Thesis (M Med (Paediatrics and Child Health)-- University of Limpopo, 2011. / ABSTRACT BACKGROUND AND OBJECTIVE: Immunization is one of the most cost effective preventative health care interventions that is available to communities; it has greatly reduced the burden of infectious diseases in childhood. Since the W orId Health Organization launched the expanded programme of immunization in 1974, routine childhood immunization is widely available and it forms an integral part of preventative healthcare. Unfortunately, many children lack access to this life saving health care intervention. Communities in poor, rural areas often lack access to basic services, including health care and immunization services. We studied immunization coverage in a poor, rural community in South Africa and further explored what factors put children in this community at risk for under-immunization. METHOD: This was a cross sectional study, in which the immunization status of children from birth to six years of age living in Mmakaunyane was assessed. The primary caregivers of these children were also interviewed to determine their knowledge, attitudes and their practices with regards to immunizations; they were further asked about their perception of healthcare service delivery in the village. Using a map of the village, it was divided it into 30 blocks with 4 clusters in each block. Field workers were looking for a maximum of 5 eligible children in each cluster. We used the Road to Health Card to check if immunization was complete for age according to the SA EPI. RESUL TS: There were 567 children enrolled in the study. The majority of the children were above 18 months of age (64.4%) We found that 92.1 % of children were in possession of a RHC. In total, 432 (76.2%) of the children were fully immunized for their age, 97 (17.1%) had incomplete immunizations and immunization status was unknown for 38 (6.7%). The primary caregiver for most of the children was the biological mother (85.5%). There was a low level of education amongst the primary caregivers with only 15.3% having completed matric or attained higher level of education. Caregiver knowledge of immunization was poor and only 21.1 % of caregivers correctly mentioned three diseases that can be prevented by immunization. The majority of the caregivers (96.0%) believed that immunizations help to keep children healthy. Approximately half (49.9%), of the caregivers perceived immunization service delivery in Mmakaunyane village to be good. Factors that were found to be associated with incomplete immunization included age of caregiver, gender of the child and knowledge of the caregiver on immunization. CONCLUSION: Only 76.2% of children were fully immunized for their age in Mmakaunyane village. This immunization coverage rate is less than the National target of 90% for all children aged one year. The proportion of children under one year of age that are fully immunized is higher than that of the whole group. This indicates that the older children have a lesser level of immunization coverage (>18 months: 74.2%). The major factors that were found to be associated with under-immunization include lack of knowledge about immunizations, older age of the caregiver as well as poor accessibility of health care services. Female children were also found to be at increased risk for under-immunization. Measures to improve immunization coverage in this community need to take all these factors into consideration

BACKGROUND: The under-5 mortality rate in Ethiopia is 118/1000. A child in Ethiopia is 30 times more likely to die before age 5 than a child in Western Europe. Children are the most vulnerable segment of the population, but many of the ailments that cause death in this population can be avoided by completion of routine childhood vaccination. METHODS: Data regarding child health from the Demographic and Health Survey (DHS), a periodic cross-sectional survey administered at the household level was utilized in this study. Data from 8,905 mothers of living children between 0-5 years of age was included in the study. Univariate and multivariate analyses of selected socio-demographic variables were conducted to examine association with vaccination status. RESULTS: Risk factors for vaccination defaulting were identified. Logistic modeling with the selected factors was conducted with vaccination status and the demographic characteristics of families as independent factors. Type of Residence, Region and Wealth Index were the only significant characteristic in predicting the likelihood of a child being vaccinated when controlled for other factors. CONCLUSION: The results of this study illustrate that geographic disparities result in lower vaccination completion for lower income families from rural settings than other groups. Families’ behavior around child vaccination is a microcosm of various social determinants affecting their decision-making. Resources further removed from health such as better roads and education can improve vaccination uptake.

In his classic book, Experiencing Architecture, Rasmussen (1959) noted that architects inspired by addressing problems in built environments created buildings with a special spirit: a distinctive stamp. Recent problems in healthcare facilities, specifically those related to reducing stress and anxiety, have inspired designers to create positive, uplifting distractions to redirect a patient's attention from a sterile environment and/or noxious event. In doing so, healthcare facilities have become special environments with a caring spirit. This study examined a specific aspect of creating a caring environment: determining whether or not a positive distraction, a child's art-light mosaic movie developed by the researcher, would lower pain and distress in children 4, 5, and 6 years old during an immunization procedure. The researcher conducted a randomized controlled study in two locations using a child's self-report pain scale, heart rate, parent/guardian report, and nurse report measures. After collecting and analyzing data from 76 well-participants receiving one to five immunizations, the researcher found no statistically significant difference between the conditions for any of the measures. Thus, the null hypothesis, the art-light mosaic image would not assist in lowering pain and distress in pediatric patients, 4 to 6 years old, during an immunization procedure, was not rejected. From these results, the researcher recommended future studies incorporate training the parent and child on how to use the distraction, combine the distraction with a topical analgesic, provide a clear understanding of pain and distress from the child's point of view, and develop more sensitive self-report measures of pain for children. / Ph. D.

This research presents a mathematical model for the transportation and distribution of COVID-19 vaccine, a simulation model for fleet optimization, and a measurement model for "Healthcare 4.0." Essay 1 examines the development of a distribution model using mixed integer programming (MIP) with the objective of maximizing the number of vaccinated individuals, minimizing transportation costs across the entire network, and ensuring widespread access. This research primarily focuses on the distribution aspect of the vaccine and accordingly devises a model for transportation and distribution that ensures swift and efficient delivery of the COVID-19 vaccine. Essay 2 provides a simulation-based model to enhance logistics performance by including drones along with vaccine trucks and air cargo in the vaccine distribution fleet. The simulation model focuses on minimization of the overall cost of distribution of medical supplies. This second study shows that the types of vehicles utilized have an impact on overall system performance. The selection of the appropriate mix for the mode of transportation impacts transportation costs and lead time. To increase the responsiveness and cost-effectiveness of the logistics system for delivery of the vaccine a proper fleet configuration is required. The model developed in this study is validated via application in Telangana, India as well as through confirmation about the applicability of the model with healthcare executives. Essay 3 introduces a measurement model and constructs for Healthcare 4.0, specifically tailored for implementation by healthcare service providers. While the concept of Healthcare 4.0 and its various components have been explored in the literature, the existing body of research primarily consists of conceptual and theoretical studies, indicating that Healthcare 4.0 is still a relatively nascent research domain. In order to facilitate practical and theoretical advancements in this field, it is imperative to refine the constructs and establish a consensus on perspectives and definitions. To address this need, the items pertaining to Healthcare 4.0 for healthcare service organizations were developed through an extensive literature review and interviews conducted with practitioners in the field. The resulting theoretical model was further validated by surveying experienced professionals from the healthcare industry, utilizing Mturk as a platform.

La vaccination est une des meilleures procédures de prévention coût-efficaces. Des couvertures vaccinales non adéquates présentent des problèmes de Santé publique considérables. Réduire ou éliminer les occasions manquées de vaccination (OMV) dans les régions les plus vulnérables permettrait d’y augmenter la couverture vaccinale. L’Inde a un des plus grands programmes de vaccination dans le monde, cependant il y existe d’importants gradients de couvertures vaccinales d’une région à l’autre. Objectifs : Cette étude visait à estimer la prévalence des OMV chez des jeunes enfants en zone rurale de Hardoi en Inde et identifier les potentiels déterminants et facteurs prédictifs des OMV. Méthodes : Les données secondaires d’une étude pré-post ont été utilisées pour mener une étude transversale. Les OMV ont été définies selon la définition de l’Organisation mondiale de la santé. Deux sources d’information sur le statut vaccinal ont été considérées : mémoire des mère ou carnet de vaccination (M/C) pour les analyses principales; et carnet de vaccination seulement (CS) en analyse de sensibilité. La prévalence des OMV dans la première année de vie (OMV-1AV) chez les enfants de 12 à moins de 24 mois et celle des OMV pendant la période optimale de vaccination (OMV-PO) chez les 0 à moins de 24 mois ont été calculées par sexe et bloc administratif. Les potentiels déterminants des OMV ont été identifiés à l’aide de modèles hiérarchiques. Des modèles prédictifs ont été construits pour identifier les facteurs qui permettraient de mieux cibler les enfants plus à risque d’OMV: leur pouvoir prédictif a été évalué avec la statistique c. Résultats : La prévalence des OMV-1AV selon la source M/C est de 19,3% ; celle selon CS est de 76,0%. La prévalence des OMV-PO selon M/C est de 14,6% alors qu’elle est de 65,7% selon CS. Pour les OMV-1AV et les OMV-PO, la prévalence variait d’un vaccin à l’autre mais seulement selon CS. Les déterminants des OMV varient selon la source d’information sur le statut vaccinal. Les principaux potentiels déterminants selon M/C sont: problèmes logistiques (OMV-1AV Rapport de cotes (RC) = 3,38; OMV-PO RC = 2,59); malaise ressenti chez l’enfant (OMV-1AV RC = 0,37; OMV-PO RC = 0,52); refus des vaccinateurs de vacciner sans avoir le carnet de vaccination (OMV-1AV RC = 5,66; OMV-1AV RC = 5,23); effets secondaires (OMV RC = 8,24; OMV-PO RC = 5,62); et le fait qu’un membre de la famille s’oppose à la vaccination de l’enfant; (OMV-1AV RC = 4,03; OMV-PO RC = 4,61). Des modèles prédictifs efficaces ont été construits et présentaient des statistiques c variant entre 0,72 et 0,79. Certains facteurs permettaient d’améliorer le pouvoir prédictif des modèles sans être nécessairement des potentiels déterminant des OMV tel que le temps de déplacement à pied entre le ménage et le centre de vaccination. Retombées : Les résultats suggèrent que la situation des OMV est complexe que ce soit du point de vue de la source d’information sur le statut vaccinal, de l’identification de leurs potentiels déterminants ou sur la capacité à cibler les individus les plus à risque. Les divergences au niveau des estimations de la prévalence selon la source d’information soulignent l’importance d’assurer un meilleur contrôle de la validité des sources d’information afin de maximiser l’exactitude des informations fournies. / Introduction: Missed opportunities for vaccination (MOV) affect vaccination coverages and contribute to create considerable vaccination gradient between and within regions. In India, despite major vaccination accomplishments, important vaccination gradients persist. MOV have been reported but the situation is not well known in many parts of the country. Aim: Quantify MOV in children in rural Hardoi district and identify potential determinants and predictive factors. Methods: We defined MOV using the definition of the World Health Organization. Our outcomes were missed opportunities for vaccination in first year of life (MOV-FYL) and missed opportunities for on-time vaccination (MO-OTV). We used a cross-sectional design. Vaccination status was verified according to two sources: by mothers’ recalls OR children vaccination card for the main analysis; and by vaccination card only for sensitivity analysis. We calculated the prevalence of both outcomes in a clustered population of 0 to under 24month-old children recruited in a census-like manner from rural area in Hardoi, India. We used multilevel binary logistic regression to identify potential determinants of MOV and multivariable logistic regression to built prediction models. Results: The prevalence was 19.30% and 14.39% for MOV-FYL and MO-OTV respectively. There were little variations across child sex and vaccines. However, among vaccination cardholders, the prevalence was 75.99% and 65.73% for MOV-FYL and MO-OTV respectively and varied across vaccines. Marked potential determinants using the main source of information about vaccination status were: logistics problems (MOV-FYL Odds Ratio (OR) = 3.38; MO-OTV OR = 2.59); child feeling unwell (MOV-FYL OR = 0.37; MO-OTV OR = 0.52); the refusal of health provider to vaccinate without the vaccination card (MOV-FYL OR = 5.66; MO-OTV OR = 5.23); side effects (MOV-FYL OR = 8.24; MO-OTV OR = 5.62); and family member not allowing vaccination (MOV-FYL OR = 4.03; MO-OTV OR = 4.61). Predictive models for MOV-FYL and MO-OTV yielded c statistics around 0.72 and 0.79 respectively and had the best sensitivity/specificity balance when used in a population with 15%-20% probability of MOV. Conclusion: Our study revealed that quantifying the prevalence of MOV is rather complexed. The source of information about vaccination status is key to obtain the best estimates, hence the knowledge on the reliability of the information from the card or obtained from recalls is a must. Many potential modifiable determinants should be explored and there is potential for predictability: interventions should be developed to reduce risks of MOV in targeted individuals, increase vaccination coverage and reduce vaccination gradients.