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1.
PLoS Negl Trop Dis ; 6(11): e1901, 2012.
Article in English | MEDLINE | ID: mdl-23145204

ABSTRACT

BACKGROUND: Use of cholera vaccines in response to epidemics (reactive vaccination) may provide an effective supplement to traditional control measures. In Haiti, reactive vaccination was considered but, until recently, rejected in part due to limited global supply of vaccine. Using Bissau City, Guinea-Bissau as a case study, we explore neighborhood-level transmission dynamics to understand if, with limited vaccine and likely delays, reactive vaccination can significantly change the course of a cholera epidemic. METHODS AND FINDINGS: We fit a spatially explicit meta-population model of cholera transmission within Bissau City to data from 7,551 suspected cholera cases from a 2008 epidemic. We estimated the effect reactive vaccination campaigns would have had on the epidemic under different levels of vaccine coverage and campaign start dates. We compared highly focused and diffuse strategies for distributing vaccine throughout the city. We found wide variation in the efficiency of cholera transmission both within and between areas of the city. "Hotspots", where transmission was most efficient, appear to drive the epidemic. In particular one area, Bandim, was a necessary driver of the 2008 epidemic in Bissau City. If vaccine supply were limited but could have been distributed within the first 80 days of the epidemic, targeting vaccination at Bandim would have averted the most cases both within this area and throughout the city. Regardless of the distribution strategy used, timely distribution of vaccine in response to an ongoing cholera epidemic can prevent cases and save lives. CONCLUSIONS: Reactive vaccination can be a useful tool for controlling cholera epidemics, especially in urban areas like Bissau City. Particular neighborhoods may be responsible for driving a city's cholera epidemic; timely and targeted reactive vaccination at such neighborhoods may be the most effective way to prevent cholera cases both within that neighborhood and throughout the city.


Subject(s)
Cholera Vaccines/administration & dosage , Cholera/epidemiology , Cholera/transmission , Disease Transmission, Infectious/prevention & control , Vaccination/methods , Cholera/prevention & control , Cholera Vaccines/immunology , Guinea-Bissau/epidemiology , Humans , Models, Statistical , Urban Population
2.
PLoS One ; 6(5): e19005, 2011 May 04.
Article in English | MEDLINE | ID: mdl-21572530

ABSTRACT

BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: We conducted two studies: 1) a descriptive analysis of the cholera epidemic in Guinea-Bissau focusing on its geographical spread (country level and within the capital); and 2) a cross-sectional study to measure the prevalence of houses with at least one cholera case in the most affected neighbourhood of the capital (Bairro Bandim) to detect clustering of households with cases (cluster analysis). All cholera cases attending the cholera treatment centres in Guinea-Bissau who fulfilled a modified World Health Organization clinical case definition during the epidemic were included in the descriptive study. For the cluster analysis, a sample of houses was selected from a satellite photo (Google Earth™); 140 houses (and the four closest houses) were assessed from the 2,202 identified structures. We applied K-functions and Kernel smoothing to detect clustering. We confirmed the clustering using Kulldorff's spatial scan statistic. A total of 14,222 cases and 225 deaths were reported in the country (AR = 0.94%, CFR = 1.64%). The more affected regions were Biombo, Bijagos and Bissau (the capital). Bairro Bandim was the most affected neighborhood of the capital (AR = 4.0). We found at least one case in 22.7% of the houses (95%CI: 19.5-26.2) in this neighborhood. The cluster analysis identified two areas within Bairro Bandim at highest risk: a market and an intersection where runoff accumulates waste (p<0.001). CONCLUSIONS/SIGNIFICANCE: Our analysis allowed for the identification of the most affected regions in Guinea-Bissau during the 2008 cholera outbreak, and the most affected areas within the capital. This information was essential for making decisions on where to reinforce treatment and to guide control and prevention activities.


Subject(s)
Cholera/epidemiology , Adolescent , Adult , Child , Child, Preschool , Cholera/prevention & control , Cholera/transmission , Cluster Analysis , Female , Geography , Guinea-Bissau/epidemiology , Humans , Infant , Infant, Newborn , Male , Middle Aged , Vibrio cholerae/pathogenicity , Young Adult
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