Population Density, Climate Variables and Poverty Synergistically Structure Spatial Risk in Urban Malaria in India.

BACKGROUND: The world is rapidly becoming urban with the global population living in cities projected to double by 2050. This increase in urbanization poses new challenges for the spread and control of communicable diseases such as malaria. In particular, urban environments create highly heterogeneous socio-economic and environmental conditions that can affect the transmission of vector-borne diseases dependent on human water storage and waste water management. Interestingly India, as opposed to Africa, harbors a mosquito vector, Anopheles stephensi, which thrives in the man-made environments of cities and acts as the vector for both Plasmodium vivax and Plasmodium falciparum, making the malaria problem a truly urban phenomenon. Here we address the role and determinants of within-city spatial heterogeneity in the incidence patterns of vivax malaria, and then draw comparisons with results for falciparum malaria. METHODOLOGY/PRINCIPAL FINDINGS: Statistical analyses and a phenomenological transmission model are applied to an extensive spatio-temporal dataset on cases of Plasmodium vivax in the city of Ahmedabad (Gujarat, India) that spans 12 years monthly at the level of wards. A spatial pattern in malaria incidence is described that is largely stationary in time for this parasite. Malaria risk is then shown to be associated with socioeconomic indicators and environmental parameters, temperature and humidity. In a more dynamical perspective, an Inhomogeneous Markov Chain Model is used to predict vivax malaria risk. Models that account for climate factors, socioeconomic level and population size show the highest predictive skill. A comparison to the transmission dynamics of falciparum malaria reinforces the conclusion that the spatio-temporal patterns of risk are strongly driven by extrinsic factors. CONCLUSION/SIGNIFICANCE: Climate forcing and socio-economic heterogeneity act synergistically at local scales on the population dynamics of urban malaria in this city. The stationarity of malaria risk patterns provides a basis for more targeted intervention, such as vector control, based on transmission 'hotspots'. This is especially relevant for P. vivax, a more resilient parasite than P. falciparum, due to its ability to relapse and the operational shortcomings of delivering a "radical cure"

The Effects of Spatio-Temporal Heterogeneities on the Emergence and Spread of Dengue Virus

The dengue virus (DENV) remains a considerable global public health concern. The interactions between the virus, its mosquito vectors and the human host are complex and only partially understood. Dependencies of vector ecology on environmental attributes, such as temperature and rainfall, together with host population density, introduce strong spatiotemporal heterogeneities, resulting in irregular epidemic outbreaks and asynchronous oscillations in serotype prevalence. Human movements across different spatial scales have also been implicated as important drivers of dengue epidemiology across space and time, and further create the conditions for the geographic expansion of dengue into new habitats. Previously proposed transmission models often relied on strong, unrealistic assumptions regarding key epidemiological and ecological interactions to elucidate the effects of these spatio-temporal heterogeneities on the emergence, spread and persistence of dengue. Furthermore, the computational limitations of individual based models have hindered the development of more detailed descriptions of the influence of vector ecology, environment and human mobility on dengue epidemiology. In order to address these shortcomings, the main aim of this thesis was to rigorously quantify the effects of ecological drivers on dengue epidemiology within a robust and computational efficient framework. The individual based model presented included an explicit spatial structure, vector and human movement, spatio-temporal heterogeneity in population densities, and climate effects. The flexibility of the framework allowed robust assessment of the implications of classical modelling assumptions on the basic reproduction number, R₀, demonstrating that traditional approaches grossly inflate R₀ estimates. The model's more realistic meta-population formulation was then exploited to elucidate the effects of ecological heterogeneities on dengue incidence which showed that sufficient levels of community connectivity are required for the spread and persistence of dengue virus. By fitting the individual based model to empirical data, the influence of climate and on dengue was quantified, revealing the strong benefits that cross-sectional serological data could bring to more precisely inferring ecological drivers of arboviral epidemiology. Overall, the findings presented here demonstrate the wide epidemiological landscape which ecological drivers induce, forewarning against the strong implications of generalising interpretations from one particular setting across wider spatial contexts. These findings will prove invaluable for the assessment of vector-borne control strategies, such as mosquito elimination or vaccination deployment programs

Challenges in dengue research: A computational perspective

This is the final version of the article. Available from Wiley via the DOI in this record.The dengue virus is now the most widespread arbovirus affecting human populations, causing significant economic and social impact in South America and South-East Asia. Increasing urbanization and globalization, coupled with insufficient resources for control, misguided policies or lack of political will, and expansion of its mosquito vectors are some of the reasons why interventions have so far failed to curb this major public health problem. Computational approaches have elucidated on dengue's population dynamics with the aim to provide not only a better understanding of the evolution and epidemiology of the virus but also robust intervention strategies. It is clear, however, that these have been insufficient to address key aspects of dengue's biology, many of which will play a crucial role for the success of future control programmes, including vaccination. Within a multiscale perspective on this biological system, with the aim of linking evolutionary, ecological and epidemiological thinking, as well as to expand on classic modelling assumptions, we here propose, discuss and exemplify a few major computational avenues—real-time computational analysis of genetic data, phylodynamic modelling frameworks, within-host model frameworks and GPU-accelerated computing. We argue that these emerging approaches should offer valuable research opportunities over the coming years, as previously applied and demonstrated in the context of other pathogens.JL, AW and SG received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no. 268904 - DIVERSITY. MR was supported by a Royal Society University Research Fellowship. NRF by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant number 204311/Z/16/Z). WT has received funding from a doctoral scholarship from the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership

Seasonality and adaptive dynamics in host-parasite systems in wildlife

I parametri ecologici sono solitamente difficili da stimare nella fauna selvatica, ma, nel caso di malattie infettive, il tasso di trasmissione del patogeno è il processo più complesso da valutare. Tra i tratti caratteristici dell’ospite la taglia corporea è sicuramente il più influente, in quanto molti parametri demografici scalano allometricamente con essa. In questo lavoro ho mostrato come le relazioni allometriche possono legare la taglia dell’ospite al tasso di trasmissione della malattia e al suo tasso netto di riproduzione. Quindi ho analizzato come le dinamiche epidemiologiche variano in funzione della taglia. Inoltre, sotto le stesse ipotesi, ho studiato l’effetto della variazione stagionale di parametri come tasso di trasmissione e natalità, sulla dinamica della malattia. Per quanto riguarda il controllo dell’infezione, ho analizzato l’effetto di politiche di abbattimento in diverse condizioni ecologiche. In particolare, mi sono concentrato sull’efficacia del controllo in presenza di ceppi a diversa virulenza e in presenza di struttura d’età nella popolazione ospite. In entrambi i casi ho trovato che esistono determinate condizioni ecologiche per cui una politica di eradicazione della malattia basata sull’abbattimento può avere conseguenze peggiori dell’alternativa zero. Ho inoltre mostrato in quali condizioni semplici politiche di abbattimento tempo-variante possono migliorare significativamente il controllo della malattia.Ecological parameters are usually hard to estimate correctly in wild populations, but, in the case of infectious diseases, the rate of transmission of the pathogen agent is often the most complex process to evaluate. Of the many traits characterizing host species demography, body size is probably the most influential one, as many demographic parameters scale allometrically with host body size. In this work I show how the allometric relationships, usually found for demographic parameters, may link host body size with the disease transmission rate and its basic reproduction number. Then, I analysed the effect of seasonal variation in different ecological and epidemiological parameters on disease dynamics. Under the point of view of disease control, I analysed the effectiveness of depopulation policies in different ecological conditions. In particular, I focused on control effectiveness when strains with different virulence co-circulate in the host population and when disease transmission is a function of the age/stage class of the host individuals. In both cases, I found that (under certain conditions) culling policies may perform worse, in terms of disease control, than the do-nothing alternative. I also show in which conditions simple time-variant control policies can improve disease control in wildlife

Childhood epidemics and the demographic landscape of the Aland Archipelago

Historically, the introduction of childhood diseases such as measles or smallpox resulted in the infection of nearly every susceptible individual in a community. While smallpox has long been considered the deadlier of the two childhood diseases, research has shown that the immune response to measles infection results in immune suppression that can last for weeks or even months. Higher mortality during measles epidemics has typically been associated with completely susceptible populations; however, in Aland, Finland--a population that experienced regular epidemics of both childhood diseases--mortality from all causes during the 1820-21 measles epidemic was 25% higher than that experienced during the 1823-24 smallpox epidemic. Excess mortality surrounding measles epidemics suggests that this disease may have larger impacts on the demographic history of populations than previously thought. This study uses archival records to investigate syndemic interactions between measles and other diseases during a 19th century measles epidemic in the Aland Islands, Finland. Comparisons to smallpox and a non-epidemic period indicated greater than expected mortality for individuals aged 5 to 9 years and over 50 years; though neither epidemic had long-term demographic consequences. These results are consistent with deaths from secondary infections due to measles-induced immune suppression, but not conclusive. The unknown impact of measles exposure on adults with antibodies, and the variety of other diseases and symptom descriptions, indicates that the possibility of co-occurring epidemics cannot be ruled out.Includes bibliographical reference

Human mobility: Models and applications

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordRecent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.US Army Research Offic

Modeling, Predicting and Capturing Human Mobility

Realistic models of human mobility are critical for modern day applications, specifically for recommendation systems, resource planning and process optimization domains. Given the rapid proliferation of mobile devices equipped with Internet connectivity and GPS functionality today, aggregating large sums of individual geolocation data is feasible. The thesis focuses on methodologies to facilitate data-driven mobility modeling by drawing parallels between the inherent nature of mobility trajectories, statistical physics and information theory. On the applied side, the thesis contributions lie in leveraging the formulated mobility models to construct prediction workflows by adopting a privacy-by-design perspective. This enables end users to derive utility from location-based services while preserving their location privacy. Finally, the thesis presents several approaches to generate large-scale synthetic mobility datasets by applying machine learning approaches to facilitate experimental reproducibility

Human mobility:Models and applications

Recent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.Comment: 126 pages, 45+ figure