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Using online public animal price data as a signal for predicting an increase in animal disease outbreak reports: a
Veerasak Punyapornwithaya1, Supitchaya Srisawang2, Chalita Jainonthee2
1Research Center of Veterinary Biosciences and Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, 50100, Thailand. veerasak.p@cmu.ac.th.
Background:
Changes in livestock prices are often linked to disease outbreaks. An animal price monitoring system has been considered a potential tool for predicting transboundary animal diseases (TADs). The aim of this study was to examine the cross-correlation between market price dynamics and disease outbreak patterns using publicly available online data to explore the potential of market prices as early indicators of impending TAD outbreaks.
Methods:
Time series data on TAD outbreak reports, including foot and mouth disease (FMD), lumpy skin disease (LSD), and African swine fever (ASF), as well as animal price data for cattle and pigs in Thailand, were analyzed. Cross-correlation analysis was conducted to assess the relationship between animal prices and disease outbreak report patterns. Data from January 2021 to December 2023 (primary dataset) were analyzed to identify cross-correlation patterns, while data from January to September 2024 (extended dataset) were incorporated to evaluate the consistency of the observed cross-correlation over the study period.
Results:
A significant cross-correlation was identified between cattle prices and the number of outbreak reports for FMD in the primary dataset. An increase in cattle prices during the preceding one to two months (lags of -1 and - 2) was associated with a subsequent rise in FMD outbreak reports. This correlation remained consistent when the extended dataset was incrementally incorporated and analyzed on a month-by-month basis. In contrast, in the primary dataset, no significant cross-correlation was observed between cattle prices and LSD outbreak reports. For ASF, cross-correlations between farm-gate pig prices and ASF outbreak reports were detected at lag 0, lag 3, lag 4, and lag 5 in the primary dataset; however, no significant correlation was observed in the extended dataset.
Conclusions:
This study demonstrates the feasibility of using animal price trends as signal tools for anticipating an increase in TAD outbreak reports. The findings specifically support the use of cattle price data as an early signal for forecasting increases in FMD outbreak reports in Thailand. The availability and consistency of publicly accessible data are essential components for the feasibility of using animal prices as a signal tool. Decision-makers and veterinary authorities may incorporate such tools into surveillance systems to support early warning efforts.
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