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Routine data used to study infectious diseases may contain biases which obscure trends. A 16-year series (up to 1968) of routine laboratory data was used to study patterns of incidence of infective gastroenteritis for which no laboratory diagnosis could be made. An artificial pattern was detected. This arose because GPs tended to refer a greater proportion of their patients during dysentery epidemics. Multiple regression analysis was used to separate out this effect so that the underlying trends could be observed. The seasonal pattern of undiagnosed cases showed an autumn peak. There were also early-winter epidemics of disease with little or no excretion of red blood or pus cells in the diagnostic faeces specimen. Some of the winter communicable disease among older children and adults appeared to be associated with signs of a temporary fat malabsorption in pre-school age cases. Undiagnosed cases in older children and adults were not related to the E. coli serotypes causing disease in infants during this period. The statistical method applied increased the usefulness of these routine data. Although this series of laboratory records is now more than a decade old the results of the analysis can be compared with new observations as more is learned about the epidemiology of previously unrecognized pathogens, especially rotaviruses.

Monitoring infectious diseases using routine microbiology data II. An example of regression analysis used to study infectious gastroenteritis