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. 2010 Mar 16;4(3):e631.
doi: 10.1371/journal.pntd.0000631.

Informal urban settlements and cholera risk in Dar es Salaam, Tanzania

Affiliations

Informal urban settlements and cholera risk in Dar es Salaam, Tanzania

Katherine Penrose et al. PLoS Negl Trop Dis. .

Abstract

Background: As a result of poor economic opportunities and an increasing shortage of affordable housing, much of the spatial growth in many of the world's fastest-growing cities is a result of the expansion of informal settlements where residents live without security of tenure and with limited access to basic infrastructure. Although inadequate water and sanitation facilities, crowding and other poor living conditions can have a significant impact on the spread of infectious diseases, analyses relating these diseases to ongoing global urbanization, especially at the neighborhood and household level in informal settlements, have been infrequent. To begin to address this deficiency, we analyzed urban environmental data and the burden of cholera in Dar es Salaam, Tanzania.

Methodology/principal findings: Cholera incidence was examined in relation to the percentage of a ward's residents who were informal, the percentage of a ward's informal residents without an improved water source, the percentage of a ward's informal residents without improved sanitation, distance to the nearest cholera treatment facility, population density, median asset index score in informal areas, and presence or absence of major roads. We found that cholera incidence was most closely associated with informal housing, population density, and the income level of informal residents. Using data available in this study, our model would suggest nearly a one percent increase in cholera incidence for every percentage point increase in informal residents, approximately a two percent increase in cholera incidence for every increase in population density of 1000 people per km(2) in Dar es Salaam in 2006, and close to a fifty percent decrease in cholera incidence in wards where informal residents had minimally improved income levels, as measured by ownership of a radio or CD player on average, in comparison to wards where informal residents did not own any items about which they were asked. In this study, the range of access to improved sanitation and improved water sources was quite narrow at the ward level, limiting our ability to discern relationships between these variables and cholera incidence. Analysis at the individual household level for these variables would be of interest.

Conclusions/significance: Our results suggest that ongoing global urbanization coupled with urban poverty will be associated with increased risks for certain infectious diseases, such as cholera, underscoring the need for improved infrastructure and planning as the world's urban population continues to expand.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Municipal and ward boundaries in Dar es Salaam, Tanzania.
A total of 45 wards were included in the Unplanned Land Property Register Project, and are indicated by stippling.
Figure 2
Figure 2. Population density by ward and major roads in Dar es Salaam, Tanzania, 2006.
Ward populations in 2006 were projected by the National Bureau of Statistics using data from the 2002 Census.
Figure 3
Figure 3. Number of suspected cholera cases by month, year, and municipality in Dar es Salaam, 2006–2008.
“NR” indicates months for which no cholera cases were reported. The shaded areas indicate time periods for which data were available at the ward level.
Figure 4
Figure 4. Cholera incidence in Dar es Salaam, 2006.
Legend categories were determined by natural breaks.
Figure 5
Figure 5. Scatter plots of the natural log of cholera incidence/10,000 population versus potential predictors among 45 wards in Dar es Salaam, Tanzania.
As the presence of roads was a categorical predictor, it was not included here. Pearson's correlation coefficient between each variable and the natural log of cholera incidence/10,000 population is indicated. * p<0.05, ** p<0.01, *** p<0.001

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