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Objective: To estimate the level and trend of development assistance for community health worker-related projects in low- and middle-income countries between 2007 and 2017., Methods: We extracted data from the Organisation for Economic Co-operation and Development's creditor reporting system on aid funding for projects to support community health workers (CHWs) in 114 countries over 2007-2017. We produced estimates for projects specifically described by relevant keywords and for projects which could include components on CHWs. We analysed the pattern of development assistance by purpose, donors, recipient regions and countries, and trends over time., Findings: Between 2007 and 2017, total development assistance targeting CHW projects was around United States dollars (US$) 5 298.02 million, accounting for 2.5% of the US$ 209 277.99 million total development assistance for health. The top three donors (Global Fund to Fight AIDS, Tuberculosis and Malaria, the government of Canada and the government of the United States of America) provided a total of US$ 4 350.08 million (82.1%) of development assistance for these projects. Sub-Saharan Africa received a total US$ 3 717.93 million, the largest per capita assistance over 11 years (US$ 0.39; total population: 9 426.25 million). Development assistance to projects that focused on infectious diseases and child and maternal health received most funds during the study period., Conclusion: The share of development assistance invested in the CHW projects was small, unstable and decreasing in recent years. More research is needed on tracking government investments in CHW-related projects and assessing the impact of investments on programme effectiveness., ((c) 2020 The authors; licensee World Health Organization.)

Background: A 2007 study published in The Lancet estimated that approximately 219 million children aged younger than 5 years were exposed to stunting or extreme poverty in 2004. We updated the 2004 estimates with the use of improved data and methods and generated estimates for 2010., Methods: We used country-level prevalence of stunting in children younger than 5 years based on the 2006 Growth Standards proposed by WHO and poverty ratios from the World Bank to estimate children who were either stunted or lived in extreme poverty for 141 low-income and middle-income countries in 2004 and 2010. To avoid counting the same children twice, we excluded children jointly exposed to stunting and extreme poverty from children living in extreme poverty. To examine the robustness of estimates, we also used moderate poverty measures., Findings: The 2007 study underestimated children at risk of poor development. The estimated number of children exposed to the two risk factors in low-income and middle-income countries decreased from 279·1 million (95% CI 250·4 million-307·4 million) in 2004 to 249·4 million (209·3 million-292·6 million) in 2010; prevalence of children at risk fell from 51% (95% CI 46-56) to 43% (36-51). The decline occurred in all income groups and regions with south Asia experiencing the largest drop. Sub-Saharan Africa had the highest prevalence in both years. These findings were robust to variations in poverty measures., Interpretation: Progress has been made in reducing the number of children exposed to stunting or poverty between 2004 and 2010, but this is still not enough. Scaling up of effective interventions targeting the most vulnerable children is urgently needed., Funding: National Institutes of Health, Bill & Melinda Gates Foundation, Hilton Foundation, and WHO., (Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND license. Published by Elsevier Ltd.. All rights reserved.)

Background: The Global Fund to Fight AIDS, Tuberculosis and Malaria was launched in 2002 to attract and rapidly disburse money to fight these diseases. However, some commentators believe that poor countries cannot effectively use such resources to increase delivery of their health programmes-referred to as a lack of absorptive capacity. We aimed to investigate the major determinants of grant implementation in developing countries., Methods: With information available publicly on the Global Fund's website, we did random-effects analysis to investigate the effect of grant characteristics, types of primary recipient and local fund agent, and country attributes on disbursements that were made between 2003 and 2005 (phase one of Global Fund payments). To check the robustness of findings, regression results from alternative estimation methods and model specifications were also tested., Findings: Grant characteristics--such as size of commitment, lag time between signature and first disbursement, and funding round-had significant effects on grant implementation. Enhanced political stability was associated with high use of grants. Low-income countries, and those with less-developed health systems for a given level of income, were more likely to have a higher rate of grant implementation than nations with higher incomes or more-developed health systems., Interpretation: The higher rate of grant implementation seen in countries with low income and low health-spending lends support to proponents of major increases in health assistance for the poorest countries and argues that focusing resources on low-income nations, particularly those with political stability, will not create difficulties of absorptive capacity. Our analysis was restricted to grant implementation, which is one part of the issue of absorptive capacity. In the future, assessment of the effect of Global Fund grants on intervention coverage will be vital.

Background: The majority of Countdown countries did not reach the fourth Millennium Development Goal (MDG 4) on reducing child mortality, despite the fact that donor funding to the health sector has drastically increased. When tracking aid invested in child survival, previous studies have exclusively focused on aid targeting reproductive, maternal, newborn, and child health (RMNCH). We take a multi-sectoral approach and extend the estimation to the four sectors that determine child survival: health (RMNCH and non-RMNCH), education, water and sanitation, and food and humanitarian assistance (Food/HA). Methods and findings: Using donor reported data, obtained mainly from the OECD Creditor Reporting System and Development Assistance Committee, we tracked the level and trends of aid (in grants or loans) disbursed to each of the four sectors at the global, regional, and country levels. We performed detailed analyses on missing data and conducted imputation with various methods. To identify aid projects for RMNCH, we developed an identification strategy that combined keyword searches and manual coding. To quantify aid for RMNCH in projects with multiple purposes, we adopted an integrated approach and produced the lower and upper bounds of estimates for RMNCH, so as to avoid making assumptions or using weak evidence for allocation. We checked the sensitivity of trends to the estimation methods and compared our estimates to that produced by other studies. Our study yielded time-series and recipient-specific annual estimates of aid disbursed to each sector, as well as their lower- and upper-bounds in 134 countries between 2000 and 2014, with a specific focus on Countdown countries. We found that the upper-bound estimates of total aid disbursed to the four sectors in 134 countries rose from US$ 22.62 billion in 2000 to US$ 59.29 billion in 2014, with the increase occurring in all income groups and regions with sub-Saharan Africa receiving the largest sum. Aid to RMNCH has experienced the fastest growth (12.4%), followed by aid to Food/HA (9.4%), education (5.1%), and water and sanitation (5.0%). With the exception of RMNCH, the average per capita aid disbursed to each sector in the 74 Countdown countries was smaller than in non-Countdown countries. While countries with a large number of child deaths tend to receive the largest amount of disbursements, non-Countdown countries with small populations usually received the highest level of per capita aid for child survival among all 134 countries. Compared to other Countdown countries, those that met MDG 4 with a high reliance on health aid received much higher per capita aid across all sectors. These findings are robust to estimation methods. Conclusions: The study suggests that to improve child survival, better targeted investments should be made in the four sectors, and aid to non-health sectors could be a possible contributor to child mortality reduction. We recommend that future studies on tracking aid for child survival go beyond the health sector and include other sectors that directly affect child survival. Investigation should also be made about the link between aid to each of the four sectors and child mortality reduction. [ABSTRACT FROM AUTHOR]

: Chunling Lu and colleagues describe a project for tracking health center financial data in two rural districts of Rwanda, which could be adapted for other low- or middle-income countries. Please see later in the article for the Editors' Summary [ABSTRACT FROM AUTHOR]

Background: In 2011, World Health Organization revised its recommendation for microbiological monitoring during treatment for multidrug-resistant tuberculosis (MDR-TB) by increasing the frequency of culture examination from quarterly to monthly after culture conversion. Implementing the recommendation requires substantial additional investment in laboratory infrastructure. The objective of this review is to provide cost evidence that is needed for national TB programs to budget for optimal monitoring strategies. Methods and Findings: We conducted the first systematic literature review on unit cost estimates of three monitoring strategies: 1) smear only; 2) culture only; 3) combined smear and culture. 26 peer-reviewed studies were selected by searching 10 databases in English and Chinese for literature published between 1995 and 2012. Cost estimates were converted into 2010 constant USD and international dollars. We assessed the quality of the estimates using a matrix with five essential elements and provided a cost projection for the combined smear and culture tests where the data were available. The 26 studies reported the cost estimates in 16 predominantly high- or middle-income countries from 1993 to 2009. The estimated unit cost for smear, culture, and combined tests ranges from $0.26 to $10.50, $1.63 to $62.01, and $26.73 to $39.57, respectively. The ratio of culture to smear costs varies from 1.35 to 11.98. The wide range of estimates is likely attributable to using different laboratory methods in different regions and years and differing practices in collecting and reporting cost data. Most studies did not report information critical for generalizing their conclusions. Conclusion: The paucity and low quality of unit cost estimates for TB monitoring in resource-poor settings impose technical challenges in predicting the resources needed for strengthening microbiological monitoring. To improve the validity and comparability of the cost data, we strongly advocate the data collection, estimation, and reporting follow protocols proposed by WHO. [ABSTRACT FROM AUTHOR]

Background: Mutuelles is a community-based health insurance program, established since 1999 by the Government of Rwanda as a key component of the national health strategy on providing universal health care. The objective of the study was to evaluate the impact of Mutuelles on achieving universal coverage of medical services and financial risk protection in its first eight years of implementation. Methods and Findings: We conducted a quantitative impact evaluation of Mutuelles between 2000 and 2008 using nationally-representative surveys. At the national and provincial levels, we traced the evolution of Mutuelles coverage and its impact on child and maternal care coverage from 2000 to 2008, as well as household catastrophic health payments from 2000 to 2006. At the individual level, we investigated the impact of Mutuelles' coverage on enrollees' medical care utilization using logistic regression. We focused on three target populations: the general population, under-five children, and women with delivery. At the household level, we used logistic regression to study the relationship between Mutuelles coverage and the probability of incurring catastrophic health spending. The main limitation was that due to insufficient data, we are not able to study the impact of Mutuelles on health outcomes, such as child and maternal mortalities, directly. The findings show that Mutuelles improved medical care utilization and protected households from catastrophic health spending. Among Mutuelles enrollees, those in the poorest expenditure quintile had a significantly lower rate of utilization and higher rate of catastrophic health spending. The findings are robust to various estimation methods and datasets. Conclusions: Rwanda's experience suggests that community-based health insurance schemes can be effective tools for achieving universal health coverage even in the poorest settings. We suggest a future study on how eliminating Mutuelles copayments for the poorest will improve their healthcare utilization, lower their catastrophic health spending, and affect the finances of health care providers.