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© 1990 Oxford University Press

research-article

The Behaviour of Common Measures of Association Used to Assess a Vaccination Programme under Complex Disease Transmission Patterns—A Computer Simulation Study of Malaria Vaccines

CLAUDIO J STRUCHINER*, MARY ELIZABETH HALLORAN**,, JAMES M ROBINS{dagger} and ANDREW SPIELMAN{ddagger}

*Escola Nactional de Saúde Pública Fundaçao Oswaldo Cruz Rio de Janeiro, RJ 21041, Brazil.
**Department of Population Sciences, Harvard School of Public Health 605 Huntington Avenue, Boston, Massachussetts, 02115, USA.
{dagger}Occupational Health Program and Biostatistics Department
{ddagger}Department of Tropical Public Health, Harvard School of Public Health

Correspondence and reprint requests to: M E Halloran, Department of Epidemiology and Biostatistics, Emory University, 1599 Clifton Road NE, Atlanta, Georgia 30329, USA.

Struchiner C J (Escola Nacional de Saú de Pú blica, Fundaçao Oswaldo Cruz, Rio de Janeiro, RJ 21041, Brazil), Halloran M E, Robins J M and Spielman A. The behaviour of common measures of association used to assess a vaccination programme under complex disease transmission patterns—A computer simulation study of malaria vaccines. International Journal of Epidemiology 1990, 19: 187–196

Case-control studies have been evoked1.3 as important alternatives to randomized clinical trials in the evaluation of infectious disease interventions. Using computer simulations, we compare the behaviour of common measures of association derived from case-control studies in the context of a malaria vaccine programme administered under complex transmission conditions. Several simplifying assumptions of previous workers2.4 have been relaxed and the simulated conditions are endemic rather than epidemic. The common estimators of association used in case-control studies remain unbiased only in limited circumstances.

The term dependent happenings, first defined by Ross in 1916, 5 is resurrected. Since the number of people becoming infected is dependent on the number of people already infected, control programmes in infectious diseases produce direct as well as indirect effects. Three different study designs with different pairs of comparison populations are defined. The choice of comparison population can be used to differentiate direct from indirect effects. In order to clarify the direct effects of a vaccination programme the comparison groups must be subjected to identical transmission intensities. In contrast, the referent group must remain unaffected by consequences of the intervention to determine indirect effects.

Revised 1 April 1989


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