The Effect of Ambient Temperature on Infectious Diarrhea and Diarrhea-like Illness in Wuxi, China
| Autor: | Ping Shi, Yujun Chen, Chao Shi, Cheng Qian, Yuan Shen, Wei-Hong Feng, Qi Zhang, Yong Xiao, Yumeng Gao |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Diarrhea
Distributed lag China medicine.medical_specialty 010501 environmental sciences medicine.disease_cause 01 natural sciences Dysentery 03 medical and health sciences 0302 clinical medicine Humans Medicine 030212 general & internal medicine Viral diarrhea Disease burden 0105 earth and related environmental sciences business.industry Public health Temperature Public Health Environmental and Occupational Health Norovirus Seasons High incidence medicine.symptom business Weather patterns Demography |
| Zdroj: | Disaster Medicine and Public Health Preparedness. 16:583-589 |
| ISSN: | 1938-744X 1935-7893 |
| Popis: | Background:The disease burden of infectious diarrhea cannot be underestimated. Its seasonal patterns indicate that weather patterns may play an important role and have an important effect on it. The objective of this study was to clarify the relationship between temperature and infectious diarrhea, and diarrhea-like illness.Methods:Distributed lag non-linear model, which was based on the definition of a cross-basis, was used to examine the effect.Results:Viral diarrhea usually had high incidence in autumn-winter and spring with a peak at -6°C; Norovirus circulated throughout the year with an insignificant peak at 8°C, while related bacteria usually tested positive in summer and peaked at 22°C. The lag-response curve of the proportion of diarrhea-like cases in outpatient and emergency cases revealed that at -6°C, with the lag days increasing, the proportion increased. Similar phenomena were observed at the beginning of the curves of virus and bacterial positive rate, showing that the risk increased as the lag days increased, peaking on days 16 and 9, respectively. The shape of lag-response curve of norovirus positive rate was different from others, presenting m-type, with 2 peaks on day 3 and day 18.Conclusion:Weather patterns should be taken into account when developing surveillance programs and formulating relevant public health intervention strategies. |
| Databáze: | OpenAIRE |
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