Factors limiting data quality in the expanded programme on immunization in low and middle-income countries: A scoping review

Harrison, Katherine; Rahimi, Nargis; Danovaro-Holliday, M. Carolina

doi:10.1016/j.vaccine.2020.02.091

Cited by 46 publications

(35 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, data used in this study are from publicly available sources such as the Global Health Observatory Data Repository and the World Bank database, and thus analyses and inference are limited to the quality of these data repositories. These sources often rely on survey datasets and other administrative sources that have known challenges in LMICs [ 120 ], and estimates may be modeled or direct estimates. However these estimates are amongst the best available globally and inferences will be meaningful, nonetheless must be interpreted with caution.…”

Section: Discussionmentioning

confidence: 99%

Non-communicable diseases among adolescents: current status, determinants, interventions and policies

et al. 2020

View full text Add to dashboard Cite

Background Addressing non-communicable disease (NCDs) is a global priority in the Sustainable Development Goals, especially for adolescents. However, existing literature on NCD burden, risk factors and determinants, and effective interventions and policies for targeting these diseases in adolescents, is limited. This study develops an evidence-based conceptual framework, and highlights pathways between risk factors and interventions to NCD development during adolescence (ages 10–19 years) and continuing into adulthood. Additionally, the epidemiologic profile of key NCD risk factors and outcomes among adolescents and preventative NCD policies/laws/legislations are examined, and a multivariable analysis is conducted to explore the determinants of NCDs among adolescents and adults. Methods We reviewed literature to develop an adolescent-specific conceptual framework for NCDs. Global data repositories were searched from Jan-July 2018 for data on NCD-related risk factors, outcomes, and policy data for 194 countries from 1990 to 2016. Disability-Adjusted Life Years were used to assess disease burden. A hierarchical modeling approach and ordinary least squares regression was used to explore the basic and underlying causes of NCD burden. Results Mental health disorders are the most common NCDs found in adolescents. Adverse behaviours and lifestyle factors, specifically smoking, alcohol and drug use, poor diet and metabolic syndrome, are key risk factors for NCD development in adolescence. Across countries, laws and policies for preventing NCD-related risk factors exist, however those targeting contraceptive use, drug harm reduction, mental health and nutrition are generally limited. Many effective interventions for NCD prevention exist but must be implemented at scale through multisectoral action utilizing diverse delivery mechanisms. Multivariable analyses showed that structural/macro, community and household factors have significant associations with NCD burden among adolescents and adults. Conclusions Multi-sectoral efforts are needed to target NCD risk factors among adolescents to mitigate disease burden and adverse outcomes in adulthood. Findings could guide policy and programming to reduce NCD burden in the sustainable development era.

show abstract

Section: Discussionmentioning

confidence: 99%

Non-communicable diseases among adolescents: current status, determinants, interventions and policies

et al. 2020

View full text Add to dashboard Cite

show abstract

“…mistakenly marking a dose as the first, second or third dose based on the child’s age at vaccination rather than on the actual dose received); (iii) errors in data aggregation (aggregation is often done manually, usually at the end of each month); and (iv) implicitly assuming that children receive all their doses at the same location, whereas this is not always the case. 22 , 38 , 39 These issues underscore the need for continued strengthening of health information systems to improve the quality of the vast amount of administrative data available. Multipronged interventions that focus on the local level where data are generated and increased use of data by individual health facilities and data aggregators have been shown to help improve data quality.…”

Section: Discussionmentioning

confidence: 99%

Subnational inequalities in diphtheria–tetanus–pertussis immunization in 24 countries in the African Region

Kirkby¹,

Bergen²,

Schlotheuber³

et al. 2021

Bull World Health Org

View full text Add to dashboard Cite

Objective To analyse subnational inequality in diphtheria–tetanus–pertussis (DTP) immunization dropout in 24 African countries using administrative data on receipt of the first and third vaccine doses (DTP1 and DTP3, respectively) collected by the Joint Reporting Process of the World Health Organization and the United Nations Children’s Fund. Methods Districts in each country were grouped into quintiles according to the proportion of children who dropped out between DTP1 and DTP3 (i.e. the dropout rate). We used six summary measures to quantify inequalities in dropout rates between districts and compared rates with national dropout rates and DTP1 and DTP3 immunization coverage. Findings The median dropout rate across countries was 2.4% in quintiles with the lowest rate and 14.6% in quintiles with the highest rate. In eight countries, the difference between the highest and lowest quintiles was 14.9 percentage points or more. In most countries, underperforming districts in the quintile with the highest rate tended to lag disproportionately behind the others. This divergence was not evident from looking only at national dropout rates. Countries with the largest inequalities in absolute subnational dropout rate tended to have lower estimated national DTP1 and DTP3 immunization coverage. Conclusion There were marked inequalities in DTP immunization dropout rates between districts in most countries studied. Monitoring dropout at the subnational level could help guide immunization interventions that address inequalities in underserved areas, thereby improving overall DTP3 coverage. The quality of administrative data should be improved to ensure accurate and timely assessment of geographical inequalities in immunization.

show abstract

“…The machine learning approach offers several policy‐relevant advantages in the analysis of VH using area‐level indicators. First, it allows us to overcome the problem of incomplete data on immunization coverage which represents a key issue particularly in low‐ and middle‐income countries (Harrison et al., 2020). Second, it allows us to predict areas at high VH risk relying on coverage data from previous immunization campaigns.…”

Section: Introductionmentioning

confidence: 99%

Predicting vaccine hesitancy from area‐level indicators: A machine learning approach

2021

View full text Add to dashboard Cite

Vaccine hesitancy (VH) might represent a serious threat to the next COVID‐19 mass immunization campaign. We use machine learning algorithms to predict communities at a high risk of VH relying on area‐level indicators easily available to policymakers. We illustrate our approach on data from child immunization campaigns for seven nonmandatory vaccines carried out in 6062 Italian municipalities in 2016. A battery of machine learning models is compared in terms of area under the receiver operating characteristics curve. We find that the Random Forest algorithm best predicts areas with a high risk of VH improving the unpredictable baseline level by 24% in terms of accuracy. Among the area‐level indicators, the proportion of waste recycling and the employment rate are found to be the most powerful predictors of high VH. This can support policymakers to target area‐level provaccine awareness campaigns.

show abstract

Factors limiting data quality in the expanded programme on immunization in low and middle-income countries: A scoping review

Cited by 46 publications

References 34 publications

Non-communicable diseases among adolescents: current status, determinants, interventions and policies

Non-communicable diseases among adolescents: current status, determinants, interventions and policies

Subnational inequalities in diphtheria–tetanus–pertussis immunization in 24 countries in the African Region

Predicting vaccine hesitancy from area‐level indicators: A machine learning approach

Contact Info

Product

Resources

About