Early detection and prediction of infection using infrared thermography

Abstract

Early detection and/or prediction of disease in an animal is the first step towards its successful treatment. The objective of this study was to investigate the capability of infrared thermography as a non-invasive, early detection method for identifying animals with a systemic infection. A viral infection model was adopted using 15 seronegative calves whose body weight averaged 172 kg. Ten of these calves were inoculated with Type 2 bovine viral diarrhoea virus (strain 24515) and five were separately housed and served as uninfected controls. A simultaneous comparison of infrared characteristics in both infected and control animals was conducted over approximately 15 d. In addition, measures of blood and saliva cortisol, immunoglobulin A, blood haptoglobin and clinical scores were obtained. Infrared temperatures, especially for facial scans, increased by 1.5°C to over 4°C (P < 0.01) several days to 1 wk before clinical scores or serum concentrations of acute phase protein indicated illness in the infected calves. The data suggest that infrared thermal measurements can be used in developing an early prediction index for infection in calves. Key words: Infection, early detection, infrared thermography, cattle