Modelling the spread of serotype-2 vaccine derived-poliovirus outbreak in Pakistan and Afghanistan to inform outbreak control strategies in the context of the COVID-19 pandemic

Abstract

Background Since July 2019, Pakistan and Afghanistan have been facing an outbreak of serotype-2 circulating vaccine derived poliovirus (cVDPV2) in addition to continued transmission of serotype-1 wild poliovirus (WPV1) and SARS-CoV-2 in 2020. Understanding the risks of cVDPV2 transmission due to pause of global vaccination efforts and the impact of potential vaccination response strategies in the current context of COVID-19 mitigation measures is critical. Methods We developed a stochastic, geographically structured mathematical model of cVDPV2 transmission which captures both mucosal and humoral immunity separately and allows for reversion of serotype-2 oral polio vaccine (OPV2) virus to cVDPV2 following vaccine administration. The model includes geographic heterogeneities in vaccination coverage, population immunity and population movement. The model was fitted to historic cVDPV2 cases in Pakistan and Afghanistan between January 2010-April 2016 and July 2019-March 2020 using iterated particle filtering. The model was used to simulate spread of cVDPV2 infection from July 2019 to explore impact of various proposed vaccination responses on stopping transmission and risk of spread of reverted Sabin-2 under varying assumptions of impacts from COVID-19 lockdown measures on movement patterns as well as declines in vaccination coverage. Results Simulated monthly incidence of cVDPV2 from the best-fit model demonstrated general spatio-temporal alignment with observed cVDPV2 cases. The model predicted substantial spread of cVDPV2 infection, with widespread transmission through 2020 in the absence of any vaccination activities. Vaccination responses were predicted to substantially reduce transmission and case burden, with a greater impact from earlier responses and those with larger geographic scope. While the greatest risk of seeding reverted Sabin-2 was predicted in areas targeted with OPV2, subsequent spread was greatest in areas with no or delayed response. The proposed vaccination strategy demonstrated ability to stop the cVDPV2 outbreak (with low risk of reverted Sabin-2 spread) by February 2021. Conclusion Outbreak response vaccination campaigns against cVDPV2 will be challenging throughout the COVID-19 pandemic but must be implemented urgently when feasible to stop transmission of cVDPV2.

Ingraining Polio Vaccine Acceptance through Public Service Advertisements in the Digital Era: The Moderating Role of Misinformation, Disinformation, Fake News, and Religious Fatalism

“…Over the past 30 years, wild poliovirus cases have significantly waned by 99%. The reported polio cases at the inception of GPEI in 1988 were 350,000 across 125 countries [ 4 ]. These cases were reduced to 33 reported cases (of polio) in 2018.…”

Review of Poliovirus Transmission and Economic Modeling to Support Global Polio Eradication: 2020–2024

“…This section begins with a brief overview of each of the 102 studies identified by the search process summarized in Figure 1 [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 ,…”

“…The studies identified for IC for 2020–2024.25 showed its continued focus on statistical analyses of existing surveillance data and data collected as part of prospective trials or challenge studies and included a new focus area related to the development of a poliovirus direct detection method. With respect to transmission modeling, IC applied an SC model to characterize the spread of serotype-2 vaccine-derived-poliovirus outbreaks in Pakistan and Afghanistan to inform outbreak control strategies in the context of the COVID-19 pandemic [ 47 ], which built on a statistical analysis that quantified movement patterns and vaccination status in high-risk mobile populations [ 48 ].…”

Real-time prediction model of cVDPV2 outbreaks to aid outbreak response vaccination strategies

“…For one, we model observed cases rather than asymptomatic infections, which are necessarily more widespread than observed cases. One could account for this by examining risk in a longer window over which latent infections would be expected to result in an observed case, or by constructing a model that estimates latent infections [16]. However, models with latent infections are computationally intensive and typically make stronger assumptions on disease dynamics [17].…”