Obtaining district-level health estimates using geographically masked location from Demographic and Health Survey data.

BACKGROUND: Demographic and Health Survey (DHS) data are an important source of maternal, newborn, and child health as well as nutrition information for low- and middle-income countries. However, DHSs are often unavailable at the administrative unit that is most interesting or useful for program planning. In addition, the location of DHS survey clusters are geomasked within 10 km, and prior to 2009, may have crossed district boundaries. We aim to use DHS surveyed information with these geomasked coordinates to estimate district assignments for use in health program planning and evaluation. METHODS: We developed three methods to assign a district to a geomasked survey cluster in two DHS surveys from Malawi: 2000 and 2004. Method A assigns districts of origin in proportion to the likelihood that results from repeated simulated geomasking, allowing more than one possible district of origin. Method B assigns a single district of origin which contains the greatest proportion of simulated geomasked survey clusters. Method C maps the geomasked survey cluster's location to a district polygon. We used these method assignments to estimate a selection of commonly used coverage indicators for each district. We compared the district coverage estimates, confidence intervals, and concordance correlation coefficients, by each of the methods, to those which used validated district assignments in 2004, and we looked at coverage change from 2000 to 2004. RESULTS: The methods we tested each approximated the validated estimates in 2004 by confidence interval comparison and concordance correlation coefficient. Estimated agreement for method A was between .14 and .98, for method B the estimated agreement was between .97 and .99, and for method C the agreement ranged from .93 to .99 when compared with the validated district assignments. Therefore, we recommend the protocol which is the simplest to implement-method C-overlaying geomasked survey cluster within district polygon. CONCLUSIONS: Using geomasked survey clusters from DHSs to assign districts provided district level coverage rates similar to those using the validated surveyed locations. This method may be applied to data sources where survey cluster centroids are available and where district level estimates are needed for program implementation and evaluation in low- and middle-income settings. This method is of special interest to those using DHSs to study spatiotemporal trends as it allows for the utilization of historic DHS data where geomasking hinders the generation of reliable subnational estimates of health in areas smaller than the first-order administrative unit (ADM1).

Youth accessing reproductive health services in Malawi: drivers, barriers, and suggestions from the perspectives of youth and parents.

BACKGROUND: Malawi has made progress in increasing its overall modern contraceptive prevalence rate since 2000, resulting in a dramatic reduction in its total fertility rate. However, youth, 15-24 years, have not had the same successes. Teenage pregnancies are on the rise and little progress has been made in reducing unmet need for family planning among youth. With two-thirds of the population under the age of 25 and with Malawi's rapid population growth, reducing unmet need for family planning among youth remains a priority for the government's reproductive health agenda. To further explore this situation, we conducted a qualitative study to explore the perspectives of youth and adults about the drivers and barriers to youth accessing family planning in Malawi and their ideas to improve services. METHODS: We conducted 34 focus group discussions with youth aged 15-24 and parents or legal guardians of female youth in 3 districts in Malawi. Focus groups were translated and transcribed. Data was input into Dedoose and analyzed using a thematic framework to identify broader patterns and themes. RESULTS: Youth participants felt motivated to use family planning to protect themselves from sexually transmitted diseases and to prevent unwanted pregnancies. Females focused on the consequences of unplanned pregnancies and believed family planning services were targeted primarily at them, while males thought family planning services targeted males and females equally. Barriers to youth accessing family planning included contraception misconceptions, the costs of family planning services, and negative attitudes. Parents had mixed views on family planning. While many parents acknowledged they could play a role in supporting youth, most said they are reluctant to support youth using family planning. Participants said improving counseling services, integrating family planning services and education within school curricula, and utilizing youth clubs could improve family planning services for youth. CONCLUSIONS: Policy makers and program implementers should consider the diverse preferences among youth and parents and continue seeking their input when designing policies and programs. Youth clubs and school-based services were among the most common suggestions. However, the effectiveness of youth clubs and school-based initiatives to increase contraceptive use among youth in Malawi is not clear.

Measuring and monitoring child health and wellbeing: recommendations for tracking progress with a core set of indicators in the Sustainable Development Goals era.

Although great improvements in child survival were achieved in the past two decades, progress has been uneven within and across countries, and the COVID-19 pandemic threatens to reverse previous advances. Demographic and epidemiological transitions around the world have resulted in shifts in the causes and distribution of child death and diseases, and many children are living with short-term and long-term chronic illnesses and disabilities. These changes, plus global threats such as pandemics, transnational and national security issues, and climate change, mean that regular monitoring of child health and wellbeing is essential if we are to achieve the Sustainable Development Goals. This Health Policy describes the three-phased process undertaken by the Child Health Accountability Tracking technical advisory group (CHAT) to develop a core set of indicators on child health and wellbeing for global monitoring purposes, and presents CHAT's research recommendations to address data gaps. CHAT reached consensus on 20 core indicators specific to the health sector, which include 11 impact-level indicators and nine outcome-level indicators that cover the topics of: acute conditions and prevention; health promotion and child development; and chronic conditions, disabilities, injuries, and violence against children. An additional six indicators (three impact and three outcome) that capture information on child health issues such as malaria and HIV are recommended; however, these indicators are only relevant to high-burden regions. CHAT's four research priorities will require investments in health information systems and measurement activities. These investments will help to increase data on children aged 5-9 years; develop standard metadata and data collection processes to enable cross-country comparisons and progress assessments over time; reach a global consensus on essential interventions and associated indicators for monitoring emerging priority areas such as child development, chronic conditions, disabilities, and injuries; and implement strategies to increase the uptake of data on child health to improve evidence-based planning, programming, and advocacy efforts.

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

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 Welch's 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 Malawi's 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 Malawi's 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.

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.

Strengthening Community-Based Vital Events Reporting for Real-Time Monitoring of Under-Five Mortality: Lessons Learned from the Balaka and Salima Districts in Malawi.

BACKGROUND: Malawi ratified a compulsory birth and death registration system in 2009. Until it captures complete coverage of vital events, Malawi relies on other data sources to calculate mortality estimates. We tested a community-based method to estimate annual under-five mortality rates (U5MR) through the Real-Time Monitoring of Under-Five Mortality (RMM) project in Malawi. We implemented RMM in two phases, and conducted an independent evaluation of phase one after 21 months of implementation. We present results of the phase two validation that covers the full project time span, and compare the results to those of the phase one validation. METHODS AND FINDINGS: We assessed the completeness of the counts of births and deaths and the accuracy of disaggregated U5MR from the community-based method against a retrospective full pregnancy history for rolling twelve-month periods after the independent evaluation. We used full pregnancy histories collected through household interviews carried out between November 2013 and January 2014 as the validation data source. Health Surveillance Agents (HSAs) across the 160 catchment areas submitted routine reports on pregnancies, births, and deaths consistently. However, for the 15-month implementation period post-evaluation, average completeness of birth event reporting was 76%, whereas average completeness of death event reporting was 67% relative to that expected from a comparable pregnancy history. HSAs underestimated the U5MR by an average of 21% relative to that estimated from a comparable pregnancy history. CONCLUSIONS: On a medium scale, the community-based RMM method in Malawi produced substantial underestimates of annualized U5MR relative to those obtained from a full pregnancy history, despite the additional incentives and quality-control activities. We were not able to achieve an optimum level of incentive and support to make the system work while ensuring sustainability. Lessons learned from the implementation of RMM can inform programs supporting community-based interventions through HSAs in Malawi.

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.

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 country's 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 children's 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 women's and children's 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.

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.