High-resolution spatial analysis of cholera patients reported in Artibonite department, Haiti in 2010–2011

Allan, Maya; Grandesso, Francesco; Pierre, Ronald L. St.; Magloire, Roc; Coldiron, Matthew E.; Martínez-Pino, Isabel; Goffeau, Thierry; Gitenet, Romain; François, Gwenola; Olson, David M.; Porten, Klaudia; Luquero, Francisco J.

doi:10.1016/j.epidem.2015.08.001

Cited by 10 publications

(14 citation statements)

References 26 publications

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“…The cholera epidemic quickly propagated from the Centre and Artibonite departments, with rapid transmission country wide over several weeks in October-November 2010 (Gaudart et al, 2013;Blackburn et al, 2014;Allan et al, 2016). Not only was the Artibonite department among the first hit, it also continues to be one of the most affected.…”

Section: Introductionmentioning

confidence: 99%

Cholera spatial-temporal patterns in Gonaives, Haiti: From contributing factors to targeted recommendations

Griffiths

Trazillio

Lebeau³

et al. 2017

Advances in Water Resources

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights  Patterns of cholera socio-environmental risk factors were identified in Gonaives City, Haiti.  Coastal flood plains are high-risk associated with easy access to a contaminated brackish water table.  Hillside areas are high-risk associated with poverty, poor water availability and open defecation.  Development of water supply networks and safe sanitation practices must be neighbourhood-specific.

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Section: Introductionmentioning

confidence: 99%

Cholera spatial-temporal patterns in Gonaives, Haiti: From contributing factors to targeted recommendations

Griffiths

Trazillio

Lebeau³

et al. 2017

Advances in Water Resources

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“…For example, while ensuring geographic proximity to cases is straightforward in the community, it may be more challenging to obtain accurate residence locations for patients recruited from a health center. Given that temporal spatial characteristics can determine vaccine uptake and cholera,(28,29) failure to adjust for these variables may bias results. In the present test-negative analyses, we adjusted for age but were unable to precisely control for area of residence or calendar time (because there were months in which a non-cholera diarrhea case was enrolled but a cholera case was not enrolled).…”

Section: Discussionmentioning

confidence: 99%

Comparison of two control groups for estimation of oral cholera vaccine effectiveness using a case-control study design

Franke

Jerome²,

Matias

et al. 2017

Vaccine

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Background Case-control studies to quantify oral cholera vaccine effectiveness (VE) often rely on neighbors without diarrhea as community controls. Test-negative controls can be easily recruited and may minimize bias due to differential health-seeking behavior and recall. We compared VE estimates derived from community and test-negative controls and conducted bias-indicator analyses to assess potential bias with community controls. Methods From October 2012 through November 2016, patients with acute watery diarrhea were recruited from cholera treatment centers in rural Haiti. Cholera cases had a positive stool culture. Non-cholera diarrhea cases (test-negative controls and non-cholera diarrhea cases for bias-indicator analyses) had a negative culture and rapid test. Up to four community controls were matched to diarrhea cases by age group, time, and neighborhood. Results Primary analyses included 181 cholera cases, 157 non-cholera diarrhea cases, 716 VE community controls and 625 bias-indicator community controls. VE for self-reported vaccination with two doses was consistent across the two control groups, with statistically significant VE estimates ranging from 72 to 74%. Sensitivity analyses revealed similar, though somewhat attenuated estimates for self-reported two dose VE. Bias-indicator estimates were consistently less than one, with VE estimates ranging from 19 to 43%, some of which were statistically significant. Conclusions OCV estimates from case-control analyses using community and test-negative controls were similar. While bias-indicator analyses suggested possible over-estimation of VE estimates using community controls, test-negative analyses suggested this bias, if present, was minimal. Test-negative controls can be a valid low-cost and time-efficient alternative to community controls for OCV effectiveness estimation and may be especially relevant in emergency situations.

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“…The mountainous eastern areas ... are prone to both, as sanitation conditions are extremely poor and the topography increases the risk of transmission through runoff." [3] Departments in Haiti vary in population and poverty levels. [1, Table 2] "Considering its high population density and poor sanitation, there is a high risk for continued cholera transmission in [the vast Artibonite estuary]. "…”

Section: Data Collection and Choices Of Model And Parametersmentioning

confidence: 99%

“…[1, Table 2] "Considering its high population density and poor sanitation, there is a high risk for continued cholera transmission in [the vast Artibonite estuary]. " [3] (Multiple maps are also included in [3].) Notice how intimately linked the modeling process is to inequities.…”

Section: Data Collection and Choices Of Model And Parametersmentioning

confidence: 99%

“…An epidemiological model and its parameters can be based somewhat on theoretical information about a disease and its transmission, but the ability to validate our choices for the model and the parameters requires reliable data. Evidence of issues with data collection in the case of Haiti is offered in [3].…”

Section: Data Collection and Choices Of Model And Parametersmentioning

confidence: 99%

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A Model of the Transmission of Cholera in a Population with Contaminated Water

Shelton¹,

Groves²,

Adrian³

2019

CODEE

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Cholera is an infectious disease that is a major concern in countries with inadequate access to clean water and proper sanitation. According to the World Health Organization (WHO), "cholera is a disease of inequityan ancient illness that today sickens and kills only the poorest and most vulnerable people.. . The map of cholera is essentially the same as a map of poverty." [27] We implement a published model [9] of a SIR model that includes a bacterial reservoir. Bacterial concentration in the water, λ, or the "force of infection," is modeled by the Monod Equation in microbiology. We investigate the sensitivity of the models to some parameters. We use parameter values for cholera in Haiti that are consistent with the ranges in meta-analysis [9] and other sources. We show the results of our numerical approximation of solutions. Our goal is to use this system of nonlinear ordinary differential equations to raise awareness among the mathematics community of the dynamics of cholera. We discuss the enhancement of undergraduate experiences by motivating learning with a real-world context in social justice implications of global health. 1 Overview Cholera is a well-established waterborne disease that spreads through populations of people who are already overly burdened. Controlling cholera will require investment of monetary and human resources, issues beyond the scope of this paper. Here, we seek to understand and illustrate more about the disease through a mathematical model. We begin with an overview of the disease and of the outbreak in Haiti. We review the basic

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High-resolution spatial analysis of cholera patients reported in Artibonite department, Haiti in 2010–2011

Cited by 10 publications

References 26 publications

Cholera spatial-temporal patterns in Gonaives, Haiti: From contributing factors to targeted recommendations

Cholera spatial-temporal patterns in Gonaives, Haiti: From contributing factors to targeted recommendations

Comparison of two control groups for estimation of oral cholera vaccine effectiveness using a case-control study design

A Model of the Transmission of Cholera in a Population with Contaminated Water

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