Seasonality and the effects of weather on Campylobacter infections

被引:40
作者
Djennad, Abdelmajid [1 ]
Lo Iacono, Giovanni [2 ]
Sarran, Christophe [3 ]
Lane, Christopher [4 ]
Elson, Richard [5 ,6 ]
Hoeser, Christoph [7 ]
Lake, Iain R. [8 ]
Colon-Gonzalez, Felipe J. [8 ]
Kovats, Sari [9 ]
Semenza, Jan C. [10 ]
Bailey, Trevor C. [11 ]
Kessel, Anthony [1 ,9 ]
Fleming, Lora E. [11 ]
Nichols, Gordon L. [1 ,11 ,12 ]
机构
[1] Publ Hlth England, Natl Infect Serv, Stat Modelling & Econ Dept, 61 Colindale Ave, London NW9 5EQ, England
[2] Univ Surrey, Sch Vet Med, Guildford, Surrey, England
[3] Met Off, Exeter, Devon, England
[4] World Hlth Org, Geneva, Switzerland
[5] Publ Hlth England, Natl Infect Serv, London, England
[6] NIHR Hlth Protect Res Unit Gastrointestinal Infec, London, England
[7] Univ Bonn, GeoHlth Ctr, Inst Hyg & Publ Hlth, Bonn, Germany
[8] Univ East Anglia, Norwich, Norfolk, England
[9] London Sch Hyg & Trop Med, London, England
[10] European Ctr Dis Prevent & Control, Stockholm, Sweden
[11] Univ Exeter, Exeter, Devon, England
[12] Univ Thessaly, Larisa, Thessaly, Greece
基金
英国自然环境研究理事会; 英国医学研究理事会;
关键词
Campylobacter; Time series; Temperature; Rainfall; Climate change; Environmental health; TIME-SERIES ANALYSIS; CLIMATE-CHANGE; NEW-ZEALAND; TEMPERATURE; ENGLAND; FLOCKS; FLIES; RISK;
D O I
10.1186/s12879-019-3840-7
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
BackgroundCampylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood.MethodsTo investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses.ResultsThe increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas.ConclusionsThe association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored.
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页数:10
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