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PLOS 22/04/14 An Environmental Data Set for Vector-Borne Disease Modeling and Epidemiology. Abstract Understanding the environmental conditions of disease transmission is important in the study of vector-borne diseases.

PLOS 22/04/14 An Environmental Data Set for Vector-Borne Disease Modeling and Epidemiology

Low- and middle-income countries bear a significant portion of the disease burden; but data about weather conditions in those countries can be sparse and difficult to reconstruct. Here, we describe methods to assemble high-resolution gridded time series data sets of air temperature, relative humidity, land temperature, and rainfall for such areas; and we test these methods on the island of Madagascar. Air temperature and relative humidity were constructed using statistical interpolation of weather station measurements; the resulting median 95th percentile absolute errors were 2.75°C and 16.6%. Missing pixels from the MODIS11 remote sensing land temperature product were estimated using Fourier decomposition and time-series analysis; thus providing an alternative to the 8-day and 30-day aggregated products. Editor: Joseph A. Introduction Methods. PLOS 29/07/14 Inter-Model Comparison of the Landscape Determinants of Vector-Borne Disease: Implications for Epidemiological and Entomological Risk Modeling.

Abstract Extrapolating landscape regression models for use in assessing vector-borne disease risk and other applications requires thoughtful evaluation of fundamental model choice issues.

PLOS 29/07/14 Inter-Model Comparison of the Landscape Determinants of Vector-Borne Disease: Implications for Epidemiological and Entomological Risk Modeling

To examine implications of such choices, an analysis was conducted to explore the extent to which disparate landscape models agree in their epidemiological and entomological risk predictions when extrapolated to new regions. Agreement between six literature-drawn landscape models was examined by comparing predicted county-level distributions of either Lyme disease or Ixodes scapularis vector using Spearman ranked correlation. AUC analyses and multinomial logistic regression were used to assess the ability of these extrapolated landscape models to predict observed national data. PLOS 08/01/15 Using Modelling to Disentangle the Relative Contributions of Zoonotic and Anthroponotic Transmission: The Case of Lassa Fever.

Abstract Background Zoonotic infections, which transmit from animals to humans, form the majority of new human pathogens.

PLOS 08/01/15 Using Modelling to Disentangle the Relative Contributions of Zoonotic and Anthroponotic Transmission: The Case of Lassa Fever

Following zoonotic transmission, the pathogen may already have, or may acquire, the ability to transmit from human to human. PLOS 24/03/15 Optimal Strategies for Controlling Riverine Tsetse Flies Using Targets: A Modelling Study. Abstract Background Tsetse flies occur in much of sub-Saharan Africa where they transmit the trypanosomes that cause the diseases of sleeping sickness in humans and nagana in livestock.

PLOS 24/03/15 Optimal Strategies for Controlling Riverine Tsetse Flies Using Targets: A Modelling Study

One of the most economical and effective methods of tsetse control is the use of insecticide-treated screens, called targets, that simulate hosts. Targets have been ~1m2, but recently it was shown that those tsetse that occupy riverine situations, and which are the main vectors of sleeping sickness, respond well to targets only ~0.06m2. The cheapness of these tiny targets suggests the need to reconsider what intensity and duration of target deployments comprise the most cost-effective strategy in various riverine habitats. PLOS 20/06/13 A Probabilistic Model in Cross-Sectional Studies for Identifying Interactions between Two Persistent Vector-Borne. Background In natural populations, individuals are infected more often by several pathogens than by just one.

PLOS 20/06/13 A Probabilistic Model in Cross-Sectional Studies for Identifying Interactions between Two Persistent Vector-Borne

In such a context, pathogens can interact. This interaction could modify the probability of infection by subsequent pathogens. Identifying when pathogen associations correspond to biological interactions is a challenge in cross-sectional studies where the sequence of infection cannot be demonstrated. Methodology/Principal Findings Here we modelled the probability of an individual being infected by one and then another pathogen, using a probabilistic model and maximum likelihood statistics. PLOS 11/01/11 Modeling the Dynamic Transmission of Dengue Fever: Investigating Disease Persistence. Abstract Background Dengue is a disease of great complexity, due to interactions between humans, mosquitoes and various virus serotypes as well as efficient vector survival strategies.

PLOS 11/01/11 Modeling the Dynamic Transmission of Dengue Fever: Investigating Disease Persistence

Thus, understanding the factors influencing the persistence of the disease has been a challenge for scientists and policy makers. The aim of this study is to investigate the influence of various factors related to humans and vectors in the maintenance of viral transmission during extended periods. Methodology/Principal Findings We developed a stochastic cellular automata model to simulate the spread of dengue fever in a dense community. PLOS - AVRIL 2012 - A Research Agenda for Helminth Diseases of Humans: Modelling for Control and Elimination.

PLOS 29/11/11 Visceral Leishmaniasis in the Indian Subcontinent: Modelling Epidemiology and Control. PLOS 08/05/12 Modelling Transmission of Vector-Borne Pathogens Shows Complex Dynamics When Vector Feeding Sites Are Limited. Results Simple Discontinuous Model We consider that each host has a limited number of feeding sites, which is on average, k.

PLOS 08/05/12 Modelling Transmission of Vector-Borne Pathogens Shows Complex Dynamics When Vector Feeding Sites Are Limited

The probability of a host being fed upon differs among species, since the two host types H and M have a different average number of feeding sites available: kh and km respectively. Therefore, from the perspective of the vector, there are a total of N feeding sites available in the host population where: (1)Clearly, the system can operate in one of two modes: (a) where there are insufficient feeding sites for all vector individuals, V>N, and (b) where there are enough feeding sites for all vector individuals, V<N. Table 1. Doi:10.1371/journal.pone.0036730.t001 To derive the basic reproduction ratio R0, we calculate the number of new infected hosts per initial infected host, over the average infectivity time of that host in a fully susceptible host population.

. (2)The expected number of new infected hosts per infected vector can be similarly derived (4). Figure 2.