Article screening and study inclusion criteria
Using the reference management software Zotero®, all exported articles and documents will be organized into separate collections, one for each disease. Once the searches completed (one per disease and per database), references for each search will be archived in a unique database, and duplicates will be removed.
Articles retrieved by the bibliographic search will be screened as detailed below to keep only those relevant for the map. An additional step of eligibility (detailed in the “Eligibility criteria” section of the “Systematic review” part of the protocol), will be performed to select the subset of articles included in the synthesis.
Screening strategy
The screening of titles, abstracts and full-texts will be performed by 3 members of the review team. Eligibility criteria have been proposed by the review team and validated by the expert panel.
Consistency checking
Prior to the beginning of the screening, the 3 persons from the review team will screen the titles of 42 articles (3 per disease) randomly extracted from those retrieved by the search equation. The Kappa scores should be larger than 0,6. Differences in screening decisions will be discussed, the eligibility criteria refined, and the screening test performed on 42 different articles, with the aim at improving the Kappa scores, if needed.
The same exercise will be conducted on 28 abstracts (2 per disease).
At the full-text stage, a double-checking of all articles rejected will be performed by the project leader.
Eligibility criteria
Different eligibility criteria will be applied at the 3 steps of the screening: title, abstract, and full-text. If the information provided by the title or abstract is not enough to reject or retain the article with certainty, it will be retained and examined at the next eligibility stage.
Title
Inclusion criteria: presence of the name of the disease or of the pathogen agent responsible for this disease, or presence of a generic term related to infectious diseases or pathogens (to ensure we do not reject relevant papers when the title is not precise enough). In the case of vector-borne diseases, the title may not contain any of the above criteria but would still be eligible if it contains the name of the vector or a generic term related to vectors (e.g. mosquitoes, ticks, vectors). The list of pathogen agents and vectors identified for each disease can be found in Additional file 1.
Exclusion criteria: absence of the above-mentioned elements; or indication that the article is a review, a meta-analysis, an opinion paper, ex situ studies or theoretical modelling. Relevant reviews and meta-analysis will be kept in a separate collection for use in the discussion of our work.
Abstract
Inclusion criteria: presence of words related to ecosystem components, functioning, or management.
Exclusion criteria: similar as for title or elements showing that the paper is a descriptive study (no exposure/intervention, no comparator); destructive intervention targeted towards a vector or a host; intervention non-related to ecosystems, such as individual prophylaxis, micro-habitats removal (tires, flower pots), spraying of organic insecticides, genetical modifications of vectors, etc.
Full text
Inclusion criteria: the outcome has been obtained from field data (e.g. vector/host collection on the field, epidemiological database collected in hospitals); presence of all PECO elements detailed in the section “Definition of the question components”.
Exclusion criteria: similar to those applied for title or abstract screening, or elements informing that the outcome is the output of a model, or has been obtained ex situ (e.g. in laboratory).
Reasons for exclusion
The list of articles excluded at full-text will be provided, with reason for their exclusion.
Study validity assessment
Critical appraisal will be limited to the identification of research design, but susceptibility to bias will not be assessed. The type and diversity of research designs will be reported in the narrative synthesis accompanying the systematic map. We expect to find research designs such as: post hoc surveys, cross-sectional studies, time-series, and maybe a few before-after studies.
Data coding strategy
Meta-data extraction for mapping will be performed by the 3 members of the review team. Meta-data will be extracted from all articles retained after the screening process. From the full-text of these articles, we will extract and store in an Excel database the following information:
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Title
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First author
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Year of publication
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Country
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Continent
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Disease
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Study design
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Type of ecosystem component/function
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Outcome measured in vector (yes/no)
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Outcome measured in intermediate host (yes/no)
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Outcome measured in non-human final host (yes/no)
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Outcome measured in human (yes/no)
In the “Country” column, the name of the country/countries in which field study was performed or data collected will be written. Studies performed at the global scale will be attributed the code “global”.
For the name of the disease, the coding will follow the list presented in the section Question components.
We will code study designs as follow: PH for post hoc surveys, CS for cross-sectional studies, TS for time-series, and BA for before-after studies.
We expect to describe ecosystem components/function with the following list established during scoping: predation, competition, dilution (includes host species richness/diversity), host density/abundance, community composition, landscape composition, landscape structure, habitat type, vegetation measurement (NDVI, % of vegetation cover), habitat perturbation, distance to habitat, habitat management. This list may be revised as appropriate if other components/functions are identified during examination at full-text.
To facilitate the use of the map, epidemiological outcomes will be coded in 4 different columns, signaling where measurements have been conducted.
Study mapping and presentation
The systematic map will be reported as an Excel spreadsheet. A geographical map will present for each disease the geographical distribution of publications. Then, we will analyse for each disease the characteristics of publications per type of ecosystem component/function (i.e. Exposure), and per type of epidemiological measurement (i.e. Outcome). These results will be presented in tables (one per disease) to highlight knowledge gaps and trends in research orientations, and as a narrative description.