Quantifying livestock vulnerability to snow disasters in the Tibetan Plateau: Comparing different modeling techniques for prediction

Ye, Tao; Liu, Weihang; Mu, Qingyang; Zong, Shuo; Li, Yijia; Shi, Peijun

doi:10.1016/j.ijdrr.2020.101578

Cited by 20 publications

(11 citation statements)

References 49 publications

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“…The dose-response association was normally expressed graphically and showed different mathematical distributions to express a clear relationship (Sullivan et al 2005 ). Mathematically, a dose-response relationship showed the expectation of potential loss as a function of different environmental indicators (Ye et al 2020 ). Chuang et al ( 2016 ) used GAM to explore the dose-response association between the daptomycin dose and mortality.…”

Section: Methodsmentioning

confidence: 99%

Association between meteorological indicators and COVID-19 pandemic in Pakistan

Raza

Khan²,

Ali

et al. 2020

Environ Sci Pollut Res

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This study was designed to investigate the impact of meteorological indicators (temperature, rainfall, and humidity) on total COVID-19 cases in Pakistan, its provinces, and administrative units from March 10, 2020, to August 25, 2020. The correlation analysis showed that COVID-19 cases and temperature showed a positive correlation. It implies that the increase in COVID-19 cases was reported due to an increase in the temperature in Pakistan, its provinces, and administrative units. The generalized Poisson regression showed that the rise in the expected log count of COVID-19 cases was 0.024 times for a 1°C rise in the average temperature in Pakistan. Second, the correlation between rainfall and COVID-19 cases was negative in Pakistan. However, the regression coefficient between the expected log count of COVID-19 cases and rainfall was insignificant in Pakistan. Third, the correlation between humidity and the total COVID-19 cases was negative, which implies that the increase in humidity is beneficial to stop the transmission of COVID-19 in Pakistan, its provinces, and administrative units. The reduction in the expected log count of COVID-19 cases was 0.008 times for a 1% increase in the humidity per day in Pakistan. However, humidity and COVID-19 cases were positively correlated in Sindh province. It is required to create awareness among the general population, and the government should include the causes, symptoms, and precautions in the educational syllabus. Moreover, people should adopt the habit of hand wash, social distancing, personal hygiene, mask-wearing, and the use of hand sanitizers to control the COVID-19.

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Section: Methodsmentioning

confidence: 99%

Association between meteorological indicators and COVID-19 pandemic in Pakistan

Raza

Khan²,

Ali

et al. 2020

Environ Sci Pollut Res

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“…A dose–response curve linked multiple dose-variables ( x ) with the probability of response-variable (infection) (Brouwer et al 2017 ; Raza et al 2020 ). In other words, the dose–response curve revealed the expectation of potential loss due to various environmental variables (Raza et al 2020 ; Ye et al 2020 ). This study applied the GAM to draw a dose–response curve between dose variables (outbreak days, wind speed, and PM2.5) and response variables (COVID-19 infection).…”

Section: Methodsmentioning

confidence: 99%

Impact of wind speed and air pollution on COVID-19 transmission in Pakistan

Ali

Raza

Saghir

et al. 2021

Int. J. Environ. Sci. Technol.

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This study investigated the effect of wind speed and air pollution on COVID-19 from March 10, 2020, to October 04, 2020, in Pakistan. Wind speed and COVID-19 had positive correlation in Pakistan and its provinces. The inverted U-shaped dose–response curve was found for wind speed and COVID-19 in Punjab. Initially, the dose–response curve showed a positive link between wind speed and COVID-19 in Pakistan, Sindh, Khyber Pakhtunkhwa, and Islamabad Capital Territory. Later, it becomes downward sloped in Sindh, Khyber Pakhtunkhwa, and Islamabad Capital Territory. The expected log count of COVID-19 was increased by 0.113 times (Pakistan), 0.074 times (Punjab), 0.042 times (Sindh), and 0.082 times (Khyber Pakhtunkhwa) for a 1 km/h increase in the wind speed. The correlation between particulate matter and COVID-19 was positive (Pakistan, Punjab, and Islamabad Capital Territory) and negative (Sindh). The dose–response curve for particulate matter and COVID-19 had inverted U-shaped (Pakistan, Punjab, and Khyber Pakhtunkhwa) positively sloped (Islamabad Capital Territory), and negatively sloped (Sindh). The inverted U-shaped association shows that the COVID-19 initially increased due to a rise in the particulate matter but reduced when the particulate matter was above the threshold level. The particulate matter was also responsible to wear face masks and restricted mobility. The expected log count of COVID-19 cases was reduced by 0.005 times in Sindh for 1 unit increase in particulate matter. It is recommended to reduce particulate matter to control respiratory problems. The government should use media (print, electronic, social) and educational syllabus to create awareness about precautionary measures.

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“…To fulfil the goal of event-based modelling, the vulnerability relationship must be built on event basis. Therefore, the results from (Li et al, 2018;Ye et al, 2018) were considered. Following their suggestion from the multi-method comparison, we chose the predictive version of the generalized additive model, ln s ,…”

Section: Vulnerability Functionmentioning

confidence: 99%

Probabilistic Risk Assessment of Livestock Snow Disasters in the Qinghai-Tibetan Plateau

Liu

Shi

et al. 2018

Preprint

Self Cite

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Abstract. Understanding risk using a quantitative risk assessment offers critical information for risk-informed reduction actions, investing in building resilience, and planning for adaptation. This study develops an event-based probabilistic risk assessment model for livestock snow disasters in the Qinghai-Tibetan Plateau (QTP) region and derives risk assessment results based on historical climate conditions (1980–2015) and present-day prevention capacity. In the model a hazard module was developed to identify/simulate individual snow disaster events based on boosted regression trees. Together with a fitted quantitative vulnerability function, and exposure derived from vegetation type and grassland carrying capacity, risk metrics based on livestock mortality and mortality rate were estimated. In our results, high risk regions include the Nyainqêntanglha Range, Tanggula Range, Bayankhar Mountains and the region between the Kailas Range and neighboring Himalayas. In these regions, annual livestock mortality rates were estimated as > 2 % and mortality was estimated as > 2 sheep unit/km2 at a return period of 1/20 a. Prefectures identified with extremely high risk included Yushu in Qinghai Province and Naqu, Shigatse, Linzhi, and Nagri in the Tibet Autonomous Region. In these prefectures, a snow disaster event with return period of 1/20 a or higher can easily claim a total loss of more than 200 000 sheep units. Our results provide a quantitative reference for preparedness and insurance solutions in reducing mortality risk. The methodology developed here can be further adapted to future climate change risk analyses and provide important information for planning climate change adaption in the QTP region.

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Quantifying livestock vulnerability to snow disasters in the Tibetan Plateau: Comparing different modeling techniques for prediction

Cited by 20 publications

References 49 publications

Association between meteorological indicators and COVID-19 pandemic in Pakistan

Association between meteorological indicators and COVID-19 pandemic in Pakistan

Impact of wind speed and air pollution on COVID-19 transmission in Pakistan

Probabilistic Risk Assessment of Livestock Snow Disasters in the Qinghai-Tibetan Plateau

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