<|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:"Presence and mobility of the population during the first wave of Covid-19 outbreak and lockdown in Italy."
Abstract:"The non-medical policies implemented by many countries to flatten the curve during the COVID-19 outbreak has people stranded in their homes and some, out of their homes unable to return due to the disruptions in the mobility network. The availability of rich datasets (in our case, Facebook) has made it possible to study the mobility dynamics and spatial distribution of people during lockdown in Italy. Our interpretation is an effort to look deeper, describing the movements occurred during lockdown, including the territorial differences. We observe that, initially, tourists left the country and later Italians abroad managed to return, thereby, stabilising the population. With regards to internal mobility, the earliest affected regions see higher number of stationary users in the initial days of the outbreak while this is less significant for the central/ southern regions until the decree for the official lockdown on the 9th of March 2020, due 2 days later. Just before lockdown, there was not a significant exodus of people from the North to the rest of the country, instead, relocation of people between cities and their urban belts, but not towards remote areas. This will be elaborated in conclusions shedding light on possible changes in future cities.."
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 = [0];
Q5 = [1];
Q6 = [1].
Presence and mobility of the population during the first wave of Covid-19 outbreak and lockdown in Italy
The non-medical policies implemented by many countries to flatten the curve during the COVID-19 outbreak has people stranded in their homes and some, out of their homes unable to return due to the disruptions in the mobility network. The availability of rich datasets (in our case, Facebook) has made it possible to study the mobility dynamics and spatial distribution of people during lockdown in Italy. Our interpretation is an effort to look deeper, describing the movements occurred during lockdown, including the territorial differences. We observe that, initially, tourists left the country and later Italians abroad managed to return, thereby, stabilising the population. With regards to internal mobility, the earliest affected regions see higher number of stationary users in the initial days of the outbreak while this is less significant for the central/ southern regions until the decree for the official lockdown on the 9th of March 2020, due 2 days later. Just before lockdown, there was not a significant exodus of people from the North to the rest of the country, instead, relocation of people between cities and their urban belts, but not towards remote areas. This will be elaborated in conclusions shedding light on possible changes in future cities.