Pathogen seasonality and links with weather in England and Wales: a big data time series analysis

Cherrie, Mark P. C.; Nichols, Gordon; Iacono, Gianni Lo; Sarran, Christophe; Hajat, Shakoor; Fleming, Lora E.

We were interested in how the correlation coefficients varied between the weather variables that measured the same phenomenon (e.g. min, max, mean temperature). In general, there were slight differences between the different measures of temperature. The mean difference in correlation coefficients between minimum and maximum temperature was 0.002 with standard deviation of 0.02. HMPV and Rotavirus showed the largest difference between the temperature variables (comparing min temp and max temp). HMPV recorded a 0.14 higher coefficient for maximum temperature, whereas Rotavirus recorded a 0.16 higher coefficient for minimum temperature. Similar associations with temperature were found with vapour pressure and sunshine, although they tended to be relatively weaker when taking the mean for all of the pathogens There were also similar moderate inverse correlations with ground frost, air frost and snow lying days. For Influenza A, days with lying snow had a higher correlation than the other weather variables (r = 0.32). Notable differences in correlations between pathogens and the precipitation variables (comparing days with over 10 mm of rain compared to days with over 1 mm of rain), included Plesiomonas shigelloides with a 0.19 higher correlation with days over 10 mm and RSV with a 0.15 higher correlation with days over 1 mm of rain.