african swine fever research paper philippines

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Indicadores, links relacionados, scientia agropecuaria, versión impresa  issn 2077-9917, scientia agropecuaria vol.11 no.4 trujillo oct-dic 2020, http://dx.doi.org/10.17268/sci.agropecu.2020.04.17 .

Original Articles

Biosecurity and readiness of smallholder pig farmers against potential African Swine Fever outbreak and other pig diseases in Baybay City, Leyte, Philippines

1 College of Veterinary Medicine, Visayas State University, Baybay City, Leyte. Philippines.

Preventing African Swine Fever (ASF) outbreaks require an active involvement of pig growers as they are in the frontline of detection, notification, and the application of strict biosecurity measures. The Eastern Visayas (Region VIII) in Central Philippines is still free of ASF but the risk can be remarkable given the high volume of pigs that enter in this region as a market hub to large pig producers both coming from Luzon (north) and Mindanao (south). This study was conducted to better understand the readiness and biosecurity practices of smallholder pig farmers who comprise most of the pig growers in the City of Baybay, Leyte. Using multiple correspondence analysis (MCA) and agglomerative hierarchical clustering (AHC) technique of data from 350 pig farmer-respondents, our study found several areas in pig raising activities that need to be highlighted. While pig farmers were generally aware of the threat posed by ASF and have relatively good biosecurity practices, only 32.90% were convinced that the City of Baybay is prepared in the case of an ASF outbreak. Moreover, the importance of vaccination, footbath, and controlling swill feeding need to be emphasized (Cluster 2, 58.29%). More efforts should be directed towards preparing and training pig farmers on disease monitoring and surveillance and improving further its biosecurity practices with special focus on bioexclusion. Similar studies should be conducted to nearby local government units particularly those located near entry and exit borders of the Eastern Visayas region.

Keywords:  African Swine Fever; biosecurity; backyard pig farmers; Baybay City

Introduction

The case of African Swine Fever (ASF) in Asia has been unprecedented with outbreaks occurring around many countries, significantly impacting animal health and welfare, the agricultural economy and food security ( Costard et al., 2009 ; FAO, 2020 ; Tian and von Cramon-Taubadel, 2020 ). While ASF does not pose direct risk to human health, its highly contagious and fatal characteristics affecting both young or old, and domestic and the wild boar population could lead to severe devastation of the pig industry ( Costard et al ., 2009 ; Costard et al ., 2013 ). African Swine Fever has ravaged the swine industry of both the Western (1960-1995) and Eastern Europe (2007-2018) ( Cwynar et al ., 2019 ; Lu et al ., 2020 ), and has caused more than a million pig deaths in China since severe outbreaks occurred in 2018, signalling fear and unprecedented spread among other countries in Asia ( Estienne, 2019 ). Inevitably enough, many Asian countries have been affected since, including Mongolia in January, Vietnam in February, Cambodia in April, North Korea in May, Laos in June, Myanmar in August, and South Korea in September, among others including the Philippines as the 9 th country affected ( Pig Progress, 2019 ; Estienne, 2019 ; FAO, 2020 ; Kim et al ., 2020 ; Parrocha, 2020 ). Record breaking increase in the number of countries affected has continued to occur since 2005 to 2018 ( Rozstalnyy and Plavšić, 2019 ). Since the ASF DNA virus is complex being unusually related to other viruses, no effective vaccine has yet been de veloped ( Costard et al ., 2013 ), thus calling for a comprehensive approach to contain and control its impact.

Due to the potential catastrophic impact of ASF on the country’s swine industry, the President of the Philippines signed Executive Order No. 105 in February 21, 2020 “creating a national task force to prevent the entry of animal-borne diseases, contain and control the transmission thereof, and address issues relating thereto”, and mandating the “Department of Agriculture, through the Bureau of animal Industry to control and eradicate dangerous communicable diseases of domestic animals” ( Offical Gazette, 2020 ). Towards the end of 2020, The Philippines has seen several thousands of deaths and/or mass culling of pigs to control the spread of ASF particularly in Luzon in the north but has also affected Mindanao in the southern part of the country ( Parrocha, 2020 ). The Philippines is among the top pork producers worldwide with a close to ₱200 billion pig industry of about 12.7M pigs ( DOST-PCAARRD, 2016 ; PSA, 2020 ). Of this about 65% is considered backyard or those pigs normally raised by smallholder farmers with seemingly limited access to feed supply, equipment, and facil ities, and veterinary health resources. The practice of swill feeding is not uncommon given the several and widely available sources including kitchen leftovers, hotels, restaurants, and the like.

The Eastern Visayas Region (Region VIII) in central Philippines where this study was conducted is still free of ASF but the risk is high considering the volume of pigs that arrive in this region both coming from Luzon (north) and Mindanao (south) pig producers. Thus, the Department of Agriculture and authorities in the region have prompted significant steps to prevent the entry of ASF including the release of relevant Executive Orders from different provincial governments to monitor and/or ban entry of live pigs, pork and pork products from different entry/exit points as well as timely reporting of pigs that manifest ASF-like symptoms ( Quirante, 2019 ). The Bureau of Animal Industry has also earlier rolled out the “1-7-10 Protocol” for culling management, surveillance, and reporting, as well as the BABES campaign which stands for: Ban pork imports from confirmed ASF-affected countries; Avoid swill feeding; Block entry at major seaport and airports, especially international ports; Educate our people; and lastly, Submit hog blood samples ( DA Communications Group 2019 ; Meniano, 2019 ). Region VIII is a potential market from among large pig producers outside of the region considering its low pig inventory in the country (3.2%; PSA, 2019 ). The demand for pork in the Province of Leyte is substantially favourable as Leyte ac counts for most slaughtered pigs within the region ( PSA, 2018 ).

Preventing further spread of ASF from the initially affected areas appears to be the core strategy to contain the economic losses caused by ASF ( GAIN, 2019 ). The Food and Agriculture Organization (FAO) through the Agriculture and Consumer Protection Department emphasizes early reaction, detection and notification including the application of strict biosecurity measures. This also includes improved husbandry prac tices, disinfection and good surveillance and monitoring of live pigs being transported ( FAO, 2020 ). Stringent compliance with biosecurity measures and cooperation with government initiatives are key strategies to prevent introduction and contain the impact of ASF. The aim of this study was to determine and understand the current situation, readiness and examine the biosecurity practices of backyard pig farmers within the City of Baybay, Leyte, Philippines. Results of this study could influence decision makers both as pig farm owners and government officials in facing the challenges posed by disease outbreaks.

Materials and methods

Location of the study and sampling procedures

The study was conducted between September 2019 to February 2020 about a year after the significant outbreak of ASF occurred in the country. The City of Baybay in the Province of Leyte, is the second largest city within the Eastern Visayas region (Region VIII) composed of at about 92 barangays, 24 of which are urban and 68 are rural, and a home to a population of about 110,000 ( PSA, 2017 ). There are only a few commercial pig farms making backyard or smallholder type of pig production a major livestock activity covering about 11,000 pig population. Following recommended sampling procedures, at least 350 pig farmers were required at 95% level of confidence and 5% margin of error after considering about 4,100 current backyard pig raisers ( The Research Advisors 2006 ; Fosgate, 2009 ; Andico and Peña, 2019 ). The farmer respondents were randomly selected and proportionally allocated per barangay from a given population of backyard pig raisers provided by the local agriculture office. The study was approved by the Student Research Committee of the College of Veterinary Medicine, Visayas State University.

Survey questionnaire and conduct of interview

A systematic questionnaire was constructed and modified following previous research by Andico and Peña (2019) including earlier studies on similar topic ( Ribbens et al ., 2008 ; Alawneh et al ., 2014 ) (Appendix). Among the questions included were the pig farmers’ socio-demographic information, pig production and health management, biosecurity practices, and farmers’ knowledge of ASF. The questionnaire was constructed in English and translated into the local dialect (Baybayanon/Cebuano) for ease and convenience during the one-on-one interview at the respective residence of the farmer respondents with prior verbal consent. Any information that has the potential to identify the farmer-respondent was handled with confidentiality and was not included in the analysis to protect the privacy of respondents. In the event the first respondent was not available or refused to participate, the next available backyard pig raiser closest to that respondent was interviewed instead. The actual interview completed about 15 minutes per respondent.

Data management and statistical analysis

All data were encoded in and analyzed using Microsoft Office Excel with XLSTAT Basic (version 2020.1.3) installed for multiple correspondence analysis (MCA), agglomerative hierarchical clustering (AHC) and parallel coordinates plots (PCP), following procedures found in the XLSTAT Support Center and as previously described ( Andico and Peña, 2019 ). From the questionnaire, variables relating to knowledge on ASF, and biosecurity practices were analyzed separately. Descriptive statistics on farmers’ socio-demographics and pig production general characteristics were also generated, accordingly.

Results and discussion

All farmers who were initially included in sampling responded providing us with sufficiently robust data to proceed with the evaluation and characterization of the different aspects of the level of preparedness and biosecurity practices of backyard pig farmers against potential ASF outbreak and other swine diseases in Baybay City, Leyte. Apparently, at least three quarters of pig farmers signified awareness of ASF (82.30%) and have correctly identified ASF as a viral disease (74.90%, Table 1 ). Almost all the respondents are aware that ASF is already present in the country and that a vaccine for prevention does not exist, thus a major concern if an outbreak occurs. Interestingly, despite attendance to seminar on ASF, almost half of the farmer respondents were convinced that the city is not likely prepared in the case of an ASF outbreak ( Table 1 ).

Table 1  Summary statistics of the farmer-respondents’ knowledge about the African Swine Fever (ASF) 

n=350; ASF, African Swine fever.

Figure 1  Multiple-correspondence analysis solution of the farmer-respondents’ knowledge about the African Swine Fever (ASF). 

Figure 1 shows the MCA solution for the variables regarding actions taken by the respondents to control and prevent pig diseases. Briefly, those respondents who responded having knowledge of ASF were the same respondents who answered correctly in terms of the cause, and the presence, including participation on a seminar about ASF (upper left quadrant), while, those who responded being not aware of ASF have not attended any seminar on ASF nor were aware of the presence of ASF in the Philippines (lower right quadrant).

Following AHC, six clusters were generated characterizing the farmer-respondents’ knowledge about ASF. Almost half (46.70%) belong to Cluster 1 (black) and is characterized by pig farmers who have signified knowledge about ASF, its cause, presence in the Philippines, that it is a concern, but is not so convinced that the city is prepared of potential ASF outbreak ( Figure 2 A). Almost similar features appear to characterize Cluster 3 (blue, 33.43%%) except that these respondents believed that ASF is caused by bacteria and that the city is prepared despite having not attended any seminar on ASF ( Figure 2 B).

Figure 3 provides summary statistics of some pertinent biosecurity practices of backyard pig farmers. Despite the remarkably high proportion of farmers who provide pens for their pigs, there are still some who do not (4.90%). While deworming is heavily practiced, the opposite was true with vaccination. Many pig farms are freely accessible to visitors, no effective footbath, nor perimeter fence provided with only less than 10% of the pig farms were at least 200m away from the household. About 30% still practiced swill feeding and a sizable portion do not necessarily own veterinary materials for use on their farms.

Figures 4 and 5A show the MCA solution, and dendrogram generated by AHC of the farmer-respondents’ biosecurity practices and pig health management in Baybay City, Leyte, respectively. Of the three clusters generated, C2 (green) is by far the largest (58.29%), followed by Cluster 1 (blue, 38.00%) and finally Cluster 3 (red) at 3.71%. The biosecurity practices between these clusters are plotted accordingly in Figure 5 B which highlights Cluster 1 (38%) with good biosecurity practices.

Figure 2  Parallel coordinate plots highlighting Cluster 1 (2A, black, 46.7%) and Cluster 3 (2B, blue, 33.43%) showing six clusters of farmer-respondents’ knowledge about African Swine Fever (ASF). 

Figure 3  Summary statistics on biosecurity practices of smallholder pig farmers. 

Figure 4  Multiple-correspondence analysis solution of the farmer-respondents’ biosecurity practices and pig health management. 

Figure 5  Dendrogram generated by AHC (A) and parallel coordinate plots (B) describing three clusters (C1= blue, 38.00%; C2= green, 58.29%; & C3= red, 3.71%) of the farmer-respondents’ biosecurity practices and pig health management. 

Table 2  Demographics and general characteristics of backyard pig farmer-respondents 

* for emphasis.

Table 2 provides summary statistics of the demographics of the farmer-respondents. Apparently, there were more females than males, and most of the pig raisers are married. Nearly half of the farmer- respondents (43.10%) have reached high school while 63.70% answered secondary source of income as the purpose of pig raising. Only a small portion have attended seminar on pig raising (18.3%) in the last six months, in the same way as membership in a swine raising organization (9.10%). In addition, the average age of the farmer-respondents was 45.67 ± 0.64 with about 8.21 ± 0.39 years of experience in raising pigsOn Table 3 is a short description of the farming practices by farmer- respondents. Nearly half of the respondents (48.31%) raise a combination of different classes of pigs with a majority using a mixed breed (84.30%). A few farmers raise boars for artificial insemination or selling semen. Good record keeping does not exist in 76% of the farms. The average number of pigs raised by each pig farmer is 5.24 ± 0.30 heads.

The potential devastation that ASF may cause to the pig industry requires an active involvement of pig growers in the community as they are in the frontline of detection, notification, and the application of strict biosecurity measures. Moreover, as pig farmers have different husbandry and health management practices, it is imperative that the government should take a proactive role in surveillance and monitoring of hygiene, proper waste disposal, swill feeding, and the conduct of related seminars on best practices and pig diseases, among others, to raise awareness within the community. In the case of the City of Baybay, Leyte, at least a longstanding city ordinance (M.O. No. 004 2004) already exits highlighting systematic and ecologically sustainable programs to be adopted in all pig raising projects. However, how this ordinance is being enforced or practiced by concerned stakeholders may need to be revisited.

Table 3  General characteristics of pig farmer raising activities 

AI = artificial insemination.

Results of our current study demonstrate several key areas in pig raising activities that need to be reviewed and LGU’s active support is important not only to improve production targets but also increase the level of preparedness among backyard pig farmers in the case of disease outbreaks like the ASF. While ASF could drastically affect large and commercial pig production businesses ( Costard et al ., 2009 ), significant losses could easily railroad small pig producers commonly known in the Philippines as backyard pig farmers apparently due to poor preventive/control measures and biosecurity in this type of production ( Edelsten and Chinombo, 1995 ; Costard et al ., 2009). As ASF can wipe out a significant fraction of the pig population, the risk it poses against food security can be difficult to imagine. Pork is still one of the most widely eaten meat globally and many countries rely heavily on the pig production trade providing significant contribution to many countries’ gross domestic product. In 2011, when an ASF outbreak occurred in Isoka district of Zambia in Africa, the pig population decreased by at least 50% ( Komba et al ., 2014 ), let alone the possible rise in the price of locally produced pork as a result of reduction in pork supply ( McOrist, 2019 ). Thus, vulnerable regions however small should engage in programs to empower both animal professionals and down to common pig growers to embrace awareness and readiness against potential disease outbreaks.

Interestingly, most pig farmers appear to be clearly knowledgeable of ASF along its presence as an active threat in the Philippine swine industry ( Table 3 ). It has been noted that most of the farmers have access to TV, newspapers, and related materials as sources of information about the ASF. This could be a good start to strengthen further the implementation of relevant programs for the prevention and control of swine diseases. Since, nearly half of the farmer respondents represented those cluster who are not so convinced that the City of Baybay is prepared in the case of an ASF outbreak (46.7%; Figure 2 A), the LGU concerned may take this as a priority to engage in different education campaigns to heighten the promotion of ASF awareness within the locality particularly among those engaged in pig farming. When the first ASF case was reported in the Philippines in about September 2019 ( McOrist, 2019 ; WAHID, n.d. ), samples require further confirmation so that appropriate measures can be applied. Moreover, this is compounded by the fact that the rate of spread depends on multiple factors many of which are yet to be understood fully ( Schulz et al ., 2019 ).

In terms of pertinent biosecurity practices of backyard pig farmers, the practices that need to be highlighted include vaccination, provision of a suitable footbath, perimeter fence, rodent control, and most importantly swill feeding. Nevertheless, it was notable to observe that the farmer-respondents have good biosecurity practices in general. However, there are still about 5% who do not provide proper shelter for their pigs ( Figure 3 ) while the importance of vaccination, swill feeding and the provision of a footbath where possible need to be emphasized for Cluster 2 (58.29%; Figure 5 A) of pig farmers. In fact, swill feeding alone is still practiced by closed to 30% ( Figure 3 ) which is quite alarming considering that the introduction of ASF into the country could have likely started from contaminated meat leftovers and waste food products fed to backyard pigs (Beek, 2019). This is almost similar in the case of ASF outbreak in Brazil in 1978 which was suspected to be due to food waste introduced by tourists from infected countries ( Lyra, 2006 ). While biosecurity in general should be attainable and reasonable, there are complex factors that need to be considered for effective implementation particularly when applied to field settings ( Anderson, 2010 ). There are practical variables including but not limited to budget, equipment, facilities, educational background, and personnel’s understanding and attitude against disease spread and prevention ( Anderson, 2010 ; Simon-Grifé et al ., 2013 ). In terms of attitude toward implementation of biosecurity programs, it appears that the economic cost and benefits associated with implementation of such programs need to be clear in the first place and how these measures play along with mandatory rules ( Gunn et al ., 2008 ). In fact, one of the reasons pig farmers and traders may have a negative atitude and less cooperation with authority towards biosecurity measures is the associated costs.

It is quite typical for backyard pig raising activities to be considered as a secondary source of income as demonstrated in the result of the study (63.70%; Table 2 ). Many of these farmers may still be engaged in other farming activities while the limited land and the capital requirements may also prohibit them to engage in commercial production. Given the average age of farmers at 45.67 ± 0.64 years, this was apparently reflected also with their relatively long experience (8.21 ± 0.39 years) in pig raising activities. This could be taken as an advantage by the LGU as these farmers demonstrate their experience and skills in pig raising given their long engagement. Quite surprisingly though, only a small portion of the farmers have answered attendance to pig raising seminars as well as membership in swine raising organization ( Table 2 ). This should be promoted as participation and involvement to relevant education activities and organization is both helpful and advantageous ( Andico and Peña, 2019 ). The problem of record keeping in the farm also needs to be addressed as most pig farmers (76%) do not keep records of their farming activities ( Table 3 ). A portion of farmers are also engaged in maintaining a boar allowing them to sell semen which again could funnel the transmission of diseases ( Table 3 ). Overall, it appears that bottomline measures directed towards early detection, timely reporting, rapid response and coordination of various stakeholders at all levels, on top of good animal husbandry, health management and biosecurity ( Swai and Lyimo, 2014 ; Yun, 2020 ) must be given priority to ensure readiness in the case of potential ASF outbreaks and other swine diseases of economic importance.

Conclusions

Pig farmers in Baybay City, Leyte are mostly aware of the African Swine Fever as a viral disease present in the country. However, despite the seemingly acceptable biosecurity practices of pig farmers with close to 95% who signified ASF as a concern or threat to the pig industry and food security, only a third believes that the City is prepared to a potential ASF outbreak. Swine stakeholders of the city should take into consideration efforts geared towards preparing and training pig farmers on disease monitoring and surveillance, and improving further its biosecurity practices perhaps with special focus on bioexclusion in order to prevent the entry of the ASF virus into the city. Similar studies should be conducted to nearby cities and municipalities (local government units) particularly near entry and exit borders of the Eastern Visayas region.

Acknowledgments

The authors wish to thank the cooperation of pig farmers, the support of the Local Government Unit (LGU) through the Office of the Mayor of the City of Baybay, the assistance of Barangay Captains or their respective representatives, and the Visayas State University for the financial assistance in publication. This manuscript forms part of the undergraduate thesis work of Bernardes (2020) .

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Questionnaire form

Survey Questionnaire No. ____________

Name: _____________________________ Barangay: ____________________

I. Socio-demographic variables

Age: _____ Gender: [] M [] F Civil status: [] Single [] Married [] Widowed Educational level: [] None [] Elementary (Grade: _) [] High School (Year: __) [] Vocational [] College (Year: ___) Occupation: _______________________________ How many years have you raised pigs? ___ Why do you raise pigs? [] Primary source of income [] Secondary source of income [] Hobby Have you attended seminars related to pig production, biosecurity management and common swine diseases in the last six months? [] Yes [] No What is the profession of the person whom you frequently asked questions regarding pig management? [] Veterinarian [] Agri-vet technician/store person []Animal Technician [] DA personnel [] Others (pls. specify) ________________________ Are you a member of any Hog Raising Association? [] Yes [] No

II. Questions about ASF

Do you know what African Swine Fever (ASF) is all about? [] Yes [] No What causes ASF disease? [] bacteria [] virus [] others_______ Have you attended any seminar about ASF? [] Yes [] No Who conducted the seminar about ASF? [] Provincial Vetetrinarian [] Other Gov’t Agriculturist/Employee [] Private personnel ([] BMEG, [] Pigrolac, [] Others: please specify:_______________________________) Is there a vaccine for ASF? [] Yes [] No Is there ASF in the Philippines? [] Yes [] No Do you think ASF can affect other pigs? [] Yes [] No Do you think ASF can affect other animals other than pigs? [] Yes [] No Do you think ASF can affect humans? [] Yes [] No Do you think Baybay City is prepared with an ASF outbreak? [] No [] Not so [] Yes Is ASF a serious concern for the pig industry? [] Yes [] No Other sources of ASF information: TV [] Radio [] Newspaper [] Others: please specify: _________

III. Production status

How many pigs are you raising? ______________ What type of pigs do you raise? [] Breeder (Sow) []Fatteners [] Breeder Boar [] Combination What is/are the breed of your pigs? [] Purebreed (pls. specify ______________[] Mixed breed [] Native What kind of records do you usually keep or note in managing pigs? [] Feed consumption [] Mortality/morbidity rate [] Health/vaccination records [] Combination [] None [] Others (pls. specify) ________ Do you have a boar? [] Yes [] No Do you do artificial insemination (AI) service and/or sell semen? [] Yes [] No

IV. Health management

Are you using artificial insemination to breed your pigs? [] Yes [] No [] Not applicable (fattening only) Do you wean your piglets only at the age of 1 month or less? [] Yes [] No [] Not applicable (Fatteners only). If yes, at what specific age? _____________________ Are you practicing tail docking to your piglets? [] Yes [] No [] Not applicable (Fatteners only). If yes, at what specific age? _____________________ Are you practicing needle teeth clipping to your piglets? [] Yes [] No [] Not applicable (Fatteners only). If yes, at what specific age? _____________________ Are you practicing castration to your male piglets? [] Yes [] No [] Not applicable (Fatteners only). If yes, at what specific age? _____________________ Is the feeds given to the pigs mainly commercial feeds? [] Yes [] No Is your pigpen properly roofed? [] Yes [] No. If yes, what is the roof made of? ________________________________ Is your pigpen’s water source coming from water district? [] Yes [] No If no, what is the source of water? _________________________________ Is proper flooring applied on your pigpen? [] Yes [] No If yes, what is it made of? _____________________ Is your piggery located at least one kilometer away from any piggeries near your area? [] Yes [] No How often do you bathe your pigs? [] once a day [] at least 3 times a week []once a week []none Do you deworm your pigs? [] Yes [] No If yes, how often? _______________________________________ Are you giving Iron supplement to your pigs? [] Yes []No If yes, how often? _______________________________________ Are you giving vitamin and/or mineral as supplement to your pigs? [] Yes [] No If yes, How often? _______________________________________

V. Biosecurity practices

Do you have pens provided to your pigs? [] Yes [] No What is your pen predominantly made of? __________________________ Where do you get your replacement stock/pigs? [] Piggeries within Leyte [] From other piggeries outside Leyte [] Own production If outside Leyte, please specify: ____________________________________________ Do you permit visitors to enter your piggery anytime? [] Yes [] No Are all persons obliged to shower before entering the piggery? [] Yes [] No Do you have footbath at the entrance of your piggery [] Yes [] No Do you wear boots when entering your piggery? [] Yes [] No Do you have separate clothes for used in your piggery purposes only? [] Yes [] No Do you have your own veterinary materials (e.g. syringe, medicines) for your own piggery? [] Yes [] No Do you share your veterinary materials with other piggery owners or vice versa? [] Yes [] No Do birds have access to your piggery? [] Yes [] No Are dogs/cats allowed to enter your piggery? [] Yes [] No Are you doing regular insect control in your piggery? [] Yes [] No If yes, what is your method of control? _______________________ Are you doing regular rodent control in your piggery? [] Yes [] No If yes, what is your method of control? _______________________ Do you have a quarantine area for the newly acquired pigs before it will be put in the pen together with other pigs? [] Yes [] No Are you raising other livestock aside from pigs? [] Yes [] No If yes, what are those? ______________________________________ Are you raising pet animals? [] Yes [] No If yes, what are those? ______________________________________ Do you practice swill feeding to your pigs? [] Yes [] No Do you isolate sick pigs from other pigs just in case? [] Yes [] No Do you provide a perimeter fence in your piggery? [] Yes [] No If yes, what is its type of fence? ________________________________ Do you vaccinate your pigs? [] Yes [] No If yes, what is its vaccines do you give? ________________________________ Do you practice proper waste disposal in your piggery? [] Yes [] No Do you bury/burn dead pigs? [] Yes [] No Do you disinfect your piggery before loading new batch of pigs? [] Yes [] No Is there a drainage system found on your piggery? [] Yes [] No Do you practice “All-in-all-out” system? [] Yes [] No Is your piggery located at least 200 meters away from the highway/main road? [] Yes [] No Is your piggery located at least 200 meters away from other houses [] Yes [] No

Received: July 18, 2020; Accepted: November 16, 2020

* Corresponding author E-mail: [email protected] (S.T. Peña, Jr.).

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Research Article

Quantifying risk factors and potential geographic extent of African swine fever across the world

Contributed equally to this work with: Dong Jiang, Tian Ma, Mengmeng Hao

Roles Data curation, Resources, Writing – original draft

Affiliations Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China, College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China

Roles Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft

Roles Data curation, Investigation, Resources, Writing – original draft

Roles Conceptualization, Methodology, Project administration, Supervision, Validation, Writing – original draft, Writing – review & editing

* E-mail: [email protected] (FD); [email protected] (SC); [email protected] (YL)

Roles Data curation, Resources

Roles Data curation, Investigation, Resources

Affiliation Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom

Affiliation School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen, Guangdong, China

Affiliation Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

Affiliation School of Geographic Sciences, Nantong University, Nantong, China

Affiliation Computer Network Information Center, Chinese Academy of Sciences, Beijing, China

Roles Writing – review & editing

Affiliation School of Veterinary Medicine, Centre for Biosecurity and One Health, Murdoch University, Perth, Australia

Roles Conceptualization, Data curation, Methodology, Software, Supervision, Writing – original draft

•  [ ... ],

Roles Conceptualization, Data curation, Methodology, Supervision, Writing – original draft

Affiliations School of Veterinary Medicine, Centre for Biosecurity and One Health, Murdoch University, Perth, Australia, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Australia

• [ view all ]
• [ view less ]
• Dong Jiang, 
• Tian Ma, 
• Mengmeng Hao, 
• Fangyu Ding, 
• Kai Sun, 
• Qian Wang, 
• Tingting Kang, 
• Di Wang, 
• Shen Zhao, 

• Published: April 21, 2022
• https://doi.org/10.1371/journal.pone.0267128
• Reader Comments

African swine fever (ASF) has spread to many countries in Africa, Europe and Asia in the past decades. However, the potential geographic extent of ASF infection is unknown. Here we combined a modeling framework with the assembled contemporary records of ASF cases and multiple covariates to predict the risk distribution of ASF at a global scale. Local spatial variations in ASF risk derived from domestic pigs is influenced strongly by livestock factors, while the risk of having ASF in wild boars is mainly associated with natural habitat covariates. The risk maps show that ASF is to be ubiquitous in many areas, with a higher risk in areas in the northern hemisphere. Nearly half of the world’s domestic pigs (1.388 billion) are in the high-risk zones. Our results provide a better understanding of the potential distribution beyond the current geographical scope of the disease.

Citation: Jiang D, Ma T, Hao M, Ding F, Sun K, Wang Q, et al. (2022) Quantifying risk factors and potential geographic extent of African swine fever across the world. PLoS ONE 17(4): e0267128. https://doi.org/10.1371/journal.pone.0267128

Editor: Simon Clegg, University of Lincoln, UNITED KINGDOM

Received: October 21, 2021; Accepted: April 2, 2022; Published: April 21, 2022

Copyright: © 2022 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper.

Funding: This research is supported and funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19040305). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors declare that they have no competing interests.

Introduction

African swine fever (ASF) is an acute, contagious swine disease that is becoming a global threat due to its devastation on pig production [ 1 ]. Its causative pathogen is African swine fever virus, which is a DNA virus belonging to the family Asfarviridae , genus Asfivirus . The virus can survive for a long time in the contaminated environment [ 2 , 3 ], which leads to a broad range of clinical signs in sick domestic pigs, such as sudden death, high fever, haemorrhage, anorexia, dyspnea and vomiting, with the lethality rates approaching 100% when highly pathogenic strains infect pigs [ 4 ]. ASF is listed by the World Organization for Animal Health (OIE) as a notifiable animal disease ( https://www.oie.int/en/disease/african-swine-fever/ ).

African swine fever was first reported in eastern Africa in 1921 [ 5 ]. Since then, additional cases have been reported in most of the Sub-Saharan countries [ 6 , 7 ]. In 1957, ASF was found in Europe, arriving in Portugal from Angola via contaminated swill from aircraft [ 8 ]. It then continued to spread to Western European countries (i.e., Spain), the Caribbean, and Brazil. The disease was eradicated in these places in the mid-1990s through culling and movement bans of live pigs and pig products, except for the Italian island of Sardinia [ 9 – 11 ]. In 2007, the disease was reported in the Republic of Georgia, a transportation hub of Europe, and then it spread widely in the vast areas of Eastern Europe, including Russia (2007), Ukraine (2012), Belarus (2013), Lithuania (2014), Estonia (2014), Poland (2014), Latvia (2014), and Romania (2017), and Czech Republic (2017) [ 6 , 12 – 15 ]. In 2018, ASF was detected in China for the first time [ 16 ]. Since then it spread to more Asian countries, including Vietnam, Cambodia, North Korea, Laos, Indonesia, Myanmar, Philippines and South Korea [ 17 – 19 ]. No commercial vaccines and effective treatments are available to control the disease [ 20 , 21 ].

In order to predict and control for the further spread of the disease beyond the existing geographic range, predictive models linking the locations of the reported cases to environmental risk factors were adopted to improve the risk-based surveillance and control [ 9 , 22 – 24 ]. For example, Cappai et al. combined biological and socio-economic factors with the negative binomial regression model to estimate the ASF risk in Sardinia [ 9 ]. A study conducted by Liang et al. showed that ASF is associated with precipitation based on several machine learning methods [ 23 ]. Based on the data of 98 ASF cases reported from 2018 to 2019 in China, Ma et al. employed a maximum entropy model using pig density and various meteorological covariates to identify the high risk areas for the disease outbreaks in China [ 24 ]. Although several environmental risk factors have been identified in previous studies, the difference in the risk of ASF in domestic pigs and wild boars was not assessed.

To address these limitations, we assembled contemporary records of ASF in both domestic pigs and wild boars, and paired them with a set of livestock density, anthropogenic and habitat correlates to quantify the risk factors. The risk of ASF was predicted at a global scale using a modeling framework. Additionally, we estimated the potential burden of ASF in countries, providing novel insights to inform global, regional and national health authorities who are developing control strategies for the disease.

Materials & methods

The data on ASF cases were downloaded from the website of the EMPRES Global Animal Disease Information System (EMPRES-i) of the Food and Agriculture Organization (FAO) of the United Nations ( http://empres-i.fao.org/eipws3g/ ), which has been designed to support veterinary services by facilitating the organization and access to regional and global disease information. The cases of ASF were collected from European Commission, FAO officers, national authorities and OIE. In this study, the ASF cases (16,550) spanned from 2005 to 2019 were used, of which 12,089 occurred in wild boars, 4,502 occurred in domestic pigs and 41 co-occurred in both wild boars and domestic swine over the world.

Spatial predictor variables.

Livestock factors . Domestic pigs play a key role in the transmission of ASF [ 25 ]. Direct contact between sick and susceptible domestic pigs have been considered to be an effective and important transmission route for this disease, which are likely to be significant in the disease persistence in endemic areas as well as sporadic outbreaks or introduction into disease-free zones [ 26 – 28 ]. In addition, previous literature have suggested that pig density distribution is associated with the occurrence of ASF [ 24 , 29 ]. Thus, in this study, the density of domestic pigs was considered to be an important livestock factor, and was downloaded from the Food and Agriculture Organization ( http://www.fao.org/livestock-systems/global-distributions/pigs/en/ ).

Anthropogenic factors . Human activity (e.g. trade and travel) can lead to transmission of ASF over both short and long distances [ 25 , 30 ]. African swine fever virus in infected animals and contaminated fomites or products may lead to transboundary or even transcontinental spread of ASF [ 31 ]. For example, an ASF outbreak in Georgia in 2007 was caused by improper disposal of contaminated pork meat from a ship at docks [ 31 ]. Moreover, a study conducted by Gulenkin et.al also suggested that the density of road networks was one of the risk factors for disease spread [ 32 ]. Population density and night-time lights could reflect the level of urbanization, and urban accessibility could imply the frequency of trade to some extent. In the present study, we assumed that population density, night-time lights and urban accessibility as three anthropogenic factors that may affect the disease transmission in our boosted regression tree (BRT) model. The data sets of urban accessibility, population density and night-time lights, can be obtained free from the European Commission Joint Research Centre (ECJRC) ( http://forobs.jrc.ec.europa.eu/ ), the Socio-economic Data and Applications Center, NASA ( https://earthdata.nasa.gov/eosdis/daacs/sedac ), and the Earth Observation Group, NOAA ( http://www.earthobservations.org ) respectively.

Habitat factors . Habitat factors play important roles in limiting the distribution of hosts, thereby affecting the risk of disease transmission. Domestic pigs, wild boars and soft tick vectors as hosts for ASF virus, have been shown to be significantly associated with the presence ASF [ 25 , 28 , 32 ]. On this basis, the habitat distribution of these hosts is supposed to be influenced by climate conditions such as precipitation and temperature according to some previous literatures [ 24 , 33 – 36 ]. In addition, land cover, elevation and NDVI also probably influence the distribution of hosts by affecting the food and habitats of hosts, for example, the bushes created habitats for ticks [ 37 ]. Hence, land cover, elevation, NDVI and climate conditions (mean temperature, water vapor pressure and annual cumulative precipitation) were supposed to be potential habitat variables for ASF presence in this study. The dataset of land cover, elevation and normalized difference vegetation index (NDVI) were obtained from NASA’s Earth Observatory Group ( https://earthobservatory.nasa.gov/ ), the CGIAR Consortium for Spatial Information ( http://srtm.csi.cgiar .org), and the Global Inventory Modelling and Mapping Studies (GIMMS) group ( https://ecocast.arc.nasa.gov/ ). Climate data including mean temperature, water vapor pressure and annual cumulative precipitation can be downloaded from WorldClim database, version 2 ( http://www.worldclim.com/ ).

Modelling analysis

Where y is the response, X = { x 1 , x 2 ,⋯, x n } denotes livestock, anthropogenic and habitat factors, f t ( X ) refers to the mapping function from X to y during the t-th iteration, λ is the learning rate, ρ t is the weight parameter, h ( X ; a t ) represents an individual tree. The parameters were estimated by minimizing a binomial loss function ( Eq 2 ).

The assembled contemporary records of ASF cases of both domestic pigs and wild boars were rasterized to grid cells to match the spatial resolution of predictor variables ( S1 Table ) of approximately 5 km × 5 km. According to the contingency plan ( http://www.moa.gov.cn/govpublic/xmsyj/202104/t20210429_6367009.htm ) published by Ministry of Agriculture and Rural Affairs of the People’s Republic of China, regions extending 13km radially away from where ASF cases are reported are designated high-risk zones for domestic pigs, while in wild boar infection areas, they require 40km further extension. In total, we obtained 1,914 and 3,520 samples of high ASF risk for domestic pigs and wild boars respectively. In the present study, areas outside the high-risk zones are determined to be low-risk, which were used as basis for pseudo-absence samples. In order to reduce the impact of the number of pseudo-absence samples on modeling procedure, the ratio of pseudo-absences to occurrence high risk samples is set to 0.5, 0.75, 1, 1.25, 1.5 and 2, respectively [ 42 ]. For each ratio, pseudo-absences samples were selected at random, and the process was conducted 25 times. During each modeling procedure, pseudo-absences samples and occurrence high risk samples were merged into a total sample, then divided into training samples (75%) and validation samples (25%). According to the suggestion of Jiang et al. [ 43 ], the main parameters were set as follows: tree.complexity as 4, learning.rate as 0.005 and max.trees as 10,000. In order to avoid over-fitting, the 10-fold cross-validation method was employed to select the optimal number of trees for each BRT model. An ensemble BRT was constructed using 150 sub-models, which was used to generate the mean infection risk level map (risk level ranging from 0 to 1) for domestic pigs and wild boars respectively. In the present study, the area under the curve of the receiver operating characteristic plot (AUC-ROC) and the relative contribution (RC) were adopted to quantify the performance of the ensemble BRT models and the importance of spatial predictor variables, respectively.

Global distribution of African swine fever

Fig 1A shows the locations of all the 16,550 ASF cases spanning from 2005 to 2019, from which we could conclude that the disease mainly occurred in western Europe, Africa, and eastern Asia, affecting 52 countries. There have been cases of domestic pigs infected with ASF in 48 countries (accounting for 92% of the total number of infected countries), and wild boars infected with ASF in 23 countries (accounting for 44% of the total number of infected countries). Fig 1B shows the number of reported ASF cases globally by year (from 2005 to 2019). During this period, the number of ASF cases showed an overall increasing trend, from 3 cases in 2005 to 6,357 in 2019. Among all ASF cases, 27% of them were derived from domestic pigs, and 73% were from wild boars.

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(A) The global distribution of 16,550 African swine fever cases from 2005 to 2019. Locations are classified by the type of pigs: domestic pigs (blue dots); and wild boars (yellow triangles). (B) The number of African swine fever cases globally over time (2005–2019).

https://doi.org/10.1371/journal.pone.0267128.g001

Relative contribution of risk factors

The relative contribution (RC) of livestock, anthropogenic and habitat predictor variables were quantified by the ensemble BRT models, as shown in Table 1 . For the risk of ASF derived from domestic pigs, the most noteworthy predictor variables were, in decreasing order of RC values, domestic pig density (RC 43.807%), water vapor pressure (RC 13.678%), urban accessibility (RC 11.512%), land cover (RC 10.255%), mean temperature (RC 6.173%) and elevation (RC 4.483%). Whilst annual cumulative precipitation (RC 2.855%), population density (RC 2.811%), NDVI (RC 2.371%) and nighttime light (RC 2.054%) did not substantially contribute to the ensemble BRT models fitted from ASF cases in domestic pigs. For the risk of spread of ASF derived from wild boars, water vapor pressure (RC 56.388%), mean temperature (RC 28.547%), NDVI (RC 4.138%), urban accessibility (RC 3.803%) and elevation (RC 3.097%) were the main predictor variables, and the RC rate of the remaining variables was less than 3%. In total, livestock factor (RC 43.807%) had high relative influence statistics for the spread risk level of ASF derived from domestic pigs, while the RC of habitat predictor variables (95.015%) was higher in the ensemble BRT models fitted from wild boars ASF cases. In the present study, correlation matrix and variance inflation factor (VIF) were calculated for collinearity test, as shown in S2 and S3 Tables. Generally, the values of VIF are less than 10, indicating that there is no collinearity between independent variables.

https://doi.org/10.1371/journal.pone.0267128.t001

Global spread risk of ASF

Maps showing the predicted global potential infection risk of ASF are presented in Fig 2 . The potential high spread risky zones of ASF derived from domestic pigs are predicted to occur in all continents except Antarctica, with hot spots in western Europe, tropical and sub-tropical areas of Africa and South America, tropical and temperate North America, southern and eastern Asia, and coastal Oceania. By contrast, the distribution of predicted risk areas derived from wild boars will be confined to Europe, central North America (mainly concentrated in the United states), and relatively few areas in eastern Asia (parts of China, Korea and Japan). In total, the potential distribution of predicted risk areas derived from domestic pigs shows a wider geographical distribution than that derived from wild boars. Validation statistic index revealed that the ensemble 150 BRT models indicate a high performance in quantifying the spread risk level of ASF derived from domestic pigs (AUC-ROC of training dataset 10-fold-cross: 0.957 ± 0.003; AUC-ROC of validation dataset: 0.957 ± 0.007) and wild boars (AUC-ROC of training dataset 10-fold-cross: 0.992±0.001; AUC-ROC of validation dataset: 0.991±0.002). We also generated the predicted spread risk maps using the 95% confidence intervals of the ensemble BRT models, as shown in S1 and S2 Figs.

Maps of global spread risk level for African swine fever, ranging from 0 (grey) to 1 (red), which were derived from domestic pigs (A) and wild boars (B) respectively.

https://doi.org/10.1371/journal.pone.0267128.g002

The number of domestic pigs at risk

We calculated the number of domestic pigs located in an area at risk of ASF by combining the global predicted disease infection risk map with the fine-scale global domestic pig population surface. First, the threshold predicted risk values of 0.63 and 0.88 were adopted to convert our predicted infection risk maps ( Fig 2 ) into binary surfaces ( S3 Fig ), which were determined to incorporate 90% of all the ASF case locations derived from domestic pigs and wild boars respectively. Every 5 km x 5 km pixel in the risk map with a value above the threshold value was considered at risk for ASF infection. Next, we multiplied the generated binary risk maps by the global domestic pig population surface, and finally we summed across all grids by continents (countries) to estimate the population at risk. Table 2 listed the domestic pig population (thousands) at risk of ASF transmission for each continent and the top five countries contributing to the potential domestic pig population at risk. We summed the swine populations at risk and have identified about 1,388 million (52% of the total swine population) swine globally living within areas that are suitable for ASF transmission. Asia contributes most of the pig population at risk globally, with 588.6 million head, of which China holds an important share (423 million). There are about 433 million pigs at risk in Europe, with half of those living in Germany, Spain, Poland, France and Demark. In the Americas, more than 340 million pigs live in the ASF risk zones, with approximately 48 percent of the population living in the United States. About 22 million pigs living in Africa are at risk of ASF, of which countries of Nigeria, Uganda and South Africa accounting for 50 percent. In Oceania, roughly 4.8 million pigs are living in risky areas for ASF, the largest proportion of which live in Australia (about 4 million).

https://doi.org/10.1371/journal.pone.0267128.t002

ASF is sweeping the global pig industry [ 44 ]. However, the potential geographic extent of ASF infection zones is unknown, as are the risk factors associated with it. Based on a modelling framework, we paired the assembled contemporary records of ASF cases with a set of livestock, anthropogenic and habitat correlates to quantify the risk factors and the risk of potential spread of ASF worldwide. Given the high cost of active surveillance and the limited resources of veterinary services in some countries [ 45 , 46 ], risk-based surveillance can save costs and help allocate limited resources reasonably to maximize utility. This study provided an important baseline for monitoring the risk of spread of ASF by estimating a possible range of infection zones and the number of domestic pigs in at-risk areas.

The predicted infection risk maps reveal that ASF has the potential to be spread to many parts of the world, especially in the northern hemisphere. For instance, in the United States, the potential geographic extent of ASF derived from domestic pigs or wild boars are mainly distributed in several states in the northeast, such as Wisconsin, Illinois, Indiana, Michigan, Ohio, Pennsylvania and New Hersey. The potential geographic extent of ASF derived from domestic pigs is different from that for wild boars. The former is influenced strongly by density of domestic pigs, while the latter is associated with natural habitat covariates. In addition, the pixel-level uncertainty of the ensemble BRT models was also quantified using the standard deviation method, as shown in S4 and S5 Figs. The uncertainty maps suggest that the uncertainty of the ensemble BRT approach is low as a whole.

Several previous literatures have linked climate-related covariates to the presence of ASF [ 23 ]. These climate factors affect the habitat distribution of wild boars and soft ticks [ 24 , 33 – 36 ], which could reflect the spatial distribution of the diseases to a certain extent. Compared with these studies, we used more abundant spatial covariates (i.e., anthropogenic and natural habitat factors), and combined with BRT modeling procedure to specifically mine the complex relationships between spatial covariates and the presence of African swine fever, as presented in S6 and S7 Figs. For example, domestic pig population is positively associated with the occurrence of ASF in domestic pigs, while there is a negative relationship between domestic pig population and ASF derived from wild boars.

By combining the domestic pig population maps with the estimated risk maps, we estimated that nearly half of the world’s domestic pigs (1.388 billion) is raised in the predicted high-risk zones. Given there are no commercial vaccines available to eradicate ASF, improving biosafety in pig farms is currently the best way to prevent the disease [ 47 ]. For the endemic zones, it is suggested that all pigs in the case farms should be slaughtered quickly, and safe disposal should be applied to all dead and slaughtered pigs and relevant products. The contaminated materials (i.e., excreta, leftover feed and sewage) should be cleaned and disposed of safely. The importation and exportation of susceptible animals and related products should be suspended when needed. For the areas belonging to the predicted high-risk zones, it is necessary to strengthen biosafety education to not only pig farmers but the public. This is important for the prevention of ASF and to improve the awareness of biosafety in pig farms. For example, protection measures should be taken to prohibit feeding of unheated swill to pigs, and avoid domestic pigs having contact with wild boars and soft ticks. In addition, quarantine should be carried out in pig farms during introduction, to reduce the risk of ASF.

There are some limitations in this study. First, considering not all continents have the same sensitive surveillance system, the notified cases in several zones (i.e., Africa) may be under-estimated, which may bring some uncertainty to the analysis. Secondly, the estimated spread risk maps can be interpreted to predict the potential geographic extent of ASF in the world, rather than where the disease will be spread in the future. A strong spatio-temporal prediction of the geographic distribution of ASF spread requires data on the movement of live pigs and pork products, farm management and migration of wild boars, which were not yet available when conducting this study. For future work, we will cooperate with multiple business units to collect more data (i.e., the movement of pigs and pork products, and farm management) to improve the model. Besides, we will combine the profits and costs of domestic pig production to evaluate the economic losses that ASF may lead to on country and global scale.

Supporting information

S1 fig. the global spread risk level for african swine fever derived from domestic swine..

https://doi.org/10.1371/journal.pone.0267128.s001

S2 Fig. The global spread risk level for African swine fever derived from wild boar.

https://doi.org/10.1371/journal.pone.0267128.s002

S3 Fig. Binary maps of global spread risk level for African swine fever.

https://doi.org/10.1371/journal.pone.0267128.s003

S4 Fig. The uncertainty of the predicted risk level derived from domestic swine based on the ensemble BRT model.

https://doi.org/10.1371/journal.pone.0267128.s004

S5 Fig. The uncertainty of the predicted risk level derived from wild swine based on the ensemble BRT model.

https://doi.org/10.1371/journal.pone.0267128.s005

S6 Fig. The relationships between spatial covariates and the presence of African swine fever derived from domestic swine over all boosted regression tree (BRT) ensembles.

https://doi.org/10.1371/journal.pone.0267128.s006

S7 Fig. The relationships between spatial covariates and the presence of African swine fever derived from wild boar over all boosted regression tree (BRT) ensembles.

https://doi.org/10.1371/journal.pone.0267128.s007

S1 Table. Spatial predictor variables adopted in this study.

https://doi.org/10.1371/journal.pone.0267128.s008

S2 Table. Correlation matrix between covariate variables used in BRT ensembles trained on domestic swine samples.

https://doi.org/10.1371/journal.pone.0267128.s009

S3 Table. Correlation matrix between covariate variables used in BRT ensembles trained on wild boar samples.

https://doi.org/10.1371/journal.pone.0267128.s010

Acknowledgments

We thank Qiaoling Zhu for providing valuable suggestions and myriad research staff who participated in compiling the most comprehensive occurrence dataset of African swine fever.

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Systematic review article, new perspective on african swine fever: a bibliometrics study and visualization analysis.

• 1 Department of Hematology, West China Hospital, Sichuan University, Chengdu, China
• 2 State Key Laboratory of Wildlife Quarantine and Surveillance (Sichuan), Technology Center of Chengdu Customs, Chengdu, China

Introduction: African swine fever (ASF) is a contagious viral disease that can have devastating effects on domestic pigs and wild boars. Over the past decade, there has been a new wave of this ancient disease spreading around the world, prompting many scholars to dedicate themselves to researching this disease. This research aims to use bibliometric methods to organize, analyze and summarize the scientific publications on ASF that have been amassed in the past two decades.

Methods: This paper used VOSviewer, CiteSpace, and a bibliometric online analysis platform to conduct performance analysis and visualization studies on 1,885 academic papers about ASF in the Web of Science from January 2003 to December 2022.

Results: The amount of literature published on ASF has increased exponentially in recent years, and the development trend of related research is good. A group of representative scholars have appeared in this research field, and some cooperative networks have been formed. Transboundary and Emerging Diseases is the journal with the most publications in this field, while Virus Research is the journal with the most citation per article. High-productivity countries are led by China in terms of the number of articles published followed by the United States and Spain. In regard to the average number of citations, the scholars in the UK are in the lead. The institution with the most articles was the Chinese Academy of Agricultural Sciences. The analysis of high-frequency keywords showed that the pathogens and epidemiology of ASF were the research hotspots in this field, and the research content was closely related to molecular biology and immunology. The burst keywords “transmission”, “identification”, “virulence”, “replication”, and “gene” reflects the research frontier. In addition, by collating and analyzing highly cited journals and highly co-cited references, we explored the knowledge structure and theoretical basis of this field.

Discussion: This is the first bibliometric analysis report on ASF research, which highlights the key characteristics of ASF research and presents the research status and evolution trend in this field from a new perspective. It provides a valuable reference for further research.

1. Introduction

African swine fever (ASF) is an acute hemorrhagic fever caused by the African swine fever virus (ASFV), which is a large double-stranded DNA virus in the family Asfarvirida ( 1 , 2 ). Hyperacute and acute forms of ASF result in nearly 100% mortality in domestic pigs ( 3 , 4 ), and no reliable commercial vaccine is currently available ( 5 – 8 ). ASFV is hosted by both suids and soft ticks from the genus Ornithodoro s. It can be maintained for extended periods in Ornithodoros ticks and replicated to high titers ( 9 ). The existence of the virus in nature can be long-term and stable by the infection of warthogs and possibly other wild suids, which is difficult to eradicate from Africa ( 10 ).

The disease was first identified in East Africa in the early twentieth century ( 11 ), and it spread from Africa to Europe twice in 1957 and 1960 and then to the Americas. Outbreaks were not eradicated until the mid-1990s, except in Africa and Sardinia ( 12 , 13 ). In 2007, ASF was first introduced to Georgia from sub-Saharan Africa ( 14 ) and then spread to the Russian Federation and the European Union ( 15 – 17 ). For the first time, ASF also spread to China, a major pork producer and consumer, in 2018 ( 18 , 19 ). In addition, cases of infection have also been detected in Southeast Asia and other parts of Asia ( 20 ). In 2021, ASF reappeared in the Americas ( 21 , 22 ). Although the disease does not pose a threat to human health, due to its high mortality rate to domestic pigs, large-scale culling operations covered by disease control regulations, restrictions on pork imports and exports, and many other factors, ASF has a serious impact on the global pig industry, people's livelihood, world trade, and food security. According to the forecast, if epidemics were to start in Denmark, there would be significant economic damage, with €12 million in direct costs and €349 million in export losses ( 23 ). If a piggery unit experiences an outbreak of ASF, it can expect to lose an estimated $910,836.70 per year ( 24 ). Therefore, ASF has been of high concern to scholars all over the world in recent years, and relevant research has also achieved fruitful results.

In this context, we used bibliometric methods to conduct a comprehensive collation of ASF research over the past two decades, analyzed the knowledge structure and quantitative information in the field, and provided performance analysis and visualization maps. The map was used to explore the internal relations between the information, and it showed the research focus and the evolution trend in recent years to provide a scientific reference for related research on ASF.

2. Methodology

2.1. research methods.

Bibliometrics is a quantitative research method that uses mathematical and statistical methods to review and describe published literature in a particular field ( 25 ). This research method can obtain and analyze important information such as the details of publication authors, keywords, journals, institutions, countries, and references. The results will help to understand the development trend of a scientific field, research focus, and researcher cooperation relationships ( 26 ). Furthermore, the use of computer technology to present results graphically and visually can help to uncover hidden relationships within the data and make the results more comprehensive ( 27 ).

Data visualization technology is a very important research method and means in bibliometrics. VOSviewer and CiteSpace are two commonly used data visualization analysis software programs. Using VOSviewer, a large-scale bibliometric map can be constructed to reflect the importance of items such as authors, keywords, institutions, and the strength of relationships with adjacent items through label views, density views, cluster density views and scatter views ( 28 ). CiteSpace is a Java application for analyzing and visualizing co-citation networks. It can divide a time interval into several time slices, from which individual co-citation networks can be obtained to highlight the main changes between adjacent time slices ( 29 ). Moreover, CiteSpace can detect and visualize trends and changes in science over time. It can be used to explore the dynamics of a profession, that is, the mapping of temporal changes from its knowledge base to the research frontier ( 30 ). Therefore, VOSviewer version 1.6.18 and CiteSpace version 6.1.R6 were used in this study to conduct a bibliometric analysis of ASF-related academic publications. In addition, BiblioShiny, a software package running in R language, and an online analysis platform of bibliometrics were used as complementary methods in this study.

2.2. Data sources

This study delimits the scope of analysis, employs a strict literature search strategy, and selects the Web of Science (WoS) as the data source. The WoS includes relevant material from a wide range of research fields and is a high-quality digital database that is widely accepted by researchers around the world ( 31 ). It exceeds other databases in functionality and complexity, with historically greater coverage ( 32 ).

The Web of Science Core Collection (WoSCC) was selected as the data source for this particular study. The Science Citation Index Expanded was chosen, and the retrieval strategy was to use “African swine fever” as the subject search term to guarantee the comprehensive and precise retrieval of data. Additionally, the time horizon was set from January 1, 2003, to December 31, 2022. The initial search identified 2,132 relevant articles, including all document types. Considering the completeness of the literature information, the literature types were selected as articles and review articles, and the language was restricted to English for ease of analysis. Finally, 1,885 valid papers were obtained. Retrieved publications were exported as plain text files with “full record and cited references”, which were uploaded to the VOSviewer and CiteSpace for analysis under the name “download_X.txt”. The selection process is detailed in Figure 1 .

Figure 1 . The publications selection process for this bibliometric analysis study.

3.1. Performance analysis

The 1,885 articles used in this study come from 7,621 authors affiliated with 2,021 institutions in 111 countries/regions. These articles were published in 338 journals and cited 46,521 references from 12,358 journals. The number and the cumulative number of papers published in different periods can reflect the development trend of this research field. In the past two decades, the temporal distribution of 1,885 articles in the ASF research field is shown in Figure 2 . Although the annual publication volume did not change much before 2013, which was < 40, on the whole, the number of publications in this field is on the rise. The number of publications has increased significantly, especially after 2018. More than 150 articles were annually published for four consecutive years from 2019 to 2022, and the increase was large. In 2018, ASF spread to China, the world's largest pig breeder, sparking a research boom among researchers in this field. Linear regression analysis was carried out on the publication time of the literature and the annual cumulative number of publications, R 2 = 0.9629. The model fitting effect is good, which is in line with the scientific exponential growth law proposed by Price, that is, various scientific indicators increase approximately exponentially with time ( 33 ). This shows that the relevant research on ASF is currently in a period of rapid development, and the speed of achievement output and literature publication is also accelerating.

Figure 2 . Distribution of publications on African swine fever (ASF) from 2003 to 2022.

3.2. Analysis of prolific authors

To understand the representative scholars and main research teams, this paper studies the top 11 scholars with the number of publications, as shown in Table 1 . Sandra Blome, a virologist from the Friedrich Loeffler Institute in Germany, published the most papers over the past two decades (75 articles, 3.98%, 25.37 average citation per article). Linda Dixon of the Pirbright Institute in the UK was second in the number of publications (64 articles, 3.40%, 64.66 average citation per article). Carmina Gallardo, a Spanish scholar from the European Union Reference Laboratory for ASF, ranked third (55 articles, 2.92%, 50.53 average citation per article). Based on the WoS, the H-index is a useful indicator to assess the impact and productivity of certain countries/regions, institutions, or scientists in an academic field ( 34 ). It can be simply expressed as H publications were cited no less than H times. For example, a scientist with an H-index of 30 means that he has 30 papers that have been cited at least 30 times. It has mostly become an objective measure of scientific achievement. According to statistics, the top 3 authors for the H-index in this study are Linda Dixon (H-index = 40), Carmina Gallardo (H-index = 34), and José Manuel Sánchez-Vizcaíno (H-index = 30). Dr. Sandra Blome is responsible for the Germany National Reference Laboratories for African and classical swine fever. Her research focuses on the pathogenesis of viral infectious diseases such as classical swine fever and ASF ( 35 , 36 ), especially the mechanism of virus–host interaction and the development of vaccines ( 37 ). Dr. Linda Dixon's research focuses on the functional genomics of ASFV(1) and the mechanisms of immune evasion and pathogenesis ( 38 ), and her research team has also been committed to the research and development of effective vaccines ( 39 ). Dr. Carmina Gallardo's main expertise is in ASF research, mainly involving new diagnostic tools, molecular epidemiology, epidemic control strategies and vaccine research ( 40 , 41 ). Professor Sánchez-Vizcaíno's research has been vital in the fight against various animal diseases, such as ASF, African horse sickness, and classical swine fever. His work has enabled the development of new techniques, quick and accurate diagnostic tools, innovative epidemiologic approaches, and novel vaccine strategies ( 42 , 43 ).

Table 1 . The top 11 authors with most publications related to African swine fever (ASF).

To highlight the collaboration between the core authors in the field, authors with more than 5 publications are visualized in Figure 3 . The size of each node in the figure represents the number of articles published by each author, and the thickness of the connecting line represents the strength of cooperative publishing between authors. Each color represents a cluster, and authors whose nodes are of the same color cooperate closely. We can see that the authors have formed multiple research groups based on their cooperative relationships, indicating that scholars in this field have a certain consensus basis on ASF. Overall, the representative scholars in this field are mainly from Europe and the United States, and they have formed their cooperation networks, and the communication and cooperation between the groups are relatively close. Although Chinese scholars also performed well in this field, only many small cooperative clusters were formed, and no good cooperation network has formed between the various groups.

Figure 3 . The network map of co-authorship related to ASF.

3.3. Most active journals

Statistics on the journals that published the literature show that articles on ASF research have been mainly published in 338 journals in the past two decades. By setting the minimum number of documents to 5, we obtained the co-occurrence map of journals as shown in Supplementary Figure S1 . The more published articles, the brighter the color. Conversely, the smaller the number of publications, the darker the color. The top 10 journals published a total of 824 articles, accounting for 43.71%. Table 2 shows the top 10 journals in terms of publication volume, which are mainly professional journals in the field of veterinary sciences and virology, and some interdisciplinary comprehensive journals. Journals that have published more than 100 articles about ASF in the past two decades include Transboundary and Emerging Diseases (203, accounting for 10.77%, 21.85 average citation per article, Q1), Viruses-Basel (137, accounting for 7.27%, 11.77 average citation per article, Q2), and Frontiers in Veterinary Science (106, accounting for 5.62%, 8.66 average citation per article, Q1). In particular, Transboundary and Emerging Diseases and Frontiers in Veterinary Science are the top journals in the field of veterinary sciences. The former favors content on novel scientific approaches to the causes, control and prevention of cross-border and emerging diseases. The latter is the third most cited journal in the field, covering almost all veterinary sciences such as animal infectious diseases, genomics, veterinary public health, and the exploration of new treatments. The journal with the most average citation is Virus Research , with a total of 50 articles published and an average of 60.20 citation per article, indicating that this journal has received more attention in the field of ASF research. Its publications consist primarily of original research papers in the field of viral molecular science, review articles, and special issues on specific topics. Book reviews, editorials and conference presentations are also occasionally accepted.

Table 2 . The top 10 journals with most publications related to ASF.

Among the top 10 journals with the most publications related to ASF, Journal of Virology had the highest impact factor (IF 2021 = 6.549), followed by Virus Research (IF 2021 = 6.286) and Viruses-basel (IF 2021 = 5.818), and these three journals belong to Q2 of Journal Citation Reports (JCR) virology category. In addition, the three journals with the highest H-index are: Transboundary and Emerging Diseases (H-index = 36) followed by Journal of Virology (H-index = 33) and Virus Research (H-index = 32), their published articles related to ASF had an important influence on this field. The publishing regions of the top 10 most productive journals are all from Europe or the United States, while the Netherlands and Switzerland have 3 each and the United States has 2, indicating that journals from Europe and the United States have been instrumental in advancing this field of research.

3.4. Contribution of countries/regions

To understand the contribution and cooperation of various countries/regions in the field of ASF research, we analyzed the number of publications of 111 countries/regions that have been identified. First, VOSviewer was used to visualize the top 20 countries/regions with the most publications, and then SCImago Graphica version 1.0.23 is used to visualize the geographical distribution, as shown in Figure 4A . The nodes in the figure represent the number of articles published by the countries, and the larger the node is, the more articles are published by the country. The line represents the strength of the association, and the thicker the line is, the greater the number of published articles in cooperation between the two countries. The colors of the nodes represent different clusters, and the cooperation between countries of the same color is relatively close. It can be seen in the figure that countries with high publication volume form four obvious clusters, indicating that there is a stable cooperative relationship between countries. The top 10 countries/regions by publication volume are presented in Table 3 . Through the analysis of the data and the visual map, it can be seen that China published the most articles in the field of ASF (401, 4,965 citations, 12.38 average citation per article), but the frequency of cooperation with other countries is not high, and the citation per article are relatively low. The second-ranked United States (353, 7,872 citations, 22.30 average citation per article), third-ranked Spain (312, 11,387 citations, 36.50 average citation per article), and fourth-ranked United Kingdom (252, 9,661 citations, 38.34 average citation per article) have more collaborative publications, indicating that they have frequent academic exchanges in this field.

Figure 4 . (A) The geographical distribution and collaboration map of the top 20 countries/regions with publications related to ASF. (B) Multi-country collaboration in the corresponding author's country/region.

Table 3 . The top 10 countries/regions with most publications related to ASF.

To further show the contribution of each country/region in the field of ASF research, we also counted the distribution of the corresponding author's country/region. China remains the most productive country (374, accounting for 19.84%), followed by the United States (238, accounting for 12.63%) and Spain (224, accounting for 11.88%). In addition, SCP represents the number of publications co-authored by authors from the same country, whereas MCP represents the number of papers co-authored with authors from multiple countries. According to the MCP ratio, Poland, as well as China, have a limited level of international collaboration, whereas Kenya is the most engaged as shown in Figure 4B .

3.5. Contribution of institutions

The publications on ASF research included contributions from 2,021 institutions. According to the number of publications statistics, Table 4 presents the top 10 producing institutions. The top 10 institutions each contributed 718 publications, accounting for 38.09%. Institutions in Europe, Africa, North America, and Asia have made outstanding contributions in this field, indicating that ASF is a global problem that has attracted great attention from scientists all over the world. Although the Chinese Academy of Agricultural Sciences has the most publications (115 papers), the number of citation per article is low (16.30 times). The top H-index value at the Pirbright Institute (H-index = 32) and the highest number of citation per article at the University of Pretoria (43.08 times). The VOSviewer presented the knowledge graph of the institutional collaboration network. By setting the minimum number of documents for one institution as 5, the cooperative network graph of 222 institutions was obtained in Figure 5 . There is deep and extensive cooperation between European and American scientific research institutions, while Chinese scientific research institutions cooperate more with domestic institutions. In general, although Chinese scientific research institutions have many publications, the average citation number of articles and the H-index value are not high, and the degree of international cooperation needs to be improved. Among the top 10 institutions, three are from Spain, indicating that the country's scientific institutions have made an outstanding contribution. In addition, scientific institutions in African are an important force in the field of ASF research.

Table 4 . The top 10 productive institutions ranked by number of publications related to ASF.

Figure 5 . The visualization network map of institutional collaboration.

3.6. Keyword analysis

3.6.1. high frequency keyword analysis.

In a subject area, the topics that scholars are concerned about, having internal connections, and being relatively large in number may be the research hotspots in this field. As a refined expression of research topics and content in academic papers, keywords can reflect the research hotspots in the subject area to a certain extent. The analysis of keywords in the research literature can be used to analyze the evolution of research hotspots.

CiteSpace was used to divide the analysis objects by 1 year per slice, the node type was selected as keyword, and the cosine algorithm was used to select the association strength of network nodes within slices. The threshold (top N) was set as 10, that is, the top 10 of high-frequency keywords in each time slice were extracted. The pathfinding algorithm was chosen in this study, pruning sliced network and pruning the merged network are used to show a clearer co-occurrence network. Table 5 lists the top 20 high-frequency keywords retrieved by CiteSpace to current research, identifying certain established themes and terra incognita in the given research area. Through keyword analysis, in addition to the search terms “African swine fever”, this study also presented keywords related to ASF pathogens, such as “African swine fever virus,” “virus,” “protein,” and “virulence”. Keywords of molecular biological and immunological research related to ASF, such as “gene,” “replication,” “identification,” and “sequence”. Keywords related to ASF epidemiological, such as “epidemiology,” “transmission,” “outbreak,” and “risk factor”. There are also keywords related to the host of ASF, such as “domestic pig” and “wild boar”.

Table 5 . The top 20 keywords for frequency related to ASF.

The keyword co-occurrence network in the ASF research field consisted of 165 nodes and 659 links, each node representing a keyword. The larger the node, the higher the frequency of the keyword. Similarly, the color of the node reflects time: the warmer the color, the more recent the time, and the colder the color, the more distant the time. The keyword co-occurrence network diagram was shown in Figure 6B . In addition, to verify the reliability of the core keywords, BiblioShiny was also used to generate the keyword cloud, larger fonts indicate a higher frequency of occurrence ( Figure 6C ), and it can be seen that the core keywords are roughly the same as those summarized above. The year-by-year evolution of the commonly used keywords is shown in Figure 6D .

Figure 6 . (A) The visualization map of keyword clusters related to ASF. (B) The visualization map of keyword co-occurrence network related to ASF. (C) The keywords cloud. (D) Trends of the main keywords over time.

3.6.2. Keyword cluster analysis

Keyword clustering is to form some small groups of closely related keywords, to realize the purpose of mining hidden information. It probed certain themes that have been established or may have been overlooked in a particular area of study. In this study, CiteSpace was used to perform keyword clustering analysis based on keyword co-occurrence, using the Log-likelihood Ratio (LLR) algorithm to perform cluster labels extracted from the publications keyword ( Figure 6A ). In the cluster graph, the presence of cross-clustering indicates that they are closely related. In general, there are two important metrics to evaluate the effect of cluster formation. The modularity Q is used to evaluate the goodness of the network modularity, and a higher value indicates a better cluster obtained by the network. Q > 0.3 means that the resulting cluster structure is significant. The cluster silhouette value S is used to measure the homogeneity of cluster members, S > 0.5 can be considered as a high consistency of cluster members and the clustering result is reasonable, and S > 0.7, the result has high credibility. The Q -value of Figure 6A was 0.7647, and the S -value was 0.8754, indicating that the clustering structure is significant, and the clustering results are convincing. In the past two decades of ASF studies, 10 meaningful clusters were formed. Sort the clusters from #0 to #9, the smaller the number, the more keywords are included in the cluster, and the details of each cluster are presented in Supplementary Table S1 .

3.6.3. Keywords bursts

By using the keyword burst feature of CiteSpace, one can observe the frequent occurrence of certain keywords within a specific period. The information can not only elucidate the dynamics of research hotspots over time but also expose research trends in recent years ( 27 ).

Keyword burst detection can be used to explore the sudden increase of research interest in a subject. The information can not only elucidate the dynamics of research hotspots over time but also expose research trends in recent years. The top 25 keywords with the strongest citation bursts were detected as shown in Figure 7 . The blue line indicates the year from the beginning to the end of the keyword, and the red line indicates the period when the keyword burst. The stronger the burst strength of the keyword, the more studies related to it. Among the top 25 keywords with the strongest citation bursts, “epidemiology” was the keyword with the greatest burst intensity (Strength = 25.16), a large number of research results are related to this word between 2014 and 2020. At the same time, “endoplasmic reticulum” is the hot keyword with the longest duration (2003–2013). Furthermore, the citation bursts of 5 keywords continued through 2022. Therefore, the 5 burst keywords of “transmission,” “identification,” “virulence,” “replication,” and “gene” reflect the latest research hotspots in the field of ASF.

Figure 7 . Top 25 keywords with the strongest citation bursts.

3.7. Co-citation analysis

The behavior of papers citing other papers can be regarded as the flow of knowledge among different research topics and the process of knowledge reorganization to produce new knowledge ( 44 ). Citation analysis can be used to evaluate the scientific value and influence of publications in a particular field of research and has a significant impact on the discussion, practice, and future research in this area ( 45 ). Moreover, co-citation analysis of cited journals helps to understand key scientific journals in related fields. To understand the most frequently cited papers in the ASF research field and the journals that publish them, as well as the internal relations between them, to obtain the knowledge base source of the research field. In this study, 46,521 references from 12,358 journals were used as data sources to analyze co-cited literature and the journals in which it was published.

3.7.1. Co-citation analysis of cited journals

VOSviewer was used to analyze the citation network among the cited journals. By setting the minimum number of citations for cited journals to 60, we obtained 183 journals, and the co-occurrence visualization map of co-cited journals was shown in Figure 8A . The node labels on the visualization map describe the co-cited journals, and the lines describe their co-citation relationships. Table 6 lists the top 10 co-cited journals related to ASF. Journal of Virology is the most cited journal (5,763 citations, IF 2021 = 6.549, Q2), followed by Transboundary and Emerging Diseases (4,125 citations, IF 2021 = 4.521, Q1) and Virus Research (3,074 citations, IF 2021 = 6.286, Q2). Additionally, Emerging Infectious Diseases is the journal with the highest impact factor (IF 2021 = 16.126), which is the top journal in the field of immunology and has a high authority in the professional field. The dual-map overlay of journals shows the position of a research subject relative to the main research science. Each dot on the map represents a journal, and the labels describe the various research areas covered by all journals. The citing journals are on the left and cited journals are on the right of the map. The colored curve is the citation line, showing the citation relationship, and the width of the curve is closely related to the citation frequency. The longer horizontal axis of the ellipse represents more papers published in the corresponding journal, and the longer vertical axis represents more authors. Figure 8B shows the three main citation paths, indicating that in the field of ASF research, the studies published in veterinary/animal/science categories cited Molecular/Biology/Genetics and veterinary/animal/parasitology Journals. The studies published in Molecular/Biology/Immunology Journals cited Molecular/Biology/Genetics Journals.

Figure 8 . (A) The visualization network map of co-cited journals related to ASF. (B) The dual-map overlay of journals related to ASF.

Table 6 . The top 10 co-cited journals related to ASF.

3.7.2. Co-citation analysis of cited references

In our study, 46,521 references were used as the analysis object, and the minimum number of citations of cited articles was set to 55, so 145 references were obtained for co-citation analysis. The visual analysis of the 145 most frequently cited articles yield three clusters ( Supplementary Figure S2 ).

Among them, cluster 1 (red) is mainly related to the virulence and pathogenicity of ASFV and its influence on the immune response of the host; cluster 2 (green) is more biased toward the review of ASF and some representative research results, covering the basic knowledge of this research field; and cluster 3 (blue) mostly focuses on genetic characteristics and genotype analysis of ASFV, providing technical support for research. The top five cited references of the three clusters are presented in Supplementary Table S2 .

The top three articles in the first cluster were published in Virus Research, Virology , and Journal of General Virology . Dixon et al. ( 1 ) is the most frequently cited (242 times), it summarizes the genome structure of ASFV and basic information about the viral replication mechanism and elaborates on the characteristics and functions of ASFV-encoded genes, providing important theoretical support for other studies. Yáñez et al. presented an analysis of the complete genome of ASFV strain BA71V, and DNA sequence analysis confirmed that ASFV belongs to an independent virus family ( 46 ). Chapman et al. ( 47 ) determined the genome sequences of two ASFV isolates: a non-pathogenic isolate, OURT88/3, and a highly pathogenic isolate, Benin 97/1. These genome sequences were compared with the BA71 V isolate after tissue culture to study the molecular basis of the differences in pathogenicity of different strains, which provides a basis for further attempts to regulate the differences in viral pathogenesis through genome manipulation.

The second cluster focuses on review articles and some representative reports and studies. The first report of ASF received the most citations in this cluster (256 times), the report titled “On A Form of Swine Fever Occurring in British East Africa (Kenya Colony)” drafted by Montgomery from the records of a veterinary pathology laboratory, then known as the case of East ASF, which was first diagnosed in June 1910. The report described in detail the epidemiological characteristics, clinical diagnosis, and immunotherapy process of the disease at that time, which provided valuable information for follow-up research on ASF ( 11 ). A TaqMan-based polymerase chain reaction assay for the detection of ASFV developed by King et al. ( 48 ) received the second most frequently citations in this cluster (255 times). As an effective method in the laboratory diagnosis of ASF, it is recommended by the World Organization for Animal Health ( 49 ). In particular, the reported occurrence of ASF in China in 2018 also appears in this cluster ( 50 ). Moreover, review articles on ASF provide a large amount of comprehensive information for research in this field, present the latest progress and existing problems, and make it easier for readers to understand the dynamics of the discipline.

Publications in the third cluster also received more attention. Rowlands et al. ( 14 ) identified the Georgia 2007 isolate of ASFV and determined that it was closely related to genotype II isolates circulating in Mozambique, Madagascar, and Zambia. This paper has been cited 262 times, making it the most cited reference among all subjects analyzed. A review by Costard ( 51 ) on how to prevent the global spread of ASF has also been highly cited (260 times). Bastos et al. ( 52 ) and Gallardo et al. ( 53 ) also received high citations, with 233 and 122 citations, respectively. These articles collectively focus on genetic characterization and genotype analysis of ASFV.

4. Discussion

4.1. main outcomes.

ASF has been present on the earth for more than 100 years since it was reported for the first time in 1921. In the past 100 years, ASF has caused serious social and economic consequences around the world. To date, there are still many problems in research in this field that urgently need to be solved. Therefore, it has received extensive attention from many scholars around the world. So this is a hot study that is constantly being updated. Based on the information of 1,885 papers on ASF from January 1, 2003 to December 31, 2022, obtained from the WoSCC, this study reviewed the development of this field employing a bibliometric system and visualized the research results through VOSviewer and CiteSpace. We identified the core journals in the field, revealed important authors, contributions of institutions, highly productive countries and their collaborative networks, and explored the keywords, co-cited literature, etc. We also found research hotspots at different times, and keywords involved in these research hotspots are presented.

From the 1,885 published articles related to ASF retrieved from the WoSCC, the number of published articles increased from 16 in 2003 to 400 in 2022. The number of publications on ASF research has increased rapidly over time, indicating that the field is receiving increasing attention. Some renowned scholars have emerged in the research field of ASF, and some author cooperation networks have been established, which play a vital role in promoting the advancement of this field. At present, the author with the most articles on ASF research was Sandra Blome from the Friedrich Loeffler Institute, while Linda Dixon of the Pirbright Institute is the most influential author. The journals that publish ASF-related papers are mainly journals in the professional fields of veterinary science and virology, many of which are top journals in the field of veterinary science. The journal Transboundary and Emerging Diseases has published the most publications in this area, it has great academic influence and high professional recognition in the field of industry segmentation. This also hinted at the ASF research has a high professional level in the field of veterinary science. China ranked first in the number of articles published. In 2018, the first ASF epidemic occurred in China and caused a serious impact, which may have caused a research boom among scholars. Another fact is that although China has the most publications, it is not dominant in this field. European countries and the United States have higher H-index and more citation per paper. Similarly, the international cooperation rate of Chinese scholars is much lower than that of scholars from Kenya, South Africa, France, and other countries from the perspective of multi-country cooperation. This shows that Chinese scholars are very important participants in this research field and have great potential for development, but they still need to strengthen cooperation with foreign research institutions and further improve the research level of ASF through complementary advantages. According to the survey of institutions, the Chinese Academy of Agricultural Sciences has contributed the most articles, while the Pirbright Institute has contributed many high-impact articles. And more, the output and quality of scientific institutions in Spain in the field of ASF research are impressive.

4.2. Hotspots and frontiers on ASF research

Keywords are indicative words that relate to the content of the research topic, which can reflect the research hotspots to a certain extent. The analysis of the literature related to ASF conducted via CiteSpace revealed important keywords, such as “gene,” “epidemiology,” “transmission,” “replication,” “protein,” “identification,” “virulence,” “protection,” “outbreak,” “cell,” “risk factor,” “macrophage,” “sequence,” etc. With the deepening and development of research, the keywords “transmission,” “identification,” “virulence,” “replication,” and “gene” continued to break out until 2022. It reflects that the research related to these keywords is the latest hotspot in the field of ASF.

It can be inferred from the high frequency keywords such as “epidemiology,” “transmission,” “wild boar,” “domestic pig,” and “outbreak” that a significant area of study for ASF is epidemiological research. Molecular biology is commonly employed by researchers as a pivotal tool for the epidemiological investigation of ASF to analyze the characteristics of viral genes and study the dynamic information of the disease. By collecting ASFV strains from domestic pigs and wild boars, researchers have been able to track the genetic variability of ASFV strains over time and understand the distribution of different genetic variants of the virus ( 54 ). Genotyping and phylogenetic analysis of ASFV can be used to determine the likely origin of the virus and to differentiate it from closely related strains ( 55 ). Furthermore, when combined with the phylogeographic approach, we can gain a more intuitive understanding of the transmission modes and dynamics of ASF. This information can then be utilized to implement targeted control strategies in specific regions to prevent the spread of this disease ( 56 ). The keywords “virus,” “protein,” and “virulence” suggested that the research hotspots were also related to the pathogen of ASF. ASFV is a complex nucleocytoplasmic large DNA virus. The uniqueness and complexity of its structure may be the factors that make it difficult to control ( 57 ). Therefore, the study of ASFV structure and protein function is also an important direction in this field. By studying the cryo-EM structure of the ASFV virion, scholars have revealed its important protein structure and the basis of assembly, opening a new way for the development of the ASF vaccine ( 7 , 57 , 58 ). It has also been found that the protein–protein interaction mechanism between ASFV and host pigs is important for studying potential drug targets and predicting the direction of antiviral drugs ( 59 ). By understanding the structure and function of certain ASFV proteins, we can gain insight into how to block the development of this virus, as well as provide dissimilar diagnostic strategies to amplify the level of diagnosis ( 60 – 62 ). Additionally, the study on the infection and immune response mechanisms of ASFV is also a crucial research direction, as evidenced by the clustered keywords such as “macrophages,” “infected cells,” “replication,” “immunologics,” and “mechanisms” (as outlined in Supplementary Table S1 ). The development of ASF may be due to virus-induced changes in the host's immune system, allowing the virus to better adapt to it ( 63 ). The mechanisms by which ASFV evades or inhibits the innate immune system involve the regulation of various complex signaling pathways ( 64 ). For example, through the inhibition of interferon regulatory factor-3 activation and stimulating interferon gene phosphorylation, the ASFV Armenia/07 virulent strain is capable of impeding the synthesis of IFN-β in porcine alveolar macrophages, thereby evading the host's immune responses ( 65 ). Moreover, certain genes of ASFV can regulate the replication of the virus within the host organism. Scholars found that ASFV with deletion of the CD2v and MGF360-505R genes caused significantly less cytopathic effects and apoptosis in PAMs than wild-type ASFV ( 66 ). The keywords “recombinant antigen,” “rDNA technology,” “immunization,” and “vaccinology” (shown in Supplementary Table S1 ) reflect the research focus on vaccines study. Despite the remarkable achievements in ASF research in recent years, we have to face the reality that there is currently not universally accepted safe and reliable ASF vaccine regimen. At present, although researchers have made many explorations into vaccine adjuvants, vaccination methods, and doses, inactivated ASFV vaccines still cannot achieve good protective effects ( 37 , 67 ). The vaccine research program for ASF is more focused on live attenuated virus vaccines and subunit vaccines. The efficacy of live attenuated vaccines has been established, and research strategies include deleting specific genes, naturally attenuated virus isolates, and cell passages. However, their safety profile is not without risk ( 68 – 70 ). Side effects have been found in vaccinated animals ( 5 ). The protective effects of subunit vaccines are also inconsistent due to various reasons, such as vaccination methods and antigen strategies used ( 71 , 72 ).

It is equally important that the co-citation analysis shows highly co-cited references and highly co-cited journals, which is helpful for subsequent scholars to quickly understand the core knowledge structure and sources of the research field. In conclusion, this study conducted a systematic and comprehensive review of ASF related studies based on the WoS database using a bibliometric approach. Through a quantitative and visual review of ASF research, researchers can accurately grasp the development dynamics and potential trends of ASF research.

5. Strengths and limitations

As opposed to traditional literature reviews, bibliometrics is a comprehensive knowledge system that integrates mathematics, statistics, and philology, and pays attention to quantification. Through visualized analysis, it can provide a clear depiction of the development process, research status, and research hotspots of a given field, thereby serving as a reference for further research. However, due to some objective factors, there are certain limitations in this research. First, the samples in this study are only from the Science Citation Index Expanded database in the WoSCC. Although the WoS covers a wide range of journals and is a mainstream source of data in the bibliometrics field, there may still be several articles on this topic that are not counted by WoS. Nevertheless, it is worth noting that WoS is the most frequently employed database in bibliometric studies ( 73 , 74 ). Second, to ensure the integrity of information in the analyzed literature, the data collected in this study were limited to articles and review articles, and literature types such as meeting reports, books, and case reports were not included. Third, although the software used for bibliometric analysis and the data collected are objective, the subjective nature of the analysis and interpretation cannot be avoided. Finally, recent high-quality studies may not be as widely cited due to their recentness, so influential studies may need to be highlighted by several years of high citation.

6. Conclusion

This is the first report that uses bibliometric indicators and information visualization tools to reveal the research status of ASF over the past two decades. It clearly shows the structural changes, research priorities, and knowledge sources of the ASF scientific research field. It will help scholars who are interested in the ASF to further understand the development process of this field and help scholars quickly find the literature, author, or journal they need to cite. Furthermore, predictions based on bibliometric analysis can also provide ideas for future research.

Data availability statement

The original contributions presented in the study are included in the article/ Supplementary material , further inquiries can be directed to the corresponding author.

Author contributions

LX and ZY designed the research subject and interpreted results. LX analyzed the data and wrote the manuscript. PS, JZha, and WA searched the literature and screened all potentially eligible studies. MY and JZhe reviewed and corrected the manuscript. HL and ZY critically revised the manuscript. All authors contributed to the article and consented to the final manuscript. All authors contributed to the article and approved the submitted version.

This work was supported by the funds from the Key Research and Development Program of the Science and Technology Department of Sichuan Province (Nos. 2020YFS0469 and 2021YFS0002), Research Projects of the General Administration of Customs, PRC (No. 2019HK045), and the Post-Doctor Research Project, West China Hospital, Sichuan University (No. 2021HXBH085).

Acknowledgments

We would like to thank Dr. Xiaodong Deng for his suggestions and technical support.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fvets.2023.1085473/full#supplementary-material

Supplementary Figure S1. The co-occurrence map of most active journals related to ASF.

Supplementary Figure S2. The co-occurrence network map of co-cited references.

Supplementary Table S1. The keywords co-occurrence cluster list.

Supplementary Table S2. The top 5 cited references in each cluster.

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Keywords: African swine fever, bibliometrics, citation, Web of Science, visualized analysis

Citation: Yu Z, Xie L, Shuai P, Zhang J, An W, Yang M, Zheng J and Lin H (2023) New perspective on African swine fever: a bibliometrics study and visualization analysis. Front. Vet. Sci. 10:1085473. doi: 10.3389/fvets.2023.1085473

Received: 31 October 2022; Accepted: 26 April 2023; Published: 17 May 2023.

Reviewed by:

Copyright © 2023 Yu, Xie, Shuai, Zhang, An, Yang, Zheng and Lin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Hua Lin, cdcclh@126.com

† These authors have contributed equally to this work

African swine fever virus: current state and future perspectives in vaccine and antiviral research

Affiliations.

• 1 Laboratory of cell biology and virology, Institute of Molecular Biology of NAS RA, Yerevan, Armenia; Yerevan State Medical University after M. Heratsi, 0025 Yerevan, Armenia. Electronic address: [email protected].
• 2 Centro de Biología Molecular Severo Ochoa, CSIC-UAM, Madrid, Spain.
• PMID: 26931386
• DOI: 10.1016/j.vetmic.2016.01.016

African swine fever (ASF) is among the most significant of swine diseases for which no effective vaccines and antivirals are available. The disease, which is endemic in Africa, was introduced to Trans-Caucasian countries and the Russian Federation in 2007, where it remains prevalent today among domestic pigs and wild boars. Although some measures were implemented, ASF continues to pose a global risk for all countries, and thereby highlighting the importance of vaccine and antiviral research. In this review, an overview of research efforts toward the development of effective vaccines during the past decades is presented. As an alternative to vaccine development, the current state in antiviral research against ASFV is also presented. Finally, future perspectives in vaccine and antiviral research giving emphasis on some strategies that may allow researchers to develop effective countermeasures against ASF are discussed.

Keywords: African swine fever; Antivirals; Vaccine.

Copyright © 2016 Elsevier B.V. All rights reserved.

Publication types

• Research Support, Non-U.S. Gov't
• Africa / epidemiology
• African Swine Fever / epidemiology*
• African Swine Fever / prevention & control*
• African Swine Fever / therapy
• African Swine Fever Virus / physiology*
• Antiviral Agents* / therapeutic use
• Europe, Eastern / epidemiology
• Research / trends*
• Viral Vaccines* / standards
• Antiviral Agents
• Viral Vaccines

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February 1, 2021

African swine fever decimates Philippine pig stocks

by SciDev.Net

African swine fever (ASF) sweeping through the Philippines has wiped out over a third of the country's pig stocks, threatening food security in a country already reeling from the economic impact of the COVID-19 pandemic.

A source requesting anonymity tell SciDev.Net that the Department of Agriculture has underestimated the devastation caused by the ASF virus, which has resulted in severe shortages of pork , an important part of the Filipino diet. The source says this has led to a rise in prices of many food items.

"The official figures of 431,000 cited by the department of agriculture as the number of hogs culled during the infestation period is an underestimation," says the source. "Private industry hog raisers estimate that the actual figure is around 4.7 million heads affected by ASF, which is over a third (or 36 percent) of the total population."

Even breeder stock important for reviving the pork industry that is valued at PHP260 billion (US$4.97 billion), has been decimated by ASF, the source adds. Also, some hog raisers have downsized their pork production to minimize business losses already estimated at US$1.2 billion.

"Such significant losses in production directly contribute to the impoverishment of livestock-breeding families, drastically reducing their opportunities to access health care and education, and sometimes leading to loss in social status," Monique Eloit, World Organisation for Animal Health (OIE) director general, tells SciDev.Net.

ASF has hit backyard farmers harder than commercial pork producers. "It negatively affects the livelihoods of numerous poor households that depend on pigs as a source of protein and income, as means to capitalize savings, and as 'safety nets' during times of hardship," says Eloit. "Many such farmers have lost or will lose their businesses because of ASF."

"Since it is impossible to control the disease in the short term without a vaccine, and due to the difficulty of applying strict biosecurity measures, communities are propelled into a downward spiral of sustained poverty," Eloit adds. The agriculture department has announced the setting aside of US$1.7 million for the development and mass production of locally made ASF test kits, though this may take time.

Pork is second only to rice as a source of food energy for Filipino working adults, according to a study published in Nutrients in April 2020. FAO Philippines told SciDev.Net that per capita consumption of pork in the Philippines is 15.2 kilograms per capita, higher than world average 11.1 kilograms.

Recently, however, pork saw steep increases in price. "The COVID-19 scenario coupled with the ongoing ASF outbreaks in Luzon and Mindanao, and other type of calamities, where supply is reduced causes pork prices to spike particularly in Metro Manila," FAO Philippines said in its statement to SciDev.Net.

In January, pork was priced at PHP400 (US$8.30) per kilogram, a 60 percent increase from its PHP250 (US$5.20) per kilogram price six months ago. It is also nearly equal to the minimum daily wage in Metro Manila, which is at PHP537 (US$11.17). The drastic increase in the price of pork has triggered a ripple effect, affecting the price of other meats, vegetables and basic commodities especially chicken which might have been an alternative protein source.

On Monday (1 February), Philippine President Rodrigo Duterte announced a price cap on pork and chicken for the next 60 days. The government earlier said that they are eyeing to triple pork imports to stabilize local supply. But pork producers say that this will disadvantage local farmers.

"Control of ASF poses a challenge, due to the complex epidemiology of the disease, lack of a safe and effective vaccine, increasing globalization, and high-risk practices that continue in certain farming sectors as well as in trade in live animals and their products," says Eloit.

"Deadly disease outbreaks will continue as long as animals are packed into filthy pens and feedlots (confined feeding quarters to speed up weight gain). Unless people stop eating meat, we might see ourselves with another pandemic on our hands very soon," says Jason Baker, senior vice president of PETA Asia, which promotes vegetarianism.

"Farmers in the Philippines can use their land to grow sustainable and healthy crops that don't threaten any lives," says Baker. "Filipino shoppers can turn to vegan foods like tofu, which is not only safer and cheaper than meat, but is also packed with protein, contains zero cholesterol, and can lower one's risk of suffering from heart disease, diabetes, cancer and many other life-threatening health issues."

Provided by SciDev.Net

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Philippines detects first African swine fever outbreak in southern province

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Reporting by Enrico dela Cruz. Editing by Gerry Doyle

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