The TNC-based VE estimate corrects for confounding bias when the confounder's effects on the probabilities of rotavirus and non-rotavirus related hospitalizations are equal. If this condition is not met, then the estimated VE may be substantially biased. The bias is more severe in low-income countries, where VE is known to be lower. Under our model, differences in PSMC between vaccinated and unvaccinated children do not result in selection bias when the TNC study design is used.
Rotavirus is the leading cause of severe diarrhea among children worldwide, and vaccines can reduce morbidity and mortality by 50-98%. The test-negative control (TNC) study design is increasingly used for evaluating the effectiveness of vaccines against rotavirus and other vaccine-preventable diseases. In this study design, symptomatic patients who seek medical care are tested for the pathogen of interest. Those who test positive (negative) are classified as cases (controls).
We use a probability model to evaluate the bias of estimates of rotavirus vaccine effectiveness (VE) against rotavirus diarrhea resulting in hospitalization in the presence of possible confounding and selection biases due to differences in the propensity of seeking medical care (PSMC) between vaccinated and unvaccinated children.
In practice, one can expect the association of PSMC (or other potential confounders) with the probabilities of rotavirus and non-rotavirus related hospitalization to be similar, in which case the confounding effects will only result in small bias in the VE estimate from TNC studies. The results of this work, along with those of our previous paper, confirm the TNC design can be expected to provide reliable estimates of rotavirus VE in both high- and low-income countries.