ReviewGlobal change biology2024
Infectious disease responses to human climate change adaptations.
Review in Global change biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Impact of climate-induced human migration on dengue exposure risk in Africa.Research square · 2026Article
- Predicting the global risk of chikungunya virus under climate change using ensemble species distribution models.Frontiers in cellular and infection microbiology · 2026Article
- Infectious disease responses to human climate change adaptations.Global change biology · 2024Review
- Associations between extreme weather events, resource insecurities, and HIV vulnerabilities with self-reported urinary tract infection symptoms among adolescent girls and young women in Kenya.The journal of climate change and healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Many recent studies have examined the impact of predicted changes in temperature and precipitation patterns on infectious diseases under different greenhouse gas emissions scenarios. But these emissions scenarios symbolize more than altered temperature and precipitation regimes; they also represent differing levels of change in energy, transportation, and food production at a global scale to reduce the effects of climate change. The ways humans respond to climate change, either through adaptation or mitigation, have underappreciated, yet hugely impactful effects on infectious disease transmission, often in complex and sometimes nonintuitive ways. Thus, in addition to investigating the direct effects of climate changes on infectious diseases, it is critical to consider how human preventative measures and adaptations to climate change will alter the environments and hosts that support pathogens. Here, we consider the ways that human responses to climate change will likely impact disease risk in both positive and negative ways. We evaluate the evidence for these impacts based on the available data, and identify research directions needed to address climate change while minimizing externalities associated with infectious disease, especially for vulnerable communities. We identify several different human adaptations to climate change that are likely to affect infectious disease risk independently of the effects of climate change itself. We categorize these changes into adaptation strategies to secure access to water, food, and shelter, and mitigation strategies to decrease greenhouse gas emissions. We recognize that adaptation strategies are more likely to have infectious disease consequences for under-resourced communities, and call attention to the need for socio-ecological studies to connect human behavioral responses to climate change and their impacts on infectious disease. Understanding these effects is crucial as climate change intensifies and the global community builds momentum to slow these changes and reduce their impacts on human health, economic productivity, and political stability.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.