<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"Coronavirus and Migration: Analysis of Human Mobility and the Spread of COVID-19."
Abstract:"Reactions, measures as well as discourses dealing with the current pandemic vary significantly across the world. While some countries were completely locked down, as was the case in Italy, some had claimed to have very few or no cases, as was the case in Turkey and Indonesia by March 10th, 2020. Nevertheless, the spread of COVID-19 from China has been clearly linked to those travelling from Wuhan in Hubei province in Central China. Therefore, it is important to understand the fravel density/volume of passengers carried as well as routes from Wuhan through connected main regional air travel hubs across China. In this study, we developed a model on migration and fravel intensity that can explain outbreak and spread of COVID-19 since it appeared at the end of 2019. We show that the presence of migrant stock populations of Chinese origin and the immigrant stock in China are useful indicators in the prediction of the spread of the outbreak worldwide in the event of interaction with several other macro factors. We argue that monitoring immigrant stock data and travel volume data based on human mobility corridors (i.e. origins and destinations), countries could have been better prepared and taken early measures to contain the spread of COVID-19.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

Q1 = [];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [1];
Q6 = [1].
Coronavirus and Migration: Analysis of Human Mobility and the Spread of COVID-19
Reactions, measures as well as discourses dealing with the current pandemic vary significantly across the world. While some countries were completely locked down, as was the case in Italy, some had claimed to have very few or no cases, as was the case in Turkey and Indonesia by March 10th, 2020. Nevertheless, the spread of COVID-19 from China has been clearly linked to those travelling from Wuhan in Hubei province in Central China. Therefore, it is important to understand the fravel density/volume of passengers carried as well as routes from Wuhan through connected main regional air travel hubs across China. In this study, we developed a model on migration and fravel intensity that can explain outbreak and spread of COVID-19 since it appeared at the end of 2019. We show that the presence of migrant stock populations of Chinese origin and the immigrant stock in China are useful indicators in the prediction of the spread of the outbreak worldwide in the event of interaction with several other macro factors. We argue that monitoring immigrant stock data and travel volume data based on human mobility corridors (i.e. origins and destinations), countries could have been better prepared and taken early measures to contain the spread of COVID-19.