, the tumor suppressor gene phosphatase and tensin homolog (PTEN) has emerged as an important player in the regulation of fibrosis in various tissues (e.g., lung, skin), which motivated us to investigate PTEN as a potential protective factor against matrix-induced myofibroblast activation in VICs. In aortic valve samples from humans, we found high levels of PTEN in healthy tissue and low levels of PTEN in diseased tissue. Then, using pharmacological inducers to treat VIC cultures, we observed PTEN overexpression prevented stiffness-induced myofibroblast activation, whereas genetic and pharmacological inhibition of PTEN further activated myofibroblasts. We also observed increased nuclear PTEN localization in VICs cultured on stiff matrices, and nuclear PTEN also correlated with smaller nuclei, altered expression of histones and a quiescent fibroblast phenotype. Together, these results suggest that PTEN not only suppresses VIC activation, but functions to promote quiescence, and could serve as a potential pharmacological target for the treatment of AVS.

Unveiling the spatial distribution and transboundary pathways of FMD serotype O in Western China and its bordering countries

Foot-and-mouth disease (FMD) is a severe, highly contagious viral disease of livestock that has a significant economic impact on domestic animals and threatens wildlife survival in China and border countries. However, effective surveillance and prevention of this disease is often incomplete and unattainable due to the cost, the great diversity of wildlife hosts, the changing range and dynamics, and the diversity of FMDV. In this study, we used predictive models to reveal the spread and risk of FMD in anticipation of identifying key nodes to control its spread. For the first time, the spatial distribution of FMD serotype O was predicted in western China and border countries using a niche model, which is a combination of eco-geographic, human, topographic, and vegetation variables. The transboundary least-cost pathways (LCPs) model for ungulates in the study area were also calculated. Our study indicates that FMD serotype O survival is seasonal at low altitudes (March and June) and more sensitive to temperature differences at high altitudes. FMD serotype O risk was higher in Central Asian countries and both were highly correlated with the population variables. Ten LCPs were obtained representing Pakistan, Kazakhstan, Kyrgyzstan, and China.

Assessing eco-geographic influences on COVID-19 transmission: a global analysis

COVID-19 has been massively transmitted for almost 3 years, and its multiple variants have caused serious health problems and an economic crisis. Our goal was to identify the influencing factors that reduce the threshold of disease transmission and to analyze the epidemiological patterns of COVID-19. This study served as an early assessment of the epidemiological characteristics of COVID-19 using the MaxEnt species distribution algorithm using the maximum entropy model. The transmission of COVID-19 was evaluated based on human factors and environmental variables, including climate, terrain and vegetation, along with COVID-19 daily confirmed case location data. The results of the SDM model indicate that population density was the major factor influencing the spread of COVID-19. Altitude, land cover and climatic factor showed low impact. We identified a set of practical, high-resolution, multi-factor-based maximum entropy ecological niche risk prediction systems to assess the transmission risk of the COVID-19 epidemic globally. This study provided a comprehensive analysis of various factors influencing the transmission of COVID-19, incorporating both human and environmental variables. These findings emphasize the role of different types of influencing variables in disease transmission, which could have implications for global health regulations and preparedness strategies for future outbreaks.

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.

Estimating the spatial distribution of African swine fever outbreak in China by combining four regional-level spatial models

The outbreaks of African Swine Fever (ASF) in China are ongoing, and the inadequate management of the pig supply chain is criticized. In the past four years, a series of preventive and control measures have been supplied national wide, while the outbreaks have not been terminated. This suggests the existing animal disease management at the district level may not be appropriate to control ASF under the current situation of the ASF outbreak in China. It is urgent to further describe real distribution areas of ASF in China. In this study, we combined four regional-scale models to predict the risk distribution of ASF in mainland China and identify risk factors related to ASF outbreaks. The results showed that the four regional-scale models were more accurate in predicting the ASF outbreaks than the nationwide scale model. The four regional-scale models identified the potential risk factors associated with ASF outbreaks, such as population density, pig density, land cover, temperature, and elevation factors. Moreover, seven clusters with high potential risk of ASF outbreaks were identified. Then, based on the results, we proposed more suitable prevention and control plans for ASF, which can assist the implementation of transport management policies within and between risk clusters.

Effect of epidemic diseases on wild animal conservation

Under the background of global species extinction, the impact of epidemic diseases on wild animal protection is increasingly prominent. Here, we review and synthesize the literature on this topic, and discuss the relationship between diseases and biodiversity. Diseases usually reduce species diversity by decreasing or extinction of species populations, but also accelerate species evolution and promote species diversity. At the same time, species diversity can regulate disease outbreaks through dilution or amplification effects. The synergistic effect of human activities and global change is emphasized, which further aggravates the complex relationship between biodiversity and diseases. Finally, we emphasize the importance of active surveillance of wild animal diseases, which can protect wild animals from potential diseases, maintain population size and genetic variation, and reduce the damage of diseases to the balance of the whole ecosystem and human health. Therefore, we suggest that a background survey of wild animal populations and their pathogens should be carried out to assess the impact of potential outbreaks on the population or species level. The mechanism of dilution and amplification effect between species diversity and diseases of wild animals should be further studied to provide a theoretical basis and technical support for human intervention measures to change biodiversity. Most importantly, we should closely combine the protection of wild animals with the establishment of an active surveillance, prevention, and control system for wild animal epidemics, in an effort to achieve a win-win situation between wild animal protection and disease control.

Risk transboundary transmission areas and driving factors of brucellosis along the borders between China and Mongolia

OBJECTIVE

Brucellosis is a common and neglected zoonotic infectious disease worldwide caused by Brucella. However, transboundary transmissions among countries, particularly those with high incidences, are seldom investigated. In the present study, by taking China and Mongolia as examples, we aim to identify transboundary transmission risk and driving factors of brucellosis along borders.

METHODS

167 brucellosis outbreak locations along the border between China and Mongolia were collected. Wildlife distribution and cross-border activities were mapped. Maximum entropy approach modeling was conducted to predict the potential risk of prevalence of brucellosis with meteorological factors, geographical environment, economic development, living habits et al. The accuracy of the models was assessed by the area under the receiver operating characteristic (ROC) curve (AUC), Kappa test, and correctly classified instances (CCI).

RESULTS

The spatial model performed excellent predictive performance with the predictor variables of soils, pastures, goat density, mean precipitation of the wettest month, temperature seasonality, and population density, which with the contribution and permutation important in 27.2 %, 31.9; 23.3 %, 6.8; 18.0 %, 17.2; 11.2 %, 18.1; 10. 3 %, 15.2; 10.0 %, 10.8. The calculated AUC, SD, Kappa, and CCI are 0.870, 0.001, 0.882, and 0.883, respectively. The distribution map of brucellosis showed high-risk areas along the borders.

CONCLUSIONS

Our study identified high-risk areas and the driving effect of brucellosis along the borders between China and Mongolia. Moreover, there is the possibility of cross-border wildlife activities in high-risk areas, which increases the risk of cross-border brucellosis transmission. The funding provides clues for cooperative prevention and control of brucellosis by reducing transboundary transmission.

Modeling the environmental suitability for Bacillus anthracis in the Qinghai Lake Basin, China

Bacillus anthracis is a gram-positive, rod-shaped and endospore-forming bacterium that causes anthrax, a deadly disease to livestock and, occasionally, to humans. The spores are extremely hardy and may remain viable for many years in soil. Previous studies have identified East Qinghai and neighbouring Gansu in northwest China as a potential source of anthrax infection. This study was carried out to identify conditions and areas in the Qinghai Lake basin that are environmentally suitable for B. anthracis distribution. Anthrax occurrence data from 2005-2016 and environmental variables were spatially modeled by a maximum entropy algorithm to evaluate the contribution of the variables to the distribution of B. anthracis. Principal Component Analysis and Variance Inflation Analysis were adopted to limit the number of environmental variables and minimize multicollinearity. Model performance was evaluated using AUC (area under the curve) ROC (receiver operating characteristics) curves. The three variables that contributed most to the suitability model for B. anthracis are a relatively high annual mean temperature of -2 to 0°C, (53%), soil type classified as; cambisols and kastanozems (35%), and a high human population density of 40 individuals per km2 (12%). The resulting distribution map identifies the permanently inhabited rim of the Qinghai Lake as highly suitable for B. anthracis. Our environmental suitability map and the identified variables provide the nature reserve managers and animal health authorities readily available information to devise both surveillance strategy and control strategy (administration of vaccine to livestock) in B. anthracis suitable regions to abate future epidemics.

Environmental suitability of Yersinia pestis and the spatial dynamics of plague in the Qinghai Lake region, China

Plague, a highly infectious disease caused by Yersinia pestis, has killed millions of people in history and is still active in the natural foci of the world nowadays. Understanding the spatiotemporal patterns of plague outbreaks in history is critically important, as it may help facilitate the prevention and control for potential future outbreaks. This study's objective was to estimate the effect of the topography, vegetation, climate, and other environmental factors on the Y. pestis ecological niche. A maximum entropy algorithm spatially modelled plague occurrence data from 2004-2018 and the environmental variables to evaluate the contribution of the variables to the distribution of Y. pestis. Our results found that the average minimum temperature in September (-8 °C to +5 °C) and the sheep population density (250 sheep per km2) were influential in characterising the niche. The rim of Qinghai Lake showed more favourable conditions for Y. pestis presence than other areas within the study area. Identifying various factors will assist any future modelling efforts. Our suitability map identifies hotspots and will help public health officials in resource allocation in their quest to abate future plague outbreaks.

Spatial modeling and ecological suitability of monkeypox disease in Southern Nigeria

The reemergence of monkeypoxvirus (MPXV) in 2017 after about 39 years of no reported cases in Nigeria, and the recent incidence in countries such as the United States of America, United Kingdom, Singapore, and Israel which have been reportedly linked with travelers from Africa, have heightened concern that MPXV may have emerged to occupy the vacant ecological and immunological niche created by the extinct smallpox virus. This study was carried out to identify environmental conditions and areas that are environmentally suitable (risky areas) for MPXV in southern Nigeria. One hundred and sixteen (116) spatially unique MPXV occurrence data from 2017–2021 and corresponding environmental variables were spatially modeled by a maximum entropy algorithm to evaluate the contribution of the variables to the distribution of the viral disease. A variance inflation analysis was adopted to limit the number of environmental variables and minimize multicollinearity. The five variables that contributed to the suitability model for MPXV disease are precipitation of driest quarter (47%), elevation (26%), human population density (17%), minimum temperature in December (7%), and maximum temperature in March (3%). For validation, our model had a high AUC value of 0.92 and standard deviation of 0.009 indicating that it had excellent ability to predict the suitable areas for monkeypox disease. Categorized risk classes across southern states was also identified. A total of eight states were predicted to be at high risk of monkeypox outbreak occurrence. These findings can guide policymakers in resources allocation and distribution to effectively implement targeted control measures for MPXV outbreaks in southern Nigeria.

Peste des Petits Ruminants in Central and Eastern Asia/West Eurasia: Epidemiological Situation and Status of Control and Eradication Activities after the First Phase of the PPR Global Eradication Programme (2017–2021)

Simple Summary

Peste des petits ruminants (PPR) is a highly contagious viral disease of domestic and wild small ruminants. The disease is endemic to large parts of Africa, the Middle East and Asia and causes severe socioeconomic losses, especially in developing countries reliant on small ruminant value chains. Currently, PPR is the only animal disease targeted by the Global Eradication Programme (PPR GEP), which aims to eradicate the disease by 2030. Following the end of the first five-year phase of the PPR GEP, the goal of this review is to provide an update on the status of the eradication progress in one of the nine regions targeted for coordinated action in the PPR Global Control and Eradication Strategy, denominated Central Asia/West Eurasia. In addition to the original nine countries, regional meetings and activities have involved four additional countries based on shared epidemiological features, which are also reviewed here. The considered area spans from Eastern Europe to East Asia and features remarkable variability in terms of both PPR presence and enacted control efforts. The achievements and constraints encountered at regional and national levels are discussed, thus providing useful data for tailoring the next steps of the eradication programme to the peculiarities of the region.

Abstract

Peste des petits ruminants (PPR) is a highly contagious infectious disease of small ruminants caused by peste des petits ruminants virus (PPRV). PPR poses a significant threat to sheep and goat systems in over 65 endemic countries across Africa, the Middle East and Asia. It is also responsible for devastating outbreaks in susceptible wildlife, threatening biodiversity. For these reasons, PPR is the target of the Global Eradication Programme (PPR GEP), launched in 2016, which is aimed at eradicating the disease by 2030. The end of the first five-year phase of the PPR GEP (2017–2021) provides an ideal opportunity to assess the status of the stepwise control and eradication process. This review analyses 13 countries belonging to Eastern Europe, Transcaucasia, and Central and East Asia. Substantial heterogeneity is apparent in terms of PPR presence and control strategies implemented by different countries. Within this region, one country is officially recognised as PPR-free, seven countries have never reported PPR, and two have had no outbreaks in the last five years. Therefore, there is real potential for countries in this region to move forward in a coordinated manner to secure official PPR freedom status and thus reap the trade and socioeconomic benefits of PPR eradication.

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.

Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides

African horse sickness (AHS) is a devastating equine infectious disease. On 17 March 2020, it first appeared in Thailand and threatened all the South-East Asia equine industry security. Therefore, it is imperative to carry out risk warnings of the AHS in China. The maximum entropy algorithm was used to model AHS and Culicoides separately by using climate and non-climate variables. The least cost path (LCP) method was used to analyze the habitat connectivity of Culicoides with the reclassified land cover and altitude as cost factors. The models showed the mean area under the curve as 0.918 and 0.964 for AHS and Culicoides. The prediction result map shows that there is a high risk area in the southern part of China while the habitats of the Culicoides are connected to each other. Therefore, the risk of introducing AHS into China is high and control of the border area should be strengthened immediately.