Literature DB >> 34872055

Impact of Temperature and Rainfall on Typhoid/Paratyphoid Fever in Taizhou, China: Effect Estimation and Vulnerable Group Identification.

Qi Gao1,2, Zhidong Liu3, Jianjun Xiang4,5, Ying Zhang6, Michael Xiaoliang Tong4, Shuzi Wang7, Yiwen Zhang8, Qiyong Liu2,9, Baofa Jiang1,2, Peng Bi4.   

Abstract

The impact of temperature and rainfall on the occurrence of typhoid/paratyphoid fever are not fully understood. This study aimed to characterize the effect of daily ambient temperature and total rainfall on the incidence of typhoid/paratyphoid in a sub-tropical climate city of China and to identify the vulnerable groups for disease prevention. Daily notified typhoid/paratyphoid fever cases and meteorological data for Taizhou from 2005 to 2013 were extracted from the National Notifiable Disease Surveillance System and the Meteorological Data Sharing Service System, respectively. Distributed lag nonlinear model was used to quantify the association between daily mean temperature, total rainfall, and typhoid/paratyphoid fever. Subgroup analyses by gender, age, and occupation were conducted to identify the vulnerable groups. A total of 625 typhoid fever cases and 1,353 paratyphoid fever cases were reported during the study period. An increased risk of typhoid fever was detected with the increase of temperature (Each 2°C rise resulted in 6%, 95% [confidence interval] CI: 2-10% increase in typhoid cases), while the increased risk was associated with the higher temperature for paratyphoid (the highest cumulative risk of temperature was 33.40 [95% CI: 12.23-91.19] at 33°C). After the onset of mild precipitation, the relative risk of typhoid fever increased in a short-lasting and with a 13-26 days delay, and the risk was no significant after the continuous increase of precipitation (the highest cumulative risk of rainfall was 24.96 [95% CI: 4.54-87.21] at 100 mm). Whereas the risk of paratyphoid fever was immediate and long lasting, and increase rapidly with the increase of rainfall (each 100 mm increase was associated with 26% increase in paratyphoid fever cases). Significant temperature-typhoid/paratyphoid fever and rainfall-typhoid/paratyphoid fever associations were found in both genders and those aged 0-4 years old, 15-60 years old, farmers, and children. Characterized with a lagged, nonlinear, and cumulative effect, high temperature and rainfall could increase the risk of typhoid/paratyphoid fever in regions with a subtropical climate. Public health interventions such as early warning and community health education should be taken to prevent the increased risk of typhoid/paratyphoid fever, especially for the vulnerable groups.

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Year:  2021        PMID: 34872055      PMCID: PMC8832923          DOI: 10.4269/ajtmh.20-1457

Source DB:  PubMed          Journal:  Am J Trop Med Hyg        ISSN: 0002-9637            Impact factor:   2.345


  62 in total

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Review 4.  Global trends in typhoid and paratyphoid Fever.

Authors:  John A Crump; Eric D Mintz
Journal:  Clin Infect Dis       Date:  2010-01-15       Impact factor: 9.079

5.  Does ambient temperature affect foodborne disease?

Authors:  Rennie M D'Souza; Niels G Becker; Gillian Hall; Keith B A Moodie
Journal:  Epidemiology       Date:  2004-01       Impact factor: 4.822

Review 6.  Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Authors: 
Journal:  Lancet       Date:  2015-06-07       Impact factor: 202.731

7.  The influence of climate variation and change on diarrheal disease in the Pacific Islands.

Authors:  R B Singh; S Hales; N de Wet; R Raj; M Hearnden; P Weinstein
Journal:  Environ Health Perspect       Date:  2001-02       Impact factor: 9.031

8.  Meteorological factors and the incidence of mumps in Fujian Province, China, 2005-2013: Non-linear effects.

Authors:  Wenqi Hu; Yuying Li; Weixiao Han; Li Xue; Wenchao Zhang; Wei Ma; Peng Bi
Journal:  Sci Total Environ       Date:  2017-11-22       Impact factor: 7.963

9.  Modeling exposure-lag-response associations with distributed lag non-linear models.

Authors:  Antonio Gasparrini
Journal:  Stat Med       Date:  2013-09-12       Impact factor: 2.373

10.  Seasonal dynamics of typhoid and paratyphoid fever.

Authors:  Neil J Saad; Victoria D Lynch; Marina Antillón; Chongguang Yang; John A Crump; Virginia E Pitzer
Journal:  Sci Rep       Date:  2018-05-02       Impact factor: 4.379

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