Using rapid evaluation methods to assess service delivery changes: Lessons learned for evaluation practice during the COVID-19 pandemic

The COVID-19 pandemic required large-scale service delivery changes for government, and provided the opportunity for evaluators to step up and support decision makers to understand the impact of these changes. Rapid evaluation methods (REM) provide a pragmatic approach for generating timely information for evidence-based policy and decision-making. Grounded in developmental and utilisation-focused evaluation theory, REM incorporates a team-based, mixed methods design, executed over a 6–8-week period. Customised rubrics were used to rigorously assess effectiveness and scalability of practice changes to inform COVID-19 response planning. REM is an alternative approach to full-scale evaluation models frequently implemented to assess policies and programs. Adapted use of REM suggests that meaningful insights can be gained through use of smaller scale evaluations. This article shares lessons learned from a novel rapid evaluation method applied in the context of the COVID-19 pandemic. The rapid evaluation approach was implemented to provide real-time insights and evaluative conclusions for 15 program and practice adaptations across Victorian health and human service settings. The article shares insights about the practical applicability of balancing rigour and timeliness when implementing a rapid evaluation, and strengths and limitations of working within a fast-paced evaluation framework. Findings can inform evaluative practice in resource and time-limited settings.

User Generated Content for Site Based Training in Virtual Reality

Objectives/Scope Through a partnership with Global Projects and the ExxonMobil IT, we set out to change the way enabling enhanced site specific operator training and model reviews are done on large complex models. The concept was to have the ability to view and navigate complex green-field 3D CAD models in VR (virtual reality) technology to aid in training, model reviews, procedure development, rounds development, maintenance planning and execution, emergency response planning / drills, and project planning. The automated toolset can be used to conduct model reviews followed by training and preparing operators for commissioning before and after site construction is completed. Methods, Procedures, Process Leveraging the 3D CAD files from Engineering Procurement & Construction (EPC) contractors, the feature set allows the ability to create a fully textured 3D Model walk-through (annotated model review), and a content creation application to easily create user generated training scenarios (similar to PowerPoint drag and drop). In the past few months, 20 onsite stations were setup and over 100 first and second line supervisors and operators leveraged the toolset. Baseline metrics were captured with an overwhelming success. Ongoing metrics collections will continue for several months to drive further adjustments on the toolset to ensure high value capture. This toolset, once fully refined, will allow other capital & global projects the ability to train operators prior to the unit being built and ongoing for operations activities bringing pieces of the Digital Twin concept to life. Results, Observations, Conclusions Technical Benefits Business Benefit Novel/Additive Information

Geo-spatial Assessment of Flood Vulnerability Areas of the Gaza Strip Towards Preparedness and Humanitarian Response Planning

Nowadays, flood and drought will become more common as climate change causes. Due to climate change consequences, flood occurrence and its impact on Gaza people have been of great concern to the Palestinian water authority, as it has a negative influence on various humanitarian and social issues. The hazards and damages resulted by flooding cause loss of life, property, displacement of people and disruption of socioeconomic activities. This research focuses on assessing Gaza Strip vulnerability to flooding using analysis of GIS-based spatial information. Not only did it consider the physical-environmental flood vulnerability, it also investigated social flood vulnerability aspects e.g., population densities. Soil and slope were considered to have the highest weight in the vulnerability mapping, as they represent the main factors in urban hydro-ecosystem structure. The long term average rainfall, a climate function factor, has the lowest weight, because it could be considered as a threat factor in addition to a vulnerability factor. This research demonstrates that urban area and population density as strong factors influencing flood vulnerability for humanitarian and saving life purposes. The findings of Geospatial analysis were used to map vulnerable areas likely to be affected in the event of flood hazard and suggest future interventions and related adaptation strategies in Gaza areas for flood mitigation.

Refining reproduction number estimates to account for unobserved generations of infection in emerging epidemics

Background Estimating the transmissibility of infectious diseases is key to inform situational awareness and for response planning. Several methods tend to overestimate the basic (R_0) and effective (R_t) reproduction numbers during the initial phases of an epidemic. The reasons driving the observed bias are unknown. In this work we explore the impact of incomplete observations and underreporting of the first generations of infections during the initial epidemic phase. Methods We propose a debiasing procedure which utilises a linear exponential growth model to infer unobserved initial generations of infections and apply it to EpiEstim. We assess the performance of our adjustment using simulated data, considering different levels of transmissibility and reporting rates. We also apply the proposed correction to reported SARS-CoV-2 incidence data reported in Italy, Sweden, the United Kingdom and the United States of America. Results In all simulation scenarios, our adjustment outperforms the original EpiEstim method. The proposed correction reduces the systematic bias and the quantification of uncertainty is more precise, as better coverage of the true R_0 values is achieved with tighter credible intervals. When applied to real world data, the proposed adjustment produces basic reproduction number estimates which closely match the estimates obtained in other studies while making use of a minimal amount of data. Conclusions The proposed adjustment refines the reproduction number estimates obtained with the current EpiEstim implementation by producing improved, more precise estimates earlier than with the original method. This has relevant public health implications.

Calculating the serial interval of SARS-CoV-2 in Lebanon using 2020 contact-tracing data

Introduction The first detected case in Lebanon on 21 February 2020 engendered implementation of a nationwide lockdown alongside timely contact-tracing and testing. Objectives Our study aims to calculate the serial interval of SARS-CoV-2 using contact tracing data collected 21 February to 30 June 2020 in Lebanon to guide testing strategies. Methods rRT-PCR positive COVID-19 cases reported to the Ministry of Public Health Epidemiological Surveillance Program (ESU-MOH) are rapidly investigated and identified contacts tested. Positive cases and contacts assigned into chains of transmission during the study time-period were verified to identify those symptomatic, with non-missing date-of-onset and reported source of exposure. Selected cases were classified in infector–infectee pairs. We calculated mean and standard deviation for the serial interval and best distribution fit using AIC criterion. Results Of a total 1788 positive cases reported, we included 103 pairs belonging to 24 chains of transmissions. Most cases were Lebanese (98%) and male (63%). All infectees acquired infection locally. Mean serial interval was 5.24 days, with a standard deviation of 3.96 and a range of − 4 to 16 days. Normal distribution was an acceptable fit for our non-truncated data. Conclusion Timely investigation and social restriction measures limited recall and reporting biases. Pre-symptomatic transmission up to 4 days prior to symptoms onset was documented among close contacts. Our SI estimates, in line with international literature, provided crucial information that fed into national contact tracing measures. Our study, demonstrating the value of contact-tracing data for evidence-based response planning, can help inform national responses in other countries.

Towards Sustainable Community-Based Systems for Infectious Disease and Disaster Response; Lessons from Local Initiatives in Four African Countries

This paper explores the role of decentralised community-based care systems in achieving sustainable healthcare in resource-poor areas. Based on case studies from Sierra Leone, Madagascar, Uganda and Ethiopia, the paper argues that a community-based system of healthcare is more effective in the prevention, early diagnosis, and primary care in response to the zoonotic and infectious diseases associated with extreme weather events as well as their direct health impacts. Community-based systems of care have a more holistic view of the determinants of health and can integrate responses to health challenges, social wellbeing, ecological and economic viability. The case studies profiled in this paper reveal the importance of expanding notions of health to encompass the whole environment (physical and social, across time and space) in which people live, including the explicit recognition of ecological interests and their interconnections with health. While much work still needs to be done in defining and measuring successful community responses to health and other crises, we identify two potentially core criteria: the inclusion and integration of local knowledge in response planning and actions, and the involvement of researchers and practitioners, e.g., community-embedded health workers and NGO staff, as trusted key interlocuters in brokering knowledge and devising sustainable community systems of care.