Population Movements to a Growth-Pole: The Case of Hosur, Tamil Nadu
In: Third world planning review: TWPR, Band 12, Heft 3, S. 231
ISSN: 2058-1076
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In: Third world planning review: TWPR, Band 12, Heft 3, S. 231
ISSN: 2058-1076
In: Third world planning review: TWPR, Band 12, Heft 3, S. 231-247
ISSN: 0142-7849
This paper discusses the effects of growth-pole development on population movements in a backward district of Tamil Nadu. The fast growth in population in Hosur in recent years is caused by immigration from other urban areas, mainly outside the district. (DSE)
World Affairs Online
BACKGROUND: Following the regional outbreak in China, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread all over the world, presenting the healthcare systems with huge challenges worldwide. In Germany the coronavirus diseases 2019 (COVID-19) pandemic has resulted in a slowly growing demand for health care with a sudden occurrence of regional hotspots. This leads to an unpredictable situation for many hospitals, leaving the question of how many bed resources are needed to cope with the surge of COVID-19 patients. OBJECTIVE: In this study we created a simulation-based prognostic tool that provides the management of the University Hospital of Augsburg and the civil protection services with the necessary information to plan and guide the disaster response to the ongoing pandemic. Especially the number of beds needed on isolation wards and intensive care units (ICU) are the biggest concerns. The focus should lie not only on the confirmed cases as the patients with suspected COVID-19 are in need of the same resources. MATERIAL AND METHODS: For the input we used the latest information provided by governmental institutions about the spreading of the disease, with a special focus on the growth rate of the cumulative number of cases. Due to the dynamics of the current situation, these data can be highly variable. To minimize the influence of this variance, we designed distribution functions for the parameters growth rate, length of stay in hospital and the proportion of infected people who need to be hospitalized in our area of responsibility. Using this input, we started a Monte Carlo simulation with 10,000 runs to predict the range of the number of hospital beds needed within the coming days and compared it with the available resources. RESULTS: Since 2 February 2020 a total of 306 patients were treated with suspected or confirmed COVID-19 at this university hospital. Of these 84 needed treatment on the ICU. With the help of several simulation-based forecasts, the required ICU and normal bed ...
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