Why predict climate hazards if we need to understand impacts? Putting humans back into the drought equation

Virtually all climate monitoring and forecasting efforts concentrate on hazards rather than on impacts, while the latter are a priority for planning emergency activities and for the evaluation of mitigation strategies. Effective disaster risk management strategies need to consider the prevailing "human terrain" to predict who is at risk and how communities will be affected. There has been little effort to align the spatiotemporal granularity of socioeconomic assessments with the granularity of weather or climate monitoring. The lack of a high-resolution socioeconomic baseline leaves methodical approaches like machine learning virtually untapped for pattern recognition of extreme climate impacts on livelihood conditions. While the request for "better" socioeconomic data is not new, we highlight the need to collect and analyze environmental and socioeconomic data together and discuss novel strategies for coordinated data collection via mobile technologies from a drought risk management perspective. A better temporal, spatial, and contextual understanding of socioeconomic impacts of extreme climate conditions will help to establish complex causal pathways and quantitative proof about climate-attributable livelihood impacts. Such considerations are particularly important in the context of the latest big data-driven initiatives, such as the World Bank's Famine Action Mechanism (FAM).

Hospital resilience after the 2015 earthquake in Nepal: a qualitative study with hospital staff

Background

Research on hospital resilience is scarce and favours top-down approaches, and evidence from the field and operational levels is lacking. The aim of our study was to understand the mechanisms of hospital and individual resilience experienced by staff from a tertiary hospital in Kathmandu, Nepal, after the 2015 Earthquake.

Methods

We conducted semi-structured interviews with different professionals in May 2018; undertook a deductive thematic analysis of hospital resilience using the framework proposed by Bruneau et al; and used an inductive thematic analysis for individual resilience.

Results

The earthquake caused different types of burden to the hospital and individuals. Redundancy was mostly influenced by linkages with lower levels of care. Resourcefulness consisted mostly of spontaneous adaptations, with task shifting the most important for human resources. External provision of resources enabled the transfer of part of the burden but precipitated accountability-related challenges. The hospital's robustness depended not only on its physical resistance, but also on the functional capacity to provide life saving care, although routine services were interrupted and quality decreased. The hospital ensured rapidity in providing life saving care to the victims and re-start of routine activities, but recovery to a sense of normality was more conflicting and dependent on the individual. Individual resilience was dictated by safety, a sense of meaningfulness, self and external appreciation, and community support.

Conclusions

Our study shows the importance of staff experiences to improve hospital resilience. Disaster plans should acknowledge the role of task shifting, and basic care should be taught to all, not just those with clinical functions. Health workers are extremely overwhelmed during disaster response, and disaster plans should engage staff at an early stage to ensure they feel safe and sufficiently supported.

Key messages

Our work is one of the first to study hospital resilience with field data from qualitative interviews with hospital staff. Hospital resilience strategies should also address individual resilience of hospital staff.

Does the presence of conflict affect maternal and neonatal mortality during Caesarean sections?

Introduction

Conflicts frequently occur in countries with high maternal and neonatal mortality and can aggravate difficulties accessing emergency care. No literature is available on whether the presence of conflict influences the outcomes of mothers and neonates during Caesarean sections (C-sections) in high-mortality settings.

Objective

To determine whether the presence of conflict was associated with changes in maternal and neonatal mortality during C-sections.

Methods

We analysed routinely collected data on C-sections from 17 Médecins Sans Frontières (MSF) health facilities in 12 countries. Exposure variables included presence and intensity of conflict, type of health facility and other types of access to emergency care.

Results

During 2008-2015, 30,921 C-sections were performed in MSF facilities; of which 55.4% were in areas of conflict. No differences were observed in maternal mortality in conflict settings (0.1%) vs. non-conflict settings (0.1%) (P = 0.08), nor in neonatal mortality between conflict (12.2%) and non-conflict settings (11.5%) (P = 0.1). Among the C-sections carried out in conflict settings, neonatal mortality was slightly higher in war zones compared to areas of minor conflict (P = 0.02); there was no difference in maternal mortality (P = 0.38).

Conclusions

Maternal and neonatal mortality did not appear to be affected by the presence of conflict in a large number of MSF facilities. This finding should encourage humanitarian organisations to support C-sections in conflict settings to ensure access to quality maternity care.

Information systems and needs assessment in natural disasters: An approach for better disaster relief management

The paper addresses the issue of information in disasters relief. It begins by establishing the need for planning and systematic organization in disaster action, in order to produce a long term effect on the vulnerability levels of communities. Information is introduced as a key element in any phase of disaster management. The different informational needs are described by phases; information types and possible sources are briefly described. The organizational network of information collection is presented and the immediate need for research in this field is emphasized.