Prediction of Human Brucellosis in China Based on Temperature and NDVI

Brucellosis occurs periodically and causes great economic and health burdens. Brucellosis prediction plays an important role in its prevention and treatment. This paper establishes relationships between human brucellosis (HB) and land surface temperature (LST), and the normalized difference vegetati...

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Main Authors: Yongqing Zhao, Rendong Li, Juan Qiu, Xiangdong Sun, Lu Gao, Mingquan Wu
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:https://www.mdpi.com/1660-4601/16/21/4289
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spelling doaj-22f421da10864fe99a79825657a41d4a2020-11-25T01:35:57ZengMDPI AGInternational Journal of Environmental Research and Public Health1660-46012019-11-011621428910.3390/ijerph16214289ijerph16214289Prediction of Human Brucellosis in China Based on Temperature and NDVIYongqing Zhao0Rendong Li1Juan Qiu2Xiangdong Sun3Lu Gao4Mingquan Wu5Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, ChinaInstitute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, ChinaInstitute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, ChinaChina Animal Health and Epidemiology Center, Qingdao 266032, ChinaChina Animal Health and Epidemiology Center, Qingdao 266032, ChinaThe State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaBrucellosis occurs periodically and causes great economic and health burdens. Brucellosis prediction plays an important role in its prevention and treatment. This paper establishes relationships between human brucellosis (HB) and land surface temperature (LST), and the normalized difference vegetation index (NDVI). A seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model is constructed to predict trends in brucellosis rates. The fitted results (Akaike Information Criterion (AIC) = 807.58, Schwarz Bayes Criterion (SBC) = 819.28) showed obvious periodicity and a rate of increase of 138.68% from January 2011 to May 2016. We found a significant effect between HB and NDVI. At the same time, the prediction part showed that the highest monthly incidence per year has a decreasing trend after 2015. This may be because of the brucellosis prevention and control measures taken by the Chinese Government. The proposed model allows the early detection of brucellosis outbreaks, allowing more effective prevention and control.https://www.mdpi.com/1660-4601/16/21/4289brucellosisremote sensingtime-seriessarimax
collection DOAJ
language English
format Article
sources DOAJ
author Yongqing Zhao
Rendong Li
Juan Qiu
Xiangdong Sun
Lu Gao
Mingquan Wu
spellingShingle Yongqing Zhao
Rendong Li
Juan Qiu
Xiangdong Sun
Lu Gao
Mingquan Wu
Prediction of Human Brucellosis in China Based on Temperature and NDVI
International Journal of Environmental Research and Public Health
brucellosis
remote sensing
time-series
sarimax
author_facet Yongqing Zhao
Rendong Li
Juan Qiu
Xiangdong Sun
Lu Gao
Mingquan Wu
author_sort Yongqing Zhao
title Prediction of Human Brucellosis in China Based on Temperature and NDVI
title_short Prediction of Human Brucellosis in China Based on Temperature and NDVI
title_full Prediction of Human Brucellosis in China Based on Temperature and NDVI
title_fullStr Prediction of Human Brucellosis in China Based on Temperature and NDVI
title_full_unstemmed Prediction of Human Brucellosis in China Based on Temperature and NDVI
title_sort prediction of human brucellosis in china based on temperature and ndvi
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1660-4601
publishDate 2019-11-01
description Brucellosis occurs periodically and causes great economic and health burdens. Brucellosis prediction plays an important role in its prevention and treatment. This paper establishes relationships between human brucellosis (HB) and land surface temperature (LST), and the normalized difference vegetation index (NDVI). A seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model is constructed to predict trends in brucellosis rates. The fitted results (Akaike Information Criterion (AIC) = 807.58, Schwarz Bayes Criterion (SBC) = 819.28) showed obvious periodicity and a rate of increase of 138.68% from January 2011 to May 2016. We found a significant effect between HB and NDVI. At the same time, the prediction part showed that the highest monthly incidence per year has a decreasing trend after 2015. This may be because of the brucellosis prevention and control measures taken by the Chinese Government. The proposed model allows the early detection of brucellosis outbreaks, allowing more effective prevention and control.
topic brucellosis
remote sensing
time-series
sarimax
url https://www.mdpi.com/1660-4601/16/21/4289
work_keys_str_mv AT yongqingzhao predictionofhumanbrucellosisinchinabasedontemperatureandndvi
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AT juanqiu predictionofhumanbrucellosisinchinabasedontemperatureandndvi
AT xiangdongsun predictionofhumanbrucellosisinchinabasedontemperatureandndvi
AT lugao predictionofhumanbrucellosisinchinabasedontemperatureandndvi
AT mingquanwu predictionofhumanbrucellosisinchinabasedontemperatureandndvi
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