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Item type:Publication, Between war and politics: National armies, military logistics and the (de)construction of the state during the Peru-Bolivian Confederation, 1836–1839(Universidad Pompeu Fabra, 2024-01-01)To consolidate the project of the Peru-Bolivian Confederation (1836-1839), the logistical needs regarding public administration by the State were fundamental. However, due to the declaration of war by Chile in 1836 and the military expeditions undertaken in 1837 and 1838, it was necessary to organize the mobilization of men, resources, and weapons for the functioning of the army. However, these needs were not always fully met, since the previous years framed in the Peruvian civil war generated counterproductive effects. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Inequality in the distribution of resources and health care in the poverty quintiles: Evidence from Peruvian comprehensive health insurance 2018–2019(Modestum LTD, 2024-02-01)In many regions of the world, healthcare is inequitable and limited, affecting poor populations who need greater health opportunities. Given that Peru’s comprehensive health insurance (SIS) seeks to enhance its coverage for the entire population, it is important to know if its coverage benefits the poorest populations. Objectives: To determine the allocation of SIS resources and care to the poorest quintile during 2018 and 2019 in Peru. Methods: We conducted a secondary analysis of data from five Peruvian technical institutions. In 39,8207 Peruvian households, we analyzed the per capita budget assigned to the population affiliated with SIS in microregions of quintile 1 and quintile 2 (poor), and quintile 4 and quintile 5 (non-poor), health coverage, and the level of poverty considering the human development index (HDI) and the regional competitiveness index (RCI). Results: The poorest regions are inversely correlated with HDI and RCI and have an average service of 25.0% affiliates. In poor areas, the allocated budget was lower (approximately $303,000 to $2.2 million), but the proportion of members requiring care was higher (>70.0%). The budget allocated to health was unfair (p<0.05) between poor areas (maximum resources from $96.28 to $108.14) and non-poor areas (maximum resources from $150.00 to $172.43). Low budget allocations and low household per capita income contributed to poverty in quintile 1 and quintile 2 (p<0.01). Conclusions: the poorest regions have greater inequity and the majority of affiliates do not use or do not have access to SIS services, but they have a greater need for health care. In addition, poor regions have a high amount of population without SIS coverage, and low allocated budgets, which affects competitiveness and regional development.