<|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:"HUMAN MOBILITY AND MALARIA RISK IN THE NAYA RIVER BASIN OF COLOMBIA."
Abstract:"This paper develops and tests a methodology for examining the manner and the extent to which human mobility can be associated with malaria risk within an endemic area. The paper presents entomological, epidemiological and mobility results obtained from macro data and micro data. Results indicate that malaria is concentrated in the delta zone of the Naya river basin where the circulation of people into this zone for economic reasons occurs at a time when vector densities are high. High human density combined with high vector density ensures continuous and intense transmission of malaria. In attempting to measure intensity of transmission, microscopic analysis of parasitaemia was found to underestimate prevalence showing it to be very low or negligible, whereas serological data collected during the same period of time reveal that prevalence is high, and similar for both sexes. Serological data also indicate that prevalence increase's with age particularly from adolescence onwards. Since mobility for agricultural purposes involves able-bodied males and females, there seems ample justification for concluding that human mobility into certain areas increases the risk of infection for adults, particularly when such mobility coincides with peak rainfall and vector densities. Micro-level data are critical in pinpointing causation and small area variations in risk. Thus the beach area is a high risk area within the delta region, particularly for adults, and his is likely to be because of high vector biting rates in the beach environment. One conclusion is that micro analysis of behaviour, when linked to epidemiological data are particularly useful in defining and locating areas and groups at highest risk; using such information to achieve intensive coverage on a small scale may be more cost-effective than attempting to achieve vector or chemotherapeutic control over a wider area for all groups.."
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 = [];
Q6 = [1].
HUMAN MOBILITY AND MALARIA RISK IN THE NAYA RIVER BASIN OF COLOMBIA
This paper develops and tests a methodology for examining the manner and the extent to which human mobility can be associated with malaria risk within an endemic area. The paper presents entomological, epidemiological and mobility results obtained from macro data and micro data. Results indicate that malaria is concentrated in the delta zone of the Naya river basin where the circulation of people into this zone for economic reasons occurs at a time when vector densities are high. High human density combined with high vector density ensures continuous and intense transmission of malaria. In attempting to measure intensity of transmission, microscopic analysis of parasitaemia was found to underestimate prevalence showing it to be very low or negligible, whereas serological data collected during the same period of time reveal that prevalence is high, and similar for both sexes. Serological data also indicate that prevalence increase's with age particularly from adolescence onwards. Since mobility for agricultural purposes involves able-bodied males and females, there seems ample justification for concluding that human mobility into certain areas increases the risk of infection for adults, particularly when such mobility coincides with peak rainfall and vector densities. Micro-level data are critical in pinpointing causation and small area variations in risk. Thus the beach area is a high risk area within the delta region, particularly for adults, and his is likely to be because of high vector biting rates in the beach environment. One conclusion is that micro analysis of behaviour, when linked to epidemiological data are particularly useful in defining and locating areas and groups at highest risk; using such information to achieve intensive coverage on a small scale may be more cost-effective than attempting to achieve vector or chemotherapeutic control over a wider area for all groups.