Results showed a low performance of the hospitals in case of an earthquake. The issue is due to the high seismic vulnerability of the existing structures. Given the importance of Lima city in Peru, structural and nonstructural retrofitting plans should be implemented to improve the preparedness of the health system in case of an emergency. (Disaster Med Public Health Preparedness. 2018;page 1 of 6).
The provision of education is a vital feature of a socially sustainable system. However, students in highly seismic areas are under permanent hazard, a critical situation for student populations with high vulnerability factors such as insecure infrastructure, low teacher salaries, and poor living conditions due to social exclusion and inequity. In this article, we use community-based elements, such as institutional arrangements and a collaborative and interdisciplinary approach, to develop a comprehensive multi-scale risk model for socially sustainable seismic risk reduction in schools. We analyze the case of schools in the city of Lima, Peru, integrating aims, objectives, and methodologies based on risk-reduction strategy from previous disciplinary studies. Identifying schools that, on one hand, can be most useful during emergencyrelief work and, on the other hand, educational facilities that could cause the most harm to students are priorities for a risk-reduction strategy. We identify social sustainability factors in schools, such as security and well-being of the student population, accessibility, incomes, basic service provision, and community organization. Specifying the spatial and territorial relationships within public school surroundings is essential to guaranteeing the effectiveness and efficiency of risk-mitigation strategies.
The failure of hospitals in recent tsunami have caused extensive social and economic losses. A simple but quantitative approach is required to assess the resilience of healthcare systems to tsunami, which relates not only to hospital building integrity, but also to maintaining hospital functionality. This paper proposes a new tsunami relative risk index (TRRI) that quantifies the impact of tsunami on critical units, (e.g. Intensive Care Unit, Maternity Ward, etc) in individual hospitals, as well as the impact on service provision across a network of hospitals. A survey form is specifically developed for collecting of field data on hospitals for the TRRI evaluation. In its current form TRRI is designed for hospital buildings of reinforced concrete construction, as these are the building types most commonly used worldwide for housing critical units. The TRRI is demonstrated through an application to three hospitals located along the southern coast of Sri Lanka. The TRRI is evaluated for three potential tsunami inundation events and is shown to be able to identify issues with both the building and functional aspects of hospital critical units. Three “what-if” intervention scenarios are presented and their effect on the TRRI is assessed. Through this exercise, it is shown that the TRRI can be used by decision makers to simply explore the effectiveness of individual and combined interventions in improving the tsunami resilience of healthcare provision across the hospital system.
Long‐distance commuting (LDC) is a growing phenomenon in specialized countries in extractive industries such as Chile. There has also been a growing concern about the potential impacts on the health of long‐distance commuters. This paper formalizes the relationship between commuting distance and self‐assessed health status and shows the monetary valuation of health costs for commuting long distances using a latent class approach. This econometric approach allows us to capture both preference and threshold heterogeneity. The results show that there are two classes of workers: the first group is not sensitive to commuting distance, whereas the monetary valuation of workers in the second group is equivalent to CLP $431 (US$0.68).
Measuring poverty is a first step to the design of effective public policies, however, it is also essential to know where the poor are located. The main objective of this research is to evaluate the spatial heterogeneity of the factors that influence monetary poverty for each district in Peru. We apply a Geographically Weighted Regression (GWR) approach, which allows us to capture the non-stationarity of the hidden data and to provide coefficients for each district, unlike the OLS model. This research mainly uses the Poverty Map and the Population and Household Census of Peru, both from 2007 and 2017. The overriding findings of our results indicate that female headship, secondary education, electricity, and sanitation services are directly associated with poverty reduction at the local level. For 2007, significant effects are mainly concentrated in the districts of Pasco, Lima and Cajamarca regions. For 2017, the results show a shift towards districts of Junín, Huancavelica, and Cajamarca regions. Likewise, it is highlighted that the highest mean negative effect on poverty is generated by Secondary Education in the GWR estimates; while malnutrition represents the highest mean positive effect on poverty for the level and intercensal models. Finally, the empirical evidence found in this research can help establish better policy designs at the district level.
Este artículo analiza el proceso de convergencia espacial del crecimiento en las 24 regiones del Perú durante el período 1979-2017. Realizamos un análisis exploratorio de datos espaciales con estadísticas globales y locales, como Moran I, para proporcionar evidencia empírica de las dependencias espaciales en el PIB per cápita regional. . Luego, estimamos la ecuación de convergencia utilizando modelos de panel espacial que controlan la heterogeneidad espacial y la interdependencia espacial, así como otras características económicas estructurales a nivel regional. Los resultados empíricos muestran que la convergencia espacial es una conclusión muy confiable durante este período y demuestran que los derrames regionales del PIB per cápita espacial juegan un papel esencial en la determinación del crecimiento a nivel local. Además, se prefiere el modelo Spatial Durbin en la formación de cuatro grupos de convergencia. El primer clúster es muy productivo y dinámico; el segundo conglomerado está compuesto por regiones selváticas y de productividad negativa; el tercer conglomerado está formado por regiones moderadamente productivas y costeras; y el cuarto grupo está compuesto por regiones estancadas y montañosas. Por último, estos resultados pueden ser fundamentales para dar un mayor enfoque a las políticas gubernamentales a largo plazo dirigidas a las regiones pobres y estancadas.
This research presents an overview of the evolution of regional economic studies in Peru. After a brief introduction, the document presents a summary of the different conceptions of space in Regional Economics through time. In addition, the document shows the origins of Regional Economics, as well as the factors that explain the interest in the development of regional studies in the Latin American context. This document also explains the importance of the geographical space of Peru for regional research. Indeed, the country is the perfect setting because Peru has a wide geographic diversity (ecosystems, microclimates) throughout its territory, it has implemented a variety of public policies to propose economic growth measures, and it has many social issues to propose territorial policies (migration, crime, health, employment, among others). Despite these characteristics, regional research in Peru is relatively less than in other Latin American countries. Finally, the document offers the contributions and criticisms of the regional studies in the Peruvian context.
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