Research Experience

  • Nov 2016 Nov 2013

    Ph.D. Student in Information Technology (Systems and Control)

    Politecnico di Milano - Dip.to di Elettronica, Informazione e Bioingegneria

    Modelling and control of waterborne infectious diseases

  • Nov 2015 Sep 2015

    Visiting Ph.D. Student

    Stanford University - Hopkins Marine Station

    Network models applied to infectious diseases

  • Oct 2013 Feb 2013

    Research Collaborator

    Politecnico di Milano - Dip.to di Elettronica, Informazione e Bioingegneria

    Eco-epidemiological models of cholera based on hydrological network and human mobility

Education

  • Ph.D.2016

    Information Technology

    Politecnico di Milano - with merit

  • M.Sc.2012

    Environmental and Land Planning Engineering

    Politecnico di Milano - 110/110 cum laude

  • B.Sc.2010

    Environmental and Land Planning Engineering

    Politecnico di Milano - 108/110

  • Diploma2007

    Liceo Scientifico

    F. Lussana, Bergamo - 98/100

Main Research Topics

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    The spatial spread of schistosomiasis in Senegal

    A spatially explicit network model for schistosomiasis transmission in Senegal is applied at different spatial scales to unveil the role of human mobility and environmental connectivity on the spread of the disease.

    The urogenital form of the schistosomiasis infection is widespread in Senegal. In the country, this disease represents a major health problem, being the third one (after malaria and lymphatic filariasis) in terms of years lived with disability. A spatially explicit model is first applied to medium-to-large spatial scales, at which human mobility is retained as the main mechanism for the spatial spread of the disease. Over finer spatial scales, instead, connectivity via hydrological transport and snail dispersal increases the risk of disease propagation. A multidimensional network model accounting for both social and environmental connectivity is thus applied to a set of connected villages in the area of the Lower Basin of the Senegal River.

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    Modelling spatio-temporal dynamics of schistosomiasis

    Schistosomiasis is a waterborne parasitic disease that affects millions of people worldwide, primarily in sub-Saharan Africa. We attempt to explain its temporal variability via a compartmental model that accounts for complexity associated with the parasite's life cycle and other mechanisms that influence the spatiotemporal dynamics of the disease.

    Schistosomiasis is a waterborne parasitic disease caused by a snail-transmitted trematode with a complex life cycle. The aim of this project is to develop conceptual framework for modelling the disease, focusing in particular on the ecology of the snail host and on the role of environmental variability. However, incorporating the biological complexity associated with the parasite's life cycle and predicting the effects of environmental changes on schistosomiasis incidence is hard, since many different factors work simultaneously. After designing this complex general framework, mathematical modelling is also used to identify the role of social interactions and physical interconnections between populations in sustaining the transmission of the disease.

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    Eco-epidemiological models of endemic cholera in Bangladesh

    In Bangladesh, cholera incidence usually exhibits two annual peaks, although the main environmental drivers peak once per year during the monsoon season. We formulate a spatially explicit model for the disease spreading taking into account hydrological connectivity, human mobility and climatic factors.

    Cholera is a disease transmitted especially through exposure to contaminated water. River networks thus represent one of the major pathways of disease spreading. This project deals with the formulation of spatial models for cholera spreading and the application to the endemic case of Bangladesh. In particular, models needs to account not only for the hydrological connectivity network, but also for the population spatial distribution and the connections that regulate human mobility among communities. Since the disease is clearly linked to the variability of climatic factors, as infections are enhanced by intense seasonal precipitation (e.g. monsoon season), the role of precipitation and temperature annual cycles needs to be integrated, incorporating annual fluctuations of water availability and considering hydro-climatological forcings as inputs of the model. So far, a compartmental SIRB (Susceptible-Infected-Recovered-Bacteria) epidemiological model has been set up and integrated with a hydrological model. The introduction of two terms of transport (hydrological transport and human mobility), together with considerations on climatic variability, allows to generate spatial patterns of cholera prevalence that qualitatively reproduce the bimodal pattern typically observed in Bangladesh.

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Heterogeneity in schistosomiasis transmission dynamics

L. Mari, M. Ciddio, R. Casagrandi, J. Perez-Saez, E. Bertuzzo, A. Rinaldo, S. H. Sokolow, G. A. De Leo, M. Gatto
Journal PaperSubmitted (Feb. 2017)

Local interactions of Vibrio cholerae with environmental drivers and phytoplankton: insight from a long-term field campaign in Matlab, Bangladesh

L. Righetto, R.U. Zaman, L. Mari, Z.H. Mahmud, E. Bertuzzo, M. Ciddio, R. Casagrandi, S. Islam, A. Rinaldo, M. Gatto
Journal PaperSubmitted (Jul. 2016)

Big-data-driven modeling unveils country-wide drivers of endemic schistosomiasis

L. Mari, M. Gatto, M. Ciddio, S. H. Sokolow, G. A. De Leo, R. Casagrandi
Journal PaperScientific Reports, in press

Abstract

Schistosomiasis is a parasitic infection that is widespread in sub-Saharan Africa, where it represents a major health problem. We study the drivers of its geographical distribution in Senegal via a spatially explicit network model accounting for epidemiological dynamics driven by local socioeconomic and environmental conditions, and human mobility. The model is parameterized by tapping demographic, socioeconomic and environmental geodatabases, and a large dataset of mobile phone traces. It reliably reproduces the observed spatial patterns of regional schistosomiasis prevalence throughout the country, provided that spatial heterogeneity and human mobility are suitably accounted for. Specifically, a fine-grained description of the socioeconomic and environmental heterogeneities involved in local disease transmission is crucial to capturing the spatial variability of disease prevalence, while the inclusion of human mobility significantly improves the explanatory power of the model. Concerning human movement, we find that moderate mobility may reduce disease prevalence, whereas either high or low mobility may result in increased prevalence of infection. The effects of control strategies based on exposure and contamination reduction via improved access to safe water or educational campaigns are also analyzed. To our knowledge, this represents the first application of an integrative schistosomiasis transmission model at a whole-country scale.

Analysis, control and forecast of schistosomiasis spatiotemporal dynamics via network modelling

M. Ciddio
Ph.D. Thesis Supervisor: M. Gatto

Abstract

Schistosomiasis is a parasitic, water-related disease that is prevalent in tropical and subtropical areas of the world, causing severe and chronic consequences especially among children. In this dissertation, different modelling frameworks are proposed, focusing on the main environmental and socioeconomic aspects considered to be relevant in schistosomiasis spread. These models are used to analyze transmission patterns in different settings, ranging from purely theoretical ones to real case studies. First, the mechanisms that drive the temporal variability of disease severity and prevalence are explored introducing nonlinearities in demographic and epidemiological dynamics. Then, the impacts of different sources of local and spatial heterogeneity are investigated, together with their implications on effectiveness of possible intervention strategies. Spatially explicit network models, properly informed by socioeconomic and environmental data, are thus used to study the spread of schistosomiasis in Senegal, where the urogenital form of the infection is widespread. The analysis is performed by integrating proxies of human mobility (inferred from a very large database of mobile phone traces) with a geospatial analysis which includes georeferenced data on demography, water supply/sanitation, and schistosomiasis prevalence. Results are presented and discussed in the perspective of using epidemiological models as tools for disease control. In this respect, the effects of intervention strategies based on human development, exposure and contamination prevention, awareness about risk factors, and biological control of snail intermediate hosts are evaluated by means of model simulation.

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

M. Ciddio, L. Mari, S. H. Sokolow, G. A. De Leo, R. Casagrandi, M. Gatto
Journal PaperAdvances in Water Resources, 2016

Abstract

Schistosomiasis is a parasitic, water-related disease that is prevalent in tropical and subtropical areas of the world, causing severe and chronic consequences especially among children. Here we study the spatial spread of this disease within a network of connected villages in the endemic region of the Lower Basin of the Senegal River, in Senegal. The analysis is performed by means of a spatially explicit metapopulation model that couples local-scale eco-epidemiological dynamics with spatial mechanisms related to human mobility (estimated from anonymized mobile phone records), snail dispersal and hydrological transport of schistosome larvae along the main water bodies of the region. Results show that the model produces epidemiological patterns consistent with field observations, and point out the key role of spatial connectivity on the spread of the disease. These findings underline the importance of considering different transport pathways in order to elaborate disease control strategies that can be effective within a network of connected populations.

A schistosomiasis transmission model to study the effects of heterogeneity on human and snail prevalence

M. Ciddio, L. Mari, R. Casagrandi, M. Gatto
Conference 1st joint conference SItE-UZI-SIB, August-September 2016

Abstract

Schistosomiasis is a parasitic, water-related disease that affects more than 200 million people worldwide, especially in rural communities of tropical and subtropical areas. It is caused by trematode worms transmitted by some species of snails inhabiting freshwater ecosystems. The contact with environmental freshwater, which can be infested with parasite larvae, has a key role in the transmission of the disease. The risk of schistosomiasis infection may be not equally distributed within a community, being higher for people spending more time in contact with environmental water. In fact, the main routine activities (e.g. agricultural, domestic, occupational, recreational activities) represent the commonest risk factors. Also, lack of hygiene and certain play habits make school-aged children particularly vulnerable to infection. In communities with access to several water sources, the infection risk may be different even within the same risk group, according to individual water-contact patterns. Therefore, socio-economic conditions and water availability are fundamental in the definition of the infection risk of different communities, in particular with respect to human habits and quality of snails habitats. In such a complex scenario, whose effects are not easy to be quantified, mathematical modelling represents a very useful analysis tool. Here, we propose a schistosomiasis transmission model that incorporates both biological complexity associated with the parasite’s life cycle and different heterogeneity sources. Specifically, through simple numerical examples, we explore the impact of heterogeneities in the human host population (arising from the presence of sub-groups with different exposure and contamination rates) and in the available water sources (in terms of contact preference and suitability as snails habitat). As for multi-group communities, results show that a heterogeneous human host population is more prone to the establishment of endemic schistosomiasis transmission than a homogeneous community, with prevalence and mean worm burden increasing with the size of the high-risk group. Instead, when a homogeneous human community has access to a set of different water sources, human and snail prevalence may be positively affected by heterogeneity in habitat quality. Some hints concerning the application of the proposed model to realistic case studies are also discussed, focusing on the need to direct control efforts towards high-risk communities.

Human population movement and schistosomiasis transmission risk: the case study of Senegal

M. Ciddio, L. Mari, R. Casagrandi, S.H. Sokolow, G. De Leo, M. Gatto
Conference 5th International Conference on Infectious Disease Dynamics (EPID), December 2015

Floquet theory for seasonally forced models of waterborne pathogen transmission

L. Mari, R. Casagrandi, M. Ciddio, M. Gatto
Conference 13th EEF & 25th SItE joint conference, September 2015

Abstract

Waterborne pathogen transmission is a complex process that is heavily linked to the seasonal variability of hydrometeorological drivers. We study simple, time-varying models for the dynamics of two paradigmatic diseases: cholera and schistosomiasis. The former is an intestinal infection caused by ingestion of water contaminated by a microparasite (the bacterium Vibrio cholerae), while the latter is a macroparasitic disease caused by water-mediated contact with the larval form of some trematode worms (genus Schistosoma) that also need an intermediate snail host to complete their life cycle. Both cholera and schistosomiasis are neglected diseases with major health, social and economic impacts. Applying Floquet theory, which allows to extend results of local stability analysis to periodically forced dynamical systems, we find conditions for pathogen invasion and establishment in systems characterized by fluctuating environmental forcing. We show that temporal variability may have multifaceted effects on the invasion threshold, as it can either favor pathogen invasion or make it less likely. Some results concerning the extension of the proposed models to a spatially explicit context are also discussed.

The impact of human mobility on schistosomiasis in Senegal: an analysis via mobile phone data

M. Ciddio, L. Mari, R. Casagrandi, S.H. Sokolow, G. De Leo, M. Gatto
Conference 9th European Congress on Tropical Medicine and International Health (ECTMIH), September 2015

Uncovering the impact of human mobility on schistosomiasis via mobile phone data

L. Mari, R. Casagrandi, M. Ciddio, S.H. Sokolow, G. De Leo, M. Gatto
Conference NetMob 2015, April 2015

Abstract

Schistosomiasis is a parasitic infection with chronic debilitating symptoms that is widespread in sub-Saharan Africa. In this work we study country-scale disease transmission dynamics in Senegal, where schistosomiasis represents a major health problem. The analysis is performed by means of a spatially explicit model accounting for both local epidemiological dynamics and human mobility. Human hosts can in fact be exposed to contaminated water (and contribute to water contamination if infected) while traveling outside their home communities to carry out their activities. Mobility patterns are estimated from low-resolution movement routes extracted from anonymized mobile phone records made available by Orange and Sonatel in the context of the D4D-Senegal data challenge. The results of our analysis show that a relatively simple model can reproduce regional patterns of schistosomiasis prevalence quite reliably. Mobility is found to play a nontrivial role in disease spread, as it can either increase or decrease transmission risk - with the latter effect being predominant at large spatial scales. We also study the effectiveness of some intervention strategies aimed at reducing the burden of the disease and discuss how the model can be transformed into a decision-support tool to help eradicate schistosomiasis from Senegal.

The temporal patterns of disease severity and prevalence in schistosomiasis

M. Ciddio, L. Mari, M. Gatto, A. Rinaldo, R. Casagrandi
Journal PaperChaos: An Interdisciplinary Journal of Nonlinear Science, 2015

Abstract

Schistosomiasis is one of the most widespread public health problems in the world. In this work, we introduce an eco-epidemiological model for its transmission and dynamics with the purpose of explaining both intra- and inter-annual fluctuations of disease severity and prevalence. The model takes the form of a system of nonlinear differential equations that incorporate biological complexity associated with schistosome's life cycle, including a prepatent period in snails (i.e., the time between initial infection and onset of infectiousness). Nonlinear analysis is used to explore the parametric conditions that produce different temporal patterns (stationary, endemic, periodic, and chaotic). For the time-invariant model, we identify a transcritical and a Hopf bifurcation in the space of the human and snail infection parameters. The first corresponds to the occurrence of an endemic equilibrium, while the latter marks the transition to interannual periodic oscillations. We then investigate a more realistic time-varying model in which fertility of the intermediate host population is assumed to seasonally vary. We show that seasonality can give rise to a cascade of period-doubling bifurcations leading to chaos for larger, though realistic, values of the amplitude of the seasonal variation of fertility.

Impact of environmental conditions on snails dynamics and schistosomiasis transmission

M. Ciddio, L. Mari, M. Gatto, A. Rinaldo, R. Casagrandi
Conference Impact of Environmental Changes on Infectious Diseases (IECID), March 2015

Abstract

Schistosomiasis is a waterborne parasitic disease that affects approximately 200 million people worldwide, primarily in sub-Saharan Africa. It is caused by a snail-transmitted trematode (genus Schistosoma) with a complex life cycle that involves two larval stages (miracidia and cercariae) and two reproduction phases within different hosts: freshwater snails (intermediate host) and humans (definitive host). The disease is clearly linked to the variability of environmental factors, which strongly influence the ecology of the snail host. However, predicting the effects of environmental changes on schistosomiasis incidence is hard, since many different factors work simultaneously. Our aim is to explain the interannual oscillations typical of many endemic regions introducing some innovations in modelling the dynamics of intermediate snail hosts. We propose a new model to study schistosomiasis transmission dynamics. The model is a system of nonlinear differential equations that incorporate both biological complexity associated with parasite’s life cycle, including prepatent period in snail and intensity of human infection, and effects of climatic variability on the ecology of the snail host. Stability and bifurcation analyses are used to investigate a time-varying model in which the fertility of the snail population is assumed to vary periodically, according to climatic variability. The analysis of the whole range of model behaviors demonstrates that snail ecology can play an important role in generating variations of disease transmission patterns over time. We discuss implications for long-term dynamics under different scenarios, including periodic and chaotic dynamics. Results imply that the basic mechanisms included in our model are able to reproduce realistic patterns of disease dynamics. This makes our model a useful tool to evaluate the impact of environmental changes on the transmission intensity of schistosomiasis, as well as a promising building brick towards a realistic framework for schistosomiasis dynamics.

A model for schistosomiasis transmission accounting for infection age in snails: sensitivity and bifurcation analyses

M. Ciddio, L. Mari, R. Casagrandi, M. Gatto
Conference XXIV Congresso della SItE, September 2014

The role of climatic variability on cholera spreading in Bangladesh

M. Ciddio, L. Righetto, L. Mari
Conference First Conference of the Italian Society for Climate Sciences (SISC), September 2013

Abstract

Cholera is a disease transmitted through exposure to water contaminated by the bacterium Vibrio cholerae. The disease is clearly linked to the variability of climatic factors, as infections are enhanced by intense seasonal precipitation (e.g. monsoon season). Here we propose a spatially explicit model for cholera and apply it to Bangladesh, where the disease is endemic, integrating the role of precipitation and temperature annual cycles. River networks represent one of the major pathways of disease spreading. The data structure designed for the application of the model is thus based on the hydrological connectivity network, as well as on the spatial distribution of the population and on the connections that regulate human mobility among communities. In this region, cholera incidence exhibits two annual peaks, although the main environmental drivers peak once per year during the monsoon season (from June to September). The proposed model attempts to explain these particular dynamics taking into account the annual fluctuations of water availability and considering hydro-climatological forcings as inputs for the model. For this purpose, a compartmental SIRB (Susceptible-Infected-Recovered-Bacteria) epidemiological model is integrated with a hydrological model. Results show that the introduction of two terms of transport (hydrological transport and human mobility) allows to generate spatial patterns of cholera prevalence that reproduce the bimodal pattern typically observed in this region.

A spatially explicit model of cholera spreading in Bangladesh: the role of climate and mobility

L. Righetto, M. Ciddio, E. Bertuzzo, L. Mari, R. Casagrandi, A. Rinaldo, M. Gatto
Conference XXIII Congresso della SItE, September 2013

A spatially explicit model of endemic cholera in Bangladesh: the role of hydroclimatological forcings

M. Ciddio, L. Mari, L. Righetto
Conference CIMAB and GASVA-SIMAI workshop, April 2013

Development of a spatially explicit model of cholera transmission and application to the endemic case of Bangladesh

M. Ciddio
M.Sc. Thesis Supervisor: M. Gatto; Co-supervisors: L. Righetto, L. Mari

Abstract

In this work, we propose a spatially explicit model of cholera transmission, which we develop in order to describe the endemic case of Bangladesh. We detail in this work the procedure of extraction of the network through which the territory can be modeled. Cholera is a disease transmitted especially through exposure to contaminated water, so the river network can be considered one of the major ways of spreading of the epidemic, besides human mobility. The data structure designed for the application of the model is therefore based on the network of hydrological connectivity, as well as on the spatial distribution of population and on the connections that regulate the movement from one community to another. In this region, the incidence of cholera exhibits two annual peaks, although the main environmental drivers (precipitation and temperature) peak once per year during the monsoon season (from June to September). The proposed model attempts to explain these particular dynamics taking into account the annual fluctuations of water availability and considering hydro-climatological forcings as inputs of the model. For this purpose, the compartmental epidemiological model Susceptible-Infected-Recovered-Bacteria is integrated with a hydrological model for the water balance in the local water reservoir. Results show that the dynamics of the disease are controlled by the annual cycle of hydroclimatological forcings, but this is not sufficient to explain the qualitative differences observed in different regions of Bangladesh, unless explicit consideration of the spatial dynamics of the phenomenon. The introduction of two terms of transport (hydrological transport and human mobility) allows to generate spatial cholera prevalence patterns that confirm the bimodal pattern typically observed in this region.

Location of biomass plants. An approach based on GIS

M. Ciddio
B.Sc. Thesis Supervisor: G. Guariso; Co-supervisor: G. Fiorese


  • Ecosystems conservation and management (Exercises)

    MS Environmental Students - A.A. 2016-2017

    Lecturer: Marino Gatto - 10 CFU

    English

    Ecologia
    (Esercitazioni)

    Allievi Ambientali - A.A. 2015-2016

    Docente: Renato Casagrandi - 8 CFU

    Italian

    Ecosystems conservation and management (Exercises)

    MS Environmental Students - A.A. 2015-2016

    Lecturer: Marino Gatto - 10 CFU

    English

    Ecologia
    (Esercitazioni)

    Allievi Ambientali - A.A. 2014-2015

    Docente: Renato Casagrandi - 7+1 CFU

    Italian

DEIB Office #238
  +39 02-2399-4032   / Voip call

Find me at 2nd floor of
Dipartimento di Elettronica, Informazione e Bioingegneria
Via Ponzio 34/5 (Leonardo Campus) - 20133 Milano
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Write me an email or use the alongside form to make an appointment.

  •    manuela dot ciddio at polimi.it         manuelka1988

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