How people-centred health systems can reach the grassroots: experiences implementing community-level quality improvement in rural Tanzania and Uganda

Background Quality improvement (QI) methods engage stakeholders in identifying problems, creating strategies called change ideas to address those problems, testing those change ideas and scaling them up where successful. These methods have rarely been used at the community level in low-income country settings. Here we share experiences from rural Tanzania and Uganda, where QI was applied as part of the Expanded Quality Management Using Information Power (EQUIP) intervention with the aim of improving maternal and newborn health. Village volunteers were taught how to generate change ideas to improve health-seeking behaviours and home-based maternal and newborn care practices. Interaction was encouraged between communities and health staff. Aim To describe experiences implementing EQUIP’s QI approach at the community level. Methods A mixed methods process evaluation of community-level QI was conducted in Tanzania and a feasibility study in Uganda. We outlined how village volunteers were trained in and applied QI techniques and examined the interaction between village volunteers and health facilities, and in Tanzania, the interaction with the wider community also. Results Village volunteers had the capacity to learn and apply QI techniques to address local maternal and neonatal health problems. Data collection and presentation was a persistent challenge for village volunteers, overcome through intensive continuous mentoring and coaching. Village volunteers complemented health facility staff, particularly to reinforce behaviour change on health facility delivery and birth preparedness. There was some evidence of changing social norms around maternal and newborn health, which EQUIP helped to reinforce. Conclusions Community-level QI is a participatory research approach that engaged volunteers in Tanzania and Uganda, putting them in a central position within local health systems to increase health-seeking behaviours and improve preventative maternal and newborn health practices

Impact of the assimilation of ozone from the Tropospheric Emission Spectrometer on surface ozone across North America

We examine the impact of assimilating ozone observations from the Tropospheric Emission Spectrometer (TES) on North American surface ozone abundances in the GEOS-Chem model in August 2006. The assimilation reduces the negative bias in the modeled free tropospheric ozone, which enhances the ozone flux into the boundary layer. Surface ozone abundances increased by as much as 9 ppb in western North America and by less than 2 ppb in the southeast, resulting in a total background source of ozone of 20-40 ppb. The enhanced ozone in the model reduced the model bias with respect to surface ozone observations in the western USA, but exacerbated it in the east. This increase in the bias in the boundary layer in the east, despite the agreement between the assimilation and ozonesonde measurements in the free troposphere, suggests errors in the ozone sources or sinks or in boundary layer mixing in the model. © 2009

Comparison of improved Aura Tropospheric Emission Spectrometer CO₂ with HIPPO and SGP aircraft profile measurements

Thermal infrared radiances from the Tropospheric Emission Spectrometer (TES) between 10 and 15 μm contain significant carbon dioxide (CO2) information, however the CO2 signal must be separated from radiative interference from temperature, surface and cloud parameters, water, and other trace gases. Validation requires data sources spanning the range of TES CO2 sensitivity, which is approximately 2.5 to 12 km with peak sensitivity at about 5 km and the range of TES observations in latitude (40° S to 40° N) and time (2005–2011). We therefore characterize Tropospheric Emission Spectrometer (TES) CO2 version 5 biases and errors through comparisons to ocean and land-based aircraft profiles and to the CarbonTracker assimilation system. We compare to ocean profiles from the first three Hiaper Pole-to-Pole Observations (HIPPO) campaigns between 40° S and 40° N with measurements between the surface and 14 km and find that TES CO2 estimates capture the seasonal and latitudinal gradients observed by HIPPO CO2 measurements. Actual errors range from 0.8–1.8 ppm, depending on the campaign and pressure level, and are approximately 1.6–2 times larger than the predicted errors. The bias of TES versus HIPPO is within 1 ppm for all pressures and datasets; however, several of the sub-tropical TES CO2 estimates are lower than expected based on the calculated errors. Comparisons to land aircraft profiles from the United States Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) between 2005 and 2011 measured from the surface to 5 km to TES CO2 show good agreement with an overall bias of −0.3 ppm to 0.1 ppm and standard deviations of 0.8 to 1.0 ppm at different pressure levels. Extending the SGP aircraft profiles above 5 km using AIRS or CONTRAIL measurements improves comparisons with TES. Comparisons to CarbonTracker (version CT2011) show a persistent spatially dependent bias pattern and comparisons to SGP show a time-dependent bias of −0.2 ppm yr−1. We also find that the predicted sensitivity of the TES CO2 estimates is too high, which results from using a multi-step retrieval for CO2 and temperature. We find that the averaging kernel in the TES product corrected by a pressure-dependent factor accurately reflects the sensitivity of the TES CO2 product