Seasonality and the effects of weather on Campylobacter infections

• Published in: BMC infectious diseases 2019-03, Vol.19 (1), p.255-10, Article 255
• Main Authors: Djennad, Abdelmajid, Lo Iacono, Giovanni, Sarran, Christophe, Lane, Christopher, Elson, Richard, Höser, Christoph, Lake, Iain R, Colón-González, Felipe J, Kovats, Sari, Semenza, Jan C, Bailey, Trevor C, Kessel, Anthony, Fleming, Lora E, Nichols, Gordon L
• Format: Article
• Language: English
• Subjects: Animals; Biosecurity; Campylobacter; Campylobacter Infections - epidemiology; Campylobacteriosis; Case studies; Chickens; Climate; Climate change; Cluster analysis; Clustering; Communicable diseases; Contamination; Disease; England - epidemiology; Environmental health; Epidemiology; Food contamination; Global temperature changes; Humans; Incidence; Infection; Infections; Infectious diseases; Insects; Laboratories; Public health; Rain; Rainfall; Risk factors; Rural areas; Salmonella; Seasonal variations; Seasons; Temperature; Temperature effects; Time series; Time series analysis; Wales - epidemiology; Wavelet analysis; Weather
• ISSN: 1471-2334; 1471-2334
• DOI: 10.1186/s12879-019-3840-7

Campylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood. To 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 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses. The 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. The 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.