Disease outbreak data to inform decision-making: the role of disease spread models in the Lao P.D.R. African Swine Fever epidemic, 2019 - Nina Matsumoto; Tariq Halasa; Kathrin Schemann; Syseng Khounsy; Bounlom Douangngeun; Watthana Thepagna; Phouvong Phommachanh; Jarunee Siengsanan-Lamont; James Young; Jenny-Ann Toribio; Russell Bush; Stuart D. Blacksell; et al. (Tropical Animal Health and Production, 2025)
Understanding the spread of African Swine Fever (ASF) between villages in the southeast-Asian, low − middle income country context is critical if this high impact disease is to be controlled by good policy and effective field activities in these resource-poor settings. Using governmental reporting data from the 2019 outbreak of ASF in Lao People’s Democratic Republic, spatial clustering techniques were used to identify clusters of outbreak villages. Then Approximate Bayesian Computation with Sequential Monte Carlo was used to estimate the transmission parameters of ASF virus between the villages within these clusters. We used a simple disease spread model to understand the impact of parameter estimation on predicted disease spread and thus decision-making. Six clusters of radius 16 to 153km were identified over the 7 month outbreak period. Within these clusters, the basic reproduction number (R 0 ) ranged from 13 to 32 between-villages and whole-village infectious periods ranged from 62 to 68 days. The final model outputs were compared to the original field report data. We found that the ability of the estimated parameters to match field data was heavily reliant on how the original field surveillance data was reported. Specifically, in situations in which cases in a cluster appeared to have been reported as batches (lack of temporal specificity) our modelling approach failed to produce satisfactory outputs in terms of model fit and precision of estimates. This study demonstrates that surveillance for transboundary diseases not only has immediate benefit for disease response, but that good quality surveillance data is valuable for informing future planning for disease response via appropriately parameterised disease spread models. There is a need for ongoing quality control of surveillance and support for field veterinary services to ensure quality data that can be used to drive policy and decision-making.

Novel estimation of African swine fever transmission parameters within smallholder villages in Lao P.D.R - Nina Matsumoto; Michael P. Ward; Tariq Halasa; Kathrin Schemann; Syseng Khounsy; Bounlom Douangngeun; Watthana Thepagna; Phouvong Phommachanh; Jarunee Siengsanan-Lamont; James R. Young; Jenny-Ann L. M. L. Toribio; Russell D. Bush; et al. (Tropical Animal Health and Production, 2024)
African Swine Fever (ASF) disease transmission parameters are crucial for making response and control decisions when faced with an outbreak, yet they are poorly quantified for smallholder and village contexts within Southeast Asia. Whilst disease-specific factors − such as latent and infectious periods − should remain reasonably consistent, host, environmental and management factors are likely to affect the rate of disease spread. These differences are investigated using Approximate Bayesian Computation with Sequential Monte-Carlo methods to provide disease parameter estimates in four naïve pig populations in villages of Lao People’s Democratic Republic. The villages represent smallholder pig farmers of the Northern province of Oudomxay and the Southern province of Savannakhet, and the model utilised field mortality data to validate the transmission parameter estimates over the course of multiple model generations. The basic reproductive number between-pigs was estimated to range from 3.08 to 7.80, whilst the latent and infectious periods were consistent with those published in the literature for similar genotypes in the region (4.72 to 6.19 days and 2.63 to 5.50 days, respectively). These findings demonstrate that smallholder village pigs interact similarly to commercial pigs, however the spread of disease may occur slightly slower than in commercial study groups. Furthermore, the findings demonstrated that despite diversity across the study groups, the disease behaved in a consistent manner. This data can be used in disease control programs or for future modelling of ASF in smallholder contexts.

Effect of probiotics and prebiotics on the composition of the equine fecal and seminal microbiomes and sperm quality: A pilot study - C Giselle Cooke; Zamira Gibb; Christopher G. Grupen; Kathrin Schemann; Nandan Deshpande; Joanna E Harnett (Journal of Equine Veterinary Science, 2024)

Investigating baseline red meat slaughter operator capacity and directions for development in Lao PDR - Joanne C. Thomas; James R. Young; Kathrin Schemann; Phaivanh Chankhamthong; Syseng Khounsy; Sonevilay Nampanya; Peter A. Windsor; Russell D. Bush (Tropical Animal Health and Production, 2017)