Publications
12 results found
Adib K, Hancock PA, Rahimli A, et al., 2021, A participatory modelling approach for investigating the spread of COVID-19 in countries of the Eastern Mediterranean Region to support public health decision-making, BMJ Global Health, Vol: 6, Pages: 1-7, ISSN: 2059-7908
<jats:p>Early on in the COVID-19 pandemic, the WHO Eastern Mediterranean Regional Office recognised the importance of epidemiological modelling to forecast the progression of the COVID-19 pandemic to support decisions guiding the implementation of response measures. We established a modelling support team to facilitate the application of epidemiological modelling analyses in the Eastern Mediterranean Region (EMR) countries. Here, we present an innovative, stepwise approach to participatory modelling of the COVID-19 pandemic that engaged decision-makers and public health professionals from countries throughout all stages of the modelling process. Our approach consisted of first identifying the relevant policy questions, collecting country-specific data and interpreting model findings from a decision-maker’s perspective, as well as communicating model uncertainty. We used a simple modelling methodology that was adaptable to the shortage of epidemiological data, and the limited modelling capacity, in our region. We discuss the benefits of using models to produce rapid decision-making guidance for COVID-19 control in the WHO EMR, as well as challenges that we have experienced regarding conveying uncertainty associated with model results, synthesising and comparing results across multiple modelling approaches, and modelling fragile and conflict-affected states.</jats:p>
Rathmes G, Rumisha SF, Lucas TCD, et al., 2020, Global estimation of anti-malarial drug effectiveness for the treatment of uncomplicatedPlasmodium falciparummalaria 1991-2019, MALARIA JOURNAL, Vol: 19
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- Citations: 7
Hancock PA, Hendriks CJM, Tangena J-A, et al., 2020, Mapping trends in insecticide resistance phenotypes in African malaria vectors, PLoS Biology, Vol: 18, Pages: 1-23, ISSN: 1544-9173
Mitigating the threat of insecticide resistance in African malaria vector populations requires comprehensive information about where resistance occurs, to what degree, and how this has changed over time. Estimating these trends is complicated by the sparse, heterogeneous distribution of observations of resistance phenotypes in field populations. We use 6,423 observations of the prevalence of resistance to the most important vector control insecticides to inform a Bayesian geostatistical ensemble modelling approach, generating fine-scale predictive maps of resistance phenotypes in mosquitoes from the Anopheles gambiae complex across Africa. Our models are informed by a suite of 111 predictor variables describing potential drivers of selection for resistance. Our maps show alarming increases in the prevalence of resistance to pyrethroids and DDT across sub-Saharan Africa from 2005 to 2017, with mean mortality following insecticide exposure declining from almost 100% to less than 30% in some areas, as well as substantial spatial variation in resistance trends.
Hancock PA, Hendriks CJM, Tangena J-A, et al., 2020, Mapping Trends in Insecticide Resistance Phenotypes in African Malaria Vectors, Publisher: Cold Spring Harbor Laboratory
<jats:title>ABSTRACT</jats:title><jats:p>Mitigating the threat of insecticide resistance in African malaria vector populations requires comprehensive information about where resistance occurs, to what degree, and how this has changed over time. Estimating these trends is complicated by the sparse, heterogeneous distribution of observations of resistance phenotypes in field populations. We use 6423 observations of the prevalence of resistance to the most important vector control insecticides to inform a Bayesian geostatistical ensemble modelling approach, generating fine-scale predictive maps of resistance phenotypes in mosquitoes from the<jats:italic>Anopheles gambiae</jats:italic>complex across Africa. Our models are informed by a suite of 111 predictor variables describing potential drivers of selection for resistance. Our maps show alarming increases in the prevalence of resistance to pyrethroids and DDT across Sub-Saharan Africa from 2005-2017 as well as substantial spatial variation in resistance trends.</jats:p>
Hancock PA, Ritchie SA, Koenraadt CJM, et al., 2019, Predicting the spatial dynamics of <i>Wolbachia</i> infections in <i>Aedes aegypti</i> arbovirus vector populations in heterogeneous landscapes, Journal of Applied Ecology, Vol: 56, Pages: 1674-1686, ISSN: 0021-8901
Hancock PA, Wiebe A, Gleave KA, et al., 2018, Associated patterns of insecticide resistance in field populations of malaria vectors across Africa, Proceedings of the National Academy of Sciences of the United States of America, Vol: 115, Pages: 5938-5943, ISSN: 0027-8424
The development of insecticide resistance in African malaria vectors threatens the continued efficacy of important vector control methods that rely on a limited set of insecticides. To understand the operational significance of resistance we require quantitative information about levels of resistance in field populations to the suite of vector control insecticides. Estimation of resistance is complicated by the sparsity of observations in field populations, variation in resistance over time and space at local and regional scales, and cross-resistance between different insecticide types. Using observations of the prevalence of resistance in mosquito species from the Anopheles gambiae complex sampled from 1,183 locations throughout Africa, we applied Bayesian geostatistical models to quantify patterns of covariation in resistance phenotypes across different insecticides. For resistance to the three pyrethroids tested, deltamethrin, permethrin, and λ-cyhalothrin, we found consistent forms of covariation across sub-Saharan Africa and covariation between resistance to these pyrethroids and resistance to DDT. We found no evidence of resistance interactions between carbamate and organophosphate insecticides or between these insecticides and those from other classes. For pyrethroids and DDT we found significant associations between predicted mean resistance and the observed frequency of kdr mutations in the Vgsc gene in field mosquito samples, with DDT showing the strongest association. These results improve our capacity to understand and predict resistance patterns throughout Africa and can guide the development of monitoring strategies.
Hancock PA, White VL, Ritchie SA, et al., 2016, Predicting Wolbachia invasion dynamics in Aedes aegypti populations using models of density-dependent demographic traits, BMC Biology, Vol: 14
Hancock PA, Thomas MB, Godfray HCJ, 2009, An age-structured model to evaluate the potential of novel malaria-control interventions: a case study of fungal biopesticide sprays, PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, Vol: 276, Pages: 71-80, ISSN: 0962-8452
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- Citations: 41
Hancock PA, Godfray HCJ, 2007, Application of the lumped age-class technique to studying the dynamics of malaria-mosquito-human interactions, MALARIA JOURNAL, Vol: 6
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- Citations: 29
Hancock PA, Milner-Gulland EJ, 2006, Optimal movement strategies for social foragers in unpredictable environments, ECOLOGY, Vol: 87, Pages: 2094-2102, ISSN: 0012-9658
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- Citations: 28
Hancock PA, Milner-Gulland EJ, Keeling MJ, 2006, Modelling the many-wrongs principle: The navigational advantages of aggregation in nomadic foragers, JOURNAL OF THEORETICAL BIOLOGY, Vol: 240, Pages: 302-310, ISSN: 0022-5193
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- Citations: 20
Hancock PA, Milner-Gulland EJ, Keeling MJ, 2005, An individual based model of bearded pig abundance, ECOLOGICAL MODELLING, Vol: 181, Pages: 123-137, ISSN: 0304-3800
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- Citations: 13
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