An Assessment of Epidemiology Capacity in a One Health Team at the Provincial Level in Thailand

A multi-sectoral core epidemiology capacity assessment was conducted in provinces that implemented One Health services in order to assess the efficacy of a One Health approach in Thailand. In order to conduct the assessment, four provinces were randomly selected as a study group from a total of 19 Thai provinces that are currently using a One Health approach. As a control group, four additional provinces that never implemented a One Health approach were also sampled. The provincial officers were interviewed on the epidemiologic capacity of their respective provinces. The average score of epidemiologic capacity in the provinces implementing the One Health approach was 66.45%, while the provinces that did not implement this approach earned a score of 54.61%. The epidemiologic capacity of surveillance systems in provinces that utilized the One Health approach earned higher scores in comparison to provinces that did not implement the approach (75.00% vs. 53.13%, p-value 0.13). Although none of the capacity evaluations showed significant differences between the two groups, we found evidence that provinces implementing the One Health approach gained higher scores in both surveillance and outbreak investigation capacities. This may be explained by more efficient capacity when using a One Health approach, specifically in preventing, protecting, and responding to threats in local communities

Data_Sheet_2_An overlooked poultry trade network of the smallholder farms in the border provinces of Thailand, 2021: implications for avian influenza surveillance.ZIP

IntroductionIn Thailand, community-level poultry trade is conducted on a small-scale involving farmers and traders with many trade networks. Understanding the poultry movements may help identify different activities that farmers and traders might contribute to the spread of avian influenza.MethodsThis study aimed to describe the characteristics of players involved in the poultry trade network at the northeastern border of Thailand using network analysis approaches. Mukdahan and Nakhon Phanom provinces, which border Laos, and Ubon Ratchathani province, which borders both Laos and Cambodia, were selected as survey sites.ResultsLocal veterinary officers identified and interviewed 338 poultry farmers and eight poultry traders in 2021. A weighted directed network identified incoming and outgoing movements of where the subdistricts traded chickens. Ninety-nine subdistricts and 181 trade links were captured. A self-looping (trader and consumer in the same subdistrict) feedback was found in 56 of 99 subdistricts. The median distance of the movements was 14.02 km (interquartile range (IQR): 6.04–102.74 km), with a maximum of 823.08 km. Most subdistricts in the network had few poultry trade connections, with a median of 1. They typically connected to 1–5 other subdistricts, most often receiving poultry from 1 to 2.5 subdistricts, and sending to 1–2 subdistricts. The subdistricts with the highest overall and in-degree centrality were located in Mukdahan province, whereas one with the highest out-degree centrality was found in Nakhon Phanom province.DiscussionThe poultry movement pattern observed in this network helps explain how avian influenza could spread over the networks once introduced.</p

Table_1_An overlooked poultry trade network of the smallholder farms in the border provinces of Thailand, 2021: implications for avian influenza surveillance.XLSX

IntroductionIn Thailand, community-level poultry trade is conducted on a small-scale involving farmers and traders with many trade networks. Understanding the poultry movements may help identify different activities that farmers and traders might contribute to the spread of avian influenza.MethodsThis study aimed to describe the characteristics of players involved in the poultry trade network at the northeastern border of Thailand using network analysis approaches. Mukdahan and Nakhon Phanom provinces, which border Laos, and Ubon Ratchathani province, which borders both Laos and Cambodia, were selected as survey sites.ResultsLocal veterinary officers identified and interviewed 338 poultry farmers and eight poultry traders in 2021. A weighted directed network identified incoming and outgoing movements of where the subdistricts traded chickens. Ninety-nine subdistricts and 181 trade links were captured. A self-looping (trader and consumer in the same subdistrict) feedback was found in 56 of 99 subdistricts. The median distance of the movements was 14.02 km (interquartile range (IQR): 6.04–102.74 km), with a maximum of 823.08 km. Most subdistricts in the network had few poultry trade connections, with a median of 1. They typically connected to 1–5 other subdistricts, most often receiving poultry from 1 to 2.5 subdistricts, and sending to 1–2 subdistricts. The subdistricts with the highest overall and in-degree centrality were located in Mukdahan province, whereas one with the highest out-degree centrality was found in Nakhon Phanom province.DiscussionThe poultry movement pattern observed in this network helps explain how avian influenza could spread over the networks once introduced.</p

Data_Sheet_1_An overlooked poultry trade network of the smallholder farms in the border provinces of Thailand, 2021: implications for avian influenza surveillance.PDF

IntroductionIn Thailand, community-level poultry trade is conducted on a small-scale involving farmers and traders with many trade networks. Understanding the poultry movements may help identify different activities that farmers and traders might contribute to the spread of avian influenza.MethodsThis study aimed to describe the characteristics of players involved in the poultry trade network at the northeastern border of Thailand using network analysis approaches. Mukdahan and Nakhon Phanom provinces, which border Laos, and Ubon Ratchathani province, which borders both Laos and Cambodia, were selected as survey sites.ResultsLocal veterinary officers identified and interviewed 338 poultry farmers and eight poultry traders in 2021. A weighted directed network identified incoming and outgoing movements of where the subdistricts traded chickens. Ninety-nine subdistricts and 181 trade links were captured. A self-looping (trader and consumer in the same subdistrict) feedback was found in 56 of 99 subdistricts. The median distance of the movements was 14.02 km (interquartile range (IQR): 6.04–102.74 km), with a maximum of 823.08 km. Most subdistricts in the network had few poultry trade connections, with a median of 1. They typically connected to 1–5 other subdistricts, most often receiving poultry from 1 to 2.5 subdistricts, and sending to 1–2 subdistricts. The subdistricts with the highest overall and in-degree centrality were located in Mukdahan province, whereas one with the highest out-degree centrality was found in Nakhon Phanom province.DiscussionThe poultry movement pattern observed in this network helps explain how avian influenza could spread over the networks once introduced.</p