A resampling-based test to detect person-to-person transmission of infectious disease

TL;DR

This paper introduces a permutation-based statistical test for early detection of person-to-person transmission of infectious diseases, demonstrating its effectiveness especially with small sample sizes and broad applicability.

Contribution

The authors developed a new permutation test and its refined version for detecting disease transmission, outperforming traditional asymptotic tests in small samples.

Findings

Refined permutation test is as powerful or better than traditional tests.

Effective with small sample sizes and moderate transmissibility.

Applicable to various problems lacking asymptotic solutions.

Abstract

Early detection of person-to-person transmission of emerging infectious diseases such as avian influenza is crucial for containing pandemics. We developed a simple permutation test and its refined version for this purpose. A simulation study shows that the refined permutation test is as powerful as or outcompetes the conventional test built on asymptotic theory, especially when the sample size is small. In addition, our resampling methods can be applied to a broad range of problems where an asymptotic test is not available or fails. We also found that decent statistical power could be attained with just a small number of cases, if the disease is moderately transmissible between humans.