Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/78831
Title: Change point analysis and time series forecast of lumpy skin disease outbreaks in Africa, Europe, and Asia
Other Titles: การวิเคราะห์จุดเปลี่ยนแปลงและการพยากรณ์อนุกรมเวลาของการระบาดของโรคลัมปีสกินในอัฟริกา ยุโรปและเอเชีย
Authors: Ayesha Anwar
Authors: Veerasak Punyapornwittaya
Kanika Na Lampang
Ayesha Anwar
Issue Date: Oct-2022
Publisher: Chiang Mai : Graduate School, Chiang Mai University
Abstract: LSD is a major transboundary disease that has a global impact on the cattle sector. The study's goals were to identify patterns and key change points, as well as to forecast the number of LSD outbreak reports in Africa, Europe, and Asia. Data from the World Or-ganisation for Animal Health's LSD out-break reports (January 2005 to January 2022) were evaluated. Binary segmentation was used to identify statistically significant change points in the time series data, and auto-regressive moving average (ARIMA) and neural network auto-regressive (NNAR) models were used to forecast the number of LSD reports. Each continent had four significant change points, according to the find-ings. In the African data, the year between the third and fourth change points (2016-2019) had the largest mean number of LSD reports. During 2015-2017, all change points in LSD epidemics in Europe coincided with major outbreaks. After the third identified change point in 2018, Asia had the highest number of LSD complaints in 2019. ARIMA and NNAR both predict an increase in the total number of LSD reports in Africa over the course of the next three years (2022-2024) and a constant number in Europe. ARI-MA, on the other hand, forecasts a steady number of outbreaks throughout Asia, whilst NNAR forecasts an increase in 2023-2024. This study adds to our understanding of the epidemiology of LSD by providing data.
URI: http://cmuir.cmu.ac.th/jspui/handle/6653943832/78831
Appears in Collections:VET: Theses

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