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İnce ÖB, Şevik M, Şener R, Türk T. Spatiotemporal analysis of foot and mouth disease outbreaks in cattle and small ruminants in Türkiye between 2010 and 2019. Vet Res Commun 2024; 48:923-939. [PMID: 38015325 DOI: 10.1007/s11259-023-10269-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Accepted: 11/23/2023] [Indexed: 11/29/2023]
Abstract
Determining the dynamics associated with foot-and-mouth disease (FMD) outbreaks is important for being able to develop effective strategic plans against the disease. In this direction, spatiotemporal analysis of FMD virus (FMDV) epidemic data that occurred in Türkiye between 2010 and 2019 was carried out. Spatiotemporal analysis was performed by the space-time scan statistic using data from a total of 7,796 FMD outbreaks. Standard deviational ellipse analysis (SDE) was performed to analyse the directional trend of FMD. Five, six, and three significant and high-risk clusters were identified by the space-time cluster analysis for serotypes A, O, and Asia-1, respectively. The SDE analysis indicated that direction of FMD transmission was northeast to southwest. A significant decrease in the number of outbreaks and cases were observed between 2014 and 2019 compared to 2010-2013 (p = 0.010). Most of the serotype A, serotype O, and serotype Asia-1 associated FMD outbreaks were observed during the dry season (April to September). Among FMD cases, cattle and small ruminants accounted for 80.75% (180,932 cases) and 19.25% (43,116 cases), respectively. Among the serotypes detected in the cases, the most frequently detected serotype was serotype O (50.84%), followed by serotypes A (35.67%) and Asia-1 (13.49%). The results obtained in this study may contribute to when and where control programs could be implemented more efficiently for the prevention and control of FMD. Developing risk-defined regional control plans by taking into account the current livestock production including uncontrolled animal movements in border regions, rural livestock, livestock trade between provinces are recommended.
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Affiliation(s)
- Ömer Barış İnce
- Department of Virology, Veterinary Faculty, Necmettin Erbakan University, Ereğli, Konya, 42310, Türkiye
| | - Murat Şevik
- Department of Virology, Veterinary Faculty, Necmettin Erbakan University, Ereğli, Konya, 42310, Türkiye.
| | - Rümeysa Şener
- Department of Geomatics Engineering, Sivas Cumhuriyet University, Sivas, 58140, Türkiye
| | - Tarık Türk
- Department of Geomatics Engineering, Sivas Cumhuriyet University, Sivas, 58140, Türkiye
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Modethed W, Singhla T, Boonsri K, Pringproa K, Sthitmatee N, Vinitchaikul P, Sansamur C, Kreausukon K, Punyapornwithaya V. Identifying the patterns and sizes of the first lumpy skin disease outbreak clusters in Northern Thailand with a high degree of dairy farm aggregation using spatio-temporal models. PLoS One 2023; 18:e0291692. [PMID: 37967138 PMCID: PMC10651038 DOI: 10.1371/journal.pone.0291692] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 09/01/2023] [Indexed: 11/17/2023] Open
Abstract
Lumpy skin disease (LSD) is one of the most important notifiable transboundary diseases affecting cattle in many parts of the world. In Thailand, LSD outbreaks in cattle farming areas have been reported in 69 out of 77 provinces, indicating a serious nationwide situation. Understanding the dynamics of spatial and temporal LSD epidemic patterns can provide important information on disease transmission and control. This study aims to identify spatial and temporal clusters in the first LSD outbreaks in dairy farming areas with a high degree of aggregation in Northern Thailand using spatio-temporal models. The data were obtained from an official LSD outbreak investigation conducted between June and August 2021 on dairy farms (n = 202). The outbreak of LSD was confirmed by employing clinical observations and laboratory analysis. The spatio-temporal models including space-time permutation (STP), Poisson, and Bernoulli were applied to the outbreak data with the settings of 10%, 25%, and 50%, respectively, for the maximum reported cluster size (MRCS). Overall, the number of most likely and secondary clusters varied depending on the model and MRCS settings. All MRCS settings in the STP model detected the most likely clusters in the same area and the Poisson models in different areas, with the largest being defined by a 50% MRCS. Although the sizes of the most likely clusters identified by the Bernoulli models were different, they all had the same cluster period. Based on the sizes of the detected clusters, strict LSD insect-vector control should be undertaken within one kilometer of the outbreak farm in areas where no LSD vaccination has been administered. This study determines the sizes and patterns of LSD outbreak clusters in the dairy farming area with a high degree of farm aggregation. The spatio-temporal study models used in this study, along with multiple adjusted MRCS, provide critical epidemiological information. These models also expand the options for assisting livestock authorities in facilitating effective LSD prevention and control programs. By prioritizing areas for resource allocation, these models can help improve the efficiency of such programs.
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Affiliation(s)
- Wittawat Modethed
- Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Tawatchai Singhla
- Ruminant Clinic, Department of Food Animal Clinics, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
- Research Center of Veterinary Biosciences and Veterinary Public Health, Chiang Mai University, Chiang Mai, Thailand
| | - Kittikorn Boonsri
- Center of Veterinary Diagnosis and Technology Transfer, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Kidsadagon Pringproa
- Research Center of Veterinary Biosciences and Veterinary Public Health, Chiang Mai University, Chiang Mai, Thailand
- Department of Veterinary Biosciences and Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Nattawooti Sthitmatee
- Research Center of Veterinary Biosciences and Veterinary Public Health, Chiang Mai University, Chiang Mai, Thailand
- Department of Veterinary Biosciences and Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
- Laboratory of Veterinary Vaccine and Biological Products, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Paramintra Vinitchaikul
- Ruminant Clinic, Department of Food Animal Clinics, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
- Research Center of Veterinary Biosciences and Veterinary Public Health, Chiang Mai University, Chiang Mai, Thailand
| | - Chalutwan Sansamur
- Akkhararatchakumari Veterinary College, Walailak University, Nakhon Si Thammarat, Thailand
| | - Khwanchai Kreausukon
- Ruminant Clinic, Department of Food Animal Clinics, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
- Research Center of Veterinary Biosciences and Veterinary Public Health, Chiang Mai University, Chiang Mai, Thailand
| | - Veerasak Punyapornwithaya
- Research Center of Veterinary Biosciences and Veterinary Public Health, Chiang Mai University, Chiang Mai, Thailand
- Department of Veterinary Biosciences and Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
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Punyapornwithaya V, Arjkumpa O, Buamithup N, Kuatako N, Klaharn K, Sansamur C, Jampachaisri K. Forecasting of daily new lumpy skin disease cases in Thailand at different stages of the epidemic using fuzzy logic time series, NNAR, and ARIMA methods. Prev Vet Med 2023; 217:105964. [PMID: 37393704 DOI: 10.1016/j.prevetmed.2023.105964] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 06/08/2023] [Accepted: 06/12/2023] [Indexed: 07/04/2023]
Abstract
Lumpy skin disease (LSD) is an important transboundary disease affecting cattle in numerous countries in various continents. In Thailand, LSD is regarded as a serious threat to the cattle industry. Disease forecasting can assist authorities in formulating prevention and control policies. Therefore, the objective of this study was to compare the performance of time series models in forecasting a potential LSD epidemic in Thailand using nationwide data. For the forecasting of daily new cases, fuzzy time series (FTS), neural network auto-regressive (NNAR), and auto-regressive integrated moving average (ARIMA) models were applied to various datasets representing the different stages of the epidemic. Non-overlapping sliding and expanding window approaches were also employed to train the forecasting models. The results showed that the FTS outperformed other models in five of the seven validation datasets based on various error metrics. The predictive performance of the NNAR and ARIMA models was comparable, with NNAR outperforming ARIMA in some datasets and vice versa. Furthermore, the performance of models built from sliding and expanding window techniques was different. This is the first study to compare the forecasting abilities of the FTS, NNAR, and ARIMA models across multiple phases of the LSD epidemic. Livestock authorities and decision-makers may incorporate the forecasting techniques demonstrated herein into the LSD surveillance system to enhance its functionality and utility.
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Affiliation(s)
- Veerasak Punyapornwithaya
- Department of Veterinary Bioscience and Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand; Center of Excellence in Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand
| | - Orapun Arjkumpa
- Department of Livestock Development, Animal Health Section, The 4th Regional Livestock Office, Khon Kaen 40260, Thailand
| | - Noppawan Buamithup
- Bureau of Disease Control and Veterinary Services, Department of Livestock Development, Bangkok 10400, Thailand
| | - Noppasorn Kuatako
- Bureau of Disease Control and Veterinary Services, Department of Livestock Development, Bangkok 10400, Thailand
| | - Kunnanut Klaharn
- Bureau of Livestock Standards and Certification, Department of Livestock Development, Bangkok 10400, Thailand.
| | - Chalutwan Sansamur
- Akkhraratchakumari Veterinary College, Walailak University, Nakhon Si Thammarat 80161, Thailand
| | - Katechan Jampachaisri
- Department of Mathematics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand.
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Punyapornwithaya V, Seesupa S, Phuykhamsingha S, Arjkumpa O, Sansamur C, Jarassaeng C. Spatio-temporal patterns of lumpy skin disease outbreaks in dairy farms in northeastern Thailand. Front Vet Sci 2022; 9:957306. [PMID: 35990277 PMCID: PMC9386524 DOI: 10.3389/fvets.2022.957306] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 07/11/2022] [Indexed: 11/13/2022] Open
Abstract
In 2021–2022, there were numerous outbreaks of lumpy skin disease (LSD) affecting cattle farms across Thailand. This circumstance was the country's first encounter with an LSD outbreak. Thus, a better understanding of LSD epidemiology is necessary. The aim of this study was to determine the spatio-temporal patterns of the LSD outbreaks in dairy farming areas. Data from LSD outbreak investigations collected from dairy farms in Khon Kean province, northeastern Thailand, were analyzed using spatio-temporal models including space-time permutation, Poisson, and Bernoulli models. LSD outbreaks were found in 133 out of 152 dairy farms from May to July, 2021. The majority of dairy farms (n = 102) were affected by the LSD outbreaks in June. The overall herd attack, morbidity and mortality rates were 87, 31, and 0.9%, respectively. According to the results of all models, the most likely clusters were found in the northern part of the study area. The space-time permutation and Poisson model identified 15 and 6 spatio-temporal outbreak clusters, respectively, while the Bernoulli model detected only one cluster. The most likely clusters from those models cover radii of 1.59, 4.51, and 4.44 km, respectively. All farms included in the cluster identified by the space-time permutation model were also included in the cluster identified by the Poisson model, implying that both models detected the same outbreak area. Furthermore, the study results suggested that farmers who own farms within a one km radius of the LSD outbreak farm should be advised to implement more stringent insect vector control measures to prevent disease spread. This study provides better insights into the spatio-temporal pattern of clusters of LSD in the outbreak area. The findings of this study can support authorities in formulating strategies to prevent and control future outbreaks as well as prioritizing resource allocation to high-risk areas.
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Affiliation(s)
- Veerasak Punyapornwithaya
- Center of Excellence in Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
- Veterinary Public Health and Food Safety Centre for Asia Pacific (VPHCAP), Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Suvaluk Seesupa
- Faculty of Veterinary Medicine, Khon Kaen University, Khon Kaen, Thailand
| | | | - Orapun Arjkumpa
- Department of Livestock Development, Animal Health Section, The 4th Regional Livestock Office, Khon Kaen, Thailand
| | - Chalutwan Sansamur
- Akkhraratchakumari Veterinary College, Walailak University, Nakhon Si Thammarat, Thailand
| | - Chaiwat Jarassaeng
- Faculty of Veterinary Medicine, Khon Kaen University, Khon Kaen, Thailand
- *Correspondence: Chaiwat Jarassaeng
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Exploring the predictive capability of machine learning models in identifying foot and mouth disease outbreak occurrences in cattle farms in an endemic setting of Thailand. Prev Vet Med 2022; 207:105706. [DOI: 10.1016/j.prevetmed.2022.105706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 06/09/2022] [Accepted: 07/01/2022] [Indexed: 11/20/2022]
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Time-Series Analysis for the Number of Foot and Mouth Disease Outbreak Episodes in Cattle Farms in Thailand Using Data from 2010-2020. Viruses 2022; 14:v14071367. [PMID: 35891349 PMCID: PMC9320723 DOI: 10.3390/v14071367] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 06/07/2022] [Accepted: 06/20/2022] [Indexed: 02/01/2023] Open
Abstract
Thailand is one of the countries where foot and mouth disease outbreaks have resulted in considerable economic losses. Forecasting is an important warning technique that can allow authorities to establish an FMD surveillance and control program. This study aimed to model and forecast the monthly number of FMD outbreak episodes (n-FMD episodes) in Thailand using the time-series methods, including seasonal autoregressive integrated moving average (SARIMA), error trend seasonality (ETS), neural network autoregression (NNAR), and Trigonometric Exponential smoothing state−space model with Box−Cox transformation, ARMA errors, Trend and Seasonal components (TBATS), and hybrid methods. These methods were applied to monthly n-FMD episodes (n = 1209) from January 2010 to December 2020. Results showed that the n-FMD episodes had a stable trend from 2010 to 2020, but they appeared to increase from 2014 to 2020. The outbreak episodes followed a seasonal pattern, with a predominant peak occurring from September to November annually. The single-technique methods yielded the best-fitting time-series models, including SARIMA(1,0,1)(0,1,1)12, NNAR(3,1,2)12,ETS(A,N,A), and TBATS(1,{0,0},0.8,{<12,5>}. Moreover, SARIMA-NNAR and NNAR-TBATS were the hybrid models that performed the best on the validation datasets. The models that incorporate seasonality and a non-linear trend performed better than others. The forecasts highlighted the rising trend of n-FMD episodes in Thailand, which shares borders with several FMD endemic countries in which cross-border trading of cattle is found common. Thus, control strategies and effective measures to prevent FMD outbreaks should be strengthened not only in Thailand but also in neighboring countries.
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Arjkumpa O, Suwannaboon M, Boonrod M, Punyawan I, Liangchaisiri S, Laobannue P, Lapchareonwong C, Sansri C, Kuatako N, Panyasomboonying P, Uttarak P, Buamithup N, Sansamur C, Punyapornwithaya V. The First Lumpy Skin Disease Outbreak in Thailand (2021): Epidemiological Features and Spatio-Temporal Analysis. Front Vet Sci 2022; 8:799065. [PMID: 35071388 PMCID: PMC8782428 DOI: 10.3389/fvets.2021.799065] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/06/2021] [Indexed: 11/13/2022] Open
Abstract
The first outbreak of lumpy skin disease (LSD) in Thailand was reported in March 2021, but information on the epidemiological characteristics of the outbreak is very limited. The objectives of this study were to describe the epidemiological features of LSD outbreaks and to identify the outbreak spatio-temporal clusters. The LSD-affected farms located in Roi Et province were investigated by veterinary authorities under the outbreak response program. A designed questionnaire was used to obtain the data. Space-time permutation (STP) and Poisson space-time (Poisson ST) models were used to detect areas of high LSD incidence. The authorities identified 293 LSD outbreak farms located in four different districts during the period of March and the first week of April 2021. The overall morbidity and mortality of the affected cattle were 40.5 and 1.2%, respectively. The STP defined seven statistically significant clusters whereas only one cluster was identified by the Poisson ST model. Most of the clusters (n = 6) from the STP had a radius <7 km, and the number of LSD cases in those clusters varied in range of 3-51. On the other hand, the most likely cluster from the Poisson ST included LSD cases (n = 361) from 198 cattle farms with a radius of 17.07 km. This is the first report to provide an epidemiological overview and determine spatio-temporal clusters of the first LSD outbreak in cattle farms in Thailand. The findings from this study may serve as a baseline information for future epidemiological studies and support authorities to establish effective control programs for LSD in Thailand.
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Affiliation(s)
- Orapun Arjkumpa
- Animal Health Section, The 4th Regional Livestock Office, Department of Livestock Development, Khon Kaen, Thailand
| | - Minta Suwannaboon
- Animal Health Section, The 4th Regional Livestock Office, Department of Livestock Development, Khon Kaen, Thailand
| | - Manoch Boonrod
- Animal Health Section, The 4th Regional Livestock Office, Department of Livestock Development, Khon Kaen, Thailand
| | - Issara Punyawan
- Animal Health Section, The 4th Regional Livestock Office, Department of Livestock Development, Khon Kaen, Thailand
| | - Supawadee Liangchaisiri
- Animal Health Section, The 4th Regional Livestock Office, Department of Livestock Development, Khon Kaen, Thailand
| | - Patchariya Laobannue
- Animal Health Section, Roi Et Provincial Livestock Office, Department of Livestock Development, Bangkok, Thailand
| | - Chayanun Lapchareonwong
- Animal Health Section, Roi Et Provincial Livestock Office, Department of Livestock Development, Bangkok, Thailand
| | - Chaiwat Sansri
- Animal Health Section, Roi Et Provincial Livestock Office, Department of Livestock Development, Bangkok, Thailand
| | - Noppasorn Kuatako
- Bureau of Disease Control and Veterinary Services, Department of Livestock Development, Bangkok, Thailand
| | - Pawares Panyasomboonying
- Bureau of Disease Control and Veterinary Services, Department of Livestock Development, Bangkok, Thailand
| | - Ponkrit Uttarak
- Bureau of Disease Control and Veterinary Services, Department of Livestock Development, Bangkok, Thailand
| | - Noppawan Buamithup
- Bureau of Disease Control and Veterinary Services, Department of Livestock Development, Bangkok, Thailand
| | - Chalutwan Sansamur
- Akkhararatchakumari Veterinary College, Walailak University, Nakhon Si Thammarat, Thailand
| | - Veerasak Punyapornwithaya
- Veterinary Public Health and Food Safety Centre for Asia Pacific (VPHCAP), Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
- Center of Excellence in Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
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Arjkumpa O, Picasso-Risso C, Perez A, Punyapornwithaya V. Subdistrict-Level Reproductive Number for Foot and Mouth Disease in Cattle in Northern Thailand. Front Vet Sci 2021; 8:757132. [PMID: 34859089 PMCID: PMC8631321 DOI: 10.3389/fvets.2021.757132] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 10/08/2021] [Indexed: 11/13/2022] Open
Abstract
Foot and mouth disease (FMD) is an important contagious transboundary disease that causes a significant economic loss for several countries. The FMD virus (FMDV) can spread very rapidly by direct and indirect transmission among susceptible animals. The complexity and magnitude of FMDV transmission at the initial stages of the epidemic can be expressed by the basic reproductive number (R 0), and furthermore, control strategies can be assessed by the estimation of the effective reproductive number. In this study, we aimed to describe FMD outbreaks among smallholder cattle farms by subdistricts in the northern Thailand and compute the effective reproductive number for outbreaks caused by FMDV serotype O and overall serotypes, including serotype O, serotype A, and unidentified serotype, at the subdistrict level (R sd ) using an epidemic doubling time method. Field data of FMD outbreaks during 2015-2017 that affected 94 subdistricts in northern Thailand were assessed to estimate the R sd . Results showed that 63.38% (90/142) of the FMD outbreak episodes in cattle were caused by FMDV serotype O. The average doubling time and the R sd estimated of the outbreaks caused by FMDV serotype O and overall serotype were 2.80 and 4.67 months, and 1.06 and 1.04, respectively. Our results indicated that transmission of FMD in cattle at the subdistrict level in northern Thailand was not controlled (R sd > 1), which indicates the endemicity of the disease in the region. Although control measures are in place, the results from this study highlighted the need for enhancing FMD monitoring and control strategies in northern Thailand.
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Affiliation(s)
- Orapun Arjkumpa
- Animal Health Section, The 4th Regional Livestock Office, Department of Livestock Development, Khon Kaen, Thailand
| | - Catalina Picasso-Risso
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, United States
| | - Andres Perez
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, United States
| | - Veerasak Punyapornwithaya
- Faculty of Veterinary Medicine, Veterinary Public Health Centre for the Asia Pacific, Chiang Mai University, Chiang Mai, Thailand.,Faculty of Veterinary Medicine, Center of Excellence in Veterinary Public Health, Chiang Mai University, Chiang Mai, Thailand
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Arjkumpa O, Yano T, Prakotcheo R, Sansamur C, Punyapornwithaya V. Epidemiology and National Surveillance System for Foot and Mouth Disease in Cattle in Thailand during 2008-2019. Vet Sci 2020; 7:vetsci7030099. [PMID: 32722145 PMCID: PMC7558286 DOI: 10.3390/vetsci7030099] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 07/16/2020] [Accepted: 07/22/2020] [Indexed: 11/16/2022] Open
Abstract
Foot and mouth disease (FMD) is a prominent transboundary disease that threatens livestock production and can disrupt the trade in animals and animal products at both regional and international levels. The aims of this study were: (1) to analyze the distribution of FMD in Thailand during the period of 2008 to 2019, (2) to outline a national surveillance approach, and (3) to identify the existing knowledge gap that is associated with this disease in relation to cattle production. We analyzed FMD outbreak data in order to determine the existing spatial and temporal trends and reviewed relevant publications and official documents that helped us outline a national surveillance program. There were 1209 FMD outbreaks in cattle farms during the study period. FMD outbreaks occurred every year throughout the study period in several regions. Notably, FMD serotype O and A were considered the predominant types. The FMD National Strategic Plan (2008–2015) and the national FMD control program (2016–2023) have been implemented in order to control this disease. The surveillance approach employed by livestock authorities included both active and passive surveillance techniques. The vaccination program was applied to herds of cattle 2–3 times per year. Additionally, numerous control measures have been implemented across the country. We have identified the need for a study on the assessment of an applicable surveillance program, the evaluation of an appropriate vaccination strategy and an assessment of the effectiveness of a measured control policy. In conclusion, this study provided much needed knowledge on the epidemiology of FMD outbreaks across Thailand from 2008 to 2019. Additionally, we identified the need for future studies to address the existing knowledge gaps. The findings from this study may also be useful for livestock authorities and stakeholders to establish an enhanced control strategy and to implement an effective surveillance system that would control and eradicate FMD throughout the country.
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Affiliation(s)
- Orapun Arjkumpa
- Ph.D. Degree Program in Veterinary Science, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand;
| | - Tedsak Yano
- Department of Food Animal Clinic, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand;
| | - Rotchana Prakotcheo
- Bureau of Disease Control and Veterinary Services, Department of Livestock Development, Bangkok 10400, Thailand;
| | - Chalutwan Sansamur
- Akkhraratchakumari Veterinary College, Walailak University, Nakhon Si Thammarat 80161, Thailand;
| | - Veerasak Punyapornwithaya
- Veterinary Public Health Centre for Asia Pacific, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand
- Correspondence: ; Tel.: +665-394-8023
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