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Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions

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Infectious Diseases of Poverty 2022年第3期11卷 37-53页

作者： Monica Golumbeanu Guo-Jing Yang Flavia Camponovo Erin M.Stuckey Nicholas Hamon Mathias Mondy sarah rees Nakul Chitnis Ewan Cameron Melissa A.Penny Swiss Tropical and Public Health Institute AllschwilSwitzerland Key Laboratory of Tropical Translational Medicine of Ministry of Education and School of Tropical Medicine and Laboratory Medicine The First and Second Affiliated Hospital of Hainan Medical UniversityHainan Medical UniversityHaikouHainanPeople’s Republic of China University of Basel BaselSwitzerland Center for Communicable Disease Dynamics Department of EpidemiologyHarvard T.H.Chan School of Public HealthBostonMA02115USA The Bill&Melinda Gates Foundation SeattleWAUSA Innovative Vector Control Consortium LiverpoolUK Malaria Atlas Project Big Data InstituteUniversity of OxfordOxfordUK Curtin University PerthAustralia Telethon Kids Institute Perth Children’s HospitalPerthAustralia

Background:Substantial research is underway to develop next-generation interventions that address current malaria control challenges.As there is limited testing in their early development,it is difficult to predefine intervention properties such as efficacy that achieve target health goals,and therefore challenging to prioritize selection of novel candidate interventions.Here,we present a quantitative approach to guide intervention development using mathematical models of malaria dynamics coupled with machine learning.Our analysis identifies requirements of efficacy,coverage,and duration of effect for five novel malaria interventions to achieve targeted reductions in malaria prevalence.Methods:A mathematical model of malaria transmission dynamics is used to simulate deployment and predict potential impact of new malaria interventions by considering operational,health-system,population,and disease characteristics.Our method relies on consultation with product development stakeholders to define the putative space of novel intervention specifications.We couple the disease model with machine learning to search this multi-dimensional space and efficiently identify optimal intervention properties that achieve specified health goals.Results:We apply our approach to five malaria interventions under development.Aiming for malaria prevalence reduction,we identify and quantify key determinants of intervention impact along with their minimal properties required to achieve the desired health goals.While coverage is generally identified as the largest driver of impact,higher efficacy,longer protection duration or multiple deployments per year are needed to increase prevalence reduction.We show that interventions on multiple parasite or vector targets,as well as combinations the new interventions with drug treatment,lead to significant burden reductions and lower efficacy or duration requirements.Conclusions:Our approach uses disease dynamic models and machine learning to support decision-making and resource investment,facilita

关键词： Infectious diseases Malaria Novel interventions Mathematical modelling Machine learning

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Laser ablation(in situ)Lu-Hf dating of magmatic fluorite and hydrothermal fluorite-bearing veins

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Geoscience Frontiers 2023年第6期14卷 142-154页

作者： Stijn Glorie Jacob Mulder Martin Hand Adrian Fabris Alexander Simpson sarah Gilbert Department of Earth Sciences University of AdelaideSA 5005Australia Geological Survey of South Australia Department for Energy and MiningAdelaideSA 5005Australia Adelaide Microscopy University of AdelaideSA 5005Australia

Fluorite(CaF_(2))is a common hydrothermal mineral,which precipitates from fluorine-rich fluids with an exceptional capacity to transport metals and Rare Earth Elements(rees).Hence,the ability to date fluorite has important implications for understanding the timing of metal transport in hydrothermal systems.Here we present,for the first time,fluorite Lu-Hf dates from fluorite-carbonate veins from the Olympic Cu-Au Province in South Australia.The fluorite dates were obtained in situ using the recently developed LA-ICP-MS/MS Lu-Hf dating method.A fluorite-calcite age of 1588±19 Ma was obtained for the Torrens Dam prospect,consistent with the timing of the formation of the nearby Olympic Dam iron-oxide copper gold Breccia Complex.Veins in the overlying Neoproterozoic successions were dated at 502±14 Ma,indicating a temporal link between Cu-sulphide remobilisation and the Delamerian Orogeny.Additionally,we present a multi-session reproducible date for magmatic fluorite from a monzogranite in the Pilbara Craton(Lu-Hf age of 2866±19 Ma).This age is consistent with a garnet Lu-Hf age from the same sample(2850±12 Ma)and holds potential to be developed into a secondary reference material for future fluorite Lu-Hf dating.

关键词： Reaction-cell ICP-MS In-situ geochronology Fluorite-calcite veins Iron oxide copper-gold Critical mineral exploration Rare Earth Elements

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The 3rd Global Summit of Research Institutes for Disaster Risk Reduction:Expanding the Platform for Bridging Science and Policy Making

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International Journal of Disaster Risk Science 2017年第2期8卷 224-230页

作者： Andrew Collins Hirokazu Tatano Wilma James Chadia Wannous Kaoru Takara Virginia Murray Charles Scawthorn Jim Mori sarah Aziz Khalid M.Mosalam Stefan Hochrainer-Stigler Irasema Alcántara-Ayala Elisabeth Krausmann Wei-Sen Li Ana Maria Cruz Subhajyoti Samaddar Tom De Groeve Yuichi Ono Kelvin Berryman Koji Suzuki Mark Ashley Parry Peter McGowran John G.rees Department of Geography/Disaster and Development Network (DDN) Northumbria University Disaster Prevention Research Institute (DPRI) Kyoto University United Nations Office for Disaster Risk Reduction (UNISDR) Public Health England United Nations Office for Disaster Reduction (UNISDR) Scientific and Technical Advisory Group and Integrated Research on Disaster Risk (IRDR) Scientific Committee Pacific Earthquake Engineering Research Center (PEER) University of CaliforniaBerkeley Centre for Southeast Asia Disaster Prevention Research Initiative (SEADPRI) Universiti Kebangsaan Malaysia Department of Civil and Environmental Engineering Pacific Earthquake Engineering CenterUniversity of CaliforniaBerkeley International Institute for Applied Systems Analysis (IIASA) Institute of Geography National Autonomous University of Mexico (UNAM) European Commission Joint Research Centre (JRC) APEC Emergency Preparedness Capacity Building Center (EPCC) International Research Institute of Disaster Science Tohoku University Natural Hazards Division GNS Science National Research Institute for Earth Science and Disaster Resilience (NIED) British Geological Survey and Research Councils UK

The Global Alliance of Disaster Research Institutes held its 3rd Global Summit of Research Institutes for Disaster Risk Reduction at the Disaster Prevention Research Institute,Kyoto University,Japan,19–21 March,2017.The Global Alliance seeks to contribute to enhancing disaster risk reduction(DRR) and disaster resilience through the collaboration of research organizations around the world.The summit aim was to expand the platform for bridging science and policy making by evaluating the evidence base needed to meet the expected outcomes and actions of the Sendai Framework for Disaster RiskReduction 2015–2030 and its Science and Technology Roadmap.The summit reflected the international nature of collaborative research and action.A pre-conference questionnaire filled out by Global Alliance members identified323 research projects that are indicative of current research.These were categorized to support seven parallel discussion sessions related to the Sendai Framework priorities for action.Four discussion sessions focused on research that aims to deepen the understanding of disaster risks.Three cross-cutting sessions focused on research that is aimed at the priorities for action on governance,resilience,and recovery.Discussion summaries were presentedin plenary sessions in support of outcomes for widely enhancing the science and policy of DRR.

关键词： Disaster risk reduction research GADRI global summit Policy Science

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GREENHOUSE GAS AND AMMONIA EMISSION MITIGATION PRIORITIES FOR UK POLICY TARGETS

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Frontiers of Agricultural Science and Engineering 2023年第2期10卷 268-280页

作者： sarah BUCKINGHAM Cairistiona F.E.TOPP Pete SMITH Vera EORY David R.CHADWICK Christina K.BAXTER Joanna M.CLOY Shaun CONNOLLY Emily C.COOLEDGE Nicholas J.COWAN Julia DREWER Colm DUFFY Naomi JFOX Asma JEBARI Becky JENKINS Dominika J.KROL Karina A.MARSDEN Graham A.MCAULIFFE Steven J.MORRISON Vincent O'FLAHERTY Rachael RAMSEY Karl G.RICHARDS Rainer ROEHE Jo SMITH Kate SMITH Taro TAKAHASHI Rachel E.THORMAN John WILLIAMS Jeremy WILTSHIRE Robert M.rees Scotland’s Rural College EdinburghEH93JGUK Institute of Biological&Environmental Sciences AberdeenAB243UUUK School of Natural Sciences Bangor UniversityBangorGwyneddLL572DGUK Agricultural Development and Advisory Service(ADAS) BoxworthCambridgeCB234NNUK School of Biological and Chemical Sciences University of GalwayH91 TK33Ireland Centre for Ecology and Hydrology Bush EstateMidlothianEH260QBUK The James Hutton Institute DundeeDD25DAUK Rothamsted Research North WykeOkehamptonDevonEX202SBUK Ricardo Energy&Environment HarwellOxonOX110QRUK Environment Soils and Land Use DepartmentTeagascCounty WexfordY35 TC97Ireland Agri-food and Biosciences Institute HillsboroughCounty DownBT266DRUK Bristol Veterinary School University of BristolSomersetBS405DUUK

Agriculture is essential for providing food and maintaining food security while concurrently delivering multiple other ecosystem services. However,agricultural systems are generally a net source of greenhouse gases and ammonia. They, therefore, need to substantively contribute to climate change mitigation and net zero ambitions. It is widely acknowledged that there is a need to further reduce and mitigate emissions across sectors, including agriculture to address the climate emergency and emissions gap. This discussion paper outlines a collation of opinions from a range of experts within agricultural research and advisory roles following a greenhouse gas and ammonia emission mitigation workshop held in the UK in March 2022. The meeting identified the top mitigation priorities within the UK's agricultural sector to achieve reductions in greenhouse gases and ammonia that are compatible with policy targets. In addition, experts provided an overview of what they believe are the key knowledge gaps, future opportunities and cobenefits to mitigation practices as well as indicating the potential barriers to uptake for mitigation scenarios discussed.

关键词： agriculture ammonia greenhouse gas mitigation net zero

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