Routine immunization in Pakistan: comparison of multiple data sources and identification of factors associated with vaccination.

Background: Within Pakistan, estimates of vaccination coverage with the pentavalent vaccine, oral polio vaccine (OPV) and measles vaccine (MV) in 2011 were reported to be 74%, 75% and 53%, respectively. These national estimates may mask regional variation. The reasons for this variation have not been explored. Methods: Data from the Multiple Indicator Cluster Surveys (MICS) for Balochistan and Punjab (2010-2011) are analysed to examine factors associated with receiving three or more doses of the pentavalent vaccine and one or more MVs using regression modelling. Pentavalent and OPV estimates from the MICS were compared to vaccine dose histories from surveillance for acute flaccid paralysis (AFP; poliomyelitis) to ascertain agreement. Results: Adjusted coverage of children 12-23 months of age were estimated to be 16.0%, 75.5% and 34.2% in Balochistan and 58.0%, 87.7% and 72.6% in Punjab for the pentavalent vaccine, OPV and MV, respectively. Maternal education, healthcare utilization and wealth were associated with receiving the pentavalent vaccine and the MV. There was a strong correlation of district estimates of vaccination coverage between AFP and MICS data, but AFP estimates of pentavalent coverage in Punjab were biased toward higher values. Conclusions: National estimates mask variation and estimates from individual surveys should be considered alongside other estimates. The development of strategies targeted towards poorly educated parents within low-wealth quintiles that may not typically access healthcare could improve vaccination rates

Population sensitivity of acute flaccid paralysis and environmental surveillance for serotype 1 poliovirus in Pakistan: an observational study.

BACKGROUND: To support poliomyelitis eradication in Pakistan, environmental surveillance (ES) of wastewater has been expanded alongside surveillance for acute flaccid paralysis (AFP). ES is a relatively new method of surveillance, and the population sensitivity of detecting poliovirus within endemic settings requires estimation. METHODS: Data for wild serotype 1 poliovirus from AFP and ES from January 2011 to September 2015 from 14 districts in Pakistan were analysed using a multi-state model framework. This framework was used to estimate the sensitivity of poliovirus detection from each surveillance source and parameters such as the duration of infection within a community. RESULTS: The location and timing of poliomyelitis cases showed spatial and temporal variability. The sensitivity of AFP surveillance to detect serotype 1 poliovirus infection in a district and its neighbours per month was on average 30.0% (95% CI 24.8-35.8) and increased with the incidence of poliomyelitis cases. The average population sensitivity of a single environmental sample was 59.4% (95% CI 55.4-63.0), with significant variation in site-specific estimates (median varied from 33.3-79.2%). The combined population sensitivity of environmental and AFP surveillance in a given month was on average 98.1% (95% CI 97.2-98.7), assuming four samples per month for each site. CONCLUSIONS: ES can be a highly sensitive supplement to AFP surveillance in areas with converging sewage systems. As ES for poliovirus is expanded, it will be important to identify factors associated with variation in site sensitivity, leading to improved site selection and surveillance system performance

Population Immunity against Serotype-2 Poliomyelitis Leading up to the Global Withdrawal of the Oral Poliovirus Vaccine: Spatio-temporal Modelling of Surveillance Data.

BACKGROUND: Global withdrawal of serotype-2 oral poliovirus vaccine (OPV2) took place in April 2016. This marked a milestone in global polio eradication and was a public health intervention of unprecedented scale, affecting 155 countries. Achieving high levels of serotype-2 population immunity before OPV2 withdrawal was critical to avoid subsequent outbreaks of serotype-2 vaccine-derived polioviruses (VDPV2s). METHODS AND FINDINGS: In August 2015, we estimated vaccine-induced population immunity against serotype-2 poliomyelitis for 1 January 2004-30 June 2015 and produced forecasts for April 2016 by district in Nigeria and Pakistan. Population immunity was estimated from the vaccination histories of children 70% population immunity among children <36 mo old. Districts with lower immunity were clustered in northeastern Nigeria and northwestern Pakistan. The accuracy of immunity estimates was limited by the small numbers of non-polio AFP cases in some districts, which was reflected by large uncertainty intervals. Forecasted improvements in immunity for April 2016 were robust to the uncertainty in estimates of baseline immunity (January-June 2015), vaccine coverage, and vaccine efficacy. CONCLUSIONS: Immunity against serotype-2 poliomyelitis was forecasted to improve in April 2016 compared to the first half of 2015 in Nigeria and Pakistan. These analyses informed the endorsement of OPV2 withdrawal in April 2016 by the WHO Strategic Advisory Group of Experts on Immunization

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Effect of Inactivated Poliovirus Vaccine Campaigns, Pakistan, 2014–2017

Pakistan began using inactivated poliovirus vaccine alongside oral vaccine in mass campaigns to accelerate eradication of wild-type poliovirus in 2014. Using case-based and environmental surveillance data for January 2014–October 2017, we found that these campaigns reduced wild-type poliovirus detection more than campaigns that used only oral vaccine

Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis

Background: Pakistan currently provides a substantial challenge to global polio eradication, having contributed to 73% of reported poliomyelitis in 2015 and 54% in 2016. A better understanding of the risk factors and movement patterns that contribute to poliovirus transmission across Pakistan would support evidence-based planning for mass vaccination campaigns. Methods and findings We fit mixed-effects logistic regression models to routine surveillance data recording the presence of poliomyelitis associated with wild-type 1 poliovirus in districts of Pakistan over 6-month intervals between 2010 to 2016. To accurately capture the force of infection (FOI) between districts, we compared 6 models of population movement (adjacency, gravity, radiation, radiation based on population density, radiation based on travel times, and mobile-phone based). We used the best-fitting model (based on the Akaike Information Criterion [AIC]) to produce 6-month forecasts of poliomyelitis incidence. The odds of observing poliomyelitis decreased with improved routine or supplementary (campaign) immunisation coverage (multivariable odds ratio [OR] = 0.75, 95% confidence interval [CI] 0.67–0.84; and OR = 0.75, 95% CI 0.66–0.85, respectively, for each 10% increase in coverage) and increased with a higher rate of reporting non-polio acute flaccid paralysis (AFP) (OR = 1.13, 95% CI 1.02–1.26 for a 1-unit increase in non-polio AFP per 100,000 persons aged <15 years). Estimated movement of poliovirus-infected individuals was associated with the incidence of poliomyelitis, with the radiation model of movement providing the best fit to the data. Six-month forecasts of poliomyelitis incidence by district for 2013–2016 showed good predictive ability (area under the curve range: 0.76–0.98). However, although the best-fitting movement model (radiation) was a significant determinant of poliomyelitis incidence, it did not improve the predictive ability of the multivariable model. Overall, in Pakistan the risk of polio cases was predicted to reduce between July–December 2016 and January–June 2017. The accuracy of the model may be limited by the small number of AFP cases in some districts. Conclusions: Spatiotemporal variation in immunization performance and population movement patterns are important determinants of historical poliomyelitis incidence in Pakistan; however, movement dynamics were less influential in predicting future cases, at a time when the polio map is shrinking. Results from the regression models we present are being used to help plan vaccination campaigns and transit vaccination strategies in Pakistan

Risk factors associated with the incidence of wild poliovirus type 1 (WPV1) cases based on the best-fitting multivariable mixed-effects lagged regression model for January–June 2010 through July–December 2016.

<p>The odds ratio (OR) and the 95% confidence interval (CI) for routine immunization and supplementary immunization activity (SIA) coverage are for an absolute 10% increase in these variables and a 1-unit increase for all other variables. Non-polio acute flaccid paralysis (AFP) rate is per 100,000 persons aged <15 years.</p

Spatio-temporal correlation between serotype-2 population immunity and the occurrence of cVDPV2 cases.

<p>Country estimates of serotype-2 population immunity and monthly number of cases of cVDPV2 in (A) Nigeria and (B) Pakistan. Proportion of districts (with 95% confidence intervals) reporting at least one cVDPV2 case within a 6-mo period among all districts/6-mo periods by intervals of 10% of estimated serotype-2 population immunity for (C) Nigeria and (D) Pakistan.</p

Reported and model-based estimates and forecasts of wild poliovirus type 1 (WPV1) cases between July 2013 and December 2016.

<p>(A) Observed WPV1 cases. (B) Estimated probability of reporting at least 1 WPV1 case based on the best-fit regression model including all available data (January 2010–December 2016). Complete figures with earlier time periods included in Figures K and L in <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002323#pmed.1002323.s002" target="_blank">S1 Text</a>. (C) Predicted probability of reporting at least 1 WPV1 case for the same periods using data up to the end of the preceding 6-month period. AUC, area under the curve.</p

Spatial distribution and trends in the incidence of poliomyelitis over time in different regions of Pakistan.

<p>In (A), the spatial distribution of wild poliovirus type 1 (WPV1)-associated poliomyelitis cases in districts of Pakistan between January 2010 and December 2016 is shown (red dots). (B) Monthly confirmed WPV1-associated poliomyelitis cases in Pakistan reported between January 2010 and December 2016 are shown (bars). The same data are shown together with estimated serotype 1 vaccine-induced population immunity among children <36 months old (lines) for (C) Punjab, Sindh, Islamabad, Azad Jammu and Kashmir (AJK), and Gilgit-Baltistan, (D) Khyber Pakhtunkhwa, (E) Balochistan, and (F) the Federally Administered Tribal Area (FATA).</p