Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-25T07:15:52.119Z Has data issue: false hasContentIssue false

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

Published online by Cambridge University Press:  25 March 2010

Hilary E. Tillett
Affiliation:
Communicable Disease Surveillance Centre, Public Health Laboratory Service, 61 Colindale Avenue, London NW9 5EQ
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

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 rota-viruses.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1981

References

REFERENCES

Cliffford, R. E., Smith, J. W. G., Tillett, H. E. & Wherry, P. J. (1977). Excess mortality associated with influenza in England and Wales. International Journal of Epidemiology 6, 115.CrossRefGoogle Scholar
Daniel, C. & Wood, F. S. (1971). Fitting Equations to Data. New York: Wiley-Interscience.Google Scholar
Dixon, W. J. (1973). Biomedical Computer Programs. Berkeley: University of California Press.Google Scholar
Draper, N. R. & Smith, H. (1966). Applied Regression Analysis. New York: Wiley-Interscience.Google Scholar
Flewett, T. H. (1976). Implications of recent virological researches. CIBA Foundation Symposium 42, 237.Google Scholar
Hamilton, J. R. (1980). Infectious diarrhoea: clinical implications of recent research. Canadian Medical Association Journal 122, 29.Google Scholar
Karmali, M. A. & Fleming, P. C. (1979). Campylobacter enteritis. Canadian Medical Association Journal 120, 1525.Google ScholarPubMed
Thomas, M. E. M. (1952). Epidemic abdominal colic associated with steatorrhoea. British Medical Journal i, 691.CrossRefGoogle Scholar
Thomas, M. E. M. & Tillett, H. E. (1975). Diarrhoea in general practice: a sixteen-year report of investigations in a microbiology laboratory, with epidemiological assessment Journal of Hygiene 74, 183.Google Scholar
Tillett, H. E. (1977). Ph.D. thesis. University of London.Google Scholar
Tillett, H. E., Smith, J. W. G. & Clifford, R. E. (1980). Excess morbidity and mortality associated with influenza in England and Wales. Lancet i, 793.CrossRefGoogle Scholar
Tillett, H. E. & Thomas, M. E. M. (1974). Culture of the faeces in the diagnosis of Sonne dysentery: a statistical method for estimating the true isolation rate. International Journal of Epidemiology 3, 177.CrossRefGoogle ScholarPubMed
Tillett, H. E. & Thomas, M. E. M. (1981). Monitoring infectious diseases using routine microbiology data. I. Study of gastroenteritis in an urban area. Journal of Hygiene 86, 49.CrossRefGoogle Scholar