An Exemplary Computational Approach to Investigate Lumpy Skin Disease in Indian Cattle
Abstract
Lumpy Skin Disease (LSD) is a highly consequential infectious ailment that affects cattle caused by the Lumpy Skin Disease Virus (LSDV), which is a DNA virus classified under the Capripoxvirus genus of the Poxviridae family. This affliction presents a significant obstacle in the cattle industries of several Asian and African countries. Although the virus may be found in many physiological fluids and excretions, such as sperm, skin lesions are the primary source of infection. Hematophagous arthropods, such as biting flies, mosquitoes, and ticks, act as mechanical vectors for transmission. The geographical expansion of LSDV is believed to have been assisted by vector-borne transmission. However, a lack of quantitative understanding of the transmission of LSDV hinders the implementation of efficient disease control measures. Obstacles as mentioned earlier, this work focuses on developing a mathematical model to analyze the phenomenon of Lumpy Skin Disease, with a specific emphasis on its implications for the cattle sectors in African and Asian countries. The model encompasses a set of differential equations incorporating the influences of infection forces originating from sick and asymptomatic cattle, along with infected vectors. The research demonstrates a plausible correlation between Lumpy Skin Disease and increased death rates in cattle. Employing rigorous examination and computational modelling, a valuable understanding of the fundamental dynamics of disease outbreaks is obtained. The mathematical model shows potential for predicting the future transmission of Lumpy Skin Disease. This presents a prospective opportunity for understanding and alleviating the disease's effects on bovine populations. Moreover, the analysis reveals that the impact of direct contact transmission on the spread of LSDV during documented outbreaks was negligible, therefore providing valuable insights into the dynamics of disease transmission. As the model is rigorously analyzed to gain insights into its qualitative dynamics of epidemics, which are present in the numerical simulations, this mathematical model can be allowed to estimate the future spread of the disease.
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