WP1 - Climate-Health Relations

• To complete the African dimension of the Liverpool University (UNILIV) Pathogen database by adding records of human and animal pathogens that occur in Africa from published literature.
• Expanding the database (in conjunction with the ERA NET Env Health project on ‘risk assessment of climate change on human health’ funded project) by the  addition of vector species and known climate and/or environmental sensitivities in an African context.
• Entering into the database published relationships between climate and diseases, details of the pilot experiment and details of their climate pathogen-vector relationships.
• To  develop an interface for African registered researcher interrogation of the database and for addition to the database.
• To map known pathogen-climate relationships for use as a visualization tool for possible areas of risk.
• To develop and display via a website mapped outputs from the whole project e.g. current climate sensitivities of disease and projection of future distributions; for regions in Africa and for selected diseases pan-African plots will be produced.

Task 1.1a: Develop methods to use host-pathogen-vector database in the African context both through visits of African partners to Liverpool and investigation of remote data entry  (UNILIV, UP, CSE, KNUST, UNIMA).

This task will involve short visits to UNILIV by African partners to learn about the database and to input  disease, pathogen and vector data into the database. Remote access to the database will be used for additions to be made to the database throughout the project.

Task 1.1b : Use of existing UNILIV pathogen database with input from African based partners to add host, pathogen and vector data for diseases important in Africa partly defined by stakeholders in WP1.3. (UNILIV, UP, CSE, KNUST, UNIMA, IPD, ILRI)

The data input activity will occur during visits of the African project partners.  The information will be identified through activities in WP1.3

Task 1.1c : Building the climate field for African entries to the database in conjunction with ERA NET EnvHealth project which is West Europe focused.  (UNILIV, UOC, UCAD, KNUST, UP)

This task will take input from WP1.2.  Most of the initial task will be defining new fields in the database that can make use of information in published literature and site specific information from the climate database in WP1.2 and entering the information into the database

Task 1.1d: Compile and add new pilot project data to the UNILIV pathogen database for target diseases and regions: RVF and malaria in Senegal, malaria in Ghana and Malawi and tick borne diseases in Malawi and across SADC countries. (UP, CSE, KNUST, UNIMA, IPD, ILRI)

New information obtained from the field studies in project partner countries will be produced in a format that can be used in the database

Task 1.1e: Build interface for database i) for registered health users and ii) for public access through a web site.  This facility will be used to map and disseminate both current climate controlled distributions of diseases but also future projections of diseases. (UNILIIV)

D1.1.a Report on current climate controls on selected infectious disease in Africa, based on database analysis and projection M18 (UNILIV, UP, CSE, KNUST, UNIMA, IPD, ILRI)

D1.1a: Report on current climate controls on selected infectious disease in Afri

D1.1.b Report on current climate sensitivities of disease and projections of future distributions including a mapped output on the project website M38 (UNILIV, UP, CSE, KNUST, UNIMA, IPD, ILRI)

D1.1b: Report on current climate sensitivities of diseases and projections of fu

M1.1.a Completion of main phase of data entry to database M15 (UNILIV)

M1.1a: Completion of main phase of data entry to database

M1.1.b Completion of disease-climate relationships from pilot projects M30 (UNILIV)

M1.1b: Completion of disease-climate relationships from pilot projects

To evaluate climate-driver disease relations and to drive dynamic vector-based disease model in hindcast and forecast modes, create a data base formatted for ease of use to all partners. Three different data set types will be added to the data base:

• decades-long gridded or surface station data sets, as well as three-dimensional atmospheric analyses
• high-resolution (in time and/or space) data sets provided by stakeholders in target countries or compiled from remotely sensed data
• partly MOS-corrected output from regional climate model integrations
• Data will be converted into common formats (ASCII, EXCEL), documented, also made available to African partners on hard disk and be transferred to the AMMA geophysical data base to allow dissemination of the data to a wide research community in Africa.

Task 1.2a: Form database for use in Africa of surface observations/reanalysis of climate variables – unprocessed database fields will be used for bias correction (UOC, ICTP, ECMWF, CSIC, UNIMA).

Task 1.2b: Integration of relevant remotely sensed data sets, for example the remote sensing of surface water in Senegal for RVF (UCAD).

Task 1.2c: Process atmospheric fields in database in terms of statistics (critical thresholds etc) relevant for disease defined in Task 1.1b (UOC, ICTP, ECMWF, CSIC, UCAD).

Task 1.2d: Assess the quality of ECMWF reanalysis products in target countries using station data: (UOC, ECMWF, ICTP).

D1.2.a: Database with gridded climate and remote sensed data and observed meteorological data
M15 (UOC)

D1.2a: Database with gridded climate and remote sensed data and observed meteoro

D1.2.b: Assessment of ECMWF interim reanalysis products for target countries M24 (ECMWF)

D1.2b: Assessment of ECMWF interim reanalysis products for target countries

D1.2.c: Final, documented database of observations for WP1.1 ready for transfer into the AMMA data base M26 (UOC)

D1.2c: Final, documented database of observations for WP1.1 ready for

M1.2.a: Furnish database on hard disk to African partners M15 (UOC)

M1.2.a: Furnish database on hard disk to African partners

M1.2.b: Final documented database transferred into the AMMA database M26 (UOC)

M1.2.b – Final documented database transferred into the AMMA database

• Define selected animal and human disease targets of importance to Africa and summarize present knowledge concerning their climate drivers.
• Using published literature, summarize present knowledge concerning their climate drivers and assess the state of knowledge of climate-disease incidence associations.
• Test the validity of a proportion of published climate –disease associations, using data collected from the pilot project target countries.
• Document these associations and present climate-disease vulnerability in a review document for planners.

Task 1.3a: Document climate drivers of priority infectious diseases, in an African context,  from published studies

This is a review task of published literature which will involve the partners from the pilot project countries and associates namely (CSE, UCAD, KNUST, UNIMA with UP, ILRI and UNILIV). The emphasis will be on diseases which are seen as having the most impact and to ascertain what is documented about their association with climate.

Task 1.3b: Test published climate-disease associations with new datasets from WP1.1 and WP1.2 in the pilot countries

The project will use its in-country experience of partners and stakeholders to examine, outside a modelling framework, where database descriptions of disease-climate association match climate regimes in the respective countries and to ascertain where these associations are manifest in those countries, (CSE, UCAD, KNUST, UNIMA with UP, ILRI and UNILIV.)

Task 1.3c: From the above analysis, identify most important and multivariate key statistics of these variables for the key identified diseases i.e. mean, max, variance and critical thresholds. (IC3, CSIC, CSE, UCAD, KNUST, UNIMA , UP, and ILRI)

This task is a step towards developing climate diagnostics for a range of diseases e.g. the criticality of rainfall frequency, above selected thresholds. These disease diagnostics will be run ahead of the modelling work to assess the usefulness of a simplified approach to utilizing the dynamical output of the climate modelling systems. The use of new statistical diagnostic approaches/tools to reassess the current (and historical) relationships in each target site between a set of (known plus some other possible) climate drivers and associated diseases (malaria, RVF etc.)  this will lead to the quantification of the scales of variability,

Task 1.3d: Prior to the work with the dynamical models in WP 2.1 we propose to build and use statistical models of increasing complexity to simulate in each region the dynamics of malaria, RVF etc. as a function of the different climate drivers. Analysis of the temporal dependence and validation of the diseases on the drivers  (GCVs, Akaike’s, etc..) and a dimensional space study will be undertaken. (IC3, CSIC)

Task 1.3e:  Document the relationships found in Tasks 1.3 a to d and the present climate disease vulnerability in a review document for planners (CSE, KNUST, UNIM, UP, CSIC and UNILIV)

Initially the document will appear on the project website, and will be built as a living document through several months of activity, but it is anticipated that an open access journal will be used for the publication of a full paper based on the document.  The scientific publication document (D1.3b) will concentrate on a smaller number of diseases.  The review document (D1.3a) will cover a larger number of diseases in a summary format.

Task 1.3f Engage core stakeholder groups in each region through the organization of a series of small workshops.  This will also act as an introduction to the project for stakeholders. (CSE, UCAD, KNUST, UNIM, UP ILRI, UNILIV, CSIC)

This activity will be undertaken in Theme 6 as part of its programme of Schools and Workshops within WPs 6.1 and 6.2.

D1.3.a  Review document for governmental and NGO planners concerning state-of-the-art knowledge concerning climate driver impact on target disease incidence and present climate vulnerabilities for endemic and epidemic incidence according to these relationships.
M12 (UNILIV, UP, CSE, KNUST, UNIM, ILRI)

D1.3.a – Review document for governmental and NGO planners concerning state-of-t

D1.3b  Scientific publication validating existing published climate-driver disease (principally malaria and Rift Valley Fever)  incidence relationships in pilot project target countries and appropriate modifications to these relationships in a future climate  M24 (UNILIV, UP, CSE, KNUST, UNIM, IPD, ILRI, CSIC)

D1.3b – Scientific publication validating existing published climate-driver dise

M1.3a: Review document for governmental and NGO planners completed M12 (UNILIV, UP, CSE, KNUST, UNIM, ILRI)

M1.3.a – Review document for governmental and NGO planners completed