Scarlet Fever and Meteorological Exposures in Jiangsu, China: A Time-stratified Case-crossover Study
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Background
Increasing interest arises in the association between short-term meteorological exposure and scarlet fever risk, but the association with individual-level infection risk remains poorly understood.
Methods
We collected weather data from ERA5-Land (hourly, 9 km × 9 km) and aggregated into daily exposures to match all scarlet fever cases data in Jiangsu, reported the Nationwide Notifiable Infectious Diseases Reporting Information System from 2005 to 2023. We conducted a time-stratified case-crossover study with associations quantified by odds ratio (ORs) with confidence interval (CI) from conditional logistic regressions with distributed lag non-linear models.
Results
The odds ratios are generally significant with a 2–5 days lag, peaking at 3 days: 0.991 (95% CI: 0.986, 0.995) for temperature, 0.995 (95% CI: 0.994, 0.996) for relative humidity, 0.994 (95% CI: 0.990, 0.997) for total precipitation, 1.009 (95% CI: 1.005, 1.012) for solar radiation, and 1.088 (95% CI: 1.057, 1.120) for surface pressure. For non-linear effects, temperature showed a reversed U-shaped curve with peak risk between 15.17 ° C and 19 ° C and fluctuated risk at extremely low temperatures (below − 5 ° C). Relative humidity posed a higher risk between 56% and 80%. Children aged over 6 exhibit greater susceptibility with stronger associations in temperature and surface pressure. Stronger associations were found in the post-COVID-19 era (2020–2023), particularly for temperature, solar radiation, and surface pressure.
Conclusions
Our study suggested significant non-linear associations between meteorological factors and scarlet fever risk, and provided some insights into the vulnerable children and the immune debt after COVID-19.
