Lois Park

Malawi and Millennium Development Goal 4: a Countdown to 2015 country case study

BACKGROUND Several years in advance of the 2015 endpoint for the Millennium Development Goals (MDGs), Malawi was already thought to be one of the few countries in sub-Saharan Africa likely to meet the MDG 4 target of reducing under-5 mortality by two-thirds between 1990 and 2015. Countdown to 2015 therefore selected the Malawi National Statistical Office to lead an in-depth country case study, aimed mainly at explaining the countrys success in improving child survival. METHODS We estimated child and neonatal mortality for the years 2000-14 using five district-representative household surveys. The study included recalculation of coverage indicators for that period, and used the Lives Saved Tool (LiST) to attribute the child lives saved in the years from 2000 to 2013 to various interventions. We documented the adoption and implementation of policies and programmes affecting the health of women and children, and developed estimates of financing. FINDINGS The estimated mortality rate in children younger than 5 years declined substantially in the study period, from 247 deaths (90% CI 234-262) per 1000 livebirths in 1990 to 71 deaths (58-83) in 2013, with an annual rate of decline of 5·4%. The most rapid mortality decline occurred in the 1-59 months age group; neonatal mortality declined more slowly (from 50 to 23 deaths per 1000 livebirths), representing an annual rate of decline of 3·3%. Nearly half of the coverage indicators have increased by more than 20 percentage points between 2000 and 2014. Results from the LiST analysis show that about 280,000 childrens lives were saved between 2000 and 2013, attributable to interventions including treatment for diarrhoea, pneumonia, and malaria (23%), insecticide-treated bednets (20%), vaccines (17%), reductions in wasting (11%) and stunting (9%), facility birth care (7%), and prevention and treatment of HIV (7%). The amount of funding allocated to the health sector has increased substantially, particularly to child health and HIV and from external sources, but remains below internationally agreed targets. Key policies to address the major causes of child mortality and deliver high-impact interventions at scale throughout Malawi began in the late 1990s and intensified in the latter half of the 2000s and into the 2010s, backed by health-sector-wide policies to improve womens and childrens health. INTERPRETATION This case study confirmed that Malawi had achieved MDG 4 for child survival by 2013. Our findings suggest that this was achieved mainly through the scale-up of interventions that are effective against the major causes of child deaths (malaria, pneumonia, and diarrhoea), programmes to reduce child undernutrition and mother-to-child transmission of HIV, and some improvements in the quality of care provided around birth. The Government of Malawi was among the first in sub-Saharan Africa to adopt evidence-based policies and implement programmes at scale to prevent unnecessary child deaths. Much remains to be done, building on this success and extending it to higher proportions of the population and targeting continued high neonatal mortality rates. FUNDING Bill & Melinda Gates Foundation, WHO, The World Bank, Government of Australia, Government of Canada, Government of Norway, Government of Sweden, Government of the UK, and UNICEF.

Independent Evaluation of the Integrated Community Case Management of Childhood Illness Strategy in Malawi Using a National Evaluation Platform Design

We evaluated the impact of integrated community case management of childhood illness (iCCM) on careseeking for childhood illness and child mortality in Malawi, using a National Evaluation Platform dose-response design with 27 districts as units of analysis. “Dose” variables included density of iCCM providers, drug availability, and supervision, measured through a cross-sectional cellular telephone survey of all iCCM-trained providers. “Response” variables were changes between 2010 and 2014 in careseeking and mortality in children aged 2–59 months, measured through household surveys. iCCM implementation strength was not associated with changes in careseeking or mortality. There were fewer than one iCCM-ready provider per 1,000 under-five children per district. About 70% of sick children were taken outside the home for care in both 2010 and 2014. Careseeking from iCCM providers increased over time from about 2% to 10%; careseeking from other providers fell by a similar amount. Likely contributors to the failure to find impact include low density of iCCM providers, geographic targeting of iCCM to “hard-to-reach” areas although women did not identify distance from a provider as a barrier to health care, and displacement of facility careseeking by iCCM careseeking. This suggests that targeting iCCM solely based on geographic barriers may need to be reconsidered.

Real-Time Assessments of the Strength of Program Implementation for Community Case Management of Childhood Illness: Validation of a Mobile Phone-Based Method in Malawi

Health surveillance assistants (HSAs) in Malawi have provided community case management (CCM) since 2008; however, program monitoring remains challenging. Mobile technology holds the potential to improve data, but rigorous assessments are few. This study tested the validity of collecting CCM implementation strength indicators through mobile phone interviews with HSAs. This validation study compared mobile phone interviews with information obtained through inspection visits. Sensitivity and specificity were measured to determine validity. Using mobile phones to interview HSAs on CCM implementation strength indicators produces accurate information. For deployment, training, and medicine stocks, the specificity and sensitivity of the results were excellent (> 90%). The sensitivity and specificity of this method for drug stock-outs, supervision, and mentoring were lower but with a few exceptions, still above 80%. This study provided a rigorous assessment of the accuracy of implementation strength data collected through mobile technologies and is an important step forward for evaluation of public health programs.

Achieving maternal and child health gains in Afghanistan: a Countdown to 2015 country case study by Akseer et al., 2016. Lancet Glob Health 2016;4:e395-413

Akseer and her colleagues recently published a seminal paper in the Lancet Global Health that adds to the compelling evidence of progress in reproductive, maternal, newborn and child health (RMNCH) in the past few decades, even in countries such as Afghanistan that are burdened by chronic conflict, rampant poverty and large health inequalities (1).

Reimagining statistical analysis for evidenced-based policy making: Early experiences using Stats Report

To address these challenges in the NEP, we used an online web application called Stats Report. Built on the R statistical package, Stats Report allows complex data analysis to be undertaken more easily and collaboratively. We used Stats Report in data analysis workshops with government staff in Malawi, Mali, Mozambique, and Tanzania. Statistical experts from our team prepared analysis code, and in–country workshop participants ran the analyses themselves, without having to adjust code, manipulate files, or download software. Using Stats Report, participants generated a variety of analytical outputs more quickly and more reliably than had been possible in previous workshops. We report the way in which participants used and responded to Stats Report.

National Assessment of Data Quality and Associated Systems-Level Factors in Malawi

Nearly all facility registers were available and complete. But accuracy varied, with antenatal care and HIV testing and counseling performing the best and family planning and acute respiratory infections data less well. Most facilities visibly displayed routine health data and most hospitals and district health offices had staff trained in health management information systems, but training was lacking at the facility level as were routine data quality checks and regular supervision. Nearly all facility registers were available and complete. But accuracy varied, with antenatal care and HIV testing and counseling performing the best and family planning and acute respiratory infections data less well. Most facilities visibly displayed routine health data and most hospitals and district health offices had staff trained in health management information systems, but training was lacking at the facility level as were routine data quality checks and regular supervision. ABSTRACT Background: Routine health data can guide health systems improvements, but poor quality of these data hinders use. To address concerns about data quality in Malawi, the Ministry of Health and National Statistical Office conducted a data quality assessment (DQA) in July 2016 to identify systems-level factors that could be improved. Methods: We used 2-stage stratified random sampling methods to select health centers and hospitals under Ministry of Health auspices, included those managed by faith-based entities, for this DQA. Dispensaries, village clinics, police and military facilities, tertiary-level hospitals, and private facilities were excluded. We reviewed client registers and monthly reports to verify availability, completeness, and accuracy of data in 4 service areas: antenatal care (ANC), family planning, HIV testing and counseling, and acute respiratory infection (ARI). We also conducted interviews with facility and district personnel to assess health management information system (HMIS) functioning and systems-level factors that may be associated with data quality. We compared systems and quality factors by facility characteristics using 2-sample t tests with Welchs approximation, and calculated verification ratios comparing total entries in registers to totals from summarized reports. Results: We selected 16 hospitals (of 113 total in Malawi), 90 health centers (of 466), and 16 district health offices (of 28) in 16 of Malawis 28 districts. Nearly all registers were available and complete in health centers and district hospitals, but data quality varied across service areas; median verification ratios comparing register and report totals at health centers ranged from 0.78 (interquartile range [IQR]: 0.25, 1.07) for ARI and 0.99 (IQR: 0.82, 1.36) for family planning to 1.00 (IQR: 0.96, 1.00) for HIV testing and counseling and 1.00 (IQR: 0.80, 1.23) for ANC. More than half (60%) of facilities reported receiving a documented supervisory visit for HMIS in the prior 6 months. A recent supervision visit was associated with better availability of data (P=.05), but regular district- or central-level supervision was not. Use of data by the facility to track performance toward targets was associated with both improved availability (P=.04) and completeness of data (P=.02). Half of facilities had a full-time statistical clerk, but their presence did not improve the availability or completeness of data (P=.39 and P=.69, respectively). Conclusion: Findings indicate both strengths and weaknesses in Malawis HMIS performance, with key weaknesses including infrequent data quality checks and unreliable supervision. Efforts to strengthen HMIS in low- and middle-income countries should be informed by similar assessments.

Achieving maternal and child health gains in Afghanistan: a Countdown to 2015 country case study by Akseer et al. , 2016. Lancet Glob Health 2016;4:e395-413

Akseer and her colleagues recently published a seminal paper in the Lancet Global Health that adds to the compelling evidence of progress in reproductive, maternal, newborn and child health (RMNCH) in the past few decades, even in countries such as Afghanistan that are burdened by chronic conflict, rampant poverty and large health inequalities (1). The article highlights how Afghanistan confronted challenges of a fragmented, deteriorating and gender segregated health system established by the fundamentalist Taliban regime during their reign between 1994 and 2001, and continued insecurity and disruptions from frequent insurgencies by investing in effective policies and programs for RMNCH and nutrition. The main strategy adopted was an emergency approach almost exclusively financed by official development assistance which prioritized contracts to large national and international Non-governmental Organizations (NGOs) to support a surge in human resource development immediately after the ousting of the Taliban through training and deployment of community health workers, nurses, midwives and general physicians, and aggressive acceleration in national immunization programs.

Hierarchical statistical models to represent and visualize survey evidence for program evaluation: ICCM in Malawi

Policy and Program evaluation for maternal, newborn and child health is becoming increasingly complex due to changing contexts. Monitoring and evaluation efforts in this area can take advantage of large nationally representative household surveys such as DHS or MICS that are increasing in size and frequency, however, this analysis presents challenges on several fronts. We propose an approach with hierarchical models for cross-sectional survey data to describe evidence relating to program evaluation, and apply this approach to the recent scale up of iCCM in Malawi. We describe careseeking for children sick with diarrhea, pneumonia, or malaria with empirical Bayes estimates for each district of Malawi at two time points, both for careseeking from any source, and for careseeking only from health surveillance assistants (HSA). We do not find evidence that children in areas with more HSA trained in iCCM are more likely to seek care for pneumonia, diarrhea, or malaria, despite evidence that many indeed are seeking care from HSA. Children in areas with more HSA trained in iCCM are more likely to seek care from a HSA, with 100 additional trained health workers in a district corresponding to a 2% average increase in careseeking from HSA. The hierarchical models presented here provide a flexible set of methods that describe the primary evidence for evaluating iCCM in Malawi and which could be extended to formal causal analyses, and to analysis for other similar evaluations with national survey data.