ArticlePloS one2025
Temperature-humidity synergistic effects on predominant intestinal infectious diseases in Shenzhen, China: A predictive modeling framework for epidemiological early warning systems.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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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Who cites it
1 citing paper in PubMed.
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The prevalence of intestinal infectious diseases (IIDs) in densely populated cities substantially escalates the burden of disease. An ecological study on the epidemiological trends of predominant IIDs-hand, foot, and mouth disease (HFMD), viral diarrhea (DV), and non-viral diarrhea (DN)-was conducted in Shenzhen, China (2012-2022), aiming to elucidate the associations of meteorological factors, including extreme temperatures, seasonal variations, and temperature-humidity interactions with IID transmission, and to establish a monitoring and early warning framework. We assessed temperature-related morbidity's short-term lagged effects, long-term cumulative impacts, and seasonal patterns using distributed lag non-linear models, finding that high temperatures (30°C) significantly increase HFMD and DN risks, low temperatures (13.8°C) worsen DV infections, and high temperatures have specific pathogenic effects on individuals aged 0 and over 20 years. Humidity-mediated seasonal variations in the incidence of IIDs were identified within equivalent temperature ranges. Generalized additive models (GAMs) further decoded the incidence patterns of IIDs across population subgroups under temperature-humidity interactions. An early warning model based on temperature-humidity indicators successfully predicted HFMD and DV outbreaks, establishing a novel framework for future epidemiological analyses grounded in temperature-humidity evidence. This study provides actionable insights for optimizing region-specific public health interventions and strengthening early risk mitigation strategies.
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