# Sub-national modelling of surveillance sensitivity to inform declaration of disease elimination: A retrospective validation against the elimination of wild poliovirus in Nigeria

## TL;DR

This study develops a statistical model to determine when a region can be declared free of polio based on surveillance data, validated using Nigeria's experience.

## Contribution

A novel statistical framework for estimating the probability of polio elimination using time-varying surveillance sensitivity.

## Key findings

- The model estimated an 85% probability of polio elimination in Nigeria after 23 months without detection in 2014–2016.
- By 2020, the probability of elimination rose to 98%, aligning with official declarations.
- The framework accurately reflected known polio status, supporting its use for future eradication decisions.

## Abstract

A fundamental question in the global commitment to polio eradication is how long a period of absence would be consistent with regional elimination, and the safe withdrawal of the oral polio vaccine is contingent on the answer. We present a statistical framework to model the time-varying sensitivity of two key components of polio surveillance - environmental sampling and clinical cases of acute flaccid paralysis - for detecting infection on a monthly basis at the local government authority level. We use this to estimate the probability of freedom from infection (FFI) at a critical prevalence level that is consistent with interruption of transmission, given the absence of virus in collected samples. We validated this framework against two periods of poliovirus absence in Nigeria (2014–2016 and 2016–2020). Our model highlights substantial heterogeneity in surveillance sensitivity over time and space and, given this, concluded an 85% probability (95% uncertainty interval: 77.1-90.0%) of the country being free from WPV1 infection after 23 months without detection from July 2014. Detection of WPV1 in July 2016 demonstrated that circulation had indeed persisted during this time. In contrast, we conclude a probability of 98% (97.5-98.5%) by the time elimination of the serotype was officially declared in 2020. The inferred probability of FFI during both time periods was found to be consistent with the retrospectively known status of regional elimination. This supports the validity of applying this framework prospectively to inform the certification of wild poliovirus elimination from remaining endemic regions, and to determine the resolution of cVDPV2 outbreaks.

This study addresses a critical question in global polio eradication: how long must poliovirus be absent before a region can be considered free from infection and the oral polio vaccine can be safely withdrawn? We developed a statistical model to assess the effectiveness of two main surveillance methods—environmental sampling and monitoring of clinical cases—for detecting poliovirus at a local level each month. Applying this model to data from Nigeria, we estimated how confident we could be that the virus was eliminated, given two periods without detection between 2014 and 2020. Our findings revealed that, by mid-2016 after 23 months with no poliovirus found, there was an 85% chance infection had fallen to elimination levels—but subsequent detection of further cases showed that actual virus circulation had persisted. By the time of the official declaration of elimination in 2020, this probability was 98%. Comparing these figures to what was later known about the presence of polio confirmed our approach’s accuracy. This framework can help policymakers decide when a region can be considered polio-free and guide steps to end vaccine-derived outbreaks, moving us closer to a polio-free world.