Analysis of Veterinary Workforce in Thailand National Veterinary Education sub committee Gr.1

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1 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

2 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

3 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

4 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

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7 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 *** *** (Standard Error) (45.156) (55.743) Trend *** *** (Standard Error) (5.129) (6.332) Adjusted R squared F statistic *** *** N 16 16

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10 Predicted Numbers of Company Vet Year Predicted numbers Poultry Vet Swine Vet ,017 2, ,141 2, ,264 2, ,388 2, ,512 2, ,636 2, ,759 2, ,883 2, ,007 2, ,131 3, ,254 3,243

11 Another Assumption Standard farm regulations Ratios of vet per animal Predict numbers of animals Predict numbers of required vets???

12 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) *** (31.828) 0.597*** (0.133) *** (1.771) F *** *** *** AIC

13 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 *** (2.660) 0.760*** (0.224) *** (44.337) *** (2.467) Adjusted R Square F *** *** *** AIC N =13

14 Ratios of Vet per pigs and chickens Year Swine Vets Per Pigs Poultry Vets Per Chickens : 5, : 165, : 5, : 128, : 5, : 147, : 6, : 169, : 5, : 165, : 4, : 153, 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

15 (approximately 90% of farms have 50 pigs)

16 (approximately 95% of farms have 50 pigs)

17 (approximately 90% of farms have 10,000 broilers)

18 (approximately >95% of farms have 10,000 layers)

19 Real work loads vets: pig vets: chicken Year farms farms : : : : : : : : : : : : pigs:farm chickens:farm : 1 3, : : 1 2, : : 1 2, : : 1 2, : : 1 3, : : 1 3, : 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.

20 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 (Standard Error) ( ) Trend *** (Standard Error) (29.159) Adjusted R squared F statistic *** N 5

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22 Predicted VPAT members Year Predicted VPAT members , , , , , , , , , , ,533

23 Licensed Vets Per dogs and VPAT members per dogs Year Vet per dogs VPAT members per dogs : 10, : 10, : 10, : 10, NA NA : 10, : 10, : 10, : 10,000

24 Demand for Government (3) Year DLD D. Fisheries Lab Animal Association Total

25 Demands vs Supplies

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28 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..

29 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

30 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

31 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

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