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Data server object:  angola_cholera




  
    Angola weekly cholera incidence at the province level collected from 2016-02-13 to 2016-05-29 (Cholera_Disease_Dyn project)
    
  
  
    
    

Angola weekly cholera incidence at the province level collected from 2016-02-13 to 2016-05-29 (Cholera_Disease_Dyn project)

Website: https://www.bco-dmo.org/dataset/719960
Data Type: Other Field Results
Version:
Version Date: 2017-11-28

Project
» Modeling the Effects of Heterogeneity in Water Quality on Cholera Disease Dynamics (Cholera_Disease_Dyn)
ContributorsAffiliationRole
Tien, JosephOhio State UniversityPrincipal Investigator
Eisenberg, Marisa CUniversity of MichiganCo-Principal Investigator
Fisman, David NUniversity of Toronto (U of T)Co-Principal Investigator
York, AmberWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager


Coverage

Spatial Extent: N:-4.3726 E:24.0821 S:-18.0421 W:11.6792
Temporal Extent: 2016-02-13 - 2016-05-29

Dataset Description

This dataset includes weekly cholera incidence data collected by the Angola Ministry of Health and compiled by the World Health Organization Cholera Task Force collected at the province level from Feb. 13th to May 29th, 2016. 

These data were published in:
Eisenberg M, Robertson SL, Tien JH (2013).  Identifiability and estimation of multiple transmission pathways in cholera and waterborne disease.  J. Theoretical Biology 324: 84-102. doi: 10.1016/j.jtbi.2012.12.021 ​​

Other relevant publication:
Lee EC et al (2017), Model distinguishability and inference robustness in mechanisms of cholera transmission and loss of immunity.  J. Theoretical Biology 420: 68-81. doi: 10.1016/j.jtbi.2017.01.032

Acquisition Description

Cholera incidence reported by the Angola Ministry of Health.


Processing Description

BCO-DMO Data Manager Processing Notes:
* added a conventional header with dataset name, PI name, version date
* modified parameter names to conform with BCO-DMO naming conventions (spaces and periods changed to underscores)


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Related Publications

Eisenberg, M. C., Robertson, S. L., & Tien, J. H. (2013). Identifiability and estimation of multiple transmission pathways in cholera and waterborne disease. Journal of Theoretical Biology, 324, 84–102. doi:10.1016/j.jtbi.2012.12.021 [details]
Lee, E. C., Kelly, M. R., Ochocki, B. M., Akinwumi, S. M., Hamre, K. E. S., Tien, J. H., & Eisenberg, M. C. (2017). Model distinguishability and inference robustness in mechanisms of cholera transmission and loss of immunity. Journal of Theoretical Biology, 420, 68–81. doi:10.1016/j.jtbi.2017.01.032 [details]

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Parameters

ParameterDescriptionUnits
year_fromStarting year of weekly cholera incidence count in format yyyy unitless
month_fromStarting month of weekly cholera incidence count in format mm unitless
day_fromStarting day of weekly cholera incidence count in format dd unitless
year_toEnding year of weekly cholera incidence count in format yyyy unitless
month_toEnding month of weekly cholera incidence count in format mm unitless
day_toEnding day of weekly cholera incidence count in format dd unitless
year_fracFractional year for stop date of the weekly incidence data in format yyyy + fraction of year (example: week ending on Jan 7, 2006 (the first week of the year)  1/52 = .019.  So value would be 2006.019. unitless
BengoWeekly cholera incidence count in Bengo province count per incidence
BenguelaWeekly cholera incidence count in Benguela province count per incidence
BieWeekly cholera incidence count in Bie province count per incidence
K_NorteWeekly cholera incidence count in Kuanza Norte province count per incidence
K_SulWeekly cholera incidence count in Kuanza Sul province count per incidence
LuandaWeekly cholera incidence count in Luanda province count per incidence
HuamboWeekly cholera incidence count in Huambo province count per incidence
MalangeWeekly cholera incidence count in Malange province count per incidence
NamibeWeekly cholera incidence count in Namibe province count per incidence
ZaireWeekly cholera incidence count in Zaire province count per incidence
HuilaWeekly cholera incidence count in Huila province count per incidence
UigeWeekly cholera incidence count in Uige province count per incidence
CabindaWeekly cholera incidence count in Cabinda province count per incidence
TOTALTotal weekly cholera incidence for all 13 provinces count per incidence

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Project Information

Modeling the Effects of Heterogeneity in Water Quality on Cholera Disease Dynamics (Cholera_Disease_Dyn)

Coverage: Haiti, Angola and London


Funding was requested to analyze and model cholera epidemics. In order to accomplish this task, the team will analyze spatio-temporal data from cholera outbreaks in Haiti (2010), Angola (2006) and London (1832); develop mathematical theory for coupled patch models of waterborne disease; and develop models to predict disease spread under different scenarios. The study will explore the contribution of humans (direct) and of environmental (delayed) pathways to disease transmission and investigate how heterogeneity in water quality, which is ubiquitous in developing countries, affects cholera disease dynamics. This project will advance understanding of the factors governing the spatial spread of cholera, examine how the arrangement and connectivity between cholera risk hot spots influence disease spread and develop a modeling framework for rapid response to a cholera crisis. The proposed study has clear practical and theoretical significance for understanding and predicting not only cholera transmission, but other waterborne diseases as well, reaching beyond the specific study system. The team will develop mathematical theory for coupled patch models of waterborne diseases and advance understanding of the effects of movement of individuals and of water to cholera transmission. The team will also explore inclusion of data from early stages of an outbreak on parameter estimates and whether information on water quality and availability and on types of sanitation facilities available can be used to improve knowledge of model parameters before the disease has reached a given area. This study will result in the training of undergraduates and graduate students, and include outreach to the Columbus Science Pub (public), Cornell's Summer Math Institute (undergraduates) and the UCLA Math Circle (grades K-12). This project will strengthen international scientific collaboration through interaction with scientists and students from the University of Toronto. The research from this study will provide society benefits through improved understanding of the factors influencing the ability of cholera to invade, spread and persist in a region. The proposed study will provide a tool to predict disease spread under different scenarios for rapid response to a cholera crisis and evaluate the efficacy of different intervention strategies on containing cholera spatial spread. The team will interact and communicate their research findings to the Centers for Disease Control and the National Biosurveillance Integration Center within the Department of Homeland Security. They will collaborate with the United Nations University Institute for Water, Environment and Health to compile a database of time series data from cholera outbreaks worldwide, in association with data on water quality, water availability, and sanitation facilities from several outbreak locales.


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Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)

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This document is created by info v 4.1f 5 Oct 2018 from the content of the BCO-DMO metadata database.    2020-03-28  16:45:44