See further below for some information about the 2011-2013 update analysis and some current and future revisions to study definitions and categories, and how this compares to the methodology for 1997-2010 data. 

The methods shown here as described similarly or exactly in most of our peer-reviewed publications (see the publications page for the references and links to the open-access papers). Each publication will typically also expand on this standard methods section with specific comments related to the topic being covered in that paper.

The overarching dataset was developed following a detailed and systematic search of all the studies for infectious disease research from the major sources of public and charitable funding for infectious disease research studies, including the Wellcome Trust, MRC and other research councils, UK government departments, European Commission, the Bill and Melinda Gates Foundation, and other research charities.

We developed the dataset by a) downloading all data from the funder website and manually filtering the infectious disease studies; or b) searching open access databases on the funder website for infection-related keyword terms; or c) contacting the funder directly and requesting details of their infection studies. Funders were identified through author’s knowledge of the R&D landscape, contributors to the National Research Register, and systematic searches of the internet. Click here to download an Excel file that contains a list of funders included here, and the source of the information.

Author MGH performed the majority of data extraction, with support from author JRF. Each study was assigned to as many primary disease categories as appropriate. Within each category, topic-specific sub-sections (including specific pathogen or disease) were documented. Studies were also allocated to one of four R&D categories: pre-clinical; phase 1, 2, or 3; product development; and implementation and operational research (including surveillance, epidemiology and statistical and modelling projects). Major funding organisations were categorised in their own right, and smaller funding organisations were grouped into categories, such as in-house university funding, research charities, and government departments. A total of twenty-six funder categories were used. Click here for definitions of each area of categorisation and keywords used to search funders websites.

Studies were excluded if: (i) they were not immediately relevant to infection; (ii) they were veterinary infectious disease research studies; (iii) they concerned the use of viral vectors to investigate non-communicable diseases; (iv) they were grants for symposia or meetings; or (v) they included UK researchers, but with the funding awarded to and administered through a non-UK institution. No private sector (commercial) funding was included in this analysis as publicly available data were limited and considered to be under-representative. Unfunded studies were excluded.

Grants awarded in a currency other than pounds sterling were converted to UK pounds using the mean exchange rate in the year of the award. All awards were adjusted for inflation and reported in 2010 UK pounds. Analysis was carried out in Microsoft Excel and Access (versions 2000 and 2007) and Stata (versions 11, 12 and 13).

For extracting 2011-2013 information (update posted Nov 2014)

The update has been carried out with a very similar methodology., as per the above detail and our already-published papers. We will list the funders included in this update (broadly the same as before, a few small changes). We wish to be as clear and transparent as possible with our work, so if anything is not clear, or you have any questions at all about the methodology, please do get in touch.  Some changes that we have made include –

Translational research category
We have revised the title of the ‘implementation and operational research’ category to ‘translational’. The actual content of what is included has not altered, merely the label. Some categories, particularly when including several types of study, can be hard to describe satisfactorily. However, various definitions online seem to suggest that ‘translational’ means different things to different people, and can therefore reasonably include epidemiology, modelling, patient-focused research, systematic reviews and evidence syntheses, outbreak research, behavioural and social sciences, implementation, operational research and a few other niche study designs.

Cross-disciplinary
We have added in a new ‘type of science’ category, this being ‘cross-disciplinary’. This is defined as there being significant components of a study that covers two types of science (as per our categorisation). For example, a pre-clinical study that incorporates a phase I trial will likely be considered  cross-disciplinary. Another example would be the use of genomics to aid oubtreak research. We made this change as there appears to be increasing numbers of studies that transcend more traditional disciplinary boundaries, and thus we wanted our dataset to reflect this growing trend.  We have not yet applied this revised categorisation to 1997-2010 data (a very big job, and time and capacity issues mean we have other priorities with this study at the moment).

Phase III studies
We have looked again at our data and concluded that some studies that have been included in the ‘intervention/product development and roll-out’ category might actually be phase III trials. It’s quite a tricky area. Some interventional studies don’t necessarily follow the traditional definitions of phase I-III in terms of trials of a new drug, for example we are considering this study to be phase III, whereas previously it would probably have been included as ‘intervention/product development’. We will post revised definitions of our revised criteria for phase III, phase IV and ‘other intervention’ studies. This work will initially be applied to the 2011-2013 update, and at a later point be applied to 1997-2010.

Future new categories and definitions
We are looking at improving the breakdown of the pre-clinical studies, to more clearly express some important areas such as genomics (this is being done at the moment), proteomics and so on. We will also look at the translational category as a whole and clearly identify the different study designs described above. These precise additions will make our dataset even more powerful and useful to funders, policymakers and researchers.

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