Analysis of Veterinary Workforce in Thailand National Veterinary Education sub committee Gr.1 Presented by Sukolrat Boonyayatra Faculty of Veterinary Medicine Chiang Mai University, Thailand
Veterinarians in Thailand First vet school started in 1935 Serve for military animals and livestock Urbanization and changes in social attitudes Increasing in small animal veterinarians More diverse career paths
Objectives 1. Build a model to estimate the demand of veterinarians in Thailand 2. Compare demand and supply of veterinarians in Thailand 3. Trend analysis of veterinary workforce in Thailand
Categorize jobs into 6 groups 1. Company (swine and poultry) 2. Small animal clinic 3. Government (DLD and others) 4. Academic and research area 5. Other animal associated organizations 6. Lost
Demand for Company (1) Simple regression to build a model to estimate changes of the number of veterinarians for chickens and pigs in Thailand (Trend analysis) Dependent Variable Veterinarian for Chicken (Model 1 1) Coefficient Veterinarian for Pig (Model 1 2) Constant 160.772*** 179.669*** (Standard Error) (45.156) (55.743) Trend 123.747*** 122.519*** (Standard Error) (5.129) (6.332) Adjusted R squared 0.9745 0.961 F statistic 582.005*** 374.399*** N 16 16
Predicted Numbers of Company Vet Year Predicted numbers Poultry Vet Swine Vet 2558 2,017 2,017 2559 2,141 2,140 2560 2,264 2,262 2561 2,388 2,385 2562 2,512 2,508 2563 2,636 2,630 2564 2,759 2,753 2565 2,883 2,875 2566 3,007 2,998 2567 3,131 3,120 2568 3,254 3,243
Another Assumption Standard farm regulations Ratios of vet per animal Predict numbers of animals Predict numbers of required vets???
Model to estimate the pig population in Thailand Constant (Standard Error) LGDP 2 (Standard Error) LGDPC 3 (Standard Error) LPOP 4 (Standard Error) Adjusted R Square N =9 Dependent Variable: LPIG 1 Model 2 1 Model 2 2 Model 2 3 Coefficient 6.974*** (2.423) 0.553*** (1.150) 8.759*** (1.591) 171.015*** (31.828) 0.597*** (0.133) 10.400*** (1.771) 0.707 0.704 0.807 F 20.328*** 20.041*** 34.478*** AIC 1.569 1.558 1.986
Model to estimate the chicken population in Thailand Dependent Variable: LCHICK 1 Model 3 1 Model 3 2 Model 3 3 Constant (Standard Error) LGDP 2 (Standard Error) LGDPC 3 (Standard Error) LPOP 4 (Standard Error) 7.811** (3.268) 0.704*** (0.202) Coefficient 10.097*** (2.660) 0.760*** (0.224) 257.31*** (44.337) 15.386*** (2.467) Adjusted R Square 0.470 0.466 0.697 F 11.647*** 11.487*** 28.662*** AIC 0.301 0.294 0.861 N =13
Ratios of Vet per pigs and chickens Year Swine Vets Per Pigs Poultry Vets Per Chickens 2008 1 : 5,956.38 1 : 165,831.78 2009 1 : 5,323.30 1 : 128,038.59 2010 1 : 5,889.58 1 : 147,764.69 2011 1 : 6,322.39 1 : 169,972.27 2012 1 : 5,201.70 1 : 165,582.78 2013 1 : 4,935.60 1 : 153,467.67 Farm types Vet:Animal for standard farm Broilers 1 : 5,000,000 Layers 1 : 2,000,000 Breeders chickens NA Fattening pigs 200,000 Breeders pigs 20,000
(approximately 90% of farms have 50 pigs)
(approximately 95% of farms have 50 pigs)
(approximately 90% of farms have 10,000 broilers)
(approximately >95% of farms have 10,000 layers)
Real work loads vets: pig vets: chicken Year farms farms 2008 1 : 132.02 1 : 41.90 2009 1 : 98.54 1 : 58.78 2010 1 : 109.93 1 : 58.90 2011 1 : 122.45 1 : 60.38 2012 1 : 97.24 1 : 49.36 2013 1 : 87.92 1 : 43.67 pigs:farm chickens:farm 45.12 : 1 3,957.39 : 1 54.58 : 1 2,178.35 : 1 53.58 : 1 2,508.62 : 1 51.63 : 1 2,814.94 : 1 53.49 : 1 3,354.76 : 1 56.14 : 1 3,514.13 : 1 This assumption should not work out. Ratios of vets per animals indicated in the standard farm regulations should not be used to estimate demands of vets.
Demand for vets in clinics (4) Simple regression to build a model to estimate changes of the number of veterinarians for small animals (VPAT members) in Thailand (Trend analysis) Dependent Variable: Number of VPAT members Coefficient Constant 796.800 (Standard Error) (352.339) Trend 453.200*** (Standard Error) (29.159) Adjusted R squared 0.984 F statistic 241.552*** N 5
Predicted VPAT members Year Predicted VPAT members 2015 6,001 2016 6,454 2017 6,908 2018 7,361 2019 7,814 2020 8,267 2021 8,720 2022 9,174 2023 9,627 2024 10,080 2025 10,533
Licensed Vets Per dogs and VPAT members per dogs Year Vet per dogs VPAT members per dogs 2010 8.76 : 10,000 5.80 : 10,000 2011 7.71 : 10,000 5.17 : 10,000 2012 NA NA 2013 14.29 : 10,000 9.90 : 10,000 2014 9.01 : 10,000 6.57 : 10,000
Demand for Government (3) Year DLD D. Fisheries Lab Animal Association Total 2015-5 25 30 2016 20-25 50 2017 25-25 50 2018 39 - - 39 2019 63 - - 63 2020 56 - - 56 2021 99 - - 99 2022 121 - - 121 2023 154 - - 154 2024 143 - - 143 2025 117 - - 117
Demands vs Supplies
Conclusions Overall demand for vets is higher than the supply (shortage of vets) High demand for company vet Increasing of population Not affected by number of animals Influenced by new standards or regulations Business expansion Other factors eg. female > male, geographical distribution of farms etc..
Conclusions(cont) Companion vets Ratios of vet per population are smaller than those of other developed countries Increased single or small families May be surplus in the next 10 years Vets in government in the next 10 years Replacement for retired staffs New regulations or policy
Limitations and Suggestions Accuracy of models due to limitation of data Models should be validated with more data in a longitudinal study Vet Education unit a common and analyzable data collecting system a common and sharable database to store data
Policy Suggestions Potential surplus of companion vet Residency programs for vet specialties Improved language skills for exporting vets Shortage of vets for farm animals MOUs between companies or government and vet schools to produce vets for farm animals Skill mixed working