Spatial model for risk prediction and sub-national prioritization to aid poliovirus eradication in Pakistan

October 11, 2017

Abstract: 

Background

Pakistan is one of only three countries where poliovirus circulation remains endemic. For the Pakistan Polio Eradication Program, identifying high risk districts is essential to target interventions and allocate limited resources.

Methods

Using a hierarchical Bayesian framework we developed a spatial Poisson hurdle model to jointly model the probability of one or more paralytic polio cases, and the number of cases that would be detected in the event of an outbreak. Rates of underimmunization, routine immunization, and population immunity, as well as seasonality and a history of cases were used to project future risk of cases.

Results

AFP surveillance in Pakistan collected data on 43,301 NPAFP cases between January 2003 and June 2016, with an average annual rate increasing from 4.3 to 11.4 NPAFP per 100,000 children under the age of 5 years from 2003 to 2016. Space–time smoothing models fit to the NPAFP vaccination dose history data indicated that zero dose RI and underimmunized rates (fewer than three doses) are highly heterogeneous across Pakistan (Figs. 1). Both zero dose RI and underimmunization rates were high in most of Punjab, Sindh, and KP provinces, and lowest in the western provinces, Balochistan and FATA.

Fig. 1

A map of smoothed estimates of zero routine immunization (RI) doses for January through June, 2016 (left) and an example of the smoothing models for observed zero RI rates for Khyber district in the Federally Administered Tribal Areas (FATA) of Pakistan from 2003 to 2016 (right)

Conclusions

The risk of poliovirus has decreased dramatically in many of the key reservoir areas in Pakistan. The results of this model have been used to prioritize sub-national areas in Pakistan to receive additional immunization activities, additional monitoring, or other special interventions.