Adverse events following immunization reporting and impact on immunization services in informal settlements in Nairobi, Kenya: a prospective mixed-methods study

Introduction: adverse events following immunization (AEFIs) are thought to contribute to cases of vaccine hesitancy, yet little data exists describing the state of reporting and management of AEFIs. This study investigated the occurrence and influence of AEFIs on vaccine hesitancy in an informal settlement of Nairobi. Methods: this was a prospective mixed-methods study involving 7 focus group discussions, 8 key informant interviews and 457 face-to-face interviews with caregivers. Caregivers were recruited at/or before the 6-week clinic visit and assessed for occurrence of AEFIs in their children at the subsequent 10- and 14-week visits and a follow-up two weeks following the 14 weeks visit via phone calls. Results: in this study, 12.3% (56/457) of the infants experienced an AEFI. Of these, 19 did not report for the next scheduled vaccine. Fever was the most common AEFI, for which most caregivers (66.7%) used paracetamol as antipyretic, while 20.8% sought help from a nearby health facility. Three of the 56 AEFIs (convulsions) that occurred in study participants could be classified as severe reactions. Diphtheria, pertussis and tetanus (DPT) 3 completion rate was 75.3%. Most (96.4%) caregivers considered immunization an important strategy for child survival. Vaccine hesitancy occurred among 3.6% of participants, 30% of whom attributed their hesitancy to occurrence of AEFIs. The review of health records revealed that no AEFI had been reported from any of the study facilities. Conclusion: cases of adverse events following immunization are not reported in Mathare Valley and they do have implications for vaccine hesitancy by some caregivers

Improving productivity and worker conditions in assembly : part 2 : rapid deployment of learnable robot skills

Collaborative robots (cobots) have a strong potential to improve both productivity as well as the working conditions of assembly operators by assisting in their tasks and by decreasing their physical and cognitive stress. The use of cobots in factories however introduces multiple challenges: how should the overall assembly architecture look like? How to allocate specific (sub)tasks to the operator or the cobot? How to program and deploy the cobot? How to make changes to the robot program? In this paper dilogy, we briefly highlight our recent contributions to this field. In part I we presented our collaborative architecture for human-robot assembly tasks and discussed the working principles of our task allocation framework, based upon agent capabilities and ergonomic measurements. In this second part we focus on our programming by demonstration approach targeted at expediting the deployment of learnable robot skills

Peste des petits ruminants in large ruminants, camels and unusual hosts

Since its first report in 1942, peste-des-petits-ruminants virus (PPRV) has caused several epidemics in a wide range of susceptible hosts around the world. In the last 30 years, the evidence of natural and experimental infections and virus isolation were reported from novel but unusual hosts such as camel, cattle, buffalo, dogs, Asiatic lion and pigs. In addition, PPRV in a potential vector, biting midges (Culicoides imicola), has been reported. Either presented as clinical and/or subclinical infections, the presence of the virus in an extended range of susceptible hosts highlights the cross-species transmission and supports the hypothesis of an endemic circulation of PPRV among susceptible hosts. However, the potential role of large ruminants, camels and unusual hosts for PPRV epidemiology is still obscure. Therefore, there is a need for molecular and epidemiological investigations of the disease among usual and unusual hosts to achieve the goals of disease control and eradication programmes initiated by national and international organisations, such as the FAO and OIE. This review is the first to summarise the scattered data on PPR in large ruminants, camels and unusual hosts to obtain the global scientific communities' attention for further research on epidemiological aspects, not only in its native hosts, but also in large ruminants, camels and other unusual hosts

A framework to estimate the cost of No-Fault Found events

The article investigates a generic framework to estimate maintenance costs attributed to the No Fault Found (NFF) phenomenon. Such overhead costs are particularly difficult to quantify due to potentially serviceable equipment being returned for repair. Other factors, such as a reduction in the availability of the system, compromising reliability of high value assets, and logistical factors, can all contribute to the cost of resolving an unknown fault. Here we apply the soft systems methodology to capture the critical cost drivers of NFF across the supply chain and build a framework to estimate the cost of NFF. We use a multi-method design including an online survey, workshops and semi-structured interviews to study NFF related cost practices based on information from 12 key participants across 7 UK organisations. The study identifies the major NFF cost drivers across the supply chain (e.g. transportation), the OEM (e.g. inventory) and the customer (e.g. lost man hours). An agent based model is used to evaluate the impact of these cost drivers on the overall NFF cost. The analysis shows how the most appropriate drivers can be selected to represent the cumulative costs due to NFF events and their impacts across the supply network. From the academic perspective, the generic framework for NFF cost estimation demonstrates how qualitative and quantitative information can be used together to achieve maintenance objectives. From a practical perspective, by applying the framework on one component, an organisation has the liberty to analyse the cost of NFF for that particular unit only

Logistics service provider selection for disaster preparation: a socio-technical systems perspective

Since 1990s, the world has seen a lot of advances in providing humanitarian aid through sophisticated logistics operations. The current consensus seems to be that humanitarian relief organizations (HROs) can improve their relief operations by collaborating with logistics service providers (CLSPs) in the commercial sector. The question remains: how can HROs select the most appropriate CLSP for disaster preparation? Despite its practical significance, no explicit effort has been done to identify the criteria/factors in prioritising and selecting a CLSP for disaster relief. The present study aims to address this gap by consolidating the list of criteria from a socio-technical systems (STS) perspective. Then, to handle the interdependence among the criteria derived from the STS, we develop a hybrid multi-criteria decision making model for CLSP selection in the disaster preparedness stage. The proposed model is then evaluated by a real-life case study, providing insights into the decision-makers in both HROs and CLSPs