Time series analyses based on the joint lagged effect analysis of pollution and meteorological factors of hemorrhagic fever with renal syndrome and the construction of prediction model

ConclusionsThe SARIMA model may help to enhance the forecast of monthly HFRS incidence based on a long-range dataset. Our study had shown that environmental factors such as humidity and SO2 have a delayed effect on the occurrence of HFRS and that the effect of humidity can be influenced by SO2 and wind speed. Public health professionals should take greater care in controlling HFRS in low humidity, low windy conditions and 2 –3 days after SO2 levels above 200 μg/m3.
Source: PLoS Neglected Tropical Diseases - Category: Tropical Medicine Authors: Source Type: research