ArticleF1000Research2026
Protocol for Systematic Review: "Understanding Climate Sensitive Infectious Disease Burden in Australia".
Article in F1000Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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Abstract
Climate change is increasingly being recognized as a major driver of infectious disease risk globally, and timely information is required to support public health policy decision-makers. This protocol aims to provide local policy makers and scientists with a framework for conducting rapid and timely systematic reviews to estimate how short/long-term climate changes influences the burden and geographical distribution of human infectious diseases in Australia. Using the Joanna Briggs Institute (JBI) Population, Exposure, Outcome (PEO) methodology, the systematic review outlined in this protocol will include observational and modelling studies from 1995-2025 that examine climate- infectious disease relationships in human populations in all regions (urban/rural and remote) of Australia. Searches are to be conducted across several databases (PubMed, Web of Science, Scopus, Embase, CINAHL, Informit, Google Scholar). Data extraction shall use concise eligibility criteria to capture study design, exposure metrics, outcome measures, statistical models, and effect measures. The review shall standardize exposures on different scales (e.g., per 1 °C or per 10 mm rainfall) for comparability and apply log transformations for meta-analysis where feasible. Risk of bias for studies included in the review will be assessed using JBI critical appraisal tools relevant to the study type being evaluated. Synthesis, with meta-analysis and meta-regression is to be considered if sufficient comparable data exists. If synthesis of data is feasible the ROBINS-E tool for risk of bias shall be applied for studies included in the meta-analysis/regression. This protocol provides the framework for the conduct of a systematic literature review that will inform public health policy that relates to climate-sensitive infectious diseases in Australia by synthesizing evidence on associations between both short-term variability of weather/climatic factors (temperature, rainfall, humidity, and extremes) as well as longer term climate change and infectious diseases in humans in Australia. PROSPERO ID: CRD420251268644.
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