Routine health management information system data in Ethiopia: consistency, trends, and challenges.

Background: Ethiopia is investing in the routine Health Management Information System. Improved routine data are needed for decision-making in the health sector. Objective: To analyse the quality of the routine Health Management Information System data and triangulate with other sources, such as the Demographic and Health Surveys. Methods: We analysed national Health Management Information System data on 19 indicators of maternal health, neonatal survival, immunization, child nutrition, malaria, and tuberculosis over the 2012-2018 time period. The analyses were conducted by 38 analysts from the Ministry of Health, Ethiopia, and two government agencies who participated in the Operational Research and Coaching for Analysts (ORCA) project between June 2018 and June 2020. Using a World Health Organization Data Quality Review toolkit, we assessed indicator definitions, completeness, internal consistency over time and between related indicators, and external consistency compared with other data sources. Results: Several services reported coverage of above 100%. For many indicators, denominators were based on poor-quality population data estimates. Data on individual vaccinations had relatively good internal consistency. In contrast, there was low external consistency for data on fully vaccinated children, with the routine Health Management Information System showing 89% coverage but the Demographic and Health Survey estimate at 39%. Maternal health indicators displayed increasing coverage over time. Indicators on child nutrition, malaria, and tuberculosis were less consistent. Data on neonatal mortality were incomplete and operationalised as mortality on day 0-6. Our comparisons with survey and population projections indicated that one in eight early neonatal deaths were reported in the routine Health Management Information System. Data quality varied between regions. Conclusions: The quality of routine data gathered in the health system needs further attention. We suggest regular triangulation with data from other sources. We recommend addressing the denominator issues, reducing the complexity of indicators, and aligning indicators to international definitions

Simulating Canadian Arctic Climate at Convection-Permitting Resolution

Inadequate representation and parameterization of sub-grid scale features and processes are one of the main sources for uncertainties in regional climate change projections, particularly for the Arctic regions where the climate change signal is amplified. Increasing model resolution to a couple of kilometers will be helpful in resolving some of these challenges, for example to better simulate convection and refined land heterogeneity and thus land–atmosphere interactions. A set of multi-year simulations has been carried out for the Canadian Arctic domain at 12 km and 3 km resolutions using limited-area version of the global environmental multi-scale (GEM) model. The model is integrated for five years driven by the fifth generation of the European Centre for medium-range weather forecast reanalysis (ERA-5) at the lateral boundaries. The aim of this study is to investigate the role of horizontal model resolution on the simulated surface climate variables. Results indicate that although some aspects of the seasonal mean values are deteriorated at times, substantial improvements are noted in the higher resolution simulation. The representation of extreme precipitation events during summer and the simulation of winter temperature are better captured in the convection-permitting simulation. Moreover, the observed temperature–extreme precipitation scaling is realistically reproduced by the higher resolution simulation. These results advocate for the use of convective-permitting resolution models for simulating future climate projections over the Arctic to support climate impact assessment studies such as those related to engineering applications and where high spatial and temporal resolution are beneficial

Did ERA5 Improve Temperature and Precipitation Reanalysis over East Africa?

Reanalysis products are often taken as an alternative solution to observational weather and climate data due to availability and accessibility problems, particularly in data-sparse regions such as Africa. Proper evaluation of their strengths and weaknesses, however, should not be overlooked. The aim of this study was to evaluate the performance of ERA5 reanalysis and to document the progress made compared to ERA-interim for the fields of near-surface temperature and precipitation over Africa. Results show that in ERA5 the climatological biases in temperature and precipitation are clearly reduced and the representation of inter-annual variability is improved over most of Africa. However, both reanalysis products performed less well in terms of capturing the observed long-term trends, despite a slightly better performance of ERA5 over ERA-interim. Further regional analysis over East Africa shows that the representation of the annual cycle of precipitation is substantially improved in ERA5 by reducing the wet bias during the rainy season. The spatial distribution of precipitation during extreme years is also better represented in ERA5. While ERA5 has improved much in comparison to its predecessor, there is still demand for improved products with even higher resolution and accuracy to satisfy impact-based studies, such as in agriculture and water resources. © 2020 by the authors

Did ERA5 Improve Temperature and Precipitation Reanalysis over East Africa?

Reanalysis products are often taken as an alternative solution to observational weather and climate data due to availability and accessibility problems, particularly in data-sparse regions such as Africa. Proper evaluation of their strengths and weaknesses, however, should not be overlooked. The aim of this study was to evaluate the performance of ERA5 reanalysis and to document the progress made compared to ERA-interim for the fields of near-surface temperature and precipitation over Africa. Results show that in ERA5 the climatological biases in temperature and precipitation are clearly reduced and the representation of inter-annual variability is improved over most of Africa. However, both reanalysis products performed less well in terms of capturing the observed long-term trends, despite a slightly better performance of ERA5 over ERA-interim. Further regional analysis over East Africa shows that the representation of the annual cycle of precipitation is substantially improved in ERA5 by reducing the wet bias during the rainy season. The spatial distribution of precipitation during extreme years is also better represented in ERA5. While ERA5 has improved much in comparison to its predecessor, there is still demand for improved products with even higher resolution and accuracy to satisfy impact-based studies, such as in agriculture and water resources

Training on Installation, Configuration and Usage of WRF-Hydro model

Understanding the mechanisms leading to heavy precipitation events and accurate modelling of the surface hydrology is crucial for producing a reliable flood early warning system. In this workshop we used uncoupled WRF-Hydro model, an open-source community model, for the flash flood prediction. The model can also be used for a range of projects, including regional hydro-climate impacts assessment, seasonal forecasting of water resources, and land-atmosphere coupling studies. The underlying goal of WRF-Hydro development is to improve prediction skill of hydro-meteorological forecasts using science based numerical prediction tools. In addition to the hydrological modelling, understanding the atmospheric process is equally important to get a better insight regarding flood events. Large scale atmospheric and surface fields associated with selected extreme precipitation events are analysed in this workshop using ERA5 reanalysis, to understand the processes leading to such heavy precipitation events

Current Conditions and Projected Changes in Crop Water Demand, Irrigation Requirement, and Water Availability over West Africa

Climate variability and change greatly affect agricultural and water resource management over West Africa. This paper presents the current characteristics and projected change in regional crop water demand (CWD), irrigation requirement (IR), and water availability (WA) over West Africa. Observed and simulated daily rainfall, minimum temperature, maximum temperature, and evapotranspiration are used to derive the above agro-meteorological and hydrological variables. For future periods, high-resolution climate data from three regional climate models under two different scenarios, i.e., representative concentration pathway (RCP) 4.5 and 8.5, are considered. Evaluation of the characteristics of present-day CWD, IR, and WA indicated that the ensemble mean of the model-derived outputs reproduced the prevailing spatial patterns of CWD and IR. Moreover, the wetter part of the domain, especially along the southern coast, was correctly delineated from the drier northern regions, despite having biases. The ensemble model also simulated the annual cycle of water supply and the bimodal pattern of the water demand curves correctly. In terms of future projections, the outcomes from the study suggest an average increase in the CWD by up to 0.808 mm/day and IR by 1.244 mm/day towards the end of the twenty-first century, compared to the baseline period. The hot-spot areas, where there is higher projected increment in CWD and IR, are over Senegal, Southern Mali, and Western Burkina Faso. In most cases, WA is projected to decrease towards the end of the twenty-first century by −0.418 mm/day. The largest decline in WA is found to be over Guinea and most of the eastern parts of West Africa. Despite the current under-utilization of the existing groundwater resources, the threat of global warming in reducing future WA and increasing CWD suggested caution on the scale of irrigation schemes and management strategies. The outcomes from the study could be a crucial input for the agricultural and water managers for introducing effective measures to ensure sustainability of irrigated farm lands

Exploring data quality and use of the routine health information system in Ethiopia: a mixed-methods study.

OBJECTIVE: A routine health information system (RHIS) enables decision making in the healthcare system. We aimed to analyse data quality at the district and regional level and explore factors and perceptions affecting the quality and use of routine data. DESIGN: This was a mixed-methods study. We used the WHO toolkit for analysing data quality and interviewed staff at the point of data generation and along with the flow of data. Data were analysed using the Performance of Routine Information System Management framework. SETTING: This study was performed in eight districts in four regions of Ethiopia. The study was nested within a 2-year programme of the Operational Research and Coaching for government Analysts. PARTICIPANTS: We visited 45 health posts, 1 district hospital, 16 health centres and 8 district offices for analysis of routine RHIS data and interviewed 117 staff members for the qualitative assessment. OUTCOME MEASURES: We assessed availability of source documents, completeness, timeliness and accuracy of reporting of routine data, and explored data quality and use perceptions. RESULTS: There was variable quality of both indicator and data element. Data on maternal health and immunisation were of higher quality than data on child nutrition. Issues ranged from simple organisational factors, such as availability of register books, to intricate technical issues, like complexity of indicators and choice of denominators based on population estimates. Respondents showed knowledge of the reporting procedures, but also demonstrated limited skills, lack of supportive supervision and reporting to please the next level. We saw limited examples of the use of data by the staff who were responsible for data reporting. CONCLUSION: We identified important organisational, technical, behavioural and process factors that need further attention to improve the quality and use of RHIS data in Ethiopia