Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2011 Oct;8(10):e1001109.
doi: 10.1371/journal.pmed.1001109. Epub 2011 Oct 18.

A statistical model of the international spread of wild poliovirus in Africa used to predict and prevent outbreaks

Affiliations

A statistical model of the international spread of wild poliovirus in Africa used to predict and prevent outbreaks

Kathleen M O'Reilly et al. PLoS Med. 2011 Oct.

Abstract

Background: Outbreaks of poliomyelitis in African countries that were previously free of wild-type poliovirus cost the Global Polio Eradication Initiative US$850 million during 2003-2009, and have limited the ability of the program to focus on endemic countries. A quantitative understanding of the factors that predict the distribution and timing of outbreaks will enable their prevention and facilitate the completion of global eradication.

Methods and findings: Children with poliomyelitis in Africa from 1 January 2003 to 31 December 2010 were identified through routine surveillance of cases of acute flaccid paralysis, and separate outbreaks associated with importation of wild-type poliovirus were defined using the genetic relatedness of these viruses in the VP1/2A region. Potential explanatory variables were examined for their association with the number, size, and duration of poliomyelitis outbreaks in 6-mo periods using multivariable regression analysis. The predictive ability of 6-mo-ahead forecasts of poliomyelitis outbreaks in each country based on the regression model was assessed. A total of 142 genetically distinct outbreaks of poliomyelitis were recorded in 25 African countries, resulting in 1-228 cases (median of two cases). The estimated number of people arriving from infected countries and <5-y childhood mortality were independently associated with the number of outbreaks. Immunisation coverage based on the reported vaccination history of children with non-polio acute flaccid paralysis was associated with the duration and size of each outbreak, as well as the number of outbreaks. Six-month-ahead forecasts of the number of outbreaks in a country or region changed over time and had a predictive ability of 82%.

Conclusions: Outbreaks of poliomyelitis resulted primarily from continued transmission in Nigeria and the poor immunisation status of populations in neighbouring countries. From 1 January 2010 to 30 June 2011, reduced transmission in Nigeria and increased incidence in reinfected countries in west and central Africa have changed the geographical risk of polio outbreaks, and will require careful immunisation planning to limit onward spread. Please see later in the article for the Editors' Summary.

PubMed Disclaimer

Conflict of interest statement

CM is a serving staff member of the World Health Organization. NG has received funding from the World Health Organization. All other authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Distribution of the size and duration of outbreaks in Africa 2003–2010.
(A) Size of outbreaks. (B) Duration of outbreaks. Where no epidemiologically linked cases have been detected in the last 6 mo the final size is reported. If cases have been recently (1 July–31 December 2010) detected, the size and duration are censored. All censored outbreaks are denoted by the blue tick marks in the Kaplan-Meier curve (B).
Figure 2
Figure 2. Distribution of the risk of poliomyelitis outbreaks in Africa.
(A) The number of poliomyelitis outbreaks reported for each country in Africa between 1 July 2004 and 31 December 2010. (B) The expected number of poliomyelitis outbreaks for each country in Africa based on the fit of the Poisson mixed effects model. (C) The temporal fit of the Poisson mixed effects model, where error bars show the 95% CIs, and the reported number of outbreaks for each 6-mo period.
Figure 3
Figure 3. Six-month-ahead predictions and comparison to the observed number of outbreaks.
(A) Predictions from 1 January 2010 to 30 June 2011 are illustrated from left to right, along with the observed number of outbreaks for the first and second halves of 2010. (B) The temporal predictions from 2007 (red lines) and the prediction intervals (dashed red lines) are illustrated. The observed number of outbreaks for each 6-mo period are overlaid (black lines). The predictive ability of the model was estimated to be 82%. Years (e.g., 2010) indicate the first half of the year (1 January–30 June); years plus 0.5 (e.g., 2010.5) indicate the second half of the year (1 July–31 December).

Similar articles

Cited by

References

    1. World Health Organization. Progress towards interruption of wild poliovirus transmission worldwide, 2009. Wkly Epidemiol Rec. 2010;85:178–184. - PubMed
    1. World Health Organization. Progress toward global eradication of poliomyelitis, 1988–1991. MMWR Morb Mortal Wkly Rep. 1993;42:486–487, 493–495. - PubMed
    1. World Health Organization. Progress toward poliomyelitis eradication—Nigeria, January 2008–July 2009. MMWR Morb Mortal Wkly Rep. 2009;58:1150–1154. - PubMed
    1. World Health Organization. Progress toward interrupting wild poliovirus circulation in countries with reestablished transmission—Africa, 2009–2010. MMWR Morb Mortal Wkly Rep. 2011;60:306–311. - PubMed
    1. World Health Organization. Poliomyelitis outbreak—Republic of the Congo, September 2010–February 2011. MMWR Morb Mortal Wkly Rep. 2011;60:312–313. - PubMed

Publication types

MeSH terms