School of BioSciences - Research Publications

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    The global distribution of the arbovirus vectors Aedes aegypti and Ae. albopictus
    Kraemer, MUG ; Sinka, ME ; Duda, KA ; Mylne, AQN ; Shearer, FM ; Barker, CM ; Moore, CG ; Carvalho, RG ; Coelho, GE ; Van Bortel, W ; Hendrickx, G ; Schaffner, F ; Elyazar, IRF ; Teng, H-J ; Brady, OJ ; Messina, JP ; Pigott, DM ; Scott, TW ; Smith, DL ; Wint, GRW ; Golding, N ; Hay, SI (eLIFE SCIENCES PUBL LTD, 2015-06-30)
    Dengue and chikungunya are increasing global public health concerns due to their rapid geographical spread and increasing disease burden. Knowledge of the contemporary distribution of their shared vectors, Aedes aegypti and Aedes albopictus remains incomplete and is complicated by an ongoing range expansion fuelled by increased global trade and travel. Mapping the global distribution of these vectors and the geographical determinants of their ranges is essential for public health planning. Here we compile the largest contemporary database for both species and pair it with relevant environmental variables predicting their global distribution. We show Aedes distributions to be the widest ever recorded; now extensive in all continents, including North America and Europe. These maps will help define the spatial limits of current autochthonous transmission of dengue and chikungunya viruses. It is only with this kind of rigorous entomological baseline that we can hope to project future health impacts of these viruses.
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    Updates to the zoonotic niche map of Ebola virus disease in Africa
    Pigott, DM ; Millear, AI ; Earl, L ; Morozoff, C ; Han, BA ; Shearer, FM ; Weiss, DJ ; Brady, OJ ; Kraemer, MUG ; Moyes, CL ; Bhatt, S ; Gething, PW ; Golding, N ; Hay, SI (ELIFE SCIENCES PUBLICATIONS LTD, 2016-07-14)
    As the outbreak of Ebola virus disease (EVD) in West Africa is now contained, attention is turning from control to future outbreak prediction and prevention. Building on a previously published zoonotic niche map (Pigott et al., 2014), this study incorporates new human and animal occurrence data and expands upon the way in which potential bat EVD reservoir species are incorporated. This update demonstrates the potential for incorporating and updating data used to generate the predicted suitability map. A new data portal for sharing such maps is discussed. This output represents the most up-to-date estimate of the extent of EVD zoonotic risk in Africa. These maps can assist in strengthening surveillance and response capacity to contain viral haemorrhagic fevers.
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    Mapping global environmental suitability for Zika virus
    Messina, JP ; Kraemer, MUG ; Brady, OJ ; Pigott, DM ; Shearer, FM ; Weiss, DJ ; Golding, N ; Ruktanonchar, CW ; Gething, PW ; Cohn, E ; Brownstein, JS ; Khan, K ; Tatem, AJ ; Jaenisch, T ; Murray, CJL ; Marinho, F ; Scott, TW ; Hay, SI (eLIFE SCIENCES PUBL LTD, 2016-04-19)
    Zika virus was discovered in Uganda in 1947 and is transmitted by Aedes mosquitoes, which also act as vectors for dengue and chikungunya viruses throughout much of the tropical world. In 2007, an outbreak in the Federated States of Micronesia sparked public health concern. In 2013, the virus began to spread across other parts of Oceania and in 2015, a large outbreak in Latin America began in Brazil. Possible associations with microcephaly and Guillain-Barré syndrome observed in this outbreak have raised concerns about continued global spread of Zika virus, prompting its declaration as a Public Health Emergency of International Concern by the World Health Organization. We conducted species distribution modelling to map environmental suitability for Zika. We show a large portion of tropical and sub-tropical regions globally have suitable environmental conditions with over 2.17 billion people inhabiting these areas.
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    Mapping the spatial distribution of the Japanese encephalitis vector, Culex tritaeniorhynchus Giles, 1901 (Diptera: Culicidae) within areas of Japanese encephalitis risk
    Longbottom, J ; Browne, AJ ; Pigott, DM ; Sinka, ME ; Golding, N ; Hay, SI ; Moyes, CL ; Shearer, FM (BIOMED CENTRAL LTD, 2017-03-16)
    BACKGROUND: Japanese encephalitis (JE) is one of the most significant aetiological agents of viral encephalitis in Asia. This medically important arbovirus is primarily spread from vertebrate hosts to humans by the mosquito vector Culex tritaeniorhynchus. Knowledge of the contemporary distribution of this vector species is lacking, and efforts to define areas of disease risk greatly depend on a thorough understanding of the variation in this mosquito's geographical distribution. RESULTS: We assembled a contemporary database of Cx. tritaeniorhynchus presence records within Japanese encephalitis risk areas from formal literature and other relevant resources, resulting in 1,045 geo-referenced, spatially and temporally unique presence records spanning from 1928 to 2014 (71.9% of records obtained between 2001 and 2014). These presence data were combined with a background dataset capturing sample bias in our presence dataset, along with environmental and socio-economic covariates, to inform a boosted regression tree model predicting environmental suitability for Cx. tritaeniorhynchus at each 5 × 5 km gridded cell within areas of JE risk. The resulting fine-scale map highlights areas of high environmental suitability for this species across India, Nepal and China that coincide with areas of high JE incidence, emphasising the role of this vector in disease transmission and the utility of the map generated. CONCLUSIONS: Our map contributes towards efforts determining the spatial heterogeneity in Cx. tritaeniorhynchus distribution within the limits of JE transmission. Specifically, this map can be used to inform vector control programs and can be used to identify key areas where the prevention of Cx. tritaeniorhynchus establishment should be a priority.
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    Mapping the zoonotic niche of Lassa fever in Africa
    Mylne, AQN ; Pigott, DM ; Longbottom, J ; Shearer, F ; Duda, KA ; Messina, JP ; Weiss, DJ ; Moyes, CL ; Golding, N ; Hay, SI (OXFORD UNIV PRESS, 2015-08-01)
    BACKGROUND: Lassa fever is a viral haemorrhagic illness responsible for disease outbreaks across West Africa. It is a zoonosis, with the primary reservoir species identified as the Natal multimammate mouse, Mastomys natalensis. The host is distributed across sub-Saharan Africa while the virus' range appears to be restricted to West Africa. The majority of infections result from interactions between the animal reservoir and human populations, although secondary transmission between humans can occur, particularly in hospital settings. METHODS: Using a species distribution model, the locations of confirmed human and animal infections with Lassa virus (LASV) were used to generate a probabilistic surface of zoonotic transmission potential across sub-Saharan Africa. RESULTS: Our results predict that 37.7 million people in 14 countries, across much of West Africa, live in areas where conditions are suitable for zoonotic transmission of LASV. Four of these countries, where at-risk populations are predicted, have yet to report any cases of Lassa fever. CONCLUSIONS: These maps act as a spatial guide for future surveillance activities to better characterise the geographical distribution of the disease and understand the anthropological, virological and zoological interactions necessary for viral transmission. Combining this zoonotic niche map with detailed patient travel histories can aid differential diagnoses of febrile illnesses, enabling a more rapid response in providing care and reducing the risk of onward transmission.
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    Predicting the geographical distributions of the macaque hosts and mosquito vectors of Plasmodium knowlesi malaria in forested and non-forested areas
    Moyes, CL ; Shearer, FM ; Huang, Z ; Wiebe, A ; Gibson, HS ; Nijman, V ; Mohd-Azlan, J ; Brodie, JF ; Malaivijitnond, S ; Linkie, M ; Samejima, H ; O'Brien, TG ; Trainor, CR ; Hamada, Y ; Giordano, AJ ; Kinnaird, MF ; Elyazar, IRF ; Sinka, ME ; Vythilingam, I ; Bangs, MJ ; Pigott, DM ; Weiss, DJ ; Golding, N ; Hay, SI (BMC, 2016-04-28)
    BACKGROUND: Plasmodium knowlesi is a zoonotic pathogen, transmitted among macaques and to humans by anopheline mosquitoes. Information on P. knowlesi malaria is lacking in most regions so the first step to understand the geographical distribution of disease risk is to define the distributions of the reservoir and vector species. METHODS: We used macaque and mosquito species presence data, background data that captured sampling bias in the presence data, a boosted regression tree model and environmental datasets, including annual data for land classes, to predict the distributions of each vector and host species. We then compared the predicted distribution of each species with cover of each land class. RESULTS: Fine-scale distribution maps were generated for three macaque host species (Macaca fascicularis, M. nemestrina and M. leonina) and two mosquito vector complexes (the Dirus Complex and the Leucosphyrus Complex). The Leucosphyrus Complex was predicted to occur in areas with disturbed, but not intact, forest cover (> 60% tree cover) whereas the Dirus Complex was predicted to occur in areas with 10-100% tree cover as well as vegetation mosaics and cropland. Of the macaque species, M. nemestrina was mainly predicted to occur in forested areas whereas M. fascicularis was predicted to occur in vegetation mosaics, cropland, wetland and urban areas in addition to forested areas. CONCLUSIONS: The predicted M. fascicularis distribution encompassed a wide range of habitats where humans are found. This is of most significance in the northern part of its range where members of the Dirus Complex are the main P. knowlesi vectors because these mosquitoes were also predicted to occur in a wider range of habitats. Our results support the hypothesis that conversion of intact forest into disturbed forest (for example plantations or timber concessions), or the creation of vegetation mosaics, will increase the probability that members of the Leucosphyrus Complex occur at these locations, as well as bringing humans into these areas. An explicit analysis of disease risk itself using infection data is required to explore this further. The species distributions generated here can now be included in future analyses of P. knowlesi infection risk.
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    Spread of yellow fever virus outbreak in Angola and the Democratic Republic of the Congo 2015-16: a modelling study
    Kraemer, MUG ; Faria, NR ; Reiner, RC ; Golding, N ; Nikolay, B ; Stasse, S ; Johansson, MA ; Salje, H ; Faye, O ; Wint, GRW ; Niedrig, M ; Shearer, FM ; Hill, SC ; Thompson, RN ; Bisanzio, D ; Taveira, N ; Nax, HH ; Pradelski, BSR ; Nsoesie, EO ; Murphy, NR ; Bogoch, II ; Khan, K ; Brownstein, JS ; Tatem, AJ ; de Oliveira, T ; Smith, DL ; Sall, AA ; Pybus, OG ; Hay, SI ; Cauchemez, S (ELSEVIER SCI LTD, 2017-03-01)
    BACKGROUND: Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock. METHODS: We jointly analysed datasets describing the epidemic of yellow fever, vector suitability, human demography, and mobility in central Africa to understand and predict the spread of yellow fever virus. We used a standard logistic model to infer the district-specific yellow fever virus infection risk during the course of the epidemic in the region. FINDINGS: The early spread of yellow fever virus was characterised by fast exponential growth (doubling time of 5-7 days) and fast spatial expansion (49 districts reported cases after only 3 months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (Pearson's r 0·52, 95% CI 0·34-0·66). The further away locations were from Luanda, the later the date of invasion (Pearson's r 0·60, 95% CI 0·52-0·66). In a Cox model, we noted that districts with higher population densities also had higher risks of sustained transmission (the hazard ratio for cases ceasing was 0·74, 95% CI 0·13-0·92 per log-unit increase in the population size of a district). A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others with a lower risk (area under the curve 0·94, 95% CI 0·92-0·97). If at the start of the epidemic, sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected. INTERPRETATION: Our findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy. FUNDING: Wellcome Trust.
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    Local, national, and regional viral haemorrhagic fever pandemic potential in Africa: a multistage analysis
    Pigott, DM ; Deshpande, A ; Letourneau, I ; Morozoff, C ; Reiner, RC ; Kraemer, MUG ; Brent, SE ; Bogoch, II ; Khan, K ; Biehl, MH ; Burstein, R ; Earl, L ; Fullman, N ; Messina, JP ; Mylne, AQN ; Moyes, CL ; Shearer, FM ; Bhatt, S ; Brady, OJ ; Gething, PW ; Weiss, DJ ; Tatem, AJ ; Caley, L ; De Groeve, T ; Vernaccini, L ; Golding, N ; Horby, P ; Kuhn, JH ; Laney, SJ ; Ng, E ; Piot, P ; Sankoh, O ; Murray, CJL ; Hay, SI (ELSEVIER SCIENCE INC, 2017-12-16)
    BACKGROUND: Predicting when and where pathogens will emerge is difficult, yet, as shown by the recent Ebola and Zika epidemics, effective and timely responses are key. It is therefore crucial to transition from reactive to proactive responses for these pathogens. To better identify priorities for outbreak mitigation and prevention, we developed a cohesive framework combining disparate methods and data sources, and assessed subnational pandemic potential for four viral haemorrhagic fevers in Africa, Crimean-Congo haemorrhagic fever, Ebola virus disease, Lassa fever, and Marburg virus disease. METHODS: In this multistage analysis, we quantified three stages underlying the potential of widespread viral haemorrhagic fever epidemics. Environmental suitability maps were used to define stage 1, index-case potential, which assesses populations at risk of infection due to spillover from zoonotic hosts or vectors, identifying where index cases could present. Stage 2, outbreak potential, iterates upon an existing framework, the Index for Risk Management, to measure potential for secondary spread in people within specific communities. For stage 3, epidemic potential, we combined local and international scale connectivity assessments with stage 2 to evaluate possible spread of local outbreaks nationally, regionally, and internationally. FINDINGS: We found epidemic potential to vary within Africa, with regions where viral haemorrhagic fever outbreaks have previously occurred (eg, western Africa) and areas currently considered non-endemic (eg, Cameroon and Ethiopia) both ranking highly. Tracking transitions between stages showed how an index case can escalate into a widespread epidemic in the absence of intervention (eg, Nigeria and Guinea). Our analysis showed Chad, Somalia, and South Sudan to be highly susceptible to any outbreak at subnational levels. INTERPRETATION: Our analysis provides a unified assessment of potential epidemic trajectories, with the aim of allowing national and international agencies to pre-emptively evaluate needs and target resources. Within each country, our framework identifies at-risk subnational locations in which to improve surveillance, diagnostic capabilities, and health systems in parallel with the design of policies for optimal responses at each stage. In conjunction with pandemic preparedness activities, assessments such as ours can identify regions where needs and provisions do not align, and thus should be targeted for future strengthening and support. FUNDING: Paul G Allen Family Foundation, Bill & Melinda Gates Foundation, Wellcome Trust, UK Department for International Development.
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    Global yellow fever vaccination coverage from 1970 to 2016: an adjusted retrospective analysis
    Shearer, FM ; Moyes, CL ; Pigott, DM ; Brady, OJ ; Marinho, F ; Deshpande, A ; Longbottom, J ; Browne, AJ ; Kraemer, MUG ; O'Reilly, KM ; Hombach, J ; Yactayo, S ; de Araujo, VEM ; da Nobrega, AA ; Mosser, JF ; Stanaway, JD ; Lim, SS ; Hay, SI ; Golding, N ; Reiner, RC (ELSEVIER SCI LTD, 2017-11-01)
    BACKGROUND: Substantial outbreaks of yellow fever in Angola and Brazil in the past 2 years, combined with global shortages in vaccine stockpiles, highlight a pressing need to assess present control strategies. The aims of this study were to estimate global yellow fever vaccination coverage from 1970 through to 2016 at high spatial resolution and to calculate the number of individuals still requiring vaccination to reach population coverage thresholds for outbreak prevention. METHODS: For this adjusted retrospective analysis, we compiled data from a range of sources (eg, WHO reports and health-service-provider registeries) reporting on yellow fever vaccination activities between May 1, 1939, and Oct 29, 2016. To account for uncertainty in how vaccine campaigns were targeted, we calculated three population coverage values to encompass alternative scenarios. We combined these data with demographic information and tracked vaccination coverage through time to estimate the proportion of the population who had ever received a yellow fever vaccine for each second level administrative division across countries at risk of yellow fever virus transmission from 1970 to 2016. FINDINGS: Overall, substantial increases in vaccine coverage have occurred since 1970, but notable gaps still exist in contemporary coverage within yellow fever risk zones. We estimate that between 393·7 million and 472·9 million people still require vaccination in areas at risk of yellow fever virus transmission to achieve the 80% population coverage threshold recommended by WHO; this represents between 43% and 52% of the population within yellow fever risk zones, compared with between 66% and 76% of the population who would have required vaccination in 1970. INTERPRETATION: Our results highlight important gaps in yellow fever vaccination coverage, can contribute to improved quantification of outbreak risk, and help to guide planning of future vaccination efforts and emergency stockpiling. FUNDING: The Rhodes Trust, Bill & Melinda Gates Foundation, the Wellcome Trust, the National Library of Medicine of the National Institutes of Health, the European Union's Horizon 2020 research and innovation programme.
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    Estimating Geographical Variation in the Risk of Zoonotic Plasmodium knowlesi Infection in Countries Eliminating Malaria
    Shearer, FM ; Huang, Z ; Weiss, DJ ; Wiebe, A ; Gibson, HS ; Battle, KE ; Pigott, DM ; Brady, OJ ; Putaporntip, C ; Jongwutiwes, S ; Lau, YL ; Manske, M ; Amato, R ; Elyazar, IRF ; Vythilingam, I ; Bhatt, S ; Gething, PW ; Singh, B ; Golding, N ; Hay, SI ; Moyes, CL ; Churcher, TS (PUBLIC LIBRARY SCIENCE, 2016-08-01)
    BACKGROUND: Infection by the simian malaria parasite, Plasmodium knowlesi, can lead to severe and fatal disease in humans, and is the most common cause of malaria in parts of Malaysia. Despite being a serious public health concern, the geographical distribution of P. knowlesi malaria risk is poorly understood because the parasite is often misidentified as one of the human malarias. Human cases have been confirmed in at least nine Southeast Asian countries, many of which are making progress towards eliminating the human malarias. Understanding the geographical distribution of P. knowlesi is important for identifying areas where malaria transmission will continue after the human malarias have been eliminated. METHODOLOGY/PRINCIPAL FINDINGS: A total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. Predictions were then made throughout Southeast Asia, including regions where infection data are sparse. The resulting map predicts areas of high risk for P. knowlesi infection in a number of countries that are forecast to be malaria-free by 2025 (Malaysia, Cambodia, Thailand and Vietnam) as well as countries projected to be eliminating malaria (Myanmar, Laos, Indonesia and the Philippines). CONCLUSIONS/SIGNIFICANCE: We have produced the first map of P. knowlesi malaria risk, at a fine-scale resolution, to identify priority areas for surveillance based on regions with sparse data and high estimated risk. Our map provides an initial evidence base to better understand the spatial distribution of this disease and its potential wider contribution to malaria incidence. Considering malaria elimination goals, areas for prioritised surveillance are identified.