A formal representation of the WHO and UNICEF estimates of national immunization coverage: a computational logic approach (original) (raw)
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arXiv (Cornell University), 2022
Estimates of national immunization coverage are crucial for guiding policy and decision-making in national immunization programs and setting the global immunization agenda. WHO and UNICEF estimates of national immunization coverage (WUENIC) are produced annually for various vaccine-dose combinations and all WHO Member States using information from multiple data sources and a deterministic computational logic approach. This approach, however, is incapable of characterizing the uncertainties inherent in coverage measurement and estimation. It also provides no statistically principled way of exploiting and accounting for the interdependence in immunization coverage data collected for multiple vaccines, countries and time points. Here, we develop Bayesian hierarchical modeling approaches for producing accurate estimates of national immunization coverage and their associated uncertainties. We propose and explore two candidate models: a balanced data
Implementation of an Immunisation Project for the Refugees Using the Logic Model
Malaysian Journal of Public Health Medicine, 2020
Refugees worldwide have been a challenge to many countries. Threats of preventable immunisable diseases amongst children that disrupt the herd immunity have been a concern as many countries lack a structured national policy to administer full vaccines to these refugees. Full immunisation coverage not only protected the refugees but also safeguarded the children of the home country. We designed a collaborative university-based community service partnership with UNHCR and International-Organisation-for-Migration, implemented a practice-integrated immunisation service initiative with the local community. This paper described the implementation process of an immunisation project for the refugees using the evaluative Logic Model. This model diagrammatically shows the relationships between the program's objectives, program activities, process indicators, outcomes, and resources used. It applies to program planning, operation, evaluation and address questions for decision making. The a...
KENDRICK: A Domain Specific Language and platform for mathematical epidemiological modelling
The 2015 IEEE RIVF International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for Future (RIVF), 2015
Mathematical modelling of infectious diseases often uses simulation models in order to explore transmission mechanisms and to plan potential management strategies to control the epidemics. However, bridging the gap between the conceptual model of epidemiology and its simulation on computer can lead to some issues related to the lack of expressiveness of implemented models and their reusability and adaptability to new circumstances due to detail computer instructions in General-purpose Programming Languages (GPLs). In this paper, we propose to develop a Domain Specific Language (DSL) for expressively specifying mathematical models of epidemiology and to construct a flexible simulation environment for investigating them. We then use our proposed approach to experiment the measles model in different epidemiological aspects. Our platform is also validated through statistical comparisons between time series generated and theoretical expectations, consequently keeping the link with literature on mathematical epidemiology.
BMC Public Health, 2017
Background: After the re-introduction of poliovirus to Syria in 2013, Lebanon was considered at high transmission risk due to its proximity to Syria and the high number of Syrian refugees. However, after a large-scale national immunization initiative, Lebanon was able to prevent a potential outbreak of polio among nationals and refugees. In this work, we used a computational individual-simulation model to assess the risk of poliovirus threat to Lebanon prior and after the immunization campaign and to quantitatively assess the healthcare impact of the campaign and the required standards that need to be maintained nationally to prevent a future outbreak. Methods: Acute poliomyelitis surveillance in Lebanon was along with the design and coverage rate of the recent national polio immunization campaign were reviewed from the records of the Lebanese Ministry of Public Health. Lebanese population demographics including Syrian and Palestinian refugees were reviewed to design individualbased models that predicts the consequences of polio spread to Lebanon and evaluate the outcome of immunization campaigns. The model takes into account geographic, demographic and health-related features. Results: Our simulations confirmed the high risk of polio outbreaks in Lebanon within 10 days of case introduction prior to the immunization campaign, and showed that the current immunization campaign significantly reduced the speed of the infection in the event poliomyelitis cases enter the country. A minimum of 90% national immunization coverage was found to be required to prevent exponential propagation of potential transmission. Conclusions: Both surveillance and immunization efforts should be maintained at high standards in Lebanon and other countries in the area to detect and limit any potential outbreak. The use of computational population simulation models can provide a quantitative approach to assess the impact of immunization campaigns and the burden of infectious diseases even in the context of population migration.
PLOS ONE, 2019
Background A common means of vaccination coverage measurement is the administrative method, done by dividing the aggregated number of doses administered over a set period (numerator) by the target population (denominator). To assess the quality of national target populations, we defined nine potential denominator data inconsistencies or flags that would warrant further exploration and examination of data reported by Member States to the World Health Organization (WHO) and UNICEF between 2000 and 2016. Methods and findings We used the denominator reported to calculate national coverage for BCG, a tuberculosis vaccine, and for the third dose of diphtheria-tetanus-pertussis-containing (DTP3) vaccines, usually live births (LB) and surviving infants (SI), respectively. Out of 2,565 possible reporting events (data points for countries using administrative coverage with the vaccine in the schedule and year) for BCG and 2,939 possible reporting events for DTP3, 194 and 274 reporting events were missing, respectively. Reported coverage exceeding 100% was seen in 11% of all reporting events for BCG and in 6% for DTP3. Of all year-to-year percent differences in reported denominators, 12% and 11% exceeded 10% for reported LB and SI, respectively. The implied infant mortality rate, based on the country's reported LB and SI, would be negative in 9% of all reporting events i.e., the country reported more SI than LB for the same year. Overall, reported LB and SI tended to be lower than the UN Population Division 2017 estimates, which would lead to overestimation of coverage, but this difference seems to be decreasing over time. Other inconsistencies were identified using the nine proposed criteria.
Stochastic Environmental Research and Risk Assessment, 2007
Emerging infectious diseases continue to place a strain on the welfare of the population by decreasing the population's general health and increasing the burden on public health infrastructure. This paper addresses these issues through the development of a computational framework for modeling and simulating infectious disease outbreaks in a specific geographic region facilitating the quantification of public health policy decisions. Effectively modeling and simulating past epidemics to project current or future disease outbreaks will lead to improved control and intervention policies and disaster preparedness. In this paper, we introduce a computational framework that brings together spatio-temporal geography and population demographics with specific disease pathology in a novel simulation paradigm termed, global stochastic field simulation (GSFS). The primary aim of this simulation paradigm is to facilitate intelligent what-if-analysis in the event of health crisis, such as an influenza pandemic. The dynamics of any epidemic are intrinsically related to a region's spatio-temporal characteristics and demographic composition and as such, must be considered when developing infectious disease control and intervention strategies. Similarly, comparison of past and current epidemics must include demographic changes into any effective public health policy for control and intervention strategies. GSFS is a hybrid approach to modeling, implicitly combining agent-based modeling with the cellular automata paradigm. Specifically, GSFS is a computational framework that will facilitate the effective identification of risk groups in the population and determine adequate points of control, leading to more effective surveillance and control of infectious diseases epidemics. The analysis of past disease outbreaks in a given population and the projection of current or future epidemics constitutes a significant challenge to Public Health. The corresponding design of computational models and the simulation that facilitates epidemiologists' understanding of the manifestation of diseases represents a challenge to computer and mathematical sciences.
2021
Immunization coverage is a traditional key performance indicator that enables stakeholders to monitor child health, investigate gaps, and take remedial actions. It is continuously challenged by validity due to the neglect of unstructured data and process indicators that track small changes/milestones. While empirical evidence indicates digitalized immunization systems establish coverage from structured data, renowned administrative and household survey estimates are often inaccurate/untimely. Government instituted awareness, accessibility, and results-based performance approaches, but stakeholders are challenged by accurate monitoring of performance against Global Vaccination Action Plan coverage targets. This heightens inappropriate strategy implementation leading to persistent low coverage and declining trends. There is scanty literature substantiating the essence of comprehensive immunization indicators in monitoring evidence-based and timely interventions. For this reason, healt...
The World Health Organization and global health estimates: improving collaboration and capacity
BMC Medicine, 2015
Global, regional, and country statistics on population and health indicators are important for assessing development and health progress and for guiding resource allocation; however, data are often lacking, especially in low-and middle-income countries. To fill the gaps, statistical modelling is frequently used to produce comparable health statistics across countries that can be combined to produce regional and global statistics. The World Health Organization (WHO), in collaboration with other United Nations agencies and academic experts, regularly updates estimates for key indicators and involves its Member States in the process. Academic institutions also publish estimates independent from the WHO using different methods. The use of sophisticated statistical estimation methods to fill missing values for countries can reduce the pressures on governments and development agencies to improve information systems. Efforts to improve estimates must be accompanied by concerted attempts to address data gaps, common standards for documentation, sharing of data and methods, and regular interaction and collaboration among all groups involved.
Logic Model Early Stage Evaluation of a European Public Health Data Analytic Framework
2019
The multi-national MIDAS (Meaningful Integration of Data Analytics and Services) project is developing a big data platform to facilitate utilisation of a wide range of health and social care data to enable integration of heterogeneous data sources, providing analytics, forecasting tools and bespoke visualisations of actionable epidemiological data. An evaluation framework starting with a logic model and semi-structured interviews using the principles of realist evaluation was developed working with end users and software developers. Parallel case studies were used to address the requirements of stakeholders at critical time points during the project. The objective was to ensure IT systems development is in line with end user requirements. Overall, the early stage interviews findings indicated the logic model is an effective framework for the evaluation of the project.