The qualitative evidence described above strongly indicates that urban populations have access to better health, nutrition and services, and are at lower risk of malaria transmission than rural populations. To quantify these differences, however, it is necessary to determine where the urban and rural populations of Africa are located. We first describe a method to partition objectively the population of Africa into urban, peri-urban and rural classes. This is achieved by investigating the population density that is associated with the largest urban areas in Africa and how it decreases with increasing distance from the urban centre. Once these population density groupings are defined they can be extrapolated to the whole continent with human population distribution maps. After such a map has been created it is then possible to overlay entomological survey data onto these population classes to examine the extent to which transmission (APfEIR) is reduced when moving from rural to urban population densities. This method has the advantage of avoiding any ambiguity in the definition of urban and rural.
As national registration systems for malaria are often inadequate, malaria burden estimates for Africa are generated by calculating the morbidity and mortality rates at intensively studied sites and associating these rates with malaria risk classes82 (link),83 . These risk classes and human population distribution have been mapped in Africa, so morbidity and mortality figures can be calculated across the wider continent. In addition, recent work has shown that these risk classes are linearly related to the PR84 . To link these two approaches, we elaborate on previous work that has demonstrated a correlation between APfEIR and PR in a community85 (link). We can therefore use the APfEIR data to quantify the impact of urbanization on transmission in Africa and its impact on PR and the malaria risk classes with which they are associated. Estimates of malaria morbidity and mortality for Africa in 2000 can then be adjusted for the effect of urbanization.
As national registration systems for malaria are often inadequate, malaria burden estimates for Africa are generated by calculating the morbidity and mortality rates at intensively studied sites and associating these rates with malaria risk classes82 (link),83 . These risk classes and human population distribution have been mapped in Africa, so morbidity and mortality figures can be calculated across the wider continent. In addition, recent work has shown that these risk classes are linearly related to the PR84 . To link these two approaches, we elaborate on previous work that has demonstrated a correlation between APfEIR and PR in a community85 (link). We can therefore use the APfEIR data to quantify the impact of urbanization on transmission in Africa and its impact on PR and the malaria risk classes with which they are associated. Estimates of malaria morbidity and mortality for Africa in 2000 can then be adjusted for the effect of urbanization.
