Estimating Latent Demand of Shared Mobility through Censored Gaussian Processes

Transport demand is highly dependent on supply, especially for shared transport services where availability is often limited. As observed demand cannot be higher than available supply, historical transport data typically represents a biased, or censored, version of the true underlying demand pattern. Without explicitly accounting for this inherent distinction, predictive models of demand would necessarily represent a biased version of true demand, thus less effectively predicting the needs of service users. To counter this problem, we propose a general method for censorship-aware demand modeling, for which we devise a censored likelihood function. We apply this method to the task of shared mobility demand prediction by incorporating the censored likelihood within a Gaussian Process model, which can flexibly approximate arbitrary functional forms. Experiments on artificial and real-world datasets show how taking into account the limiting effect of supply on demand is essential in the process of obtaining an unbiased predictive model of user demand behavior.Comment: 21 pages, 10 figure

Timeliness of Routine Childhood Vaccination in The Gambia: Examining the Burden, Spatial Pattern, Determinants and the Impact of COVID-19 Pandemic

The success of immunisation programmes is traditionally evaluated by measuring vaccination coverage rates, which assumes uptake, but overlooks if vaccine doses are delivered within the recommended and accepted timeframes. The timeliness of routine childhood vaccination shapes childhood vaccine-preventable diseases (VPDs) risk, thus, is an important public health metric. To achieve the goals of the Immunisation Agenda 2030, countries must also ensure that all children receive vaccination in a timely, age-appropriate manner. While studies on the timeliness of childhood vaccination have gained traction in low-and middle- income countries (LMICs), many of them have key measurement and methodological gaps that limit their utility and comparability. These studies generated estimates of timeliness at the national or regional level, masking significant within and between country heterogeneities that hinders the identification of hotspots that could benefit from targeted interventions. Existing research have rarely explored the specific impact of supply-side determinants on vaccination timeliness, despite their known influence on the uptake of childhood vaccination. This PhD investigated the burden and spatial pattern of untimely childhood vaccinations in The Gambia, and examined the demand and supply-side determinants of timely vaccination. It also examined the impact of the COVID-19 pandemic on the timeliness of childhood vaccination in The Gambia. The first objective of the PhD was to determine the methodological and measurement gaps in assessing vaccination timeliness in LMICs through a scoping review of existing literature. The review relied on the guidance framework for scoping reviews described by the Joanna Briggs Institute. The second objective leveraged the latest available nationally representative Demographic and Health Survey (DHS) data to investigate all dimensions of childhood vaccination timeliness, analysing outcomes across two birth cohorts in The Gambia. The second objective also identified the hotspots of untimely routine vaccination by leveraging a well validated fully Bayesian geostatistical modelling approach and generated high-resolution maps depicting the prevalence of untimely childhood vaccination in The Gambia. Additionally, this analysis identified specific districts with a combination of high estimated prevalence and a substantial number of affected infants. The third objective of the PhD examined the impact of the COVID-19 pandemic on vaccination coverage and timeliness in The Gambia. This analysis leveraged a binomial interrupted time-series regression model and monthly longitudinal birth cohort data of 57,286 children in over 300 communities in two large Health and Demographic Surveillance Systems in The Gambia, covering five years preceding and two years during the COVID-19 pandemic. Finally, the fourth objective investigated the demand- and supply-side factors determining timely vaccination in The Gambia, guided by two complementary conceptual frameworks. To achieve this objective, two nationally-representative and temporally aligned datasets were integrated. This PhD, through the most extensive review on the topic to date, spanning four decades and including 224 studies from 103 LMICs, identified significant measurement and methodological gaps in the existing literature on vaccination timeliness. Specifically, there was substantial variation in the definition, dimensions studied, and operationalisation of timeliness. The subsequent objectives of the PhD addressed these gaps through a robust approach. Delayed vaccination was the most common dimension of untimely vaccination in The Gambia, with the highest proportion and the longest median number of days children were vaccinated after the recommended time frames. The spatial modelling of vaccination timeliness, potentially the first globally, revealed significant subnational heterogeneity, with most 'hotspots' of delayed vaccination clustered in the eastern part of The Gambia. The COVID-19 pandemic had no significant negative impact on the timeliness and coverage of routine childhood vaccinations in The Gambia. Demand-side factors were the most common drivers of timely vaccination; however, supply-side factors such as travel time, availability of cold storage, and staffing levels at the nearest immunisation clinic were also significant determinants. Taken together, the PhD research underscores the need for a comprehensive, nuanced and robust approach to measuring vaccination timeliness. The findings have key implications for policy and practice for The Gambian routine immunisation system and similar LMICs context. While optimising overall vaccination coverage rates and reaching zero-dose children remain crucial, focusing solely on these measures may obscure other important aspects of programme performance, particularly the timeliness of vaccination. This is even more important for ‘maturing’ immunisation systems like The Gambia, which, despite achieving relatively high routine vaccination coverage rates, continue to grapple with untimely vaccination and VPDs outbreaks