<|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:"Reduced case fatality among hospitalized children during a war in Guinea-Bissau: a lesson in equity."
Abstract:"Background: During a recent armed conflict in Guinea-Bissau, we observed a marked decline in the case fatality among hospitalized children at the only paediatric department in the country. Aim: To analyse the causes behind the observed fall in case fatality. Material: All children hospitalized at the only paediatric department in the capital of Guinea-Bissau. The war cohort comprised all children hospitalized during the war, which lasted from June 1998 to May 1999, and the peace cohort comprised all children hospitalized in the year preceding the war. As part of a longitudinal community study, we also registered all children being hospitalized from the Bandim Health Project's study area, including routinely collected information on socio-economic background factors. Methods: The war cohort was compared with the peace cohort in terms of determinants for hospital case fatality. Through information in the community register, we examined post-hospital mortality in the 2 wk after discharge as well as socio-economic differences in recruitment during the war. Hospital case fatality was estimated by odds ratios and compared by multiple logistic regression. Community mortality risk was estimated by deaths per person years. Results: The case fatality among children aged 0-14 y fell during the war (age-adjusted OR = 0.58; 95% CI: 0.50-0.68). There was a uniform reduction in case fatality among children hospitalized less than 7 d, while we observed no decline among children hospitalized longer. There were more children per bed during the war and mean hospitalization time was shorter, and post-discharge mortality also fell (mortality ratio (MR) = 0.57; 95% CI: 0.40-0.83). Adjustment for socio-economic con-founders in recruitment during the war period made no difference to the estimated decline in case fatality. The decline in case fatality at the hospital was not explained by a general decline in mortality. Compared with the preceding year, the mortality ratio was 1.34 (1.20-1.51) in the Bandim Health Project's study area during the war. Adjusted for age, the decline in case fatality at the hospital was most marked for disadvantaged groups. For example, the general reduction in case fatality was 42% (95% CI: 11-63); however, children of mothers without any schooling experienced a reduction of 73% (95% CI: 27-90%), whereas the reduction was only 33% (95% CI: 14-61%) for children of mothers with school education. Conclusion: The decline in case fatality could be explained neither by a general decline in childhood mortality nor by changes in recruitment or discharge policy. The decline was therefore most likely due to improved treatment as a result of better availability of drugs funded by humanitarian aid and the presence of dedicated staff, which was offered relief food as compensation. Interventions improving case management may have a proportionately larger effect for poor families.."
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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 = [4];
Q3 = [2];
Q4 = [0];
Q5 = [1];
Q6 = [1].
Reduced case fatality among hospitalized children during a war in Guinea-Bissau: a lesson in equity
Background: During a recent armed conflict in Guinea-Bissau, we observed a marked decline in the case fatality among hospitalized children at the only paediatric department in the country. Aim: To analyse the causes behind the observed fall in case fatality. Material: All children hospitalized at the only paediatric department in the capital of Guinea-Bissau. The war cohort comprised all children hospitalized during the war, which lasted from June 1998 to May 1999, and the peace cohort comprised all children hospitalized in the year preceding the war. As part of a longitudinal community study, we also registered all children being hospitalized from the Bandim Health Project's study area, including routinely collected information on socio-economic background factors. Methods: The war cohort was compared with the peace cohort in terms of determinants for hospital case fatality. Through information in the community register, we examined post-hospital mortality in the 2 wk after discharge as well as socio-economic differences in recruitment during the war. Hospital case fatality was estimated by odds ratios and compared by multiple logistic regression. Community mortality risk was estimated by deaths per person years. Results: The case fatality among children aged 0-14 y fell during the war (age-adjusted OR = 0.58; 95% CI: 0.50-0.68). There was a uniform reduction in case fatality among children hospitalized less than 7 d, while we observed no decline among children hospitalized longer. There were more children per bed during the war and mean hospitalization time was shorter, and post-discharge mortality also fell (mortality ratio (MR) = 0.57; 95% CI: 0.40-0.83). Adjustment for socio-economic con-founders in recruitment during the war period made no difference to the estimated decline in case fatality. The decline in case fatality at the hospital was not explained by a general decline in mortality. Compared with the preceding year, the mortality ratio was 1.34 (1.20-1.51) in the Bandim Health Project's study area during the war. Adjusted for age, the decline in case fatality at the hospital was most marked for disadvantaged groups. For example, the general reduction in case fatality was 42% (95% CI: 11-63); however, children of mothers without any schooling experienced a reduction of 73% (95% CI: 27-90%), whereas the reduction was only 33% (95% CI: 14-61%) for children of mothers with school education. Conclusion: The decline in case fatality could be explained neither by a general decline in childhood mortality nor by changes in recruitment or discharge policy. The decline was therefore most likely due to improved treatment as a result of better availability of drugs funded by humanitarian aid and the presence of dedicated staff, which was offered relief food as compensation. Interventions improving case management may have a proportionately larger effect for poor families.