Difference between revisions of "Human development/Description"
| Line 20: | Line 20: | ||
Here, we only discuss the first three causes of mortality as they are linked to environmental factors. The mortality rate due to a specific disease is a multiplication of the incidence rate (fraction of the population with the specific disease) and the case fatality rate (the fraction of people who die from a specific disease), distinguishing for the two sexes and five-year age cohorts. These mortality rates can then be used to calculated age-specific life expectancy (for details see [[Hilderink, 2000]]). | Here, we only discuss the first three causes of mortality as they are linked to environmental factors. The mortality rate due to a specific disease is a multiplication of the incidence rate (fraction of the population with the specific disease) and the case fatality rate (the fraction of people who die from a specific disease), distinguishing for the two sexes and five-year age cohorts. These mortality rates can then be used to calculated age-specific life expectancy (for details see [[Hilderink, 2000]]). | ||
| − | + | === Malaria risk === | |
| + | In the [[GISMO model]], incidence rates of malaria are determined by the areas which are suitable for the malaria mosquito, based on the monthly climatic factors of temperature and precipitation ([[Craig et al., 1999]]). Incidence rates are decreased by the level of insecticide treated bed nets and indoor residual spraying, modelled separately as potential policy options. The case fatality rate of malaria is increased by underweight levels and decreased by case management, i.e. treatment. | ||
| − | + | === Access to food, water and energy === | |
| + | GISMO relates incidence and case fatality rates of major communicable (infectious) diseases to access to food, water and energy (see Table), with access defined by per-capita food availability, access to safe drinking water and improved sanitation, and access to modern energy sources for cooking and heating. The per-capita food availability (Kcal/cap/day) is obtained from the [[Agricultural economy and forestry]] module. The levels of access to safe drinking water and improved sanitation are modelled separately by applying linear regression. The explanatory variables include GDP per capita, urbanisation rate and population density. Developments in water supply are assumed to be implemented ahead of sanitation. As such, developments in access follow a pathway from no sustainable access to safe drinking water and basic sanitation, to improved water supply only, improved water supply and sanitation, household connection for water supply only, and to a household connection for watersupply and sanitation. The level of access to modern energy sources for cooking and heating distinguishes between the use of | ||
# Traditional biomass and coal on traditional stoves; | # Traditional biomass and coal on traditional stoves; | ||
# Traditional biomass and coal on improved stoves; | # Traditional biomass and coal on improved stoves; | ||
| Line 42: | Line 44: | ||
Incidence rates of diarrhoea depend on the different levels of access to drinking water and sanitation facilities, child underweight levels and also on climate change. Case fatality rates are increased by underweight levels and decreased by the level of oral rehydration therapy. | Incidence rates of diarrhoea depend on the different levels of access to drinking water and sanitation facilities, child underweight levels and also on climate change. Case fatality rates are increased by underweight levels and decreased by the level of oral rehydration therapy. | ||
| − | + | === Urban air pollution === | |
| + | Mortality rates of lung cancer, cardiopulmonary diseases and acute respiratory infections due to urban air pollution (i.e. PM10 and PM2.5 concentration levels) are derived by applying the [[HasAcronym::GBD]] methodology ([[Mathers and Loncar, 2006]]). Based on the emissions of NOx, SO2 and black carbon ([[Emissions]]), PM10 concentration levels are determined using the [[Global Urban Air quality Model]] (GUAM). GUAM originates from the GMAPS model ([[Pandey et al., 2006]]), which determines PM10 concentration levels by economic activity, population, urbanisation and meteorological factors. PM2.5 concentrations are obtained using a region-specific PM10–PM2.5 ratio. Based on these concentration levels and the exposed population, mortality attributable to the aforementioned causes of death is derived using relative risks. These relative risks have been obtained from epidemiological literature ([[Dockery et al., 1993]]; [[Pope et al., 1995]]). | ||
== GISMO poverty model == | == GISMO poverty model == | ||
Revision as of 19:27, 16 December 2013
Parts of Human development/Description
| Component is implemented in: |
|
| Related IMAGE components |
| Projects/Applications |
| Models/Databases |
| Key publications |
| References |
