The spatial spread of schistosomiasis: A multidimensional network model applied to Saint-Louis region, Senegal

Ciddio, Manuela; Mari, Lorenzo; Sokolow, Susanne H.; Leo, Giulio A. De; Casagrandi, Renato; Gatto, Marino

doi:10.1016/j.advwatres.2016.10.012

Cited by 51 publications

(30 citation statements)

References 41 publications

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“…This was attributed to the upstream discharge of domestic and industrial effluents into the river. Similar results were found in Ghana, Senegal, Indonesia, and Iran [27,63,80,83].…”

Section: Discussionsupporting

confidence: 82%

“…Relatedly, it was recorded that higher concentrations of E. coli and fecal matter in drinking-water were associated with diarrheal diseases (cholera and dysentery) [45,58]. In the same fashion, schistosomiasis was associated with polluted surface water systems in Kenya and Senegal, due to the presence of fecal matter in the water, which promotes the survival of the intermediate snail host [35,76,[83][84][85][86]. Table 3.…”

Section: Water Quality Parameters and The Potential Water-related Infmentioning

confidence: 95%

“…Temperature, turbidity, pH Dengue [75] Temperature Malaria [59,75,87] E. coli, fecal coliform Cholera [45,61,62,81,88] E. coli, fecal coliform, turbidity, pH Dysentery [61,62,89] E. coli, fecal coliform Typhoid fever [61,62] E. coli, fecal coliform, BOD, temperature, DO Cryptosporidiosis [70,81] Fecal coliform Schistosomiasis [76,77,83,85,[90][91][92] E. coli, fecal coliform, temperature, turbidity Buruli ulcer [85] E. coli, fecal coliform, temperature, DO, BOD, TSS, turbidity Hookworm [92] pH = Potential of Hydrogen; DO = Dissolved Oxygen; BOD = Biochemical Oxygen Demand; TSS = Total Dissolved Solid.…”

Section: Water Quality Parameters Diseases Sourcesmentioning

confidence: 99%

“…In addition, the reviewed studies revealed that most direct interactions between humans and water, which resulted in water-based disease outbreaks, were through human skin contacts with polluted water [35,43,83]. Relatedly, the probability of being infected depends on the frequency and patterns of human-water contacts.…”

Section: Influences Of Water Quality On Wridmentioning

confidence: 99%

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Influences of Land-Use Dynamics and Surface Water Systems Interactions on Water-Related Infectious Diseases—A Systematic Review

Ntajal

Falkenberg

Kistemann

et al. 2020

Water

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Human interactions with surface water systems, through land-use dynamics, can influence the transmission of infectious water-related diseases. As a result, the aim of our study was to explore and examine the state of scientific evidence on the influences of these interactions on water-related infectious disease outcomes from a global perspective. A systematic review was conducted, using 54 peer-reviewed research articles published between 1995 and August 2019. The study revealed that there has been an increase in the number of publications since 2009; however, few of these publications (n = 6) made explicit linkages to the topic. It was found that urban and agricultural land-use changes had relatively high adverse impacts on water quality, due to high concentrations of fecal matter, heavy metals, and nutrients in surface water systems. Water systems were found as the common “vehicle” for infectious disease transmission, which in turn had linkages to sanitation and hygiene conditions. The study found explicit linkages between human–surface water interaction patterns and the transmission of water-based disease. However, weak and complex linkages were found between land-use change and the transmission of water-borne disease, due to multiple pathways and the dynamics of the other determinants of the disease. Therefore, further research studies, using interdisciplinary and transdisciplinary approaches to investigate and enhance a deeper understanding of these complexities and linkages among land use, surface water quality, and water-related infectious diseases, is crucial in developing integrated measures for sustainable water quality monitoring and diseases prevention.

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“…This was attributed to the upstream discharge of domestic and industrial effluents into the river. Similar results were found in Ghana, Senegal, Indonesia, and Iran [27,63,80,83].…”

Section: Discussionsupporting

confidence: 82%

Section: Water Quality Parameters and The Potential Water-related Infmentioning

confidence: 95%

Section: Water Quality Parameters Diseases Sourcesmentioning

confidence: 99%

Section: Influences Of Water Quality On Wridmentioning

confidence: 99%

See 2 more Smart Citations

Influences of Land-Use Dynamics and Surface Water Systems Interactions on Water-Related Infectious Diseases—A Systematic Review

Ntajal

Falkenberg

Kistemann

et al. 2020

Water

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show abstract

“…Our study presents a number of simplifications and limitations that, however, do not impair our main conclusions. Specifically, 1) although the human effort involved in the collection of epidemiological data has been major, the granularity of available data is limited in time, spatial resolution, and individual information [for instance, the only published assessment of mobility changes in Italy following lockdown (37) refers to publicly unavailable data; properly anonymized call detail records have been useful in other epidemic and endemic contexts (34,53,54)]; 2) should anonymized individual information from hospitals and laboratories be available, a proper probability distribution of relevant rates and periods (e.g., latency, incubation, infection) could be employed by any modeling approaches (see ref. 55 for estimates based on high data granularity regarding the Lombardy region); and 3) the effect of age structure (56) in terms of differential mobility, social contact patterns, vulnerability, and case fatality ratio [often associated with hyperinflammation in elderly people (57)] would need to be included, therefore relying on higher granularity of data (39).…”

Section: Discussionmentioning

confidence: 99%

Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures

Gatto

Bertuzzo

Mari

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

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1,060

1,121

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The spread of coronavirus disease 2019 (COVID-19) in Italy prompted drastic measures for transmission containment. We examine the effects of these interventions, based on modeling of the unfolding epidemic. We test modeling options of the spatially explicit type, suggested by the wave of infections spreading from the initial foci to the rest of Italy. We estimate parameters of a metacommunity Susceptible-Exposed-Infected-Recovered (SEIR)like transmission model that includes a network of 107 provinces connected by mobility at high resolution, and the critical contribution of presymptomatic and asymptomatic transmission. We estimate a generalized reproduction number (R 0 = 3.60 [3.49 to 3.84]), the spectral radius of a suitable next-generation matrix that measures the potential spread in the absence of containment interventions. The model includes the implementation of progressive restrictions after the first case confirmed in Italy (February 21, 2020) and runs until March 25, 2020. We account for uncertainty in epidemiological reporting, and time dependence of human mobility matrices and awareness-dependent exposure probabilities. We draw scenarios of different containment measures and their impact. Results suggest that the sequence of restrictions posed to mobility and human-to-human interactions have reduced transmission by 45% (42 to 49%). Averted hospitalizations are measured by running scenarios obtained by selectively relaxing the imposed restrictions and total about 200,000 individuals (as of March 25, 2020). Although a number of assumptions need to be reexamined, like age structure in social mixing patterns and in the distribution of mobility, hospitalization, and fatality, we conclude that verifiable evidence exists to support the planning of emergency measures.

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Digital Infrastructure Enabling Platforms for Health Information and Education in the Global South

Radovanović¹,

Houngbonon

Quentrec

et al. 2020

Digital Inequalities in the Global South

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The spatial spread of schistosomiasis: A multidimensional network model applied to Saint-Louis region, Senegal

Cited by 51 publications

References 41 publications

Influences of Land-Use Dynamics and Surface Water Systems Interactions on Water-Related Infectious Diseases—A Systematic Review

Influences of Land-Use Dynamics and Surface Water Systems Interactions on Water-Related Infectious Diseases—A Systematic Review

Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures

Digital Infrastructure Enabling Platforms for Health Information and Education in the Global South

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