Cholera Epidemic in Guinea-Bissau (2008): The Importance of “Place”

As resources are limited when responding to cholera outbreaks, knowledge about where to orient interventions is crucial. We describe the cholera epidemic affecting Guinea-Bissau in 2008 focusing on the geographical spread in order to guide prevention and control activities

Geographical distribution of the probability of finding a house with at least one cholera case in Bairro Bandim (Bissau) in percentage and areas over the 95% confidence interval.

<p>Coordinates expressed in sexagesimal degrees. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019005#pone-0019005-g005" target="_blank">Figure 5a</a> shows the Google Earth™ picture and the overimposed image of the risk surface (probability of finding a house with at least one cholera case). The <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019005#pone-0019005-g005" target="_blank">figure 5b</a> shows the risk surface and the two areas with statistically significant higher risk (black bold line). The same two clusters were detected (dashed blue circles) using the Kulldorff's spatial scan statistic (cluster A: Log likelihood ratio = 9.95, P = 0.029; cluster B: Log likelihood ratio = 8.81, P = 0.05).</p

Differences of K-functions and 95% confidence intervals between households with cholera cases and households without cases in Bairro Bandim (Bissau), 2008–2009.

<p>A homogeneous set of points in the plane is a set that is distributed such that approximately the same number of points occurs in any circular region of a given area. A set of points that lacks homogeneity is spatially clustered. The k-function is defined as the expected number of points within a distance <i>s</i> of an arbitrary point, divided by the overall density of the points. Due to variations in the spatial distribution of the population at risk, a k-function computed only for cases may not be informative. Instead, the k-function calculated for cases can be compared with the one calculated for non-cases, with the difference between the two functions representing a measure of the extra-aggregation of cases over and above the observed for the non-cases. This difference is represented in the figure above, showing extra-aggregation of cases.</p

Number of cases, population, attack rate per 100 people (AR%), risk ratios (RR) and adjusted risk ratios (ARR) by age, sex and sanitary area.

<p>*Cholera treatment unit set up in this area.</p><p>**Cholera treatment centre set up in this area.</p><p>Sector Autónomo de Bissau, 2008.</p

Age and gender adjusted cholera attack rates (%) by Sanitary Area in Sector Autónomo de Bissau, 2008–2009.

<p>Coordinates expressed in sexagesimal degrees. * Sanitary area with a cholera treatment centre. + Sanitary area with a cholera treatment unit.</p

Geographical distribution of the crude cholera attack rate by region and sub-regions in Guinea- Bissau, 2008–2009.

<p>Coordinates expressed in sexagesimal degrees.</p

Weekly number of cholera cases and case fatality ratio (CFR%) in Guinea-Bissau 2008–2009.

<p>Weekly number of cholera cases and case fatality ratio (CFR%) in Guinea-Bissau 2008–2009.</p