Publications
72 results found
Parham PE, Pople D, Christiansen-Jucht C, et al., 2012, Modelling the Role of Environmental Variables on the Population Dynamics of the Malaria Vector Anopheles gambiae sensu stricto, Malaria Journal, Vol: 11: 271
Truscott J, Fraser C, Cauchemez S, et al., 2012, Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza, Journal of the Royal Society Interface, Vol: 9, Pages: 304-312, ISSN: 1742-5662
Seasonal influenza has considerable impact around the world, both economically and in mortality among risk groups, but there is considerable uncertainty as to the essential mechanisms and their parametrization. In this paper, we identify a number of characteristic features of influenza incidence time series in temperate regions, including ranges of annual attack rates and outbreak durations. By constraining the output of simple models to match these characteristic features, we investigate the role played by population heterogeneity, multiple strains, cross-immunity and the rate of strain evolution in the generation of incidence time series. Results indicate that an age-structured model with non-random mixing and co-circulating strains are both required to match observed time-series data. Our work gives estimates of the seasonal peak basic reproduction number, R0, in the range 1.6–3. Estimates of R0 are strongly correlated with the timescale for waning of immunity to current circulating seasonal influenza strain, which we estimate is between 3 and 8 years. Seasonal variation in transmissibility is largely confined to 15–30% of its mean value. While population heterogeneity and cross-immunity are required mechanisms, the degree of heterogeneity and cross-immunity is not tightly constrained. We discuss our findings in the context of other work fitting to seasonal influenza data.
Sinerchia M, Field AJ, Woods JD, et al., 2011, Using an individual-based model with four trophic levels to model the effect of predation and competition on squid recruitment, ICES Journal of Marine Science
The Lagrangian Ensemble recruitment model (LERM) is the first prognostic model of fisheries recruitment based upon individuals. It incorporates five functional groups: phytoplankton (diatoms), herbivorous zooplankton (copepods), carnivorous zooplankton (squid paralarvae), and two top predators. Physiology and behaviour are described by equations derived from literature based on reproducible laboratory experiments. LERM is built using the Lagrangian Ensemble metamodel, in which the demography and biofeedback of each dynamic population are diagnostic properties, emerging from the life histories of individuals. The response of the plankton ecosystem and squid recruitment to different scenarios of exogenous forcing is investigated. Simulations were run at 41°N 27°W (Azores) under a stationary annual cycle of atmospheric forcing. The ecosystem adjusts to a stable attractor for each scenario. The emergent properties of each attractor are investigated, with focus on predation, competition for food, and spawning magnitude. Annual recruitment is a complex emergent property dependent on several factors, including food availability, predation, competition, and post-hatching growth rate, as proposed by Hjort's critical period theory, relating recruitment to predation mortality, depending on growth rate and hence food availability. The model provides a useful step towards linking small-scale processes governing the life histories of larvae and fisheries on the large scale.
Griffin JT, Hollingsworth D, Okell LC, et al., 2010, STRATEGIES TOWARDS <i>PLASMODIUM FALCIPARUM</i> MALARIA ELIMINATION IN AFRICA USING CURRENTLY AVAILABLE TOOLS, 59th Annual Meeting of the American-Society-of-Tropical-Medicine-and-Hygiene (ASTMH), Publisher: AMER SOC TROP MED & HYGIENE, Pages: 262-262, ISSN: 0002-9637
Griffin JT, Hollingsworth TD, Okell LC, et al., 2010, Reducing Plasmodium falciparum malaria transmission in Africa: a model-based evaluation of intervention strategies., PLoS Med, Vol: 7, Pages: 1-27, ISSN: 1549-1676
BACKGROUND: Over the past decade malaria intervention coverage has been scaled up across Africa. However, it remains unclear what overall reduction in transmission is achievable using currently available tools. METHODS AND FINDINGS: We developed an individual-based simulation model for Plasmodium falciparum transmission in an African context incorporating the three major vector species (Anopheles gambiae s.s., An. arabiensis, and An. funestus) with parameters obtained by fitting to parasite prevalence data from 34 transmission settings across Africa. We incorporated the effect of the switch to artemisinin-combination therapy (ACT) and increasing coverage of long-lasting insecticide treated nets (LLINs) from the year 2000 onwards. We then explored the impact on transmission of continued roll-out of LLINs, additional rounds of indoor residual spraying (IRS), mass screening and treatment (MSAT), and a future RTS,S/AS01 vaccine in six representative settings with varying transmission intensity (as summarized by the annual entomological inoculation rate, EIR: 1 setting with low, 3 with moderate, and 2 with high EIRs), vector-species combinations, and patterns of seasonality. In all settings we considered a realistic target of 80% coverage of interventions. In the low-transmission setting (EIR approximately 3 ibppy [infectious bites per person per year]), LLINs have the potential to reduce malaria transmission to low levels (<1% parasite prevalence in all age-groups) provided usage levels are high and sustained. In two of the moderate-transmission settings (EIR approximately 43 and 81 ibppy), additional rounds of IRS with DDT coupled with MSAT could drive parasite prevalence below a 1% threshold. However, in the third (EIR = 46) with An. arabiensis prevailing, these interventions are insufficient to reach this threshold. In both high-transmission settings (EIR approximately 586 and 675 ibppy), either unrealistically high coverage levels (>90%) or novel tools and/or
Truscott J, Fraser C, Hinsley W, et al., 2009, Quantifying the transmissibility of human influenza and its seasonal variation in temperate regions., PLoS Curr, Vol: 1
Seasonal influenza has considerable impact around the world, both economically and in mortality among risk groups. The long term patterns of disease are hard to capture with simple models, while the interplay of epidemiological processes with antigenic evolution makes detailed modelling difficult and computationally intensive. We identify a number of characteristic features of flu incidence time series in temperate regions, including ranges of annual attack rates and outbreak durations. We construct pseudo-likelihoods to capture these characteristic features and examine the ability of a collection of simple models to reproduce them under seasonal variation in transmission. Results indicate that an age-structured model with non-random mixing and co-circulating strains are both required to match time series data. The extent of matching behaviour also serves to define informative ranges for parameters governing essential dynamics. Our work gives estimates of the seasonal peak basic reproduction, R0, in the range 1.7-2.1, with the degree of seasonal variation having limited impact of these estimates. We find that it is only really possible to estimate a lower bound on the degree of seasonal variation in influenza transmissibility, namely that transmissibility in the low transmission season may be only 5-10% less than the peak value. These results give some insight into the extent to which transmissibility of the H1N1pdm pandemic virus may increase in Northern Hemisphere temperate countries in winter 2009. We find that the timescale for waning of immunity to current circulating seasonal influenza strain is between 4 and 8 years, consistent with studies of the antigenic variation of influenza, and that inter-subtype cross-immunity is restricted to low levels.
Fraser C, Donnelly CA, Cauchemez S, et al., 2009, Influenza: Making Privileged Data Public Response, SCIENCE, Vol: 325, Pages: 1072-1073, ISSN: 0036-8075
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Fraser C, Donnelly CA, Cauchemez S, et al., 2009, Pandemic Potential of a Strain of Influenza A (H1N1): Early Findings, SCIENCE, Vol: 324, Pages: 1557-1561, ISSN: 0036-8075
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Christophe Fraser, Christl AD, Cauchemez S, et al., 2009, Response, Science, Vol: 325, Pages: 1072-1073, ISSN: 0036-8075
Hinsley W, Field T, Woods J, 2007, Creating Individual Based Models of the Plankton Ecosystem, International Conference on Computational Science, Publisher: Springer-Verlag, LNCS, Pages: 111-118, ISSN: 0302-9743
Hinsley W, Field T, Woods J, 2007, Creating individual based models of the plankton ecosystem, 7th International Conference on Computational Science (ICCS 2007), Publisher: SPRINGER-VERLAG BERLIN, Pages: 111-+, ISSN: 0302-9743
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- Citations: 2
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