A Theoretical Analysis of the Geography of Schistosomiasis in Burkina Faso Highlights the Roles of Human Mobility and Water Resources Development in Disease Transmission

Enrico Bertuzzo, Natalie Claire Ceperley, Marino Gatto, Theophile Mande, Lorenzo Mari, Francisco Javier Perez Saez, Andrea Rinaldo, Yeli Mariam Sou
Public Library of Science, 2015
Article

Résumé

We study the geography of schistosomiasis across Burkina Faso by means of a spatially explicit model of water-based disease dynamics. The model quantitatively addresses the geographic stratification of disease burden in a novel framework by explicitly accounting for drivers and controls of the disease, including spatial information on the distributions of population and infrastructure, jointly with a general description of human mobility and climatic/ecological drivers. Spatial patterns of disease are analysed by the extraction and the mapping of suitable eigenvectors of the Jacobian matrix subsuming the stability of the disease-free equilibrium. The relevance of the work lies in the novel mapping of disease burden, a byproduct of the parametrization induced by regional upscaling, by model-guided field validations and in the predictive scenarios allowed by exploiting the range of possible parameters and processes. Human mobility is found to be a primary control at regional scales both for pathogen invasion success and the overall distribution of disease burden. The effects of water resources development highlighted by systematic reviews are accounted for by the average distances of human settlements from water bodies that are habitats for the parasite’s intermediate host. Our results confirm the empirical findings about the role of water resources development on disease spread into regions previously nearly disease-free also by inspection of empirical prevalence patterns. We conclude that while the model still needs refinements based on field and epidemiological evidence, the proposed framework provides a powerful tool for large-scale public health planning and schistosomiasis management.

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https://infoscience.epfl.ch/record/213715?ln=fr

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Enrico Bertuzzo, Natalie Claire Ceperley, Marino Gatto, Theophile Mande, Lorenzo Mari, Francisco Javier Perez Saez, Andrea Rinaldo, Yeli Mariam Sou
Public Library of Science, 2015
Article

Résumé

Official source

https://infoscience.epfl.ch/record/213715?ln=fr

À propos de ce résultat

Concepts associés (15)

Concepts associés

Chargement

Publications associées (3)

Publications associées

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Generalized reproduction numbers and the prediction of patterns in waterborne disease

Enrico Bertuzzo, Marino Gatto, Lorenzo Mari, Lorenzo Righetto, Andrea Rinaldo

Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers R-0 be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix G(0), explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number Lambda(0) (the dominant eigenvalue of G(0)) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of G(0). Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of G(0) provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections.

Natl Acad Sciences2012

Chargement

Successful control of schistosomiasis, a water-borne parasitic disease, is challenged by the intricacy of the wormâs lifecycle, which depends on aquatic snail intermediate hosts, and involves environmental, ecologic, and socio-economic factors. Current strategies rely on deworming through mass drug administration which however do not protect against reinfection and the persistence of hotspots. It is recognized that multifaceted approaches will be necessary to reach elimination, whose development will require a renewed focus on the diseaseâs social-ecological drivers. Taking cue from the hydrological underpinning of these drivers, this Thesis aims at developing an ecohydrological approach to schistosomiasis with a view to identifying and exploiting the points in which its cycle can be broken. Schistosomiasis is a poverty-reinforcing disease affecting more than 150 million people in sub-Saharan Africa, being the parasitic disease causing the largest health burden after malaria. However, the impairing morbidity it causes has been undervalued in the past, qualifying it as a neglected tropical disease. Moreover, water resources development often exacerbate transmission, posing scientific and ethical challenges in addressing the ensuing trade-off between economic development and public health. The relevance of this Thesisâ work lies in furthering tools to offset this trade-off by unlocking the predictive appraisal of the social-ecological drivers of transmission. An integration of fieldwork applied in Burkina Faso (West Africa) and theoretical methods are employed to address this aim. This Thesis establishes the use of spatially explicit mathematical models of schistosomiasis at the national-scale, allowing to study the effect of human mobility and spatial heterogeneity of transmission parameters. Weekly ecological samplings of snail abundance and continuous environmental monitoring were preformed at three sites along the countryâs climatic gradient, leveraged through ecological modelling. A novel methodology for the large-scale prediction of river network ephemerality allowed for refined snail species distribution models, and the analysis of the diseaseâs geography in link with socio-economic covariates. Finally, surveys and participatory workshops shed light on local-scale water contact patterns. The obtained results substantiate the stance that hydrology is a first-order control of disease transmission. Stability analysis of the spatially explicit model generated additional insight into the impact of the expansion of suitable snail habitat due to water resources development, highlighting the interplay between local and country-wide effects driven by human mobility. Models of snail ecology revealed key hydrological drivers, and disputed density feedbacks. Uncovered phase shifts between permanent and ephemeral habitats were adequately reproduced at the national scale through model regionalization. Characterization and predictions of hydrological ephemerality improved the estimation of the snailsâ ecological range, mirroring the diseaseâs geography. Finally a national-scale association between ephemerality and disease risk was observed, possibly due to human-water contacts aggregation, as supported by preliminary results at village-level. The future incorporation of these ecohydrological findings into spatially explicit models of schistosomiasis is considered promising for optimizing control strategies and attaining disease elimination.

EPFL2018

Chargement

Classification and prediction of river network ephemerality and its relevance for waterborne disease epidemiology

Natalie Claire Ceperley, Theophile Mande, Francisco Javier Perez Saez, Andrea Rinaldo

The transmission of waterborne diseases hinges on the interactions between hydrology and ecology of hosts, vectors and parasites, with the long-term absence of water constituting a strict lower bound. However, the link between spatio-temporal patterns of hydrological ephemerality and waterborne disease transmission is poorly understood and difficult to account for. The use of limited biophysical and hydroclimate information from otherwise data scarce regions is therefore needed to characterize, classify, and predict river network ephemerality in a spatially explicit framework. Here, we develop a novel large-scale ephemerality classification and prediction methodology based on monthly discharge data, water and energy availability, and remote-sensing measures of vegetation, that is relevant to epidemiology, and maintains a mechanistic link to catchment hydrologic processes. Specifically, with reference to the context of Burkina Faso in sub-Saharan Africa, we extract a relevant set of catchment covariates that include the aridity index, annual runoff estimation using the Budyko framework, and hysteretical relations between precipitation and vegetation. Five ephemerality classes, from permanent to strongly ephemeral, are defined from the duration of 0-flow periods that also accounts for the sensitivity of river discharge to the long-lasting drought of the 70's-80's in West Africa. Using such classes, a gradient-boosted tree-based prediction yielded three distinct geographic regions of ephemerality. Importantly, we observe a strong epidemiological association between our predictions of hydrologic ephemerality and the known spatial patterns of schistosomiasis, an endemic parasitic waterborne disease in which infection occurs with human-water contact, and requires aquatic snails as an intermediate host. The general nature of our approach and its relevance for predicting the hydrologic controls on schistosomiasis occurrence provides a pathway for the explicit inclusion of hydrologic drivers within epidemiological models of waterborne disease transmission.

Elsevier Sci Ltd2017

Chargement

Classification and prediction of river network ephemerality and its relevance for waterborne disease epidemiology

Natalie Claire Ceperley, Theophile Mande, Francisco Javier Perez Saez, Andrea Rinaldo

Elsevier Sci Ltd2017

EPFL2018