A series of Médecins Sans Frontières projects for irregular migrants over the past decade have consistently documented high rates of 14 physical and sexual trauma, extortion and mental illness amidst severe healthcare, food, and housing limitations. Complex interventions were needed to begin to address illness and barriers to healthcare and to help restore dignity to the most vulnerable women, children and men. Promising interventions included mobile clinics, use of cultural mediators, coordination with migrant-friendly entities and NGOs and integrating advocacy programs and mental health care with medical services. Ongoing interventions, research and coordination are needed to address this neglected humanitarian crisis.
Between August-December 2014, Ebola Virus Disease (EVD) patients from Tonkolili District were referred for care to two Médecins Sans Frontières (MSF) Ebola Management Centres (EMCs) outside the district (distant EMCs). In December 2014, MSF opened an EMC in Tonkolili District (district EMC). We examined the effect of opening a district-based EMC on time to admission and number of suspect cases dead on arrival (DOA), and identified factors associated with fatality in EVD patients, residents in Tonkolili District. Residents of Tonkolili district who presented between 12 September 2014 and 23 February 2015 to the district EMC and the two distant EMCs were identified from EMC line-lists. EVD cases were confirmed by a positive Ebola PCR test. We calculated time to admission since the onset of symptoms, case-fatality and adjusted Risk Ratios (aRR) using Binomial regression. Of 249 confirmed Ebola cases, 206 (83%) were admitted to the distant EMCs and 43 (17%) to the district EMC. Of them 110 (45%) have died. Confirmed cases dead on arrival (n = 10) were observed only in the distant EMCs. The median time from symptom onset to admission was 6 days (IQR 4,8) in distant EMCs and 3 days (IQR 2,7) in the district EMC (p<0.001). Cases were 2.0 (95%CI 1.4–2.9) times more likely to have delayed admission (>3 days after symptom onset) in the distant compared with the district EMC, but were less likely (aRR = 0.8; 95%CI 0.6–1.0) to have a high viral load (cycle threshold ≤22). A fatal outcome was associated with a high viral load (aRR 2.6; 95%CI 1.8–3.6) and vomiting at first presentation (aRR 1.4; 95%CI 1.0–2.0). The opening of a district EMC was associated with earlier admission of cases to appropriate care facilities, an essential component of reducing EVD transmission. High viral load and vomiting at admission predicted fatality. Healthcare providers should consider the location of EMCs to ensure equitable access during Ebola outbreaks.
BackgroundDuring the 2014–16 Ebola virus disease (EVD) outbreak, the Magburaka Ebola Management Centre (EMC) operated by Médecins Sans Frontières (MSF) in Tonkolili District, Sierra Leone, identified that available district maps lacked up-to-date village information to facilitate timely implementation of EVD control strategies. In January 2015, we undertook a survey in chiefdoms within the MSF EMC catchment area to collect mapping and village data. We explore the feasibility and cost to mobilise a local community for this survey, describe validation against existing mapping sources and use of the data to prioritise areas for interventions, and lessons learned.MethodsWe recruited local people with self-owned Android smartphones installed with open-source survey software (OpenDataKit (ODK)) and open-source navigation software (OpenStreetMap Automated Navigation Directions (OsmAnd)). Surveyors were paired with local motorbike drivers to travel to eligible villages. The collected mapping data were validated by checking for duplication and comparing the village names against a pre-existing village name and location list using a geographic distance and text string-matching algorithm.ResultsThe survey teams gained sufficient familiarity with the ODK and OsmAnd software within 1–2 hours. Nine chiefdoms in Tonkolili District and three in Bombali District were surveyed within two weeks. Following de-duplication, the surveyors collected data from 891 villages with an estimated 127,021 households. The overall survey cost was €3,395; €3.80 per village surveyed. The MSF GIS team (MSF-OCG) created improved maps for the MSF Magburaka EMC team which were used to support surveillance, investigation of suspect EVD cases, hygiene-kit distribution and EVD survivor support. We shared the mapping data with OpenStreetMap, the local Ministry of Health and Sanitation and Sierra Leone District and National Ebola Response Centres.ConclusionsInvolving local community and using accessible technology allowed rapid implementation, at moderate cost, of a survey to collect geographic and essential village information, and creation of updated maps. These methods could be used for future emergencies to facilitate response.
Schumann and Bates (2018), hereafter referred to as SB, argue that there is a need for a global scale, high-accuracy, open-access Digital Elevation Model (DEM). They find current global DEM data unacceptable in accuracy and resolution. They position their argument mainly around hydraulic applications, by referring to required accuracies to estimate hydraulic energy slopes, and the need for highly detailed topography in urban zones, where most flood impacts are felt. A vertical accuracy of 0.5 meter is suggested to be adequate for local scale applications. This DEM, according to SB, can be established through a collaborative effort of industry, governments and humanitarian agencies by merging and quality assuring DEMs from different existing sources such as Light-Detection and Ranging missions, photogrammetry or satellite stereo. They close their plea by stating that the anticipated DEM will "help communities build resilience to anticipated climate impacts."We support the statement that a DEM with the envisioned accuracy is useful. In fact, it is a general prerequisite to simulating flood behavior at large scales, as indicated by SB. In addition, terrain and elevation data at this level of detail may find its application in other fields such as morphology (e.g., Tarolli and Sofia, 2016), cadastral digitization (e.g., Dorninger and Pfeifer, 2008) and landslide predictions (e.g., Ciampalini et al., 2016). However, at the level of detail suggested (urban zones), an accurate DEM alone is not enough if the objective of flood modeling goes beyond awareness raising or flood zoning. In this commentary, we argue that: (a) the "consortium effort" proposed by SB should focus on regions that will profit most: developing countries; (b) technically, at the local scale where the suggested accuracy (0.5 m) with the suggested spatial resolution (∼5 m) becomes useful, other properties of the environment besides terrain become dominant in flood behavior and, consequently, in flood risk. These include the water infrastructure (bridges, channels, culverts, etc.) and its maintenance state. Such infrastructure information is key in establishing what makes a street, neighborhood or city more flood resilient, hence supporting communities in their decision-making for a sustainable future; and (c) that a bottom-up data collection approach for infrastructure and maintenance states will lead to less inequality in global data coverage
By November 2015, the West Africa Ebola epidemic had caused 28598 infections and 11299 deaths in the three countries most affected. The outbreak required rapid innovation and adaptation. Médecins sans Frontières (MSF) scaled up its usual 20-30 bed Ebola management centres (EMCs) to 100-300 beds with over 300 workers in some settings. This brought challenges in patient and clinical data management resulting from the difficulties of working safely with high numbers of Ebola patients. We describe a project MSF established with software developers and the Google Social Impact Team to develop context-adapted tools to address the challenges of recording Ebola clinical information. We share the outcomes and key lessons learned in innovating rapidly under pressure in difficult environmental conditions. Information on adoption, maintenance, and data quality was gathered through review of project documentation, discussions with field staff and key project stakeholders, and analysis of tablet data. In March 2015, a full prototype was deployed in Magburaka EMC, Sierra Leone. Inpatient data were captured on 204 clinical interactions with 34 patients from 5 March until 10 April 2015. Data continued to also be recorded on paper charts, creating theoretically identical record “pairs” on paper and tablet. 83 record pairs for 33 patients with 22 data items (temperature and symptoms) per pair were analysed. The overall Kappa coefficient for agreement between sources was 0.62, but reduced to 0.59 when rare bleeding symptoms were excluded, indicating moderate to good agreement. The time taken to deliver the product was more than that anticipated by MSF (7 months versus 6 weeks). Deployment of the tablet coincided with a dramatic drop in patient numbers and thus had little impact on patient care. We have identified lessons specific to humanitarian-technology collaborative projects and propose a framework for emergency humanitarian innovation. Time and effort is required to bridge differences in organisational culture between the technology and humanitarian worlds. This investment is essential for establishing a shared vision on deliverables, urgency, and ownership of product.
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