Person:

Ozonoff, Alexander

Child mortality measurement is essential to the impact evaluation of maternal and child healthcare systems interventions. In the absence of vital statistics systems, however, assessment methodologies for locally relevant interventions are severely challenged. Methods for assessing the under-5 mortality rate for cross-country comparisons, often used in determining progress towards development targets, pose challenges to implementers and researchers trying to assess the population impact of targeted interventions at more local levels. Here, we discuss the programmatic approach we have taken to mortality measurement in the context of delivering healthcare via a public–private partnership in rural Nepal. Both government officials and the delivery organisation, Possible, felt it was important to understand child mortality at a fine-grain spatial and temporal level. We discuss both the short-term and the long-term approach. In the short term, the team chose to use the under-2 mortality rate as a metric for mortality measurement for the following reasons: (1) as overall childhood mortality declines, like it has in rural Nepal, deaths concentrate among children under the age of 2; (2) 2-year cohorts are shorter and thus may show an impact more readily in the short term of intervention trials; and (3) 2-year cohorts are smaller, making prospective census cohorts more feasible in small populations. In the long term, Possible developed a digital continuous surveillance system to capture deaths as they occur, at which point under-5 mortality assessment would be desirable, largely owing to its role as a global standard.

Background: Surveillance systems are increasingly relying upon community-based or crowd-sourced data to complement traditional facilities-based data sources. Data collected by community health workers during the routine course of care could combine the early warning power of community-based data collection with the predictability and diagnostic regularity of facility data. These data could inform public health responses to epidemics and spatially-clustered endemic diseases. Here, we analyze data collected on a daily basis by community health workers during the routine course of clinical care in rural Nepal. We evaluate if such community-based surveillance systems can capture temporal trends in diarrheal diseases and acute respiratory infections. Methods: During the course of their clinical activities from January to December 2013, community health workers recorded healthcare encounters using mobile phones. In parallel, we accessed condition-specific admissions from 2011–2013 in the hospital from which the community health program was based. We compared diarrhea and acute respiratory infection rates from both the hospital and the community, and assigned three categories of local disease activity (low, medium, and high) to each week in each village cluster with categories determined by tertiles. We compared condition-specific mean hospital rates across categories using ANOVA to assess concordance between hospital and community-collected data. Results: There were 2,710 cases of diarrhea and 373 cases of acute respiratory infection reported by community health workers during the one-year study period. At the hospital, the average weekly incidence of diarrhea and acute respiratory infections over the three-year period was 1.8 and 3.9 cases respectively per 1,000 people in each village cluster. In the community, the average weekly rate of diarrhea and acute respiratory infections was 2.7 and 0.5 cases respectively per 1,000 people. Both diarrhea and acute respiratory infections exhibited significant differences between the three categories of disease rate burden (diarrhea p = 0.009, acute respiratory infection p = 0.001) when comparing community health worker-collected rates to hospital rates. Conclusion: Community-level data on diarrhea and acute respiratory infections modestly correlated with hospital data for the same condition in each village each week. Our experience suggests that community health worker-collected data on mobile phones may be a feasible adjunct to other community- and healthcare-related data sources for surveillance of such conditions. Such systems are vitally needed in resource-limited settings like rural Nepal.